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Faecalibacterium prausnitzii is one of your gut's best friends: it makes butyrate that feeds your colon and calms inflammation. When it disappears, that is usually a sign of disease, not a cause you would want to remove.
Faecalibacterium prausnitzii is one of the most abundant beneficial bacteria in the healthy gut and a major butyrate producer. It is anti-inflammatory and depleted in conditions such as Crohn's disease, so on this database its signal is usually one of protective loss, and the lever to support it is dietary fiber.
Microbiome-targeted interventions (MBTIs) are validated using a dual-evidence logical framework. First, the intervention must realign the condition’s microbiome signature by increasing beneficial taxa that are consistently depleted and reducing pathogenic taxa that are consistently enriched. Second, the intervention must demonstrate measurable clinical benefit. Concordance of these effects in the same context validates the intervention as an MBTI and supports the clinical relevance of the microbiome signature.
Karen Pendergrass is a microbiome researcher specializing in microbiome-targeted interventions (MBTIs). She systematically analyzes scientific literature to identify microbial patterns, develop hypotheses, and validate interventions. As the founder of the Microbiome Signatures Database, she bridges microbiome research with clinical practice. In 2012, based on her own investigative research, she became the first documented case of FMT for Celiac Disease, four years before the first published case study.
Read MoreFaecalibacterium prausnitzii is one of the most abundant and important beneficial bacteria in the healthy human gut. A member of the phylum Firmicutes, it is a major producer of butyrate, the short-chain fatty acid that fuels colon cells and calms inflammation, and it is recognized as an anti-inflammatory commensal.[1][2] On this database it appears as a differentially abundant taxon across many human microbiome studies, and unlike a pathogen its story is usually one of loss: it is depleted in a wide range of diseases.
What makes F. prausnitzii distinctive is that its decline is itself a signal of disease. A reduced abundance was one of the first reproducible microbiome findings in Crohn's disease, where lower F. prausnitzii predicted postoperative relapse, and both the bacterium and its secreted molecules dampen inflammation in cell and animal models.[1] This makes it less a target to attack than a keystone to protect, and the lever that supports it is what it eats: dietary fiber.[2]
F. prausnitzii is a non-spore-forming, non-motile rod in the phylum Firmicutes (class Clostridia) and one of the most abundant bacteria in the healthy colon.[2] It is an extremely oxygen-sensitive strict anaerobe, which makes it difficult to culture and vulnerable to conditions that raise oxygen at the gut wall, such as inflammation.[1][2]
F. prausnitzii is a specialist fiber fermenter and one of the gut's main butyrate producers. Butyrate is the preferred energy source for colonocytes and reinforces the epithelial barrier, and its production is a central reason this organism is considered health-promoting.[2] Because it depends on dietary fiber reaching the colon, its abundance tracks a fiber-rich diet.[2]
F. prausnitzii is the archetypal anti-inflammatory commensal. Its abundance is reduced in Crohn's disease, and a lower proportion on resected ileal mucosa predicted endoscopic recurrence within six months.[1] Both live bacteria and their cell-free supernatant reduce inflammation: they block NF-kB activation and IL-8 production, lower IL-12 and interferon-gamma, raise anti-inflammatory IL-10, and reduce the severity of chemically induced colitis in mice.[1] These properties make it a leading candidate next-generation probiotic.[1][2]
Where a pathogen page lists virulence factors, F. prausnitzii's notable molecules are the ones that help the host.
| Beneficial factor | Description and role |
|---|---|
| Butyrate | Its main short-chain fatty acid product fuels colonocytes, strengthens the gut barrier, and has anti-inflammatory effects.[2] |
| Secreted anti-inflammatory metabolites | The cell-free supernatant alone blocks NF-kB activation and IL-8 production, indicating secreted molecules with anti-inflammatory activity independent of the live cell.[1] |
| Immune modulation toward IL-10 | It shifts the cytokine balance toward anti-inflammatory IL-10 and away from IL-12 and interferon-gamma, and reduces experimental colitis.[1] |
For a protective microbe, the relevant "vulnerabilities" are what threaten it, because losing it is a step toward dysbiosis.
| Threat | Why it matters |
|---|---|
| Oxygen and inflammation | As a strict anaerobe, F. prausnitzii is harmed by the raised oxygen at an inflamed gut wall, so inflammation and its decline can reinforce each other in a vicious cycle.[1][2] |
| Low-fiber diet | Because it feeds on fiber-derived substrates, a fiber-poor Western diet starves it and lowers butyrate.[2] |
| Antibiotics and dysbiosis | Broad disruption of the microbiota reduces F. prausnitzii along with other beneficial anaerobes, a hallmark of dysbiosis.[2] |
For a beneficial keystone, an intervention is anything that supports or restores it. Everything below is research-stage and is not medical advice; each is classified by our validation method. The through-line is simple: feed it fiber and protect it from inflammation.
| Intervention | Class | Status |
|---|---|---|
| Dietary fiber / prebiotics | Diet | Validation In Progress |
| F. prausnitzii as a next-generation probiotic | Concept | Validation In Progress |
| Reduce gut inflammation and oxygen | Concept | Validation In Progress |
| Intervention | Mechanism |
| Dietary fiber / prebiotics | Provides the fermentable substrate this specialist fiber-degrader needs, raising its abundance and butyrate output.[2] |
| F. prausnitzii or its supernatant | Live cells and secreted molecules both blunt inflammation and reduce colitis in models, the basis for its use as a next-generation probiotic.[1] |
| Reduce inflammation and oxygen | Lowering mucosal inflammation restores the anaerobic niche this oxygen-sensitive organism needs.[1] |
A chronically fiber-poor diet and unnecessary broad-spectrum antibiotics, both of which deplete F. prausnitzii and the butyrate it provides.[2]
Where F. prausnitzii (NCBI:txid853) appears as a differentially abundant taxon across the Microbiome Medicine corpus. Each row aggregates every experiment in which the organism moved in a given condition; direction is its change in the case/exposure group, and grade is the strongest single study's methodology weight (A·D·S·C·R), the same engine that grades every signature on this site.
Across 109 conditions and 173 studies, it is enriched in 28, depleted in 56, and direction-conflicting in 25. Consistent with its role as a protective, anti-inflammatory commensal, the signal leans toward depletion: it is lost more often than it is gained across disease states. Because loss of a beneficial microbe is itself a marker of dysbiosis rather than a specific disease mechanism, the aggregate evidence tier is Low.
How to read these. F. prausnitzii is a genuine, abundant, health-associated resident, so a depletion here usually marks a less healthy or inflamed gut rather than a cause of the condition. As a strict anaerobe it can be under-detected in stool by some methods. Read a decline as a signal of dysbiosis and a candidate to restore, not a target to remove. This is why the aggregate tier stays Low.
Internal summaries of the 172 studies we reviewed in which F. prausnitzii was a differential taxon across this corpus.
This study characterized the gut microbiome in the context of HTLV-1 infection and its clinical stages, including the neuroinflammatory disease HAM/TSP. Researchers analyzed fecal bacterial composition and diversity using Illumina MiSeq sequencing, drawing an analogy to the established gut-brain axis role seen in other neurological diseases like multiple sclerosis. Functional analysis was also performed to identify differentially enriched gene categories and KEGG metabolic modules. The overall aim was to determine whether gut microbiome alterations track with HTLV-1 infection and disease progression to HAM/TSP.
The study included 112 Brazilian individuals in a cross-sectional design. This comprised 24 healthy controls and 88 HTLV-1-infected individuals, the latter group spanning different disease stages: 38 patients with HAM, 17 with intermediate syndromes, and 33 asymptomatic carriers. Fecal samples were collected from each participant for sequencing and functional analysis.
HTLV-1-infected individuals showed significant gut dysbiosis compared to healthy controls, marked by reduced bacterial diversity and an inverted Firmicutes/Bacteroidetes ratio. Specific bacterial genera changed across disease stages, and functional KEGG modules were differentially enriched between groups. Notably, patients with HAM (the most advanced, symptomatic stage) exhibited decreased Faecalibacterium, a genus recognized for its anti-inflammatory, butyrate-producing commensal members, alongside increases in other bacteria.
These findings suggest gut microbiome alterations, including loss of anti-inflammatory commensals like Faecalibacterium, may be linked to disease progression from asymptomatic HTLV-1 carriage to HAM/TSP. This supports extending the gut-brain axis framework, already established in diseases like multiple sclerosis, to HTLV-1-associated neuroinflammation. The results position the gut microbiome as a potential area for further investigation in understanding or monitoring HAM/TSP progression.
This pilot study applied an integrative multi-omics workflow to identify plasma metabolite, lipid, and gut-microbiome signatures associated with sarcopenia. Sarcopenia is the age-related decline in muscle mass and strength, and the researchers combined plasma metabolomics, lipidomics, and 16S rRNA gut-microbiome sequencing to look for markers linked to the condition. Participants were classified as sarcopenic or non-sarcopenic using EWGSOP2 criteria, which incorporate grip strength, chair rise time, psoas muscle cross-sectional area on CT, and the SARC-F screening score.
The cohort consisted of forty community-dwelling older adults, aged 60 to 87 years, from an Indian population. Of these, fifteen were classified as sarcopenic and twenty-five as non-sarcopenic based on EWGSOP2 criteria. This was a pilot study, so the sample size was small and intended to generate preliminary integrative findings rather than definitive population-level estimates.
Dominant hand grip strength was the strongest clinical predictor of sarcopenia, with an AUROC of 0.93. Sarcopenic subjects showed higher systemic inflammation, reflected in an elevated neutrophil-to-lymphocyte ratio, and elevated plasma arachidonic acid compared to non-sarcopenic subjects. Thirteen lipid species, primarily lysophosphatidylcholines, lysophosphatidylethanolamines, and hexosylceramides, were identified as discriminating between the two groups, and a support vector machine model with recursive feature elimination was used to identify these discriminative metabolites, with gut microbiome profiles correlated against the metabolite patterns. The abstract as provided does not mention Faecalibacterium prausnitzii, butyrate, or anti-inflammatory commensals specifically.
The findings suggest that sarcopenia in older adults is accompanied by a distinct signature of systemic inflammation, altered lipid metabolism, and arachidonic acid elevation that can be captured through integrative multi-omics profiling. Combining clinical measures like grip strength with plasma metabolomic, lipidomic, and gut-microbiome data may help identify biological markers of sarcopenia beyond physical function tests alone. Because this was a small pilot study within an Indian cohort, larger and more diverse studies would be needed before these metabolite, lipid, and microbiome signatures could be used as validated diagnostic or monitoring tools.
This study investigated how infection with the soil-transmitted helminth Trichuris trichiura affects the composition and function of the human gut microbiota. Researchers used standardized, high-resolution metagenomic profiling to compare infected and uninfected individuals across three geographically distinct, endemic regions. The analysis looked at both taxonomic shifts (which microbial taxa change) and functional shifts (how microbial metabolism changes) in response to infection.
The study drew on gut microbiota samples from individuals living in three helminth-endemic countries: Cote d'Ivoire, Laos, and Tanzania. The abstract does not give an exact sample size, but the design compares T. trichiura-infected individuals to uninfected individuals within each of these three regional populations. This cross-country design allowed the researchers to distinguish patterns shared across sites from patterns specific to a single country.
Infection was consistently associated with depletion of short-chain fatty acid (SCFA) producing bacteria, including Blautia sp. MSJ 9 and Holdemanella biformis, alongside enrichment of mucin-degrading genera such as Ruminococcus and Bacteroides. Infected individuals also showed increased microbial use of host-derived carbohydrates and destabilization of microbial community networks, including the emergence of Segatella copri. While the specific taxa involved varied by country, the overall trend toward SCFA depletion and mucin degradation was shared across all three regions, suggesting a common metabolic response to trichuriasis.
The consistent loss of SCFA-producing, anti-inflammatory commensals alongside increased mucin degradation suggests that T. trichiura infection compromises gut barrier function and alters immune modulation. These microbial changes may create conditions that help the parasite persist in the host. The findings point to gut microbiota alterations as a shared, cross-regional feature of trichuriasis that could inform future understanding of host-parasite-microbiome interactions.
This randomized, double-blind, placebo-controlled trial tested whether daily supplementation with two specific probiotic strains, Bifidobacterium animalis subsp. lactis XLTG11 and Lactiplantibacillus plantarum CCFM8661, could reduce recurrent respiratory tract infections (RRTIs) in children. Over 180 days, the study tracked infection frequency and duration alongside changes in gut microbiota composition, functional metabolic pathways, and immune biomarkers. The design allowed the researchers to link clinical respiratory outcomes to underlying shifts in the gut microbial community and immune regulation.
The study enrolled 120 children who had been diagnosed with recurrent respiratory tract infections. Participants were randomly assigned to receive either the probiotic combination or a matched placebo daily for 180 days. The abstract does not provide further demographic details such as age range or sex distribution.
Children receiving the probiotics had significantly reduced duration and frequency of fever, cough, upper respiratory tract infections, trachea or bronchitis, pneumonia, and overall RRTI recurrence compared with placebo (all p < 0.05). Gut microbiota profiling at day 180 showed clear community differences between groups, with the probiotic group showing greater abundance of beneficial commensal taxa and the placebo group showing more opportunistic genera. Functional pathway analysis pointed to enhanced metabolic stability in the probiotic recipients, and immune biomarker patterns showed comparatively stable IgG, IgM, and complement C3 levels, suggesting a more regulated humoral immune response. Growth trajectories remained normal in both groups.
These findings support strain-defined probiotic supplementation as a viable adjunct strategy for reducing the burden of recurrent respiratory infections in children. The parallel shifts in gut microbial composition, metabolic function, and humoral immune stability suggest the respiratory benefit may be mediated through gut-immune axis modulation rather than a direct respiratory-tract effect. Because growth remained normal, the intervention appears well tolerated over a six-month period, supporting its potential for longer-term pediatric preventive use pending further confirmatory trials.
This study used multi-omics technologies, including 16S rRNA sequencing and metagenomic analysis, to characterize age-related changes in the gut microbiome and metabolome of Kunming dogs. It examined how these microbial and metabolic shifts across different life stages related to the dogs' police performance. The authors describe it as the first study to apply this multi-omics approach to investigate the gut microbiota-performance relationship in this working dog breed.
The subjects were Kunming dogs, a working dog breed used in police roles, grouped by age category: puppies, young dogs, adult dogs, and elderly dogs. The abstract does not give an exact sample size or number of animals per group. Police performance was assessed and compared across these four age stages.
Puppies, young dogs, and adult dogs showed significantly better police performance than elderly dogs, with young dogs scoring highest overall. Gut microbial diversity and stability were greatest at the young dog stage and declined progressively with age. Metagenomic analysis identified that abundances of Lactobacillus acidophilus, Lactobacillus johnsonii, Limosilactobacillus reuteri, Ligilactobacillus animalis, and Muribaculum gordoncarteri were strongly correlated with police performance scores.
The findings suggest that age-related decline in gut microbial diversity and stability may parallel, and potentially contribute to, the decline in police working performance seen in elderly dogs. Identifying specific taxa such as Lactobacillus and Ligilactobacillus species correlated with performance offers candidate targets for microbiome-based interventions. The authors propose this provides a theoretical foundation for enhancing working dog capability through targeted modulation of intestinal microecology.
This study examined gut microbiota composition in children with three rare, monogenic intoxication-type inborn errors of metabolism: methylmalonic acidemia (MMA), propionic acidemia (PA), and maple syrup urine disease (MSUD). All affected children were on medically supervised, protein-restricted diets, which the authors note may itself alter the gut microbiome. Fecal samples were analyzed using 16S rRNA sequencing, and both alpha and beta diversity were assessed. The authors highlight that no prior study had characterized gut microbiota in MMA or MSUD specifically.
The cohort consisted of eight children with these disorders (five with MMA, one with PA, and two with MSUD), all following a protein-restricted diet under medical supervision. Eleven age-matched healthy children served as controls. This is a small, real-world pediatric clinical sample rather than a public dataset, reflecting the rarity of these inborn errors of metabolism.
Patients with MMA, PA, and MSUD showed significantly altered gut microbiota composition compared to healthy controls. Alpha diversity was reduced in patients, with significantly lower Chao1 and observed OTU indices, indicating decreased microbial richness. Beta diversity analysis showed distinct clustering, meaning the overall community structure differed significantly between patient and control groups. The abstract does not mention Faecalibacterium prausnitzii, butyrate, or specific anti-inflammatory commensal taxa.
These findings suggest that children managing MMA, PA, or MSUD with strict protein-restricted diets may develop a less rich and structurally distinct gut microbiome relative to healthy peers. Because this is the first data available for MMA and MSUD, it establishes a baseline for future research into how dietary protein restriction and disease biology jointly shape the microbiome in these disorders. Given the very small sample size, these results should be viewed as preliminary and hypothesis-generating rather than conclusive. Larger studies are needed to clarify whether microbiota alterations relate to disease pathophysiology, dietary restriction, or both, and whether they carry clinical consequences.
This study characterized the gut microbiota of patients with natural killer/T-cell lymphoma (NKTCL), an aggressive malignancy with a poor prognosis, using shotgun metagenomic sequencing. The researchers aimed to identify marker species linked to disease outcomes and to test whether specific gut bacteria could act as probiotics to slow NKTCL progression. They combined cross-sectional microbiota profiling with in vivo and in vitro tumor models, plus metabolomics, RNA sequencing, chromatin immunoprecipitation sequencing, Western blot, immunohistochemistry, and gene knockdown experiments to trace the underlying mechanism.
The study drew on two Chinese cohorts of NKTCL patients, with findings validated in an independent Korean cohort. Cox proportional hazards models were used to relate microbial marker species to patient survival outcomes across these cohorts. Beyond the human cohorts, the mechanistic work relied on in vivo and in vitro tumor models rather than additional patient populations.
NKTCL patients showed marked gut microbiota dysbiosis, most notably a reduction in Faecalibacterium prausnitzii, a butyrate-producing commensal. This depletion correlated strongly with shorter patient survival. The abstract further indicates that F. prausnitzii demonstrated antitumour properties against NKTCL, with the fuller mechanistic work pointing toward suppression of the JAK-STAT pathway as noted in the study title.
The findings position F. prausnitzii, a butyrate-producing anti-inflammatory commensal, as a potential prognostic marker and probiotic candidate in NKTCL, a cancer with few therapeutic levers. Restoring this depleted organism could represent a novel adjunct strategy to dampen tumor-promoting JAK-STAT signaling. These results support further investigation into microbiome-targeted interventions for aggressive lymphomas where gut dysbiosis tracks with clinical outcomes.
This study investigated the effects of a novel elite athlete derived probiotic, a multi-strain Lactobacillus consortium, on sleep quality, exercise recovery, and gut microbiome composition. The researchers used a two phase design: an open-label study followed by a controlled longitudinal study. Multi-omics analyses were used to examine changes in microbiome composition and function alongside host physiological markers.
The study included elite athletes (n = 11), specifically a professional soccer team for the controlled longitudinal phase, and a general population sample (n = 257) in the open-label phase. This dual-cohort design allowed comparison between high-performance athletes and a broader nonathlete population. No further demographic details are given in the abstract.
In the placebo-controlled study, probiotic intervention was associated with significant improvements in self-reported sleep quality (69%), energy levels (31%), and bowel movements (37%) relative to placebo. These improvements coincided with a significant decrease in D-ROMS, a marker of oxidative stress, and a significantly higher free-testosterone to cortisol ratio. Multi-omics analyses revealed specific changes in gut microbiome composition and function that may help explain these host effects.
The findings suggest that a targeted Lactobacillus consortium can meaningfully influence sleep, energy, recovery-related hormone balance, and oxidative stress through gut microbiome-mediated mechanisms. This supports the gut microbiome as a plausible intervention point connecting sleep and exercise recovery in both elite athletes and the general population. The multi-omics insights point toward mechanistic pathways that could inform future probiotic formulations aimed at recovery and wellness.
This study examined the human gut microbiome across diverse African populations using shotgun metagenomic sequencing. It aimed to characterize how geography, lifestyle, and environmental factors shape gut microbial composition in regions underrepresented in prior microbiome research. The researchers also assembled bacterial genomes directly from the metagenomic data and looked for microbiome signatures associated with HIV infection.
The AWI-Gen 2 Microbiome Project sampled 1,801 women from Burkina Faso, Ghana, Kenya, and South Africa. The cohort spanned a wide range of community settings, from rural and horticultural communities to post-industrial and urban informal settlements. This design was intended to capture a breadth of population diversity not typically represented in large-scale gut microbiome studies, which have historically underrepresented low- and middle-income countries.
The study identified taxa with clear geographic and lifestyle associations, including loss of Treponema and Cryptobacteroides species and gain of Bifidobacterium species in urban populations. The researchers assembled 1,005 bacterial metagenome-assembled genomes from the dataset. They also found evidence that antibiotic susceptibility may drive the absence of Treponema succinifaciens in urban populations. Additionally, an HIV infection signature was identified, defined by several taxa, including Dysosmobacter welbionis and Enterocloster species, not previously linked to HIV.
This work represents the largest population-representative survey of the gut microbiome in Africa, expanding the global microbiome atlas beyond historically overrepresented, industrialized populations. The urbanization-linked taxa shifts suggest that lifestyle transitions, including antibiotic exposure, can rapidly reshape the gut microbiome. The discovery of a novel HIV-associated taxa signature, involving organisms not previously implicated, opens new avenues for investigating host-microbiome interactions in HIV infection across diverse global populations.
This study examined how juicing affects the gut and oral microbiome, since juicing removes most insoluble fiber found in whole fruits and vegetables. Researchers compared three diets: an exclusive juice diet, a juice-plus-food diet, and a plant-based food diet, each followed for three days. Stool, saliva, and inner cheek swab samples were collected at baseline, after a pre-intervention elimination diet, immediately after the juice intervention, and 14 days later. Microbiota composition was analyzed using 16S rRNA gene amplicon sequencing.
Fourteen participants took part in this intervention study, each assigned to one of the three dietary arms (exclusive juice, juice plus food, or plant-based food). Samples were drawn from three body sites per person (stool, saliva, and inner cheek) across four time points. The abstract does not specify additional demographic details such as age range or sex distribution.
The saliva microbiome changed significantly in response to the pre-intervention elimination diet, as measured by both unweighted UniFrac (F = 1.72, R² = 0.06, p < 0.005) and weighted UniFrac (F = 7.62, R² = 0.23, p = 0.0025) distances. This shift included a significant reduction in Firmicutes abundance. The abstract provided did not include the full results for the juice intervention itself or for the gut (stool) microbiome, so those comparisons cannot be summarized here.
The findings suggest that short-term dietary changes, even a pre-intervention elimination diet, can measurably alter oral microbiome composition, particularly Firmicutes levels. This underscores that oral and gut microbiota may respond quickly to shifts in fiber and food-matrix intake, relevant to concerns that juice-only diets strip away insoluble fiber. Because the available abstract text stops short of the juicing-specific outcomes, firm conclusions about juicing's net effect on the microbiome await the complete results.
This study investigated whether baseline gut microbiota composition could predict treatment response to the pharmacological agent empagliflozin in patients with metabolic dysfunction-associated steatotic liver disease (MASLD) who did not have diabetes mellitus. Researchers prospectively followed these patients from baseline through week 52 (end of treatment), performing clinical, anthropometric, and laboratory assessments alongside MRI-proton density fat fraction (MRI-PDFF) imaging to track liver fat content. Baseline stool samples underwent shotgun DNA metagenomic sequencing to profile the gut microbiome. Treatment response was defined as an MRI-PDFF decline of 30% or more from baseline to end of treatment.
The cohort consisted of 45 non-diabetic MASLD patients who used empagliflozin, with a median age of 56.9 years (interquartile range 51.0 to 63.2) and 23 patients (51.1%) male. Of these 45 patients, 22 (48.9%) achieved treatment response by the end of treatment. This was a prospectively followed clinical cohort rather than a public dataset, with baseline stool samples collected from each participant for metagenomic analysis.
Baseline gut microbiome composition differed significantly between patients based on later treatment outcomes, with differences observed in alpha diversity (Shannon index p < 0.001, Simpson index p = 0.001) and beta diversity (p = 0.048). Linear discriminant analysis (LDA) effect size methods were used to identify putative bacterial species associated with treatment response. Multivariable logistic regression was then applied to derive adjusted odds ratios linking specific bacterial species to treatment outcome after accounting for clinical factors. The abstract provided does not name specific taxa such as Faecalibacterium prausnitzii or mention butyrate.
These findings suggest that baseline gut microbiota diversity and composition may serve as a biomarker to predict which non-diabetic MASLD patients are more likely to respond to empagliflozin therapy. This could support a more personalized approach to selecting pharmacological treatment for MASLD based on an individual's microbiome profile. Further validation would be needed to confirm which specific bacterial species drive this predictive relationship and how they might inform clinical decision-making.
This study investigated Roseburia hominis as a novel candidate probiotic (next-generation live biotherapeutic) for treating obesity and related metabolic disease. The researchers first examined how R. hominis abundance related to obesity status, then tested whether supplementing R. hominis could prevent metabolic disturbances in a diet-induced obesity model. They also explored a possible mechanism involving nicotinamide riboside production and Sirtuin1/mTOR signaling.
The abstract describes stool samples compared between obese subjects and lean controls, indicating a human cohort used to establish the association between R. hominis abundance and body mass index and serum triglycerides. The interventional portion of the study was conducted in mice fed a high-fat diet to model diet-induced obesity. Specific numbers of human subjects or mice, and demographic details, are not given in the abstract.
Roseburia hominis was depleted in the stool of obese subjects compared with lean controls, and its abundance was negatively correlated with body mass index and serum triglycerides. In high-fat-diet mice, supplementing R. hominis prevented body weight gain, corrected glucose and lipid metabolism disorders, prevented fatty liver, inhibited white adipose tissue expansion, and reduced brown adipose tissue whitening, while boosting lean-associated microbial species. These effects were linked in part to R. hominis production of nicotinamide riboside and upregulation of the Sirtuin1/mTOR signaling pathway.
The findings position Roseburia hominis as a promising next-generation live biotherapeutic candidate for preventing obesity and metabolic disease. Because its depletion tracks with obesity and adverse metabolic markers in humans, restoring this commensal species could represent a targeted microbiome-based strategy rather than a broad-spectrum probiotic approach. The nicotinamide riboside and Sirtuin1/mTOR mechanism offers a specific pathway for further mechanistic and translational research.
The study examined how Zhuyang Tongbian Decoction (ZTD), a treatment for functional constipation (FC), affects the gut microbiome and related inflammatory markers. Researchers used 16S rRNA sequencing, metagenomics, and metabolomics to track changes in intestinal flora composition and microbiota metabolic function. They also measured fecal short-chain fatty acid (SCFA) levels and serum concentrations of TLR4, NF-κB, TNF-α, and IL-6 before and after treatment.
The study included 40 patients with functional constipation, randomly divided into a control group (20 cases, treated with lactulose) and a treatment group (20 cases, treated with ZTD). Twenty healthy volunteers were also recruited during the same period, presumably for comparison. Sample sizes were small, consistent with the pilot nature of the study.
The ZTD treatment group showed a significant increase in beneficial bacteria, including Bifidobacterium, Lactobacillus, and Faecalibacterium prausnitzii (P < 0.05). Desulfobacterota and Ruminococcus were significantly reduced in the treatment group (P < 0.05). Fecal acetic and propionic acid levels, both short-chain fatty acids linked to anti-inflammatory commensal activity, were also affected by treatment, though the abstract text describing the exact direction and magnitude was cut off.
The findings suggest ZTD may relieve functional constipation partly by reshaping the gut microbiota toward beneficial, SCFA-producing organisms such as Faecalibacterium prausnitzii while reducing potentially less favorable taxa. This points to a microbiome-mediated mechanism, possibly involving reduced inflammatory signaling through the TLR4/NF-κB pathway, as part of ZTD's therapeutic effect. As a pilot study with a small sample size, these results support further, larger trials to confirm the mechanism and clinical benefit.
This study conducted a machine learning meta-analysis of gut microbiome data from multiple prior Parkinson's disease (PD) studies, pooling an unprecedented 4,489 samples. The researchers built classification models to identify microbiome features associated with PD and tested how well these models generalized across different, independently collected datasets. They also performed meta-analysis of shotgun metagenomic data to identify PD-associated microbial functional pathways.
The analysis drew on 4,489 samples pooled from multiple existing PD microbiome studies, rather than a single new patient cohort. The abstract does not specify demographic details of the underlying individuals, but the dataset includes both PD patients and comparison samples, since models were evaluated for their ability to distinguish PD from other neurodegenerative diseases. This makes the population effectively a large, multi-study compilation of previously published microbiome sequencing data.
Machine learning models trained within a single study classified PD patients accurately, with an average AUC of 71.9 percent, but these models performed much worse when applied to other studies, dropping to an average AUC of 61 percent, showing poor generalizability. Training models on multiple combined datasets improved generalizability, raising the average leave-one-study-out AUC to 68 percent, and improved specificity for PD compared to other neurodegenerative diseases. Meta-analysis of shotgun metagenomes identified PD-associated microbial pathways linked to gut health deterioration and potential translocation of pathogenic molecules along the gut-brain axis. Notably, microbial pathways involved in solvent and pesticide biotransformation were enriched in PD samples.
The findings suggest that single-study PD microbiome signatures do not reliably generalize, so meaningful diagnostic use requires models trained across multiple, diverse datasets. The enrichment of pesticide and solvent biotransformation pathways aligns with epidemiological evidence linking these exposures to increased PD risk, raising the possibility that gut microbes modulate toxicity from environmental chemicals. Overall, the study points toward the gut-brain axis and microbial detoxification pathways as promising targets for understanding PD risk and improving diagnostic tools.
This meta-analysis examined the gut microbiome in obese children with metabolic dysfunction-associated steatotic liver disease (MASLD) or metabolic dysfunction-associated steatohepatitis (MASH). Researchers searched electronic databases for studies providing shotgun metagenomic sequencing data on the gut microbiome in children with obesity, with or without MASLD or MASH. The analysis combined data from multiple existing studies with an additionally recruited cohort to compare microbiome composition and function across disease states.
The pooled analysis included obese children with MASLD (n = 153) and MASH (n = 70), compared against obese children without liver disease (n = 58) and healthy controls (n = 132). This population was assembled from nine identified studies plus one additionally recruited cohort, all using shotgun metagenomic sequencing. The study therefore draws on a multi-cohort pediatric dataset rather than a single trial population.
Fecal microbiomes of children with MASLD and MASH differed significantly in alpha- and beta-diversity compared to obese and healthy children (p < 0.001). Faecalibacterium prausnitzii and Prevotella copri were differentially abundant across the obese, MASLD, and MASH groups. Machine-learning models (XGBoost and random forest) accurately distinguished MASLD from obesity (AUROC 87%) and MASH from MASLD (AUROC 89%), with pathway-abundance-based models performing similarly well (81% and 88%, respectively). Increasing hepatic fibrosis was accompanied by further gut microbiome alteration and a concomitant rise in Prevotella copri abundance (p = 0.0082).
The findings suggest that gut microbiome composition, including shifts in species such as Faecalibacterium prausnitzii and Prevotella copri, tracks with the progression from obesity to MASLD to MASH and fibrosis severity in children. The high predictive accuracy of microbiome-based machine-learning models points to potential non-invasive tools for staging pediatric liver disease. These results also support the gut microbiome as a plausible target for future diagnostic or therapeutic strategies in pediatric metabolic liver disease.
This study investigated whether preeclampsia in pregnant women is associated with changes in gut microflora composition. Researchers used Illumina HiSeq sequencing to characterize 16S rRNA bacterial profiles from stool samples. They compared overall bacterial diversity and specific taxa abundances across preeclampsia and normal pregnancy groups, and further examined differences by preeclampsia severity.
The study included 54 pregnant women divided into an experimental group of 27 women with preeclampsia and a control group of 27 healthy pregnant women (NOR). Within the preeclampsia group, 13 women had severe preeclampsia (SP) and 14 had non-severe preeclampsia (P). Stool samples from these four subgroups were used for gut microbiome sequencing and comparison.
Bacterial alpha diversity was higher in the preeclampsia group than the normal group, though this difference did not reach statistical significance. Bacteroidetes, Firmicutes, and Proteobacteria were the dominant phyla across all groups. Synergistetes abundance was significantly lower in the preeclampsia group compared to normal pregnancy, while Bacteroidetes was significantly higher and Firmicutes significantly lower in non-severe preeclampsia compared to severe preeclampsia. LEfSe analysis identified nine differential taxa between preeclampsia and normal groups, with Ruminococcaceae distinguishing non-severe from severe preeclampsia, and differential species screening found three taxa distinguishing preeclampsia from normal pregnancy and four taxa distinguishing non-severe from severe preeclampsia.
The findings suggest that preeclampsia, and its severity, is accompanied by measurable shifts in gut microbial community composition, particularly involving Synergistetes, Bacteroidetes, Firmicutes, and Ruminococcaceae. This raises the possibility that gut flora composition could serve as a biomarker to distinguish preeclampsia status or severity in pregnant women. Further research would be needed to determine whether these microbial changes are causally involved in preeclampsia pathophysiology or are secondary to the condition.
This study pooled stool metagenomic data across 18 cohorts to search for reproducible gut microbial biomarkers of colorectal cancer (CRC) across disease stages and at the strain level. It combined 12 existing metagenomic datasets with 6 newly added cohorts that gave detailed information on cancer stage and tumor location. The goal was to improve CRC prediction accuracy from gut metagenomics alone and to characterize species and strain-level signatures tied to disease progression.
The pooled dataset totaled 3,741 stool metagenomes: 930 from patients with CRC, 210 from patients with adenomas, and 976 from healthy control individuals across 12 original cohorts (n = 2,116), plus 6 new cohorts adding 1,625 more samples. The new cohorts specifically contributed granular staging and tumor-location data not available in the earlier datasets. This represents a large, multi-cohort, cross-stage human patient population rather than a single-site or small trial.
CRC prediction accuracy based solely on gut metagenomics improved to an average area under the curve of 0.85, aided by 19 newly profiled species and distinct Fusobacterium nucleatum clades. Specific gut species distinguished left-sided from right-sided CRC (area under the curve = 0.66), with right-sided tumors showing enrichment of oral-typical microbes. Strain-level analysis identified CRC signatures in the commensals Ruminococcus bicirculans and Faecalibacterium prausnitzii, with certain subclades of these species associated specifically with late-stage CRC.
The findings confirm that the gut microbiome can serve as a clinical target for CRC screening, with metagenomic profiles achieving strong predictive accuracy across a large, diverse pooled cohort. The identification of strain-level subclades of commensals like Faecalibacterium prausnitzii associated with late-stage disease suggests the microbiome may also function as a biomarker for CRC progression, not just detection. Differentiating left- versus right-sided CRC based on microbial composition, including oral-microbe enrichment, points toward more anatomically precise, non-invasive screening approaches in the future.
This observational study examined whether the gut microbiota influences functional recovery three months after acute ischemic stroke. Researchers used shotgun metagenomic sequencing on stool samples collected from patients treated at a tertiary stroke centre between January 2020 and March 2022. They compared microbial community structure, diversity, and functional gene pathways between patients with favorable versus unfavorable outcomes on the modified Rankin Scale. They also used two-sample Mendelian randomization with GWAS summary statistics to test whether specific bacteria have a causal relationship with post-stroke outcomes.
The study population consisted of 128 patients with acute ischemic stroke recruited from a single tertiary stroke centre. Outcomes were stratified using modified Rankin Scale scores at three months post-stroke, with scores of 0 to 2 classified as favorable and 3 to 6 classified as unfavorable. The abstract does not provide further demographic details such as age, sex distribution, or stroke severity at baseline.
Beta-diversity analysis showed a clear separation in overall microbial community structure between patients with favorable and unfavorable outcomes, and alpha-diversity measures showed greater bacterial richness in the favorable outcomes group. Taxonomic profiling found that a greater abundance of pathogenic bacteria, including Pseudomonas, Finegoldia, and Porphyromonas, was associated with unfavorable functional outcomes. Functional profiling of the metagenomic data revealed differences between groups in the ethylbenzene degradation pathway and in 16S rRNA (uracil1498-N3)-methyltransferase. The abstract text provided is truncated before the Mendelian randomization results are reported in full, so the specific causal findings from that analysis cannot be summarized here.
The findings suggest that gut microbial diversity and composition may help explain some of the unexplained variability in functional recovery after ischemic stroke. Lower bacterial richness and higher abundance of pathogenic taxa appear linked to worse three-month outcomes, pointing to the gut microbiota as a potential prognostic marker or modifiable target after stroke. The use of Mendelian randomization suggests the authors aimed to move beyond association toward establishing whether specific bacteria causally affect recovery, which could inform future microbiome-targeted interventions. This abstract does not mention Faecalibacterium prausnitzii, butyrate, or anti-inflammatory commensals specifically, so the study's implications should be understood on its own terms as centered on pathogenic bacterial abundance and overall community diversity rather than on any single beneficial organism.
This study investigated whether gut microbiota composition and plasma metabolic profiles are altered in lymph node tuberculosis (LNTB), a form of tuberculosis whose relationship with gut microbiota had not previously been explored. Researchers used metagenomic sequencing to characterize gut microbial diversity and composition, paired with plasma metabolomics to assess circulating metabolite changes. KEGG pathway analysis was applied to link microbial gene content to metabolic function, focusing especially on short-chain fatty acid (SCFA) biosynthesis. An integrated analysis then examined correlations between specific gut bacteria and plasma metabolites in LNTB.
The abstract does not report specific participant numbers, ages, or geographic setting. It indicates a comparison between individuals diagnosed with lymph node tuberculosis (the LNTB group) and healthy individuals serving as controls. Samples analyzed included gut microbiota (via metagenomic sequencing) and plasma (via metabolomics) from these two groups.
LNTB patients showed significantly altered gut microbial diversity, with notable reductions in SCFA-producing taxa including Ruminococcus, Faecalibacterium, Roseburia, and Blautia compared to healthy individuals. KEGG pathway analysis indicated that this gut dysbiosis negatively affected SCFA biosynthesis and metabolism. Plasma metabolomics revealed disruptions in metabolites tied to SCFA synthesis and inflammation pathways, and integrated analysis found significant correlations between taxa such as Blautia, Butyricicoccus, Coprococcus, Ruminococcus, Bacteroides, and Clostridium and plasma metabolites including alpha-benzylbutyric acid, acetic acid, and succinic acid.
The findings suggest that gut microbiota dysbiosis and consequent metabolic dysfunction, particularly reduced SCFA production, may play a role in LNTB pathophysiology. Because SCFAs and related anti-inflammatory commensal bacteria appear diminished in LNTB, restoring these microbial functions could represent a novel therapeutic target for disease management. This work opens a new avenue for considering the gut-immune axis in tuberculosis affecting lymph nodes, beyond the traditional focus on pulmonary disease.
This cross-sectional study examined how westernization affects the gut microbiome by comparing Indians living in India, Indo-Immigrants, and Indo-Canadians against Euro-Canadian and Euro-Immigrant controls. Stool samples underwent 16S rRNA and shotgun sequencing to characterize microbial taxa and functional gene profiles. Dietary and demographic data were also collected to evaluate lifestyle patterns alongside the microbiome data.
The study population consisted of Indians residing in India, Indo-Immigrants, and Indo-Canadians, compared against Euro-Canadian and Euro-Immigrant control groups. The abstract does not report specific sample sizes or detailed demographic breakdowns for these groups. The comparison design was built around migration status and country of residence rather than clinical diagnosis.
Indians and Indo-Immigrants harbored gut microbiotas distinct from Euro-Canadian and Euro-Immigrant controls, marked by high abundances of Prevotella species and carbohydrate-active enzymes (CAZymes) reflecting a diet rich in complex carbohydrates. Indo-Canadians showed a transitional microbiome profile that moved toward the westernized pattern seen in controls. This shift paralleled increasing dietary acculturation among Indo-Canadians rather than a fixed, heritable microbial signature.
Because 44% of Canadians are first- or second-generation immigrants, and westernized dietary practices are spreading globally, microbiome transitions like this one may be widespread and consequential. Since Indian immigration to westernized countries has surged and post-migration IBD risk rises accordingly, this dietary-driven microbiome shift may help explain that increased disease susceptibility. The authors call for future research into the health implications of such microbiome transitions in immigrant populations and in newly industrialized nations.
This study characterized the microbial DNA profile present in organ preservation solution (OPS) used during liver transplantation, using 16S rRNA sequencing. The researchers asked whether specific microbial taxa detected in the OPS, reflecting the intrahepatic graft's native microbiota, are associated with short-term clinical outcomes after transplant. They also built machine learning models to predict outcomes from these microbial features and used RNA sequencing of matched liver biopsies to validate host-microbiome interactions.
The discovery cohort consisted of 110 liver transplant donors, with an independent validation cohort of 29 additional donors. Microbial signatures were derived from the organ preservation solution collected in association with each donor's liver, rather than from patient stool or blood samples. Clinical outcome data for recipients were linked to these donor-derived OPS samples using MaAsLin2-adjusted statistical models.
The microbial DNA signature detected in the OPS closely resembled known liver and bile microbiome profiles and was dominated by Proteobacteria. Specific bacterial genera, including Bacillus and Prevotella, were differentially abundant and statistically associated with adverse post-transplant outcomes, being hyperabundant in cases with worse results. Gene pathway enrichment analysis and RNA sequencing of matched liver biopsies were used to explore host-microbiome interactions underlying these associations.
This work suggests that the intrahepatic graft's own microbiota, detectable in the preservation solution at the time of transplant, carries prognostic information that has previously been overlooked in favor of gut microbiota studies. Machine learning models built on these OPS-derived microbial features could enable early risk stratification for liver transplant recipients before complications arise. If validated further, this approach could support a practical, minimally invasive tool for predicting short-term transplant outcomes.
Only the title of this study was available, with no abstract to draw on. The title indicates the researchers examined microbial sharing between siblings and how it relates to metabolic functions that may protect against allergy. Beyond this framing, no specific methods, hypotheses, or experimental design details can be honestly reported.
No cohort, sample size, or population details are given in the available material. Based on the title referencing siblings, the study likely involved family units or sibling pairs, possibly using microbiome sequencing data from such households. No further demographic or sample specifics can be stated without inventing information.
The title suggests that siblings share microbes in ways that support metabolic functions with a protective role against allergy. No specific results, statistics, taxa, or metabolic pathways are provided in the available material. Without an abstract, the precise nature or strength of this finding cannot be described further.
If confirmed by the full study, sibling microbial sharing could represent a meaningful route by which household exposures shape metabolic and immune development. This would support broader interest in early-life microbial transmission as a factor in allergy risk. Further review of the complete study is needed to assess the actual implications, since only the title was available here.
This study examined whether rifaximin, a gut-specific non-absorbable antibiotic, could reduce gut-derived systemic inflammation in severe acute pancreatitis (SAP). The researchers combined murine experimental models with a single-center, open-label randomized controlled trial (ChiCTR2100049794). They assessed pancreatic injury, systemic inflammatory markers, and gut microbiota composition, and tested whether rifaximin's effects depended on modulating the microbiota by using antibiotic-treated and germ-free mice.
The animal component used murine models of severe acute pancreatitis, including antibiotic-treated and germ-free mice used to probe the mechanism. The clinical component enrolled 60 patients with predicted severe acute pancreatitis, randomized to receive rifaximin or standard control treatment. No further demographic details are given in the abstract.
In mice, rifaximin reduced pancreatic injury and systemic inflammation and decreased mucin-degrading gut genera such as Akkermansia, but its protective effects persisted even in antibiotic-treated and germ-free mice, indicating mechanisms beyond microbiota modulation. In patients, rifaximin significantly lowered systemic inflammation, with white blood cell count falling from a median of 11.50 x10^9/L to 8.49 x10^9/L and TNF-alpha falling from 15.05 pg/mL to 11.00 pg/mL. However, the rate of culture-confirmed infection was identical between rifaximin and control groups (13.3% vs 13.3%), and adverse events were comparable between groups.
The findings suggest rifaximin can dampen systemic inflammation in severe acute pancreatitis through mechanisms that are not solely dependent on reshaping the gut microbiota, pointing to a possible direct anti-inflammatory or barrier-protective effect. Because inflammation markers improved without any change in infection risk, rifaximin may offer a safe adjunct for controlling inflammatory injury in SAP without added infectious risk. This supports further investigation of rifaximin as a therapeutic strategy for gut-derived inflammation in acute pancreatitis, alongside continued study of its non-microbiota-dependent mechanisms.
This cross-sectional exploratory study examined associations between subjective sleep indices and gut microbiome features in adults with colorectal cancer (CRC). Researchers compared patients to their sleep-partner caregivers using sleep diaries, stool sampling, and dietary intake questionnaires. The design allowed comparison of microbiome and sleep characteristics within matched household pairs who shared similar diet and environment.
Forty participants were studied, consisting of 20 patient-caregiver dyads. Each dyad included an adult with colorectal cancer and their sleep-partner caregiver, and both members completed sleep diaries, stool sampling, and dietary questionnaires individually. Patients and caregivers had comparable demographics, dietary intake, and sleep indices at baseline.
Patients with CRC had significantly different gut microbiome beta diversity (p = .005) and alpha diversity (Inverse Simpson, p = .029) compared with their caregivers, along with 7 more and 6 less differentially abundant taxa. Among patients only, those with high sleep efficiency (at least 85%) had higher gut microbial diversity than those with lower sleep efficiency (Inverse Simpson p = .019, Shannon Index p = .035). Some oral and gut microbes were also differentially abundant between patients with high versus low sleep efficiency scores.
The findings highlight a link between sleep health and gut microbiome characteristics specifically in patients with colorectal cancer, distinct from their genetically unrelated but cohabiting caregivers. This suggests sleep quality may be associated with gut microbial diversity in cancer patients, though the abstract does not identify specific taxa driving this relationship. The authors note that further research with a larger sample is needed to replicate these findings and identify the pathways linking sleep to gut microbiome features.
This study examined how ethnicity and geography each relate to fecal microbiota composition and dietary habits among Tibeto-Burman-speaking hill-tribe populations in Northern Thailand. Researchers used quantitative PCR to characterize gut microbiota and applied multivariate statistical methods, including multiple factor analysis and partial least squares discriminant analysis, to link microbiota composition with ethnicity, geographic location, dietary behaviors, and other host variables. The goal was to disentangle whether ethnic identity or regional residence is the stronger driver of gut microbiota variation, a question the abstract notes is understudied in Thailand.
The study population consisted of 102 individuals from Tibeto-Burman hill-tribe ethnic groups, specifically the Akha, Lahu, and Lisu peoples. These participants resided in two provinces of Northern Thailand, Chiang Mai and Chiang Rai, allowing comparisons both across ethnic groups and across geographic locations. The abstract does not provide further demographic detail such as age or sex distribution.
Both ethnicity and geography were associated with gut microbiota composition and dietary patterns, but geography showed a stronger association with microbiota variation than ethnicity did. Ethnicity, by contrast, was primarily linked to differences in dietary habits rather than directly to microbiota composition. Notably, microbiota profiles were more similar among different ethnic groups sharing the same location than among the same ethnic group split across different regions, and the diet-microbiota relationship itself varied by ethnic and geographic group. Host factors other than diet, ethnicity, and geography had a comparatively minor influence on microbiota composition.
The findings suggest that shared environment and geography can outweigh shared ethnic ancestry in shaping the gut microbiota, at least among closely related hill-tribe populations living in the same region. This implies that microbiome studies should account for local geographic and environmental exposures rather than treating ethnicity alone as the key explanatory variable. The results also highlight that diet, rather than ethnicity per se, may be the more direct pathway linking population identity to microbiota differences, which is relevant for designing future studies of diet-microbiome relationships in diverse populations.
This study investigated how type 2 diabetes mellitus (T2DM) affects the vaginal microbiota in perimenopausal and postmenopausal women. Researchers used metagenomic sequencing of vaginal secretion samples to characterize microbial community structure and functional homeostasis. They assessed alpha diversity (Observe, ACE, Shannon-Weaver, Gini-Simpson indices) and beta diversity (PCoA, NMDS), and applied taxonomic profiling, LEfSe analysis, co-occurrence network construction, and neutral community modeling to determine whether stochastic or deterministic processes shaped the community.
The study included 22 women with T2DM (the DM group) and 23 healthy women (the CT group), all in perimenopausal or postmenopausal life stages. The two groups did not differ significantly in age (62.22 plus or minus 5.74 years vs. 58.23 plus or minus 7.55 years, p = 0.052) or in the proportion of perimenopausal versus postmenopausal participants (3/19 vs. 5/18, p = 0.748). This design allowed the researchers to isolate the effect of T2DM on the vaginal microbiota independent of age or menopausal status.
The DM group showed significantly higher alpha diversity than the control group (p < 0.05), along with distinct clustering on beta diversity analysis (p < 0.05). This shift was marked by reduced Lactobacillus abundance in the diabetic women compared to healthy controls. The abstract indicates additional taxonomic and network-level differences were identified through LEfSe and co-occurrence analyses, alongside evidence bearing on stochastic versus deterministic community assembly, though the abstract text provided does not detail every specific taxon or network finding beyond the Lactobacillus reduction.
The findings suggest that T2DM is associated with a less Lactobacillus-dominated, more diverse and heterogeneous vaginal microbial community in perimenopausal and postmenopausal women, independent of age or menopausal stage. Since a Lactobacillus-depleted vaginal environment is generally linked to reduced protective function, this points to T2DM as a distinct driver of vaginal dysbiosis risk in this population. These results underscore the need to consider metabolic status, not just menopause, when evaluating vaginal microbiome health and potential dysbiosis-adjustment strategies in aging women.
This study investigated the relationship between intestinal microbiota and abdominal fat deposition in meat ducks. Researchers used a combined multi-omics approach, including 16S rRNA gene sequencing, metagenomics, and whole transcriptomics, to compare ducks with high and low abdominal fat rates. They profiled multiple intestinal segments, including the duodenum, jejunum, ileum, rectum, and cecum, to identify which region and which microbial features were most associated with fat accumulation.
The subjects were an F2 population of meat ducks derived from a cross between Cherry Valley Ducks (male) and Runzhou Crested White Ducks (female), evaluated at 42 days of age. Ducks were sorted into a low abdominal fat (LF) group, with an abdominal fat rate of 0 to 0.75 percent, and a high abdominal fat (HF) group, with a rate of 1.5 to 2.25 percent. This was an animal-based comparative cohort rather than a human or purely computational dataset.
The cecum showed the highest microbial diversity of all intestinal segments examined and was significantly enriched in carbohydrate metabolism pathways, underscoring its central role in nutrient utilization and growth. Because of this, the cecum was selected for deeper analysis. Metagenomic analysis of cecal contents revealed significantly different microbial beta diversity between the high and low abdominal fat rate groups, indicating that overall cecal community composition differs by fat status.
The findings point to the cecum as the key intestinal segment linking gut microbiota to abdominal fat deposition in ducks, largely through its role in carbohydrate metabolism. This positions cecal microbial composition and function as a potential target for strategies to improve feed efficiency and reduce excess fat in meat duck production. The multi-omics design also offers a model for tracing host-microbe interactions underlying fat storage in poultry more broadly.
This study examined the longitudinal development of infant gut microbiota and its relationship to tetanus toxoid vaccine responses. Researchers used 16S rRNA gene sequencing to profile gut microbiota at two early-life time points, under one week and 15 weeks of age. They evaluated whether HIV exposure without infection altered microbiota composition and succession, and whether these microbiota patterns were linked to anti-tetanus antibody titers measured by enzyme-linked immunosorbent assay.
The study included 278 infants total, drawn from two cohorts: 82 South African infants (61 exposed to HIV but uninfected, and 21 HIV-unexposed and uninfected) and 196 Nigerian infants (141 exposed to HIV but uninfected, and 55 HIV-unexposed and uninfected). All infants were assessed at both the under-one-week and 15-week time points. Feeding practice was also documented, noting that the Nigerian infants were exclusively breastfed.
Gut microbiota composition and its succession over the first 15 weeks of life were shaped more strongly by geographic location and infant age than by HIV exposure status. Nigerian infants underwent a dramatic microbiota shift over this period, becoming dominated by Bifidobacterium longum subspecies infantis, a shift not seen in South African infants even when the analysis was restricted to exclusively breastfed babies. Using Least Absolute Shrinkage and Selection Operator (LASSO) regression, the study found that HIV exposure and gut microbiota composition were each independently associated with tetanus antibody titers at 15 weeks, with high passively transferred maternal antibody also playing a role.
The findings suggest that geography and associated feeding and environmental practices are more powerful drivers of early infant gut microbiota development than HIV-exposure status alone. The emergence of Bifidobacterium longum subspecies infantis dominance in exclusively breastfed Nigerian infants, but not South African infants, points to population-specific factors shaping microbiota maturation beyond breastfeeding alone. Because gut microbiota and HIV exposure independently predicted vaccine antibody responses, these results support further investigation into microbiota-targeted strategies to optimize infant immune and vaccine responses across diverse populations.
This study investigated how the gut microbiota influences differential host resistance to porcine epidemic diarrhea virus (PEDV) infection in piglets. Researchers combined single-cell transcriptomics, 16S amplicon sequencing, metagenomics, and untargeted metabolomics to characterize the microbial and metabolic changes that follow PEDV infection. The work focused on identifying specific bacterial species and their metabolites that mediate protection against this pathogen.
The study used Landrace and Min pig breeds, two breeds with differing natural resistance to PEDV infection. Landrace pigs, which lose resistance quickly after infection, received fecal microbiota transplants from Min pigs, which are comparatively resistant. Animal protection models were then used to test the effects of specific bacteria and metabolites identified through the multi-omics analysis.
PEDV infection caused significant changes in the gut microbiota of piglets, and transplanting fecal microbiota from resistant Min pigs into susceptible Landrace pigs alleviated the infection. Metagenomic and animal protection models identified Lactobacillus reuteri and Lactobacillus amylovorus as playing an anti-infective role. Metabolomic screening linked these bacteria to the secondary bile acids deoxycholic acid (DCA) and lithocithocholic acid (LCA), but only LCA showed a protective effect in the animal model, and LCA supplementation altered the distribution of intestinal T-cell populations, notably enriching CD8+ populations.
These findings identify lithocholic acid as a key gut microbiota-derived metabolite mediating protection against PEDV infection in piglets. The results point to Lactobacillus reuteri and Lactobacillus amylovorus as candidate probiotic strains that could be harnessed to boost disease resistance through bile acid metabolism. This work suggests that modulating the gut microbiota and its bile acid metabolites, particularly LCA, and their effects on intestinal T-cell populations, could be a strategy for improving resistance to enteric viral pathogens in livestock.
This study used species-level shotgun metagenomic sequencing to characterize the gut microbiota of men who have sex with men (MSM). It investigated why the MSM gut microbiome, previously shown to differ from that of non-MSM, so often resembles the microbial communities seen in non-Westernized populations. The researchers also used questionnaire data and machine learning to link specific sexual practices to variation in microbiota composition among MSM.
The study population was men who have sex with men of Western origin, compared against patterns typical of non-Westernized populations. The abstract does not give an exact sample size, but participants contributed both stool samples for shotgun metagenomics and questionnaire responses on sexual practices. This design allowed the authors to relate individual behavioral data to individual gut microbiome profiles within the MSM cohort.
Many MSM with Western origin had gut microbiomes resembling those of non-Westernized populations rather than typical Western gut profiles. These microbiomes were frequently dominated by Prevotellaceae family members, including co-colonization by species from the Segatella copri complex alongside unknown Prevotellaceae members. Questionnaire analysis and machine learning further identified specific sexual practices as microbial features associated with this altered, Prevotellaceae-rich composition.
The findings show that sexual activity itself can be a driver of major gut microbiome alterations, independent of the diet and lifestyle factors usually invoked to explain Westernized versus non-Westernized microbiota differences. Because MSM gut microbiomes can resemble non-Westernized profiles, sexual practice becomes an important variable that population-based microbiota studies may need to account for. This has implications for how researchers select and interpret control or reference populations in microbiome research and for disentangling behavioral from dietary or geographic influences on gut microbial composition.
This study examined the relationship between the gut microbiome and the host genome and transcriptome in colorectal cancer (CRC). Researchers profiled the fecal microbiome structure alongside genomic and transcriptomic data from matched tumor and normal mucosa tissue. Exome sequencing was used to identify somatic mutations, and gene expression patterns were annotated and clustered against microbial abundance data. Immune and stromal cell composition was also estimated from the transcriptomic profiles.
The cohort consisted of 41 patients with colorectal cancer. For each patient, matched tumor tissue and normal mucosa tissue were analyzed alongside fecal microbiome samples. The abstract does not provide further demographic details such as age, sex, or geographic origin of the participants.
The researchers identified 22 gut microbial species significantly associated with CRC and estimated relative abundance across functional (KEGG) pathway categories. Four significantly mutated genes, TP53, APC, KRAS, and SMAD4, were linked to specific cancer-associated microbes. Fusobacterium nucleatum in particular showed a positive correlation with multiple host metabolic pathways, tying a specific pathogen to altered tumor metabolism. The abstract text is truncated before further results are described.
The findings support a functional link between specific gut bacteria, such as Fusobacterium nucleatum, and the somatic mutation landscape and metabolic activity of colorectal tumors. This multi-omic approach suggests that microbial taxa may interact with host driver mutations like TP53, APC, KRAS, and SMAD4 rather than merely coexisting with the tumor. Such associations could inform future work on microbiome-informed risk stratification or targets in CRC, though the abstract does not describe therapeutic testing or outcomes.
This study tested whether Parkinson's disease alters the periodontitis-associated oral microbiome. Researchers collected unstimulated saliva samples and stool samples and profiled microbial communities using next-generation sequencing of the 16S ribosomal RNA gene (V1-V3 regions). Clinical, periodontal, and neurological parameters were recorded, including the severity of Parkinson's disease motor dysfunction.
Three groups were enrolled: patients with periodontitis and Parkinson's disease (PA+P), patients with periodontitis but without Parkinson's disease (P), and systemically and periodontally healthy individuals used as controls (HC). The abstract does not give exact group sizes. The PA+P group had mild to moderate motor dysfunction, and plaque scores were comparable between the PA+P and P groups, indicating similarly effective oral hygiene.
Beta diversity in saliva differed significantly between HC and PA+P, between HC and P, and between P and PA+P groups, showing that both periodontitis and the presence of Parkinson's disease reshape the oral microbial community. Saliva and fecal microbial profiles were distinct from each other. Mycoplasma faucium, Tannerella forsythia, Parvimonas micra, and Saccharibacteria (TM7) were increased in the P group, while Prevotella pallens, Prevotella melaninogenica, and Neisseria multispecies were more abundant in the PA+P group. In fecal samples from the P group, Ruthenibacterium lactatiformans, Dialister succinatiphilus, Butyrivibrio crossotus, and Alloprevotella tannerae were detected.
The findings support the hypothesis that Parkinson's disease is associated with a distinct periodontitis-related oral microbial signature, separate from periodontitis alone. Because oral and gut microbial profiles diverged between groups despite similar oral hygiene, the results suggest disease-associated shifts rather than simple hygiene differences drive these community changes. This points to the oral-gut microbiome axis as a potential area for further investigation in Parkinson's disease and periodontitis.
This study examined the early development of the human gut microbiome by comparing infants to their mothers and grandmothers within the same family lines. Researchers used a multi-omics approach combining metagenomics (16S rRNA gene and shotgun sequencing) with two independent metabolomics platforms, gas chromatography and capillary electrophoresis coupled to mass spectrometry. The goal was to characterize differences in microbial populations, function, and metabolite output across three generations.
Fecal samples were collected from 200 individuals spanning three generations of the same families. This included infants aged 0 to 12 months (55% female, 45% male) along with their respective mothers and grandmothers. The design allowed direct comparison of gut microbiota and metabolome across a shared generational line.
Infants showed markedly less diverse gut microbiota than their mothers and grandmothers, along with distinct microbial population and functional profiles. The infant metabolome also differed substantially from the adults, particularly in short- and branched-chain fatty acids. These metabolite shifts were linked to corresponding differences in bacterial populations between infants and elders.
The findings offer biochemical insight into how the gut microbiome is shaped during infancy within a single family lineage. Because dysregulation of the gut microbiome at this early stage may contribute to disease later in life, understanding these generational differences could inform strategies to support healthy microbiome development in infants. The authors suggest this multi-omics approach could ultimately help improve childhood health outcomes.
This study examined whether the gut microbiota plays a causal role in inflammatory depression, a treatment-resistant subtype of depression linked to low-grade inflammation. Researchers analyzed gut microbiota composition, plasma inflammatory factors and short-chain fatty acids (SCFAs), and intestinal mucosal inflammation and permeability markers in patients with inflammatory depression. They then used fecal microbiota transplantation (FMT) and probiotic supplementation in animal experiments to test whether the microbiota could directly cause disease features. The overall aim was to move beyond association and establish a causal link between gut microbes and inflammatory depression.
The human portion of the study involved patients with inflammatory depression enrolled in an observational trial registered as ChiCTR1900025175. The abstract does not give an exact sample size for this cohort. The causal experiments were conducted in mice, which received fecal microbiota transplants from the human inflammatory depression patients or were given Clostridium butyricum supplementation within a mouse model of inflammatory depression.
Patients with inflammatory depression had gut microbiota showing higher Bacteroides and lower Clostridium, along with an increase in SCFA-producing species that displayed abnormal butanoate metabolism. After FMT from these patients, recipient mice developed increased peripheral and central inflammatory factors, greater intestinal mucosal permeability, and depressive and anxiety-like behaviors. Administration of Clostridium butyricum normalized the gut microbiota, decreased inflammatory factors, and produced antidepressant-like effects in the mouse model. These findings demonstrate a direct causal contribution of the gut microbiota to inflammatory depression, mediated through altered butanoate metabolism, systemic inflammation, and gut barrier permeability.
The findings support the gut microbiota as a causal driver, not merely a correlate, of inflammatory depression through disrupted butanoate metabolism and increased intestinal permeability. This suggests that restoring specific commensal populations such as Clostridium butyricum could offer a targeted therapeutic strategy for this treatment-resistant depression subtype. The results position gut barrier integrity and SCFA metabolism as potential biomarkers or intervention targets in psychiatric care. Overall, this strengthens the rationale for microbiota-based approaches, including targeted probiotic or FMT strategies, in inflammatory subtypes of depression.
This study examined gut microbial features associated with Parkinson's disease (PD) by meta-analyzing shotgun metagenomic sequencing data across six independent datasets from different countries. The researchers also established GC-MS and LC-MS/MS assays to directly quantify fecal short-chain fatty acids (SCFAs) and fecal polyamines. They analyzed taxonomic composition, functional gene pathways, and carbohydrate-active enzymes (CAZymes) in relation to PD status, adjusting for confounding factors.
The core dataset consisted of 94 PD patients and 73 controls whose fecal samples were shotgun sequenced in Japan. This Japanese cohort was combined with five previously reported datasets from the USA, Germany, China (two separate cohorts), and Taiwan. In total, the meta-analysis spanned six countries, giving the study an international, multi-cohort scope rather than a single-population sample.
Across all six datasets, alpha-diversity was consistently increased in PD. Taxonomic analysis showed Akkermansia muciniphila was increased in PD, while Roseburia intestinalis and Faecalibacterium prausnitzii, both associated with anti-inflammatory, butyrate-related commensal activity, were decreased. Genes for riboflavin and biotin biosynthesis and five of six CAZyme categories were markedly decreased in PD, and fecal SCFAs and polyamines were significantly reduced, with riboflavin/biotin gene abundance positively correlated with these metabolite levels.
The convergent, cross-country decrease in Faecalibacterium prausnitzii, Roseburia intestinalis, SCFAs, and polyamines suggests a reproducible loss of beneficial, anti-inflammatory commensal function in PD gut microbiota. Because the specific bacteria driving reduced riboflavin biosynthesis differed between Japan/USA/Germany and China1/China2/Taiwan, the findings imply that shared functional deficits in PD can arise from different taxonomic routes depending on population. This points toward B-vitamin biosynthesis and short-chain fatty acid/polyamine metabolism as potential functional biomarkers or intervention targets for PD that generalize better across populations than single-taxon signatures.
This study examined how gut microbiota composition differs in children with diarrhea versus children with constipation, compared to healthy children. The researchers used 16S rRNA sequencing on stool samples to profile bacterial communities and looked for microbial diversity changes and specific taxa shifts. They also ran pathway analysis to identify functional mechanisms that might link the two opposite digestive conditions through a shared microbial driver.
The study included 618 Chinese children aged 0 to 3 years, drawn from a cross-sectional case-control design. Of these, 66 children had diarrhea, 138 had constipation, and 414 were healthy controls. Stool samples were collected from each child for gut microbiota analysis.
Children with diarrhea showed significantly lower gut microbial diversity than healthy controls, while children with constipation showed significantly higher diversity (p < 0.05). Ruminococcus was identified as a key differentiator: it increased in constipation (p = 0.03) and decreased in diarrhea (p < 0.01) relative to healthy children. Pathway analysis linked Ruminococcus to five shared pathways (membrane transport, nervous system, energy metabolism, signal transduction, and endocrine system), suggesting one underlying regulatory mechanism connects both conditions.
The findings point to Ruminococcus as a core microorganism whose imbalance may disrupt gut steady-state in opposite directions, contributing to either diarrhea or constipation in young children. Because the same genus and overlapping metabolic pathways appear to regulate both conditions, it may serve as a useful reference point for diagnosis. The authors suggest this shared mechanism could inform future treatment approaches that target gut microbial balance rather than treating diarrhea and constipation as unrelated conditions.
This study examined the relationship among urinary phthalate (PAE) metabolites, gut microbiota composition, and gut metabolome profiles in dementia with Lewy bodies (DLB). Researchers measured urinary phthalate metabolite levels using liquid chromatography and profiled gut microbiota and metabolites using high-throughput sequencing and liquid chromatography-mass spectrometry. They then used a fecal microbiota transplantation (FMT) experiment in alpha-synuclein transgenic DLB/Parkinson's disease mice to test whether phthalate-associated gut dysbiosis could contribute to worsening cognitive dysfunction.
The human portion of the study included 43 patients with dementia with Lewy bodies and 45 normal control subjects, whose urine and fecal samples were analyzed. The animal portion used alpha-synuclein transgenic mice modeling DLB/Parkinson's disease, which received fecal microbiota transplants to test causal effects of gut dysbiosis on cognition.
DLB patients had higher levels of several phthalate metabolites, including DEHP metabolites MEOHP, MEHHP, and MEHP, as well as MMP and MnBP, but lower levels of MBP and MBzP compared to controls. Gut microbiota composition also differed between groups, with a significantly higher abundance of Ruminococcus gnavus and a lower abundance of Prevotella in DLB patients. The FMT experiment was performed to verify whether phthalate-associated gut dysbiosis contributes to aggravating cognitive dysfunction in the DLB/PD mouse model.
These findings suggest that environmental phthalate exposure is associated with distinct patterns of urinary metabolites and gut dysbiosis in people with dementia with Lewy bodies. The use of an FMT model linking phthalate-associated dysbiosis to cognitive dysfunction raises the possibility that environmental chemical exposures could influence neurodegenerative disease risk through gut microbiota changes. This points to gut microbiota and metabolome profiling as a potential avenue for understanding environmental contributions to DLB and warrants further mechanistic investigation.
This study examined the gut microbiome's association with type 2 diabetes (T2D) by analyzing shotgun metagenomic sequencing data. Researchers looked beyond species-level associations to strain-level and phylogenetic diversity within species, aiming to identify specific microbial features and functional pathways linked to T2D. The analysis also explored community-level functional changes, such as perturbations in glucose metabolism, and mechanisms like horizontal gene transfer that could explain strain-specific effects on metabolic risk.
The study drew on 8,117 shotgun metagenomes pooled from 10 cohorts spanning the United States, Europe, Israel, and China. These cohorts included individuals with type 2 diabetes, prediabetes, and normoglycemic (non-diabetic) status. The abstract does not provide individual-level demographic details, but the analysis represents a large, multi-national, cross-cohort metagenomic dataset.
Dysbiosis in 19 phylogenetically diverse species was associated with T2D at a false discovery rate below 0.10, including enrichment of Clostridium bolteae and depletion of Butyrivibrio crossotus. These microorganisms contributed to community-level functional changes, such as perturbations in glucose metabolism, that may underlie T2D pathogenesis. The study further identified within-species phylogenetic diversity across 27 species, such as Eubacterium rectale, that explained inter-individual differences in T2D risk, with some effects attributable to strain-specific gene carriage involved in horizontal gene transfer and other novel biological processes.
By resolving microbial associations with T2D down to the strain level, this work helps explain why prior species-level findings have been inconsistent across studies. Identifying strain-specific gene carriage and functional pathways, including those affecting glucose metabolism, offers a clearer mechanistic basis for how gut microbes may contribute to T2D pathogenesis. This strain-resolved approach could inform future efforts to develop microbiome-based biomarkers or targeted interventions for metabolic disease risk.
This study examined how environmental, socioeconomic, and health factors relate to gut microbiome composition at both the species and strain level. Researchers used deeply sequenced metagenomic data to identify associations between bacterial species and a range of host phenotypes and situational factors. They also performed a meta-analysis of species-level profiles across multiple datasets to look for consistent patterns, such as links to body mass index.
The study drew on a community-based cohort of 1,871 people living in 19 isolated villages in the Mesoamerican highlands of western Honduras. This is a non-industrialized, geographically isolated population, a setting the authors note remains uncommon in deep gut microbiome sequencing studies. Additional comparisons were made using species-level profiles from other, unspecified datasets as part of a meta-analysis.
Socioeconomic factors accounted for 51.44% of all associations found between the gut microbiome and human phenotypes, making them the dominant category of influence. Meta-analysis across datasets identified several bacterial species associated with body mass index, consistent with prior research. Incorporating strain-level phylogenetic information changed the overall picture of host-microbiome relationships, especially for factors like household wealth, where wealthier individuals were found to harbor different strains of Eubacterium rectale than less wealthy individuals.
The findings suggest that socioeconomic circumstances are a major driver of gut microbiome variation, potentially more so than many other individual health factors. The demonstration that strain-level differences (not just species presence) track with wealth indicates that species-level analysis alone can miss biologically meaningful variation. The authors conclude that gut microbiome surveillance in such populations could help illuminate broader patterns relevant to both individual and public health.
This study used whole-genome shotgun sequencing and gas chromatography/mass spectrometry to profile gut microbial and metabolic signatures across seven different malignancies. The researchers compared taxonomic and metabolomic configurations in cancer patients against sex- and age-matched healthy controls. The goal was to identify both common and cancer-type-specific gut microbiome and metabolite alterations.
The study included patients with colorectal cancer (40), stomach cancer (45), breast cancer (71), lung cancer (34), melanoma (50), lymphoid neoplasms (60), and acute myeloid leukemia (40). Each cancer group was compared against its own sex- and age-matched healthy control group. In total the analysis spanned 300 cancer patients across seven malignancy types plus their matched controls.
Beta-diversity differed between every cancer group and its healthy controls, while alpha-diversity differed only for the lymphoid neoplasm and acute myeloid leukemia groups. Of 203 unique species identified, 179 were under-represented and 24 were over-represented in cancer patients relative to controls. Faecalibacillus intestinalis was under-represented across all seven cancer groups, and Anaerostipes hadrus was under-represented in all groups except stomach cancer, with a marked reduction in the gut microbiome cancer index in every group except acute myeloid leukemia. Among the short-chain fatty acids and amino acids tested, formic acid concentration was significantly altered.
The consistent depletion of Faecalibacillus intestinalis and altered formic acid levels across seven distinct cancer types suggest these may represent shared, cross-cancer markers of gut dysbiosis rather than disease-specific findings. This points toward a common gut microbial and metabolic signature that could inform future pan-cancer diagnostic or monitoring approaches. Because the pattern held despite differences in cancer biology and location, it strengthens the case for a generalizable link between gut dysbiosis and malignancy.
This study used metagenomic sequencing to characterize taxonomic and functional changes in the gut microbiome of people with Parkinson's disease (PD). The researchers examined how these microbial changes relate to bacterial metabolites and to clinical disease progression. Motor and non-motor symptoms were tracked over up to five yearly study visits using the MDS-UPDRS scale and levodopa equivalent dose. Stool samples collected at baseline were used for the metagenomic analysis.
The study population consisted of 176 individuals with Parkinson's disease and 100 control participants who provided baseline stool samples for metagenomic sequencing. Disease progression was followed longitudinally across as many as five yearly visits using standardized clinical rating scales. The abstract does not specify age, sex distribution, or geographic recruitment site for these participants.
PD-derived stool samples showed reduced intermicrobial connectivity and seven species that were differentially abundant compared to controls. A range of bacterial functions also differed between groups, including depletion of carbohydrate degradation pathways and enrichment of ribosomal genes. Notably, Faecalibacterium prausnitzii-specific reads contributed to more than half of all the differentially abundant functional terms identified. A subset of these disease-associated functional terms correlated with faster progression on MDS-UPDRS part IV and could distinguish slow from fast progressors with moderate accuracy.
The findings reinforce that Parkinson's disease involves large-scale, functional disruption of the gut microbiome, not just shifts in a handful of taxa. The outsized contribution of Faecalibacterium prausnitzii, a key butyrate-producing, anti-inflammatory commensal, to the disrupted functional signature suggests its depletion may be mechanistically important rather than incidental. The link between specific functional terms and faster motor progression raises the possibility that gut microbial function could serve as a biomarker of disease trajectory. These results support further investigation into F. prausnitzii and related carbohydrate-degradation pathways as targets for monitoring or intervention in PD.
This study examined whether fecal gut microbiota composition differs between children with acute versus prolonged or persistent diarrhea and non-diarrheal controls in Ethiopia. The researchers used a case-control design to determine if these compositional differences relate to diarrheal etiology and duration. They compared bacterial diversity and the abundance of specific taxa across the three groups.
The study included Ethiopian children under five years of age, with 554 cases of acute diarrhea (less than 7 days) and 95 cases of prolonged or persistent diarrhea (7 days or more, including 14 days or more). These cases were compared against 663 frequency-matched non-diarrheal controls. All groups were drawn from the same pediatric population in a low- and middle-income country setting.
Diarrhea cases showed lower bacterial diversity and were enriched in Escherichia spp., Campylobacter spp., and Streptococcus spp. compared to controls. Cases were also depleted in beneficial gut commensals including Prevotella copri, Faecalibacterium prausnitzii, and Dialister succinatiphilus. This depletion of commensals was most pronounced in the prolonged and persistent diarrhea cases, suggesting a link between commensal loss and longer diarrheal duration.
The findings suggest that prolonged and persistent diarrhea in young children is accompanied by a progressive loss of beneficial gut commensals such as Faecalibacterium prausnitzii, not just acute dysbiosis. This points to microbiota-directed food supplements as a potential treatment strategy to re-establish depleted commensals. The results support targeting gut microbiota restoration as a way to shorten or prevent prolonged diarrheal episodes in vulnerable children.
This study investigated the relationship between periodontitis and the oral-gut axis in first-trimester pregnant women using integrative microbiome and metabolome profiling. Researchers combined 16S rRNA sequencing of subgingival plaque, saliva, and stool with untargeted metabolomics of serum and other sample types, alongside clinical traits. The goal was to characterize how oral dysbiosis linked to periodontitis translates into distal gut microbial and metabolic changes during early pregnancy.
The cohort consisted of 54 Chinese pregnant women sampled at the first trimester. Of these, 31 women had maternal periodontitis (the Perio group) and 23 women served as Non-Perio controls. Subgingival plaque, saliva, serum, and stool samples were collected from each participant for multi-omics analysis.
The study identified a novel bacterial distinguisher, Coprococcus, in the feces of women with periodontitis, and this genus was associated with subgingival periodontopathogens. Notably, Coprococcus behaved differently from other fecal genera within the Lachnospiraceae family. The ratio of fecal Coprococcus to Lachnoclostridium was able to discriminate between the Perio and Non-Perio groups, indicating a measurable gut-level signature tied to oral disease status.
The findings support the existence of a functional oral-gut axis through which periodontitis in early pregnancy is reflected in distinct gut microbial and metabolic alterations. Identifying the fecal Coprococcus to Lachnoclostridium ratio as a discriminating feature suggests potential translational value as a biomarker linking oral and gut health in pregnant women. This integrative multi-omics approach may help clarify how periodontitis contributes to adverse pregnancy outcomes via systemic, gut-mediated pathways.
This study used deep shotgun metagenomic sequencing to characterize the taxonomic and functional composition of the gut microbiome in older adults from Singapore. The researchers examined how gut microbial communities and their metabolic capabilities relate to aging phenotypes. They performed joint species-level analysis together with other Asian cohorts to identify age-associated shifts in microbial composition and function. The work also linked microbiome features to clinical markers of inflammation, cardiometabolic health, and liver health.
The cohort consisted of 234 community-living octogenarians in Singapore who were described as well-phenotyped. Their gut microbiomes were compared jointly against data from other Asian cohorts to identify consistent age-associated species shifts. The abstract does not specify sex distribution, exact age range beyond octogenarian status, or additional demographic details.
Aging was associated with reduced microbial richness and enrichment of specific Alistipes and Bacteroides species, including Alistipes shahii and Bacteroides xylanisolvens. Functional analysis showed a corresponding expansion of metabolic potential toward pathways synthesizing and utilizing amino-acid precursors, in contrast to the dominant butyrate-producing guilds such as Faecalibacterium prausnitzii and Roseburia inulinivorans that generate butyrate from pyruvate. The study also identified more than ten robust microbial associations with inflammation and with cardiometabolic and liver health markers, including a potential probiotic species, Parabacteroides goldsteinii.
The findings suggest that healthy aging in this population is accompanied by a measurable shift away from butyrate-producing commensals like Faecalibacterium prausnitzii toward microbes with alternate amino-acid metabolic capacity. This shift, combined with the identified links to inflammation and cardiometabolic and liver health markers, points to specific microbial species and pathways that could serve as biomarkers or targets for supporting healthy aging. The results also highlight potential probiotic candidates, such as Parabacteroides goldsteinii, for further investigation in aging-related interventions.
This study examined how gut microbiota and their metabolites change during acute pancreatitis (AP), an inflammatory disease of the pancreas that currently lacks effective therapy. The researchers used metagenomic sequencing to profile gut bacterial communities and metabolomic sequencing to profile metabolites, then applied correlation analysis to clarify how the two systems interact. KEGG pathway analysis was used to connect differential bacteria and metabolites to specific metabolic functions.
The study was conducted using three distinct AP mouse models rather than human subjects. Each model was constructed specifically to allow comparison of gut microbiota and metabolite profiles across different disease conditions. No human cohort, sample size, or patient population is described in the abstract.
Each AP mouse model exhibited a unique flora and metabolite profile, with differential bacteria and metabolite-enriched pathways correlating with lipid metabolism and amino acid metabolism. Two bacterial species, Burkholderiales bacterium YL45 and Bifidobacterium pseudolongum, emerged as core differential species across the models. Eleven differential metabolites were also identified as appearing to exert effects during the course of AP.
By mapping the crosstalk between gut microbiota and their derived metabolites, the study suggests specific bacterial species and metabolites, especially those tied to lipid and amino acid metabolism, may play mechanistic roles in AP development. This integrated metagenomic-metabolomic approach could inform new diagnostic markers and treatment strategies for AP. Further exploration of this microbiota-metabolite relationship is proposed as a route to novel clinical insights.
This study tested whether a healthy low-carbohydrate diet (HLCD) and time-restricted eating (TRE), alone or combined, affect body weight and the gut microbiome beyond what caloric restriction alone produces. It used a 12-week two-by-two factorial randomized controlled feeding trial with a 28-week follow-up period. The design let researchers isolate the added effects of carbohydrate restriction and eating-window timing on top of isocaloric-restricted feeding.
The trial enrolled 96 participants with overweight or obesity. Participants were assigned across the two-by-two factorial design to receive isocaloric-restricted feeding with or without HLCD and with or without TRE. The abstract does not give further demographic detail such as age or sex distribution.
Isocaloric-restricted feeding produced significant weight loss ranging from 2.57 to 4.11 kg across groups, and both HLCD and TRE produced additional reductions in body mass index beyond caloric restriction alone. HLCD led to additional fat mass loss, while TRE led to more lean mass loss, showing the two strategies affect body composition differently. HLCD also decreased fecal branched-chain amino acids, and TRE tended to increase the abundance of probiotic species that synthesize short-chain fatty acids. The fat-mass-reducing effect of HLCD persisted through the post-intervention follow-up period.
The findings suggest that dietary carbohydrate composition and meal timing each add measurable value to weight management beyond simple calorie counting. HLCD and TRE produce distinct effects on body composition (fat versus lean mass) and distinct, profound alterations to the gut microbiome and metabolome. The persistence of HLCD's fat-loss effect after the intervention ended points to potential durability of low-carbohydrate approaches. These results support tailoring weight-management strategies to specific metabolic and microbiome-related goals rather than treating all caloric-restriction approaches as equivalent.
This study examined whether the composition of the oral microbiome is linked to autism spectrum disorder (ASD) and neurodevelopmental outcomes. Researchers used large-scale metagenomic sequencing of saliva samples to test whether microbial community differences could distinguish ASD subjects from neurotypical individuals. They also examined whether microbiome composition correlated with cognitive impairment (measured by IQ) and whether microbial strain sharing between children and parents differed by diagnosis and IQ status. A functional enrichment analysis was performed to identify metabolic pathways that might underlie these differences.
The study drew on more than 7000 whole-genome sequenced salivary samples from 2025 US families that included children diagnosed with ASD. Each family contributed samples from both an ASD-diagnosed child and a neurotypical sibling (NT), allowing within-family comparisons. This is a large, family-based cross-sectional cohort rather than a small clinical sample.
Oral microbiome composition discriminated ASD children from their neurotypical siblings with an AUC of 0.66, based on 108 differentiating species (q < 0.005). The relative abundance of these species was highly correlated with Full-Scale IQ, and ASD children with IQ below 70 showed significantly lower microbiome strain sharing with their parents than neurotypical children (p < 10-6). Functional enrichment analysis pointed to enzymes involved in serotonin, GABA, and dopamine degradation pathways as contributors to the distinct microbial community differences between ASD and NT samples. Restrictive eating patterns and oral hygiene proxies had only minor effects on these microbiome differences.
The findings support oral microbiome composition, including neurotransmitter-degradation pathway activity, as a candidate biological marker associated with ASD and its severity as measured by IQ. The reduced strain sharing with parents in lower-IQ ASD children suggests altered microbial transmission or colonization dynamics may track with symptom severity. However, the authors note that causal relationships could not be established, and residual lifestyle differences between groups may still explain part of the association, so these results should be viewed as correlational markers rather than proof of a mechanistic link.
This randomised, parallel, double-blind, placebo-controlled pilot study examined the effect of a heat-treated postbiotic, Bifidobacterium longum CECT 7347 (HT-ES1), in healthy adults with mild to moderate digestive symptoms. Participants received either HT-ES1 or a matching placebo daily for 8 weeks, with an additional follow-up assessment at week 10. The study tracked gastrointestinal symptom scores, gut microbiota composition via 16S rRNA sequencing, biochemical markers, anthropometric parameters, and adverse events.
A total of 60 healthy adults with mild to moderate digestive symptoms were recruited and randomised to receive either the HT-ES1 postbiotic or an identical placebo. The abstract does not specify further demographic details such as age range or sex distribution. The population was drawn from generally healthy individuals rather than a diagnosed patient cohort.
Gastrointestinal symptoms changed minimally between the two groups, but the HT-ES1 group showed a significant decrease in total and non-HDL cholesterol compared to placebo. The intervention group also had a significant increase in the abundance of Faecalibacterium and Anaerobutyricum, both of which correlated positively with butyrate concentrations. Faecal calprotectin rose significantly over time in the placebo group but stayed stable in the HT-ES1 group.
The findings suggest that this heat-treated Bifidobacterium longum postbiotic may support cardiometabolic and intestinal health in healthy adults, even without producing marked changes in digestive symptoms. The rise in butyrate-associated, anti-inflammatory commensals such as Faecalibacterium alongside stable calprotectin levels points to a possible gut-barrier or anti-inflammatory benefit. These results support further, larger trials to confirm postbiotic effects on cholesterol and microbiota composition.
This study used metagenomic sequencing to examine how chemotherapy affects gut microbiota composition and antibiotic resistance genes (ARGs) in patients with acute leukemia (AL). The researchers compared pre- and post-chemotherapy stool samples to track shifts in microbial richness, taxa abundance, and resistance gene carriage. They also examined co-occurrence networks linking ARGs to specific microbial species and to antibiotic dosage, and correlated gut microbiota changes with blood inflammatory markers.
The subjects were patients with acute leukemia who provided stool samples both before and after chemotherapy treatment. The abstract does not give an exact number of patients or demographic details, so the cohort size cannot be stated precisely. What can be said is that this was a clinical patient cohort studied longitudinally around a chemotherapy course, using paired pre- and post-treatment samples rather than a single cross-sectional dataset.
Post-chemotherapy stool samples showed decreased alpha diversity and increased dispersion in microbial community structure compared to pre-chemotherapy samples. Enterococcus, Klebsiella, and Escherichia coli were identified as the bacteria most prevalent in carrying antibiotic resistance genes. Correlation analysis linked specific microbial species to inflammatory biomarkers, including C-reactive protein (CRP) and adenosine deaminase (ADA), and network analysis revealed 179 nodes and 206 edges connecting co-occurring ARGs with microbial species, plus 50 nodes and 50 edges linking ARGs to antibiotic dosages. Certain antibiotics, notably cephamycin and sulfonamide, were associated with the emergence of multidrug-resistant Klebsiella colonization.
The findings suggest that chemotherapy in acute leukemia patients drives measurable disruption of the gut microbiome alongside expansion of antibiotic-resistant, potentially pathogenic bacteria such as Klebsiella. The links between specific antibiotics and multidrug-resistant colonization point to antibiotic choice and dosage as modifiable factors in resistance risk during leukemia treatment. The correlations between microbiota shifts and inflammatory markers like CRP and ADA suggest gut microbial changes may be intertwined with the inflammatory status of these immunocompromised patients, though the abstract does not establish causation.
This study investigated the neonatal gut bacterial and viral microbiome in infants exposed to HIV but who remained uninfected, and examined how this exposure relates to inflammatory biomarkers in plasma. The researchers also tested whether HIV exposure alters antibody-microbiota binding in the neonatal gut. Finally, they assessed whether antibodies present in breast milk affect the growth of commensal gut bacteria.
The study compared neonates exposed to HIV but uninfected (nHEU) with unexposed, uninfected neonates (nHU). Breast milk from mothers living with HIV was also analyzed and compared for its antibody function. The abstract does not give specific sample sizes, so the exact cohort size cannot be stated.
Neonates exposed to HIV but uninfected showed an altered gut bacteriome and a milder change in the enteric DNA virome compared to unexposed neonates. HIV exposure also differentially affected IgA binding to gut microbiota. The relative abundance of Blautia spp., in both whole stool and IgA-bound microbiota, was positively associated with plasma C-reactive protein levels. Breast milk IgA from mothers living with HIV showed a significantly reduced ability to inhibit the growth of Blautia coccoides, and this reduced inhibitory capacity was associated with inflammation in the exposed neonates.
The findings suggest that elevated inflammation in HIV-exposed but uninfected neonates may stem in part from a weakened capacity of maternal breast milk IgA to control specific commensal bacteria such as Blautia coccoides. This points to a potential antibody-mediated mechanism linking maternal HIV status, infant gut microbiota composition, and systemic inflammation in the infant. Understanding this pathway could inform strategies to support healthy immune development in this vulnerable population.
This study examined whether exercise intensity changes gut microbiome composition and function in low active people with type 2 diabetes. It compared two 8-week supervised exercise programs: combined aerobic and resistance moderate intensity continuous training (C-MICT) versus combined aerobic and resistance high-intensity interval training (C-HIIT). Faecal samples were collected before and after the intervention and analyzed with metagenome shotgun sequencing to assess microbial taxa, metabolic pathways, and short-chain fatty acids.
The participants were low active adults with type 2 diabetes enrolled in a sub-study of the Exercise for Type 2 Diabetes Study, a single centre, prospective, randomised controlled trial. A total of 12 participants completed the 8-week intervention, randomised to either the C-MICT or C-HIIT group. This is a small clinical cohort rather than a large population sample.
Post-exercise alpha-diversity differed between the two intensity groups, as did the relative abundance of specific taxa (p < .05). Lower exercise intensity (C-MICT) was associated with higher post-exercise relative abundance of Bifidobacterium, Akkermansia muciniphila, and the butyrate-producers Lachnospira eligens, Enterococcus spp., and Clostridium Cluster IV. The abstract also indicates that other butyrate-producers, from the orders Eryspelothrichales and Oscillospirales, along with a methane producer, showed a different pattern, though the specific direction of that difference is cut off in the provided text.
The findings suggest that exercise intensity, not just exercise participation, can shape gut microbiome composition in people with type 2 diabetes. Because lower intensity training was linked to higher levels of several butyrate-producing commensals, exercise prescription choices may carry distinct implications for gut microbial and metabolic health in this population. Larger studies would be needed to confirm these intensity-specific effects and their functional consequences.
This study examined the fecal microbiota of Korean patients with inflammatory bowel disease (IBD) to characterize how bacterial composition relates to clinical phenotypes. Researchers compared ulcerative colitis (UC), Crohn's disease (CD), and healthy controls using 16S sequencing of fecal samples. They analyzed alpha-diversity and overall community composition using the EzBioCloud database and 16S microbiome pipeline. The goal was to identify taxonomic biomarkers useful for diagnosis and prognosis in IBD.
The study included 70 patients with ulcerative colitis, 39 patients with Crohn's disease, and 100 healthy control individuals, all from a Korean population. Fecal samples were collected from each group and amplified via polymerase chain reaction before sequencing on the Illumina MiSeq platform. Within the UC group, patients were further stratified by disease severity and disease extent for additional analysis.
Alpha-diversity of fecal bacteria was significantly lower in both UC and CD patients compared to healthy controls. Bacterial community composition, measured via Bray-Curtis dissimilarities, differed significantly between UC, CD, and healthy controls, and also differed between UC and CD themselves. Within UC, diversity decreased further as disease severity and extent increased, with community composition also varying by disease extent. The researchers identified 9 biomarkers of UC severity, 6 biomarkers of disease extent, 5 biomarkers of active disease, and additional biomarkers described in the abstract as being identified for disease course or prognosis.
These findings support the fecal microbiota as a potential tool for distinguishing UC and CD from healthy individuals and from each other in a Korean population. The identification of taxa linked to severity, extent, and disease activity suggests fecal bacterial profiling could aid in staging and monitoring IBD. This points toward a role for microbiome-based biomarkers in personalizing diagnostic and prognostic assessment for IBD patients, pending further validation in additional cohorts.
This study profiled the gut microbiome of breast cancer patients from the Midwestern region of the United States using 16S ribosomal RNA sequencing. Researchers compared bacterial composition between breast cancer patients and healthy controls, examining both alpha diversity (within-sample richness) and beta diversity (between-group differences). They also performed a gene pathway analysis to assess the functional capabilities of the gut bacterial community, focusing on short-chain fatty acid (SCFA) production.
The study compared breast cancer (BC) patients from the Midwestern United States to healthy controls (HC). The abstract does not give exact sample sizes, ages, or other demographic details of the cohort. What is clear is that this was a region-specific comparison, chosen because geographic location can influence gut microbiome composition.
Alpha diversity did not differ significantly between breast cancer patients and healthy controls, but beta diversity showed distinct clustering between the two groups at the species and genus level. A Wilcoxon Rank Sum test identified modulation of several gut bacteria in breast cancer patients, including reduced abundance of beneficial organisms such as Faecalibacterium prausnitzii. Machine learning analysis confirmed the significance of several of these modulated bacteria, and functional pathway analysis showed decreased abundance of SCFA (propionate) production pathways in breast cancer patients compared to healthy controls.
The findings point to gut dysbiosis in breast cancer patients characterized by depletion of SCFA-producing gut bacteria, including Faecalibacterium prausnitzii, suggesting a possible role for these organisms in breast cancer pathobiology. Because SCFAs such as propionate are linked to anti-inflammatory and metabolic effects, their reduced production may be mechanistically relevant to disease. The study underscores the importance of examining region-specific microbiome signatures rather than assuming universal patterns across populations.
This study investigated the microbiome associated with ovarian cancer (OC) and its potential role in detection, disease progression, and prognosis. Researchers examined microbial taxa across multiple body sites in OC patients compared with a benign cohort. The aim was to identify microbial indicators that could aid early detection, track disease stage and grade, and predict treatment response.
The abstract does not give a specific cohort size or demographic description. It describes an OC patient cohort compared against a benign cohort, with sampling across several body sites; stool and omentum were sampled in the OC cohort but not in the benign cohort. Beyond this, the population can only be described in general terms as ovarian cancer patients versus patients with benign gynecological conditions.
The researchers identified a distinct OC microbiome with general enrichment of several microbial taxa, including Dialister, Corynebacterium, Prevotella, and Peptoniphilus, across body sites in the OC cohort. These same taxa were depleted in advanced-stage and high-grade OC patients compared with early-stage and low-grade patients, suggesting decreased accumulation as disease advances. The mainly pathogenic taxa were also more abundant in OC patients with adverse treatment outcomes compared to those without treatment-related events.
The enrichment and depletion patterns of these taxa suggest they could serve as potential indicators for early detection of ovarian cancer. Their accumulation in patients with adverse treatment outcomes suggests they could also help predict how patients will respond to treatment. Together these findings point to a possible diagnostic and prognostic role for the OC-associated microbiome, though the abstract does not describe validation in an independent cohort.
This study used shotgun metagenomic sequencing to profile the fecal gut metagenome in Parkinson's disease (PD), examining microbial composition, taxon abundance, metabolic pathways, and microbial gene products. The researchers looked for alterations that were consistently associated with PD compared to control groups. They also cross-referenced their findings with public metagenomic datasets from previous studies to check whether any changes held up across different populations. The goal was to identify generalizable, disease-associated microbiome features rather than findings specific to a single cohort.
The primary analysis included 244 stool donors from two independent cohorts in the United States. Each cohort included individuals with PD (n = 48 and n = 47), environmental household controls (n = 29 and n = 30), and community population controls (n = 41 and n = 49). These findings were then cross-referenced against public metagenomic datasets from two previous studies conducted in Germany and China.
Several taxa were significantly altered between PD and controls within the two newly sequenced US cohorts. When the data were compared across all four global cohorts, only Intestinimonas butyriciproducens showed consistent changes in PD. Pathway enrichment analysis revealed disruptions in microbial carbohydrate and lipid metabolism, along with increased amino acid and nucleotide metabolism in PD. The abstract also indicates that global gene-level signatures pointed to further alterations, though the specific gene products were not detailed in the available text.
By analyzing multiple cohorts across different countries, this study helps distinguish gut microbiome features that are truly associated with PD from findings that may be specific to one population or study design. The consistent alteration in Intestinimonas butyriciproducens across four independent cohorts suggests this taxon may be a reproducible microbial marker of PD worth further investigation. The disruptions in carbohydrate, lipid, amino acid, and nucleotide metabolism point to broader metabolic dysfunction in the PD gut microbiome that could inform future mechanistic or biomarker research.
This study examined the gut microbiome of patients with Peutz-Jeghers syndrome (PJS), a rare hereditary disorder marked by intestinal polyposis and a high risk of intussusception. Researchers used 16S rRNA sequencing to characterize overall microbiome composition and metagenomic sequencing on a subset of samples to assess functional pathway changes. The goal was to determine whether gut microbiota imbalance is associated with PJS and, specifically, with the complication of intussusception.
Stool samples were collected from 168 patients with PJS and 68 healthy family members who lived in the same household. For the deeper metagenomic functional analysis, a representative subset of 61 PJS patients and 27 healthy family members was used. Using cohabitating relatives as controls helps account for shared diet and environment.
The fecal microbiome of PJS patients showed greater variation in beta-diversity compared with healthy family members. PJS patients had an enhancement of Escherichia coli and a reduction of Faecalibacterium prausnitzii, an anti-inflammatory, butyrate-associated commensal. Among PJS patients, those with intussusception showed a further reduction in Faecalibacterium prausnitzii, marking it as a distinguishing microbial feature of this complication. Functional analysis found propanoate metabolism enriched in PJS patients overall and further enriched in those with intussusception, with Escherichia coli identified as the major contributor to this pathway.
These findings suggest gut microbiome imbalance, particularly loss of Faecalibacterium prausnitzii and expansion of Escherichia coli, may play a role in PJS pathogenesis and specifically in the development of intussusception. The progressive depletion of this anti-inflammatory commensal alongside enriched propanoate metabolism points to a possible microbial signature that could help identify PJS patients at greater risk for this complication. This raises the possibility that restoring depleted commensals or targeting E. coli-driven metabolic pathways could be explored as future strategies, though the abstract does not report interventional data.
This study examined whether alterations in the gut microbiome are linked not just to COVID-19 severity but to COVID-19 prognosis. Researchers performed genome-resolved metagenomic analysis on fecal samples to identify microbial genomes associated with disease severity. They then grouped these genomes into co-abundance "guilds" and tested whether a guild-based index could predict clinical outcomes.
The study analyzed fecal samples from 300 in-hospital COVID-19 patients, collected at the time of hospital admission. Patients were classified into mild, moderate, and severe or critical severity groups. The guild-level microbiome index was further validated across patients in different countries and compared against COVID-19 patients, pneumonia controls, and healthy subjects in four independent data sets.
Redundancy analysis identified 33 high quality metagenome-assembled genomes that differed across severity groups, and these organized into two competing guilds. Guild 1 carried more genes for short-chain fatty acid biosynthesis and fewer genes for virulence and antibiotic resistance compared with Guild 2. The resulting guild-level microbiome index (GMI) classified patients by severity group with an average AUROC of 0.83, correlated with 8 clinical parameters predictive of prognosis on day 7, and was associated with death or discharge outcome in critical patients.
The findings show that the gut microbiome's relationship to COVID-19 is genome-specific rather than simply taxon-specific, since two competing functional guilds, one linked to short-chain fatty acid production and one linked to virulence and resistance genes, tracked with disease severity. Because GMI at admission was consistently associated with clinical trajectory and distinguished COVID-19 patients from pneumonia controls and healthy subjects across independent data sets, this genome-resolved guild-level signature may help identify hospitalized patients at high risk of severe outcomes early, at the time of admission.
This case-control study compared the gut microbiota composition of breast cancer survivors to that of healthy women. Researchers sequenced the V3 and V4 regions of the 16S rRNA gene using next-generation sequencing, then assigned taxonomy with Kraken2, refined by Bracken, against a curated database called GutHealth_DB. They assessed alpha diversity (richness and evenness), beta diversity (compositional differences between groups), and the Firmicutes/Bacteroidetes ratio, using non-parametric statistical tests including Mann-Whitney U and Kruskal-Wallis.
The study included 23 breast cancer survivors (group 1) and 291 healthy female controls (group 2). All participants were women, and gut microbiota was assessed through stool-derived 16S rRNA sequencing. The abstract does not provide further demographic details such as age range or geographic location.
Alpha diversity was significantly higher in breast cancer survivors than in healthy controls, based on both the Chao index and the ACE index. The Shannon index, which reflects both richness and evenness, did not differ significantly between groups. Beta diversity analysis showed that overall microbiota composition differed significantly between the two groups using PERMANOVA and Anosim tests with weighted UniFrac distance, while beta-dispersion did not differ. Differential abundance testing identified differences across multiple taxonomic levels, including 14 phyla, 29 classes, 25 orders, 64 families, 116 genera, and 74 species.
These findings suggest that breast cancer survivors carry a gut microbiota that is compositionally distinct from that of healthy women, with greater taxonomic richness rather than simply reduced diversity. This challenges any assumption that survivorship is associated with a uniformly depleted microbiome and instead points to a reorganization of community structure across many taxonomic levels. The results support further investigation into whether these microbiota differences relate to cancer history, treatment exposure, or long-term health outcomes in survivors.
This study examined whether a designed consortium of gut bacteria could restore secondary bile acid metabolism and reduce intestinal inflammation. The researchers screened human gut bacterial strains for bile acid metabolizing activity and assembled a three-species consortium, named BAC, consisting of Clostridium AP sp000509125, Bacteroides ovatus, and Eubacterium limosum. They tested whether BAC could convert conjugated primary bile acids into the anti-inflammatory secondary bile acids ursodeoxycholic acid (UDCA) and lithocholic acid (LCA), both in vitro and in a mouse model of colitis.
The subjects were mice given dextran sulfate sodium (DSS) to induce colitis, then treated with the BAC consortium by oral gavage. The bacterial strains themselves were sourced from the human gut, consistent with findings from the Integrative Human Microbiome Project and other human cohort studies on inflammatory bowel disease. No human patient cohort was directly enrolled or tested in this particular study.
The BAC consortium converted taurochenodeoxycholic acid and glycochenodeoxycholic acid into the secondary bile acids UDCA and LCA in vitro. In DSS-treated mice, oral BAC treatment produced protective effects against colitis, including reduced weight loss and increased colon length. BAC treatment also raised fecal levels of bile acids, including UDCA and LCA, indicating that the consortium was functionally active in vivo.
This study demonstrates that restoring secondary bile acid metabolism through a defined bacterial consortium can ameliorate colitis, directly addressing the bile acid dysbiosis seen in human inflammatory bowel disease. It suggests that engineered, function-based bacterial consortia, rather than single strains, may offer a targeted strategy for correcting metabolic deficits in dysbiotic guts. These findings support further investigation of bile acid-producing consortia such as BAC as a potential therapeutic approach for inflammatory bowel disease.
This study examined whether Faecalibacterium prausnitzii, a next-generation probiotic candidate, could mitigate nonalcoholic steatohepatitis (NASH). The researchers used 16S rRNA sequencing to analyze gut microbiota composition and tested oral administration of F. prausnitzii strains in a mouse model of NASH induced by a high-fructose high-fat diet over 16 weeks. Outcomes were assessed using oral glucose tolerance tests, biochemical assays, and histological analyses of liver tissue.
The abstract describes two study populations. First, patients with NASH and healthy controls underwent 16S rRNA sequencing analysis of their gut microbiota. Second, four F. prausnitzii strains (EB-FPDK3, EB-FPDK9, EB-FPDK11, and EB-FPYYK1) were isolated from fecal samples of four healthy individuals and then tested in mice fed a high-fructose high-fat diet to induce NASH.
The 16S rRNA sequencing analyses confirmed differences in gut microbiota between NASH patients and healthy controls, supporting a link between dysbiosis and NASH pathophysiology. The abstract text is truncated before the specific results of the mouse experiments are given, so the precise magnitude of hepatic protection cannot be stated. However, the study's framing indicates that F. prausnitzii administration was evaluated for its ability to alleviate characteristic NASH phenotypes, including glucose tolerance, biochemical markers, and liver histology.
The findings support the premise that F. prausnitzii, a commensal gut bacterium, may serve as a next-generation probiotic for the prevention or treatment of NASH. This work extends probiotic research beyond traditional strains and highlights gut dysbiosis as a therapeutic target in fatty liver disease. If confirmed, it points toward microbiome-based interventions as a strategy for mitigating hepatic damage in metabolic liver disease.
This study examined how technical choices made throughout a microbiome workflow, from sample collection through sequencing, can bias the resulting microbiota profiles. The researchers compared different sample preservation methods, DNA extraction approaches, DNA input amounts, and PCR cycle numbers. They also investigated potential batch effects introduced during DNA extraction, sequencing, and barcoding steps.
The study used commercially available mock communities, including both bacterial-strain mock communities and DNA-based mock communities, rather than a human patient cohort. It also used multiple human fecal samples collected and processed under different conditions. A large set of 139 positive controls, created as a random mix of several participant samples, was included to assess batch effects.
Samples preserved in either of two commercial stabilization buffers (OMNIgene GUT and Zymo Research) showed less overgrowth of Enterobacteriaceae compared to unpreserved samples stored at room temperature. However, these stabilized room-temperature samples still differed in composition from samples frozen immediately upon collection. This indicates that both preservation method and storage condition independently shape the observed microbiota profile.
The findings show that technical variation at multiple stages of the microbiome workflow, including sample preservation, extraction, and processing batch, can introduce biases that affect comparability across studies. Researchers comparing microbiome results across studies or sites need to account for these methodological differences rather than assuming profiles reflect biology alone. Standardizing or at least reporting preservation and processing methods would improve the reliability of cross-study comparisons.
This study examined whether gut microbiome imbalance is associated with endometrial cancer, given that metabolic diseases like obesity, diabetes, and hypertension are known risk factors for the cancer and gut dysbiosis can drive metabolic alterations. Researchers profiled the fecal microbial communities of endometrial cancer patients and compared them with healthy controls using 16S rRNA high-throughput gene sequencing on the Illumina NovaSeq platform. The goal was to determine whether gut microbiota composition differs between the two groups and could represent an indirect factor in endometrial cancer development.
The study included 33 patients with endometrial cancer (the EC group) and 32 healthy controls (the N group). Fecal samples were collected from all participants between February 2021 and July 2021. The total number of operational taxonomic units (OTUs) identified was 28,537 in the healthy control group and 18,465 in the endometrial cancer group, with 4,771 OTUs shared between the two groups.
This was the first study to report that alpha diversity of the gut microbiota was significantly reduced in endometrial cancer patients compared with healthy controls. There was also a significant difference in overall microbial community distribution between the two groups. Specifically, the abundance of Firmicutes, Clostridia, Clostridiales, Ruminococcaceae, Faecalibacterium, and Gemmiger_formicis decreased in the endometrial cancer group relative to controls.
The findings suggest that gut microbiome dysbiosis, marked by reduced diversity and depletion of Faecalibacterium and related Firmicutes taxa, may be linked to endometrial cancer, potentially through metabolic pathways. Faecalibacterium species, including Faecalibacterium prausnitzii, are commonly recognized as anti-inflammatory, butyrate-producing commensals, so their depletion points toward a loss of protective microbial functions in these patients. These results support further investigation of gut microbiota as a potential indirect factor in endometrial cancer risk and as a possible target for future research.
This study examined fecal bacterial composition, bacterial co-abundance networks, and metagenome function in US adults with type 2 diabetes (T2DM) compared to healthy adults. Samples were grouped into three enterotypes based on dominant bacterial families: Bacteroidaceae (ET-B), Lachnospiraceae (ET-L), and Prevotellaceae (ET-P). Machine learning and network analysis were used to identify the primary bacteria and bacterial interactions associated with T2DM incidence within each enterotype.
The analysis drew on 1,911 fecal bacterial files representing 1,039 adults with T2DM and 872 healthy adults from the Human Microbiome Projects, all based in the United States. Operational taxonomic units were generated from these samples after filtering and cleaning with Qiime2 tools. This represents a large public metagenomic dataset rather than a newly recruited clinical cohort.
The Bacteroidaceae enterotype (ET-B) showed the highest incidence of T2DM among the three enterotypes. Alpha-diversity was significantly lower in T2DM subjects within the Lachnospiraceae (ET-L) and Prevotellaceae (ET-P) enterotypes, but not within ET-B, while beta-diversity showed a clear separation between T2DM and healthy groups across all three enterotypes. An XGBoost machine learning model achieved high accuracy and sensitivity in distinguishing T2DM from healthy samples, and specific taxa, including Enterocloster bolteae, Faecalicatena fissicatena, Clostridium symbiosum, and Faecalibacterium prausnitzii, were found to be more abundant in the T2DM group.
The findings suggest that enterotype context matters for understanding how gut microbiota relate to T2DM, since diversity changes and bacterial signatures differed depending on which enterotype a person fell into. The elevated abundance of Faecalibacterium prausnitzii, an organism generally regarded as a butyrate-producing, anti-inflammatory commensal, alongside T2DM in this dataset highlights the complexity of interpreting single-taxon abundance without accounting for enterotype and network context. Machine learning models built on enterotype-stratified microbiome data may offer a useful approach for identifying T2DM-associated microbial signatures in US populations.
This study examined the gut microbiome in Parkinson's disease (PD) using shotgun metagenomic sequencing, a method that captures microbial functional potential rather than taxonomy alone. The researchers designed a nested case-control study to investigate both recently onset PD and prodromal (premotor) PD, a stage that prior microbiome research had largely overlooked. They analyzed fecal metagenomes to identify bacterial species and metabolic pathways associated with PD and with features suggestive of the prodromal phase.
The study drew on 420 participants nested within two large epidemiological cohorts, the Nurses' Health Study and the Health Professionals Follow-up Study. This included 75 people with recently onset PD, 101 with features of prodromal PD, 113 controls with constipation, and 131 healthy controls. The design allowed comparison across a spectrum from prodromal symptoms through diagnosed disease against two distinct control groups.
Participants with PD or features of prodromal PD showed depletion of several strict anaerobes, bacteria types that the abstract links to reduced inflammation. A microbiome-based classifier achieved moderate accuracy in distinguishing recently onset PD cases from controls, with an area under the curve of 0.76 based on species composition and 0.74 based on functional pathways. These taxonomic changes were accompanied by corresponding functional shifts in the metagenome, indicating that both which microbes are present and what they metabolically do differ in PD.
By identifying microbial changes already present in prodromal, premotor PD, this study suggests gut microbiome alterations may precede or accompany the earliest detectable stages of disease rather than only appearing after motor symptoms emerge. The depletion of anaerobes associated with reduced inflammation points toward loss of anti-inflammatory microbial function as a feature of the disease process. The moderate classifier accuracy suggests gut metagenomic profiles could eventually contribute to tools for identifying at-risk individuals, though the abstract does not claim diagnostic readiness.
This study investigated the duodenal mucosa-associated microbiota and its surrounding microenvironment in relation to hyperglycemia, an area far less studied than stool microbiota in metabolic disease. The researchers compared paired stool and duodenal microbial samples between hyperglycemic and normoglycemic individuals. They also assessed the duodenal microenvironment directly by measuring tissue oxygen saturation, serum inflammatory markers, and zonulin as a marker of gut permeability. The goal was to determine whether duodenal, rather than stool, microbial changes track more closely with glycemic status.
The study population consisted of 33 subjects with hyperglycemia, defined as HbA1c of 5.7% or higher and fasting plasma glucose above 100 mg/dl, compared against 21 normoglycemic subjects. Both groups contributed paired stool and duodenal samples, allowing direct comparison of microbiota across two body sites within the same individuals. No further demographic details are given in the abstract.
Hyperglycemic subjects had a significantly higher duodenal bacterial count than normoglycemic subjects, along with increased pathobionts and reduced beneficial flora. This bacterial overload correlated with elevated serum zonulin and higher TNF-alpha, suggesting a link to increased gut permeability and inflammation. The hyperglycemic group also showed reduced duodenal oxygen saturation, higher total leukocyte count, and lower IL-10, indicating a systemic proinflammatory state. Notably, unlike stool flora, duodenal bacterial profile variability was specifically associated with glycemic status.
These findings suggest the duodenal microbiome and its local microenvironment, rather than stool alone, may play a distinct role in the pathogenesis of hyperglycemia and prediabetes. The association between bacterial overload, reduced oxygen saturation, and systemic inflammatory markers points to a possible mechanistic pathway linking small intestinal dysbiosis to metabolic dysfunction. This work highlights the duodenum as an underexplored but potentially important site for understanding and possibly intervening in early glycemic disturbances.
This study examined whether gut microbial communities are linked to the severity of COVID-19 in hospitalized patients. Researchers profiled stool samples using metagenomic sequencing to identify gut microbial taxa, their biochemical pathways, and stool metabolites associated with disease severity. They also built a random forest classifier to test whether microbiome data could distinguish severe from moderate COVID-19, and used network analyses to examine microbial community structure.
The study included 127 hospitalized patients with COVID-19, of whom 79 had severe disease and 48 had moderate disease. These patients collectively provided 241 stool samples collected from April 2020 to May 2021. The classifier's performance was also externally validated in an independent cohort, though details of that cohort are not given in the abstract.
Forty-eight microbial species were associated with severe COVID-19 after accounting for antibiotic use, age, sex, and comorbidities. Severe disease was marked by significant in-hospital depletion of Fusicatenibacter saccharivorans and Roseburia hominis, two commensals previously linked to post-acute COVID syndrome, or long COVID, suggesting they may serve as early biomarkers for its later development. The random forest classifier achieved excellent performance distinguishing severe from moderate COVID-19 stool samples, a result that held up in external validation, and network analysis pointed to fragility in the gut microbial community structure of severe cases.
The findings suggest that gut microbial depletion during acute COVID-19, particularly of Fusicatenibacter saccharivorans and Roseburia hominis, could help identify patients at risk of developing long COVID before it manifests. The strong, externally validated classifier performance indicates that stool-based microbiome signatures could become a practical tool for stratifying COVID-19 severity risk. These results also reinforce the broader role of specific gut commensals in shaping immune resilience during respiratory viral infection.
This study examined how the gut microbiota changes with age and how those age-related changes relate to colorectal cancer (CRC). The researchers analyzed 11 metagenomic data sets, correcting for batch effects, then compared species composition and abundance across three age groups in both healthy individuals and CRC samples. They used LEfSe analysis to identify bacteria whose relative abundance differed by age group, then built age-prediction and CRC-risk-prediction models from those age-differentiated species.
The abstract does not report a single original cohort with a specific sample size. Instead, the study population consisted of previously published metagenomic samples drawn from 11 combined data sets accessed through the curatedMetagenomicData R package, covering both healthy individuals and people with colorectal cancer. These samples were stratified into three age groups for comparison.
The structure and composition of the gut microbiota differed significantly across the three age groups in both healthy and CRC samples. Bacteroides vulgatus abundance was lower in the older group compared to the other two groups, while Bacteroides fragilis abundance increased with aging. The researchers also identified seven bacterial species whose abundance rose with age, and found that abundance of pathogenic bacteria, including Escherichia coli, increased as well.
By linking specific age-associated shifts in gut microbiota, such as declining Bacteroides vulgatus and rising Bacteroides fragilis and Escherichia coli, to both healthy aging and CRC samples, this work suggests the microbiome could serve as a biomarker for biological aging and CRC risk. The construction of age-prediction and CRC-risk-prediction models based on these age-differentiated bacteria points toward potential microbiota-based tools for estimating cancer risk as people age. This approach could inform future screening or risk-stratification strategies that account for age-related microbial changes.
This pilot study explored the composition of the gut microbiota in patients with prediabetes and in treatment naive type 2 diabetes (T2D), compared to healthy subjects. Fecal samples were analyzed using the bacterial 16S rRNA gene, with two complementary technologies employed to give broad coverage of potential T2D associated bacteria: the GA-map 131-plex probe panel spanning the V3-V9 regions, and the LUMI-Seq full-length 16S sequencing platform spanning V1-V9. The researchers used multivariate methods to explore variation between groups, estimated differential bacterial abundance, and built classification models to identify microbiota signatures that could discriminate between the groups.
The study included 24 patients with prediabetes and 18 patients with treatment naive type 2 diabetes, recruited alongside healthy comparison subjects in Norway. Fecal samples were collected from all participants for bacterial genomic DNA extraction and analysis. The abstract does not provide further demographic details such as age or sex distribution.
Using two independent 16S rRNA based technologies, the study found variation in gut microbiota composition across the prediabetes, treatment naive T2D, and healthy groups. Differential bacterial abundance was estimated between groups, and classification models were used to identify microbiota signatures capable of discriminating prediabetes and T2D patients from healthy subjects. The abstract does not specify which individual taxa, including Faecalibacterium prausnitzii or other anti-inflammatory commensals, were found to differ, so no such specific findings can be reported here.
By applying two different 16S rRNA sequencing approaches in parallel, this pilot study demonstrates a strategy for more comprehensively capturing bacteria potentially associated with early and untreated T2D. The identification of microbiota signatures that discriminate prediabetes and treatment naive T2D from healthy states suggests the gut microbiota could eventually serve as a marker of disease status before or at diagnosis. As a pilot study, its findings point toward the value of larger, confirmatory studies to establish a reproducible T2D associated microbiota profile.
This study used metagenomic sequencing to characterize the gut microbiota of patients with non-segmental vitiligo. Researchers examined microbial community composition, diversity, and gene functions using bioinformatic analysis. They also predicted gut metabolic modules with the KEGG and MetaCyc databases to identify functional differences linked to the disease.
The study enrolled 25 patients with non-segmental vitiligo and 25 matched healthy controls. All 50 participants underwent metagenomic sequencing of their gut microbiota for comparison between the two groups.
Alpha diversity of the gut microbiome was significantly reduced in vitiligo patients compared with healthy controls. At the species level, Staphylococcus thermophiles was decreased while Bacteroides fragilis was increased in patients with vitiligo. LEfSe analysis identified additional microbial markers distinguishing vitiligo patients, including Lachnospiraceae_bacterium_BX3, Massilioclostridium_coli, and TM7_phylum_sp_oral_taxon_348, alongside Bacteroides_fragilis.
These findings support a link between altered gut microbial composition and non-segmental vitiligo, reinforcing gut dysbiosis as a feature of the disease. The reduced diversity and specific species shifts, particularly the increase in Bacteroides fragilis, may serve as microbial markers for further investigation. Characterizing associated gene functions and metabolic modules could help clarify mechanisms connecting gut microbiota to vitiligo pathogenesis.
This study examined how a 7-day course of amoxicillin affects the gut microbiome and antibiotic resistome of children treated for severe acute malnutrition. It was a secondary, retrospective metagenomic analysis nested within a randomised, double-blinded, placebo-controlled trial (NCT01613547). Faecal samples were collected at baseline and multiple follow-up points (weeks 1, 4, 8, and 12, with a subset followed out to week 104) and profiled by metagenomic sequencing. The design let researchers track both immediate and longer-term shifts in gut microbial composition and resistance genes.
The source trial enrolled children aged 6 to 59 months with severe acute malnutrition treated as outpatients in Madarounfa, Niger, out of an overall cohort of 2,399 children. For this analysis, 161 children were randomly selected for initial 12-week follow-up (September 23, 2013 to February 3, 2014), and a convenience sample from that group, chosen by anthropometric measures, was followed again two years later (September 28 to October 27, 2015). Reference controls consisted of 38 children without severe acute malnutrition and six children with severe acute malnutrition matched to the original cohort's baseline ages.
The abstract text provided is truncated after stating that amoxicillin led to an immediate effect in the 12-week follow-up group, so the specific findings on the direction and magnitude of microbiome and resistome changes are not available here. What can be confirmed is that the study was designed to detect both acute (short-term) and long-term (two-year) changes in gut microbial communities and antibiotic resistance genes following amoxicillin treatment. No details on Faecalibacterium prausnitzii, butyrate, or specific anti-inflammatory commensals are present in the available abstract text.
By pairing microbiome profiling with resistome surveillance in a placebo-controlled trial, this study offers a rare opportunity to weigh the benefits of antibiotic treatment for severe acute malnutrition against its effects on gut ecology and antibiotic resistance. The two-year follow-up component is notable because it allows assessment of whether short-course amoxicillin produces lasting, rather than only transient, changes to the microbiome and resistome. Findings from this kind of analysis could inform how clinicians weigh antibiotic use in vulnerable, malnourished pediatric populations against the risk of promoting antibiotic resistance.
This study examined the mucosal microbiome in patients with early, pre-cancerous bowel polyps compared to patients with no polyps at the time of colonoscopy. Most prior work in this area relied on stool microbiota and short-read sequencing of variable regions of the 16S rRNA gene, an approach the authors note has produced inconsistent findings across studies. To address this, the researchers directly compared short-read and PacBio long-read 16S rRNA sequencing on the same mucosal samples. The goal was to see whether sequencing technology itself affects which microbial differences are detected between polyp and non-polyp mucosa.
The subjects were patients undergoing colonoscopy who were grouped by whether they presented with one or more bowel polyps or had no polyps. The abstract does not give an exact sample size, age range, or other demographic details for this cohort. What can be said is that mucosal tissue samples, rather than stool, were collected from these colonoscopy patients for microbiome analysis.
Neither short-read nor long-read 16S rRNA sequencing found significant differences in overall microbial diversity between patients with and without bowel polyps. Differential abundance analysis showed amplicon sequence variants for Ruminococcus gnavus and Escherichia coli were elevated in polyp-associated mucosa, while variants for Parabacteroides merdae, Veillonella nakazawae, and Sutterella wadsworthensis were relatively decreased. Notably, only Ruminococcus gnavus was consistently identified as altered by both sequencing technologies, whereas the other taxa showed discrepant results between methods. The abstract does not mention Faecalibacterium prausnitzii, butyrate, or other anti-inflammatory commensals.
The findings suggest that the choice of 16S rRNA sequencing technology can materially affect which mucosal microbial signals are detected in association with bowel polyps. This helps explain why earlier studies using only short-read sequencing have produced inconsistent results in this area. The consistent detection of Ruminococcus gnavus across both platforms strengthens confidence that this taxon is genuinely associated with polyp-bearing mucosa, marking it as a candidate worth further investigation in pre-cancerous colorectal disease.
This study investigated the gastrointestinal microbiota of sheep using 16S rDNA and metagenomic sequencing, examining bacterial composition and function across the rumen, duodenum, and colon. The researchers aimed to link specific microbial species to meat quality traits, focusing on the fatty acid content of muscle tissue. Functional annotation using GO, KEGG, and CAZyme databases was used to connect these bacteria to metabolic pathways involving glucose, lipids, and amino acids.
The study population consisted of Tan sheep and Dorper sheep, two breeds compared for differences in their gastrointestinal microbial communities. Samples were drawn from multiple gut segments (ruminal, duodenal, and colonic) within these animals rather than from a single site. No specific numeric cohort size is given in the abstract beyond the two-breed comparison across gut regions.
Distinct bacteria were uniquely identified in each breed, including Agrobacterium tumefaciens, Bacteroidales bacterium CF, and several members of the family Oscillospiraceae. These breed-specific bacteria were functionally linked to glucose, lipid, and amino acid metabolism. Sixteen microbial species were associated with muscle fatty acid content, particularly lauric acid (C12:0), with four species, including Achromobacter xylosoxidans, Mageeibacillus indolicus, and Mycobacterium dioxanotrophicus, showing positive correlation with C12:0 levels.
These findings suggest that gastrointestinal microbiota composition may directly influence meat quality traits such as fatty acid profiles in sheep muscle. Identifying specific bacterial species tied to lauric acid content offers a potential microbial target for improving meat quality through breed selection or microbiome management. This work also underscores the value of comparing gut segments and breeds together to uncover functional links between gut bacteria and host metabolic outcomes.
This study examined whether the gut microbiome could be used to differentiate and diagnose Crohn's disease (CD) and ulcerative colitis (UC), the two major forms of inflammatory bowel disease (IBD). Researchers compared the abundance and composition of gut microbiota across disease states and looked for specific biomarkers linked to disease activity. The work also examined how microbial diversity changed as disease progressed through different stages.
The abstract describes patients with IBD, split into CD and UC groups, compared against healthy controls (HC). Specific numbers of participants, demographics, and enrollment details are not given in the abstract, so the exact cohort size and characteristics cannot be stated. The comparison design (IBD patients versus healthy controls, with CD and UC analyzed separately) is the only population detail confirmed.
Gut microbiome diversity was lower in IBD patients than in healthy controls, and this reduction was significantly more pronounced in CD patients. The researchers identified 68 microbiota members associated with these diseases, 28 linked to CD and 40 linked to UC. Microbial diversity also declined further as disease progressed through more advanced stages. Specific taxa tracked with severity: Alistipes shahii and Pseudodesulfovibrio aespoeensis abundances were negatively correlated with CD severity, while Polynucleobacter wianus abundance was positively associated with it.
These findings suggest the gut microbiome could serve as a diagnostic tool to distinguish CD from UC, addressing a clinically difficult differential diagnosis. Identifying species whose abundance correlates with disease severity points toward potential microbial biomarkers for monitoring disease activity and staging. Such biomarkers could support more precise, long-term treatment planning for IBD patients.
This study examined the active (transcriptionally expressed) lung microbiota of COVID-19 patients using metatranscriptomic data from bronchoalveolar lavage fluid (BALF). The researchers analyzed bacterial microbiota and virome composition to determine whether SARS-CoV-2 infection alters the lung microbial landscape. They assessed alpha-diversity, beta-diversity, and species composition to characterize dysbiosis associated with infection.
The analysis drew on BALF metatranscriptomic data from 19 COVID-19 patients and 23 healthy controls. These samples came from 6 independent projects, indicating a pooled, multi-cohort secondary analysis of existing sequencing data rather than a newly recruited single-site cohort. No further demographic details are given in the abstract.
SARS-CoV-2 infection substantially altered lung microbiota, as shown by shifts in alpha-diversity, beta-diversity, and species composition between groups. The COVID-19 group showed enrichment of pathogens such as Klebsiella oxytoca, immunomodulatory probiotics including lactic acid bacteria and Faecalibacterium prausnitzii (a butyrate producer), and Tobacco mosaic virus (TMV), together indicating severe microbiota dysbiosis. A significant correlation among Rothia mucilaginosa, TMV, and SARS-CoV-2 pointed to intense inflammatory interactions among host, virus, and other microbes in the lungs.
The findings suggest that COVID-19 involves not just SARS-CoV-2 alone but a broader disruption of the active lung microbial community, including bacteria and viruses beyond the primary pathogen. The unexpected enrichment of the butyrate producer Faecalibacterium prausnitzii alongside pathogens highlights that dysbiosis in this context is complex rather than a simple loss of beneficial microbes. Tracking active microbiota and virome members like TMV and Rothia mucilaginosa may help explain inflammatory complications of COVID-19 and could inform future study of lung microbial contributions to disease severity.
This study investigated the connection between the oral and gut microbiome in Parkinson's disease (PD) using shotgun metagenomic sequencing. Researchers examined both the taxonomic composition and the functional gene content of these microbial communities. The aim was to determine whether oral microbiome changes relate to gut microbiome changes in PD, and whether these shifts produce functional alterations rather than just compositional differences.
The abstract does not report specific sample sizes, ages, or recruitment details. The study compared PD patients to healthy controls, using paired oral and gut microbiome samples analyzed by shotgun metagenomic sequencing. Beyond the PD-versus-control design, no further cohort characteristics are given in the abstract.
The taxonomic composition of both the oral and gut microbiome differed significantly between PD patients and healthy controls (P = 0.003 and 0.001, respectively). Oral Lactobacillus was more abundant in PD patients and was associated with opportunistic pathogens in the gut (FDR-adjusted P < 0.038). Functionally, microbial gene markers for glutamate and arginine biosynthesis were downregulated, while antimicrobial resistance gene markers were upregulated in PD patients compared to healthy controls (all P < 0.001).
The findings suggest a connection between the oral and gut microbiota in PD that may drive functional, not just compositional, alterations of the microbiome. The rise in oral Lactobacillus alongside opportunistic gut pathogens points to the oral cavity as a potential contributor to gut dysbiosis in PD. Reduced glutamate and arginine biosynthesis and increased antimicrobial resistance gene markers highlight functional microbial pathways that may warrant further investigation as they relate to PD pathophysiology.
This study investigated how probiotic supplementation affects the gut microbiota of extremely preterm infants in the neonatal intensive care unit. Probiotics were already known to reduce necrotizing enterocolitis (NEC) risk in this population, but the underlying mechanism was unclear. The researchers used a prospective cohort design to compare gut microbiota composition between infants who received probiotics and those who did not. They also examined whether probiotic exposure was associated with clinical outcomes such as NEC, late-onset sepsis, and duration of total parenteral nutrition.
The cohort consisted of 120 extremely preterm neonates with a gestational age of 28 weeks or less. Infants were enrolled between August 2019 and December 2021 and divided into a study group that received probiotics and a control group that did not. This was a real-world clinical NICU population rather than a public dataset or animal model.
Neonates who received probiotics had a significantly increased abundance of Lactobacillus compared with the control group (adjusted odds ratio 4.33, 95% CI 1.89 to 9.96, p = 0.009). The probiotic group also spent significantly fewer days on total parenteral nutrition (median 29.0 days versus 35.5 days, p = 0.004). In addition, the probiotic group had a significantly lower rate of late-onset sepsis than the control group.
The findings suggest that probiotics may benefit extremely preterm infants partly by reshaping the gut microbiota toward greater Lactobacillus abundance, alongside reductions in parenteral nutrition duration and late-onset sepsis. This offers a plausible microbiota-mediated mechanism linking probiotic use to previously reported reductions in NEC and other neonatal morbidities. The results support continued clinical use of probiotics in extremely preterm NICU populations and point to gut microbiota composition as a relevant marker for future studies of probiotic mechanisms in this vulnerable group.
This scoping review examined the human gut microbiota and its relation to glucose metabolism, insulin resistance, and type 2 diabetes risk. The authors searched PubMed and screened 5983 records down to 45 original observational studies. They focused on identifying key bacterial taxa associated with markers and stages of glucose dysregulation, independent of overweight, obesity, and metabolic drugs. The review also considered the potential mediating role of short-chain fatty acids (SCFAs) and the influence of diet and diet-microbiota derived metabolites.
The review drew on human observational studies conducted in healthy adults as well as adults with metabolic disease and associated risk factors. Rather than a single cohort, the evidence base was pooled across 45 separate original studies identified from the PubMed literature. Specific sample sizes or demographic details for individual cohorts are not given in the abstract.
Across the reviewed studies, alpha diversity and 45 distinct bacterial taxa were associated with glucose metabolism outcomes. Six taxa emerged as most frequently linked to glucose metabolism, including Akkermansia muciniphila, Bifidobacterium longum, the Clostridium leptum group, and Faecalibacterium prausnitzii. The authors present evidence supporting SCFAs as a mechanism that may mediate the relationship between these gut bacteria and glucose regulation. Diet and microbiota-derived metabolites are also highlighted as relevant contributors to these associations.
Identifying specific gut bacteria, including SCFA-associated and anti-inflammatory commensals such as Faecalibacterium prausnitzii, consistently linked to glucose metabolism could open new avenues for type 2 diabetes prevention. Because these associations were found independent of obesity and metabolic drug use, the gut microbiota may represent an independent target for intervention. The proposed role of SCFAs and diet-derived metabolites suggests that dietary strategies aimed at shaping the microbiota could be a practical entry point for future prevention efforts. Overall, the findings support further mechanistic and interventional research into these key taxa and their metabolic products.
This study investigated the ocular surface microbiome in patients with unilateral or asymmetric glaucoma who were using topical ophthalmic medications in only one eye. Researchers used V3-V4 16S rRNA sequencing on ocular surface swabs to characterize microbial diversity and composition. They then tested whether differences in microbial composition were related to measures of ocular surface disease, including tear meniscus height, tear break-up time, and Dry Eye Questionnaire scores.
The study included 17 subjects total. Ten were patients with asymmetric or unilateral glaucoma who used topical glaucoma therapy in only one eye, allowing comparison between their treated and untreated eyes. Seven were age-matched healthy controls with no history of ocular disease or eyedrop use, and samples were grouped into three categories: treated glaucomatous eyes, untreated contralateral eyes, and healthy control eyes.
Both the treated and the untreated eyes of glaucoma patients showed significantly greater alpha-diversity and a greater relative abundance of gram-negative organisms compared to healthy control eyes. This pattern occurred even in the contralateral eye that received no eyedrops, suggesting a systemic or bilateral effect rather than one confined to the treated eye alone. The microbial composition of patient eyes was also associated with decreased tear meniscus height and decreased tear break-up time, linking microbiome alterations to signs of ocular surface disease.
The findings suggest that topical glaucoma therapy is associated with ocular surface microbiome shifts that extend beyond the directly treated eye, potentially through systemic exposure or shared tear film dynamics. Because these microbial changes correlated with impaired tear film stability, the results implicate the ocular surface microbiome as a factor in medication-related ocular surface disease among glaucoma patients. This raises the possibility that microbiome monitoring could inform strategies to reduce ocular surface complications in long-term glaucoma treatment.
This double-blind phase II randomized trial (ColoViD) examined the interplay between vitamin D supplementation, gut microbiota, and colorectal cancer (CRC) outcomes. Patients who had completed standard CRC treatment received either 2000 IU/day of vitamin D or placebo for one year. Fecal samples were collected before and after treatment and analyzed by shotgun metagenomic sequencing to identify taxa and pathways associated with supplementation. The study also used mediation analysis to test whether microbiota changes explained vitamin D's effect on blood 25(OH)D levels, and a Cox model to examine disease-free survival.
The trial enrolled 74 CRC patients who had completed standard treatment, of whom 60 were ultimately analyzed. All participants had undergone fecal sampling and blood 25(OH)D testing at baseline and after one year of supplementation or placebo. The abstract notes that sex differences in vitamin D levels, microbiota composition, and pathways were observed within this cohort.
Overall microbial diversity did not differ between the vitamin D and placebo arms, with comparable changes in alpha diversity (Shannon p = 0.77, Simpson p = 0.63) and post-treatment beta diversity (p = 0.70). Despite this, post-treatment abundances of 63 taxa and 32 pathways differed significantly between arms. Notably, these 63 taxa were found to mediate the effect of vitamin D supplementation on 25(OH)D blood levels (p = 0.02), and sex-specific differences emerged in vitamin D levels, microbiota, and pathways.
The findings suggest that vitamin D supplementation influences specific gut bacterial taxa and metabolic pathways even without altering overall community diversity, and that these taxa may partly govern how well vitamin D is absorbed or metabolized into its active blood form. This points to a bidirectional relationship between the gut microbiota and vitamin D status in CRC survivors that could inform future supplementation strategies. The observed sex differences further suggest that vitamin D-microbiota interactions may need to be considered separately for men and women in future research and clinical practice.
This study investigated specific alterations in the gut microbiome and serum metabolome in polycystic ovary syndrome (PCOS) and how the two systems interact. Researchers used shotgun metagenomic sequencing on stool samples and ultrahigh performance liquid chromatography quadrupole time-of-flight mass spectrometry on serum to profile microbial and metabolite changes. They then built an integrative network combining the metagenomics and metabolomics datasets to map possible interactions between gut bacteria and circulating metabolites. This network-derived hypothesis was further tested using fecal microbiota transplantation (FMT) in a rat trial.
The human portion of the study involved stool and serum samples from 32 patients with PCOS and 18 healthy controls. The abstract does not provide further demographic details such as age range or geographic location. The mechanistic findings were additionally tested in a rat model via fecal microbiota transplantation, not in additional human subjects.
Fecal metagenomics identified 64 microbial strains that differed significantly between PCOS patients and healthy controls, with about half of these enriched in the PCOS group. These altered species were associated with disruption of host metabolic homeostasis, including insulin resistance and fatty acid metabolism, and with heightened inflammatory signaling such as the PI3K/Akt/mTOR pathway. The bacteria appeared linked to these effects partly through expression of sterol regulatory element-binding transcription factor-1, serine/threonine-protein kinase mTOR, and 3-oxoacyl-[acyl-carrier-protein] synthase III. The abstract does not mention Faecalibacterium prausnitzii, butyrate, or other anti-inflammatory commensals specifically.
The findings suggest that specific gut microbial strains may causally contribute to the metabolic and inflammatory disturbances seen in PCOS, rather than merely correlating with the condition. The use of an integrative metagenome-metabolome network, validated through fecal microbiota transplantation in rats, strengthens the case for a functional gut microbiome to host metabolism link. This points to the gut microbiome and its metabolic outputs as potential targets for future diagnostic or therapeutic strategies in PCOS. Further human studies would be needed to confirm causality and clinical relevance.
This study investigated whether the gut microbiota is altered in mild cognitive impairment (MCI) and Alzheimer's disease (AD) through suppression of the parasympathetic nervous system (PNS), a hypothesized mechanism within the gut-brain axis. Researchers combined fecal bacterial sequencing data from four prior human AD studies and tested the PNS-suppression hypothesis in rats using scopolamine injections to induce memory impairment. Rats were maintained on a high-fat diet for six weeks and assigned to memory-impaired, saline-control, and donepezil-treated positive-control groups. An XGBoost machine learning model was applied to identify the bacterial taxa most predictive of cognitive status.
The human component drew on combined fecal bacterial FASTA/Q data from four separate Alzheimer's disease studies, totaling 410 samples. The animal component used rats fed a high-fat diet for six weeks, divided into groups receiving scopolamine injections (to induce memory deficits), saline injections (no memory impairment), or scopolamine plus donepezil (a positive-control treatment). No individual human demographic details beyond the combined sample size are given in the abstract.
Using the optimal XGBoost-derived model, Blautia luti, Pseudomonas mucidolens, Escherichia marmotae, and Gemmiger formicillis were positively correlated with mild cognitive impairment. Escherichia fergusonii, Mycobacterium neglectum, and Lawsonibacter asaccharolyticus were positively correlated with Alzheimer's disease. These distinct bacterial signatures suggest that MCI and AD are associated with different, identifiable shifts in gut microbial composition. The abstract does not report findings related to Faecalibacterium prausnitzii, butyrate, or anti-inflammatory commensals specifically.
The findings support a link between parasympathetic nervous system suppression, gut microbiota alteration, and cognitive decline, reinforcing the relevance of the gut-brain axis in dementia-related conditions. Because distinct bacterial taxa were associated with MCI versus AD, gut microbiota profiles may hold potential as biomarkers for distinguishing stages of cognitive impairment. The combined human-and-rat approach also suggests that scopolamine-induced PNS suppression in animal models can help validate mechanisms observed in human AD microbiota data, supporting further mechanistic and interventional research.
This study examined the gut microbiome in Parkinson's disease (PD) using large-scale, high-resolution shotgun metagenomic sequencing of fecal DNA. The researchers applied uniform, standardized methods throughout, followed by metagenome-wide association studies requiring agreement between two independent statistical methods (ANCOM-BC and MaAsLin2) before declaring a disease association. They also conducted network analysis to identify clusters of co-occurring microbial species and functional profiling to characterize microbial genes and pathways.
The study enrolled 490 individuals with Parkinson's disease and 234 control individuals. Fecal samples from this cohort underwent deep shotgun sequencing to generate the metagenomic data analyzed in the study. The abstract does not provide further demographic detail on the participants.
Over 30 percent of the species, genes, and pathways tested showed altered abundances in Parkinson's disease, indicating widespread dysbiosis. PD-associated species organized into polymicrobial clusters that grew, shrank, or competed together rather than acting independently. The PD microbiome was disease permissive: it showed overabundance of pathogens and immunogenic components, dysregulated neuroactive signaling, an excess of molecules that induce alpha-synuclein pathology, and overproduction of toxicants, alongside a reduction in anti-inflammatory and neuroprotective factors that would otherwise support recovery.
By validating in human PD patients findings previously seen only in experimental models, this study strengthens the case that the gut microbiome contributes to multiple disease mechanisms in Parkinson's disease. The reconciliation of prior human PD microbiome literature helps resolve inconsistencies across earlier studies and establishes a more standardized foundation for future research. The reduction in anti-inflammatory and neuroprotective microbial factors points to a loss of protective capacity that may limit the body's ability to counteract disease processes, suggesting the microbiome as a potential target for future mechanistic and therapeutic investigation.
This single-center study profiled the gut mucosa-associated microbiome of Kenyan colorectal cancer (CRC) patients and healthy volunteers. Researchers used 16S rRNA sequencing to characterize microbial community composition, examining alpha and beta diversity, differential taxa abundance, and predicted microbial metabolic profiles. The study also evaluated associations between microbiome profiles and patient age, motivated by rising and increasingly early-onset CRC incidence in Kenya.
The cohort consisted of 18 CRC patients and 18 healthy controls recruited at the Moi Teaching and Referral Hospital, Moi University, in Kenya. This population was chosen because microbiome studies in Kenyan CRC patients are rare, despite CRC incidence rates tripling in the country between 1997 and 2017. The hospital has also observed an increase in CRC diagnoses among younger patients.
Alpha diversity did not differ significantly between CRC patients and healthy controls, but beta diversity metrics showed clear dissimilarities in overall microbial community structure between the two groups. The most notably underrepresented species in the CRC group were Prevotella copri and Faecalibacterium prausnitzii, an anti-inflammatory, butyrate-associated commensal. The abstract also points to an association with bacterial glutamate degradation pathways as part of the CRC-associated microbial signature.
The findings suggest that gut microbiome dysbiosis, marked by loss of key commensals like Faecalibacterium prausnitzii and Prevotella copri, may contribute to CRC pathobiology in a Kenyan population that has been understudied in microbiome research. Because overall diversity was preserved while community composition shifted, compositional and functional changes rather than diversity loss appear more relevant to CRC in this setting. These results support further investigation of microbiome signatures, including glutamate metabolism pathways, as potential contributors to the rising and increasingly early-onset CRC burden in Sub-Saharan Africa.
This study examined the interaction between the gut microbiota and colorectal cancer (CRC) using metagenomic data retrieved from the GMrepo database. Researchers analyzed differences in gut microbiota distribution between CRC cases and controls at the species level, built a co-occurrence network, and assessed microbial interactions with environmental factors. Random forest models were then used to identify significant microbial biomarkers capable of differentiating CRC samples from control samples.
The analysis drew on 709 metagenomic samples from six projects in the GMrepo database. After matching, the study population consisted of 86 CRC patients and 86 matched healthy controls from six countries. A total of 484 microbial species and 166 related genera were analyzed across these paired samples.
The study confirmed previously recognized associations between Fusobacterium nucleatum and species within the genera Peptostreptococcus, Porphyromonas, and Prevotella with colorectal cancer. It also identified new associations involving the novel species Parvimonas micra and Collinsella. These findings, generated through a paired-sample design and machine learning models, point to an expanded panel of species-level microbial signals tied to CRC status.
By quantifying and visualizing microbiota-CRC interactions across a multi-country dataset, this work supports the development of a more precise, species-level microbiota panel for CRC diagnosis. The identification of novel associated species such as Parvimonas micra and Collinsella suggests additional candidate biomarkers beyond the well-established Fusobacterium nucleatum signal. This paired-sample, network-based approach offers a template for refining microbial diagnostic panels in colorectal cancer research.
This study examined the gut microbial composition and structure associated with colorectal cancer (CRC) across populations from different geographic regions. Researchers used whole-genome sequencing (WGS) data, annotated with MetaPhlAn2, to determine species and genus level relative abundance. They applied PCA and LEfSe analysis to compare microbial differences between regional datasets and used Spearman correlation analysis to examine relationships among CRC-associated differential species. The ultimate goal was to build and verify CRC risk prediction models based on these regional microbial differences.
The analysis drew on a metagenomic dataset of 601 samples collected from six countries, sourced from the GMrepo and NCBI databases. This represents a secondary analysis of previously generated whole-genome sequencing data rather than a newly recruited clinical cohort. The abstract does not specify individual patient demographics such as age or sex, only the multi-country, multi-sample composition of the dataset.
The composition of the intestinal bacterial community varied by region, and the specific differential intestinal bacteria linked to CRC were inconsistent from country to country. Despite this regional variability, the researchers identified a common diversity of bacteria shared across all six countries, including Peptostreptococcus. These findings indicate that CRC-associated microbiota show both a conserved core signature and considerable geographic variation.
The findings suggest that CRC risk prediction models based on gut microbiota may need to account for regional differences in microbial composition rather than assuming a universal signature. Identifying bacteria that are consistently associated with CRC across diverse populations, such as Peptostreptococcus, could support more broadly generalizable diagnostic or risk-assessment tools. At the same time, the region-specific differences highlight the importance of validating any microbiome-based CRC model within the population it will be applied to.
This study examined how gut microbiota composition, gut permeability, and systemic inflammation relate to glycemic status in a refugee population with a high burden of type 2 diabetes. Researchers measured circulating lipopolysaccharide binding protein (LBP), a marker of gut permeability, alongside inflammatory cytokines and dietary fiber intake. Metagenomic sequencing was used to characterize gut microbiota genus abundance, species richness, and alpha diversity. The goal was to understand whether gut microbiome features and inflammation help explain elevated diabetes risk in this understudied group.
The study population was a convenience sample of 50 Bhutanese refugee adults residing in New Hampshire. This is a South Asian refugee community previously underrepresented in chronic disease research despite experiencing a high risk of obesity and type 2 diabetes. The design was cross-sectional, meaning all measures (microbiome, inflammation, LBP, fiber intake, glycemic status) were assessed at a single point in time in these 50 individuals.
The researchers found a substantial chronic disease burden in this population, along with a correlation between glycemic status, LBP, and inflammation. Glycemic status also correlated with gut microbiome alpha diversity. A significant correlation was identified between proinflammatory bacterial taxa and inflammatory cytokines. Additionally, short-chain fatty acid (SCFA)-producing taxa were inversely correlated with age.
This is described as the most comprehensive examination to date of metabolic health and the gut microbiome in a Bhutanese refugee population in New Hampshire. The findings point to inflammation, gut permeability (via LBP), and microbiome composition as interconnected factors worth further investigation in glycemic impairment. The results are intended to inform future research and potential interventions targeting this vulnerable, understudied population.
This study examined the effect of antiparkinsonian medication, specifically levodopa (LD) and levodopa-carbidopa intestinal gel (LCIG), on the gut microbiota and fecal metabolome in Parkinson disease (PD). Fecal DNA was analyzed using next-generation sequencing of the V3 and V4 regions of the 16S rRNA gene. Fecal metabolic extracts were also evaluated using gas chromatography mass spectrometry to characterize metabolome differences across treatment groups.
The study included 107 patients with a clinical diagnosis of Parkinson disease. Patients were divided into three groups: an LCIG group (n = 38) receiving levodopa-carbidopa intrajejunal gel, an LD group (n = 46) receiving oral levodopa, and a Naive group (n = 23) not taking any antiparkinsonian medications. This design allowed comparison of gut microbiota composition across different treatment exposures within a PD population.
Multivariate analysis showed that the LCIG group had a significantly higher abundance of Enterobacteriaceae, Escherichia, and Serratia compared to the LD group. Compared to the Naive group, the LD group showed a reduction of Blautia and Lachnospirae. The LCIG group additionally showed an increase in Proteobacteria and Enterobacteriaceae alongside a reduction in Firmicutes, Lachnospiraceae, and Blautia relative to the Naive group.
The findings suggest that the route and form of levodopa therapy, oral versus intrajejunal gel, are associated with distinct gut microbiota profiles in Parkinson disease. The reduction of Blautia and Lachnospiraceae, taxa associated with short-chain fatty acid production, alongside enrichment of Enterobacteriaceae in LCIG-treated patients points to a treatment-related shift toward a less favorable microbial composition. These distinctive features may warrant further investigation into how PD medication choice shapes gut microbial and metabolic health over the course of treatment.
This study examined whether gut microbiome composition is linked to disease severity in patients with COVID-19, and whether any microbiome disturbances resolve after the SARS-CoV-2 virus is cleared. Researchers used shotgun sequencing of total DNA extracted from stool samples to characterize gut microbiome composition. They also measured concentrations of inflammatory cytokines and other blood markers from plasma to relate gut microbial changes to immune dysfunction.
The study drew on a two-hospital cohort of 100 patients with laboratory-confirmed SARS-CoV-2 infection, from whom blood, stool, and patient records were collected. Serial stool samples were collected from 27 of these 100 patients for up to 30 days after clearance of the virus, allowing the researchers to track whether microbiome changes persisted or resolved over time.
Gut microbiome composition was significantly altered in patients with COVID-19 compared with non-COVID-19 individuals, regardless of whether patients had received medication. Several gut commensals with known immunomodulatory potential, including Faecalibacterium prausnitzii, Eubacterium rectale, and bifidobacteria, were underrepresented in patients with COVID-19. These organisms remained depleted in stool samples collected up to 30 days after disease resolution, indicating the perturbation did not quickly correct itself.
The persistence of a disturbed gut microbiome for weeks after viral clearance suggests COVID-19 related gut dysbiosis is not merely a transient bystander effect of infection. Because the depleted organisms, including Faecalibacterium prausnitzii, are known for anti-inflammatory and immunomodulatory functions, their loss may contribute to dysfunctional immune responses seen in the disease. This points to the gut microbiome as a potential factor in COVID-19 severity and recovery, meriting further investigation as a target for monitoring or intervention.
This study examined how three very different diets, an omnivore diet, a vegan diet, and a fiber-free synthetic enteral nutrition (EEN) diet, affect the human gut microbiome and its metabolome over time. The researchers performed a longitudinal analysis linking gut microbiota composition to fecal metabolite production, and also assessed how these dietary shifts affected the plasma metabolome. The design included a microbiota depletion intervention, allowing the team to observe microbiome and metabolome recovery under each diet.
The abstract does not specify a cohort size, age range, or other demographic details. Based on the study design described, the population appears to consist of individuals following one of three defined diets (omnivore, vegan, or EEN) who underwent a microbiota depletion intervention followed by longitudinal sampling of stool and plasma. No further participant characteristics are given in the abstract.
Omnivore and vegan diets, but not the fiber-free EEN diet, altered fecal amino acid levels by promoting the growth of Firmicutes capable of amino acid metabolism. This shift correlated with changes in a substantial number of fecal amino acid metabolites, including some not previously linked to the gut microbiota. In contrast, the effect of diet on the plasma metabolome was comparatively modest.
The findings indicate that dietary fiber plays a key role in shaping which gut bacteria recover and thrive after microbiota disruption, particularly Firmicutes involved in amino acid metabolism. Because these microbially driven metabolite changes were far more pronounced in stool than in plasma, the results suggest diet's influence on host-relevant metabolites may act primarily at the level of the gut rather than systemic circulation. This underscores fiber's broader role in shaping microbiome-derived metabolite classes that could affect host health.
This study examined the relationship between SARS-CoV-2 infection and the upper respiratory tract (URT) microbiome. Researchers compared the URT microbiome of adults infected with SARS-CoV-2 to that of uninfected adults. They also examined whether SARS-CoV-2 viral load was associated with features of the URT microbiome during COVID-19. The URT microbiome was characterized using 16S ribosomal RNA sequencing, and models examined alpha-diversity, beta-diversity, and bacterial taxa abundance.
The study included 59 adults. Of these, 38 had confirmed, symptomatic, mild to moderate COVID-19, and 21 were asymptomatic, uninfected controls. SARS-CoV-2 viral load was measured by quantitative reverse transcription PCR in those with COVID-19. All main models were adjusted for age and sex.
The observed species index, a measure of bacterial richness, was significantly higher in SARS-CoV-2-infected adults than in uninfected adults (beta coefficient = 7.53, 95% CI 0.17 to 14.89, P = .045). Differential abundance testing identified nine amplicon sequence variants that were significantly different across the comparisons performed. These findings indicate that SARS-CoV-2 infection status is associated with measurable shifts in URT bacterial community composition and richness.
The findings suggest that SARS-CoV-2 infection and its viral load are linked to detectable changes in the upper respiratory tract microbiome. This raises the possibility that the URT microbiome could serve as a marker of infection or disease dynamics in COVID-19. Further research building on these associations could help clarify how the respiratory microbiome interacts with viral infection and whether it holds diagnostic or prognostic value.
This study used 16S rRNA gene sequencing on rectal swabs to characterize the gut microbiota of patients with COVID-19 pneumonia. It compared microbial composition and diversity across two groups of infected patients against healthy controls. The goal was to determine whether gut microbiota composition differed with COVID-19 pneumonia and its severity.
The study compared COVID-19 pneumonia patients admitted to an intensive care unit (i-COVID19) and those admitted to infectious disease wards (w-COVID19) against a control group (CTRL). Exact sample sizes are not given in the abstract. The comparison design indicates a clinical cohort stratified by disease severity rather than a single uniform population.
i-COVID19 patients showed a decrease in the Chao1 index compared to both CTRL and w-COVID19 patients, indicating lower microbial richness in the ICU group, while Shannon Index diversity did not differ. At the phylum level, Proteobacteria increased in w-COVID19 patients compared to CTRL. Fusobacteria and Spirochetes decreased overall, with Spirochetes specifically reduced in i-COVID19 patients relative to CTRL.
These preliminary findings show that gut microbial communities shift significantly in COVID-19 pneumonia and vary with disease severity. The authors suggest these microbial changes could serve as promising biomarkers for diagnosis. If validated in larger cohorts, this approach could help stratify COVID-19 patients by severity using gut microbiota profiles.
This study examined the composition of gut microbiota in the third trimester of pregnancy to characterize how it differs in women with gestational diabetes mellitus (GDM) compared to healthy pregnant women. Researchers sequenced the V3-V4 regions of the 16S ribosomal RNA gene from stool samples to profile bacterial taxa at multiple levels, including phylum and species. The aim was to identify specific gut flora associated with GDM that could inform future use of intestinal microecological agents as a treatment approach.
The study included 52 singleton pregnant women who were more than 28 weeks into gestation. Stool samples were collected from these women and divided into comparison groups, including a normal (NOR) group versus a GDM group, as well additional groupings referred to as G and LG. The abstract does not provide further demographic detail such as age, geographic location, or recruitment setting.
Significant differences emerged between the NOR and GDM groups, and between the G and LG groups, in the relative abundance of Bacteroides, Firmicutes, and the Firmicutes/Bacteroides ratio. At the species level, eight species differed significantly in abundance between the NOR and GDM groups. Notably, Clostridium_spiroforme, Eubacterium_dolichum, and Ruminococcus_gnavus were positively correlated with fasting blood glucose (FBG), while Pyramidobacter_piscolens was negatively correlated with FBG.
These findings support the idea that distinct gut microbial signatures accompany gestational diabetes in late pregnancy and track with fasting blood glucose levels. Identifying species positively and negatively correlated with FBG provides candidate microbial targets for further investigation. The authors frame this work as a basis for future clinical attempts to use intestinal microecological agents as a therapeutic strategy for GDM.
This study examined whether the gut microbiome carries a detectable signature of prediabetes, a stage preceding type 2 diabetes mellitus (T2D). Researchers sequenced the V1-V5 variable regions of the 16S rRNA gene to profile gut microbiota composition. They also measured fasting serum inflammatory biomarkers in the same participants. The goal was to identify robust microbial signatures that could aid early diagnosis and prevention of T2D.
The study analyzed two cohorts, one from India and one from Denmark, combining prediabetic and normoglycemic individuals. In total, 262 prediabetic subjects were compared against 275 normoglycemic subjects. This trans-ethnic design allowed the researchers to correct for a strong country-specific cohort effect and look for microbial patterns shared across both populations.
After correcting for cohort effects, 16 operational taxonomic units (OTUs) were enriched in normoglycemic subjects relative to those with prediabetes, including members of Prevotella9, Phascolarctobacterium, Barnesiella, Flavonifractor, Tyzzerella_4, Bacteroides, Faecalibacterium, and Agathobacter. Faecalibacterium, a genus that includes the anti-inflammatory, butyrate-producing species Faecalibacterium prausnitzii, was among the taxa depleted in prediabetic subjects. Conversely, 144 OTUs were found enriched in the prediabetic subjects, indicating a broader shift in community composition alongside the loss of these beneficial commensals.
The depletion of Faecalibacterium and other short-chain-fatty-acid-associated genera in prediabetes, observed consistently across two ethnically distinct cohorts, supports gut microbiota as a candidate early marker of metabolic disease risk. Because these signatures held after correcting for country-specific effects, they suggest a trans-ethnic microbial pattern rather than a population-specific artifact. This strengthens the rationale for using microbiome profiling in early prediabetes screening and for exploring interventions that restore anti-inflammatory, butyrate-producing commensals before progression to overt T2D.
This study examined how SARS-CoV-2 infection affects the gut microbiome, looking at both the bacteriome and the virome together. The researchers investigated whether gut bacterial and viral communities shift during COVID-19 infection and whether these shifts relate to disease severity. They also used a mouse COVID-19 model to test whether SARS-CoV-2 infection alone could reproduce similar gut microbial changes and to examine immune and infection-related gene expression in gut epithelial cells.
The human portion of the study involved a cohort of 13 COVID-19 patients in Beijing, China, compared with five healthy controls. Patients were further grouped by disease severity (mild to moderate versus severe) to compare gut bacteriome and virome composition. The findings from this human cohort were then replicated in a mouse model of COVID-19.
The gut virome and bacteriome of COVID-19 patients were notably different from those of healthy controls, with a bacterial dysbiosis signature marked by reduced diversity and viral shifts. Among patients, bacterial and viral composition differed by disease severity, though these differences were not entirely separable from the effect of antibiotics. Severe cases showed a greater abundance of opportunistic pathogens and were depleted for butyrate-producing groups of bacteria compared with mild to moderate cases. The mouse model confirmed virome differences and bacteriome dysbiosis from SARS-CoV-2 infection, alongside differential expression of immune and infection-related genes in gut epithelial cells.
The results suggest that SARS-CoV-2 infection measurably disrupts gut bacteriome and virome composition, not just respiratory tract microbiology. Because compositional signatures differed with severity, including depletion of butyrate-producing bacteria in severe cases, the gut microbiome may reflect or even contribute to disease severity and recovery. This points to the gut bacteriome and virome as a potential avenue for understanding COVID-19 progression and treatment outcomes, though the mixing of antibiotic effects with infection effects in the human cohort means further work is needed to disentangle these contributions.
This study examined changes in intestinal bacterial communities across healthy people, patients with inflammatory bowel disease (IBD), and patients with colorectal cancer (CRC). The researchers performed metagenome-wide association studies on fecal samples to characterize bacterial community structure, relative abundance, and functional predictions. They also analyzed differentially abundant bacteria and co-occurrence networks to compare the three groups.
The analysis drew on fecal metagenomic data from 290 healthy subjects, 512 IBD patients, and 285 CRC patients. Healthy and CRC data were obtained from the European Nucleotide Archive under several study accession numbers, while IBD patient data came from the Integrated Human Microbiome Project via the Human Microbiome Project Data Portal. This makes the cohort a large, multi-source pooled metagenomic dataset rather than a single newly recruited study population.
The bacterial community structure in both IBD and CRC patients differed significantly from that of healthy subjects. Notably, IBD patients showed low intestinal bacterial diversity, while CRC patients showed high intestinal bacterial diversity, a contrasting pattern between the two disease states. The abstract does not specify Faecalibacterium prausnitzii, butyrate, or other named commensals, so no claim is made about those organisms here.
The finding that IBD and CRC involve opposite directions of diversity change suggests these two diseases are associated with distinct, rather than uniform, disruptions of the gut microbiome. This distinction could help refine how metagenomic diversity and community structure are used to distinguish disease states from health and from each other. It also underscores the value of large, pooled public metagenomic datasets for characterizing disease-associated microbial signatures.
This study examined the microbiological composition of the intestines of people with ulcerative colitis (UC) compared with healthy individuals. UC is an inflammatory disease affecting the colon and rectum, and the authors note that the role of intestinal microbiota in its pathogenesis has been incompletely characterized. The researchers used sequencing on the IonTorrent PGM system followed by data analysis to profile bacterial genera and species. They specifically framed the work as addressing a gap in comprehensive data on the microbial composition of UC patients in Russia.
The study compared patients with ulcerative colitis to a control group of healthy individuals, with intestinal samples analyzed from both groups. The abstract does not give an exact number of participants, so no specific cohort size can be stated. The population is described as being from the Central European part of Russia, addressing what the authors describe as a lack of prior microbiological data on UC patients in that country.
Sequencing revealed significant changes in bacterial genera and species in UC patients compared with controls. Several genera were significantly increased in UC patients, including Haemophilus, Olsenella, Prevotella, Cedecea, Peptostreptococcus, Faecalibacterium, Lachnospira, Negativibacillus, and Butyrivibrio. Species-level increases included Bacteroides coprocola, Phascolarctobacterium succinatutens, Dialister succinatiphilus, Sutterella wadsworthensis, and Faecalibacterium prausnitzii. Notably, F. prausnitzii, an organism often associated with butyrate production and anti-inflammatory commensal activity, was found elevated rather than depleted in these UC patients.
The findings suggest that ulcerative colitis in this Russian cohort is associated with distinct shifts in gut microbial genera and species relative to healthy controls, expanding the geographic evidence base for microbiota-UC associations. The unexpected increase in Faecalibacterium and F. prausnitzii, rather than the depletion sometimes reported elsewhere, highlights that microbial signatures in UC may vary by population and underscores the need for region-specific microbiome characterization. These results support continued investigation into the intestinal microbiota as a factor in UC pathogenesis rather than establishing a definitive causal mechanism.
This study examined whether HIV infection alters the gut fecal microbiome in children, and whether any such changes relate to immune status, viral load, and the type of pediatric antiretroviral therapy (ART) regimen used. Researchers characterized gut microbiome structure and function, looking at measures such as alpha diversity (within-sample diversity) and beta diversity (between-sample compositional differences). They also considered factors like prophylactic co-trimoxazole use and ethnicity or geography as potential influences on microbiome composition.
The study included 87 children living with HIV and 82 non-exposed, HIV-negative children, all from Yaounde, a cosmopolitan city in Cameroon. The HIV-infected children were on antiretroviral therapy, with some receiving ritonavir-boosted protease inhibitor (PI/r)-based regimens and others receiving non-nucleoside reverse-transcriptase inhibitor-based regimens. This design allowed comparison of gut microbiomes across HIV status and across different ART regimen types within the same geographic population.
Children living with HIV had significantly lower alpha diversity and altered beta diversity in their gut microbiome compared to HIV-negative children, and these differences did not appear to be explained by CD4+ T cell count or viral load. The HIV-infected children showed increased levels of Akkermansia and Faecalibacterium genera and decreased levels of Escherichia and other Gamma proteobacteria, among other compositional differences. Ethnicity or geography also appeared to influence gut microbiome composition, and children on PI/r-based ART had microbiome profiles that diverged more from HIV-negative controls than those on non-nucleoside reverse-transcriptase inhibitor-based ART.
The findings suggest that gut microbiome alterations in children with HIV are shaped not only by the infection itself but also by the specific antiretroviral regimen used, since PI/r-based ART was linked to greater divergence from HIV-negative microbiome profiles. Notably, the increase in Faecalibacterium, a genus known for anti-inflammatory, butyrate-producing commensals, alongside Akkermansia, indicates that HIV-associated microbiome shifts are more complex than a simple loss of beneficial taxa. The authors note that further studies are needed to investigate the role of this altered gut microbiome, pointing to an open area for future research on its functional and clinical significance in children with HIV.
This study examined whether the intestinal microbiome influences clinical outcome and treatment side effects in early breast cancer. Researchers used shotgun metagenomics to characterize fecal microbiota composition and paired this with plasma metabolomics. They looked at associations between the gut microbiota, measured at baseline and after chemotherapy, and both breast cancer prognosis and therapy-induced side effects. Findings were then tested for clinical relevance in an immunocompetent mouse model colonized with patient microbiota and challenged with mouse breast cancer and chemotherapy.
The human cohort consisted of 76 early breast cancer patients contributing 121 fecal specimens, with 45 patients providing paired samples collected before and after chemotherapy. These patients were enrolled in the CANTO prospective study, which was designed to record side effects associated with clinical management of breast cancer. The findings were further validated in immunocompetent mice colonized with breast cancer patient microbiota.
Specific gut commensals were found to be overabundant in breast cancer patients compared with healthy individuals. These overabundant commensals were associated with worse breast cancer prognosis. Chemotherapy modulated the abundance of these gut microbes, and the same microbes appeared to influence weight gain and neurological side effects linked to breast cancer therapies.
The results suggest that gut microbiota composition could serve as a modifiable factor affecting both cancer prognosis and treatment tolerability in early breast cancer. Because chemotherapy itself reshapes these microbial communities, monitoring or targeting the microbiome during treatment may offer a way to improve outcomes and reduce side effects. The authors note that these findings, obtained in adjuvant and neoadjuvant settings, warrant prospective validation before any clinical application.
This study evaluated the role of oral microbiota in colorectal cancer (CRC) progression by comparing bacterial communities in saliva and stool. Researchers used 16S rRNA analysis and next-generation sequencing to characterize both sample types. Linear discriminant analysis effect size (LEfSe) was applied to identify bacterial species that differed significantly between groups and across CRC stages.
The study included 52 patients with colorectal cancer and 51 healthy controls, with saliva and stool samples collected from each participant. CRC patients were further divided into an early-stage group (Stage I or II, n = 26) and an advanced-stage group (Stage III or IV, n = 26). This design allowed comparison not only between CRC patients and healthy subjects but also between disease stages.
Indigenous oral bacteria, including Peptostreptococcus, Streptococcus, and Solobacterium species, were present at significantly higher relative abundance in both saliva and stool of CRC patients compared with healthy controls. Among these, Peptostreptococcus stomatis, Streptococcus anginosus, Streptococcus koreensis, and Streptococcus moorei were identified as oral-cavity-derived species shared between the two body sites in CRC patients. Streptococcus moorei was further found at significantly higher relative abundance in advanced-stage (Stage III, IV) patients compared with early-stage (Stage I, II) patients, and this pattern held consistently in both saliva and stool samples.
The consistent presence of the same four oral-derived bacterial species in both saliva and stool of CRC patients supports a link between oral microbiota and gut microbiota in CRC. The stage-dependent enrichment of Streptococcus moorei suggests these oral bacteria may track with, or contribute to, CRC progression rather than merely being present. These findings raise the possibility that saliva-based microbial signatures could serve as accessible, non-invasive markers related to CRC status or stage.
This study examined the composition of gut microbiota in people with obesity compared to control subjects using 16S rRNA sequencing of fecal bacteria. The researchers analyzed differences in microbial diversity and abundance at multiple taxonomic levels, including the phylum level. They also used bioinformatics and statistical methods to predict functional potential changes in the microbiota associated with obesity.
The study compared 21 adults with obesity to 21 control subjects. The obesity group's fecal samples were sequenced on an Illumina MiSeq instrument, while the control group's raw sequencing data came from 21 healthy Beijing volunteers downloaded from the Microbial Genome Database System. Both groups therefore consisted of 21 individuals each, drawn from comparable population sources.
Gut microbiota diversity decreased significantly in people with obesity compared to controls. Significant differences between the two groups were found at multiple levels, including notable shifts in the phyla Firmicutes, Bacteroidetes, Actinobacteria, and Fusobacteria. Notably, the ratio of Firmicutes to Bacteroidetes decreased significantly in the obesity group, a reversal of the pattern often reported in prior obesity microbiome research.
These findings reinforce that gut microbiota composition and diversity are meaningfully altered in obesity, supporting the idea that the microbiome plays a role in this condition. The observed shift in the Firmicutes/Bacteroidetes ratio and changes in functional potential suggest that microbiota profiling could help characterize metabolic differences in people with obesity. This work adds to the evidence base motivating further investigation into gut bacteria as a factor in obesity and its associated health burden.
This study investigated the gut microbiota of people recovering from COVID-19 and examined whether specific bacterial taxa correlated with persistent symptoms after hospital discharge. Stool samples were collected three months after discharge and analyzed using 16S rRNA gene sequencing. The researchers compared bacterial diversity and relative abundance between recovered patients and healthy controls, then tested correlations between individual bacterial taxa and reported symptoms such as fatigue, myalgia, chest tightness, anorexia, and cough.
The study population consisted of 15 recovered healthcare workers (HCWs) who had been diagnosed with COVID-19, sampled three months after their hospital discharge. A comparison group of 14 healthy controls (HCs) provided stool samples over the same period, between May and July 2020. Both groups underwent 16S rRNA gene sequencing of their fecal microbiota.
Recovered HCWs had reduced bacterial diversity three months after discharge compared with healthy controls, along with a significantly higher relative abundance of opportunistic pathogens and a significantly lower relative abundance of beneficial bacteria. Escherichia unclassified was positively correlated with fatigue, chest tightness after activity, and myalgia, while Intestinibacter bartlettii was positively correlated with anorexia and fatigue. In contrast, Faecalibacterium prausnitzii was negatively correlated with chest tightness after activity, and Intestinimonas butyriciproducens (a butyrate producer) was negatively correlated with cough.
The findings suggest that gut microbiota alterations persist for months after COVID-19 recovery and are linked to ongoing physical symptoms, not just acute illness. The inverse correlations involving Faecalibacterium prausnitzii and the butyrate producer Intestinimonas butyriciproducens point toward a possible protective or anti-inflammatory role for these commensals against certain post-discharge symptoms. The authors conclude that gut microbiota may play an important role in the recovery process of COVID-19 patients, raising the possibility that microbiome status could help explain, or eventually be targeted to address, persistent post-COVID symptoms.
This study examined the gut microbiota of breast cancer patients according to menopausal status, focusing specifically on premenopausal breast cancer, which has been understudied compared to postmenopausal disease. The researchers assessed overall microbial diversity, community composition, and functional pathways. They also evaluated whether specific gut microbial markers could distinguish breast cancer patients by menopausal status and whether these markers had diagnostic value.
The study analyzed 267 breast cancer patients with different menopausal statuses (premenopausal and postmenopausal) along with age-matched female controls. The abstract notes that premenopausal breast cancer is a growing concern in Asian countries, where younger patients make up an increasing share of cases, in contrast to Western countries where breast cancer more often occurs in older postmenopausal women. Beyond the total cohort size, no further demographic or geographic details are given in the abstract.
Alpha-diversity of the gut microbiota was significantly reduced in premenopausal breast cancer patients, and beta-diversity differed significantly between breast cancer patients and controls. Through multiple analyses and classification approaches, the researchers identified 14 microbial markers that differed according to menopausal status in breast cancer. Notably, Bacteroides fragilis was specifically found in younger, premenopausal patients, while Klebsiella pneumoniae was specifically found in older, postmenopausal patients.
The findings suggest that gut microbial profiles in breast cancer are menopausal-status specific, meaning premenopausal and postmenopausal disease may involve distinct microbial signatures rather than a single uniform pattern. The identification of menopausal-specific microbial markers, such as Bacteroides fragilis in premenopausal patients, points toward potential diagnostic applications tailored to age and menopausal status. This underscores the need for future breast cancer microbiome research to separately account for premenopausal patients rather than focusing predominantly on postmenopausal disease.
This study examined the gut microbiome composition and function of people with irritable bowel syndrome (IBS) compared to healthy controls, using metagenomic sequencing of stool samples. The researchers aimed to identify microbial features that distinguish IBS and its subtypes from non-IBS individuals. They also tested whether a daily synbiotic supplementation intervention could shift the abundance of IBS-associated microbial features over time.
The study analyzed stool samples from 490 individuals with IBS, spanning all dominant IBS subtypes, and 122 individuals without IBS as controls. A subset of 134 IBS participants was followed longitudinally while receiving daily synbiotic supplementation, with the supplement composition varying between participants. This represents a comparatively large cohort for microbiome research on IBS symptom heterogeneity.
IBS participants had significantly lower alpha diversity, an enrichment in Gram-negative bacteria, and reduced pathways for short-chain fatty acid and vitamin synthesis compared to controls. Shigella species were significantly associated with IBS, while Eubacterium rectale and Faecalibacterium prausnitzii, both associated with anti-inflammatory, butyrate-related commensal activity, were associated with healthy controls instead. Random forest analysis identified microbial features unique to and shared across the different IBS subtypes. Among the 134 subjects followed over time, daily synbiotic supplementation did not change alpha diversity but did increase probiotic abundance and shift other microbial features.
The findings support a role for specific microbial imbalances, including depletion of beneficial commensals like Faecalibacterium prausnitzii and Eubacterium rectale and reduced short-chain fatty acid pathways, in distinguishing IBS from healthy states. The identification of subtype-specific and shared microbial features could help inform more targeted diagnostic or treatment approaches for IBS. However, since synbiotic supplementation increased probiotic abundance without restoring overall diversity, the authors note that further work is needed to determine whether these microbiome changes translate into actual improvement of IBS symptoms.
This study examined the gut microbiome composition of patients with young-onset colorectal cancer (yCRC), a form of sporadic colorectal cancer whose incidence is rising. Researchers used 16S rRNA gene sequencing to identify microbial markers distinguishing yCRC, then validated these findings in an independent cohort. Metagenome sequencing was also performed to characterize species-level and functional differences in bacterial communities associated with yCRC.
The discovery analysis drew on 728 samples analyzed by 16S rRNA gene sequencing. An independent validation cohort of 310 samples was used to confirm the identified microbial markers. A further subset of 200 samples underwent metagenome sequencing for species-level and functional analysis.
Gut microbial diversity was increased in yCRC compared to other groups studied. Flavonifractor plautii emerged as an important bacterial species associated with yCRC, whereas the genus Streptococcus contained the key phylotype linked to old-onset colorectal cancer. Functional analysis showed that yCRC-associated bacterial communities were distinguished by a dominance of DNA binding and RNA-dependent DNA biosynthetic processes, and a random forest classifier built on these microbial features achieved strong classification performance.
The findings suggest that gut microbiota biomarkers, particularly Flavonifractor plautii abundance and associated functional signatures, could serve as a non-invasive tool for detecting and distinguishing yCRC. This approach could help address the diagnostic gap for younger patients as sporadic colorectal cancer incidence rises in this age group. The distinct microbial and functional profile of yCRC versus old-onset colorectal cancer also points to potentially different underlying disease biology between the two age groups.
This prospective cohort study compared the composition of gastrointestinal microbiota between patients with Parkinson's disease (PD) treated only with Levodopa and healthy controls. Fecal samples were collected from all participants and analyzed using Next-Generation Sequencing to assess microbiota composition. The study's endpoint was the difference in gut microbiota composition between the two groups, motivated by the idea that the gut microbiome and colonic inflammation may be associated with PD predisposition and progression.
The study enrolled 27 hospitalized PD patients with well-controlled symptoms, recruited at a single academic hospital between July 2019 and July 2020. The control group consisted of 44 healthy subjects matched for age. Demographic data and medical history were collected from all participants using a set of questionnaires.
PD patients showed a higher abundance of the Bacteroides phylum, the class Corynebacteria within phylum Actinobacteria, and the class Deltaproteobacteria within phylum Proteobacteria. Genera more abundant in PD patients included Butyricimonas, Robinsoniella, and Flavonifractor. At the species level, Akkermansia muciniphila, Eubacterium biforme, and Parabacteroides merdae were identified as more common in the gut microbiota of PD patients compared with healthy controls.
The findings indicate that patients with PD have a distinct gut microbiota composition compared to healthy, age-matched controls. This distinct microbial signature, spanning multiple phyla, classes, genera, and species, supports the broader hypothesis that gut microbiome alterations are linked to PD. These differences may serve as a basis for future research into the gut microbiome's role in PD predisposition and progression, though the abstract does not describe specific mechanistic or clinical applications.
This study examined how gut microbiota composition changes after stroke and whether those changes relate to functional recovery. Researchers compared fecal microbial diversity, composition, and species cooccurrence between stroke patients and healthy controls. They used 16S rRNA gene sequencing (V3-V4 regions) on the Illumina MiSeq platform to characterize the bacterial communities. Random forest and receiver operating characteristic analyses were then applied to identify bacterial genera that might serve as diagnostic biomarkers linked to poststroke outcomes.
The cohort consisted of thirty-eight patients who had experienced a stroke and thirty-five healthy controls matched to the patients by demographics. Fecal DNA was extracted from all participants for microbial sequencing. This was a prospective cohort study comparing a clinical stroke population against a demographically similar healthy comparison group.
Poststroke patients showed significantly higher alpha diversity of gut microbiota than healthy controls. Beta diversity analysis confirmed that overall microbiota composition differed significantly between the two groups. At the genus level, nine genera increased significantly in abundance in poststroke patients, while eighty-two genera decreased significantly, indicating a broad and pronounced shift in the gut microbial community following stroke.
The findings support the existence of a distinct poststroke gut microbiota signature linked to the gut-microbiota-brain axis. Because specific bacterial genera were identified as potential discriminant markers with ties to functional outcomes, gut microbiota profiling may eventually help predict or monitor functional recovery after stroke. This adds to evidence that stroke does not just affect the brain but is accompanied by substantial, measurable disruption of the gut microbial ecosystem.
This study examined whole metagenome sequences of cecum microbiomes from Ethiopian indigenous chickens raised at two different altitudes. Researchers compared microbial community composition, functional gene pathways, and antibiotic resistance gene abundance between the two locations. Functional profiling used the KEGG, eggNOG, and CAZy databases, and taxonomic differences were identified using LEfSe.
The subjects were Ethiopian indigenous chickens sampled from two distinct geographical zones: the Afar district (Dulecha, 730 meters above sea level) and the Amhara district (Menz Gera Midir, 3300 meters above sea level). The abstract does not give an exact number of birds sampled, so the cohort is best described as cecum microbiome samples drawn from these two altitude-defined chicken populations.
Cecum microbial populations in both groups were mainly dominated by Bacteroidetes and Firmicutes, and the two groups shared 2210 common genes. Coprobacter, Geobacter, Cronobacter, Alloprevotella, and Dysgonomonas were more abundant in the low-altitude Afar chickens than in the high-altitude Amhara chickens. Functional pathway analysis showed enrichment in metabolism, genetic information processing, environmental information processing, and cellular process categories, and this functional abundance was linked to nutrient absorption and microbial localization. Antibiotic resistance genes for LSM, cephalosporin, and tetracycline were significantly more abundant in the Afar (low-altitude) group than in the Amhara (high-altitude) group.
The findings suggest that altitude and geographic location are associated with meaningful shifts in gut microbial composition, function, and antibiotic resistance gene burden in indigenous chickens. The higher abundance of resistance genes at lower altitude raises questions about environmental or management factors that could influence antibiotic resistance in poultry gut microbiomes. These results provide a baseline for understanding how environment shapes microbiome-linked traits relevant to poultry health and food safety in indigenous chicken populations.
This study examined whether gut microbiota composition in young children and their mothers is associated with different environmental exposures in a low-income, rural setting. Researchers analyzed faecal samples using 16S rRNA sequencing to characterize bacterial OTU and genus abundances, microbiota maturity, diversity, and UniFrac distances. Environmental exposure variables considered included socio-economic status, water source, sanitary facility, presence of domestic animals, maternal characteristics, season, antibiotic use, and delivery mode. The guiding hypothesis was that more adverse environmental exposures would correspond to lower microbiota maturity and diversity.
The study drew on faecal samples from up to 631 children and their mothers participating in a nutrition intervention trial in rural Malawi. Children were sampled longitudinally at 1, 6, 12, 18, and 30 months of age, while mothers were sampled at 1 month after their child's birth. This is a population from a low-income setting where childhood malnutrition is common, a context the authors note has been understudied for microbiota-environment relationships.
The abstract text describing the results is truncated, so specific quantitative findings on microbiota maturity and diversity in children cannot be reported here. What is stated is that measures of microbiota maturity and diversity in children were examined in relation to the listed environmental exposures using comparisons of OTU and genus abundances and UniFrac distances. No mention of Faecalibacterium prausnitzii, butyrate, or specific anti-inflammatory commensals appears in the provided abstract text.
By linking specific environmental exposures, such as water source, sanitation, domestic animal contact, and antibiotic use, to gut microbiota development in early childhood, this work supports the idea that environmental conditions shape microbiota maturation in low-income settings. Because childhood malnutrition is common in this population, understanding these environment-microbiota relationships could inform strategies to support healthier microbiota development during a critical early-life window. The longitudinal, multi-timepoint design in both children and mothers also provides a framework for tracking how exposures and microbiota composition evolve together over the first years of life.
This study investigated the gut microbiome of renal transplant recipients (RTRs) using 16S rRNA sequencing. The researchers compared the composition of the gut microbiome in RTRs to that of healthy controls. They also aimed to identify clinical and treatment-related determinants of the gut microbiome in RTRs, using multivariate association with linear models (MaAsLin).
The study included 139 renal transplant recipients (50% male, mean age 58.3 plus or minus 12.8 years) and 105 healthy controls (57% male, mean age 59.2 plus or minus 10.6 years). Participants were drawn from the TransplantLines Biobank and Cohort Study (NCT03272841). The median time since transplantation among RTRs was 6.0 years (range 1.5 to 12.5 years), and fecal samples were collected from all participants.
The gut microbiome composition of RTRs differed significantly from that of healthy controls, and RTRs showed lower microbial diversity (p less than 0.01). Proton-pump inhibitors, mycophenolate mofetil, and estimated glomerular filtration rate (eGFR) were identified as significant determinants of the gut microbiome in RTRs (p less than 0.05). The abstract text provided is truncated after introducing mycophenolate, so further specific findings beyond these associations are not available.
These findings indicate that renal transplantation is associated with measurable intestinal dysbiosis, likely driven by immunosuppressive drugs, other medications such as proton-pump inhibitors, and kidney function itself. Identifying mycophenolate mofetil and proton-pump inhibitor use as determinants of gut microbiome alterations suggests these exposures may be modifiable targets for future study. Understanding this dysbiosis could inform strategies to monitor or manage gut health in transplant recipients over the long term.
This study examined the relationship between the gut microbiota and psychiatric symptom severity among inpatients with serious mental illness. Researchers used 16S rRNA gene sequencing and whole genome shotgun sequencing to characterize fecal samples collected early in hospitalization. They then tested whether microbial richness and alpha diversity were associated with depression, anxiety, trauma, and suicide severity measures, and whether these microbial features predicted treatment outcome at discharge.
The study population consisted of 111 adult inpatients with serious mental illness. Diagnoses, suicide severity, trauma, depression, and anxiety were assessed shortly after admission. Participants self-collected fecal swabs early in the course of their hospital stay for microbiota analysis.
Depression and anxiety severity shortly after admission were negatively associated with bacterial richness and alpha diversity, meaning more severe symptoms corresponded to a less rich and less diverse gut microbiota. Specific bacterial taxa were identified as associated with depression and anxiety severity. Gut microbiota richness and alpha diversity measured early in hospitalization also significantly predicted depression remission by the time of discharge.
The findings support a link between gut microbial diversity and psychiatric symptom severity in a clinical inpatient population, extending prior evidence from animal models and small human studies. Because early microbiota measures predicted depression remission at discharge, gut microbiota composition may hold value as a marker of treatment response in serious mental illness. This strengthens the rationale for further investigating the brain-gut relationship as a factor in psychiatric care and outcomes.
This study examined the gut microbiome of Mexican children using two complementary methods: metatranscriptomic sequencing to characterize gene expression, and 16S rRNA profiling to characterize microbial community composition. The researchers focused specifically on defining the "Secrebiome," the subset of expressed microbial genes predicted to encode secreted (excreted) proteins, since these secreted proteins can shape microbial colonization and host-microbiota immune interactions. The comparison was made across children with normal weight, obesity, and obesity with metabolic syndrome.
The study population was Mexican children divided into three groups: normal weight (NW), obesity (O), and obesity with metabolic syndrome (OMS). The abstract does not provide exact sample sizes, ages, or recruitment details for these groups. Beyond identifying the children as the three named weight/metabolic categories, no further demographic specifics are given in the abstract.
Of 115,712 metatranscriptome genes encoding proteins, 30,024 (26%) were predicted to be secreted, constituting the Secrebiome of the gut microbiome. The 16S rRNA profiling confirmed increased Firmicutes and decreased Bacteroidetes abundance in the obesity groups compared with normal weight children. The obesity groups also showed significantly higher microbial richness and diversity than the normal weight group. The study additionally identified novel candidate biomarkers associated with obesity with metabolic syndrome.
By characterizing the actively expressed secreted-protein repertoire of the gut microbiome rather than just its taxonomic composition, this work adds a functional layer to understanding how gut bacteria may influence obesity and metabolic syndrome in children. The confirmed Firmicutes/Bacteroidetes shift and altered diversity reinforce compositional signatures already linked to obesity, while the newly defined Secrebiome offers a novel avenue for biomarker discovery. These secreted-protein candidates could eventually inform diagnostic or mechanistic research into pediatric obesity and metabolic syndrome, pending further validation.
The study characterised the relationships between gut microbiome composition, serum and faecal metabolites (including uraemic toxins and secondary bile acids), and clinical symptoms in end-stage renal disease (ESRD). Researchers used multidimensional data integration across microbiome, metabolome, and phenotype datasets to identify links between microbial functions and toxin accumulation. They then tested these relationships mechanistically using chronic kidney disease (CKD) rodent models, transplanting patient-derived microbiota into germ-free mice and antibiotic-treated rats to assess effects on toxin production and disease severity.
The human portion of the study included a cohort of 223 patients with end-stage renal disease (ESRD) and 69 healthy controls. Gut microbiome, serum, and faecal metabolome data were collected from these individuals. The mechanistic portion of the study used renal-injured germ-free mice and antibiotic-treated rats as recipients of human-derived microbiota, rather than additional human subjects.
A specific group of microbial species was enriched in ESRD patients and correlated tightly with clinical variables, and these species encoded functions involved in synthesizing uraemic toxins and secondary bile acids. The abundance of these microbial functions correlated with the serum and faecal concentrations of the corresponding metabolites. When microbiota from ESRD patients were transplanted into renal-injured germ-free mice or antibiotic-treated rats, the animals showed higher serum uraemic toxin production and more severe renal fibrosis and oxidative stress compared to animals receiving control microbiota. Two specific species, including Eggerthella lenta, were highlighted among those enriched in ESRD.
The findings support a causal role for specific gut microbial species and their toxin-synthesizing functions in driving uraemic toxin accumulation and worsening renal injury, rather than the microbiome shift being merely a byproduct of kidney failure. This suggests that targeting these microbial species or their metabolic pathways could be a strategy to reduce toxin burden and slow renal fibrosis in ESRD patients. The transplantation experiments in rodents strengthen the case that gut-derived microbial functions have a direct, testable effect on host kidney disease severity.
This study examined whether gut microbiota alterations previously linked to HIV are actually explained by sexual practice, since sexual practice is a known source of microbiota variation. The researchers compared gut microbiota composition between antiretroviral-treated persons with HIV (PWH) and seronegative controls, using a design that matched participants for age, body-mass index, sex, and sexual practice to remove these as confounders. They then related the resulting HIV-associated microbiota pattern to inflammatory markers and age-associated noncommunicable comorbidities.
Participants were drawn from the AGEhIV Cohort, specifically a well-powered subset of antiretroviral-treated PWH and HIV-seronegative controls. Controls were matched to the PWH group for age, body-mass index, sex, and sexual practice, including men who have sex with men (MSM) and individuals reporting receptive anal intercourse. The abstract does not give an exact number of participants.
Gut microbiota differences in PWH were significant regardless of sex and sexual practice, including enrichment of Gammaproteobacteria, depletion of Lachnospiraceae and Ruminococcaceae, and decreased alpha diversity. Separately, MSM showed a distinct microbiota signature marked by Prevotella enrichment and increased alpha diversity, which was linked to receptive anal intercourse in both males and females. The HIV-associated microbiota signature also correlated with inflammatory markers such as suPAR, with nadir CD4 count, and with the prevalence of age-associated noncommunicable comorbidities.
By matching for sexual practice, the study shows that HIV-associated gut dysbiosis is not simply a byproduct of sexual behavior but a distinct feature of treated HIV disease itself. The depletion of commensal families like Lachnospiraceae and Ruminococcaceae alongside Gammaproteobacteria enrichment suggests a loss of beneficial gut bacteria that coincides with inflammation and comorbidity risk. This supports the idea that gut microbiota alterations in PWH are clinically relevant markers linked to chronic inflammation and noncommunicable disease burden, separate from sexual practice-related signatures like the Prevotella-enriched MSM pattern.
This study examined changes in the fecal (gut) microbiome of patients hospitalized with COVID-19 over the course of their illness. Researchers used shotgun metagenomic sequencing to profile fecal samples collected repeatedly during hospitalization, from admission until discharge. The aim was to determine whether gut microbiome composition tracked with disease severity and with fecal shedding of SARS-CoV-2. Comparisons were made against patients with community-acquired pneumonia and against healthy individuals.
The study population was 15 patients with confirmed COVID-19 who were hospitalized in Hong Kong between February 5 and March 17, 2020. Fecal samples were collected two or three times per week from each patient from hospitalization through discharge. Disease severity among these patients was categorized as mild, moderate, severe, or critical based on respiratory and clinical criteria. Two comparison groups were also included: 6 subjects with community-acquired pneumonia and 15 healthy individuals serving as controls.
Patients with COVID-19 showed significant alterations in their gut microbiome composition compared to both the community-acquired pneumonia group and the healthy controls, as stated in the abstract. Gut microbiome profiles were assessed in relation to disease severity and to fecal shedding of SARS-CoV-2, indicating that microbiome features were linked to both the clinical course of infection and viral persistence in stool. The abstract does not provide the specific taxa, effect sizes, or statistical values underlying these associations, so no individual organisms or magnitudes can be reported here.
The findings suggest that the gut microbiome may be an active participant in, or at least a marker of, COVID-19 severity and gastrointestinal viral shedding rather than a passive bystander. This raises the possibility that gut microbiome status could eventually inform monitoring of disease course or duration of fecal viral shedding during hospitalization. Because the abstract text is truncated and does not detail specific taxa or mechanisms, any therapeutic implications remain speculative and would need confirmation from the full results section.
This cross-sectional study used shotgun metagenomic sequencing of fecal samples to identify differences in gut microbial species between women with polycystic ovary syndrome (PCOS) and controls. The researchers also collected clinical parameters, including body mass index, endocrine hormone levels, and glycemia, to test for correlations with the gut microbiota. The aim was to reveal a possible relationship between gut dysbiosis and the pathological changes seen in PCOS.
The study included reproductive-aged women with PCOS (n = 14) and healthy controls (n = 14), recruited from the Centre for Reproductive Medicine at an academic institution. Fecal samples from these 28 women underwent shotgun metagenomic sequencing, and their clinical data were gathered for correlation analysis.
Several microbial strains, including Parabacteroides merdae, Bacteroides fragilis, and strains of Escherichia and Shigella, were significantly more abundant in the PCOS group. In contrast, Faecalibacterium prausnitzii, a butyrate-producing, anti-inflammatory commensal, was enriched in the control group rather than in PCOS. Metagenomic species analysis showed that the microbial profiles of the PCOS group were negatively correlated with those of the control group. Notably, PCOS-associated microbial species were positively correlated with endocrine disorders, including higher body mass index and elevated serum testosterone levels.
These findings support a link between gut dysbiosis and the metabolic and endocrine disturbances characteristic of PCOS. The depletion of Faecalibacterium prausnitzii alongside enrichment of Parabacteroides merdae, Bacteroides fragilis, Escherichia, and Shigella suggests a shift away from anti-inflammatory commensals toward potentially pro-inflammatory or opportunistic organisms. The correlation between these microbial changes and elevated testosterone and body mass index points to the gut microbiome as a possible contributor to, or biomarker of, PCOS pathology.
This pilot study examined whether gut microbiome disturbances, gut barrier dysfunction, bacterial translocation, and resulting inflammation are associated with cognitive dysfunction in dementia. Researchers assessed gut microbiome composition, gut barrier integrity, bacterial translocation markers, and inflammatory markers using stool and serum samples. Microbiome composition was profiled through 16S rRNA sequencing, with analysis performed using QIIME 2 and Calypso 7.14 tools. Nutritional status and medication use were also documented to characterize the study population.
The study included 23 patients with dementia and 18 age and sex matched controls without cognitive impairment. Nutritional status was assessed in participants using the Mini Nutritional Assessment Short Form (MNA-SF). Detailed information on drug use was also collected from the cohort. This was a relatively small, matched case control pilot study rather than a large population based investigation.
Dementia was associated with dysbiosis, reflected in differences in beta diversity and shifts in taxonomic composition of the gut microbiome compared to controls. Gut permeability was increased in dementia patients, as shown by elevated serum diamine oxidase (DAO) levels. Systemic inflammation was also confirmed, evidenced by increased soluble cluster of differentiation 14 levels. The abstract does not report findings specific to Faecalibacterium prausnitzii, butyrate, or anti-inflammatory commensals.
These findings support the hypothesis that gut microbiome disturbances, impaired gut barrier function, and resulting systemic inflammation may contribute to cognitive dysfunction in dementia. The results suggest a potential gut-brain axis mechanism linking dysbiosis and barrier dysfunction to the inflammatory processes implicated in cognitive decline. As a pilot study with a modest sample size, these findings point toward the need for larger studies to confirm causal relationships and explore microbiome-targeted interventions for dementia.
This study examined the fecal gut microbiota in people with schizophrenia (SZ) and compared it to that of demographically matched healthy individuals. Researchers used 16S rRNA sequencing to characterize microbial community composition at the phylum and genus levels. They then looked for correlations between the altered gut microbiota and the severity of schizophrenia symptoms. The work sits within the broader microbiome-gut-brain axis framework, which links gut microbial composition to mental health and psychiatric disease.
The study population consisted of 82 patients diagnosed with schizophrenia and 80 demographically matched normal controls. The two groups were matched to allow for a direct comparison of gut microbiota differences attributable to schizophrenia rather than to age, sex, or other demographic factors. Fecal samples from these 162 individuals were profiled using 16S rRNA sequencing.
Alpha diversity (within-sample richness) did not differ significantly between the schizophrenia and control groups, but beta diversity showed clear separation in overall microbiome composition between the two groups. At the phylum level, the schizophrenia group had relatively more Actinobacteria and less Firmicutes than controls. At the genus level, several taxa, including Collinsella, Lactobacillus, Succinivibrio, Mogibacterium, Corynebacterium, and undefined Ruminococcus and Eubacterium, were significantly increased in the schizophrenia group, while Adlercreutzia and other genera were decreased. These compositional shifts were correlated with the severity of schizophrenia symptoms, though the abstract does not mention Faecalibacterium prausnitzii, butyrate, or anti-inflammatory commensals specifically.
The findings support the idea that gut microbiota composition differs systematically in schizophrenia and may track with how severe a patient's symptoms are. This raises the possibility that specific bacterial taxa could eventually serve as biomarkers to aid diagnosis or monitoring of schizophrenia. Because overall community structure (beta diversity) differed even without a change in richness (alpha diversity), the results point toward the pattern of which organisms are present, not simply how diverse the community is, as the more informative signal. Confirming and extending these associations could inform future microbiome-based approaches to understanding or managing schizophrenia.
This study characterized the gut microbiota of patients with advanced primary hepatocellular carcinoma (HCC) who received immune checkpoint inhibitors (ICIs). Researchers amplified and sequenced the 16S rDNA V4 region on the MiSeq platform to profile bacterial composition. The goal was to determine whether specific gut bacterial taxa relate to how patients respond to ICI treatment.
The study drew on an initial cohort of 65 patients with metastatic melanoma who were treated with ICIs at Fujian provincial geriatric hospital between August 2016 and June 2018. This cohort was used in the context of a larger Chinese population-based study of HCC patients with hepatitis B virus infection who received ICIs. Patients were later stratified into high versus low groups based on the median relative abundance of specific bacterial taxa in their gut microbiome.
Gut microbiota diversity was found to be notably increased in HCC patients who received ICIs, a pattern attributed to negative feedback between microbial metabolic activity and host pathways. The Faecalibacterium genus was highlighted in the response group, while the Bacteroidales order stood out in the non-response group. Patients with high Faecalibacterium abundance had significantly prolonged progression-free survival (PFS) compared to those with low abundance.
These findings suggest that gut microbiota composition, particularly Faecalibacterium abundance, may serve as a biomarker for predicting response and progression-free survival in HCC patients treated with immune checkpoint inhibitors. Because Faecalibacterium prausnitzii is a recognized butyrate-producing, anti-inflammatory commensal, its association with better outcomes points to a possible link between gut-derived anti-inflammatory activity and immunotherapy efficacy. This raises the possibility that modulating gut microbiota could become a strategy to improve ICI outcomes in liver cancer, though further studies are needed to establish causality.
This study examined the salivary microbiome to understand how type-2 diabetes mellitus (T2DM) and hypoglycemic (metformin) treatment alter oral bacterial communities in people with periodontitis. Researchers used 16S rRNA gene sequencing to profile saliva samples and identify shifts in microbial diversity and composition across disease states. They also explored whether specific salivary taxa could serve as an early biomarker for T2DM in periodontitis patients. In total, 29 phyla, 322 genera, and 333 species of salivary microbiome were annotated.
The study population consisted of saliva samples from five groups: healthy individuals, periodontitis patients, T2DM patients without periodontitis, periodontitis patients with T2DM (DAP), and DAP patients treated with metformin. The abstract does not specify exact sample sizes or demographic details for each group. This comparative, multi-group design allowed the researchers to isolate the effects of periodontitis, diabetes, and metformin treatment on the oral microbiome.
Periodontitis patients, with or without T2DM, showed significantly higher salivary microbial diversity than healthy individuals, while T2DM and metformin-treated groups showed no significant difference in abundance but a trend toward increasing diversity. Beyond well-known periodontitis-associated pathogens, Prevotella copri, Alloprevotella rava, and Ralstonia pickettii were significantly increased in periodontitis patients regardless of diabetes status. After effective glycemic control with metformin, the abundance of these taxa, including Prevotella copri, Alloprevotella rava, and Ralstonia pickettii, decreased in periodontitis patients with concurrent T2DM. Classification models were built to differentiate health, periodontitis, and diabetes-related groups based on these microbial signatures.
The findings suggest that specific salivary taxa such as Prevotella copri, Alloprevotella rava, and Ralstonia pickettii could serve as microbial indicators linking periodontitis and glycemic status. Because these taxa decreased after effective glycemic control, they may have potential as early warning biomarkers for T2DM in periodontitis patients. This points toward saliva-based microbiome monitoring as a noninvasive tool for tracking metabolic-periodontal interactions and treatment response. Further validation could support integrating salivary microbiome profiling into diabetes and periodontal disease management.
This pilot study examined whether the gut microbiota is linked to unintentional weight loss in Parkinson's disease (PD). Researchers profiled gut microbiota composition using 16S rRNA gene sequencing and applied KEGG functional predictions to infer the metabolic pathways associated with the bacterial communities present. The aim was to compare microbiota profiles and predicted functions between PD patients who had experienced weight loss and those who had not.
The study compared three groups: PD patients with unintended weight loss (WL), PD patients with steady weight (non-WL, or NWL), and matched normal (non-PD) subjects. The abstract does not report specific sample sizes for any of the three groups. It is described as a pilot study, indicating a small, exploratory cohort rather than a large-scale trial.
Gut microbiota profiles differed between the weight-loss (WL) and steady-weight (NWL) PD patients. Predicted functional pathways also diverged: the WL group's microbiota was characterized by fatty acid biosynthesis pathways, while the NWL group's microbiota was characterized by inflammation-related pathways. These findings suggest that distinct microbial functional signatures accompany different weight trajectories in PD.
The findings suggest the gut microbiota may actively participate in the weight changes observed in Parkinson's disease. This could occur through bacteria associated with weight gain and inflammation on one hand, or through bacteria linked to energy expenditure on the other. If confirmed in larger studies, gut microbiota profiling could help identify PD patients at risk of unintentional weight loss and point toward microbiome-targeted strategies to address it.
This study examined how a high-protein low-carbohydrate (HPLC) diet, compared with a standard control diet, affects the gut microbiome of domestic cats. Researchers used 16S rRNA gene profiling to track microbial composition across two feeding phases. The design compared responses between overweight and lean cats to see whether body condition changes how diet shapes gut microbiota.
The study enrolled thirty-nine lean and overweight domestic short-haired cats, with a median age of 7.2 years. Lean cats had a median body fat of 15.8%, while overweight cats had a median body fat of 32.5%. All cats first ate a control diet for 8 weeks, after which half continued on the control diet and half switched to the HPLC diet for another 8 weeks.
Dietary protein and carbohydrate ratio significantly impacted the gut microbiome, and this effect was more pronounced in overweight cats than in lean cats. No microbial taxon differed between diet groups among lean cats. In overweight cats, however, compositional changes occurred at multiple taxonomic ranks, including a phylum-level increase in Fusobacteria in cats fed the HPLC diet compared to those fed the control diet.
The findings suggest that body weight status influences how strongly diet reshapes the feline gut microbiome, with obese cats showing greater microbial sensitivity to macronutrient shifts than lean cats. This implies that high-protein low-carbohydrate diets recommended for weight management may have body-condition-dependent effects on gut microbiota. Further research is needed to determine whether these microbial shifts, such as the rise in Fusobacteria, carry functional or health consequences for obese cats undergoing dietary weight management.
This study examined whether the composition of the gut microbiota differs between children with acute lymphoblastic leukemia (ALL) and healthy children. Fecal samples were analyzed using 16S rRNA quantitative arrays combined with bioinformatics analysis. The researchers compared overall community structure using Principal Coordinates Analysis (PCoA) and Non-metric Multidimensional Scaling (NMDS), and then looked for individual bacterial species that distinguished the two groups.
The study included 81 subjects total, comprising 58 pediatric patients with acute lymphoblastic leukemia and 23 healthy children serving as controls. All participants provided fecal samples for microbiota analysis. The abstract does not specify additional demographic details such as age range, sex distribution, or geographic location.
PCoA and NMDS both showed that the microbial composition of ALL patients deviated from the tight cluster formed by healthy controls, indicating a distinct gut microbiota profile in disease. Multiple bacterial species showed significant changes in abundance in ALL samples, including Roseburia faecis, Edwardsiella tarda, and Fusobacterium naviforme. Some of these differentially abundant taxa were correlated with interleukin-10 levels, suggesting a link between microbiota shifts and immune signaling. A random forest model built on these differential species distinguished ALL cases from healthy controls with good accuracy (area under the ROC curve of 0.843).
The findings suggest that childhood ALL is accompanied by a characteristic, measurable alteration in the gut microbiota rather than a random or negligible shift. The correlation between specific taxa and interleukin-10 raises the possibility that these microbial changes are connected to immune regulation in ALL patients. The strong classification performance of the random forest model suggests gut microbiota profiling could eventually contribute to distinguishing ALL cases from healthy children, supporting further investigation into microbiota-based biomarkers for this disease.
This study examined the gut microbiome of pediatric patients with acute lymphoblastic leukemia (ALL) during treatment, focusing on its relationship to infectious complications. The researchers combined 16S rRNA gene profiling with metagenomic shotgun sequencing, an approach designed to capture both broad taxonomic shifts and finer functional differences encoded by individual bacterial species. This dual method addressed a gap in prior research, which had relied only on 16S rRNA profiling and could miss species-level functional variation. Infectious complications occurring within the first 6 months of therapy were the primary outcome of interest.
The study population consisted of an independent pediatric cohort of patients undergoing treatment for acute lymphoblastic leukemia. Stool samples were collected from these patients and analyzed using paired 16S rRNA and shotgun metagenomic sequencing. The abstract does not specify an exact number of participants or detailed demographic characteristics beyond the pediatric ALL treatment setting.
Patients who developed infectious complications within the first 6 months of therapy showed distinctive differences in both alpha diversity and beta diversity compared to those who did not. The metagenomic sequencing also identified specific bacterial species and functional pathways that differed significantly in relative abundance between the two groups. Machine learning models built on patient metadata and bacterial species data were able to classify samples according to infectious complication status with high accuracy.
The findings suggest that gut microbiome composition and function, not just broad taxonomic shifts, may be linked to infection risk during pediatric ALL treatment. Combining 16S rRNA and shotgun metagenomic sequencing offers a more complete picture of these microbial changes than taxonomic profiling alone. The high accuracy of machine learning classification raises the possibility that microbiome-based signatures could eventually help identify patients at greater risk for infectious complications during therapy.
This study examined the relationship between gut microbiome composition and childhood eczema using 16S rRNA gene sequencing. Researchers compared microbial profiles between healthy children and children with eczema, stratifying samples into four age groups (0-0.5, 0.5-1, 1-2, and 2-3 years) to account for developmental and environmental influences on the gut microbiome. Findings from sequencing were further verified using quantitative polymerase chain reaction targeting Bifidobacterium and Bacteroides.
The cohort included 172 subjects under age three, divided into a healthy group of 123 children and an eczema group of 49 children. Samples were further split across four narrower age brackets to examine how the microbiome-eczema relationship changed over early development. No further demographic or geographic details were given in the abstract.
Lower relative abundance of Bifidobacterium was associated with childhood eczema, though this difference was not significant in infants younger than six months old. From 0.5 to 3 years of age, decreased Bifidobacterium was a major and consistent finding in the eczema group compared to age-matched healthy controls. Decreased microbial diversity was also observed in eczema samples across all age groups, most significantly in children aged 2-3 years. Bifidobacterium operational taxonomic units showed strong predictive power for eczema status, with a Random Forest model achieving an AUC of 0.83 in ROC analysis.
The findings suggest that reduced Bifidobacterium levels in the gut, emerging after the first six months of life, may be linked to the development of childhood eczema. Because Bifidobacterium abundance showed high predictive accuracy for eczema status, it may serve as a candidate microbial marker for risk assessment in early childhood. The age-stratified design also indicates that timing matters: the microbiome-eczema association strengthens as children move past infancy, pointing to a developmental window relevant to future preventive or diagnostic strategies.
This study asked whether gut microbiome signatures linked to colorectal cancer (CRC) hold up reliably across different patient cohorts and populations. The researchers meta-analyzed fecal metagenomic sequencing data to identify microbial taxa and functional pathways that consistently distinguish CRC from controls. They also examined the microbiome's functional potential, comparing metabolic pathways such as gluconeogenesis, putrefaction, fermentation, and choline degradation between CRC and control samples. Finally, they built and tested predictive microbiome signatures for CRC diagnosis.
The analysis drew on 969 fecal metagenomes assembled from five publicly available datasets plus two newly collected cohorts, with findings further validated on two additional independent cohorts. The abstract does not specify demographic details such as age, sex, or geographic origin of participants. This design represents a large-scale, multi-population pooling of existing and new CRC and control stool metagenome datasets rather than a single defined patient group.
The gut microbiome in CRC showed reproducibly higher richness than in controls (P < 0.01), partly driven by expansions of species normally derived from the oral cavity. Functional meta-analysis linked gluconeogenesis and putrefaction/fermentation pathways to CRC, while stachyose and starch degradation pathways were associated with controls. A predictive microbiome signature trained across multiple datasets achieved consistently high accuracy in datasets and independent validation cohorts it had not been trained on, with an average area under the curve of 0.84. Pooled raw metagenome analysis also found the choline trimethylamine-lyase gene overabundant in CRC samples (P = 0.001), linking microbiome choline metabolism to CRC.
By validating microbial richness increases, specific functional pathway shifts, and a diagnostic signature across multiple independent cohorts, this study strengthens the case that gut microbiome-based biomarkers for CRC can generalize beyond a single population. The identification of an overabundant choline trimethylamine-lyase gene points to microbiome-driven choline degradation as a mechanistic link worth further investigation in CRC. The high, cross-cohort predictive accuracy (AUC 0.84) supports the feasibility of microbiome-based tools as non-invasive adjuncts for CRC screening or risk stratification.
This study examined how long-term cotrimoxazole prophylaxis reduces systemic inflammation in HIV infection, a known independent driver of HIV-related mortality. Researchers investigated whether cotrimoxazole's clinical benefits could be explained by changes in the gut microbiome and intestinal inflammatory biomarkers, since subclinical enteropathogen carriage and enteropathy can drive systemic inflammation. They also used in vitro models of systemic and intestinal inflammation to isolate direct immune effects of cotrimoxazole from its antibiotic effects on gut bacteria.
The study population was HIV-positive Ugandan and Zimbabwean children receiving antiretroviral therapy. Plasma inflammatory markers were compared between children randomized to continue cotrimoxazole (n = 144) versus stop it (n = 149). A smaller subset underwent gut microbiome and fecal biomarker analysis, with 36 children continuing cotrimoxazole compared to 36 stopping it.
Plasma inflammatory markers were lower in children who continued cotrimoxazole compared to those who stopped, and this difference was not explained by clinical illness, HIV progression, or nutritional status. Overall gut microbiome composition was unchanged, but viridans group Streptococci and streptococcal mevalonate pathway enzymes were lower among children continuing cotrimoxazole. These microbial changes were associated with lower fecal myeloperoxidase, an intestinal inflammatory biomarker, and in vitro experiments showed cotrimoxazole had modest but consistent direct inhibitory effects on proinflammatory cytokine production.
The findings suggest cotrimoxazole prophylaxis reduces systemic inflammation in HIV infection through a combination of altering specific gut bacterial populations and directly dampening immune activation, rather than through broad microbiome restructuring. Targeting streptococcal populations and intestinal inflammation, alongside direct anti-inflammatory drug effects, may be a mechanism underlying reduced HIV-related mortality and morbidity. This dual mechanism could inform strategies to further optimize prophylactic approaches in HIV-positive populations on antiretroviral therapy.
This study examined whether gut microbiome composition differs in people with fibromyalgia (FM), a syndrome marked by chronic widespread pain, fatigue, and impaired sleep. Researchers compared microbiome profiles using both 16S rRNA gene amplification and whole-genome sequencing. They also measured serum levels of the short-chain fatty acids butyrate and propionate to see whether metabolite changes tracked with any bacterial shifts. The design combined differential abundance analysis, variance analysis against clinical and environmental variables, and machine-learning classification.
The study population consisted of 77 women diagnosed with fibromyalgia and 79 control participants who were unrelated to the patients. Microbiome data came from stool samples analyzed by 16S rRNA sequencing and whole-genome sequencing, paired with targeted serum metabolite testing in the same participants. No further demographic or geographic details were given in the abstract.
Differential abundance analysis revealed significant differences in several bacterial taxa between FM patients and controls. Variance in microbiome composition was explained by FM-related variables more than by any other innate or environmental factor, and this variance correlated with clinical indices of FM. Consistent with alterations in butyrate-metabolizing bacterial species, serum levels of butyrate and propionate also differed in FM patients. Using machine-learning algorithms, microbiome composition alone classified patients versus controls with a receiver operating characteristic area under the curve of 87.8%.
This is described as the first demonstration of gut microbiome alteration in a nonvisceral pain condition, extending microbiome-disease links beyond gut-localized disorders. The strong classification performance suggests the microbiome could potentially serve as a diagnostic aid for fibromyalgia, a syndrome that is otherwise difficult to diagnose. The link to altered butyrate and propionate levels points toward specific metabolic pathways that may warrant further mechanistic study. The authors frame these findings as a foundation for future work on FM pathophysiology and possible new treatment approaches.
This study examined whether the composition of the intestinal microbiota is associated with treatment outcome in multiple myeloma (MM), specifically minimal residual disease (MRD) status after upfront treatment. Fecal samples were analyzed using 16S ribosomal RNA sequencing to characterize microbiota composition. Samples were collected after induction therapy and at the time of flow cytometry-based bone marrow MRD testing. The analysis also compared microbial relative abundance against autologous stem cell transplantation history and MM paraprotein isotype.
The study included 34 patients with multiple myeloma who had undergone induction therapy. Of these, 16 patients were classified as MRD-negative and 18 as MRD-positive based on bone marrow flow cytometry testing. All participants provided fecal samples for microbiota analysis. No further demographic details are given in the abstract.
MRD-negative patients showed a higher relative abundance of Eubacterium hallii compared with MRD-positive patients. No association was found between microbial relative abundance and either autologous stem cell transplantation history or MM paraprotein isotype. Additionally, no differences in microbiota alpha diversity were observed between the MRD-negative and MRD-positive groups. This suggests that specific taxa, rather than overall diversity, may relate to treatment response.
The findings point to a potential link between intestinal microbiota composition, particularly Eubacterium hallii abundance, and achieving MRD negativity in multiple myeloma. Since MRD negativity is associated with superior outcomes, this raises the possibility that the gut microbiome could serve as a biomarker or modifiable factor in MM treatment response. The authors frame this as a preliminary association warranting further correlative and clinical investigation rather than a definitive causal finding. Larger studies would be needed to confirm and clarify this relationship.
This study examined whether small RNA sequencing and shotgun metagenomic sequencing of stool could be combined to detect colorectal cancer (CRC). The researchers profiled both human small noncoding RNAs and bacterial small RNAs (bsRNAs) in stool, alongside DNA-based microbiome taxonomic data. They evaluated whether these small RNA profiles reflect gut microbiome composition and whether dysbiosis in CRC is detectable through altered small RNA patterns. The overall goal was to test the combined use of these data types as a predictive tool for disease detection.
The analysis used 80 stool specimens collected in a cross-sectional study. Samples came from patients with colorectal cancer, patients with adenomas, and healthy subjects. No further demographic or clinical details of the cohort are given in the abstract.
The researchers found considerable overlap and a correlation between metagenomic and bacterial small RNA (bsRNA) quantitative taxonomic profiles derived from the two sequencing approaches. They identified a combined predictive signature of 32 features drawn from human small RNAs, microbial small RNAs, and DNA-based microbiome data. This signature accurately classified CRC samples as distinct from healthy and adenoma samples, achieving an area under the curve (AUC) of 0.87. The findings show that host-microbiome dysbiosis in CRC can be observed through altered small RNA stool profiles, not just through standard microbiome sequencing.
The results suggest that integrating small RNA data (both human and bacterial) with microbiome DNA sequencing can improve noninvasive stool-based detection of colorectal cancer. Because bsRNA and metagenomic taxonomic profiles correlate, small RNA sequencing may serve as an additional or complementary readout of gut microbiome composition. The 32-feature combined signature points toward multi-omic stool panels as a promising direction for distinguishing CRC from adenomas and healthy states. This integrated approach may inform future noninvasive screening tools designed for earlier CRC detection.
This study examined how mode of delivery affects the earliest colonization of the infant gut microbiota during the neonatal period (up to one month of age) and into infancy. The researchers used longitudinal sampling combined with whole-genome shotgun metagenomic analysis to track which microbial strains and species established themselves in newborns over time. They specifically compared babies born by caesarean section to those born vaginally, and also looked at the effects of maternal antibiotic prophylaxis and breastfeeding status during the neonatal window.
The cohort comprised 596 full-term babies born in UK hospitals, from whom 1,679 gut microbiota samples were collected at multiple time points during the neonatal period and later in infancy. For a subset of these infant-mother pairs, matched maternal samples were also collected, totaling 175 mothers paired with 178 babies. This gave the study both a large infant sample size and a smaller nested set of mother-infant pairs for tracking strain transmission.
Babies delivered by caesarean section showed disrupted transmission of maternal Bacteroides strains, meaning these commensal organisms were less successfully passed from mother to infant compared to vaginal delivery. Caesarean-born infants also showed high-level colonization by opportunistic pathogens associated with the hospital environment, including Enterococcus, Enterobacter, and Klebsiella species. These same disruptions, though to a lesser extent, were also observed in vaginally delivered babies whose mothers received antibiotic prophylaxis and in infants who were not breastfed during the neonatal period.
The findings suggest that both caesarean delivery and antibiotic exposure around birth can independently disrupt the normal, low-risk colonization of the infant gut by maternal commensal strains. This disruption opens the door for opportunistic, hospital-associated pathogens to establish themselves early in life instead. Because early gut microbiota composition has been linked to later childhood and lifelong disease risk, these results point to birth mode, antibiotic use, and breastfeeding as modifiable factors that could be targeted to support healthier early microbiome establishment.
This study investigated the gut microbiome and metabolome in colorectal cancer (CRC) to test whether host-microbiome associations found in prior research, mostly from developed countries, also hold in a distinct population. Researchers performed metagenomic and metabolomic analyses of fecal samples, then compared their results with CRC microbiome data available from other populations. The focus was on identifying bacterial taxa and metabolic pathways linked to CRC in a setting where the disease has historically been rare.
The study analyzed fecal samples from 30 colorectal cancer patients and 30 healthy controls recruited from two different locations in India. This population was chosen specifically because India has a low incidence of colorectal cancer and a distinct diet, lifestyle, and gut microbiome compared to other global populations. Data from this Indian cohort were also compared against previously published CRC microbiome datasets from other countries.
The researchers confirmed that Bacteroides and other bacterial taxa already linked to CRC in earlier studies were also associated with CRC in this Indian cohort. A novel finding was the association of Flavonifractor plautii, a flavonoid-degrading bacterium, with CRC in these patients. This association correlated with enzymes and metabolic modules involved in flavonoid degradation, suggesting a link between the breakdown of beneficial anticarcinogenic flavonoids and the disease. The team also identified 20 potential microbial taxonomic markers and 33 potential microbial gene markers that distinguished CRC from healthy microbiomes with high accuracy using machine learning.
The findings suggest that loss of beneficial, flavonoid-degrading control (via F. plautii) may contribute to cancer progression in this Indian cohort, expanding the known microbial players beyond previously identified taxa like Bacteroides. Because India has unusually low CRC incidence alongside a distinct gut microbiome, these cohort-specific biomarkers may not generalize globally and highlight the need for population-specific microbiome research. The taxonomic and gene markers identified could also support development of noninvasive, microbiome-based diagnostic tools for CRC in diverse populations.
This study examined the composition of gut microbiota in pediatric patients with pulmonary tuberculosis (PTB) compared with healthy controls. Researchers collected fecal samples upon admission and analyzed microbial DNA using 16SrDNA sequencing on the Illumina MiSeq platform. A follow-up assessment was also conducted one month after anti-tuberculosis treatment to track changes in the gut microbiota over the course of therapy.
The study population consisted of pediatric patients diagnosed with pulmonary tuberculosis alongside healthy pediatric controls, using a case-controlled design. Fecal samples were gathered from both groups at admission, with PTB patients reassessed one month later following anti-tuberculosis treatment. The abstract does not specify exact sample sizes or additional demographic details beyond the pediatric PTB and healthy control groups.
Children with pulmonary tuberculosis showed decreased microbial diversity in their gut microbiota compared with healthy controls. PTB patients had increased levels of the pro-inflammatory bacterium Prevotella and the opportunistic pathogen Enterococcus. At the same time, beneficial bacteria including Ruminococcaceae, Bifidobacteriaceae, and Faecalibacterium prausnitzii were reduced. One month after anti-tuberculosis therapy, the richness of the gut microbiota was further depleted.
These findings suggest that pulmonary tuberculosis in children is associated with a disrupted gut microbiota, marked by loss of diversity and depletion of beneficial, anti-inflammatory commensals such as Faecalibacterium prausnitzii, alongside expansion of pro-inflammatory and opportunistic organisms. The further depletion of microbial richness after anti-tuberculosis treatment raises the possibility that therapy itself compounds gut microbial disruption in these children. This points to the gut microbiota as a potentially important, underexplored factor in the physiological response to pulmonary tuberculosis and its treatment in pediatric patients.
This study examined whether anti-Saccharomyces cerevisiae antibody (ASCA) status is associated with a distinct gut mucosal microbiome and clinical phenotype in pediatric Crohn disease (CD). Researchers compared ileocolonic mucosal biopsy microbiota between ASCA-positive and ASCA-negative CD patients, and against non-inflammatory bowel disease controls. They assessed microbial alpha and beta diversity, richness, and species-level associations with ASCA status, alongside clinical characteristics such as age, disease location, and surgical risk.
The study included 135 children with Crohn disease and 45 controls without inflammatory bowel disease, all of whom underwent ileocolonic mucosal biopsy. Within the CD group, patients were further divided by ASCA positivity or negativity for comparison. The abstract does not specify additional demographic details beyond the pediatric age range implied by the disease association with age 10 years and older.
ASCA was highly specific but poorly sensitive for diagnosing CD, and ASCA positivity was associated with older age (10 years or older), ileocolonic disease location, and long-term risk of surgery. Microbial alpha and beta diversity did not differ significantly between ASCA-positive and ASCA-negative CD patients, though both groups showed significantly lower diversity than non-IBD controls; microbial richness was similar across all three groups. Fourteen bacterial species were associated with ASCA-positive CD and fourteen with ASCA-negative CD, and after false discovery rate correction, Ruminococcus torques and bacterium Yersinia enterocolitica 61 remained significantly associated with ASCA status.
These findings suggest that ASCA status marks a clinically meaningful CD subgroup, associated with older age, ileocolonic involvement, and greater surgical risk, even though overall microbial diversity does not differ by ASCA status. The species-level associations, particularly Ruminococcus torques and Yersinia enterocolitica, point to specific taxa that may help explain or predict the more aggressive clinical course seen in ASCA-positive patients. This supports further investigation of ASCA-associated microbial signatures as potential biomarkers for disease stratification in pediatric CD.
This study examined whether the oral and gut microbiome influences how melanoma patients respond to anti-PD-1 checkpoint blockade immunotherapy. Researchers compared microbiome diversity, composition, and metagenomic function between patients who responded to treatment and those who did not. They also tested whether transferring the gut microbiome from responding patients could alter antitumor immunity in mice.
The study included 112 melanoma patients undergoing anti-PD-1 immunotherapy, whose oral and gut microbiomes were profiled. A subset of 43 patients had fecal microbiome samples analyzed in detail, comprising 30 responders and 13 nonresponders. Germ-free mice were also used as recipients in fecal transplant experiments from responding patients.
Responding patients had significantly higher gut microbiome alpha diversity and a significantly greater relative abundance of bacteria from the Ruminococcaceae family compared to nonresponders. Metagenomic analysis showed functional differences in the gut bacteria of responders, including enrichment of anabolic pathways. Immune profiling indicated enhanced systemic and antitumor immunity in responding patients with a favorable gut microbiome, and this enhanced immunity was also observed in germ-free mice that received fecal transplants from responders.
These findings suggest the gut microbiome plays a causal role in shaping how melanoma patients respond to immune checkpoint inhibitor therapy, extending prior mouse-model evidence into human cancer patients. The identification of specific compositional and functional microbiome features, such as Ruminococcaceae abundance and enriched anabolic pathways, associated with response points toward potential microbiome-based biomarkers or interventions. This has direct implications for improving outcomes in melanoma patients treated with immune checkpoint inhibitors.
This study evaluated DAV132, a product designed to deliver activated charcoal to the late ileum, as a means of protecting the gut microbiome during antibiotic treatment. Researchers tested whether coadministering DAV132 with the fluoroquinolone antibiotic moxifloxacin could adsorb residual antibiotic in the gut and limit its disruption of the intestinal microbiota. The trial also assessed plasma drug levels and safety, and separately tested DAV132's ability to adsorb other antibiotics outside the body.
The study enrolled 28 human volunteers who received a 5-day clinical regimen of moxifloxacin, split into two parallel groups, one receiving DAV132 alongside the antibiotic and one not. Two additional control groups of 8 volunteers each received either DAV132 alone or a nonactive substitute. All participants appear to be healthy volunteers rather than patients with an existing condition.
Coadministration of DAV132 reduced free moxifloxacin concentrations in feces by 99%, while plasma drug levels were unaffected, indicating the effect was localized to the gut and did not interfere with systemic antibiotic action. Shotgun quantitative metagenomics showed that the richness and composition of the intestinal microbiota were largely preserved in subjects who received DAV132 with moxifloxacin. No adverse effects were observed, and DAV132 also efficiently adsorbed a wide range of clinically relevant antibiotics in ex vivo testing.
These findings suggest DAV132 could be a practical tool for protecting the gut microbiome during antibiotic therapy without reducing the antibiotic's systemic availability or efficacy. Because DAV132 adsorbed multiple other antibiotics ex vivo, this approach may generalize beyond moxifloxacin to broader clinical use. Preserving microbiota richness and composition during antibiotic courses could help mitigate the short-term and longer-term consequences of antibiotic-associated microbiome disruption.
This study used metagenomic sequencing to characterize the meconium (initial fecal) microbiome of neonates in the first 24 hours after birth. The researchers compared microbiome composition, diversity, metabolic function, and antibiotic resistance gene (ARG) prevalence between infants delivered vaginally and by cesarean section. Because meconium is collected before feeding can meaningfully shape the gut microbiome, this design isolates the effect of delivery mode itself.
The cohort was a group of Chinese neonates, including infants delivered vaginally, infants delivered by cesarean section, and two newborns conceived via in vitro fertilization (IVF) who were also delivered by cesarean section. Meconium samples were collected from feces within the first 24 hours of life. The abstract does not specify an exact total sample size beyond identifying these delivery-mode subgroups.
Meconium microbiome diversity was higher in vaginally delivered infants than in those delivered by cesarean section. Propionibacterium species were most abundant in vaginally delivered infants, whereas Bacillus licheniformis dominated the cesarean-section group. Notably, the two IVF newborns delivered by cesarean section had microbial communities taxonomically similar to the vaginal microbiome rather than to the typical cesarean pattern. Metabolic function in the cesarean group was more strongly shaped by the dominant B. licheniformis, while the vaginal group's metabolism was more homogeneous and driven by multiple microbes, and delivery mode also affected antibiotic resistance gene prevalence.
The findings suggest that delivery mode exerts a measurable effect on the infant gut microbiome from the very first day of life, before feeding can be a confounding factor. The distinct taxonomic dominance, metabolic profiles, and antibiotic resistance gene patterns linked to cesarean versus vaginal birth point to delivery mode as an early, foundational influence on microbiome assembly and function. The unexpected similarity between IVF cesarean infants and the vaginal-birth pattern also raises questions about additional factors beyond delivery route that may shape the earliest microbiome.
This study examined how the phenylalanine (Phe) restricted diet used to treat phenylketonuria (PKU) affects gut microbiota and short chain fatty acid (SCFA) production. Researchers compared dietary intakes, gut microbiota biodiversity, and fecal SCFAs between children on a low-Phe diet and children with unrestricted diets. Fecal microbiota was analyzed using denaturing gradient gel electrophoresis (DGGE) and Real-time PCR, and SCFAs were quantified by gas chromatography.
The study enrolled 21 children with PKU, who followed a low-Phe diet with Phe-free l-amino acid supplementation, and 21 children with mild hyperphenylalaninemia (MHP), who followed an unrestricted diet. The two groups were matched for gender, age, and body mass index z-score. This case-control design allowed direct comparison of diet-driven microbiota differences between the two pediatric groups.
PKU children showed higher carbohydrate, fiber, and vegetable intake, along with higher glycemic index and glycemic load, compared with MHP children. Despite this, PKU children had lower gut microbial diversity and significantly decreased fecal butyrate content. Faecalibacterium spp. and Roseburia spp., two of the most abundant butyrate-producing genera, were significantly depleted in the PKU group compared with MHP children.
These findings suggest that the low-Phe diet, despite increasing carbohydrate and fiber intake, alters the quality of substrates available for microbial fermentation in a way that reduces butyrate production. Since Faecalibacterium prausnitzii and related butyrate producers are considered beneficial, anti-inflammatory commensals, their depletion in PKU children raises concern about gut health in this population. The authors call for further studies to characterize the microbial species affected by the PKU diet, which could eventually support the use of prebiotic or probiotic supplementation in these children.
This study examined gut microbiota composition in people with obesity, comparing obese adolescents and obese adults against age-matched normal weight (NW) volunteers. Researchers used 16S rRNA-based metagenomics to profile bacterial communities and applied ecological, univariate, multivariate, and correlation analyses to the resulting profiles. They also used the 16S rRNA gene survey data to predict functional metagenome content, including metabolic pathways, in each group.
The study compared obese adolescents and obese adults to normal weight (NW) volunteers matched by age, meaning both an adolescent obese/NW pair and an adult obese/NW pair were analyzed. The abstract does not give exact participant numbers, so specific cohort size cannot be stated. The population appears to be human volunteers recruited specifically for age- and obesity-related microbiota comparison rather than a purely public dataset.
Ecological analyses showed that microbiota profiles differed meaningfully between the obese adolescent and obese adult subgroups, indicating age-dependent patterns in obesity-associated gut microbiota. Statistical analysis identified Faecalibacterium prausnitzii and Actinomyces as microbial markers of obese adolescents, while Parabacteroides, Rikenellaceae, Bacteroides caccae, Barnesiellaceae, and Oscillospira marked the normal weight adolescents. Predicted metabolic profiles also differed between the adolescent groups, with differences noted in primary bile acid and steroid acid biosynthesis pathways.
The findings suggest that gut microbiota signatures of obesity are not uniform across the lifespan and instead follow age-dependent patterns, meaning adolescent and adult obesity may involve distinct microbial contributors. The identification of Faecalibacterium prausnitzii, an anti-inflammatory, butyrate-associated commensal, as a marker specifically in obese adolescents raises questions about its role or dysregulation in early-life obesity rather than a simple depletion pattern seen in other conditions. Altered predicted bile acid and steroid metabolism further points to functional, not just compositional, microbiome differences that could inform age-specific approaches to studying or addressing obesity.
This study examined whether obesity is associated with a consistent, identifiable taxonomic signature in the human gut microbiome. The researchers compared gut microbiome diversity, overall community composition, and the abundance of individual bacterial taxa across obese, overweight, and healthy-weight adults. They used 16S rRNA gene sequencing of stool samples and tested whether any signature found could be replicated across separate populations.
The analysis included 599 adults whose gut microbiomes were assessed from stool samples. Participants were classified into three groups based on body mass index: obese (BMI 30 or above), overweight (BMI 25 to under 30), and healthy-weight (BMI 18.5 to under 25). The findings were tested across two independent study populations, and results were further validated against a previously published external dataset.
Obese participants, but not overweight participants, showed significantly reduced gut species richness and significantly altered overall microbiome composition compared to healthy-weight participants. Obesity was characterized by increased abundance of class Bacilli, including the families Streptococcaceae and Lactobacillaceae, alongside decreased abundance of several groups within class Clostridia, including Christensenellaceae, Clostridiaceae, and Dehalobacteriaceae. These compositional differences were consistent across both independent study populations. Random forest models trained on one population and tested on the other, as well as on a previously published dataset, predicted obesity with good accuracy of approximately 70 percent.
By identifying a taxonomic signature of obesity that held up across independent populations, the study strengthens the case that specific gut microbiota shifts are reliably associated with obesity in humans, not just in animal models. The reproducible depletion of Clostridia groups alongside enrichment of Bacilli suggests these taxa could serve as biomarkers for obesity status. The roughly 70 percent prediction accuracy of models built from microbiome composition points toward potential future use of gut microbiota profiling as a tool for identifying or stratifying obesity risk.
This study used next generation sequencing-based 16S rRNA gene analysis to characterize the gut microbiota composition in colorectal cancer (CRC) patients following anti-cancer treatment. The researchers specifically compared microbial communities across patients treated with surgery versus those treated with chemotherapy. The goal was to identify how these treatments reshape the microbiome and whether specific bacteria are linked to chemoresistance during CRC therapy.
The analysis was based on a total of 69 fecal samples collected across four clinical groups. These groups included healthy individuals, untreated CRC patients, CRC patients treated with surgery, and CRC patients treated with chemotherapy. The abstract does not provide further demographic details such as age or sex distribution.
Surgery was found to greatly reduce bacterial diversity in the gut microbiota of CRC patients. Fusobacterium nucleatum was shown to confer chemoresistance during CRC therapy. Additionally, certain bacterial strains or genera, including the genus Sutterella and the species Veillonella dispar, were specifically associated with CRC patients treated with chemotherapeutic cocktails, suggesting a potential relationship with chemoresistance.
These findings suggest that specific gut bacteria, such as Fusobacterium nucleatum, Sutterella, and Veillonella dispar, could serve as candidate biomarkers for monitoring or predicting chemoresistance in CRC patients. The marked loss of bacterial diversity after surgery also points to a treatment-related microbiome disruption that may warrant clinical attention. Together, these results support further investigation into the gut microbiota as a tool for guiding or evaluating CRC therapy.
This study examined how a diet perturbation, in which individual micronutrients were spiked into a standardized background diet, affects the human gut microbiome. The researchers designed a highly controlled experiment to quantify the impact of specific dietary components, including prebiotics, on microbiota composition and function. They tracked responses at both the microbial strain level and the functional gene level, and compared microbiome stability under this low complexity diet to stability under a complex, varying diet.
The study was conducted in a healthy human cohort, though the abstract does not give an exact number of participants. Individuals in this cohort consumed a standardized background diet spiked with individual micronutrients, including prebiotic compounds and non-prebiotic micronutrients, allowing within-person comparisons across a controlled dietary intervention.
Participants showed strong and predictable microbial responses to prebiotic spike-ins, evident at both the strain level and the level of functional genes, suggesting fine-scale resource partitioning among gut microbes. No such predictable responses were found for non-prebiotic micronutrients. Surprisingly, the standardized low complexity diet did not reduce day-to-day variability of the microbiota compared to a complex, varying diet, and instead the data showed evidence of diet-induced stress and an associated loss of biodiversity.
The findings suggest that a low complexity diet can stress the gut microbiome and reduce its biodiversity rather than stabilizing it. Because microbial responses to prebiotics were predictable only at the strain and functional gene level, the authors conclude that effective personalized dietary interventions will require functional, strain-level characterization of an individual's microbiota. This points toward precision, individualized approaches rather than one-size-fits-all prebiotic recommendations.
This study examined differences in intestinal flora structure between obese and normal-weight school-age children. Researchers used Illumina Miseq next-generation sequencing with 16S rDNA high-throughput sequencing technology to characterize gut bacterial communities. Gut bacteria were classified into Operational Taxonomic Units (OTUs) using the RDP 16S rRNA database and RDP classifier. Both alpha diversity (within-sample diversity) and beta diversity (between-sample dissimilarity) were calculated to compare the two groups.
The study included 39 obese school-age children and 38 normal-weight control children of the same age range. The abstract does not specify the children's exact ages, sex distribution, or geographic location beyond this case-control design. Comparisons were made strictly between these two defined groups based on obesity status.
Intestinal flora in obese children showed lower alpha diversity than in normal-weight controls. Significant differences in the relative abundance of intestinal flora were detected at multiple levels of taxonomic classification. Beta diversity comparisons further confirmed that the microbial community structure differed meaningfully between the obese and normal groups. The abstract does not name specific bacterial taxa or note Faecalibacterium prausnitzii, butyrate, or other anti-inflammatory commensals.
Identifying which specific intestinal bacteria differ between obese and normal-weight children may help clarify the role these organisms play in the development of childhood obesity. This case-control comparison suggests reduced gut microbial diversity could be a feature of pediatric obesity. The findings may support future work aimed at finding new approaches, such as microbiome-targeted strategies, for addressing childhood obesity. Because the abstract's findings section was truncated, further specific implications beyond this general direction cannot be confirmed.
This study examined the relationship between dietary fibre intake and gut microbiota composition in adults. Researchers used 16S rRNA gene sequencing to characterize the gut microbiota in faecal samples and calculated energy-adjusted fibre intake from food frequency questionnaires. They evaluated associations between fibre intake and both overall microbial community composition and individual taxon abundance, adjusting for age, sex, race, BMI, and smoking. This work was motivated by evidence that gut microbiota may influence colorectal cancer risk and that diet, particularly fibre, may modify that microbiota.
The study drew on 151 adults from two independent study populations: the National Cancer Institute (NCI) cohort (n 75) and the New York University (NYU) cohort (n 76). Each population was analyzed separately and then combined in a meta-analysis. The abstract does not provide further demographic detail on these participants beyond the adjustment variables used (age, sex, race, BMI, smoking).
Total fibre intake was significantly associated with overall gut microbial community composition in the NYU population (P=0.008) but not in the NCI population (P=0.81). In the meta-analysis combining both populations, higher fibre intake tended to be associated with greater abundance of several genera within class Clostridia, including SMB53, Lachnospira, and Faecalibacterium (likely reflecting Faecalibacterium prausnitzii, a butyrate-producing, anti-inflammatory commensal). Higher fibre intake was also associated with lower abundance of Actinomyces, Odoribacter, and Oscillospira.
The findings suggest that dietary fibre intake is linked to specific shifts in gut microbiota composition, particularly favoring Clostridia genera such as Faecalibacterium that are associated with butyrate production and anti-inflammatory activity. Because gut microbiota composition may in turn influence colorectal cancer risk, these fibre-associated microbial shifts could represent one pathway by which diet affects cancer risk. The inconsistent association with overall community composition across the two study populations also highlights the need for further research to clarify how consistently fibre intake shapes the gut microbiome across different populations.
This study examined the gut microbiota of women in relation to obesity, focusing on the ecological co-occurrence network structure of microbial communities and the relationship between short chain fatty acids (SCFAs) and body weight status. Researchers compared microbial alpha-diversity, beta-diversity, fecal SCFA concentrations, and network topology (density, connectivity, stability) between lean and obese participants. They also profiled taxonomic composition and predicted microbial genes involved in butyric acid production via pyruvate or branched amino-acid fermentation.
The study included 100 women of African origin, drawn from rural Ghana and the urban United States. Half of the women were lean (BMI under 25 kg/m2) and half were obese (BMI 30 kg/m2 or greater), split evenly across the two geographic populations. This design allowed comparison of diet, microbiota, and metabolic markers across both BMI status and country of residence.
Ghanaian women consumed significantly more dietary fiber and had greater microbial alpha-diversity, distinct beta-diversity, and higher total fecal SCFA concentrations than US women. Lean Ghanaians showed significantly greater microbial network density, connectivity, and stability than obese Ghanaians and than both lean and obese US women. Bacteroides uniformis was more abundant in lean women regardless of country, while lean Ghanaians also had greater proportions of Ruminococcus callidus, Prevotella copri, and Escherichia coli, and lower proportions of Lachnospiraceae, Bacteroides, and Parabacteroides. Lean Ghanaians additionally showed a significantly greater abundance of predicted microbial genes catalyzing butyric acid production via fermentation of pyruvate or branched amino acids, compared with obese Ghanaians and US women of either BMI status.
The findings suggest that a less stable, less connected gut microbial ecosystem, together with reduced capacity for butyrate production, may be associated with obesity in women of African origin. Diet, particularly fiber intake, appears linked to both microbial network stability and SCFA output, pointing to diet-driven ecological resilience as a factor in metabolic health. These results support further investigation into microbial network stability and butyrate-producing pathways as potential markers or targets related to obesity.
This study evaluated whether faecal metagenomes could be used to diagnose colorectal cancer (CRC) non-invasively. Researchers performed metagenome-wide association studies on stool samples to identify microbial species and gene markers associated with CRC. They then tested whether a small set of these markers could reliably distinguish CRC patients from controls using both metagenomic sequencing and targeted quantitative PCR (qPCR) assays. The candidate biomarkers were validated across multiple independent cohorts from different countries.
The primary cohort included 74 patients with CRC and 54 controls from China. Validation cohorts included 16 CRC patients and 24 controls from Denmark, plus two previously published cohorts from France and Austria. A further independent Chinese cohort of 47 patients with CRC and 109 controls was used for qPCR-based validation.
The study confirmed known associations between CRC and Fusobacterium nucleatum and Peptostreptococcus stomatis, and identified new associations with species including Parvimonas micra and Solobacterium moorei. Researchers identified 20 microbial gene markers differentiating CRC and control microbiomes, of which 4 were validated in the Danish cohort. These four genes distinguished CRC from controls in the French and Austrian cohorts with AUCs of 0.72 and 0.77, and qPCR measurement of two of these genes classified CRC patients in an independent Chinese cohort with an AUC of 0.84 and an odds ratio of 23.
These findings suggest that faecal microbial gene markers, including some detectable at early cancer stages, could serve as non-invasive biomarkers for CRC screening. Validation across cohorts from China, Denmark, France, and Austria supports the generalizability of a small panel of markers across different populations. Because qPCR is a simple, targeted assay, these markers may be practical to develop into a clinical diagnostic test for CRC.
This case control study evaluated gut microbiota biodiversity in school-aged children, looking at both bacterial and fungal communities. Fecal samples were analyzed using 16S rRNA amplification followed by denaturing gradient gel electrophoresis (DGGE) and sequencing. Real-time PCR was then used to quantify the most representative microbial species and genera. The goal was to compare gut microbial composition between obese and normal-weight children.
The study included 28 obese children (mean age 10.03 years) and 33 age- and sex-matched normal-weight children. BMI z-scores were calculated for each child, and obesity status was defined according to WHO criteria. Fecal samples from these 61 school-aged children formed the basis of the analysis.
Bacterial biodiversity was high across DGGE profiles and did not correlate significantly with BMI z-score groups, but fungal (yeast) richness was lower than bacterial richness overall. Eubacterium rectale, Saccharomyces cerevisiae, Candida albicans, and Candida glabrata were present in all samples, while Debaryomyces hansenii appeared only in two obese children. Obese children showed a significantly lower abundance of Akkermansia muciniphila, Faecalibacterium prausnitzii, and Bacteroides/Prevotella compared to normal-weight children.
The reduced abundance of Faecalibacterium prausnitzii, a butyrate-producing anti-inflammatory commensal, and Akkermansia muciniphila in obese children suggests these microbes may play a protective role against childhood obesity. The findings indicate that both bacterial and fungal gut community shifts, not bacteria alone, may be relevant to pediatric obesity. This supports further investigation into these specific taxa as potential biomarkers or targets in childhood obesity research.
This study characterized the composition of the gut microbiota in children using 16S rRNA gene-targeted sequencing. Researchers compared taxa abundance between obese and normal-weight children based on age- and sex-normalized body mass index (BMI z-score). They also examined correlation network structure among operational taxonomic units (OTUs) and measured short chain fatty acid (SCFA) levels as markers of bacterial fermentation activity.
The study population consisted of 42 obese children and 36 normal-weight children, all aged 6 to 16 years. Gut microbiota composition was assessed via stool-derived 16S rRNA sequencing across this pediatric cohort. No further demographic details are given in the abstract.
Obesity in children was associated with an altered gut microbiota marked by elevated Firmicutes and depleted Bacteroidetes. The obese children's microbiota also showed increased correlation density and clustering among OTUs, reflecting a more tightly interconnected community structure. Bacteroidetes members were generally stronger predictors of BMI z-score and obesity than Firmicutes, likely because Firmicutes OTUs showed discordant, inconsistent responses. SCFA levels, the main metabolites produced by gut bacteria, were higher in obese children and correlated with multiple taxa, suggesting elevated substrate utilization and fermentation.
The findings suggest that gut microbiota dysbiosis and elevated fermentation activity are already detectable in childhood obesity, not just in adults. Because Firmicutes populations respond discordantly, simple Firmicutes-to-Bacteroidetes ratio measures may be less reliable than Bacteroidetes-based markers for predicting pediatric obesity. The tight link observed between specific taxa, SCFA levels, and obesity points to microbial fermentation as a potential mechanistic contributor worth further investigation in children.
This study examined how different combined antiretroviral therapy (cART) regimens affect bacterial translocation and gut microbiota composition in HIV-infected patients. Prior work had shown that increased bacterial translocation and altered gut microbiota persist in HIV infection despite cART, contributing to immune activation and inflammation, but the role of specific drug combinations had not been investigated. Researchers measured soluble markers of bacterial translocation and inflammation and analyzed gut microbiota using 16S rDNA pyrosequencing (Illumina MiSeq).
The cross-sectional study included 45 HIV-infected patients on cART, divided into three regimen groups: NRTIs plus protease inhibitors (n = 15), NRTIs plus non-nucleoside reverse transcriptase inhibitors (n = 22), and NRTIs plus integrase strand transfer inhibitors (INSTIs, n = 8). Also included were 5 untreated HIV-infected patients and 21 non-infected volunteers as comparison groups.
The NRTIs plus INSTIs regimen was associated with systemic inflammation levels similar to those seen in uninfected controls, distinguishing it from the other cART combinations. HIV infection was linked to a reduction in fecal bacterial diversity. The abstract text was truncated, so further comparative details on translocation markers and microbiota composition across regimens are not available here.
The findings suggest that the specific composition of a cART regimen, not just cART use in general, may influence residual inflammation and gut microbiota disruption in people living with HIV. This raises the possibility that regimens including INSTIs could offer advantages for reducing systemic inflammation compared to other combinations. Further research is needed to confirm these differential effects and clarify their clinical significance.
This study examined whether the composition of gut microbiota present before treatment could predict two outcomes of ipilimumab therapy in metastatic melanoma: anti-tumor response and intestinal toxicity (colitis). Ipilimumab is an immune checkpoint inhibitor targeting CTLA-4 that can prolong survival but also trigger immune-related adverse events, including enterocolitis. Fecal microbiota composition was assessed using 16S rRNA gene sequencing at baseline and before each ipilimumab infusion, and patients were clustered according to their microbiota patterns. Peripheral blood lymphocyte immunophenotypes were also studied in parallel to relate microbiota patterns to immune status.
Twenty-six patients with metastatic melanoma who were prospectively enrolled and treated with ipilimumab. Patients were divided into two microbiota-based clusters: cluster B, driven by Bacteroides (n = 10), and cluster A, enriched with Faecalibacterium and other Firmicutes (n = 12). Fecal samples and blood were collected from this cohort at baseline and at subsequent treatment timepoints.
A distinct baseline gut microbiota composition was associated with both clinical response and colitis risk. Patients in cluster A, whose baseline microbiota was enriched with Faecalibacterium genus and other Firmicutes, had significantly longer progression-free survival (P = 0.0039) than cluster B patients, whose microbiota was driven by Bacteroides, with a trend toward longer overall survival (P = 0.051). Most baseline colitis-associated phylotypes were related to Firmicutes, including relatives of Faecalibacterium prausnitzii and Gemmiger formicilis, whereas no colitis-related phylotypes were linked to the Bacteroides-driven cluster.
Baseline gut microbiota composition may serve as a predictive biomarker for both the effectiveness and the toxicity of ipilimumab in metastatic melanoma. The same Firmicutes-enriched, Faecalibacterium-associated microbiota pattern that tracked with better clinical outcomes also tracked with greater colitis risk, suggesting response and toxicity may share overlapping microbial and immune underpinnings. These findings support further investigation into using pretreatment microbiota profiling to stratify patients and anticipate immune-related adverse events during checkpoint inhibitor therapy.
This study examined whether the gastrointestinal microbiome and peripheral immune signaling are associated with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Researchers combined rigorous clinical characterization with fecal bacterial metagenomics and plasma immune molecule analyses. They specifically looked at whether irritable bowel syndrome (IBS) co-morbidity and body mass index shaped bacterial composition and bacterial metabolic pathways.
The study included 50 patients diagnosed with ME/CFS and 50 healthy controls. Controls were frequency-matched to patients for age, sex, race/ethnicity, geographic site, and season of sampling. This matched case-control design allowed comparisons of fecal and plasma profiles between the two groups.
Topological analysis linked IBS co-morbidity, body mass index, fecal bacterial composition, and bacterial metabolic pathways, but found no such association with plasma immune molecules. IBS co-morbidity was the strongest factor separating topological networks based on bacterial profiles and metabolic pathways. Predictive selection models confirmed that ME/CFS subgroups defined by IBS status could be distinguished from controls with high accuracy, and the bacterial taxa predictive of ME/CFS with IBS differed from those predictive of ME/CFS without IBS.
The findings suggest ME/CFS is not a single uniform condition but includes at least two microbiome-linked subgroups defined by IBS status. Fecal bacterial profiles and metabolic pathways, rather than circulating immune molecules, appear to track most closely with this clinical subdivision. This supports stratifying ME/CFS patients by gut comorbidity status when investigating mechanisms or designing future microbiome-targeted studies.
This study examined how the gut microbiome and circulating serum metabolites differ between lean and obese individuals. Researchers used a metagenome-wide association study paired with serum metabolomics profiling to identify obesity-associated gut microbial species and link them to changes in blood metabolites. They further tested a specific microbial species, Bacteroides thetaiotaomicron, in mice to determine its direct effect on body weight and fat accumulation. The study also examined whether bariatric surgery could reverse the microbial and metabolic changes seen in obesity.
The human portion of the study involved a cohort of lean and obese, young, Chinese individuals, though the abstract does not specify exact sample size. A subset of these obese individuals also underwent bariatric surgery as a weight-loss intervention, with pre- and post-surgery comparisons used to assess reversal of obesity-associated changes. In addition to the human cohort, the researchers used a mouse model to test the functional effects of B. thetaiotaomicron administration via gavage.
The abundance of Bacteroides thetaiotaomicron, a glutamate-fermenting commensal, was markedly decreased in obese individuals and was inversely correlated with serum glutamate concentration. In mice, gavage with B. thetaiotaomicron reduced plasma glutamate concentration and alleviated diet-induced body-weight gain and adiposity. Weight-loss intervention by bariatric surgery partially reversed these obesity-associated microbial and metabolic alterations, including restoring B. thetaiotaomicron abundance and lowering elevated serum glutamate.
These findings identify a previously unknown link between a specific gut commensal, circulating amino acid levels, and obesity. The inverse relationship between B. thetaiotaomicron and serum glutamate, confirmed functionally in mice, suggests this microbe helps regulate host metabolism through glutamate fermentation. The results suggest it may be possible to intervene in obesity by directly targeting the gut microbiota, offering a potential mechanistic target for future metabolic therapies.
This prospective study examined whether pretreatment gut microbiota and metabolites are associated with response to immune checkpoint inhibitor (ICT) therapy in metastatic melanoma. Patients were treated with ipilimumab, nivolumab, ipilimumab plus nivolumab (IN), or pembrolizumab (P), and response was assessed using Response Evaluation Criteria in Solid Tumors. The study combined metagenomic shotgun sequencing of gut microbiota with unbiased shotgun metabolomic profiling to identify features linked to therapy efficacy. It builds on preclinical work showing specific gut microbiota can promote melanoma regression in mice.
The study included 39 metastatic melanoma patients treated with ICT regimens (ipilimumab, nivolumab, ipilimumab plus nivolumab, or pembrolizumab). The abstract does not provide further demographic details such as age, sex distribution, or geographic site. IN yielded 67% responses and 8% stable disease, while pembrolizumab achieved 23% responses and 23% stable disease among these patients.
Across all therapy types, ICT responders were enriched for Bacteroides caccae in their gut microbiome. Among IN responders specifically, the microbiome was enriched for Faecalibacterium prausnitzii, Bacteroides thetaiotaomicron, and Holdemania filiformis, while pembrolizumab responders showed enrichment of Dorea formicogenerans. Unbiased shotgun metabolomics further revealed high levels of anacardic acid in ICT responders, linking a specific metabolite to treatment response.
The findings suggest that specific gut bacteria, including the anti-inflammatory commensal Faecalibacterium prausnitzii, and metabolites such as anacardic acid may serve as pretreatment indicators of ICT response in melanoma. As a pilot study, the authors state that both additional confirmatory clinical studies and preclinical testing of these bacterial and metabolite associations are needed. If validated, these microbiota and metabolite signatures could inform patient selection or adjunct strategies to improve ICT efficacy, particularly for patients failing standard therapy.
This study examined whether the enteric virome, alongside the bacterial microbiome, contributes to HIV-associated immunodeficiency and gut disease. Researchers characterized viral and bacterial communities in stool to see how they relate to HIV infection, antiretroviral therapy (ART) status, and CD4 T cell counts. The goal was to determine whether virome alterations track with immune decline independent of treatment.
The cohort consisted of Ugandan patients, including individuals without HIV infection and individuals with HIV infection who were either on ART or untreated. The abstract does not give an exact sample size or additional demographic detail. Findings are grouped by HIV status, treatment status, and peripheral CD4 T cell count level.
Low peripheral CD4 T cell counts were associated with an expansion of enteric adenovirus sequences, and this pattern held regardless of ART treatment. Patients with lower CD4 counts also had a bacterial microbiome with reduced phylogenetic diversity and richness. Specific bacterial taxa showed differential abundance, notably an increase in Enterobacteriaceae, a group linked to inflammation.
The findings suggest that immunodeficiency in progressive HIV infection is accompanied by coordinated shifts in both the enteric virome and bacterial microbiome, not bacterial changes alone. Because the adenovirus expansion occurred regardless of ART status, viral alterations may persist even in treated patients and could still contribute to gut dysfunction. These combined viral and bacterial changes may help drive AIDS-associated enteropathy and disease progression, pointing to the virome as an underexplored factor in HIV-related gut pathology.
This study examined whether the composition of the gut microbial community differs in children with early onset multiple sclerosis (MS) compared with children without autoimmune disease. Researchers profiled fecal bacterial community composition using 16S ribosomal RNA sequencing and used PICRUSt to predict the functional capacity of these communities. They also tested whether overall community diversity (beta diversity) or specific taxa abundance related to MS status or to immunomodulatory drug (IMD) exposure.
The cohort consisted of 18 children with relapsing-remitting MS and 17 control children, matched for age and sex, seen at a University of California, San Francisco pediatric clinic. Participants were 18 years old or younger, with a mean age of 13 years (range 4 to 18). The MS cases were within 2 years of disease onset, had a short mean disease duration of 11 months (range 2 to 24), and about half had never been exposed to immunomodulatory drugs.
Overall gut bacterial beta diversity was not significantly associated with MS status itself. However, beta diversity was significantly associated with immunomodulatory drug exposure (Canberra distance, P less than 0.02). Relative to controls, the MS cases showed a significant enrichment in relative abundance of certain taxa, though the abstract provided does not specify which organisms were enriched.
The findings suggest that in early pediatric MS, treatment exposure may shape the gut microbiota community more strongly than disease status alone, at least at the level of overall community diversity. The detection of specific taxa enriched in MS cases points to potential microbial features worth further investigation as markers or contributors to disease. Because this is a small case-control study, these results should be viewed as hypothesis generating rather than definitive, and larger studies are needed to confirm which taxa are involved and how treatment affects microbiota findings.
This study examined how Roux-en-Y gastric bypass (RYGB) surgery changes the gut microbiota of morbidly obese patients over time. The researchers used shotgun metagenomic sequencing of fecal DNA to characterize microbial composition at both the species and gene level. They also performed functional annotation of the microbial genes to understand how the metabolic potential of the gut community shifted after surgery. The goal was to describe the taxonomic and functional changes that accompany the weight loss and metabolic improvements known to follow RYGB.
The study recruited 13 morbidly obese patients scheduled to undergo RYGB surgery. Patients were phenotyped and had stool samples collected before surgery (n = 13), then again at 3 months (n = 12) and 12 months (n = 8) after surgery. This design allowed the same individuals to be followed longitudinally as their own before-and-after comparison.
Gut microbial diversity increased within the first 3 months after RYGB and remained elevated a year later, tracking alongside the weight loss and metabolic improvements the patients experienced. RYGB altered the relative abundance of 31 bacterial species within the first 3 months after surgery. These shifts occurred rapidly and persisted through the 12-month follow-up, indicating the surgery induces a durable restructuring of the individual gut microbiota rather than a transient disturbance.
The findings support the idea that major, lasting changes in gut microbial community structure accompany the metabolic benefits of RYGB, such as improved insulin sensitivity and glucose homeostasis. Because the diversity and compositional changes appear swiftly and persist for at least a year, the gut microbiota may be an active participant in, rather than a passive bystander to, post-surgical metabolic improvement. This raises the possibility that microbiome-targeted strategies could someday complement or mimic some of the benefits currently achieved only through bariatric surgery.
This randomized, double-blind, placebo-controlled trial tested whether manipulating the gut microbiota with antibiotics affects host metabolism in obese, prediabetic men. Participants received seven days of amoxicillin, vancomycin, or placebo. Researchers then measured bacterial composition alongside metabolic outcomes including insulin sensitivity, energy and substrate metabolism, systemic inflammation, gut permeability, and adipocyte size. Effects were assessed both immediately after treatment and at an 8-week follow-up.
The study enrolled 57 obese, prediabetic men. All participants were randomized to one of three arms: amoxicillin, vancomycin, or placebo, taken for seven days. The abstract does not provide further demographic detail such as age range or geographic site.
Vancomycin, but not amoxicillin, reduced bacterial diversity and decreased Firmicutes involved in short-chain fatty acid and bile acid metabolism, and this was accompanied by altered plasma and fecal metabolite concentrations. Adipose tissue gene expression of oxidative pathways increased with antibiotic treatment, while vancomycin specifically downregulated immune-related pathways in adipose tissue. Despite these microbial and gene-expression changes, antibiotics did not alter tissue-specific insulin sensitivity, energy or substrate metabolism, postprandial hormones and metabolites, systemic inflammation, gut permeability, or adipocyte size. At 8-week follow-up, energy harvest, adipocyte size, and whole-body insulin sensitivity remained unchanged even though microbial composition was still considerably altered.
Short-term antibiotic-driven disruption of the adult gut microbiota, even when it measurably depletes Firmicutes and short-chain fatty acid and bile acid related metabolism, does not translate into clinically meaningful changes in metabolic health in obese humans. This suggests the adult microbiota may be more resilient to producing metabolic harm from brief antibiotic perturbation than some prior human and animal data implied. The persistence of altered microbial composition without a corresponding metabolic effect at 8 weeks also indicates that compositional change alone is not a reliable proxy for metabolic consequence in this population.
This study examined the gut microbial community using 16S rRNA gene sequencing to compare obese and lean populations in Japan. Researchers sequenced the V3-V4 hypervariable regions of 16S rRNA from fecal samples using the Illumina MiSeq II platform. The goal was to characterize how gut microbiota composition differs with obesity status and to identify specific taxa associated with each phenotype.
The study included 20 Japanese volunteers divided into two groups of 10 obese and 10 lean individuals. The average body mass index was 38.1 kg/m2 in the obese group and 16.6 kg/m2 in the lean group, a statistically significant difference. Fecal samples from these volunteers formed the basis of all microbial community comparisons.
The lean group showed significantly higher Shannon diversity than the obese group, indicating greater microbial richness and evenness. Firmicutes and Fusobacteria were significantly more abundant in obese participants, while the Bacteroidetes abundance and Bacteroidetes/Firmicutes ratio did not differ between groups. At the genus level, Alistipes, Anaerococcus, Corpococcus, Fusobacterium, and Parvimonas were enriched in obese individuals, while Bacteroides, Desulfovibrio, Faecalibacterium, Lachnoanaerobaculum, and Olsenella were enriched in lean individuals. Notably, Faecalibacterium prausnitzii, a species known for anti-inflammatory properties, increased significantly in the lean group, whereas pro-inflammatory species increased in the obese group.
These findings support a link between reduced gut microbial diversity, a shift toward pro-inflammatory taxa, and obesity in a Japanese population. The enrichment of anti-inflammatory commensals like Faecalibacterium prausnitzii in lean individuals suggests that gut microbial composition may influence inflammatory tone and metabolic health. This work adds population-specific evidence to the broader case that gut microbiota profiling could inform obesity risk assessment or targeted interventions, though causality cannot be established from this comparative design.
This study examined whether short chain fatty acid (SCFA) concentrations and gut microbiota composition differ between people with Parkinson's disease (PD) and matched controls. Researchers measured fecal SCFA levels by gas chromatography and quantified bacterial groups by quantitative PCR. The work was motivated by PD's frequent gastrointestinal symptoms, such as constipation, and by PD-typical pathological changes in the enteric nervous system that can precede motor symptoms. It builds on prior reports linking altered gut microbiota composition to PD.
The study included 34 patients with Parkinson's disease and 34 age-matched controls. Fecal samples were collected from each participant for SCFA and microbiota analysis. The abstract does not provide further demographic, geographic, or disease-severity details about the cohort.
Fecal SCFA concentrations were significantly reduced in PD patients compared to controls. Within the microbiota, the phylum Bacteroidetes and the family Prevotellaceae were reduced in PD patients, while the family Enterobacteriaceae was more abundant. These findings confirm previously reported associations between PD and specific shifts in gut microbiota composition.
The findings support a link between altered gut bacterial composition and reduced SCFA production in Parkinson's disease, connecting a metabolic deficit to the compositional shifts seen in prior microbiome studies. Because SCFA are a main metabolic product of gut bacteria, this reduction may be relevant to the gastrointestinal and enteric nervous system changes seen early in PD. These results strengthen the rationale for further investigating gut microbiota and its metabolic output as a factor in PD pathophysiology.
This study examined whether the composition of the gut microbiota in infants differs between those with eczema and those without. Researchers used high-throughput sequencing of the V3-V4 hypervariable regions of the 16S rRNA gene to profile bacterial communities in fecal samples. The analysis identified 12,386 operational taxonomic units (OTUs) at 97% similarity and compared taxa abundance and composition between groups.
The study was a case-control comparison of 50 infants with eczema (cases) and 51 healthy infants without eczema (controls). Fecal samples from these 101 infants were the source material for the 16S rRNA sequencing analysis. No further demographic details are given in the abstract.
Gut microbiota differed between groups in taxa abundance, though not in overall taxonomic composition. Healthy infants showed enrichment of Bifidobacterium, Megasphaera, Haemophilus and Streptococcus. Infants with eczema showed enrichment of Escherichia/Shigella, Veillonella, Faecalibacterium, Lachnospiraceae incertae sedis and Clostridium XlVa, with Faecalibacterium prausnitzii and Ruminococcus gnavus, taxa associated with atopy or inflammation, significantly enriched in the eczema group. Higher abundance of Akkermansia muciniphila in eczematous infants was also noted and may relate to reduced intestinal barrier integrity.
The findings support a link between altered gut bacterial abundance and eczema in infancy, pointing to specific genera and species as candidate markers of the atopic gut. The enrichment of Faecalibacterium prausnitzii alongside other inflammation-associated taxa in eczema cases suggests that microbiota composition changes may accompany, or contribute to, atopic disease processes rather than protect against them in this context. These results could inform future research into microbiota-targeted approaches for eczema risk assessment or intervention in infants.
This study examined how GSK1322322, a novel antibacterial agent that inhibits bacterial peptide deformylase, affects the gastrointestinal microbiota. Researchers used next-generation sequencing of bacterial 16S rRNA genes in stool samples to compare the gut microbiota before dosing and at the end of the study. The drug was tested in a phase I, randomized, double-blind, placebo-controlled design, given either intravenously alone or as an oral-intravenous combination across single- and repeat-dose-escalation infusions.
The study population consisted of 61 healthy volunteers who provided stool samples at predosing and end-of-study time points. Participants were assigned to placebo, intravenous-only GSK1322322, or oral-intravenous combination GSK1322322 treatment groups. The abstract does not report additional demographic details such as age or sex distribution.
Placebo and intravenous-only treatment produced no significant changes in the relative abundance of gastrointestinal operational taxonomic units between the prestudy and end-of-study samples. Oral-intravenous treatment, however, caused significant decreases in Firmicutes and Bacteroidales and significant increases in Betaproteobacteria, Gammaproteobacteria, and Bifidobacteriaceae. Microbiome diversity plots clearly separated the end-of-study oral-intravenous samples from all other samples, and inferred genome function pointed to increased bacterial transporter and xenobiotic metabolism pathways in this group. A phylogenetic analysis of peptide deformylase sequences suggested that antibiotic target homology is one factor shaping how gut bacteria respond to the drug.
The findings indicate that route and regimen of antibiotic dosing, not just the drug's mechanism of action, materially determine its impact on the gut microbiota. Because oral-intravenous administration produced distinct, measurable shifts while intravenous-only dosing did not, dosing strategy could be used to help limit disruption of the gastrointestinal microbiome during antibiotic development. The results also suggest that target homology across bacterial species should be considered when predicting an antibiotic's off-target effects on commensal populations.
This study examined the microbiome of the colorectal tumor microenvironment compared with matched normal colon tissue from the same individuals. Researchers sequenced these paired samples to identify microbial taxa that were differentially abundant between tumor and normal tissue. They also functionally characterized the microbiome of each pair to find metabolic and virulence-related pathways enriched in tumor-associated bacteria. Using matched pairs from the same patient provided an internal control for host genetics and environmental exposures.
The study drew on 44 primary colorectal tumor tissue samples and 44 patient-matched normal colon tissue samples, for a total of 88 samples. Each tumor sample was paired with adjacent normal tissue from the same individual, rather than from separate healthy controls. The abstract does not report additional demographic details such as age, sex, or cancer stage.
Tumors harbored microbial communities that were distinct from those of nearby healthy tissue, with increased microbial diversity in the tumor microenvironment. The abundances of both commensal and pathogenic bacterial taxa shifted between tumor and normal samples, including changes involving Fusobacterium and Providencia. Functional analysis identified pathways enriched in the tumor-associated microbiota, pointing toward virulence-related genes as a feature of this shifted community.
By using matched tumor and normal tissue from the same patients, the study strengthens evidence that the colorectal tumor microenvironment selects for a distinct, functionally altered microbial community rather than reflecting only general host or environmental differences. The enrichment of virulence-associated pathways in tumor-associated bacteria suggests that host-bacteria interactions, including pathogenic taxa such as Fusobacterium, may play an active role in the tumor microenvironment. These findings support further investigation into microbial virulence factors as potential contributors to, or markers of, colorectal cancer biology.
This study investigated whether the gut microbiota is altered in patients with multiple sclerosis (MS), an autoimmune disease of the brain and spinal cord whose pathogenesis remains poorly understood. Researchers had been guided by findings from experimental autoimmune encephalomyelitis (EAE) animal models suggesting that altered gut microbiota could play a role in MS development. Fecal bacterial communities were profiled using high-throughput, culture-independent pyrosequencing of the 16S ribosomal RNA gene. The analysis compared community structure and species-level relative abundance between MS patients and healthy subjects.
The cohort included 20 Japanese patients with relapsing-remitting multiple sclerosis (MS20), compared against 40 healthy Japanese subjects (HC40). An additional 18 healthy subjects (HC18) contributed repeated fecal samples over the course of months, totaling 158 longitudinal samples, which were used to test whether the MS-associated differences were reproducible against natural fluctuations in a healthy gut microbiota. This design let the researchers distinguish disease-associated dysbiosis from normal within-person variability over time.
Pyrosequencing revealed a moderate dysbiosis in the overall structure of the gut microbiota in patients with MS compared to healthy controls. Twenty-one bacterial species showed significantly different relative abundance between the MS20 and HC40 groups. Notably, when compared against the 158 longitudinal HC18 samples, these differences held up reproducibly, and the abstract highlights a striking depletion of species belonging to the Clostridia XIVa and IV clusters in MS patients.
The findings support the hypothesis that gut microbiota alterations are associated with multiple sclerosis, reinforcing a possible gut-immune axis in MS pathogenesis. The specific depletion of Clostridia XIVa and IV cluster species is notable because these clusters include many commensal, fiber-fermenting bacteria implicated in immune regulation. This work adds human evidence to a link previously suggested mainly by animal EAE models and points toward gut microbiota as a potential avenue for understanding or influencing MS disease processes.
This study examined the gut mucosal microbiome across sequential stages of colorectal tumorigenesis, from adenoma to carcinoma. Researchers catalogued microbial communities in lesion tissue and in adjacent, seemingly normal mucosae to trace how dysbiosis develops as colorectal cancer (CRC) progresses. They used probabilistic partitioning of relative abundance profiles to identify recurring microbial community configurations, or metacommunities, associated with each stage. They also examined correlation and co-exclusion patterns among bacterial taxa to characterize how community structure changes over the course of disease.
The analysis drew on human gut mucosal tissue from 47 paired samples of adenoma and adenoma-adjacent mucosae, and 52 paired samples of carcinoma and carcinoma-adjacent mucosae. An additional 61 healthy control samples were included for comparison. The findings were further checked against two previously published, independently collected data sets to confirm the alterations observed in the CRC-associated microbiome.
A metacommunity dominated by members of the oral microbiome was primarily associated with colorectal cancer, distinguishing cancerous tissue from healthy and precancerous states. Paired-sample analysis revealed clear differences in microbial community configuration between lesions and their adjacent mucosae. Correlation analysis of bacterial taxa showed early signs of dysbiosis already present in adenoma, the precancerous stage, while co-exclusive relationships among taxa became more common as tissue progressed to carcinoma. These patterns were validated against two independent published data sets, supporting the consistency of the association.
The findings suggest that a taxonomically defined microbial consortium, enriched in oral-associated bacteria, is implicated in the development of colorectal cancer. Because dysbiosis signals appear as early as the adenoma stage, gut mucosal microbiome profiling could support earlier detection of precancerous changes. The progressive shift toward co-exclusive taxa relationships from adenoma to carcinoma points to microbial community structure, not just individual species, as a marker of disease progression. Validation across independent data sets strengthens the case for using defined microbial consortia as reproducible biomarkers in colorectal carcinogenesis.
This study examined the gut microbiome in patients with new-onset Crohn's disease before they had started any treatment. Samples were collected from multiple gastrointestinal locations, including the ileum and rectum, as well as fecal samples. The goal was to characterize microbial dysbiosis at the earliest, treatment-naive stage of disease and to compare microbial signatures across sample sites and antibiotic exposure status.
The study drew on the largest pediatric Crohn's disease cohort assembled for microbiome analysis to date. Participants were newly diagnosed, treatment-naive children and adolescents with Crohn's disease. The abstract does not give an exact sample size or additional demographic detail.
An axis of dysbiosis emerged in which Enterobacteriaceae, Pasteurellaceae, Veillonellaceae, and Fusobacteriaceae were increased, while Erysipelotrichales, Bacteroidales, and Clostridiales were decreased, and this axis correlated strongly with disease status. Comparing patients with and without antibiotic exposure showed that antibiotic use amplified this Crohn's-associated dysbiosis. Comparisons across ileal, rectal, and fecal samples showed distinct microbial signatures by sample site at this early stage of disease.
Because dysbiosis is detectable before treatment begins, the rectal mucosal-associated microbiome may offer a convenient, minimally invasive target for early diagnosis of Crohn's disease. The finding that antibiotics amplify dysbiosis suggests antibiotic exposure should be accounted for when interpreting microbiome studies in IBD. Identifying a consistent dysbiosis axis across a large pediatric cohort also helps reconcile inconsistencies seen among smaller prior studies.
This study examined how the gut microbial community changes over time during the development of colitis-associated colorectal cancer. Researchers used azoxymethane/dextran sodium sulphate (AOM/DSS) treated mice as a model of chronic colitis progressing to cancer, comparing them against control mice. They applied high-throughput sequencing of the bacterial 16S rRNA gene (V3 region) to track longitudinal shifts in microbial community structure. They also measured a molecular network of six interconnected factors linking inflammation to cancer to see how microbiome changes corresponded with disease pathogenesis.
The study population was AOM/DSS treated mice modeling colitis-associated colorectal cancer, compared against untreated control mice. Sampling occurred longitudinally, with phylotype and molecular measurements taken after each AOM/DSS treatment cycle. This is an animal model study rather than a human cohort, so no patient demographic details apply.
Chronic colitis significantly altered the structure of the gut microbial community over time. Specific microbes, including Streptococcus luteciae, Lactobacillus hamster, Bacteroides uniformis, and Bacteroides ovatus, increased in abundance during colorectal carcinogenesis. These microbial shifts correlated with changes in a six-factor molecular network (p65, p53, COX-2, PPARgamma, CCR2, and beta-catenin) spanning inflammation to cancer pathways. The longitudinal microbial network constructed from these data showed that phylotype shifts across AOM/DSS cycles were complex and highly dynamic rather than following a simple linear pattern.
The findings suggest that specific bacterial taxa track closely with the molecular pathogenesis of colitis-associated colorectal cancer, supporting a mechanistic link between microbiome shifts and disease progression. Mapping dynamic microbe and molecule networks over time, rather than single time-point snapshots, may better capture how gut bacteria contribute to carcinogenesis. This network-based approach could help identify candidate microbial markers or targets tied to specific stages of inflammation-driven cancer development. Because this is a mouse model, further work would be needed to confirm relevance to human colitis-associated colorectal cancer.
This study examined changes in the human gut microbiome before and 3 months after Roux-en-Y gastric bypass (RYGB) surgery, using metagenomic sequencing. The researchers characterized intra-individual shifts in microbial composition following surgery. They then correlated these metagenomic changes with clinical indices of inflammation and metabolism. The aim was to better understand the poorly characterized cross talk between RYGB-induced metabolic effects and gut microbial changes.
The study population consisted of morbidly obese patients with a body mass index (BMI) greater than 40 kg/m2 who also had type 2 diabetes mellitus. Each patient's gut microbiome was sampled before RYGB and again 3 months after the procedure, allowing intra-individual comparison. The abstract does not state the exact number of patients enrolled.
Based on gene relative abundance profiles, the researchers identified 1061 species, 729 genera, 44 phyla, and 5127 KEGG Orthology (KO) groups, with most bacteria assignable to seven bacterial divisions. RYGB induced an overall shift characterized by a reduction in Firmicutes and Bacteroidetes and an increase in Proteobacteria. Twenty-two microbial species and 11 genera were significantly altered by the surgery. Principal component analysis grouped highly correlated species into two components, with Component 1 species mainly associated with BMI and C-reactive protein levels.
The findings suggest that RYGB produces a distinct and reproducible signature of gut microbial change, marked by a shift away from Firmicutes and Bacteroidetes toward Proteobacteria. The correlation between specific bacterial taxa and inflammatory markers like C-reactive protein and BMI supports the idea that post-surgical microbiome remodeling is linked to improvements in metabolic and inflammatory status. This points to the gut microbiome as a potential mechanistic contributor to, or biomarker of, the metabolic benefits of bariatric surgery in type 2 diabetes.
This study compared the diversity, composition, and temporal stability of the distal gut (fecal) microbiota between healthy children living in two very different settings. The researchers used molecular sequencing of the 16S rRNA gene, analyzing over 8,000 near full-length sequences plus more than 845,000 pyrosequencing reads of the V1-V3 region, to characterize which bacteria were present and how communities were structured. The goal was to fill a gap in knowledge, since prior gut microbiome research had focused mostly on infants and adults in developed countries rather than older children in developing countries.
The study compared healthy children ages 9 to 14 years living in an urban slum in Bangladesh with healthy children of the same age range living in an upper-middle class suburban community in the United States. Both groups were sampled for fecal bacterial community composition, and community structure was also tracked over time to assess stability. The abstract does not give an exact number of participants in each cohort.
The distal gut microbiota of Bangladeshi children showed significantly greater bacterial diversity than that of U.S. children, including novel lineages from several bacterial phyla. Bangladeshi and U.S. children also had distinct fecal bacterial community membership and structure overall. The Bangladeshi children's microbiota was enriched in Prevotella, Butyrivibrio, and Oscillospira and depleted in Bacteroides relative to U.S. children, a pattern that was similar to what has been seen in Bangladeshi adults.
These findings show that geography, diet, and living environment are associated with substantial differences in gut microbial diversity and composition even among healthy children of the same age. The presence of novel bacterial lineages and a distinct compositional pattern in Bangladeshi children suggests that microbiome reference data drawn mainly from developed-country populations may not generalize to children in developing countries. This underscores the need to study diverse populations and age groups, including older children and adolescents, when defining what constitutes a healthy gut microbiome.
This study investigated how the composition of the human intestinal microbiota relates to intestinal permeability and both local and systemic inflammation in obesity. Researchers profiled fecal microbiota using a phylogenetic microarray and compared this to markers of gut and whole-body inflammation. They also assessed gastroduodenal, small intestinal, and colonic permeability using a multisaccharide test, alongside metabolic markers such as HbA1c, transaminases, and lipids.
The study population consisted of 28 subjects spanning a wide BMI range of 18.6 to 60.3 kg/m2, covering both nonobese and obese individuals. Based on microbiota composition, these subjects segregated into two clusters: one made up predominantly of obese participants (15 of 19) and another made up exclusively of nonobese participants (9 of 9). This design allowed comparison of inflammatory and permeability measures across microbiota-defined groups rather than by BMI category alone.
Intestinal permeability did not differ between the two microbiota clusters, but the obese-predominant cluster showed reduced bacterial diversity, a decreased Bacteroidetes to Firmicutes ratio, and an increased abundance of potentially proinflammatory Proteobacteria. Fecal calprotectin, a marker of intestinal inflammation, was only detectable in a subset of subjects within the obese microbiota cluster (8 of 19, P = 0.02). Plasma C-reactive protein, a marker of systemic inflammation, was also increased in these subjects, linking microbiota composition to both local and systemic inflammatory signals.
The findings suggest that a distinct, less diverse microbiota profile enriched in Proteobacteria and depleted in Bacteroidetes relative to Firmicutes is associated with detectable gut and systemic inflammation in some obese individuals, independent of measured intestinal permeability. This points to microbiota composition, rather than barrier leakiness alone, as a candidate driver or marker of the inflammatory state seen in obesity. These results support further work on microbiota-targeted strategies to address obesity-associated inflammation.
This study examined whether human intestinal microbes play a role in the autoimmunity that often leads to type 1 diabetes (T1D), building on prior murine and rat models linking gut bacteria to diabetes onset. Researchers used high-throughput, culture-independent sequencing approaches to profile gut bacterial communities over time. They tracked how bacterial composition and diversity changed as autoimmunity developed, comparing children who progressed to T1D-associated autoimmunity with those who did not.
The subjects were young children at high genetic risk for type 1 diabetes. Autoimmune cases were compared over time against age-matched, genotype-matched, nonautoimmune control children. The abstract does not give an exact sample size, but the design followed this at-risk pediatric cohort longitudinally as they moved from infancy toward the toddler stage.
Bacterial diversity diminished over time in children who developed autoimmunity, relative to matched nonautoimmune controls. A single species, Bacteroides ovatus, accounted for nearly 24% of the total increase in the phylum Bacteroidetes in autoimmune cases compared with controls. Conversely, a human Firmicute strain (CO19) represented nearly 20% of the increase in Firmicutes seen in controls over the same period, a pattern opposite to what was seen in cases.
The findings support the idea that healthy infants develop increasingly stable, more diverse microbiomes as they approach toddlerhood, while children destined for autoimmunity show a different, less stable trajectory. This suggests specific microbial shifts, including loss of certain Firmicutes and expansion of Bacteroides ovatus, may be linked to the immune processes preceding type 1 diabetes. The results point toward the gut microbiome as a potential early marker or contributor to autoimmune risk in genetically susceptible children, warranting further work to define an autoimmune-associated microbiome signature.
This study examined the composition of predominant faecal microbiota in obese and non-obese children, focusing on gut bacteria involved in fermenting unabsorbed carbohydrate for energy conservation. Researchers used real-time PCR with primers targeted at 16S rDNA to quantify specific faecal bacterial groups. Dietary intake was also assessed through a 24 hour diet recall and a food frequency questionnaire covering the prior three months.
The study included 28 children aged 11 to 14 years who provided fresh faecal samples and completed the dietary survey. Fifteen participants (seven female) were classified as obese, with a median BMI-for-age at the 99th percentile. Thirteen participants (seven female) were normal weight, with a median BMI-for-age at the 50th percentile.
Energy, carbohydrate, fat and protein intake did not differ significantly between the obese and non-obese groups. Faecal levels of Bacteroides-Prevotella, Bifidobacterium species, the Lactobacillus acidophilus group, and Eubacterium rectale showed no significant differences between groups. Faecalibacterium prausnitzii, an anti-inflammatory commensal known for butyrate production, was significantly higher in obese children than in non-obese children (P = 0.0253).
The finding of elevated Faecalibacterium prausnitzii in obese children, despite comparable diets and similar levels of other major faecal bacteria, suggests this organism may be linked to obesity status independent of energy or macronutrient intake. Because F. prausnitzii is generally regarded as a beneficial, butyrate-producing commensal, this result complicates any simple framing of it as uniformly protective and points to the need for further work on its role in paediatric obesity. These findings support continued investigation into how specific commensal populations relate to weight status in children.
This study examined how habitual diet shapes gut microbial composition by comparing fecal microbiota profiles across two child populations with very different diets. The researchers used high-throughput 16S rDNA sequencing paired with biochemical analyses to characterize bacterial taxa and metabolic byproducts. The rural African diet studied was high in fiber and considered similar to diets from early agricultural human settlements, offering a natural contrast to a Westernized diet.
The study compared fecal samples from European children (EU) with those from children living in a rural village in Burkina Faso (BF). The BF children followed a polysaccharide-rich, high-fiber traditional diet, while the EU children followed a typical Western diet. The abstract does not give an exact number of participants.
BF children showed significant enrichment in Bacteroidetes and depletion in Firmicutes compared to EU children (P < 0.001). BF children uniquely harbored bacteria from the genera Prevotella and Xylanibacter, which carry genes for cellulose and xylan hydrolysis and were completely absent in EU children. BF children also had significantly higher short-chain fatty acid levels (P < 0.001) and significantly fewer potentially pathogenic Enterobacteriaceae, including Shigella and Escherichia (P < 0.05), than EU children.
The findings suggest that gut microbiota coevolved with a polysaccharide-rich diet, allowing fiber-fermenting bacteria to maximize energy extraction from otherwise indigestible plant polysaccharides. This points to fiber-degrading taxa like Prevotella and Xylanibacter, along with the short-chain fatty acids they produce, as central to a healthier microbial ecosystem. The lower abundance of Shigella and Escherichia in the high-fiber diet group also suggests diet may help shape microbiota in ways that limit pathogenic bacteria.
Only the title of this study was available, not the abstract, so this summary is necessarily limited. The title indicates the researchers examined the metabolic genes of the gut microbiome in patients who have an ileo-anal pouch. The stated focus was on whether this metabolic-gene dysbiosis resembles the pattern seen in Crohn's disease.
The title identifies the population as patients with an ileo-anal pouch, a surgically constructed reservoir typically created after removal of the colon and rectum. No sample size, recruitment setting, or additional demographic details are given in the title. Without an abstract, the exact cohort characteristics cannot be honestly specified beyond this population description.
The title states that the gut microbiomes of ileo-anal pouch patients show dysbiosis in metabolic genes. It further states that this pattern of dysbiosis resembles what is observed in Crohn's disease. No specific genes, pathways, taxa, or magnitude of change are provided, since only the title was available.
If metabolic-gene dysbiosis in ileo-anal pouches mirrors Crohn's disease, this suggests a shared functional microbial signature across these two gut conditions. This could support using Crohn's disease-associated metabolic markers to help understand or monitor pouch dysfunction. Because only the title was available, these implications are inferred and would need confirmation from the full study.
2026-07-04
Faecalibacterium prausnitzii majorTaxon page created: biology (morphology, butyrate metabolism, anti-inflammatory role), the beneficial factors and what threatens them, supportive interventions, the data-derived Conditions table across 109 conditions, and the full research feed.
Sokol H, Pigneur B, Watterlot L, et al.
Faecalibacterium prausnitzii is an anti-inflammatory commensal bacterium identified by gut microbiota analysis of Crohn disease patients.Proc Natl Acad Sci U S A. 2008
Hiippala K, Jouhten H, Ronkainen A, et al.
The potential of gut commensals in reinforcing intestinal barrier function and alleviating inflammation.Nutrients. 2018
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