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Anaerobutyricum hallii (formerly Eubacterium hallii) sits at a metabolic crossroads: it turns the acetate and lactate other microbes leave behind into butyrate, and it even makes vitamin B12.
Anaerobutyricum hallii, formerly Eubacterium hallii, is a beneficial gut commensal and a metabolic hub that converts leftover acetate and lactate into butyrate, also forms propionate, and produces vitamin B12. It improves insulin sensitivity in preclinical models and is a leading next-generation probiotic candidate.
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 MoreAnaerobutyricum hallii, formerly named Eubacterium hallii, is a beneficial anaerobic gut commensal that sits at a metabolic crossroads in the intestine.[1] It takes up glucose and the fermentation intermediates acetate and lactate that other microbes release and converts them into butyrate and hydrogen, and it also forms propionate and produces cobalamin (vitamin B12), making it a hub in the gut's metabolic trophic chain.[1] On this database it appears as a differentially abundant taxon across many human microbiome studies.
A. hallii improves insulin sensitivity and increases butyrate and energy expenditure in preclinical models, which has made it a leading next-generation probiotic candidate for metabolic health.[2] In this database's framework it is not a metal-weaponizing pathogen but a stabilizing, cross-feeding commensal whose presence marks the healthy anaerobic gut in which nutritional immunity keeps opportunists in check.[3]
A. hallii is a Gram-positive (structurally), strictly anaerobic, rod-shaped bacterium in the Lachnospiraceae family, adapted to ferment a broad range of substrates in the colon.[1] Its metabolic versatility, rather than any structural virulence trait, defines it.
A. hallii is a beneficial commensal. By converting acetate and lactate into butyrate it prevents lactate accumulation and supplies the colon's preferred fuel, stabilizing the fermentation chain and supporting barrier and metabolic health.[1] In diabetic models its administration improved insulin sensitivity, raised butyrate, and altered bile-acid metabolism.[2]
Its useful features are metabolic.
| Factor | Description and role |
|---|---|
| Lactate-to-butyrate cross-feeding | Converts acetate and lactate left by other microbes into butyrate, preventing lactate build-up and fueling colonocytes.[1] |
| Propionate formation | Uses 1,2-propanediol to form propionate, adding a second beneficial short-chain fatty acid.[1] |
| Vitamin B12 (cobalamin) production | Synthesizes cobalamin, contributing to the gut's vitamin economy and enabling its own propanediol metabolism.[1] |
| Insulin-sensitizing effect | Improved insulin sensitivity and energy expenditure in diabetic animal models, a basis for its probiotic development.[2] |
A. hallii is a cross-feeding fermenter, not a metal scavenger. By mopping up lactate and acetate into butyrate it keeps the fermentation chain balanced and the mucosa anaerobic, indexing a gut that resists the shift toward oxygen-tolerant, lipopolysaccharide-rich Enterobacteriaceae, the metal-weaponizing opportunists this database tracks.[3] Its decline marks that dysbiotic transition.
Its dependence on cross-fed substrates and an anaerobic niche makes it sensitive to diet and dysbiosis.
| Pressure | Effect |
|---|---|
| Low-fiber diet | Less fermentable substrate reduces the acetate and lactate supply that A. hallii cross-feeds on.[1] |
| Metabolic disease | Lower abundance accompanies insulin resistance and metabolic syndrome, both as marker and contributor.[2] |
| Dysbiosis and antibiotics | Loss of anaerobic cross-feeders during dysbiosis accompanies the Enterobacteriaceae shift.[3] |
The entries below are supportive strategies classified by our validation method and are not medical advice. The goal is to sustain this cross-feeding commensal.
| Intervention | Class | Status |
|---|---|---|
| Dietary fiber and resistant starch | Diet | Validation In Progress |
| A. hallii as a next-generation probiotic | Probiotic | Validation In Progress |
| Metabolic-health support | Practice | Validation In Progress |
| Intervention | Mechanism |
| Fiber and resistant starch | Feed the primary fermenters whose acetate and lactate A. hallii converts into butyrate.[1] |
| A. hallii probiotic | Administration improved insulin sensitivity and butyrate in preclinical models, the basis for its probiotic development.[2] |
| Metabolic-health support | Sustaining cross-feeding butyrate producers supports the anti-inflammatory, anaerobic gut that resists opportunist expansion.[3] |
Where Anaerobutyricum hallii (formerly Eubacterium hallii, NCBI:txid39488) 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 88 conditions and 104 studies, the signal is genuinely mixed: enriched in 30, depleted in 47, and direction-conflicting in 11 (directional agreement 0.61). Because A. hallii is a health-associated cross-feeding butyrate producer, depletion in a disease group is the more mechanistically interpretable direction, so the aggregate evidence tier is Low.
How to read these. A. hallii is often reported under its older name Eubacterium hallii, so pipelines built on either name may split its counts. It behaves as a marker of a healthy fermentation chain, so a drop in a disease cohort is the interpretable signal, and direction can vary by cohort, which is why the aggregate tier stays Low.
Internal summaries of the 104 studies we reviewed in which A. hallii was a differential taxon across this corpus.
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 examined whether gut microbiome composition and microbial metabolite profiles differ between lean and obese youth with type 1 diabetes (T1D). Researchers used metagenomic shotgun sequencing of stool samples to characterize bacterial community structure and taxa abundance. They also measured short-chain fatty acids (SCFAs) as microbial metabolite outputs. The goal was to describe obesity-associated gut microbial changes in a T1D population, a group already at elevated risk for complications.
The pilot study included T1D youth divided into a lean group (BMI 5th to under 85th percentile, n = 27) and an obese group (BMI at or above the 95th percentile, n = 21). Participants had a mean age of 15.3 years, mean glycated hemoglobin A1c of 7.8%, and mean diabetes duration of 5.1 years. The combined sample was 42.0% female and 94.0% White.
Bacterial community composition (beta-diversity) differed significantly between BMI groups. The obese group showed a significantly higher ratio of Prevotella to Bacteroides and increased relative abundance of Prevotella copri, along with other taxa that differed between lean and obese groups. Functional profiling also revealed upregulation of branched-chain amino acid (BCAA) biosynthesis pathways in the obese group, pointing to a metabolic signature accompanying the taxonomic shifts.
These findings suggest that obesity in T1D youth is accompanied by measurable, structured changes in gut microbial ecology and function, not just body composition differences. The Prevotella to Bacteroides shift and BCAA biosynthesis upregulation echo patterns reported in obesity research more broadly, raising the possibility of shared microbial mechanisms across metabolic conditions. Because this was a pilot study, the findings support further investigation into the gut microbiome as a potential contributor to, or biomarker for, obesity-related complications in T1D.
The study examined how consumption of fermented foods, specifically fermented milk and soybean products, relates to seasonal changes in gut microbiota structure and metabolite composition. Researchers sampled gut microbiota across three seasons: hot-humid summer, autumn, and dry winter. They tracked shifts between two microbial community states, one driven by Prevotella and another driven by Bifidobacterium and Ruminococcus, along with associated fatty acid derivatives. They also examined bimodal changes in Bacteroidota community structure that appeared most pronounced during summer.
The study population was 78 healthy Indian agrarian individuals living in a rural setting. Participants differed in how much fermented milk and soybean products they consumed, and this variation was used to compare microbiota outcomes. Sampling occurred repeatedly across the three seasons to capture within-person seasonal fluctuation rather than a single cross-sectional snapshot.
Gut microbiota shifted seasonally between two ecological states, a Prevotella-driven type and a Bifidobacterium/Ruminococcus-driven type, each linked to distinct fatty acid derivative profiles. Bacteroidota community structure showed a bimodal change during summer, an effect that was particularly evident in people who consumed fermented milk. Long-term consumption of fermented foods was associated with reduced gut microbiota diversity and lower bacterial load overall. The researchers also identified specific taxonomic groups that appeared to drive these seasonal fluctuations and the transitions between the two ecological states.
The findings suggest that habitual fermented food intake can shape how stable or resilient a person's gut microbiota is across seasons, rather than only affecting its composition at one point in time. Identifying the taxa that drive seasonal shifts and ecological-state transitions offers concrete targets for future dietary interventions. The authors frame this as a step toward strategies that could help sustain a healthy and resilient gut microbiota through diet.
Functional constipation (FC) significantly impacts children's health. This study investigates the prevalence and microbiota characteristics of FC in children aged 0-4 years in Zunyi area.
From October to December 2023, 2039 children aged 0-4 years in Zunyi were selected using stratified sampling and cross-sectional survey methods. A questionnaire based on Rome IV diagnostic criteria was used. Twenty-nine children with FC were randomly selected as the functional constipation group (FCG), and 26 healthy children, matched for age, sex, and area, were selected as the control group (CG).
A total of 2051 questionnaires were collected, with 2039 valid responses. Among them, 151 children had FC, resulting in a prevalence rate of 7.4%. The prevalence rates in boys and girls were 6.6% and 8.5%, respectively, with no significant gender difference (P > 0.05). Alpha diversity analysis revealed higher richness and diversity of intestinal flora in the FCG compared to the CG. At the phylum level, Actinobacteria, Firmicutes, Proteobacteria, and Bacteroidetes were dominant in both groups. The FCG showed a higher relative abundance of Firmicutes, Actinobacteria, and Proteobacteria compared to the CG (P < 0.05).
The prevalence of FC in children aged 0-4 years in Zunyi is 7.4%. Disease characteristics vary with age and living environment but are unrelated to gender. The gut microbiota of children with FC shows significant alterations, with higher diversity and specific phyla abundance.
Attention-deficit/hyperactivity disorder (ADHD), a common neurodevelopmental disorder in children, is associated with alterations in gut microbiota and short-chain fatty acids (SCFAs), which are metabolites influencing the gut-brain axis. Evidence suggests that psychostimulant medications, widely used to manage ADHD symptoms, may also impact gut microbiota composition and SCFA levels. This study explores these potential effects by examining gut microbiota profiles and SCFA concentrations in unmedicated and medicated children with ADHD, compared to healthy controls. Fecal samples from 30 children aged 6-12 years (10 unmedicated ADHD, 10 medicated ADHD, and 10 healthy controls) were analyzed using 16 S rRNA sequencing and targeted metabolomics. Unmedicated ADHD children show distinct gut microbiota profiles, with lower level of Tyzzerella, Prevotellaceae, and Coriobacteriaceae, compared to controls. Notably, propionic acid levels were negatively associated with ADHD symptom severity, suggesting a potential biomarker role. Medicated ADHD children showed lower gut microbial diversity, unique taxa, and lower SCFA levels, compared to unmedicated children with ADHD. These findings suggest that gut microbiota and SCFAs may be linked to ADHD symptomatology, underscoring the importance of gut-brain interactions in ADHD. This study highlights the potential of gut health monitoring as part of future ADHD management strategies.
The study developed a machine learning prediction model for postprandial glycemic response (PPGR) to food in pregnant women. It examined whether adding gut microbiota data to inputs like continuous glucose monitoring (CGM), meal content, lifestyle factors, and biochemical parameters could improve prediction accuracy. Gut microbiota composition was assessed using 16S rRNA gene sequence analysis of stool samples. The model's performance was then compared against a simpler approach based only on carbohydrate counting.
The study involved 105 pregnant women, of whom 77 had diet-treated gestational diabetes mellitus (GDM) and 28 were healthy. All participants underwent continuous glucose monitoring for 7 days, kept food diaries, and provided stool samples for microbiome analysis. This design allowed comparison of glycemic responses across both GDM-affected and healthy pregnancies.
Adding microbiome data increased the explained variance in peak glycemic levels (GLUmax) from 34% to 42%, and in incremental area under the glycemic curve (iAUC120) from 50% to 52%. The final model, which incorporated microbiota features, correlated better with measured PPGRs than a model based only on carbohydrate counts (r = 0.72 versus r = 0.51 for iAUC120). Despite this improvement, the authors noted that the microbiome's contribution to overall model performance was modest relative to other factors.
These findings suggest that gut microbiota data can meaningfully, though not dramatically, improve personalized glycemic response prediction for pregnant women, including those with gestational diabetes. This points toward the potential for microbiome-informed, individualized dietary guidance rather than relying solely on carbohydrate counting during pregnancy. Because the microbiome's added value was modest, it is likely best used as a complement to, rather than a replacement for, standard clinical and dietary monitoring tools.
The human microbiome plays a vital role in human health, mediated by the gut-brain axis, with a large diversity of functions and physiological benefits. The dynamics and mechanisms of meditations on oral and gut microbiome modulations are not well understood. This study investigates the short-term modulations of the gut and oral microbiome during an Arhatic Yoga meditation retreat as well as on the role of microbiome in improving well-being through a possible gut-brain axis.
A single-arm pilot clinical trial was conducted in a controlled environment during a 9-day intensive retreat of Arhatic Yoga meditation practices with vegetarian diet. Oral and fecal samples of 24 practitioners were collected at the start (Day0: T1), middle (Day3: T2), and end (Day9:T3) of the retreat. Targeted 16S rRNA gene amplicon sequencing was performed for both oral and gut samples. Functional pathway predictions was identified using phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt2). DESeq2 was used to identify the differential abundant taxa. Various statistical analyses were performed to assess the significant changes in the data.
Our findings revealed that Arhatic Yoga meditation together with a vegetarian diet led to changes in the oral and gut microbiome profiles within the 9-day retreat. Oral microbiome profile showed a significant (p < 0.05) difference in the species richness and evenness at the end of study, while non-metric multidimensional scaling (NMDS) confirmed the shift in the gut microbiome profile of the practitioners by T2 timepoint, which was further supported by PERMANOVA analysis (p < 0.05). Health-benefiting microbes known to improve the gastrointestinal and gut-barrier functions, immune modulation, and gut-brain axis were enriched. Gut microbiome of both beginner and advanced Arhatic Yoga practitioners showed similar trends of convergence by the end of study. This implies a strong selection pressure by Arhatic Yoga meditation together with a vegetarian diet on the beneficial gut microbiome.
This pilot study demonstrates that Arhatic Yoga meditation practices combined with a vegetarian diet during a short intensive retreat resulted in enrichment of known health-promoting microbes. Such microbial consortia may be developed for potential health benefits and used as probiotics to improve the gastrointestinal and immune systems, as well as functions mediated by the gut-brain axis.
Sauerkraut is a fermented food that has been suspected to have a beneficial impact on the gut microbiome, but scientific evidence is sparse. In this crossover intervention trial with 87 participants (DRKS00027007), we investigated the impact of daily consumption of fresh or pasteurized sauerkraut for 4 weeks on gut microbial composition and the metabolome in a healthy study population.
Using shotgun metagenomic sequencing, we observed changes in single bacterial species following fresh and pasteurized sauerkraut consumption. More pronounced changes were observed in the pasteurized sauerkraut intervention arm. Only pasteurized sauerkraut consumption increased serum short-chain fatty acids (SCFAs).
The gut microbiome of healthy individuals is rather resilient to short-term dietary interventions even though single species might be affected by sauerkraut consumption. Video Abstract.
Wild animals face numerous challenges in less ideal habitats, including the lack of food as well as changes in diet. Understanding how the gut microbiomes of wild animals adapt to changes in food resources within suboptimal habitats is critical for their survival. Therefore, we conducted a longitudinal sampling of three gibbon species living in high-quality (Nomascus hainanus) and suboptimal (Nomascus concolor and Hoolock tianxing) habitats to address the dynamics of gut microbiome assembly over one year. The three gibbon species exhibited significantly different gut microbial diversity and composition. N. hainanus showed the lowest alpha diversity and highest nestedness, suggesting a more specialized and potentially stable microbial community in terms of composition, while H. tianxing displayed high species turnover and low nestedness, reflecting a more dynamic microbial ecosystem, which may indicate greater sensitivity to environmental changes or a flexible response to habitat variability. The gut microbial community of N. concolor was influenced by homogeneous selection in the deterministic process, primarily driven by Prevotellaceae. In contrast, the gut microbial communities of H. tianxing and N. hainanus were influenced by dispersal limitation in the stochastic process, driven by Acholeplasmataceae and Fibrobacterota, respectively. Further, the microbial response patterns to leaf feeding in N. hainanus differed from those of the other two gibbon species. In conclusion, this first cross-species comparative study provides initial insights into the different ecological adaptive strategies of gut microbiomes from a point of community assembly, which could contribute to the long-term conservation of wild primates. In this study, we conducted longitudinal sampling of three gibbon species living in high-quality (Nomascus hainanus) and suboptimal (Nomascus concolor and Hoolock tianxing) habitats to address the dynamics of gut microbiome (composition, alpha diversity, beta diversity and assembly process) over one year.
Steatotic liver disease (SLD) is a leading cause of chronic liver disease worldwide. As SLD pathogenesis has been linked to gut microbiome alterations, we aimed to identify SLD-associated gut microbiome features early in SLD development by utilising a highly characterised cohort of community-dwelling younger adults.
At age 27 years, 588 participants of the Raine Study Generation 2 underwent cross-sectional assessment. Hepatic steatosis was quantified using a validated magnetic resonance imaging (MRI) volumetric liver fat fraction (VLFF) equation (HepaFat). Of the 588 participants, 488 (83%) were classified as having 'no SLD' (VLFF ≤ 3.55%), 76 (12.9%) with 'mild-moderate'
SLD in younger adults is associated with reduced intestinal microbial diversity and a pattern of bacterial taxa depletion that is consistent with other chronic inflammatory conditions. Our characterisation of gut microbiome characteristics in early SLD development provides a potential basis for risk identification and reduction.
Clinical data on oral fecal microbiota transplantation (FMT), a promising therapy for Crohn's disease (CD), are limited. Herein, we determined the short-term safety and feasibility of FMT for pediatric patients with active CD.
In this open-label, parallel-group, single-center prospective trial, patients with active CD were treated with oral FMT capsules combined with partial enteral nutrition (PEN) (80%). The control group comprised pediatric patients with active CD treated with PEN (80%) and immunosuppressants. Thirty-three patients (11.6 ± 1.82 years)-17 in the capsule and 16 in the control groups-were analyzed. Data regarding the adverse events, clinical reactions, intestinal microbiome composition, and biomarker parameters were collected and compared post-treatment.
At week 10, the clinical and endoscopic remission rates did not differ between the two groups. By week 10, the mean fecal calprotectin level, C-reactive protein level, erythrocyte sedimentation rate, simple endoscopic score for CD, and pediatric CD activity index decreased significantly in the capsule group (all P < 0.05). The main adverse event was mild-to-moderate constipation. Core functional genera, Agathobacter, Akkermansia, Roseburia, Blautia, Subdoligranulum, and Faecalibacterium, were lacking pre-treatment. Post-treatment, the implantation rates of these core functional genera increased significantly, which positively correlated with the anti-inflammatory factor, interleukin (IL)-10, and negatively correlated with the pro-inflammatory factor, IL-6. The combination of these six functional genera distinguished healthy children from those with CD (area under the curve = 0.96).
Oral FMT capsules combined with PEN (80%) could be an effective therapy for children with active CD. The six core functional genera identified here may be candidate biomarkers for identifying children with CD.
Shigella is a significant cause of diarrhea, predominantly affecting children in low- and middle-income countries, as well as international travelers. Not all individuals exposed to Shigella or other enteropathogens have symptomatic responses, and investigating the differences between symptomatic and asymptomatic individuals can further our understanding of enteropathogen proliferation and symptomatic responses. Here, we profiled the fecal microbiomes of 45 individuals infected with Shigella sonnei strain 53G through 16S rRNA sequencing in a controlled human infection model before and during infection, after antibiotic treatment, and after clinical recovery. This model allowed for a detailed exploration of microbiome temporal dynamics during infection, as well as a comparative analysis between those with shigellosis (defined as severe symptoms caused by Shigella infection, including severe diarrhea, fever, and/or abdominal pain) and those without shigellosis. Alpha diversity decreased to a greater degree in individuals with shigellosis. Perturbations in microbial composition during infection and antibiotic treatment were significantly larger in individuals diagnosed with shigellosis than in those who were not. Participants with shigellosis had persistent changes to their microbiomes after recovery, while those without shigellosis recovered to a composition resembling their pre-infection microbiomes. These persistent changes included taxa associated with gut inflammation, such as a decrease in Faecalibacterium and an increase in Ruminococcus gnavus. Furthermore, the initial microbiomes of participants who did not develop shigellosis had a greater abundance of taxa associated with short-chain fatty acid production than participants who did develop shigellosis, including Bifidobacterium, Roseburia, and Faecalibacterium. These data could help prevent Shigella infection or symptoms
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.
The gut microbiota has been linked to non-communicable diseases, including chronic kidney disease (CKD). However, the relationships between gut microbiome composition changes, uraemic toxins (UTs) accumulation, and diet on CKD severity and progression remain underexplored. To characterise relationships between gut microbiome composition and functionality, UTs diet, and CKD severity and progression, as well as assess microbial contributions to UTs accumulation through mice faecal microbiota transplantation (FMT).
This study profiled the gut microbiome of 240 non-dialysis patients with CKD (CKD-REIN cohort) using shotgun metagenomics, with follow-up in 103 patients after 3 years, with comparisons with healthy volunteers from the Milieu Intérieur cohort. A multiomics approach identifies features associated with CKD severity (and progression), with validation in an independent Belgian cohort. Experimental models used FMT to test CKD gut microbiome effects on UTs and kidney fibrosis. Changes in gut microbiome over time were evaluated, and the impact of diet on these changes was assessed.
Compared with matched healthy controls, patients with CKD exhibited gut microbiota alteration, with enrichment of UT precursor-producing species. Patients with severe CKD exhibited higher UT levels and greater enrichment of UT (precursor)-producing species in the microbiota than patients with moderate CKD. Over time, UT (precursor)-producing species increased, and a plant-based low protein diet appeared to mitigate these changes. FMT from patients with CKD to antibiotic-treated CKD model mice increased serum UT levels and exacerbated kidney fibrosis.
This study highlights the role of the microbiome and UTs in CKD, suggesting a potential therapeutic target to slow disease progression.
COVID-19 has had a profound impact on public health globally. However, most studies have focused on patients with long COVID or those in the acute phase of infection, with limited research on the health of individuals who have recovered from mild COVID-19. This study investigates the long-term changes in bacterial and fungal communities in individuals recovering from mild COVID-19 and their clinical relevance.
Healthy individuals from Hainan Province were enrolled before the COVID-19 outbreak, along with individuals recovering from COVID-19 at 3 months and 6 months post-recovery. Stool, blood samples, and metadata were collected. Metagenomic sequencing and Internal Transcribed Spacer (ITS) analysis characterized bacterial and fungal communities, while bacterial-fungal co-occurrence networks were constructed. A random forest model evaluated the predictive capacity of key taxa.
The gut microbiota of COVID-19 recoverees differed significantly from that of healthy individuals. At 3 months post-recovery, probiotics (e.g., Blautia massiliensis and Kluyveromyces spp.) were enriched, linked to improved metabolism, while at 6 months, partial recovery of probiotics (e.g., Acidaminococcus massiliensis and Asterotremella spp.) was observed alongside persistent pathogens (e.g., Streptococcus equinus and Gibberella spp.). Dynamic changes were observed, with Acidaminococcus massiliensis enriched at both baseline and 6 months but absent at 3 months. Co-occurrence network analysis revealed synergies between bacterial (Rothia spp.) and fungal (Coprinopsis spp.) taxa, suggesting their potential roles in gut restoration. The bacterial random forest model (10 taxa) outperformed the fungal model (8 taxa) in predicting recovery status (AUC = 0.99 vs. 0.80).
These findings highlight the significant long-term impacts of mild COVID-19 recovery on gut microbiota, with key taxa influencing metabolism and immune regulation, supporting microbiome-based strategies for recovery management.
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.
Metabolic dysfunction-associated steatotic liver disease (MASLD) is associated with dysbiosis of the gut microbiota. We evaluated the effect of next generation probiotics (Lactobacillus delbrueckii subsp. Lactis [LL001], L. helveticus [LH001], and Pediococcus pentosaceus KID7 [PPKID7]) on liver function parameters and stool microbiome in patients with MASLD.
We conducted a double-blind parallel trial of 110 patients diagnosed with MASLD. Participants were randomly assigned to four groups given three probiotics (3 capsules [9 × 109 CFU]/day, n = 85) or placebo (n = 25) alongside sylimarin for 8 weeks. Clinical characteristics, serum samples, and stool samples for 16 S rRNA gene sequencing were collected at the start and end point of the study. The primary endpoint was improvement in liver function.
In the probiotic group, LL001 treatment improved alanine transaminase (87.3 ± 8.2 to 71.1 ± 6.0 U/L, P = 0.01) and aspartate transaminase levels (64.9 ± 4.9 to 50.0 ± 3.5 U/L, P < 0.01), LH001 group showed body weight reduction (78.4 ± 3.0 to 77.2 ± 2.8 kg, P = 0.01), and PPKID7 reduced cholesterol levels (186.1 ± 7.0 to 178.0 ± 7.9 mmol/L, P = 0.03). Probiotics treatment decreased the abundance of Proteobacteria and increased the abundance of Ruminococcaceae and Lachnospiraceae in the LL001 group. In the pre- and post-comparison of probiotic treatment at the level of the top 20 genera, a tendency was observed to decrease the genera Haemohlius and Ruminococcus_g2 while increasing the genus Bifidobacterium.
Eight weeks of probiotics supplementation was associated with changes in the stool microbiome and improvements in the blood biochemical parameters of MASLD.
This study analyzed a newly built resource called curatedMetagenomicData (cMD) 3, a uniformly processed collection of over 22,000 human microbiome samples with manually curated metadata. The researchers combined data across 94 studies and 42 countries to make large-scale meta-analysis possible, something that had been difficult due to a lack of standardization across public datasets. Using this resource, they searched for microbial species and functions associated with host traits and disease status. They also developed a new metric, the oral enrichment score (OES), based on the relative abundance in the gut of bacteria that are typically found in the oral cavity rather than the gut.
The analysis drew on more than 22,000 human microbiome samples aggregated from 94 separate studies conducted across 42 countries. This is a public, pooled metagenomic dataset rather than a single original cohort recruited for this study. The abstract does not give specific demographic breakdowns beyond noting that sex, age, body mass index, and disease status were among the host variables examined across this large, internationally diverse sample collection.
The meta-analysis identified hundreds of microbial species and thousands of microbial functions that were significantly associated with a person's sex, age, body mass index, and disease status. The team catalogued these associations as a reference resource for the field. Most notably, they found that a higher oral enrichment score (OES), meaning greater relative abundance of oral-type bacteria in the gut, was a consistent feature of individuals with disease. The overall patterns identified across the dataset were described as modest but widely shared across the many studies pooled together.
The findings suggest that OES can serve as a simple, quantifiable signal of altered gut microbiome health, since oral bacteria showing up in the gut appears to track with disease status across many different conditions and populations. Because cMD 3 is described as reproducible and readily updatable, it offers an ongoing reference dataset that other researchers can use to validate microbiome-disease associations. This kind of large, standardized meta-analysis approach could help establish more generalizable, cross-study biomarkers of microbiome health rather than relying on findings from single, smaller cohorts.
Altered gut microbiota has been connected to hepatocellular carcinoma (HCC) occurrence and advancement. This study was conducted to identify a gut microbiota signature in differentiating between viral-related HCC (Viral-HCC) and non-hepatitis B-, non-hepatitis C-related HCC (NBNC-HCC). Fecal specimens were obtained from 16 healthy controls, 33 patients with viral-HCC (17 and 16 cases with hepatitis B virus (HBV) and hepatitis C virus (HCV) infection, respectively), and 18 patients with NBNC-HCC. Compositions of fecal microbiota were assessed by 16S rRNA sequencing. Bioinformatic analysis was performed by the DADA2 pipeline in the R program. Significantly different genera from the top 50 relative abundance were used to classify between subgroups of HCC by the Random Forest algorithm. Our data demonstrated that the HCC group had a significantly decreased alpha-diversity and changed microbial composition in comparison with healthy controls. Within the top 50 relative abundance, there were 11 genera including Faecalibacterium, Agathobacter, and Coprococcus that were significantly enhanced in Viral-HCC, while 5 genera such as Bacteroides, Streptococcus, Ruminococcus gnavus group, Parabacteroides, and Erysipelatoclostridium were enhanced in NBNC-HCC. Compared to Viral-HCC, the NBNC-HCC subgroup significantly reduced various short-chain fatty acid-producing bacteria, as well as declined fecal butyrate but elevated plasma surrogate markers of microbial translocation. Based on the machine learning algorithm, a high diagnostic accuracy to classify HCC subgroups was achieved with an area under the receiver-operating characteristic (ROC) curve (AUC) of 0.94. Collectively, these data revealed that gut dysbiosis was distinct according to etiological factors of HCC, which might play an essential role in hepatocarcinogenesis. These findings underscore the possible use of a gut microbiota signature for the diagnosis and therapeutic approaches regarding different subgroups of HCC. KEY POINTS: • Gut dysbiosis is connected to hepatocarcinogenesis and can be used as a novel biomarker. • Gut microbiota composition is significantly altered in different etiological factors of HCC. • Microbiota-based signature can accurately distinguish between Viral-HCC and NBNC-HCC.
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 examined whether the gut and pharyngeal microbiome is associated with tuberculosis (TB) disease stages. Researchers used full-length 16S rDNA amplicon sequencing performed with Oxford Nanopore Technologies to profile bacterial communities. The comparison spanned TB-negative controls, latent TB, and active TB groups. The goal was to identify microbial differences that track with TB progression from latent to active disease.
The subjects were 71 cynomolgus macaques, an animal model used to study TB pathogenesis. The macaques were divided into three groups: TB (-) control, TB (+) latent, and TB (+) active. No human cohort was involved, so findings reflect a non-human primate model rather than a human population.
In the pharyngeal microbiome, Haemophilus hemolyticus was decreased and Prevotella species were increased in TB (+) macaques compared to controls. In the gut microbiome, Eubacterium coprostanoligenes was enriched in TB (+) macaques. These shifts distinguished infected animals from TB-negative controls, suggesting that specific taxa track with TB status in both the pharynx and the gut.
The findings suggest that alterations in gut and pharyngeal bacteria may influence host immune regulation and TB severity, though the underlying mechanisms still need to be explored and validated. This work points to potential host-microbe interactions relevant to TB progression that could inform future understanding of disease biology. It also raises the possibility that microbiome-based markers or targets could eventually contribute to TB therapeutics, pending further mechanistic and translational research.
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.
People living with HIV (PLWH), even when viral replication is controlled through antiretroviral therapy (ART), experience persistent inflammation. This inflammation is partly attributed to intestinal microbial dysbiosis and translocation, which may lead to non-AIDS-related aging-associated comorbidities. The extent to which living with HIV - influenced by the infection itself, ART usage, sexual orientation, or other associated factors - affects the biological age of the intestines is unclear. Furthermore, the role of microbial dysbiosis and translocation in the biological aging of PLWH remains to be elucidated. To investigate these uncertainties, we used a systems biology approach, analyzing colon and ileal biopsies, blood samples, and stool specimens from PLWH on ART and people living without HIV (PLWoH) as controls.
PLWH exhibit accelerated biological aging in the colon, ileum, and blood, as measured by various epigenetic aging clocks, compared to PLWoH. Investigating the relationship between microbial translocation and biological aging, PLWH had decreased levels of tight junction proteins in the intestines, along with increased microbial translocation. This intestinal permeability correlated with faster biological aging and increased inflammation. When investigating the relationship between microbial dysbiosis and biological aging, the intestines of PLWH had higher abundance of specific pro-inflammatory bacteria, such as Catenibacterium and Prevotella. These bacteria correlated with accelerated biological aging. Conversely, the intestines of PLWH had lower abundance of bacteria known for producing the anti-inflammatory short-chain fatty acids, such as Subdoligranulum and Erysipelotrichaceae, and these bacteria were associated with slower biological aging. Correlation networks revealed significant links between specific microbial genera in the colon and ileum (but not in feces), increased aging, a rise in pro-inflammatory microbe-related metabolites (e.g., those in the tryptophan metabolism pathway), and a decrease in anti-inflammatory metabolites like hippuric acid.
We identified specific microbial compositions and microbiota-related metabolic pathways that are intertwined with intestinal and systemic biological aging. This microbial signature of biological aging is likely reflecting various factors including the HIV infection itself, ART usage, sexual orientation, and other aspects associated with living with HIV. A deeper understanding of the mechanisms underlying these connections could offer potential strategies to mitigate accelerated aging and its associated health complications. Video Abstract.
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.
The role of the gut microbiota in energy metabolism of the host has been established, both in overweight/obesity, as well as in undernutrition/stunting. Dysbiosis of the gut microbiota may predispose to stunting. The aim of this study was to compare the gut microbiota composition of stunted Indonesian children and non-stunted children between 36 and 45 months from two sites on the East Nusa Tenggara (ENT) islands. Fecal samples were collected from 100 stunted children and 100 non-stunted children in Kupang and North Kodi. The gut microbiota composition was determined by sequencing amplicons of the V3-V4 region of the 16S rRNA gene. Moreover, fecal SCFA concentrations were analyzed. The microbiota composition was correlated to anthropometric parameters and fecal metabolites. The phyla Bacteroidetes (Bacteroidota; q = 0.014) and Cyanobacteria (q = 0.049) were significantly higher in stunted children. Three taxa at genus levels were consistently significantly higher in stunted children at both sampling sites, namely Lachnoclostridium, Faecalibacterium and Veillonella (q < 7 * 10-4). These and 9 other taxa positively correlated to the z-score length-for-age (zlen), while 11 taxa negatively correlated with zlen. Several taxa also correlated with sanitary parameters, some of which were also significantly different between the two groups. All three fecal SCFA concentrations (acetate, propionate and butyrate) and their total were lower in stunted children compared to non-stunted children, although not significant for butyrate, indicating lower energy-extraction by the gut microbiota. Also, since SCFA have been shown to be involved in gut barrier function, barrier integrity may be affected in the stunted children. It remains to be seen if the three taxa are involved in stunting, or are changed due to e.g. differences in diet, hygiene status, or other factors. The observed differences in this study do not agree with our previous observations in children on Java, Indonesia. There are differences in infrastructure facilities such as clean water and sanitation on ENT and Java, which may contribute to the differences observed. The role of the gut microbiota in stunting therefore requires more in depth studies. Trial registration: the trial was registered at ClinicalTrials.gov with identifier number NCT05119218.
This pilot prospective cohort study examined whether ethnicity influences gut microbiome dysbiosis in pregnancies complicated by gestational diabetes mellitus (GDM). The researchers also investigated whether diet and lifestyle modifications made after a GDM diagnosis could modulate the gut microbiome. Fecal samples were collected at two time points, 24 to 28 weeks and 36 to 40 weeks of gestation, and analyzed using targeted 16S rRNA gene-based amplicon sequencing. Statistical comparisons between groups used PERMANOVA, differential abundance testing used DeSeq2, and functional predictions were generated with PICRUSt2.
The cohort included 53 women with GDM and 16 women without GDM, all residing in Singapore. Participants belonged to three Asian ethnic groups: Chinese, Malay, and Indian. This design allowed comparison of gut dysbiosis patterns both across GDM status and across ethnic background within the same population.
Among women with GDM, gut microbiomes from the different ethnic groups shared common features rather than diverging by ethnicity. This suggests that GDM-related dysbiosis is a relatively consistent phenomenon across the Chinese, Malay, and Indian groups studied. The abstract indicates that ethnicity was not a major driver of the microbiome differences observed in these GDM pregnancies.
If GDM-associated gut dysbiosis is largely independent of Asian ethnic background, microbiome-targeted strategies for GDM may generalize across these ethnic groups rather than needing ethnicity-specific approaches. This supports the idea that dietary and lifestyle interventions after a GDM diagnosis could be evaluated and applied similarly across diverse populations. As a pilot study, these findings point to the need for larger cohorts to confirm whether microbiome-based interventions can be standardized across ethnicities.
This study examined the relationship between faecal microbiota and nutritional status in schoolchildren using a double-blinded cluster-randomized controlled trial. Researchers tested the impact of six months of consumption of rice fortified with two different levels of vitamins and minerals. The faecal microbiota was characterized using 16S rRNA sequencing and analyzed against nutritional, micronutrient, inflammatory, and parasitic infection markers. The trial was registered with ClinicalTrials.gov (NCT01706419).
The study population consisted of 380 Cambodian schoolchildren enrolled in a cluster-randomized trial. Participants were assessed for age, sex, nutritional status (including underweight and stunting), and micronutrient status covering iron, zinc, and vitamin A deficiencies. Additional measures included anaemia, iron deficient anaemia, hemoglobinopathy, systemic and gut inflammation, and parasitic infection status.
The faecal microbiota of these schoolchildren showed a surprisingly high proportion of Lactobacillaceae. Deficiencies in specific micronutrients, namely iron and vitamin A, correlated with particular microbiota profiles, while zinc deficiency showed no such association. The six-month rice fortification intervention altered both the composition and the predicted functions of the microbiota, with the two rice treatments producing different effects. The abstract does not report findings related to Desulfovibrio, sulfate-reducing bacteria, or sulfur metabolism.
These findings suggest that specific micronutrient deficiencies, rather than micronutrient status broadly, are linked to distinct gut microbiota signatures in children. The differential response of microbiota composition and function to two fortification formulations indicates that the type of nutrient fortification matters, not just its presence. This work supports further investigation into how targeted nutritional interventions might be designed to favorably shape childhood gut microbiota and, in turn, nutritional and inflammatory outcomes.
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 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 the gut microbiome and serum metabolome differ between people with lactose intolerance (LI) and those without it. The researchers combined a paired-sample analysis of American Gut Project (AGP) data with metagenomic and untargeted metabolomic analyses in a separate cohort. They also performed fecal microbiota transplantation (FMT) experiments to test whether the LI-associated gut microbiome could influence inflammatory outcomes. The goal was to characterize the interaction between gut microbiota and circulating metabolites in LI.
The study drew on two data sources: paired samples from the American Gut Project (AGP), a large public microbiome dataset, and a Chinese cohort in which metagenomic and metabolomic profiling was performed. The abstract does not give exact sample sizes for either group. FMT experiments were also conducted, implying an animal model component, though further details are not specified in the abstract.
Fourteen microbial genera differed significantly between LI and control individuals in the AGP data. In the Chinese cohort, a machine learning approach identified seven bacterial species and nine metabolites that could distinguish the two groups. Notably, increased Escherichia coli in the LI group was negatively correlated with several metabolites, including PC (22:6/0:0), indole, and Lyso PC, while reduced levels of Faecalibacterium prausnitzii and Eubacterium rectale were positively associated with other metabolic changes.
The findings suggest that lactose intolerance is accompanied by a distinct gut microbial and metabolic signature, not just a lactase enzyme deficiency. The rise in Escherichia coli alongside depletion of beneficial short-chain-fatty-acid producers like Faecalibacterium prausnitzii and Eubacterium rectale points to a shift toward a more pro-inflammatory microbial community. This raises the possibility that microbiome-targeted interventions could help manage LI-related gastrointestinal symptoms, and the FMT experiments support a causal link between this altered microbiome and inflammatory outcomes.
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.
Background/Objectives: Age-related macular degeneration (AMD) is a leading cause of visual impairment in the elderly and is characterized by a multifactorial etiology. Emerging evidence points to the potential involvement of the gut-retina axis in AMD pathogenesis, prompting exploration into novel therapeutic strategies. This study aims to investigate the effects of some micronutrients (such as lutein and zeaxanthin) and saffron (as a supplement)-known for their anti-inflammatory properties-on ophthalmological and microbial parameters in neovascular AMD (nAMD) patients. Methods: Thirty naive nAMD patients were randomized to receive daily micronutrient supplementation alongside anti-VEGF (vascular endothelial growth factor) therapy, or anti-VEGF treatment alone, over a 6-month period, with comparisons made to a healthy control (HC) group (N = 15). Ophthalmological assessments, biochemical measurements, and stool samples were obtained before and after treatment. Gut microbiota (GM) characterization was performed using 16S rRNA sequencing, while short-chain fatty acids (SCFAs), medium-chain fatty acids (MCFAs), and long-chain fatty acids (LCFAs) were analyzed with a gas chromatography-mass spectrometry protocol. Results: Compared to HC, nAMD patients exhibited reduced GM alpha diversity, altered taxonomic composition, and decreased total SCFA levels, in addition to elevated levels of proinflammatory octanoic and nonanoic acids. Micronutrient supplementation was associated with improved visual acuity relative to the group treated with anti-VEGF alone, along with a decrease in the total amount of MCFAs, which are metabolites known to have adverse ocular effects. Conclusions: In conclusion, despite certain limitations-such as the limited sample size and the low taxonomic resolution of 16S rRNA sequencing-this study highlights compositional and functional imbalances in the GM of nAMD patients and demonstrates that micronutrient supplementation may help restore the gut-retina axis. These findings suggest the therapeutic potential of micronutrients in enhancing ocular outcomes for nAMD patients, underscoring the complex interaction between GM and ocular health.
Developing microbiome-based markers for pediatric inflammatory bowel disease (PIBD) is challenging. Here, we evaluated the diagnostic and prognostic potential of the gut microbiome in PIBD through a case-control study and cross-cohort analyses. In a Korean PIBD cohort (24 patients with PIBD, 43 controls), we observed that microbial diversity and composition shifted in patients with active PIBD versus controls and recovered at remission. We employed a differential abundance meta-analysis approach to identify microbial markers consistently associated with active inflammation and remission across seven PIBD cohorts from six countries (n = 1,670) including our dataset. Finally, we trained and tested various machine learning models for their ability to predict a patient's future remission based on baseline bacterial composition. An ensemble model trained with the amplicon sequence variants effectively predicted future remission of PIBD. This research highlights the gut microbiome's potential to guide precision therapy for PIBD.
This study examined whether appendectomy raises colorectal cancer (CRC) risk by disturbing the gut microbiome. The researchers combined a population-based longitudinal analysis with shotgun metagenomic sequencing of fecal samples to characterize microbial changes after appendectomy. They then tested whether appendectomy directly promotes colorectal tumorigenesis using a mouse model, and examined microbial network structure to identify which bacteria most strongly organize the post-appendectomy community.
Cohort 1 was a large population-based longitudinal group of 129,155 individuals followed for up to 20 years to assess CRC incidence after appendectomy. Cohort 2 consisted of 314 people whose fecal samples underwent shotgun metagenomic sequencing to compare gut microbial composition between appendectomy subjects and controls. The mouse tumorigenesis experiments used an animal model to test causality, as described in the abstract.
Appendectomy was associated with a 73.0 percent increase in CRC risk over 20 years of follow-up (adjusted SHR 1.73, 95% CI 1.49-2.01, P < 0.001). Metagenomic sequencing showed appendectomy subjects had enrichment of seven CRC-promoting bacteria, including Bacteroides fragilis (B. fragilis), Bacteroides vulgatus, Veillonella dispar, and several Prevotella species, alongside depletion of five beneficial commensals such as Collinsella aerofaciens and multiple Blautia species. Microbial network analysis revealed stronger correlations among the enriched, oncogenic-pathway-associated bacteria in appendectomy subjects, with B. fragilis occupying the central, most connected position in this network. Mouse experiments confirmed that appendectomy promoted colorectal tumorigenesis through its effects on the gut microbiome.
These findings suggest appendectomy is not a neutral procedure with respect to long-term colorectal cancer risk, and that this risk may be mediated by a shift toward a CRC-promoting, B. fragilis-centered microbial network. Because B. fragilis functioned as the hub of this altered network, it may represent a key node for monitoring or intervention in post-appendectomy patients. The mouse data support a causal, not merely correlational, link between appendectomy-driven dysbiosis and tumorigenesis, strengthening the rationale for microbiome surveillance in this population.
This study examined how gut microbiome composition and function differ across subtypes of irritable bowel syndrome (IBS), including IBS with diarrhea (IBS-D), IBS with constipation (IBS-C), and unclassified IBS (IBS-U). Researchers used 16S sequencing data to compare taxonomic and functional profiles of gut bacteria between these IBS subtypes and matched non-IBS controls. They also examined how clinical characteristics, dietary factors, and depression status related to microbial composition within IBS.
The study drew on deeply phenotyped individuals enrolled in the American Gut Project, a large public microbiome dataset with associated clinical and dietary information. A total of 942 subjects with IBS (spanning IBS-D, IBS-C, and IBS-U) were included and matched by age, gender, body mass index, geography, and dietary patterns with 942 non-IBS controls. This design allowed comparison of microbiome features across IBS subtypes while controlling for major demographic and lifestyle confounders.
Subjects with IBS-D or IBS-U, but not IBS-C, showed significantly reduced bacterial diversity compared to controls. Each IBS subtype was associated with a distinct bacterial signature and corresponding functional shifts tied to disease pathogenesis. Notably, IBS-D was linked to an increased hydrogen sulfide production pathway, while IBS-C was linked to increased palmitoleate biosynthesis. Among IBS subjects, those with depression showed lower Bifidobacterium, Sutterella, and Butyricimonas and higher Proteus than those without depression, and short-chain fatty acid production pathways were reduced in affected patients.
These findings support treating IBS as a heterogeneous condition with subtype-specific microbial and metabolic signatures rather than a single uniform disorder. The elevated hydrogen sulfide production pathway identified in IBS-D points to sulfur metabolism, potentially involving sulfate-reducing bacterial activity, as a mechanistic feature worth further investigation in diarrhea-predominant disease. The link between depression and specific bacterial taxa also suggests that mental health status should be considered when characterizing IBS microbiome profiles. Together, these results could inform more precise, subtype-tailored approaches to diagnosing and managing IBS.
This study examined whether gut microbiome composition differs in people with nontreated plaque psoriasis compared with people without the condition. The researchers used metagenomic gene sequencing of fecal samples to compare microbial taxa and functional gene pathways across groups. They also compared psoriasis patients directly against their own healthy spouses, a design meant to control for shared household and dietary exposures. Gene functional analysis was performed to see whether specific microbial pathways were altered alongside compositional shifts.
The study included 32 nontreated plaque psoriasis patients, 15 unrelated healthy controls, and 17 healthy spouses of the patients (healthy couples). Fecal samples from these three cohorts were analyzed by metagenomic sequencing. The abstract does not specify age, sex distribution, or geographic origin of participants.
The relative abundance of intestinal microbiota in the psoriasis group differed from both healthy controls and the patients' own healthy partners, though overall microbial diversity was similar across all three groups. At the phylum level, the relative abundances of Firmicutes and Bacteroidetes were reversed in psoriasis patients, and Escherichia coli was significantly enriched compared with both comparison groups. Functional gene analysis showed ribosome pathway genes upregulated, while flagellar assembly and bacterial chemotaxis pathways were downregulated in the psoriasis cohort. Additionally, microbiota composition differed between patients with severe psoriasis and those with milder disease, suggesting a relationship between gut dysbiosis and disease severity.
These findings strengthen the case for a link between intestinal flora and psoriasis, including a possible relationship between microbial dysbiosis and disease severity. Using patients' own healthy spouses as a comparison group helps address some of the conflicting results in prior psoriasis microbiome research. The authors note that further, more meaningful experiments are needed to clarify the mechanisms underlying this association.
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.
The gut microbiome is involved in autoimmunity. Data on its composition in chronic inflammatory demyelinating polyneuropathy (CIDP), the most common chronic autoimmune disorder of peripheral nerves, are currently lacking.
In this monocentric exploratory pilot study, stool samples were prospectively collected from 16 CIDP patients (mean age 58 ± 10 years, 25% female) before and 1 week after administration of intravenous immunoglobulin (IVIg). Gut microbiota were analyzed via bacterial 16S rRNA gene sequencing and compared to 15 age-matched healthy subjects (mean age 59 ± 15 years, 66% female).
The gut microbiota of CIDP patients showed an increased alpha-diversity (p = 0.005) and enrichment of Firmicutes, such as Blautia (p = 0.0004), Eubacterium hallii (p = 0.0004), or Ruminococcus torques (p = 0.03), and of Actinobacteriota (p = 0.03) compared to healthy subjects. IVIg administration did not alter the gut microbiome composition in CIDP in this short-term observation (p = 0.95).
The gut microbiome in IVIg-treated CIDP shows distinct features, with increased bacterial diversity and enrichment of short-chain fatty acid producing Firmicutes. IVIg had no short-term impact on the gut microbiome in CIDP patients. As the main limitation of this exploratory pilot study was small cohort size, future studies also including therapy-naïve patients are warranted to verify our findings and to explore the impact of long-term IVIg treatment on the gut microbiome in CIDP.
Colorectal polyps are common precursors of colorectal cancer (CRC) and are influenced by various lifestyle and environmental factors. Increasing evidence highlights the role of gut microbiota in the development of intestinal diseases, including CRC. Previous studies have reported differences between mucosal and faecal microbiota, with certain taxa such as Fusobacterium and Bacteroides fragilis being implicated in disease progression. However, microbiota signatures across different sampling sites in individuals with colorectal polyps remain unclear. This study aimed to characterize and compare the gut microbiota in faecal samples, normal colorectal mucosa, and polyp tissues from patients with colorectal polyps, as well as in healthy individuals. Using 16S rRNA gene sequencing and bioinformatic analysis, the study evaluates differences in microbial composition across these sites. The findings are expected to provide insight into site-specific microbiota variations and contribute to understanding microbial changes involved in the progression from colorectal polyps to colorectal cancer.
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.
The investigations related to how gut microbiota changes the brain-gut axis in idiopathic Parkinson's disease (PD) attract growing interest. We aimed to determine whether gut microbiota is altered in PD patients and whether non-motor symptoms of PD and disease duration had any relation with alterations of microbiota profiles among patients.
Microbial taxa in stool samples obtained from 84 subjects (42-PD patients and 42-healthy spouses) were analyzed using 16S rRNA amplicon-sequencing.
We observed a significant decrease of Firmicutes and a significant increase of Verrucomicrobiota at the phylum level. At the family level, Lactobacillaceae and Akkermansiaceae were significantly increased and Coriobacteriales Incertae Sedis were significantly decreased in the PD patients compared to their healthy spouses. Genus level comparison inferred significant increase in abundance only in Lactobacillus while the abundance of Lachnospiraceae ND3007 group, Tyzzerella, Fusicatenibacter, Eubacterium hallii group and Ruminococcus gauvreauii group were all decreased. We determined that the abundance of Prevotella genus decreased, but not significantly in PD patients. In addition, we found differences in microbiota composition between patients with and without non-motor symptoms.
We observed differences in gut microbiota composition between PD patients and their healthy spouses. Our findings suggest that disease duration influenced microbiota composition, which in turn influenced development of non-motor symptoms in PD. This study is the first in terms of both gut microbiota research in Turkish PD patients and the probable effect of microbiota on non-motor symptoms of PD.
Non-alcoholic fatty liver disease (NAFLD) is the most common cause of liver disease. Increasing evidence indicates that the gut microbiota can play an important role in the pathophysiology of NAFLD. Recently, several studies have tested the predictive value of gut microbiome profiles in NAFLD progression; however, comparisons of microbial signatures in NAFLD or non-alcoholic steatohepatitis (NASH) have produced discrepant results, possibly due to ethnic and environmental factors. Thus, we aimed to characterize the gut metagenome composition of patients with fatty liver disease.
Gut microbiome of 45 well-characterized patients with obesity and biopsy-proven NAFLD was evaluated using shot-gun sequencing: 11 non-alcoholic fatty liver controls (non-NAFL), 11 with fatty liver, and 23 with NASH.
Our study showed that Parabacteroides distasonis and Alistipes putredenis were enriched in fatty liver but not in NASH patients. Notably, in a hierarchical clustering analysis, microbial profiles were differentially distributed among groups, and membership to a Prevotella copri dominant cluster was associated with a greater risk of developing NASH. Functional analyses showed that although no differences in LPS biosynthesis pathways were observed, Prevotella-dominant subjects had higher circulating levels of LPS and a lower abundance of pathways encoding butyrate production.
Our findings suggest that a Prevotella copri dominant bacterial community is associated with a greater risk for NAFLD disease progression, probably linked to higher intestinal permeability and lower capacity for butyrate production.
Age-related macular degeneration (AMD) is the leading cause of vision loss in those over the age of 50. Recently, intestinal microbiota has been reported to be involved in the pathogenesis of ocular diseases. The purpose of this study was to discover more about the involvement of the intestinal microbiota in AMD patients.
Fecal samples from 30 patients with AMD (AMD group) and 17 age- and sex-matched healthy controls (control group) without any fundus disease were collected. DNA extraction, PCR amplification, and 16S rRNA gene sequencing of the samples were performed to identify intestinal microbial alterations. Further, we used BugBase for phenotypic prediction and PICRUSt2 for KEGG Orthology (KO) as well as metabolic feature prediction.
The intestinal microbiota was found to be significantly altered in the AMD group. The AMD group had a significantly lower level of Firmicutes and relatively higher levels of Proteobacteria and Bacteroidota compared to those in the control group. At the genus level, the AMD patient group showed a considerably higher proportion of Escherichia-Shigella and lower proportions of Blautia and Anaerostipes compared with those in the control group. Phenotypic prediction revealed obvious differences in the four phenotypes between the two groups. PICRUSt2 analysis revealed KOs and pathways associated with altered intestinal microbiota. The abundance of the top eight KOs in the AMD group was higher than that in the control group. These KOs were mainly involved in lipopolysaccharide biosynthesis.
The findings of this study indicated that AMD patients had different gut microbiota compared with healthy controls, and that AMD pathophysiology might be linked to changes in gut-related metabolic pathways. Therefore, intestinal microbiota might serve as non-invasive indicators for AMD clinical diagnosis and possibly also as AMD treatment targets.
This study investigated the role of gut microbiota and their metabolites, particularly short-chain fatty acids (SCFAs), in the pathogenesis of functional constipation (FC). The researchers used shotgun metagenomic sequencing of gut microbiota alongside serum SCFA analysis to examine relationships between microbial composition, butyric acid levels, and defecation frequency. They then tested the direct effects of butyrate on intestinal neurons using an in vitro mouse model to explore a possible mechanistic link between microbial butyrate metabolism and enteric nervous system damage.
The primary cohort consisted of 460 Chinese women with differing defecation frequencies, who underwent shotgun metagenomic sequencing and serum SCFA measurement. Findings were verified in an independent cohort of 6 patients with functional constipation and 6 controls. In addition, mouse intestinal neurons were used in vitro to test the cellular effects of butyrate exposure at concentrations of 0.1, 0.5, 1, and 2.5 mM.
The abundance of Fusobacterium varium, a butyric acid-producing bacterium, was positively correlated with defecation frequency, while serum butyric acid concentration was negatively correlated with defecation frequency. These findings were confirmed in the independent validation cohort. In vitro, intestinal neurons treated with 0.5 mM butyrate proliferated better than neurons exposed to other tested concentrations, with significant differences observed in cell cycle and oxidative phosphorylation signaling pathways.
The findings suggest that abnormal butyrate metabolism, including altered production by gut bacteria such as Fusobacterium varium and shifts in serum butyrate levels, may damage the enteric nervous system and contribute to functional constipation. This points to butyrate-modulating microbes and serum butyrate concentration as potential biomarkers or targets for understanding and managing FC. It also highlights that butyrate's effect on enteric neurons is concentration-dependent, meaning both insufficient and excessive levels may be relevant to disease mechanisms.
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.
Changes in diet and environment can lead to acute diarrhea in companion animals, but the composition and interactions of the gut microbiome during acute diarrhea remain unclear. In this multicenter case-control study, we investigated the relationship between intestinal flora and acute diarrhea in two breeds of cats. Acutely diarrheic American Shorthair (MD, n = 12) and British Shorthair (BD, n = 12) and healthy American Shorthair (MH, n = 12) and British Shorthair (BH, n = 12) cats were recruited. Gut microbial 16S rRNA sequencing, metagenomic sequencing, and untargeted metabolomic analysis were performed. We observed significant differences in beta-diversity (Adonis, P < 0.05) across breeds and disease state cohorts. Profound differences in gut microbial structure and function were found between the two cat breeds. In comparison to healthy British Shorthair cats, Prevotella, Providencia, and Sutterella were enriched while Blautia, Peptoclostridium, and Tyzzerella were reduced in American Shorthair cats. In the case-control cohort, cats with acute diarrhea exhibited an increased abundance of Bacteroidota, Prevotella, and Prevotella copri and a decreased abundance of Bacilli, Erysipelotrichales, and Erysipelatoclostridiaceae (both MD and BD cats, P < 0.05). Metabolomic analysis identified significant changes in the BD intestine, affecting 45 metabolic pathways. Moreover, using a random forest classifier, we successfully predicted the occurrence of acute diarrhea with an area under the curve of 0.95. Our findings indicate a distinct gut microbiome profile that is associated with the presence of acute diarrhea in cats. However, further investigations using larger cohorts of cats with diverse conditions are required to validate and extend these findings. IMPORTANCE Acute diarrhea is common in cats, and our understanding of the gut microbiome variations across breeds and disease states remains unclear. We investigated the gut microbiome of two cat breeds (British Shorthair and American Shorthair) with acute diarrhea. Our study revealed significant effects of breeds and disease states on the structure and function of the gut microbiota in cats. These findings emphasize the need to consider breed-related factors in animal nutrition and research models. Additionally, we observed an altered gut metabolome in cats with acute diarrhea, closely linked to changes in bacterial genera. We identified a panel of microbial biomarkers with high diagnostic accuracy for feline acute diarrhea. These findings provide novel insights into the diagnosis, classification, and treatment of feline gastrointestinal diseases.
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.
Allergic diseases affect millions of people worldwide. An increase in their prevalence has been associated with alterations in the gut microbiome, i.e., the microorganisms and their genes within the gastrointestinal tract. Maturation of the infant immune system and gut microbiota occur in parallel; thus, the conformation of the microbiome may determine if tolerant immune programming arises within the infant. Here we show, using deeply phenotyped participants in the CHILD birth cohort (n = 1115), that there are early-life influences and microbiome features which are uniformly associated with four distinct allergic diagnoses at 5 years: atopic dermatitis (AD, n = 367), asthma (As, n = 165), food allergy (FA, n = 136), and allergic rhinitis (AR, n = 187). In a subset with shotgun metagenomic and metabolomic profiling (n = 589), we discover that impaired 1-year microbiota maturation may be universal to pediatric allergies (AD p = 0.000014; As p = 0.0073; FA p = 0.00083; and AR p = 0.0021). Extending this, we find a core set of functional and metabolic imbalances characterized by compromised mucous integrity, elevated oxidative activity, decreased secondary fermentation, and elevated trace amines, to be a significant mediator between microbiota maturation at age 1 year and allergic diagnoses at age 5 years (βindirect = -2.28; p = 0.0020). Microbiota maturation thus provides a focal point to identify deviations from normative development to predict and prevent allergic disease.
Long-term effect of Direct-acting antivirals (DAAs) on gut microbiota, short-chain fatty acids (SCFAs) and microbial translocation in patients with hepatitis C virus (HCV) infection who achieve sustained virological response (SVR) were limited. A longitudinal study of 50 patients with HCV monoinfection and 19 patients with HCV/HIV coinfection received DAAs were conducted. Fecal specimens collected at baseline and at week 72 after treatment completion (FUw72) were analyzed for 16S rRNA sequencing and the butyryl-CoA:acetateCoA transferase (BCoAT) gene expression using real-time PCR. Plasma lipopolysaccharide binding protein (LBP) and intestinal fatty acid binding protein (I-FABP) were quantified by ELISA assays. SVR rates in mono- and coinfected patients were comparable (94% vs. 100%). The improvement of gut dysbiosis and microbial translocation was found in responders but was not in non-responders. Among responders, significant restoration of alpha-diversity, BCoAT and LBP were observed in HCV patients with low-grade fibrosis (F0-F1), while HCV/HIV patients exhibited partial improvement at FUw72. I-FABP did not decline significantly in responders. Treatment induced microbiota changes with increasing abundance of SCFAs-producing bacteria, including Blautia, Fusicatenibacter, Subdoligranulum and Bifidobacterium. In conclusion, long-term effect of DAAs impacted the restoration of gut dysbiosis and microbial translocation. However, early initiation of DAAs required for an alteration of gut microbiota, enhanced SCFAs-producing bacteria, and could reduce HCV-related complications.
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.
Coronary artery disease (CAD) is a widespread heart condition caused by atherosclerosis and influences millions of people worldwide. Early detection of CAD is challenging due to the lack of specific biomarkers. The gut microbiota and host-microbiota interactions have been well documented to affect human health. However, investigation that reveals the role of gut microbes in CAD is still limited. This study aims to uncover the synergistic effects of host genes and gut microbes associated with CAD through integrative genomic analyses.
Herein, we collected 52 fecal and 50 blood samples from CAD patients and matched controls, and performed amplicon and transcriptomic sequencing on these samples, respectively. By comparing CAD patients with health controls, we found that dysregulated gut microbes were significantly associated with CAD. By leveraging the Random Forest method, we found that combining 20 bacteria and 30 gene biomarkers could distinguish CAD patients from health controls with a high performance (AUC = 0.92). We observed that there existed prominent associations of gut microbes with several clinical indices relevant to heart functions. Integration analysis revealed that CAD-relevant gut microbe genus Fusicatenibacter was associated with expression of CAD-risk genes, such as GBP2, MLKL, and CPR65, which is in line with previous evidence (Tang et al., Nat Rev Cardiol 16:137-154, 2019; Kummen et al., J Am Coll Cardiol 71:1184-1186, 2018). In addition, the upregulation of immune-related pathways in CAD patients were identified to be primarily associated with higher abundance of genus Blautia, Eubacterium, Fusicatenibacter, and Monoglobus.
Our results highlight that dysregulated gut microbes contribute risk to CAD by interacting with host genes. These identified microbes and interacted risk genes may have high potentials as biomarkers for CAD.
The most common toxic side effect after chemotherapy, one of the main treatments for colorectal cancer (CRC), is myelosuppression. To analyze the correlation between gut microbiota and leukopenia after chemotherapy in CRC patients.
Stool samples were collected from 56 healthy individuals and 55 CRC patients. According to the leukocytes levels in peripheral blood, the CRC patients were divided into hypoleukocytes group (n = 13) and normal leukocytes group (n = 42). Shannon index, Simpson index, Ace index, Chao index and Coverage index were used to analyze the diversity of gut microbiota. LDA and Student's t-test(St test) were used for analysis of differences. Six machine learning algorithms, including logistic regression (LR) algorithm, random forest (RF) algorithm, neural network (NN) algorithm, support vector machine (SVM) algorithm, catboost algorithm and gradient boosting tree algorithm, were used to construct the prediction model of gut microbiota with leukopenia after chemotherapy for CRC.
Compared with healthy group, the microbiota alpha diversity of CRC patients was significantly decreased (p < 0.05). After analyzing the gut microbiota differences of the two groups, 15 differential bacteria, such as Bacteroides, Faecalibacterium and Streptococcus, were screened. RF prediction model had the highest accuracy, and the gut microbiota with the highest predictive value were Peptostreptococcus, Faecalibacterium, and norank_f__Ruminococcaceae, respectively. Compared with normal leukocytes group, the microbiota alpha diversity of hypoleukocytes group was significantly decreased (p < 0.05). The proportion of Escherichia-Shigella was significantly decreased in the hypoleukocytes group. After analyzing the gut microbiota differences of the two groups, 9 differential bacteria, such as Escherichia-Shigella, Fusicatenibacter and Cetobacterium, were screened. RF prediction model had the highest accuracy, and the gut microbiota with the highest predictive value were Fusicatenibacte, Cetobacterium, and Paraeggerthella.
Gut microbiota is related to leukopenia after chemotherapy. The gut microbiota may provide a novel method for predicting myelosuppression after chemotherapy in CRC patients.
Recent studies reveal that imbalanced microbiota is related to thyroid diseases. However, studies on the alterations in fecal metabolites in Graves' disease and clinical hypothyroidism patients are insufficient. Here, we identified 21 genera and 53 metabolites that were statistically significant among Graves' disease patients, hypothyroidism patients, and controls integrating microbiome and untargeted metabolome analysis. Disease groups revealed a decreased abundance in butyrate-producing microbiota and an increased abundance in potentially pathogenic microbiota. Lipids molecules were the major differential metabolites identified in all fecal samples. Network analysis recognized that microbiota may affect thyroid function by targeting specific metabolites. We further identified specific microbiota and metabolites that could distinguish Graves' disease patients, hypothyroidism patients, and controls. Our study reveals a distinct microbial and metabolic signature in hypothyroidism patients and Graves' disease patients and further validates the potential role of microbiota in thyroid diseases, providing new ideas for future research into the etiology and clinical intervention of thyroid diseases.
This study examined whether gut microbiota composition influences the return of estrus in post-weaning sows by regulating the metabolism of sex steroid hormones. The researchers used 16S rRNA gene sequencing, metagenomic sequencing, and fecal metabolome analysis to link microbial community changes to hormone-related outcomes. They specifically looked at how shifts in gut bacterial species affect the functional capacity for steroid hormone biosynthesis within the gut microbiome.
The study analyzed 207 fecal samples from well-phenotyped sows using 16S rRNA gene sequencing to find associations between gut microbes and estrus return. A subset of 85 fecal samples underwent metagenomic sequencing to identify specific bacterial species tied to estrus return status. The findings were then confirmed in a separate validation cohort of sows.
Metagenomic analysis identified 37 bacterial species significantly associated with estrus return after weaning. Sows that returned to normal estrus had increased abundances of L. reuteri and P. copri, and decreased abundances of B. fragilis, S. suis, and B. pseudolongum, compared to non-returning sows. These microbial shifts significantly altered the gut microbiome's functional capacity for steroid hormone biosynthesis, and metabolome analysis found significant differences in sex steroid hormones and related compounds between normal and non-return sows.
By integrating differential bacterial species, metagenomic function, and fecal metabolome data, the study provides evidence that gut microbiota, including reduced B. fragilis abundance, is linked to normal post-weaning estrus return through effects on sex steroid hormone metabolism. This suggests that specific gut bacteria could serve as biomarkers or targets for improving reproductive efficiency in sows. The findings point toward potential microbiome-based strategies to address delayed or absent estrus return, a costly problem in swine production.
This study investigated the gut microbiome and fecal metabolite profile in functional constipation (FC), a condition whose underlying mechanisms remain unclear. The researchers combined 16S rDNA sequencing with non-targeted metabolomic detection using liquid chromatography-mass spectrometry (LC-MS/MS) to characterize fecal samples. The goal was to identify how gut microbiota and metabolites are altered in FC and how the two are interrelated, since this relationship had received limited attention in prior literature.
The study compared fecal samples from patients with functional constipation to samples from healthy individuals, referred to as the healthy control (HC) group. The abstract does not specify exact participant numbers, age range, or geographic setting. The comparison design indicates a case-control human cohort study rather than an animal or purely computational dataset.
Gut microbiota richness and diversity were significantly increased in FC patients compared to healthy controls (p < 0.01). Eighteen bacterial genera showed statistically significant changes between groups, including Intestinibacter, Klebsiella, and Akkermansia (p < 0.05). Metabolomic analysis revealed 79 differentially abundant metabolites, such as (-)-caryophyllene oxide, chenodeoxycholic acid, and biliverdin, with primary bile acid biosynthesis and porphyrin and chlorophyll metabolism emerging as the most significantly enriched pathways (FDR < 0.01).
The findings suggest that functional constipation involves coordinated shifts in both gut microbial composition and metabolic output, particularly involving bile acid metabolism. Because chenodeoxycholic acid and related bile acids are implicated, altered microbial processing of bile acids may contribute to disrupted bowel function in FC. Mapping these microbiome-metabolite relationships could help identify biomarkers or microbiome-targeted strategies for diagnosing or managing functional constipation.
We collected clinical data and stool samples from participants. Bacterial 16S rRNA genes were amplified, sequenced, and clustered into operational taxonomic unit. Alpha diversity was studied by Shannon and Simpson indexes. To study how different the gut microbiota composition is between the different groups, beta diversity estimation was evaluated by principal coordinate analysis (PCoA) using Bray-Curtis dissimilarity. To further analyze differences in microbiome composition we performed a linear discriminant analysis (LDA) effect size (LEfSe).
We included 30 HIV+MASLD+, 30 HIV+MASLD- and 20 HIV-MASLD+ participants. Major butyrate producers, including Faecalibacterium, Ruminococcus, and Lachnospira dominated the microbiota in all three groups. Shannon's and Simpson's diversity metrics were higher among MASLD+ individuals (Kruskal-Wallis p = 0.047). Beta diversity analysis showed distinct clustering in MASLD-, with MASLD+ participants overlapping regardless of HIV status (ADONIS significance <0.001). MASLD was associated with increased homogeneity across individuals, in contrast to that observed in the HIV+NAFDL- group, in which the dispersion was higher (Permanova test, p value <0.001; ANOSIM, p value <0.001). MASLD but not HIV determined a different microbiota structure (HIV+MASLD- vs. HIV+MASLD+, q-value = 0.002; HIV-MASLD+ vs. HIV+MASLD+, q-value = 0.930; and HIV-MASLD+ vs. HIV+MASLD-, q-value < 0.001). The most abundant genera in MASLD- were Prevotella, Bacteroides, Dialister, Acidaminococcos, Alloprevotella, and Catenibacterium. In contrast, the most enriched genera in MASLD+ were Ruminococcus, Streptococcus, Holdemanella, Blautia, and Lactobacillus.
We found a microbiome signature linked to MASLD, which had a greater influence on the overall structure of the gut microbiota than HIV status alone.
This prospective, observational study examined whether gut microbiota composition is associated with immune responses and adverse events following COVID-19 vaccination. Researchers compared two vaccine types: the inactivated CoronaVac vaccine and the mRNA BNT162b2 vaccine. They performed shotgun metagenomic sequencing on stool samples collected at baseline and again one month after the second vaccine dose. Immune responses were assessed using a SARS-CoV-2 surrogate virus neutralisation test and a spike receptor-binding domain IgG ELISA.
The study included 138 adult COVID-19 vaccine recipients, of whom 37 received CoronaVac and 101 received BNT162b2. Stool samples from these vaccinees were collected at two time points, baseline and one month post second dose, for shotgun metagenomic analysis. The abstract does not specify additional demographic details such as age range, sex distribution, or geographic location.
Immune responses were significantly lower in CoronaVac recipients than in BNT162b2 recipients. Among CoronaVac vaccinees, higher persistent levels of Bifidobacterium adolescentis were associated with higher neutralising antibody responses, and their baseline gut microbiome was enriched in carbohydrate metabolism pathways. In BNT162b2 vaccinees, neutralising antibody levels correlated positively with the total abundance of flagellated and fimbriated bacteria, including Roseburia faecis. Prevotella copri and two Megamonas species were enriched in individuals who experienced fewer adverse events after vaccination.
These findings suggest that baseline gut microbiota composition and function may help explain individual variation in vaccine immunogenicity and tolerability. Specific taxa, such as Bifidobacterium adolescentis, Roseburia faecis, Prevotella copri, and Megamonas species, and microbial functional features like carbohydrate metabolism pathways and flagellar or fimbrial machinery, appear linked to stronger antibody responses or fewer adverse events. This raises the possibility that gut microbiome profiling or modulation could eventually inform strategies to improve vaccine efficacy or reduce adverse events. Further research is needed to determine whether these associations are causal and generalizable across vaccine platforms and populations.
This study examined whether fecal microbiota composition and fecal amino acid levels change in the presence of colonic adenomas and after those adenomas are removed. Researchers longitudinally tracked stool samples collected before colonoscopy and again three months after polypectomy. The goal was to determine whether microbial and amino acid signals could help detect adenomas and monitor patients after endoscopic removal, given that surveillance colonoscopy has low yield and interval colorectal cancers still occur.
The study included patients with advanced adenomas and nonadvanced adenomas (0.5 to 1.0 cm) who underwent polypectomy during colonoscopy, totaling 19 patients. These patients were strictly matched on age, body-mass index, and smoking habits to 19 control participants who had no endoscopic abnormalities. Fecal samples were collected from both groups before bowel preparation, and microbial taxa were profiled by 16S rRNA sequencing while amino acids were measured by high-performance liquid chromatography.
Adenoma patients could be distinguished from controls based on both their amino acid profiles and their microbial composition. Levels of proline, ornithine, and serine were significantly increased in adenoma patients compared to controls, and these three amino acids together formed a candidate adenoma-specific panel with an AUC of 0.79. After endoscopic removal of the adenomas, levels of these amino acids decreased and came to resemble those seen in controls, suggesting the changes were tied to the presence of the lesion itself rather than fixed host traits. The abstract does not mention Desulfovibrio, sulfate-reducing bacteria, or sulfur metabolism among the described findings.
These findings suggest that fecal amino acid panels, potentially combined with microbial composition data, could serve as a noninvasive tool to help detect adenomas and monitor patients after polypectomy. Because these markers normalized after adenoma removal, they may also help confirm successful resection or flag patients who need closer follow-up. This approach could complement or improve upon current endoscopic surveillance strategies, which have low yield despite the continued occurrence of interval colorectal cancers.
Dysbiosis of human gut microbiota has been reported in association with ulcerative colitis (UC) in both children and adults using either 16S rRNA gene or shotgun sequencing data. However, these studies used either 16S rRNA or metagenomic shotgun sequencing but not both. We sequenced feces samples from 19 pediatric UC and 23 healthy children ages between 7 to 21 years using both 16S rRNA and metagenomic shotgun sequencing. The samples were analyzed using three different types of data: 16S rRNA genus level abundance, microbial species and pathway abundance profiles. We demonstrated that (a) the alpha diversity of pediatric UC cases is lower than that of healthy controls; (b) the beta diversity within children with UC is more variable than within the healthy children; (c) several microbial families including Akkermansiaceae, Clostridiaceae, Eggerthellaceae, Lachnospiraceae, and Oscillospiraceae, contain species that are depleted in pediatric UC compared to controls; (d) a few associated species unique to pediatric UC, but not adult UC, were also identified, e.g. some species in the Christensenellaceae family were found to be depleted and some species in the Enterobacteriaceae family were found to be enriched in pediatric UC; and (e) both 16S rRNA and shotgun sequencing data can predict pediatric UC status with area under the receiver operating characteristic curve (AUROC) of close to 0.90 based on cross validation. We showed that 16S rRNA data yielded similar results as shotgun data in terms of alpha diversity, beta diversity, and prediction accuracy. Our study demonstrated that pediatric UC subjects harbor a dysbiotic and less diverse gut microbial population with distinct differences from healthy children. We also showed that 16S rRNA data yielded accurate disease prediction results in comparison to shotgun data, which can be more expensive and laborious. These conclusions were confirmed in an independent data set of 7 pediatric UC cases and 8 controls.
Studies of both, microbiota and target therapy associated with gene mutations in colorectal cancer, (CRC) have attracted increasing attention. However, only a few of them analyzed the combined effects on CRC. we analyzed differences in intestinal microbiota of 44 colorectal cancer patients and 20 healthy controls (HC) using 16S rRNA gene sequencing of fecal samples. For 39 of the CRC patients, targeted Next Generation Sequencing (NGS) was carried out at formalin fixed paraffin embedded (FFPE) samples to identify somatic mutation profiles. Compared to the HC group, the microbial diversity of CRC patients was significantly lower. In the CRC group, we found a microbiome that was significantly enriched for strains of Bifidobacterium, Bacteroides, and Megasphaera whereas in the HC group the abundance of Collinsella, Faecalibacterium, and Agathobacter strains was higher. Among the mutations detected in the CRC group, the APC gene had the highest mutation rate (77%, 30/39). We found that the KRAS mutant type was closely associated with Faecalibacterium, Roseburia, Megamonas, Lachnoclostridium, and Harryflintia. Notably, Spearman correlation analysis showed that KRAS mutations were negatively correlated with the existence of Bifidobacterium and positively correlated with Faecalibacterium. By employing 16S rRNA gene sequencing, we identified more unique features of microbiota profiles in CRC patients. For the first time, our study showed that gene mutations could directly be linked to the microbiota composition of CRC patients. We hypothesize that the effect of a targeted colorectal cancer therapy is also closely related to the colorectal flora, however, this requires further investigation.
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 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 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.
The incidence of gestational diabetes mellitus (GDM) is increasing worldwide, and has been associated with some changes in the gut microbiota. Studies have shown that the maternal gut microbiota pattern with hyperglycemia can be transmitted to the offspring. The study aimed to evaluate the gut microbiota of obese postpartum women with and without previous GDM and their offspring.
We evaluated a total of 84 puerperal women who had (n = 40) or not GDM (n = 44), and their infants were also included. Stool samples were obtained 2-6 months after delivery. The molecular profile of the fecal microbiota was obtained by sequencing V4 region of 16S rRNA gene (Illumina® MiSeq).
We found that the gut microbiota structures of the puerperal women and their infants were similar. Stratifying according to the type of delivery, the relative abundance of Victivallis genus was higher in women who had natural delivery. Exposure to exclusive breastfeeding was associated with a greater abundance of Bacteroides and Staphylococcus. The differential abundance test showed correlations to clinical and laboratory parameters. This work showed no difference in the microbiota of obese puerperal women with and without GDM and their offspring. However, breastfeeding contributed to the ecological succession of the intestinal microbiota of the offspring.
This work can contribute to understanding the potential effects of GDM and early life events on the gut microbiome of mothers and their offspring and its possible role in metabolism later in life.
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.
Background: Gut microbiota are considered to be intrinsic regulators of thyroid autoimmunity. We designed a cross-sectional study to examine the makeup and metabolic function of microbiota in Graves' disease (GD) patients, with the ultimate aim of offering new perspectives on the diagnosis and treatment of GD. Methods: The 16S ribosomal RNA (rRNA) V3-V4 DNA regions of microbiota were obtained from fecal samples collected from 45 GD patients and 59 controls. Microbial differences between the two groups were subsequently analyzed based on high-throughput sequencing. Results: Compared with controls, GD patients had reduced alpha diversity (p < 0.05). At the phylum level, GD patients had a significantly lower proportion of Firmicutes (p = 0.008) and a significantly higher proportion of Bacteroidetes (p = 0.002) compared with the controls. At the genus level, GD patients had greater numbers of Bacteroides and Lactobacillus, although fewer Blautia, [Eubacterium]_hallii_group, Anaerostipes, Collinsella, Dorea, unclassified_f_Peptostreptococcaceae, and [Ruminococcus]_torques_group than controls (all p < 0.05). Subgroup analysis of GD patients revealed that Lactobacillus may play a key role in the pathogenesis of autoimmune thyroid diseases. Nine distinct genera showed significant correlations with certain thyroid function tests. Functional prediction revealed that Blautia may be an important microbe in certain metabolic pathways that occur in the hyperthyroid state. In addition, linear discriminant analysis (LDA) and effect size (LEfSe) analysis showed that there were significant differences in the levels of 18 genera between GD patients and controls (LDA >3.0, all p < 0.05). A diagnostic model using the top nine genera had an area under the curve of 0.8109 [confidence interval: 0.7274-0.8945]. Conclusions: Intestinal microbiota are different in GD patients. The microbiota we identified offer an alternative noninvasive diagnostic methodology for GD. Microbiota may also play a role in thyroid autoimmunity, and future research is needed to further elucidate the role.
Although gut microbiota dysbiosis has been reported in HIV infected individuals recently, the relationship between the gut microbiota and immune activation in patients with different immune responses to highly active antiretroviral therapy (HAART) is still not well understood. Gut microbiota and immune activation were studied in 36 non-HIV-infected subjects (healthy controls) and 58 HIV-infected individuals, including 28 immunological responders (IR) and 30 immunological non-responders (INR) (≥500 and < 200 CD4+ T-cell counts/μl after 2 years of HIV-1 viral suppression respectively) without comorbidities.
Metagenome sequencing revealed that HIV-infected immunological responders and immunological non-responders could not recover completely from the gut microbiota dysbiosis. At a 97% similarity level, the relative abundances of Fusobacterium, Ruminococcus gnavus and Megamonas were greater, whereas Faecalibacterium, Alistipes, Bifidobacterium, Eubacterium rectale and Roseburia were more depleted in the IR and INR groups than those in the healthy controls. Ruminococcaceae and Alistipes were positively correlated with nadir and current CD4+ T-cell counts, but negatively correlated with CD8 + CD57+ T-cell counts. Inflammation markers and translocation biomarkers (LPS) levels were positively correlated with the abundances of genera Ruminococcus and Fusobacterium but were negatively correlated with the genus Faecalibacterium. The relative abundances of Escherichia-Shigella and Blautia were significantly higher in the IR than those in the INR group. Escherichia-Shigella were negatively correlated with the CD4/CD8 ratio but positively correlated with the amount of CD8 + CD57+ T-cells. Roseburia and Blautia were negatively associated with nadir CD4+ T-cell and positively associated with CD8 + CD57+ T-cell counts.
Gut microbiota dysbiosis may be one of the factors contributing to different immune responses and treatment outcomes to HAART.
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 the environmental drivers of gut microbiome composition and function in wild Ethiopian geladas. Researchers focused on how food availability, tracked using rainfall, and thermoregulatory stress, tracked using temperature, predicted shifts in gut microbial diversity. Geladas were chosen because they live in a cold, high-altitude environment and eat a low-quality, grass-based diet, creating both energetic and thermoregulatory pressures. The study looked beyond diet alone to ask whether other environmental factors also shape the gut microbiome in a natural setting.
The subjects were wild Ethiopian geladas (Theropithecus gelada), a nonhuman primate species living at high altitude in a cold climate. The dataset comprised 758 gut microbiome samples collected from these wild animals, making it the largest wild nonhuman primate gut microbiome dataset generated to date. The abstract does not specify the number of individual animals sampled or their sex or age distribution.
Gut microbiome composition in geladas covaried with both rainfall and temperature, but in patterns suggesting distinct responses to dietary versus thermoregulatory challenges. Seasonal microbial shifts tracked changes in the dominant components of the diet. During rainier periods, the gut was dominated by cellulolytic and fermentative bacteria specialized in digesting grass, while dry-period communities differed accordingly. This indicates that the gelada gut microbiome adjusts compositionally in step with seasonal food quality and availability.
The findings suggest that gut microbiome plasticity helps wild primates cope with seasonal swings in diet quality and possibly with thermoregulatory demands, not diet changes alone. By generating the largest wild nonhuman primate gut microbiome dataset to date, this work provides a foundation for studying how environmental variables beyond diet shape host-microbe relationships in natural settings. It also underscores the value of long-term, in-situ sampling for understanding adaptive microbiome responses to seasonal environmental stress.
This study examined the gut microbiota of patients with COVID-19 pneumonia using 16S rRNA gene sequencing performed on rectal swabs. Researchers compared microbial composition and diversity between patients treated in the intensive care unit (i-COVID19), patients treated in infectious disease wards (w-COVID19), and healthy controls (CTRL). The goal was to characterize how gut microbial communities differ across varying levels of COVID-19 disease severity.
The study population consisted of patients hospitalized with COVID-19 pneumonia, divided into two groups by care setting: those admitted to the intensive care unit and those managed in infectious disease wards. These two patient groups were compared against a control group without COVID-19. The abstract does not report exact sample sizes, ages, or other demographic details for these cohorts.
Patients in the ICU showed a decrease in the Chao1 index compared to both controls and ward patients, indicating lower microbial richness in the most severely ill patients, while the Shannon index showed no significant change. At the phylum level, ward patients showed an increase in Proteobacteria compared to controls. Fusobacteria and Spirochetes were both decreased relative to controls, with Spirochetes showing the greatest decrease in ICU patients specifically.
The findings indicate that gut microbial communities shift in composition and richness according to COVID-19 disease severity, with the most pronounced changes occurring in critically ill ICU patients. These preliminary results suggest the gut microbiota may hold promising biomarkers for diagnosing COVID-19 and gauging disease severity. The authors note that validation in larger cohorts could support using microbiota profiles to help stratify patients by severity.
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.
Endometriosis (EM) in reproductive females has an incidence of 6-10% and greatly affects female fertility, quality of life, and long-term health. The gut microbiota can affect the physiological and pathological processes of humans through various pathways, such as those involving the nervous and endocrine systems and immunity, and it plays important roles in endocrine and inflammatory diseases. Whether the gut microbiota plays a role in EM has gradually attracted researchers' attention. In the present study, fecal and blood samples were collected from 12 patients with stage 3/4 EM and 12 healthy controls. We performed 16S rRNA high-throughput sequencing to compare the gut microbiota between the EM and control groups. Serum levels of hormones and inflammatory cytokines were measured. We found that compared with the control group, the EM group had a lower α diversity of gut microbiota and a higher Firmicutes/Bacteroidetes ratio. The abundances of various taxa (such as Actinobacteria, Tenericutes, Blautia, Bifidobacterium, Dorea, and Streptococcus) were significantly different between the two groups. The taxon with the highest abundance in the EM group was Prevotella_7, and that in the control group was Coprococcus_2. The serum levels of E2 and IL-8 were significantly higher in the EM group than in the control group (E2: EM group 74.7 ± 22.5 pg/L vs CON group 47.9 ± 12.5 pg/L; IL-8: EM group 6.39 ± 1.59 pg/mL vs CON group 4.14 ± 0.73 pg/mL). Additionally, the gut microbiota of the EM group was enriched for the microbial function categories environmental information processing, endocrine system, and immune system. Correlations were detected between each of Blautia and Dorea abundance and estradiol level and between Subdoligranulum abundance and IL-8 level. This study elucidated the associations between the gut microbiota and both serum hormones and inflammatory factors in EM. However, the findings need to be verified in future studies.
This study examined the fecal gut metagenomes of three common intestinal diseases: Crohn's disease, ulcerative colitis, and colorectal cancer. The researchers performed a meta-analysis across 13 separate fecal metagenome data sets spanning these three conditions. Their goal was to identify microbial species and metabolic pathways that change consistently across multiple data sets for each disease, and to compare these signatures across diseases. They also built multidisease diagnostic models based on the markers they identified.
The abstract does not describe a single new patient cohort but rather a meta-analysis pooling 13 existing fecal metagenome data sets covering Crohn's disease, ulcerative colitis, and colorectal cancer patients and controls. No specific sample sizes, ages, or geographic origins are given in the abstract. This can be honestly described as a secondary analysis of multiple public or previously published metagenomic cohorts rather than a single primary study population.
The analysis identified 87 marker species and 65 marker pathways that were consistently altered across multiple data sets of the same disease. These markers grouped into disease-specific and disease-common clusters with distinct phylogenetic relationships: species specific to Crohn's disease were phylogenetically closely related, while colorectal cancer-specific species were more phylogenetically distant from one another. Notably, ulcerative colitis-specific species were phylogenetically closer to colorectal cancer-associated species, consistent with the known elevated colorectal cancer risk in ulcerative colitis patients. Marker species within the same cluster shared metabolic preferences, and disease cases showed more tightly coordinated microbial changes than controls, suggesting a more stressed, selective gut environment in disease states, with a subset of markers also correlating with an indicator of gut barrier (leaky gut) dysfunction.
By mapping how disease-specific and disease-common microbial signatures relate phylogenetically and metabolically, this work supports the development of multidisease diagnostic models that could help distinguish between conditions with overlapping symptoms, such as Crohn's disease, ulcerative colitis, and colorectal cancer. The finding that ulcerative colitis markers resemble colorectal cancer markers phylogenetically offers a microbiome-based rationale for the elevated cancer risk seen in ulcerative colitis. The link between marker species and leaky gut indicators further ties gut dysbiosis to compromised intestinal barrier function. Overall, the study suggests cross-disease microbiome comparisons can sharpen diagnostic precision beyond single-disease marker panels.
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.
Parkinson's disease (PD) is a neurodegenerative disorder and 70-80% of PD patients suffer from gastrointestinal dysfunction such as constipation. We aimed to assess the efficacy and safety of fecal microbiota transplantation (FMT) for treating PD related to gastrointestinal dysfunction. We conducted a prospective, single- study. Eleven patients with PD received FMT. Fecal samples were collected before and after FMT and subjected to 16S ribosomal DNA (rDNA) gene sequencing. Hoehn-Yahr (H-Y) grade, Unified Parkinson's Disease Rating Scale (UPDRS) score, and the Non-Motion Symptom Questionnaire (NMSS) were used to assess improvements in motor and non-motor symptoms. PAC-QOL score and Wexner constipation score were used to assess the patient's constipation symptoms. All patients were tested by the small intestine breath hydrogen test, performed before and after FMT. Community richness (chao) and microbial structure in before-FMT PD patients were significantly different from the after-FMT. We observed an increased abundance of Blautia and Prevotella in PD patients after FMT, while the abundance of Bacteroidetes decreased dramatically. After FMT, the H-Y grade, UPDRS, and NMSS of PD patients decreased significantly. Through the lactulose H2 breath test, the intestinal bacterial overgrowth (SIBO) in PD patients returned to normal. The PAC-QOL score and Wexner constipation score in after-FMT patients decreased significantly. Our study profiles specific characteristics and microbial dysbiosis in the gut of PD patients. FMT might be a therapeutic potential for reconstructing the gut microbiota of PD patients and improving their motor and non-motor symptoms.
Coronavirus disease 2019 (COVID-19) has infected over 124 million people worldwide. In addition to the development of therapeutics and vaccines, the evaluation of the sequelae in recovered patients is also important. Recent studies have indicated that COVID-19 has the ability to infect intestinal tissues and to trigger alterations of the gut microbiota. However, whether these changes in gut microbiota persist into the recovery stage remains largely unknown. Here, we recruited seven healthy Chinese men and seven recovered COVID-19 male patients with an average of 3-months after discharge and analyzed their fecal samples by 16S rRNA sequencing analysis to identify the differences in gut microbiota. Our results suggested that the gut microbiota differed in male recovered patients compared with healthy controls, in which a significant difference in Chao index, Simpson index, and β-diversity was observed. And the relative abundance of several bacterial species differed clearly between two groups, characterized by enrichment of opportunistic pathogens and insufficiency of some anti-inflammatory bacteria in producing short chain fatty acids. The above findings provide preliminary clues supporting that the imbalanced gut microbiota may not be fully restored in recovered patients, highlighting the importance of continuous monitoring of gut health in people who have recovered from COVID-19.
Patients with COVID-19 have been reported to experience gastrointestinal symptoms as well as respiratory symptoms, but the effects of COVID-19 on the gut microbiota are poorly understood. We explored gut microbiome profiles associated with the respiratory infection of SARS-CoV-2 during the recovery phase in patients with asymptomatic or mild COVID-19. A longitudinal analysis was performed using the same patients to determine whether the gut microbiota changed after recovery from COVID-19. We applied 16S rRNA amplicon sequencing to analyze two paired fecal samples from 12 patients with asymptomatic or mild COVID-19. Fecal samples were selected at two time points: during SARS-CoV-2 infection (infected state) and after negative conversion of the viral RNA (recovered state). We also compared the microbiome data with those from 36 healthy controls. Microbial evenness of the recovered state was significantly increased compared with the infected state. SARS-CoV-2 infection induced the depletion of Bacteroidetes, while an abundance was observed with a tendency to rapidly reverse in the recovered state. The Firmicutes/Bacteroidetes ratio in the infected state was markedly higher than that in the recovered state. Gut dysbiosis was observed after infection even in patients with asymptomatic or mild COVID-19, while the composition of the gut microbiota was recovered after negative conversion of SARS-CoV-2 RNA. Modifying intestinal microbes in response to COVID-19 might be a useful therapeutic alternative.
This study assessed whether the gut microbiota composition differs between children with autism spectrum disorder (ASD) and healthy children. Researchers used high-throughput sequencing of the V3-V4 region of the 16S rRNA gene to characterize fecal bacterial communities. They evaluated alpha diversity using the Shannon, Chao, and ACE indexes, and beta diversity using unweighted UniFrac analysis and PCA plots. LDA and LEfSe were applied to identify bacterial taxa that differed in abundance between groups.
The study included 25 children diagnosed with ASD and 20 healthy children serving as controls. Autistic symptoms were diagnosed using the Diagnostic and Statistical Manual for Mental Disorders and assessed for severity with the Autism Treatment Evaluation Checklist (ATEC). Gastrointestinal symptoms in the ASD group were further evaluated with a GI Severity Index (GSI) questionnaire.
Children with higher GSI scores had markedly higher ATEC Total scores than those with lower GSI scores, indicating that gastrointestinal symptoms were strongly associated with the severity of autism symptoms. There was no significant difference in overall bacterial diversity, as measured by the Chao, ACE, and Shannon indexes, between children with ASD and healthy controls. Despite similar diversity levels, both groups showed differences in the composition of specific bacterial taxa, based on the abstract provided.
The findings suggest that gastrointestinal symptoms in children with ASD are closely tied to the severity of their behavioral symptoms, reinforcing the relevance of the gut-brain axis in autism. The lack of difference in overall diversity but presence of compositional shifts implies that specific taxonomic imbalances, rather than overall community richness, may be more informative for understanding ASD-related gut disruption. These results support further investigation into targeted microbiota-based markers or interventions tied to GI symptom severity in ASD.
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 study examined how fecal and oral sample collection methods, along with room temperature storage, affect measurements of the human microbiota. Researchers compared fecal preservation using RNAlater and fecal occult blood test (FOBT) cards over four days at room temperature. They also compared oral sampling using OMNIgene ORAL kits versus Scope mouthwash. Comparability and stability were assessed using interclass correlation coefficients (ICCs) across alpha and beta diversity metrics and phylum-level relative abundance.
Participants were drawn from two Iranian cohorts: a rural population in Yazd (n = 46) and an urban population in Gonbad (n = 38). Both fecal and oral samples were collected from these participants for the method-comparison analyses. The abstract does not provide further demographic detail such as age or sex distribution.
Fecal samples remained stable at room temperature for four days, with generally high ICCs across microbial metrics for both RNAlater and FOBT cards. Comparability between RNAlater and FOBT cards was also high, with ICCs ranging from 0.63 for relative abundance of Firmicutes to 0.93 for unweighted UniFrac. Scope mouthwash likewise showed generally high ICCs for stability. The abstract does not mention Desulfovibrio, sulfate-reducing bacteria, hydrogen sulfide, or sulfur metabolism, so this study is summarized on its own terms.
The findings support the feasibility of using RNAlater, FOBT cards, and Scope mouthwash for microbiota collection in field settings where cold storage may not be available for several days. This has practical value for prospective cohort studies conducted in resource-limited or geographically dispersed settings, including the rural and urban Iranian sites studied here. Reliable room temperature stability could reduce logistical burden and cost for large-scale microbiome research.
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.
Discriminating depressive episodes of bipolar disorder (BD) from major depressive disorder (MDD) is a major clinical challenge. Recently, gut microbiome alterations are implicated in these two mood disorders; however, little is known about the shared and distinct microbial characteristics in MDD versus BD. Here, using 16S ribosomal RNA (rRNA) gene sequencing, the microbial compositions of 165 subjects with MDD are compared with 217 BD, and 217 healthy controls (HCs). It is found that the microbial compositions are different between the three groups. Compared to HCs, MDD is characterized by altered covarying operational taxonomic units (OTUs) assigned to the Bacteroidaceae family, and BD shows disturbed covarying OTUs belonging to Lachnospiraceae, Prevotellaceae, and Ruminococcaceae families. Furthermore, a signature of 26 OTUs is identified that can distinguish patients with MDD from those with BD or HCs, with area under the curve (AUC) values ranging from 0.961 to 0.986 in discovery sets, and 0.702 to 0.741 in validation sets. Moreover, 4 of 26 microbial markers correlate with disease severity in MDD or BD. Together, distinct gut microbial compositions are identified in MDD compared to BD and HCs, and a novel marker panel is provided for distinguishing MDD from BD based on gut microbiome signatures.
Coronavirus disease 2019 (COVID-19) is an emerging serious global health problem. Gastrointestinal symptoms are common in COVID-19 patients, and severe acute respiratory syndrome coronavirus 2 RNA has been detected in stool specimens. However, the relationship between the gut microbiome and disease remains to be established.
We conducted a cross-sectional study of 30 patients with COVID-19, 24 patients with influenza A(H1N1), and 30 matched healthy controls (HCs) to identify differences in the gut microbiota by 16S ribosomal RNA gene V3-V4 region sequencing.
Compared with HCs, COVID-19 patients had significantly reduced bacterial diversity; a significantly higher relative abundance of opportunistic pathogens, such as Streptococcus, Rothia, Veillonella, and Actinomyces; and a lower relative abundance of beneficial symbionts. Five biomarkers showed high accuracy for distinguishing COVID-19 patients from HCs with an area under the curve (AUC) up to 0.89. Patients with H1N1 displayed lower diversity and different overall microbial composition compared with COVID-19 patients. Seven biomarkers were selected to distinguish the 2 cohorts (AUC = 0.94).
The gut microbial signature of patients with COVID-19 was different from that of H1N1 patients and HCs. Our study suggests the potential value of the gut microbiota as a diagnostic biomarker and therapeutic target for COVID-19, but further validation is needed.
The present study aimed to determine the differences in gut microbiota between patients with chronic kidney disease (CKD) and healthy controls (HC) and search for better microbial biomarkers associated with CKD. The 16S rRNA gene sequencing approach was used to investigate the differences in gut microbiota between the CKD and HC groups. The study found that 12 phylotypes were overrepresented in the CKD group and 19 in the HC group at the genus level. Furthermore, genera Lachnospira and Ruminococcus_gnavus performed the best in differentiating between HC and CKD populations. In addition, this novel study found that the genera Holdemanella, Megamonas, Prevotella 2, Dielma, and Scardovia were associated with the progression of CKD and hemodialysis. In conclusion, the composition of gut microbiota was different in CKD populations compared with healthy populations, and Lachnospira and R._gnavus were better microbial biomarkers. In addition, five phylotypes, including Holdemanella, Megamonas, Prevotella2, Dielma, and Scardovia, served as an indicator of the progression of CKD and hemodialysis. However, large-scale prospective studies should be performed to identify the reliability of the set of these phylotypes as biomarkers.
This study investigated the relationship between gut microbiota composition, microbial metabolic pathways, and metabolite profiles in thyroid carcinoma (TC). Researchers used 16S rRNA gene sequencing to characterize fecal microbial communities and applied PICRUSt to predict functional metabolic pathways. In a subset of participants, liquid chromatography mass spectrometry was also performed to characterize circulating or fecal metabolite profiles and correlate them with microbial genera.
The primary comparison included 30 patients with thyroid carcinoma and 35 healthy controls, whose fecal samples were used for 16S rRNA sequencing. A smaller, matched subset of the same population, 15 TC patients and 15 healthy controls, was then analyzed in more depth for combined microbiota and metabolite profiling. All participants were human subjects recruited for direct comparison between disease and healthy states.
Gut microbiota composition differed significantly between TC patients and healthy controls, with 19 genera enriched and 8 genera depleted in TC samples. Six differentially abundant genera distinguished TC patients from healthy controls with an area under the curve of 0.94, indicating strong discriminatory potential. Twelve metabolic pathways predicted by PICRUSt were significantly altered, and in the smaller matched subset, 21 differential genera and 72 significantly changed metabolites were identified and found to correlate with one another. Several genera also correlated with clinical parameters such as lipoprotein A and apolipoprotein B.
The findings suggest that gut microbiota alterations and their associated metabolite changes are linked to thyroid carcinoma and may reflect or contribute to underlying metabolic disturbances in these patients. The high discriminatory accuracy of the six-genus panel raises the possibility that gut microbiota signatures could serve as non-invasive biomarkers for thyroid carcinoma. The correlations between specific genera, metabolites, and clinical lipid parameters point toward a potential mechanistic link between the gut microbiome and host lipid metabolism in thyroid carcinoma that warrants further investigation.
The intestinal microbiota was linked to autoimmune diseases. Graves' orbitopathy (GO) is an autoimmune disease that is usually associated with Graves' disease. However, information on the microbiome of GO patients is yet lacking. To investigate whether GO patients differ from healthy controls in the fecal microbiota.
A cross-sectional study. 33 patients with severe and active GO and 32 healthy controls of Han nationality were enrolled between March 2017 and March 2018. The Gut microbial communities of the fecal samples of GO patients and healthy controls were analyzed and compared by 16S rRNA gene sequencing.
Community diversity (Simpson and Shannon) was significantly reduced in fecal samples from patients with GO as compared to controls (p < 0.05). The similarity observed while assessing the community diversity (PCoA) proposed that the microbiota of patients with GO differ significantly from those of controls (p < 0.05). At the phyla levels, the proportion of Bacteroidetes increased significantly in patients with GO (p < 0.05), while at the genus and species levels, significant differences were observed in the bacterial profiles between the two groups (p < 0.05).
The present study indicated distinctive features of the gut microbiota in GO patients. The study provided evidence for further exploration in the field of intestinal microbiota with respect to the diagnosis and treatment of GO patients by modifying the microbiota profile.
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.
Recently, gut microbiota have been studied extensively for health promotion, disease prevention, disease treatment, and exercise performance. It is recommended that athletes avoid dietary fiber and resistant starch to promote gastric emptying and reduce gastrointestinal distress during exercise, but this diet may reduce microbial diversity and compromise the health of the athlete's gut microbiota. This study compared fecal microbiota characteristics using high-throughput sequencing among healthy sedentary men (as controls), bodybuilders, and distance runners, as well as the relationships between microbiota characteristics, body composition, and nutritional status.
Body composition was measured using DXA, and physical activity level was assessed using IPAQ. Dietary intake was analyzed with the computerized nutritional evaluation program. The DNA of fecal samples was extracted and it was sequenced for the analysis of gut microbial diversity through bioinformatics cloud platform.
We showed that exercise type was associated with athlete diet patterns (bodybuilders: high protein, high fat, low carbohydrate, and low dietary fiber diet; distance runners: low carbohydrate and low dietary fiber diet). However, athlete type did not differ in regard to gut microbiota alpha and beta diversity. Athlete type was significantly associated with the relative abundance of gut microbiota at the genus and species level: Faecalibacterium, Sutterella, Clostridium, Haemophilus, and Eisenbergiella were the highest (p < 0.05) in bodybuilders, while Bifidobacterium and Parasutterella were the lowest (p < 0.05). At the species level, intestinal beneficial bacteria widely used as probiotics (Bifidobacterium adolescentis group, Bifidobacterium longum group, Lactobacillus sakei group) and those producing short chain fatty acids (Blautia wexlerae, Eubacterium hallii) were the lowest in bodybuilders and the highest in controls. In addition, aerobic or resistance exercise training with an unbalanced intake of macronutrients and low intake of dietary fiber led to similar diversity of gut microbiota. Specifically, daily protein intake was negatively correlated with operation taxonomic unit (r = - 0.53, p < 0.05), ACE (r = - 0.51, p < 0.05), and Shannon index (r = - 0.64, p < 0.01) in distance runners..
Results suggest that high-protein diets may have a negative impact on gut microbiota diversity for athletes, while athletes in resistance sports that carry out the high protein low carbohydrates diet demonstrate a decrease in short chain fatty acid-producing commensal bacteria.
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.
Checkpoint-blockade immunotherapy targeting programmed cell death protein 1 (PD-1) has recently shown promising efficacy in hepatocellular carcinoma (HCC). However, the factors affecting and predicting the response to anti-PD-1 immunotherapy in HCC are still unclear. Herein, we report the dynamic variation characteristics and specificities of the gut microbiome during anti-PD-1 immunotherapy in HCC using metagenomic sequencing.
Fecal samples from patients responding to immunotherapy showed higher taxa richness and more gene counts than those of non-responders. For dynamic analysis during anti-PD-1 immunotherapy, the dissimilarity of beta diversity became prominent across patients as early as Week 6. In non-responders, Proteobacteria increased from Week 3, and became predominant at Week 12. Twenty responder-enriched species, including Akkermansia muciniphila and Ruminococcaceae spp., were further identified. The related functional genes and metabolic pathway analysis, such as carbohydrate metabolism and methanogenesis, verified the potential bioactivities of responder-enriched species.
Gut microbiome may have a critical impact on the responses of HCC patients treated with anti-PD-1 immunotherapy. The dynamic variation characteristics of the gut microbiome may provide early predictions of the outcomes of immunotherapy in HCC, which is critical for disease-monitoring and treatment decision-making.
Background: There is accumulating evidence suggesting a connection between the gut and Parkinson's disease (PD). Gut microbiota may play an important role in the intestinal lesions in PD patients. Objective: This study aims to determine whether gut microbiota differs between PD patients and healthy controls in Northeast of China, and to identify the factors that influence the changes in the gut microbiota. Methods: We enrolled 51 PD patients and 48 healthy controls in this study. Microbial species in stool samples were determined through 16S-rRNA gene sequencing. Dietary intakes were collected from a subset of 42 patients and 23 controls using a food frequency questionnaire (FFQ). Gut microbiota species richness, diversity, differential abundance of individual taxa between PD patients and controls, and the relationship between the gut microbiota abundance and the dietary and clinical factors were analyzed. Results: PD patients showed decreased species richness, phylogenetic diversity, β- diversity, and altered relative abundance in several taxa compared to the controls. PD- associated clinical scores appeared to be the most influential factors that correlated with the abundance of a variety of taxa. The most consistent findings suggested by multiple analyses used in this study were the increase of Akkermansia and the decrease of Lactobacillus in PD patients in Northeast China. Conclusion: Gut microbiota significantly differed between a group of PD patients and healthy controls in Northeast China, with decreased species richness, phylogenetic diversity, β-diversity, and altered relative abundance in several taxa compared to the controls.
BACKGROUND Increasing evidence has suggested that gut flora play an important role in tumor progression and prognosis. However, the relationship between fecal microbiota and hematologic malignancy requires further investigation. This study aimed to characterize the relationship of the fecal microbial community in multiple myeloma (MM) patients. MATERIAL AND METHODS A total of 40 MM patients and healthy controls (n=17) were retrospectively collected from the First Affiliated Hospital of Sun Yat-sen University between October 2018 and May 2019. The fecal samples were collected for 16S rRNA high-throughput sequencing for the fecal microbial community, as well as diversity and correlation analysis. Furthermore, 21 MM patients and their family members were selected for the matched pair analysis to confirm the fecal microbiota taxonomic changes by qRT-PCR assay. RESULTS Diversity analysis showed that diversity measured by Shannon index was lower in MM patients compared with healthy controls. At the phylum level, higher abundances of Proteobacteria but lower abundances of Actinobacteria were identified in the MM group in comparison with the healthy control group. At the genus level, the proportion of Bacteroides, Faecalibacterium, and Roseburia was significantly higher in the MM group. The matched pair analysis showed that Pseudomonas aeruginosa and Faecalibacterium were significantly more abundant in the MM group. Further analysis on prognostic risk factors revealed that the Faecalibacterium prausnitzii level was significantly correlated with ISS stage. CONCLUSIONS Our study highlights the imbalanced composition and diversity of the gastrointestinal microbiome in MM patients, which could be further used as a potential biomarker for MM risk screening, therapeutic strategies, and prognostic prediction.
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.
Hashimoto's thyroiditis (HT) is an organ-specific autoimmune disease in which both genetic predisposition and environmental factors serve as disease triggers. Many studies have indicated that alterations in the gut microbiota are important environmental factors in the development of inflammatory and autoimmune diseases. A comparative analysis was systematically performed of the gut microbiota in HT patients and healthy controls.
First, a cross-sectional study of 28 HT patients and 16 matched healthy controls was conducted. Fecal samples were collected, and microbiota were analyzed using 16S ribosomal RNA gene sequencing. Second, an independent cohort of 22 HT patients and 11 healthy controls was used to evaluate the diagnostic potential of the selected biomarkers.
Similar levels of bacterial richness and diversity were found in the gut microbiota of HT patients and healthy controls (p = 0.11). A detailed fecal microbiota Mann-Whitney U-test (Q value <0.05) revealed that the abundance levels of Blautia, Roseburia, Ruminococcus_torques_group, Romboutsia, Dorea, Fusicatenibacter, and Eubacterium_hallii_group genera were increased in HT patients, whereas the abundance levels of Fecalibacterium, Bacteroides, Prevotella_9, and Lachnoclostridium genera were decreased. A correlation matrix based on the Spearman correlation distance confirmed correlations among seven clinical parameters. Additionally, the linear discriminant analysis effect size method showed significant differences in 27 genera between the two groups that were strongly correlated with clinical parameters. The linear discriminant analysis value was used to select the first 10 species from the 27 different genera as biomarkers, achieving area under the curve values of 0.91 and 0.88 for exploration and validation data, respectively.
Characterization of the gut microbiota in HT patients confirmed that HT patients have altered gut microbiota and that gut microbiota are correlated with clinical parameters, suggesting that microbiome composition data could be used for disease diagnosis. Further investigation is required to understand better the role of the gut microbiota in the pathogenesis of HT.
This study examined whether gut microbiome composition differs in people with kidney stones (nephrolithiasis) compared to healthy people. Researchers used 16S ribosomal RNA (rRNA) gene sequencing to characterize the gut microbiota of both groups. They assessed diversity, overall community structure, and genus-level abundance differences, and examined correlations between specific bacterial genera and blood trace-element concentrations.
The study included 13 patients with multiple kidney stones and 13 matched healthy controls. This is a small, case-control cohort rather than a large population sample. Matching between the two groups was used to help isolate microbiome differences associated with nephrolithiasis.
Beta diversity analysis showed a clear separation in gut microbial community structure between nephrolithiasis patients and healthy controls. Twenty genera differed significantly in relative abundance between the two groups. Among these, Phascolarctobacterium, Parasutterella, Ruminiclostridium_5, Erysipelatoclostridium, Fusicatenibacter, and Dorea were correlated with blood concentrations of trace elements including potassium, sodium, calcium, and chlorinum. A decreasing trend in observed species richness was seen in patients, though it did not reach statistical significance (p = 0.086).
These findings suggest a distinct gut microbiome signature is associated with nephrolithiasis and may link to blood trace-element balance. This raises the possibility that specific gut genera could serve as biomarkers or contribute mechanistically to kidney stone risk. Given the small sample size, larger studies are needed to confirm these associations and clarify causality.
Colorectal cancer (CRC) is a common malignant gastrointestinal tumor. In China, CRC is the 5th most commonly diagnosed cancer. The vast majority of CRC cases are sporadic and evolve with the adenoma-carcinoma sequence. There is mounting evidence indicating that gut microbiota and inflammation play important roles in the development of CRC although study results are not entirely consistent. In the current study, we investigated the changes in the CRC-associated bacteria and plasma inflammatory factors and their relationships based on data from a case-control study of Han Chinese. We included 130 initially diagnosed CRC patients, 88 advanced colorectal adenoma patients (A-CRA), 62 patients with benign intestinal polyps and 130 controls.
Fecal microbiota composition was obtained using 16S ribosomal DNA (16S rDNA) sequencing. PCOA analysis showed structural differences in microbiota among the four study groups (P = 0.001, Unweighted Unifrac). Twenty-four CRC-associated bacteria were selected by a two-step statistical method and significant correlations were observed within these microbes. CRC-associated bacteria were found to change with the degree of malignancy. Plasma C-reactive protein (CRP) and soluble tumor necrosis factor II (sTNFR-II) displayed significant differences among the four study groups and increased with adenoma-carcinoma sequence. The correlations of CRP and sTNFR-II with several CRC-associated microbes were also explored.
CRC-associated species and plasma inflammatory factors tended to change along the adenoma-carcinoma sequence. Several CRC-associated bacteria were correlated with CRP and sTNFR-II. It is likely that gut microbiome and inflammation gradually form a microenvironment that is associated with CRC development.
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 study examined whether human gut microbial enterotypes, defined by the ratio of Prevotella to Bacteroides abundance (P/B ratio), are a stable and biologically meaningful way to classify individuals. The researchers used quantitative PCR to measure the P/B ratio and 35 selected bacterial taxa. They then tested whether a 6-month controlled dietary intervention, comparing the new Nordic diet (NND) to the average Danish diet (ADD), could shift these microbial groupings or the underlying taxa.
The study included 62 subjects between 18 and 65 years old who had central obesity and components of metabolic syndrome. Participants were grouped into two discrete clusters based on their P/B ratio, then followed through the randomized 6-month dietary intervention comparing NND and ADD.
Subjects could be reliably divided into two discrete groups using only their P/B ratio, and this grouping remained stable across the 6-month diet intervention. Neither the P/B-based groups nor the broader cohort showed significant changes in the 35 quantified bacterial taxa when comparing the ADD and NND diets. Despite this microbial stability, the high-P/B group had higher total plasma cholesterol than the low-P/B group after the intervention.
The findings suggest that P/B-based enterotyping identifies a stable, diet-resistant trait of the gut microbiota rather than a state that shifts readily with short-term dietary change. Because the high-P/B group showed higher plasma cholesterol after intervention, stratifying individuals by P/B ratio could help identify subgroups with differing metabolic or cardiovascular risk responses to diet. This supports using P/B ratio as a simple stratification tool for future studies assessing individualized responses to dietary interventions.
This study examined whether fecal microbiota composition could serve as a non-invasive marker for detecting colorectal cancer (CRC). Researchers used metagenomic sequencing of stool samples to identify taxonomic markers distinguishing CRC patients from tumor-free controls. They then compared the accuracy of this metagenomic approach to the standard fecal occult blood test (FOBT), including a combined-test strategy. The study also explored whether fecal microbial changes reflected microbial community shifts at the tumor site itself, along with associated metabolic changes.
The initial study population comprised 156 participants whose fecal samples were profiled by metagenomic sequencing to build the taxonomic marker panel. The findings were then validated in independent patient and control populations totaling 335 individuals from different countries. Together, the cohorts spanned both early- and late-stage CRC cases alongside tumor-free controls, though the abstract does not specify age, sex, or other demographic details.
Metagenomic detection of CRC performed similarly to the standard FOBT, and combining the two approaches improved sensitivity by more than 45 percent relative to FOBT alone while maintaining its specificity. Detection accuracy did not differ significantly between early- and late-stage cancer, and the results were validated across independent populations from different countries. CRC-associated fecal microbiome changes partly mirrored microbial community composition at the tumor itself, suggesting tumor-related host-microbe interactions. The data also indicated a metabolic shift from fiber degradation in controls to utilization of host carbohydrates and amino acids in CRC patients, accompanied by increased lipopolysaccharide metabolism.
These findings suggest fecal metagenomic profiling could serve as a non-invasive, early-stage screening tool for colorectal cancer, particularly when combined with existing tests like FOBT to boost sensitivity without sacrificing specificity. The ability to detect early-stage cancer as reliably as late-stage disease points to potential use in earlier intervention and improved outcomes. The parallel between fecal and tumor-associated microbial shifts, along with a metabolic move toward host-carbohydrate and amino-acid utilization and elevated lipopolysaccharide metabolism, implicates the gut microbiome as an active participant in tumor-related host-microbe interactions rather than a passive bystander. This reinforces the rationale for further validation of microbiome-based screening across broader, more diverse populations.
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.
2026-07-04
Anaerobutyricum hallii majorTaxon page created: biology (morphology, health role, beneficial factors), its cross-feeding metabolic role, what depletes it, supportive interventions, the data-derived Conditions table across 88 conditions, and the full research feed.
Engels C, Ruscheweyh HJ, Beerenwinkel N, Lacroix C, Schwab C.
The common gut microbe Eubacterium hallii also contributes to intestinal propionate formation.Front Microbiol. 2016
Udayappan S, Manneras-Holm L, Chaplin-Scott A, Belzer C, Herrema H, Dallinga-Thie GM, Duncan SH, Stroes ESG, Groen AK, Flint HJ, Backhed F, de Vos WM, Nieuwdorp M.
Oral treatment with Eubacterium hallii improves insulin sensitivity in db/db mice.NPJ Biofilms Microbiomes. 2016
Hiippala K, Jouhten H, Ronkainen A, Hartikainen A, Kainulainen V, Jalanka J, Satokari R.
The potential of gut commensals in reinforcing intestinal barrier function and alleviating inflammation.Nutrients. 2018
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