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Streptococcus salivarius is one of the first microbes to colonize a newborn's mouth and stays a dominant, friendly resident for life. Some strains are sold as probiotics that crowd out throat and mouth pathogens.
Streptococcus salivarius is a pioneer commensal of the human mouth and upper digestive tract and a well-known probiotic. Friendly strains such as K12 produce bacteriocins that suppress oral and throat pathogens, and in a randomized trial K12 reduced severe radiotherapy-induced oral mucositis while enriching healthy oral commensals.
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 MoreStreptococcus salivarius is a Gram-positive commensal that is among the first microbes to colonize the mouth after birth and remains one of the dominant, benign residents of the oral cavity and upper gastrointestinal tract throughout life. Friendly strains, notably K12 and M18, are used as probiotics because they produce bacteriocins that suppress oral and throat pathogens.[1] On this database it appears as a differentially abundant taxon across many human microbiome studies.
In a randomized controlled trial, the S. salivarius K12 probiotic significantly reduced severe oral mucositis in head-and-neck radiotherapy patients while inhibiting opportunistic pathogens and enriching healthy oral commensals.[1] In this database's framework it is not a metal-weaponizing pathogen but a pioneer commensal whose presence marks a stable, well-defended mucosa in which nutritional immunity keeps opportunists in check.[2]
S. salivarius is a Gram-positive, non-motile coccus that grows in chains and colonizes mucosal surfaces of the mouth and upper digestive tract.[1] It is generally regarded as safe, and select strains are formulated as oral probiotic lozenges.[1]
S. salivarius is a beneficial pioneer commensal. By occupying mucosal surfaces and producing bacteriocins it competes with pathogens for space and resources, supporting a balanced oral and upper-GI community.[1] Probiotic strains have shown clinical benefit, including reduced radiotherapy-induced oral mucositis.[1]
Its useful features are ecological and antimicrobial.
| Factor | Description and role |
|---|---|
| Bacteriocin production | Friendly strains secrete bacteriocins that inhibit oral and throat pathogens, the basis of their probiotic use.[1] |
| Pioneer colonization | Early, durable colonization of mucosal surfaces provides competitive exclusion of opportunists.[1] |
| Commensal enrichment | In trial, the K12 probiotic enriched healthy oral commensals while suppressing pathogens during radiotherapy.[1] |
| Mucosal protection | Reduced the incidence, onset, and duration of severe oral mucositis with a good safety profile.[1] |
S. salivarius is a mucosal commensal, not a metal scavenger. By holding niche space and producing bacteriocins it helps maintain a stable community that resists opportunist expansion, aligning with the balanced-mucosa signal this database favors.[2]
As an oral and upper-GI resident, its detection in stool-based gut studies can reflect swallowed oral flora rather than a stable colonic population.
| Consideration | Effect |
|---|---|
| Oral-to-gut translocation | Signals in gut studies may reflect swallowed oral S. salivarius, so gut-abundance changes need cautious interpretation.[1] |
| Antibiotics | Broad antibiotics can disrupt this beneficial commensal along with the wider community.[2] |
The entries below are supportive strategies classified by our validation method and are not medical advice.
| Intervention | Class | Status |
|---|---|---|
| S. salivarius K12/M18 oral probiotic | Probiotic | Validation In Progress |
| Oral-mucositis support during radiotherapy | Clinical | Validation In Progress |
| Oral-hygiene and antibiotic stewardship | Practice | Validation In Progress |
| Intervention | Mechanism |
| K12/M18 probiotic | Delivers bacteriocin-producing strains that suppress pathogens and enrich healthy commensals.[1] |
| Radiotherapy support | In trial, K12 reduced severe oral mucositis incidence, onset, and duration.[1] |
| Stewardship | Limiting unnecessary antibiotics preserves this beneficial commensal.[2] |
Where Streptococcus salivarius (NCBI:txid1304) 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 80 conditions and 92 studies, the signal is genuinely mixed: enriched in 39, depleted in 27, and direction-conflicting in 14 (directional agreement 0.63). Because S. salivarius is chiefly an oral and upper-GI commensal, gut-study signals can reflect swallowed oral flora, so the aggregate evidence tier is Low.
How to read these. S. salivarius primarily lives in the mouth and upper gut, so a differential signal in a fecal study may reflect oral-to-gut translocation rather than a stable colonic population. This is why direction can vary by cohort and the aggregate tier stays Low.
Internal summaries of the 92 studies we reviewed in which S. salivarius was a differential taxon across this corpus.
This study examined how diet shapes the human gut microbiome at species-level resolution, using app-based diet logs paired with shotgun metagenomic sequencing. The researchers modeled associations between specific foods, broader dietary patterns (including degree of food processing), and microbial diversity, species composition, and functional pathways. They also tested whether these diet-microbiome associations held up over a multi-year period and explored whether predicted microbiome shifts could inform personalized dietary interventions.
The analysis drew on 10,068 participants from the Human Phenotype Project, each contributing app-based dietary logs and shotgun metagenomic data. The abstract does not specify demographic details such as age range, sex distribution, or geographic location beyond identifying the cohort as part of this project. This represents one of the largest paired diet-microbiome datasets described in the abstract, but no further population characteristics are given.
Diet significantly predicted microbial diversity, with correlations of 0.26 for richness and 0.24 for the Shannon Index, and it predicted the relative abundance of 669 of 724 species tested (92.4 percent) and 313 of 320 functional pathways (97.8 percent), all at a false discovery rate below 0.05. Feature attribution revealed specific food-microbe links, including coffee with Lawsonibacter asaccharolyticus (r = 0.43), yogurt with Streptococcus thermophilus (r = 0.42), and milk with Bifidobacterium species (r = 0.31 to 0.36). Degree of food processing emerged as a broader dietary pattern predictor of microbial diversity and composition, and 82.5 percent of species showed significant longitudinal tracking between predicted and observed abundances over four years.
The scale and consistency of these diet-microbiome associations, holding for the large majority of species and pathways tested and persisting over four years, suggest diet is a robust and durable lever for shaping gut microbial ecology. The identification of specific, reproducible food-microbe pairings (such as coffee, yogurt, and milk with particular taxa) and the role of food processing level point toward concrete dietary targets rather than vague nutritional advice. The exploratory framework for simulating personalized dietary interventions with predicted microbiome shift effects moves this work toward practical, individualized nutrition strategies rather than one-size-fits-all recommendations.
This study examined whether alterations in the gut microbiome track the development of Parkinson's disease (PD) in people who carry GBA1 gene variants but have not (yet) developed PD symptoms. The researchers combined clinical data with fecal metagenomics and used an analysis method that assessed both differential abundance of microbial species and the coherence of that abundance variation across groups, measured with Cliff's delta. The goal was to determine whether microbiome composition could serve as an early marker of PD risk in genetically at-risk individuals.
The primary cohort included 271 patients with PD, 43 carriers of GBA1 variants who had not developed PD symptoms (GBA-NMC), and 150 healthy controls. Findings were then checked against three independent cohorts from the United States, Korea, and Turkey, together comprising 638 additional PD patients and 319 additional healthy controls. In total, the study drew on clinical and fecal metagenomic data from close to 1,400 individuals across four countries.
About 25% of the gut microbiome in GBA-NMC individuals showed a composition that was intermediate between healthy controls and patients with PD. This intermediate microbiome signature was strongly correlated with disease progression in patients who already had PD, and with prodromal symptoms suggestive of future PD in both GBA-NMC and healthy individuals. Similar microbiome alterations were reproduced across the three independent international cohorts, strengthening confidence that the pattern is not specific to one population.
The findings suggest gut microbiome changes can flag both genetically at-risk (GBA1 carriers) and non-genetically at-risk people in the general population who may be on a trajectory toward developing PD. This positions the microbiome as a potential early, non-invasive marker during the premanifest phase of disease, before clinical symptoms appear. Such a marker could eventually help identify candidates for early monitoring or intervention trials aimed at delaying or preventing PD onset.
Irritable bowel syndrome (IBS) is a common functional gastrointestinal disorder characterized by abdominal pain, altered bowel habits, and frequent comorbidity with anxiety and depression. The gut microbiota has been implicated in gut-brain axis (GBA) dysfunction, but consistent microbial signatures remain unclear. We performed whole metagenome shotgun sequencing of stool samples from 63 female patients with moderate to severe IBS and 34 female healthy controls and assessed microbial composition and functional pathways. Microbial richness and diversity were slightly reduced in IBS, though with high variability and no robust separation from controls. Differential abundance analyses revealed enrichment of Streptococcus sp. and the sulfate-reducing bacterium Desulfovibrio piger in IBS, alongside reductions in Bifidobacterium and Methanobrevibacter. Functional profiling identified 39 differentially abundant pathways: amino acid biosynthesis (e.g., L-isoleucine, L-threonine) was more prominent in IBS, while carbohydrate degradation pathways (e.g., galactose, stachyose) were enriched in healthy controls. These findings indicate modest but significant IBS-associated shifts in gut microbial composition and function that may contribute to IBS symptoms. However, high intra-group variability underscores the complexity of IBS and highlights the need for larger, multi-omics studies to define robust microbial markers. These results contribute to a growing body of evidence emphasizing the complexity of gut microbiota-host interactions and the need for high-resolution, systems-level approaches in microbiome-associated disorders.
This study examined how Moderate Acute Malnutrition (MAM) in early childhood relates to the gut microbiome, plasma lipid levels, brain electrical activity, and early language development. Using multi-system SHAP-interpreted random forest models and network analysis, the researchers looked for interconnected biological pathways linking these systems. The goal was to build a mechanistic picture of how malnutrition might give rise to lasting neurocognitive consequences.
The study population was a cohort of one-year-old children in Dhaka, Bangladesh. The abstract does not report an exact sample size. Children were assessed for fecal microbiome composition, plasma lipid profiles, electroencephalogram (EEG) activity, and vocalization as part of the analysis.
MAM was associated with enrichment of fecal Rothia mucilaginosa and Streptococcus salivarius, both oral commensal species, alongside depletion of Bacteroides fragilis. These microbiome shifts formed interconnected pathways linked to reduced plasma odd-chain fatty acid levels, decreased gamma and beta EEG power in temporal and frontal brain regions, and reduced vocalization. The pattern suggests that prolonged colonization of the gut by oral bacteria may coincide with delayed gut microbiome and brain development.
The findings support the hypothesis that oral commensal overgrowth in the gut, alongside loss of species such as Bacteroides fragilis, may delay both microbiome maturation and brain development in malnourished children. Because the fecal microbiome, plasma lipids, and brain activity appear connected through shared pathways, interventions might need to address multiple systems at once rather than gut bacteria alone. The authors note that causal links still require empirical validation, but this work offers a foundation for designing interventions targeting MAM-associated neurodevelopmental deficits.
This study examined the human gut microbiome across diverse African populations using shotgun metagenomic sequencing. It aimed to characterize how geography, lifestyle, and environmental factors shape gut microbial composition in regions underrepresented in prior microbiome research. The researchers also assembled bacterial genomes directly from the metagenomic data and looked for microbiome signatures associated with HIV infection.
The AWI-Gen 2 Microbiome Project sampled 1,801 women from Burkina Faso, Ghana, Kenya, and South Africa. The cohort spanned a wide range of community settings, from rural and horticultural communities to post-industrial and urban informal settlements. This design was intended to capture a breadth of population diversity not typically represented in large-scale gut microbiome studies, which have historically underrepresented low- and middle-income countries.
The study identified taxa with clear geographic and lifestyle associations, including loss of Treponema and Cryptobacteroides species and gain of Bifidobacterium species in urban populations. The researchers assembled 1,005 bacterial metagenome-assembled genomes from the dataset. They also found evidence that antibiotic susceptibility may drive the absence of Treponema succinifaciens in urban populations. Additionally, an HIV infection signature was identified, defined by several taxa, including Dysosmobacter welbionis and Enterocloster species, not previously linked to HIV.
This work represents the largest population-representative survey of the gut microbiome in Africa, expanding the global microbiome atlas beyond historically overrepresented, industrialized populations. The urbanization-linked taxa shifts suggest that lifestyle transitions, including antibiotic exposure, can rapidly reshape the gut microbiome. The discovery of a novel HIV-associated taxa signature, involving organisms not previously implicated, opens new avenues for investigating host-microbiome interactions in HIV infection across diverse global populations.
The study examined how Zhuyang Tongbian Decoction (ZTD), a treatment for functional constipation (FC), affects the gut microbiome and related inflammatory markers. Researchers used 16S rRNA sequencing, metagenomics, and metabolomics to track changes in intestinal flora composition and microbiota metabolic function. They also measured fecal short-chain fatty acid (SCFA) levels and serum concentrations of TLR4, NF-κB, TNF-α, and IL-6 before and after treatment.
The study included 40 patients with functional constipation, randomly divided into a control group (20 cases, treated with lactulose) and a treatment group (20 cases, treated with ZTD). Twenty healthy volunteers were also recruited during the same period, presumably for comparison. Sample sizes were small, consistent with the pilot nature of the study.
The ZTD treatment group showed a significant increase in beneficial bacteria, including Bifidobacterium, Lactobacillus, and Faecalibacterium prausnitzii (P < 0.05). Desulfobacterota and Ruminococcus were significantly reduced in the treatment group (P < 0.05). Fecal acetic and propionic acid levels, both short-chain fatty acids linked to anti-inflammatory commensal activity, were also affected by treatment, though the abstract text describing the exact direction and magnitude was cut off.
The findings suggest ZTD may relieve functional constipation partly by reshaping the gut microbiota toward beneficial, SCFA-producing organisms such as Faecalibacterium prausnitzii while reducing potentially less favorable taxa. This points to a microbiome-mediated mechanism, possibly involving reduced inflammatory signaling through the TLR4/NF-κB pathway, as part of ZTD's therapeutic effect. As a pilot study with a small sample size, these results support further, larger trials to confirm the mechanism and clinical benefit.
The colonization and evolution of gut microbiota early in life play a vital role in shaping a healthy, robust immune system for infant health, whether in combating short-term illness or improving long-term health outcomes. Early-life clinical practices may interrupt or disrupt the normal colonization process of the infant gut microbiota, thereby increasing disease susceptibility. In this prospective cohort study, we analyzed the gut microbiota of 46 term and 23 preterm infants using 16S rRNA gene metagenomic sequencing. Fecal samples were collected at six timepoints during the first three months of life. Notably, gestational age was the main factor contributing to differences in the meconium microbial composition. Intriguingly, our study unveiled a more homogeneous microbial composition in preterm infants with more abundant Bifidobacterium from the postnatal age (PNA) of one month. Concurrently, the beneficial bacteria Bifidobacterium and Lactobacillus gradually increased, and the potentially pathogenic bacteria Clostridium, Enterobacter, Enterococcus, Klebsiella, and Pseudomonas gradually decreased. Furthermore, our study underscored a link between decreased microbial diversity of preterm infants and exclusive breastfeeding and antibiotic exposure. Moreover, preterm infants with patent ductus arteriosus (PDA) exhibited reduced microbial diversity but higher abundances of Streptococcus oralis and Streptococcus mitis.
Primary Immunodeficiencies (PIDs) arise from rare genetic defects affecting humoral and cellular immunity, which can lead to reduced dental plaque control. This study aimed to characterise the subgingival dental plaque microbiome in neutropenic PID children compared to healthy controls and assess their response to non-surgical periodontal therapy.
Subgingival plaque was collected from three first molars and one first incisor at baseline and 6 months post therapy from children with PID (n = 24) and systematically healthy control participants (n = 24) who were recruited from Great Ormond Street Hospital and Barts Health NHS Trust, respectively. The subgingival microbiome was profiled using an Illumina metabarcoding approach on the bacterial 16S rRNA gene V1-V2 region.
Significant shifts in community structure were observed post therapy, as measured by alpha and beta diversities. An increase in Rothia spp., Neisseria spp. and Actinomyces spp. was noted in PID children post therapy, consistent with clinical improvements. Baseline blood absolute neutrophil counts in PID children were positively associated with Streptococcus cristatus and Gemella spp., and negatively with Saccharibacteria, Capnocytophaga and Porphyromonas spp., highlighting key host-microbial relationships.
Non-surgical periodontal therapy modulated the subgingival microbiota in neutropenic PID children, revealing novel host-microbial interactions important for the oral microbiome in health.
The gut microbiota is a complex microbial ecosystem with a major impact on health and disease. Some gut unicellular eukaryotes (particularly Blastocystis) have been linked to features of intestinal eubiosis. Meanwhile, little is known regarding associations between gut-pathogenic protozoa, such as Giardia, and gut microbiota signatures. We therefore characterized and compared gut microbiota profiles of 60 Giardia-positive and 31 Giardia-negative Algerian individuals using amplicon-based next-generation sequencing of prokaryotic and eukaryotic ribosomal genes and stratifying for co-colonization with other unicellular eukaryotes, such as species of Archamoebae or Blastocystis. Overall, we found that alpha and beta microbiota diversity did not differ significantly between Giardia-positive and Giardia-negative individuals, regardless of the presence or absence of Archamoebae and Entamoeba (p > 0.05). However, significant differences were observed in both alpha and beta diversity between Giardia-positive, Blastocystis-negative and Giardia-positive, Blastocystis-positive individuals (observed richness, p = 0.0016; ANOSIM = 0.001), and similar differences were noticed between Blastocystis-negative and-positive carriers (p < 0.05), regardless of Giardia carrier status. Importantly, these differences in gut microbiota were considered to be independent of factors such as sex, age, and location (p > 0.05). Conclusively, Giardia-positive individuals may exhibit features of eubiosis, but whether this depends on the presence of Blastocystis should be confirmed by future studies. These findings combined might indicate that Blastocystis could be an active driver of gut microbiota diversity.
The microbiota is actively engaged in interaction networks both with the host and among its own constituent members. However, comprehensive studies examining the microbiome profiles across various respiratory sites in pulmonary tuberculosis (PTB) are lacking. Here, we explored the diversity of the microbiome in PTB patients across multiple respiratory sites and investigated potential interactions between the microbiomes of these sites.
A total of 130 respiratory tract samples were collected from multiple sites of 22 patients with PTB and 14 healthy individuals, including the oral cavity, trachea, and both the healthy and affected sides of the lungs. These samples were subjected to metagenomic sequencing to analyze the characteristics and diversity of the respiratory microbiome.
We found that the respiratory tract of PTB patients had higher microbial diversity than seen in the healthy individuals (8,182 vs 6,465). Among them, Rothia, Prevotella and Actinomyces exhibited higher proportions in PTB. The characteristics of high diversity features in the oral site were more prominent with PTB, especially the notable difference of Rothia mucilaginosa. Additionally, Streptococcus, Neisseria, Prevotella and Fusobacterium have strong interactions with other species at present at various sites of PTB patients, as well as frequent communication between these species during migration in the upper and lower respiratory tract.
The diversity and translocation of microbiota across the respiratory tract in PTB patients are associated with increased susceptibility of microbiome. The predominance of Rothia, Prevotella, and Actinomyces may represent progression-associated microbial signatures, warranting mechanistic studies on their pathogenic potential through host-microbe interactions to guide therapeutic targeting.
Respiratory microbial dysbiosis has been implicated in the occurrence and progression of community-acquired pneumonia (CAP). However, the dynamic variation in the respiratory microbiota and its interaction with the host response remain poorly understood. Here, we performed metagenomic analysis of respiratory and gut microbiota, along with blood transcriptomics, using longitudinally collected samples from 38 CAP patients. CAP patients presented disrupted sputum microbiota at the early, middle, and late stages of hospitalization. Microbial pathways involved in peptidoglycan biosynthesis and immune evasion, particularly contributed by the Streptococcus genus, were enriched in CAP patients. Additionally, several Streptococcus strains demonstrated correlation between respiratory and gut microbiota in CAP patients. By incorporating host response data, we revealed that Streptococcus oralis (SOR) was associated with host pathways involved in the innate immune response to infection, and this microbe‒host interaction was reproduced in a newly enrolled CAP cohort consisting of 22 patients with influenza infection. The host-SOR interaction was validated in a mouse model, where SOR demonstrated protective efficacy against influenza virus infection comparable to that of the well-established respiratory probiotic Lactobacillus rhamnosus GG. Preaspiration of SOR in mice significantly mitigated body weight loss, reduced lung inflammation, and lowered viral loads following influenza virus challenge. Host response profiling indicated that SOR priming activated a greater innate immune response at the early stage of infection and that this response resolved timely as the host began to recover. These findings suggest that respiratory commensals play an immune-protective role by inducing a timely innate immune response to prevent CAP progression.
This cross-sectional exploratory study examined associations between subjective sleep indices and gut microbiome features in adults with colorectal cancer (CRC). Researchers compared patients to their sleep-partner caregivers using sleep diaries, stool sampling, and dietary intake questionnaires. The design allowed comparison of microbiome and sleep characteristics within matched household pairs who shared similar diet and environment.
Forty participants were studied, consisting of 20 patient-caregiver dyads. Each dyad included an adult with colorectal cancer and their sleep-partner caregiver, and both members completed sleep diaries, stool sampling, and dietary questionnaires individually. Patients and caregivers had comparable demographics, dietary intake, and sleep indices at baseline.
Patients with CRC had significantly different gut microbiome beta diversity (p = .005) and alpha diversity (Inverse Simpson, p = .029) compared with their caregivers, along with 7 more and 6 less differentially abundant taxa. Among patients only, those with high sleep efficiency (at least 85%) had higher gut microbial diversity than those with lower sleep efficiency (Inverse Simpson p = .019, Shannon Index p = .035). Some oral and gut microbes were also differentially abundant between patients with high versus low sleep efficiency scores.
The findings highlight a link between sleep health and gut microbiome characteristics specifically in patients with colorectal cancer, distinct from their genetically unrelated but cohabiting caregivers. This suggests sleep quality may be associated with gut microbial diversity in cancer patients, though the abstract does not identify specific taxa driving this relationship. The authors note that further research with a larger sample is needed to replicate these findings and identify the pathways linking sleep to gut microbiome features.
Thirty participants undergoing health checkups were classified into three groups-normal weight (BMI 18.5-22.9), overweight (BMI 23.0-24.9), and obese (BMI ≥25.0)-with ten individuals per group. Those with H. pylori infection, atrophic gastritis, or intestinal metaplasia were excluded. Gastric microbiota from four antral biopsies per subject were analyzed using 16S rRNA sequencing and functional profiling by metagenomic prediction.
Alpha diversity (Gini-Simpson index) was significantly lower in the combined overweight/obese group than that in the normal group (P=0.049). Beta diversity analysis revealed clear group separation (Bray-Curtis, P=0.005; unweighted UniFrac, P=0.004). Significant species differences between the groups were observed; specifically, the abundances of Muribaculum gordoncarteri, Turicibacter bilis, and Duncaniella dubosii, were significantly reduced in the overweight/obese group. Functional predictions showed differential enrichment of pathways related to fatty acid, amino acid, vitamin, and carbohydrate metabolism across BMI categories. These findings suggest that alterations in the gastric microbiota may be linked to obesity and metabolic dysregulation.
This study examined whether the gut microbiome is related to brain structure in apparently healthy adults. The researchers used 16S ribosomal RNA gene sequencing of stool samples to characterize gut microbiome composition and diversity. They paired this with brain magnetic resonance imaging and automated voxel-based morphometry to measure brain volumes, including gray matter and white matter. Statistical methods included principal coordinate analysis, linear discriminant analysis, and multivariable linear regression to test associations between microbiome measures and brain volume.
The study population was 623 Japanese men drawn from the Shiga Epidemiological Study on Subclinical Atherosclerosis (SESSA), a population-based cross-sectional cohort. Stool samples were collected during the study's follow-up stage, and participants had a mean age of 68.0 years (SD 8.0), ranging from 46 to 83 years. All participants underwent brain MRI as part of the same assessment.
After adjusting for age and total intracranial volume, gray matter volume showed a positive association with alpha diversity, specifically the Shannon index richness, at a q-value below 0.01. However, this association was no longer significant once the analysis further adjusted for body mass index, physical activity, smoking, drinking, and hypertension. Beta diversity, measured using weighted UniFrac distances via principal coordinate analysis, showed differences related to white matter volume, though the abstract text describing this result is incomplete. This pattern of the abstract is not about Christensenellaceae, Christensenella, leanness, BMI-associated taxa, or heritability; the study centers instead on gut microbiome diversity and brain morphometry.
The findings suggest that in generally healthy older men, any apparent link between gut microbial diversity and gray matter volume may largely reflect shared lifestyle and metabolic factors such as body mass index, physical activity, smoking, drinking, and hypertension rather than a direct, independent relationship. This underscores the importance of adjusting for lifestyle and cardiometabolic confounders when studying gut-brain associations in human populations. The results also support continued investigation of beta diversity and white matter relationships as a potentially distinct avenue linking the gut microbiome to brain structure. Overall, the study adds population-based human evidence to a field previously dominated by animal models and specific patient populations.
This randomized, placebo-controlled trial examined whether resistant starch (RS), a prebiotic, has therapeutic effects in metabolic dysfunction-associated steatotic liver disease (MASLD). The researchers focused on why RS efficacy was heterogeneous, since about 30% of participants showed limited benefit. Using multi-omics analysis, fecal microbiota transplantation, population stratification, network analysis, and in vitro and in vivo experiments, they sought the microbial basis of this variable response. They then built a predictive model combining baseline microbial and clinical features to forecast who would respond.
Participants were drawn from the original randomized, placebo-controlled trial of resistant starch in MASLD, with the finding of heterogeneous response replicated in a separate multi-center trial (ChiCTR2300074588). The abstract does not give exact participant numbers or demographic details for either trial. A strain, Bifidobacterium pseudocatenulatum RRP01, was isolated from the study cohort for further experimentation.
Baseline gut microbiota composition was the dominant contributor to whether a participant responded to resistant starch. Prevotella was identified as a key cause of low response because it inhibits RS-degrading bacteria, impairing RS utilization. In contrast, the cohort-derived strain Bifidobacterium pseudocatenulatum RRP01 restored RS degradation and improved the RS response that Prevotella had attenuated. A predictive model integrating baseline microbial and clinical features achieved an area under the curve of 0.74 to 0.87 for stratifying likely responders.
The findings show that pre-existing gut microbiota composition, not just the intervention itself, determines whether resistant starch benefits patients with MASLD. This supports moving toward microbiota-oriented precision therapeutics, where baseline microbial and clinical features are used to predict who will respond before treatment begins. It also points to specific microbiota-targeted strategies, such as supplementing Bifidobacterium pseudocatenulatum RRP01, to overcome Prevotella-driven non-response and expand the benefit of prebiotic therapy to more patients.
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.
Colorectal cancer (CRC) has a high mortality rate worldwide. Oral and intestinal microbiota members may have an effect on gastrointestinal tumors' pathogenesis, particularly in CRC. Designed as a pilot study, this study's aim was to investigate the relationship between CRC and oral microbiota and to identify potential biomarkers for CRC diagnosis. Saliva samples were collected from recently diagnosed CRC patients (n = 14) and healthy controls (n = 14) between March 2023 and December 2023. Microbiota (16S rRNA) analyses were conducted on these saliva samples using a next-generation sequencing method. Phylogenetic analyses, including alpha diversity, principal component analysis (PCA), principal coordinate analysis (PCoA), beta diversity, biomarker, and phenotype analyses, were conducted using the Qiime2 (Quantitative Insights Into Microbial Ecology) platform. Alpha diversity indices (Shannon: p = 0.78, Cho1: p = 0.28, Simpson: p = 0.81) showed no significant difference between CRC and control groups. Beta diversity analysis using Bray-Curtis PCoA indicated significant differences in the microbial community between the two groups (p = 0.003). Examination of OTU distributions revealed that the Mycoplasmatota phylum was undetectable in the oral microbiota of healthy controls but was significantly elevated in CRC patients (CRC: 0.13 ± 0.30, Control: 0.00 ± 0.00, p < 0.05). Additionally, Metamycoplasma salivarium, Bacteroides intestinalis, and Pseudoprevotella muciniphila were undetectable in healthy controls but significantly more prevalent in CRC patients (p < 0.05 for all three species). LEfSe analysis identified eight species with an LDA score > 2, Granulicatella adiacens, Streptococcus thermophilus, Streptococcus gwangjuense, Capnocytophaga sp. FDAARGOS_737, Capnocytophaga gingivalis, Granulicatella elegans, Bacteroides intestinalis, and Pseudoprevotella muciniphila, as potential biomarkers. The results of this study contribute critical evidence of the role of oral microbiota in the pathogenesis of colorectal cancer. Alterations in the microbiota suggest potential biomarkers in understanding the biological mechanisms underlying CRC and developing diagnostic and therapeutic strategies.
To evaluate the effect of different oral irrigators on the sub-gingival microbiome composition in patients with naturally occurring plaque-induced gingivitis.
Sub-gingival plaque was collected from adults participating in a clinical trial assessing the efficacy of oral hygiene with two different oral irrigators (Waterpik Water Flosser [Group 1] and Oral-B Water Flosser [Group 2]) versus dental flossing (Group 3) for microbiome analysis. Plaque samples were reflective of naturally occurring plaque-induced gingivitis at baseline and of gingival health at the endpoint (4 weeks). Clinical measures of gingival inflammation were collected, and the sub-gingival microbiome was analysed by 16S rRNA sequencing to identify amplicon sequence variants.
Oral hygiene instruction with self-performed manual toothbrushing and water-jet irrigation led to significant reductions in inflammation for all groups; both oral irrigators outperformed flossing in bleeding-on-probing reduction (p < .001). Microbiome diversity of sub-gingival plaque remained relatively stable over time, but significant changes were noted in certain taxa, consistent with increases in the relative abundance of commensals and reductions in late colonizers and periodontal pathogens in the water-jet groups.
Reduction in gingival inflammation at 4 weeks within the water-jet groups is accompanied by slight but critical changes in microbiome composition. Although biodiversity does not substantially change within 4 weeks during the resolution of naturally induced gingivitis, significant relative increases in commensal early colonizers such as Streptococcus, Veillonella and Fusobacterium were accompanied by a shift towards a less anaerobic microbiota associated with return to health. These changes were contingent upon the type of interdental hygiene, with Group 1 exhibiting more significant alterations in microbiome composition towards a periodontal-health-compatible community.
This study examined the longitudinal development of infant gut microbiota and its relationship to tetanus toxoid vaccine responses. Researchers used 16S rRNA gene sequencing to profile gut microbiota at two early-life time points, under one week and 15 weeks of age. They evaluated whether HIV exposure without infection altered microbiota composition and succession, and whether these microbiota patterns were linked to anti-tetanus antibody titers measured by enzyme-linked immunosorbent assay.
The study included 278 infants total, drawn from two cohorts: 82 South African infants (61 exposed to HIV but uninfected, and 21 HIV-unexposed and uninfected) and 196 Nigerian infants (141 exposed to HIV but uninfected, and 55 HIV-unexposed and uninfected). All infants were assessed at both the under-one-week and 15-week time points. Feeding practice was also documented, noting that the Nigerian infants were exclusively breastfed.
Gut microbiota composition and its succession over the first 15 weeks of life were shaped more strongly by geographic location and infant age than by HIV exposure status. Nigerian infants underwent a dramatic microbiota shift over this period, becoming dominated by Bifidobacterium longum subspecies infantis, a shift not seen in South African infants even when the analysis was restricted to exclusively breastfed babies. Using Least Absolute Shrinkage and Selection Operator (LASSO) regression, the study found that HIV exposure and gut microbiota composition were each independently associated with tetanus antibody titers at 15 weeks, with high passively transferred maternal antibody also playing a role.
The findings suggest that geography and associated feeding and environmental practices are more powerful drivers of early infant gut microbiota development than HIV-exposure status alone. The emergence of Bifidobacterium longum subspecies infantis dominance in exclusively breastfed Nigerian infants, but not South African infants, points to population-specific factors shaping microbiota maturation beyond breastfeeding alone. Because gut microbiota and HIV exposure independently predicted vaccine antibody responses, these results support further investigation into microbiota-targeted strategies to optimize infant immune and vaccine responses across diverse populations.
This study 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.
The relationship between periodontitis and Alzheimer's disease (AD) has attracted more attention recently, whereas profiles of subgingival microbiomes and gingival crevicular fluid (GCF) metabolic signatures in AD patients have rarely been characterized; thus, little evidence exists to support the oral-brain axis hypothesis. Therefore, our study aimed to characterize both the microbial community of subgingival plaque and the metabolomic profiles of GCF in patients with AD and amnestic mild cognitive impairment (aMCI) for the first time.
This was a cross-sectional study. Clinical examinations were performed on all participants. The microbial community of subgingival plaque and the metabolomic profiles of GCF were characterized using the 16S ribosomal RNA (rRNA) gene high-throughput sequencing and liquid chromatography linked to tandem mass spectrometry (LC-MS/MS) analysis, respectively.
Thirty-two patients with AD, 32 patients with aMCI, and 32 cognitively normal people were enrolled. The severity of periodontitis was significantly increased in AD patients compared with aMCI patients and cognitively normal people. The 16S rRNA gene sequencing results showed that the relative abundances of 16 species in subgingival plaque were significantly correlated with cognitive function, and LC-MS/MS analysis identified a total of 165 differentially abundant metabolites in GCF. Moreover, multiomics Data Integration Analysis for Biomarker discovery using Latent cOmponents (DIABLO) analysis revealed that 19 differentially abundant metabolites were significantly correlated with Veillonella parvula, Dialister pneumosintes, Leptotrichia buccalis, Pseudoleptotrichia goodfellowii, and Actinomyces massiliensis, in which galactinol, sn-glycerol 3-phosphoethanolamine, D-mannitol, 1 h-indole-1-pentanoic acid, 3-(1-naphthalenylcarbonyl)- and L-iditol yielded satisfactory accuracy for the predictive diagnosis of AD progression.
This is the first combined subgingival microbiome and GCF metabolome study in patients with AD and aMCI, which revealed that periodontal microbial dysbiosis and metabolic disorders may be involved in the etiology and progression of AD, and the differential abundance of the microbiota and metabolites may be useful as potential markers for AD in the future.
Although the pathology of multiple chemical sensitivity (MCS) is unknown, the central nervous system is reportedly involved. The gut microbiota is important in modifying central nervous system diseases. However, the relationship between the gut microbiota and MCS remains unclear. This study aimed to identify gut microbiota variations associated with MCS using shotgun metagenomic sequencing of fecal samples.
We prospectively recruited 30 consecutive Japanese female patients with MCS and analyzed their gut microbiomes using shotgun metagenomic sequencing. The data were compared with metagenomic data obtained from 24 age- and sex-matched Japanese healthy controls (HC).
We observed no significant difference in alpha and beta diversity of the gut microbiota between the MCS patients and HC. Focusing on the important changes in the literatures, at the genus level, Streptococcus, Veillonella, and Akkermansia were significantly more abundant in MCS patients than in HC (p < 0.01, p < 0.01, p = 0.01, respectively, fold change = 4.03, 1.53, 2.86, respectively). At the species level, Akkermansia muciniphila was significantly more abundant (p = 0.02, fold change = 3.3) and Faecalibacterium prausnitzii significantly less abundant in MCS patients than in HC (p = 0.03, fold change = 0.53). Functional analysis revealed that xylene and dioxin degradation pathways were significantly enriched (p < 0.01, p = 0.01, respectively, fold change = 1.54, 1.46, respectively), whereas pathways involved in amino acid metabolism and synthesis were significantly depleted in MCS (p < 0.01, fold change = 0.96). Pathways related to antimicrobial resistance, including the two-component system and cationic antimicrobial peptide resistance, were also significantly enriched in MCS (p < 0.01, p < 0.01, respectively, fold change = 1.1, 1.2, respectively).
The gut microbiota of patients with MCS shows dysbiosis and alterations in bacterial functions related to exogenous chemicals and amino acid metabolism and synthesis. These findings may contribute to the further development of treatment for MCS.
Metabolic associated fatty liver disease (MAFLD) is a novel concept proposed in 2020, which is more practical for identifying patients with fatty liver disease with high risk of disease progression. Fatty liver is a driver for extrahepatic complications, particularly cardiovascular diseases (CVD). Although the risk of CVD in MAFLD could be predicted by carotid ultrasound test, a very early stage prediction method before the formation of pathological damage is still lacking.
Stool microbiomes and plasma metabolites were compared across 196 well-characterized participants encompassing normal controls, simple MAFLD patients, MAFLD patients with carotid artery pathological changes, and MAFLD patients with diagnosed coronary artery disease (CAD). 16S rDNA sequencing data and untargeted metabolomic profiles were interrogatively analyzed using differential abundance analysis and random forest (RF) machine learning algorithm to identify discriminatory gut microbiomes and metabolomic.
Characteristic microbial changes in MAFLD patients with CVD risk were represented by the increase of Clostridia and Firmicutes-to-Bacteroidetes ratios. Faecalibacterium was negatively correlated with mean-intima-media thickness (IMT), TC, and TG. Megamonas, Bacteroides, Parabacteroides, and Escherichia were positively correlated with the exacerbation of pathological indexes. MAFLD patients with CVD risk were characterized by the decrease of lithocholic acid taurine conjugate, and the increase of ethylvanillin propylene glycol acetal, both of which had close relationship with Ruminococcus and Gemmiger. Biotin l-sulfoxide had positive correlation with mean-IMT, TG, and weight. The general auxin pesticide beta-naphthoxyacetic acid and the food additive glucosyl steviol were both positively correlated with the increase of mean-IMT. The model combining the metabolite signatures with 9 clinical parameters accurately distinguished MAFLD with CVD risk in the proband and validation cohort. It was found that citral was the most important discriminative metabolite marker, which was validated by both in vitro and in vivo experiments.
Simple MAFLD patients and MAFLD patients with CVD risk had divergent gut microbes and plasma metabolites. The predictive model based on metabolites and 9 clinical parameters could effectively discriminate MAFLD patients with CVD risk at a very early stage.
Bronchiectasis is a condition characterized by abnormal and irreversible bronchial dilation resulting from lung tissue damage and can be categorized into two main groups: cystic fibrosis (CF) and non-CF bronchiectasis (NCFB). Both diseases are marked by recurrent infections, inflammatory exacerbations, and lung damage. Given that infections are the primary drivers of disease progression, characterization of the respiratory microbiome can shed light on compositional alterations and susceptibility to antimicrobial drugs in these cases compared to healthy individuals.
To assess the microbiota in the two studied diseases, 35 subjects were recruited, comprising 10 NCFB and 13 CF patients and 12 healthy individuals. Nasopharyngeal swabs and induced sputum were collected, and total DNA was extracted. The DNA was then sequenced by the shotgun method and evaluated using the SqueezeMeta pipeline and R.
We observed reduced species diversity in both disease cohorts, along with distinct microbial compositions and profiles of antimicrobial resistance genes, compared to healthy individuals. The nasopharynx exhibited a consistent microbiota composition across all cohorts. Enrichment of members of the Burkholderiaceae family and an increased Firmicutes/Bacteroidetes ratio in the CF cohort emerged as key distinguishing factors compared to NCFB group. Staphylococcus aureus and Prevotella shahii also presented differential abundance in the CF and NCFB cohorts, respectively, in the lower respiratory tract. Considering antimicrobial resistance, a high number of genes related to antibiotic efflux were detected in both disease groups, which correlated with the patient's clinical data.
Bronchiectasis is associated with reduced microbial diversity and a shift in microbial and resistome composition compared to healthy subjects. Despite some similarities, CF and NCFB present significant differences in microbiome composition and antimicrobial resistance profiles, suggesting the need for customized management strategies for each disease.
This study examined the gut microbiome's association with type 2 diabetes (T2D) by analyzing shotgun metagenomic sequencing data. Researchers looked beyond species-level associations to strain-level and phylogenetic diversity within species, aiming to identify specific microbial features and functional pathways linked to T2D. The analysis also explored community-level functional changes, such as perturbations in glucose metabolism, and mechanisms like horizontal gene transfer that could explain strain-specific effects on metabolic risk.
The study drew on 8,117 shotgun metagenomes pooled from 10 cohorts spanning the United States, Europe, Israel, and China. These cohorts included individuals with type 2 diabetes, prediabetes, and normoglycemic (non-diabetic) status. The abstract does not provide individual-level demographic details, but the analysis represents a large, multi-national, cross-cohort metagenomic dataset.
Dysbiosis in 19 phylogenetically diverse species was associated with T2D at a false discovery rate below 0.10, including enrichment of Clostridium bolteae and depletion of Butyrivibrio crossotus. These microorganisms contributed to community-level functional changes, such as perturbations in glucose metabolism, that may underlie T2D pathogenesis. The study further identified within-species phylogenetic diversity across 27 species, such as Eubacterium rectale, that explained inter-individual differences in T2D risk, with some effects attributable to strain-specific gene carriage involved in horizontal gene transfer and other novel biological processes.
By resolving microbial associations with T2D down to the strain level, this work helps explain why prior species-level findings have been inconsistent across studies. Identifying strain-specific gene carriage and functional pathways, including those affecting glucose metabolism, offers a clearer mechanistic basis for how gut microbes may contribute to T2D pathogenesis. This strain-resolved approach could inform future efforts to develop microbiome-based biomarkers or targeted interventions for metabolic disease risk.
This study examined how environmental, socioeconomic, and health factors relate to gut microbiome composition at both the species and strain level. Researchers used deeply sequenced metagenomic data to identify associations between bacterial species and a range of host phenotypes and situational factors. They also performed a meta-analysis of species-level profiles across multiple datasets to look for consistent patterns, such as links to body mass index.
The study drew on a community-based cohort of 1,871 people living in 19 isolated villages in the Mesoamerican highlands of western Honduras. This is a non-industrialized, geographically isolated population, a setting the authors note remains uncommon in deep gut microbiome sequencing studies. Additional comparisons were made using species-level profiles from other, unspecified datasets as part of a meta-analysis.
Socioeconomic factors accounted for 51.44% of all associations found between the gut microbiome and human phenotypes, making them the dominant category of influence. Meta-analysis across datasets identified several bacterial species associated with body mass index, consistent with prior research. Incorporating strain-level phylogenetic information changed the overall picture of host-microbiome relationships, especially for factors like household wealth, where wealthier individuals were found to harbor different strains of Eubacterium rectale than less wealthy individuals.
The findings suggest that socioeconomic circumstances are a major driver of gut microbiome variation, potentially more so than many other individual health factors. The demonstration that strain-level differences (not just species presence) track with wealth indicates that species-level analysis alone can miss biologically meaningful variation. The authors conclude that gut microbiome surveillance in such populations could help illuminate broader patterns relevant to both individual and public health.
This study used 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 aimed to compare the gut and oral microbiota composition of professional male football players and amateurs. Environmental and behavioral factors are well known to modulate intestinal microbiota composition. Active lifestyle behaviors are involved in the improvement of metabolic and inflammatory parameters. Exercise promotes adaptational changes in human metabolic capacities affecting microbial homeostasis. Twenty professional football players and twelve amateurs were invited to the study groups. Fecal and oral microbiota were analyzed using next-generation sequencing of the 16S rRNA gene. Diversity in the oral microbiota composition was similar in amateurs and professionals, while the increase in training intensity reduced the number of bacterial species. In contrast, the analysis of the intestinal microbiota showed the greatest differentiation between professional football players and amateurs, especially during intensive training. Firmicutes were characterized by the largest population in all the studied groups. Intensive physical activity increases the abundance of butyrate and succinate-producing bacteria affecting host metabolic homeostasis, suggesting a very beneficial role for the host immune system's microbiome homeostasis and providing a proper function of the host immune system.
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 how exclusive enteral nutrition (EEN), a first-line therapy for pediatric Crohn's disease, produces its protective effects on the gut. The researchers used integrated multi-omics analysis of fecal microbiota and metabolites to identify functional network clusters associated with treatment response. They further validated these diet-driven microbiome changes using gut chemostat cultures and by transferring microbiota into germ-free Il10-deficient mice.
The abstract describes a prospective pediatric cohort of treatment-naive Crohn's disease patients, registered as German Clinical Trials DRKS00013306, who were followed as they began EEN therapy. Exact patient numbers are not given in the abstract. Findings from this human cohort were then extended experimentally using gnotobiotic (germ-free) Il10-deficient mice colonized with patient-derived microbiota.
Multi-omics analysis identified individually variable microbiome network clusters, with Lachnospiraceae and medium-chain fatty acids emerging as protective features associated with EEN response. Bioorthogonal non-canonical amino acid tagging pinpointed specific bacterial species that responded to medium-chain fatty acids, and metagenomic analysis revealed high strain-level dynamics during EEN therapy. When patient-derived microbiota were transferred into gnotobiotic Il10-deficient mice, individual patient-specific strain signatures could either prevent or cause inflammatory bowel disease-like inflammation.
The findings show that EEN operates through explicit, functional, and highly individualized changes in the fecal microbiome rather than a single uniform mechanism. Because protective effects were tied to specific strains and metabolites such as medium-chain fatty acids, this suggests that microbiome and metabolite profiling could help predict or enhance EEN response in pediatric Crohn's disease. The demonstration that individual strain signatures can causally prevent or induce inflammation in a gnotobiotic model also supports strain-level and metabolite-targeted approaches as a path toward more precise dietary or microbial therapies for Crohn's disease.
Fermented foods are becoming more popular due to their purported links to metabolic health and the gut microbiome. However, direct clinical evidence for the health claims is lacking. Here, we describe an eight-week clinical trial that explored the effects of a four-week kombucha supplement in healthy individuals consuming a Western diet, randomized into the kombucha (n = 16) or control (n = 8) group. We collected longitudinal stool and blood samples to profile the human microbiome and inflammation markers. We did not observe significant changes in either biochemical parameters or levels of circulating markers of inflammation across the entire cohort. However, paired analysis between baseline and end of intervention time points within kombucha or control groups revealed increases in fasting insulin and in HOMA-IR in the kombucha group whereas reductions in HDL cholesterol were associated with the control group. Shotgun metagenomic analysis revealed the relative abundance of Weizmannia, a kombucha-enriched probiotic and several SCFA producing taxa to be overrepresented in consumers at the end of the intervention. Collectively, in our healthy cohort consuming a Western diet, a short-term kombucha intervention induced modest impacts on human gut microbiome composition and biochemical parameters, which may be attributed to relatively small number of participants and the extensive inter-participant variability.
Chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) is a rare acquired immune-mediated neuropathy. Although microbial infection is potentially a contributing factor, a causative link between CIDP and microbial infection remains unclear. There is also no definitive biomarker for CIDP diagnostics and therapies. The present study aimed to characterize the serum metabolic profile and gut microbiome structure in CIDP.
Targeted metabolomics profiling of serum, using liquid chromatography-mass spectrometry, and metagenomics sequencing of stool samples from a cohort of CIDP and non-CIDP subjects were performed to evaluate serum metabolic profiles and gut microbiome structure in CIDP subjects relative to healthy controls.
Metabolome data revealed that the bile acids profile was perturbed in CIDP with bile acids and arachidonic acid enriched significantly in CIDP versus non-CIDP controls. Metagenome data revealed that opportunistic pathogens, such as Klebsiella pneumonia and Megamonas funiformis, and genes involved in bacterial infection were notably more abundant in CIDP subjects, while gut microbes related to biotransformation of secondary bile acids were abnormal in CIDP versus non-CIDP subjects. Correlation analysis revealed that changes in secondary bile acids were associated with altered gut microbes, including Bacteroides ovatus, Bacteroides caccae, and Ruminococcus gnavus.
Bile acids and arachidonic acid metabolism were disturbed in CIDP subjects and might be affected by the dysbiosis of gut microbial flora. These findings suggest that the combination of bile acids and arachidonic acid could be used as a CIDP biomarker and that modulation of gut microbiota might impact the clinical course of CIDP.
This study examined the gut microbiome of patients with Peutz-Jeghers syndrome (PJS), a rare hereditary disorder marked by intestinal polyposis and a high risk of intussusception. Researchers used 16S rRNA sequencing to characterize overall microbiome composition and metagenomic sequencing on a subset of samples to assess functional pathway changes. The goal was to determine whether gut microbiota imbalance is associated with PJS and, specifically, with the complication of intussusception.
Stool samples were collected from 168 patients with PJS and 68 healthy family members who lived in the same household. For the deeper metagenomic functional analysis, a representative subset of 61 PJS patients and 27 healthy family members was used. Using cohabitating relatives as controls helps account for shared diet and environment.
The fecal microbiome of PJS patients showed greater variation in beta-diversity compared with healthy family members. PJS patients had an enhancement of Escherichia coli and a reduction of Faecalibacterium prausnitzii, an anti-inflammatory, butyrate-associated commensal. Among PJS patients, those with intussusception showed a further reduction in Faecalibacterium prausnitzii, marking it as a distinguishing microbial feature of this complication. Functional analysis found propanoate metabolism enriched in PJS patients overall and further enriched in those with intussusception, with Escherichia coli identified as the major contributor to this pathway.
These findings suggest gut microbiome imbalance, particularly loss of Faecalibacterium prausnitzii and expansion of Escherichia coli, may play a role in PJS pathogenesis and specifically in the development of intussusception. The progressive depletion of this anti-inflammatory commensal alongside enriched propanoate metabolism points to a possible microbial signature that could help identify PJS patients at greater risk for this complication. This raises the possibility that restoring depleted commensals or targeting E. coli-driven metabolic pathways could be explored as future strategies, though the abstract does not report interventional data.
This study 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 examined the gut microbiota landscape of patients with diffuse large B-cell lymphoma (DLBCL) and its relationship to peripheral blood immune cell subtypes. Researchers used metagenomic sequencing to characterize gut bacterial composition and full-spectral flow cytometry to profile immune cell subsets. The goal was to identify microbiota and immune features that differ across NCCN-International Prognostic Index (NCCN-IPI) risk categories, since the gut microbe landscape in DLBCL and its link to immunity had remained largely unknown.
A total of 87 newly diagnosed adult DLBCL patients were enrolled and had peripheral blood samples collected for immune cell subtyping. Of these, 69 of the 87 patients also had stool or tumor-associated samples submitted for metagenomic sequencing to assess microbiota composition. Patients were grouped according to NCCN-IPI risk categories: low-risk, low-intermediate-risk, intermediate-high-risk, and high-risk.
Metagenomic sequencing identified 10 bacterial phyla, 31 orders, and 455 bacterial species across the 69 profiled DLBCL patients. Six bacteria showed abundance differences of note, including Blautia sp. CAG 257, Actinomyces sp. S6 Spd3, Streptococcus parasanguinis, Bacteroides salyersiae, and Enterococcus faecalis. The abstract does not mention Bacteroides fragilis, polysaccharide A, or the B. fragilis toxin, so this study's findings center on other bacterial taxa and their association with NCCN-IPI risk groups and peripheral immune cell subsets.
By linking specific gut bacterial abundances to NCCN-IPI prognostic risk groups and peripheral immune cell subtypes, this work suggests the gut microbiome may play a role in shaping immune status and disease risk stratification in DLBCL. These integrated microbiome-immune signatures could eventually inform prognostic tools or risk-adapted monitoring for newly diagnosed patients. Further validation would be needed before such microbiota features could guide clinical decision-making in lymphoma care.
This study examined the gut microbiome in Parkinson's disease (PD) using shotgun metagenomic sequencing, a method that captures microbial functional potential rather than taxonomy alone. The researchers designed a nested case-control study to investigate both recently onset PD and prodromal (premotor) PD, a stage that prior microbiome research had largely overlooked. They analyzed fecal metagenomes to identify bacterial species and metabolic pathways associated with PD and with features suggestive of the prodromal phase.
The study drew on 420 participants nested within two large epidemiological cohorts, the Nurses' Health Study and the Health Professionals Follow-up Study. This included 75 people with recently onset PD, 101 with features of prodromal PD, 113 controls with constipation, and 131 healthy controls. The design allowed comparison across a spectrum from prodromal symptoms through diagnosed disease against two distinct control groups.
Participants with PD or features of prodromal PD showed depletion of several strict anaerobes, bacteria types that the abstract links to reduced inflammation. A microbiome-based classifier achieved moderate accuracy in distinguishing recently onset PD cases from controls, with an area under the curve of 0.76 based on species composition and 0.74 based on functional pathways. These taxonomic changes were accompanied by corresponding functional shifts in the metagenome, indicating that both which microbes are present and what they metabolically do differ in PD.
By identifying microbial changes already present in prodromal, premotor PD, this study suggests gut microbiome alterations may precede or accompany the earliest detectable stages of disease rather than only appearing after motor symptoms emerge. The depletion of anaerobes associated with reduced inflammation points toward loss of anti-inflammatory microbial function as a feature of the disease process. The moderate classifier accuracy suggests gut metagenomic profiles could eventually contribute to tools for identifying at-risk individuals, though the abstract does not claim diagnostic readiness.
This study 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.
Since the coronavirus disease 2019 (COVID-19) outbreak, many COVID-19 variants have emerged, causing several waves of pandemics and many infections. Long COVID-19, or long-term sequelae after recovery from COVID-19, has aroused worldwide concern because it reduces patient quality of life after rehabilitation. We aimed to characterize the functional differential profile of the oral and gut microbiomes and serum metabolites in patients with gastrointestinal symptoms associated with long COVID-19.
We prospectively collected oral, fecal, and serum samples from 983 antibiotic-naïve patients with mild COVID-19 and performed a 3-month follow-up postdischarge. Forty-five fecal and saliva samples, and 25 paired serum samples were collected from patients with gastrointestinal symptoms of long COVID-19 at follow-up and from healthy controls, respectively. Eight fecal and saliva samples were collected without gastrointestinal symptoms of long COVID-19 at follow-up. Shotgun metagenomic sequencing of fecal samples and 2bRAD-M sequencing of saliva samples were performed on these paired samples. Two published COVID-19 gut microbiota cohorts were analyzed for comparison. Paired serum samples were analyzed using widely targeted metabolomics.
Mild COVID-19 patients without gastrointestinal symptoms of long COVID-19 showed little difference in the gut and oral microbiota during hospitalization and at follow-up from healthy controls. The baseline and 3-month samples collected from patients with gastrointestinal symptoms associated with long COVID-19 showed significant differences, and ectopic colonization of the oral cavity by gut microbes including 27 common differentially abundant genera in the Proteobacteria phylum, was observed at the 3-month timepoint. Some of these bacteria, including Neisseria, Lautropia, and Agrobacterium, were highly related to differentially expressed serum metabolites with potential toxicity, such as 4-chlorophenylacetic acid, 5-sulfoxymethylfurfural, and estradiol valerate.
Our study characterized the changes in and correlations between the oral and gut microbiomes and serum metabolites in patients with gastrointestinal symptoms associated with long COVID-19. Additionally, our findings reveal that ectopically colonized bacteria from the gut to the oral cavity could exist in long COVID-19 patients with gastrointestinal symptoms, with a strong correlation to some potential harmful metabolites in serum.
Treating oral squamous cell carcinoma (OSCC) introduces new ecological environments in the oral cavity. This is expected to cause changes in the oral microbiome. The purpose of this study was to gain new information on the salivary microbiome of OSCC patients in order to improve the aftercare of OSCC patients. The aims of this study were to investigate possible changes in the salivary microbiome profiles of OSCC patients before and after cancer treatment and to compare these changes with the profiles of healthy controls.
Paraffin-stimulated whole saliva samples were collected, and the salivary flow rate was measured from 99 OSCC patients prior to surgical resection of the tumor and other adjuvant therapy. After treatment, 28 OSCC patients were re-examined with a mean follow-up time of 48 months. In addition, 101 healthy controls were examined and sampled. After DNA extraction and purification, the V4 hypervariable region of the 16S rRNA gene was amplified and sequenced using Illumina MiSeq. The merged read pairs were denoised using UNOISE3, mapped to zero-radius operational taxonomic units (zOTUs), and the representative zOTU sequences were assigned a taxonomy using HOMD. Descriptive statistics were used to study the differences in the microbial profiles of OSCC patients before and after treatment and in comparison to healthy controls.
At baseline, the OSCC patients showed a higher relative abundance of zOTUs classified as Streptococcus anginosus, Abiotrophia defectiva, and Fusobacterium nucleatum. The microbial profiles differed significantly between OSCC patients and healthy controls (F = 5.9, p < 0.001). Alpha diversity of the salivary microbiome of OSCC patients was decreased at the follow-up, and the microbial profiles differed significantly from the pre-treatment (p < 0.001) and from that of healthy controls (p < 0.001).
OSCC patients' salivary microbiome profile had a higher abundance of potentially pathogenic bacteria compared to healthy controls. Treatment of the OSCC caused a significant decrease in alpha diversity and increase in variability of the salivary microbiome, which was still evident after several years of follow-up. OSCC patients may benefit from preventive measures, such as the use of pre- or probiotics, salivary substitutes, or dietary counseling. Video Abstract.
This study examined how the gut microbiota changes with age and how those age-related changes relate to colorectal cancer (CRC). The researchers analyzed 11 metagenomic data sets, correcting for batch effects, then compared species composition and abundance across three age groups in both healthy individuals and CRC samples. They used LEfSe analysis to identify bacteria whose relative abundance differed by age group, then built age-prediction and CRC-risk-prediction models from those age-differentiated species.
The abstract does not report a single original cohort with a specific sample size. Instead, the study population consisted of previously published metagenomic samples drawn from 11 combined data sets accessed through the curatedMetagenomicData R package, covering both healthy individuals and people with colorectal cancer. These samples were stratified into three age groups for comparison.
The structure and composition of the gut microbiota differed significantly across the three age groups in both healthy and CRC samples. Bacteroides vulgatus abundance was lower in the older group compared to the other two groups, while Bacteroides fragilis abundance increased with aging. The researchers also identified seven bacterial species whose abundance rose with age, and found that abundance of pathogenic bacteria, including Escherichia coli, increased as well.
By linking specific age-associated shifts in gut microbiota, such as declining Bacteroides vulgatus and rising Bacteroides fragilis and Escherichia coli, to both healthy aging and CRC samples, this work suggests the microbiome could serve as a biomarker for biological aging and CRC risk. The construction of age-prediction and CRC-risk-prediction models based on these age-differentiated bacteria points toward potential microbiota-based tools for estimating cancer risk as people age. This approach could inform future screening or risk-stratification strategies that account for age-related microbial changes.
This study examined the oral (saliva) microbiome composition of diverse human populations from southwestern Angola and Zimbabwe. It used the non-human sequencing reads recovered from an expanded exome capture approach, repurposing genomic data to characterize salivary bacterial communities. The aim was to add southern African, non-industrialized populations to the global picture of oral microbiome composition and diversity, which remains poorly understood on a broad scale.
The sample comprised 52 individuals drawn from eight ethnolinguistically diverse southern African populations. These included the Kuvale, Kwepe, Himba, Tjimba, Kwisi, Twa, and !Xun from Angola, and the Tshwa from Zimbabwe. The groups represented a range of subsistence strategies, including foragers, food-producers, and peripatetic communities that provide services to dominant neighboring groups.
Neisseria, Streptococcus, Prevotella, Rothia, and Porphyromonas were the five most frequent genera across all southern African groups, consistent with patterns reported in other human populations worldwide. Neither host genetics nor livelihood strategy appeared to shape the overall oral microbiome profile, pointing to a broadly homogeneous core community. However, some individuals from the Tshwa and Twa forager groups showed an enrichment of pathogenic genera belonging to the Enterobacteriaceae family, a family that includes Salmonella and other clinically relevant organisms.
The findings suggest that the human oral microbiome maintains a stable, homogeneous core composition across ethnolinguistically and subsistence-diverse populations, independent of genetic ancestry or lifestyle. This supports the idea that core oral genera are a conserved feature of human biology rather than a product of industrialization or diet alone. The localized enrichment of pathogenic Enterobacteriaceae in specific forager subgroups also highlights that certain communities may carry distinct risks worth further investigation in relation to oral and systemic health.
This study aimed to investigate alterations in the gut microbiota of patients with depression compared to those in the gut microbiota of healthy individuals based on enterotypes as a classification framework. Fecal bacteria FASTA/Q samples from 333 Chinese participants, including 107 healthy individuals (Healthy group) and 226 individuals suffering from depression (DP group), were analyzed. The participants were classified into three enterotypes: Bacteroidaceae (ET-B), Lachnospiraceae (ET-L), and Prevotellaceae (ET-P). An α-diversity analysis revealed no significant differences in microbial diversity between the Healthy and DP groups across all enterotypes. However, there were substantial differences in the gut microbial composition for β-diversity, particularly within ET-L and ET-B. The DP group within ET-B exhibited a higher abundance of Proteobacteria, while a linear discriminant analysis (LDA) of the DP group showed an increased relative abundance of specific genera, such as Mediterraneibacter, Blautia, Bifidobacterium, and Clostridium. Within ET-L, Bifidobacterium, Blautia, Clostridium, Collinsella, and Corynebacterium were significantly higher in the DP group in the LDA and ANOVA-like differential expression-2 (ALDEx2) analyses. At the species level of ET-L, Blautia luti, Blautia provencensis, Blautia glucerasea, Clostridium innocuum, Clostridium porci, and Clostridium leptum were the primary bacteria in the DP group identified using the machine learning approach. A network analysis revealed a more tightly interconnected microbial community within ET-L than within ET-B. This suggests a potentially stronger functional relationship among the gut microbiota in ET-L. The metabolic pathways related to glucose metabolism, tryptophan and tyrosine metabolism, neurotransmitter metabolism, and immune-related functions showed strong negative associations with depression, particularly within ET-L. These findings provide insights into the gut-brain axis and its role in the pathogenesis of depression, thus contributing to our understanding of the underlying mechanisms in Asian individuals. Further research is warranted to explain the mechanistic links between gut microbiota and depression and to explore their potential for use in precision medicine interventions.
This study examined whether the gut microbiome differs in young children with airway allergic disease compared with healthy children. Researchers used high-throughput metagenomic shotgun gene sequencing on fecal samples to characterize the gut microbiota at both the phylum and genus levels. The goal was to identify unique gut microbial features associated with allergic asthma and allergic rhinitis in children.
The study included three groups of children: those with allergic asthma (n = 23), those with allergic rhinitis (n = 18), and healthy controls (n = 19). Fecal samples were collected from each child for shotgun metagenomic analysis. No further demographic details, such as age range or geographic location, are given in the abstract.
Children with allergic asthma and allergic rhinitis showed increased gut microbial richness and diversity compared with healthy controls, with Simpson and Shannon diversity indices significantly elevated in the asthma group. Principal coordinates analysis showed that gut microbial community clustering in both allergic groups differed significantly from healthy controls, though asthma and rhinitis groups did not differ significantly from each other. At the phylum level, Firmicutes was enriched and Bacteroidetes was reduced in both allergic groups, while at the genus level Corynebacterium, Streptococcus, Dorea, Actinomyces, Bifidobacterium, Blautia, and Rothia were significantly enriched in the allergic children. The abstract does not mention Candida, fungi, yeast, or the mycobiome.
The findings support a link between gut microbiome composition and airway allergic disease in children, suggesting the gut-lung axis may play a role in asthma and rhinitis development. The shared microbial alterations across asthma and rhinitis groups suggest a common underlying gut dysbiosis pattern rather than disease-specific signatures. These bacterial taxa could serve as candidate biomarkers or targets for future microbiome-directed strategies in pediatric airway allergic disease, pending further mechanistic and validation studies.
The study characterized the upper respiratory tract (URT) microbiome, meaning the combined nasal and oral bacterial communities, in patients infected with the SARS-CoV-2 Delta versus Omicron variant compared with healthy controls. The authors aimed to identify variant-specific microbiome signatures, since prior work had compared COVID-19 patients to controls but had not examined how distinct variants shape the URT microbiome.
The cohort comprised 43 COVID-19 patients (24 Delta and 19 Omicron) and 19 healthy controls from Eastern India, with samples collected in 2021 to 2022 (average age about 36 years in patients and 33 in controls). URT swabs were profiled by next-generation sequencing of the V3 to V4 variable regions of the 16S rRNA gene on the Illumina NovaSeq 6000 platform, yielding 12,172 amplicon sequence variants across 34 phyla, 924 genera, and 1,429 species.
COVID-19 patients showed significantly lower intra-individual (alpha) diversity and higher inter-individual (beta) diversity than controls, with Proteobacteria dominant in patients (73.57 percent versus 22.24 percent) and genera such as Pseudomonas, Klebsiella, Enterobacter, and Acinetobacter enriched, while control-associated commensals including Streptococcus, Veillonella, Prevotella, Neisseria, and Bifidobacterium were depleted. Delta patients had lower diversity and greater dysbiosis than Omicron patients, and nine control-associated species declined in a consistent trend of control greater than Omicron greater than Delta. A random forest classifier built on core species distinguished the three groups with roughly 90 percent (plus or minus 0.5 percent) accuracy (class error 0 percent for controls, 18 percent for Omicron, 14 percent for Delta).
The authors conclude that different SARS-CoV-2 variants are associated with variant-specific URT microbiome signatures, with the newer Omicron variant more closely resembling the healthy control microbiome than the older Delta variant, which may inform host-microbiome interaction research and future nasal probiotic strategies. Because this is an observational, cross-sectional comparison in a modest sample, the results reflect association rather than causation and, as the authors note, sample size is a limitation.
This study examined whether the gut microbiome could be used to differentiate and diagnose Crohn's disease (CD) and ulcerative colitis (UC), the two major forms of inflammatory bowel disease (IBD). Researchers compared the abundance and composition of gut microbiota across disease states and looked for specific biomarkers linked to disease activity. The work also examined how microbial diversity changed as disease progressed through different stages.
The abstract describes patients with IBD, split into CD and UC groups, compared against healthy controls (HC). Specific numbers of participants, demographics, and enrollment details are not given in the abstract, so the exact cohort size and characteristics cannot be stated. The comparison design (IBD patients versus healthy controls, with CD and UC analyzed separately) is the only population detail confirmed.
Gut microbiome diversity was lower in IBD patients than in healthy controls, and this reduction was significantly more pronounced in CD patients. The researchers identified 68 microbiota members associated with these diseases, 28 linked to CD and 40 linked to UC. Microbial diversity also declined further as disease progressed through more advanced stages. Specific taxa tracked with severity: Alistipes shahii and Pseudodesulfovibrio aespoeensis abundances were negatively correlated with CD severity, while Polynucleobacter wianus abundance was positively associated with it.
These findings suggest the gut microbiome could serve as a diagnostic tool to distinguish CD from UC, addressing a clinically difficult differential diagnosis. Identifying species whose abundance correlates with disease severity points toward potential microbial biomarkers for monitoring disease activity and staging. Such biomarkers could support more precise, long-term treatment planning for IBD patients.
While oral mirobial dysbiosis due to tobacco smoking has been studied thoroughly, there is limited data on the effect of waterpipe smoking on the oral microbiome. This study aims to compare the salivary microbiome between waterpipe smokers and non-smokers.
Unstimulated saliva samples were collected from 60 participants, 30 smokers and 30 non-smokers in Kuala Lumpur and Klang Valley, Malaysia. DNA extraction was performed using the Qiagen DNA mini kit, and the 16S rRNA bacterial gene was amplified and sequenced using the Illumina MiSeq platform. Sequencing reads were processed using DADA2, and the alpha and beta diversity of the bacterial community was assessed. Significantly differentiated taxa were identified using LEfSe analysis, while differentially expressed pathways were identified using MaAsLin2.
A significant compositional change (beta diversity) was detected between the two groups (PERMANOVA P < 0.05). Specifically, the levels of phylum Firmicutes and genus Streptococcus were elevated in smokers, whereas phylum Proteobacteria and genus Haemophilus were depleted compared to non-smokers. At the species level, Streptococcus oralis, Streptococcus salivarius, and Streptococcus gingivalis were enriched in smokers. We observed significant differences in the abundance of thirty-seven microbial metabolic pathways between waterpipe smokers and non-smokers. The microbial pathways enriched in smokers were those implicated in polymer degradation and amino acid metabolism.
The taxonomic and metabolic profile of the salivary microbiome in waterpipe smokers compared to healthy controls exhibited a paradigm shift, thus, implying an alteration in the homeostatic balance of the oral cavity posing unique challenges for oral health.
This study investigated whether gut bacteria that produce endogenous ethanol contribute to nonalcoholic steatohepatitis (NASH). Researchers measured fecal ethanol, glucose, total proteins, triglyceride and total cholesterol using high-performance liquid chromatography. They also characterized the gut microbiota using microbial culturomics and 16S rRNA metagenomics targeting the V3V4 hypervariable region to identify which viable bacteria and genetic signatures were enriched in NASH.
The study compared fecal samples from 41 patients with NASH to 24 controls without the disease. This case-control design allowed direct comparison of biochemical parameters and microbial composition between diseased and healthy states. No further demographic details are given in the abstract.
Fecal ethanol and glucose were significantly elevated in NASH patients compared to controls, while triglyceride, total cholesterol and total protein levels did not differ. Culturomics identified enrichment of the ethanol-producing bacteria Enterocloster bolteae and Limosilactobacillus fermentum in NASH samples. 16S rRNA sequencing confirmed enrichment of ethanol-producing bacteria including L. fermentum, corroborating the culture-based findings with independent genetic evidence.
The findings support endogenous ethanol production by specific gut bacteria as a plausible mechanistic contributor to NASH, independent of dietary alcohol intake. By combining culturomics with 16S metagenomics, the study strengthens the case that microbially derived ethanol, rather than only enterobacteria or yeasts previously implicated, may drive liver injury in NASH. This suggests ethanol-producing bacteria such as L. fermentum and E. bolteae could become targets for diagnostic or therapeutic strategies aimed at reducing hepatic damage in NASH patients.
This study used metagenomic shotgun sequencing to characterize the oral microbiota, antibiotic resistance genes (ARGs), and virulence genes (VirGs) associated with periodontitis. The researchers examined shifts in microbial community composition and functional pathways in periodontitis compared with controls. They also analyzed selection pressure on ARGs and VirGs using the Ka/Ks ratio to determine whether these genes were being positively selected in the oral microbiome.
The abstract describes periodontitis patients compared with control subjects, though it does not specify exact sample sizes or demographic details. The researchers combined their own metagenomic sequencing data with a previously published periodontitis dataset for the gene selection analysis. No cohort age range, geographic origin, or recruitment setting is given in the abstract.
Periodontitis patients showed a significant shift in oral microbiota composition along with several functional pathways that were more abundant than in controls. Several ARGs and VirGs showed evidence of positive selection (Ka/Ks ratio greater than 1) across both datasets analyzed. Notably, 5 of 12 positively selected ARGs and VirGs found in periodontitis patients were also present in the genomes of respiratory tract pathogens, and most background VirGs carried non-synonymous mutations consistent with natural selection.
The overlap between positively selected virulence and resistance genes in periodontal bacteria and respiratory pathogens suggests a possible mechanistic link between periodontitis and respiratory infection. This raises the possibility that oral microbial communities could act as a reservoir for genes that enhance virulence or antibiotic resistance in distant infection sites. The findings support closer surveillance of oral microbiota as a factor in respiratory disease risk and antibiotic resistance spread, though further studies are needed to establish causality.
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 the active (transcriptionally expressed) lung microbiota of COVID-19 patients using metatranscriptomic data from bronchoalveolar lavage fluid (BALF). The researchers analyzed bacterial microbiota and virome composition to determine whether SARS-CoV-2 infection alters the lung microbial landscape. They assessed alpha-diversity, beta-diversity, and species composition to characterize dysbiosis associated with infection.
The analysis drew on BALF metatranscriptomic data from 19 COVID-19 patients and 23 healthy controls. These samples came from 6 independent projects, indicating a pooled, multi-cohort secondary analysis of existing sequencing data rather than a newly recruited single-site cohort. No further demographic details are given in the abstract.
SARS-CoV-2 infection substantially altered lung microbiota, as shown by shifts in alpha-diversity, beta-diversity, and species composition between groups. The COVID-19 group showed enrichment of pathogens such as Klebsiella oxytoca, immunomodulatory probiotics including lactic acid bacteria and Faecalibacterium prausnitzii (a butyrate producer), and Tobacco mosaic virus (TMV), together indicating severe microbiota dysbiosis. A significant correlation among Rothia mucilaginosa, TMV, and SARS-CoV-2 pointed to intense inflammatory interactions among host, virus, and other microbes in the lungs.
The findings suggest that COVID-19 involves not just SARS-CoV-2 alone but a broader disruption of the active lung microbial community, including bacteria and viruses beyond the primary pathogen. The unexpected enrichment of the butyrate producer Faecalibacterium prausnitzii alongside pathogens highlights that dysbiosis in this context is complex rather than a simple loss of beneficial microbes. Tracking active microbiota and virome members like TMV and Rothia mucilaginosa may help explain inflammatory complications of COVID-19 and could inform future study of lung microbial contributions to disease severity.
This study examined how delivery mode shapes the early gut microbiota of newborns using high-resolution shotgun sequencing. Researchers tracked the composition and dynamics of the neonatal gut microbiome over the first month of life. The design specifically compared elective cesarean section against vaginal delivery to sidestep the confounding effect of emergency cesareans, which can muddy conclusions about delivery mode's true influence.
The cohort consisted of Tunisian newborns, with stool samples collected from 5 infants born by elective cesarean section and 5 born vaginally. Samples were taken longitudinally at Day 0, Day 15, and Day 30 after birth. This is a small, delivery-mode-stratified newborn cohort rather than a large population sample.
Bacterial richness and diversity were similar between the elective cesarean and vaginally delivered groups, and both showed a shift in microbiota community composition during the first two weeks regardless of delivery mode. Both groups were dominated by Proteobacteria, Actinobacteria, and Firmicutes. However, starting from the second week, cesarean-delivered infants showed an underrepresentation of Bacteroides alongside an enrichment of opportunistic pathogenic species belonging to the ESKAPE group.
The findings suggest that even elective, non-emergency cesarean delivery is associated with a distinct early gut microbiota signature marked by Bacteroides depletion and ESKAPE pathogen enrichment, not merely overall diversity differences. This points to delivery mode as an independent driver of neonatal microbiome composition beyond confounding clinical circumstances. The emergence of opportunistic ESKAPE species by two weeks of age raises questions about potential vulnerability to opportunistic infection in cesarean-born infants that merit further, larger-scale investigation.
This scoping review examined the human gut microbiota and its relation to glucose metabolism, insulin resistance, and type 2 diabetes risk. The authors searched PubMed and screened 5983 records down to 45 original observational studies. They focused on identifying key bacterial taxa associated with markers and stages of glucose dysregulation, independent of overweight, obesity, and metabolic drugs. The review also considered the potential mediating role of short-chain fatty acids (SCFAs) and the influence of diet and diet-microbiota derived metabolites.
The review drew on human observational studies conducted in healthy adults as well as adults with metabolic disease and associated risk factors. Rather than a single cohort, the evidence base was pooled across 45 separate original studies identified from the PubMed literature. Specific sample sizes or demographic details for individual cohorts are not given in the abstract.
Across the reviewed studies, alpha diversity and 45 distinct bacterial taxa were associated with glucose metabolism outcomes. Six taxa emerged as most frequently linked to glucose metabolism, including Akkermansia muciniphila, Bifidobacterium longum, the Clostridium leptum group, and Faecalibacterium prausnitzii. The authors present evidence supporting SCFAs as a mechanism that may mediate the relationship between these gut bacteria and glucose regulation. Diet and microbiota-derived metabolites are also highlighted as relevant contributors to these associations.
Identifying specific gut bacteria, including SCFA-associated and anti-inflammatory commensals such as Faecalibacterium prausnitzii, consistently linked to glucose metabolism could open new avenues for type 2 diabetes prevention. Because these associations were found independent of obesity and metabolic drug use, the gut microbiota may represent an independent target for intervention. The proposed role of SCFAs and diet-derived metabolites suggests that dietary strategies aimed at shaping the microbiota could be a practical entry point for future prevention efforts. Overall, the findings support further mechanistic and interventional research into these key taxa and their metabolic products.
Down syndrome (DS), a most frequently occurring genetic disorder, is associated with oral morphological abnormalities and higher incidence rates of oral diseases. Recent studies have analyzed the oral microbiome to elucidate their relationships with oral diseases and general health; however, reports on the oral microbiome in individuals with DS are scarce. This study aimed to characterize the oral microbiome in children with DS.
A total of 54 children aged 1-13 years were enrolled in this case-control study. Of these children, 27 had DS (Case: DS group) and 27 were age-matched healthy children (Control: ND group). Saliva in the oral cavity was collected with a swab, cultured, and tested for cariogenic and periodontopathic bacteria by quantitative polymerase chain reaction (qPCR) detection, and the salivary microbiome was analyzed using next-generation sequencing. The student's t-test, Fisher's exact test, Mann-Whitney U test, and permutational multivariate analysis of variance were used for statistical analysis.
Results of culture and qPCR detection tests for cariogenic and periodontopathic bacteria showed no significant differences in the detected bacteria between the DS and ND groups, with the exception of a significantly higher detection rate of Candida albicans in children with DS with mixed dentition. A comparison of the salivary microbiomes by 16S sequencing showed no significant difference in α diversity; however, it showed a significant difference in β diversity. Children with DS had a higher relative abundance of Corynebacterium and Cardiobacterium, and lower relative abundance of TM7.
This study provided basic data on the salivary microbiome of children with DS and showed the microbiological markers peculiar to children with DS. However, further research to identify the relationship with oral diseases is warranted.
The purpose of this study was to compare the microbial composition of 3 types of oral samples through 16S metagenomic sequencing to determine how to resolve some sampling issues that occur during the collection of sub-gingival plaque samples.
In total, 20 subjects were recruited. In both the healthy and periodontitis groups, samples of saliva and supra-gingival plaque were collected. Additionally, in the periodontitis group, sub-gingival plaque samples were collected from the deepest periodontal pocket. After DNA extraction from each sample, polymerase chain reaction amplification was performed on the V3-V4 hypervariable region on the 16S rRNA gene, followed by metagenomic sequencing and a bioinformatics analysis.
When comparing the healthy and periodontitis groups in terms of alpha-diversity, the saliva samples demonstrated much more substantial differences in bacterial diversity than the supra-gingival plaque samples. Moreover, in a comparison between the samples in the case group, the diversity score of the saliva samples was higher than that of the supra-gingival plaque samples, and it was similar to that of the sub-gingival plaque samples. In the beta-diversity analysis, the sub-gingival plaque samples exhibited a clustering pattern similar to that of the periodontitis group. Bacterial relative abundance analysis at the species level indicated lower relative frequencies of bacteria in the healthy group than in the periodontitis group. A statistically significant difference in frequency was observed in the saliva samples for specific pathogenic species (Porphyromonas gingivalis, Treponema denticola, and Prevotella intermedia). The saliva samples exhibited a similar relative richness of bacterial communities to that of sub-gingival plaque samples.
In this 16S oral microbiome study, we confirmed that saliva samples had a microbial composition that was more similar to that of sub-gingival plaque samples than to that of supra-gingival plaque samples within the periodontitis group.
The application of clinical mNGS for diagnosing respiratory infections improves etiology diagnosis, however at the same time, it brings new challenges as an unbiased sequencing method informing all identified microbiomes in the specimen.
Strategy evaluation and metagenomic analysis were performed for the mNGS data generated between March 2017 and October 2019. Diagnostic strengths of four specimen types were assessed to pinpoint the more appropriate type for mNGS diagnosis of respiratory infections. Microbiome complexity was revealed between patient cohorts and infection types. A bioinformatic pipeline resembling diagnosis results was built based upon multiple bioinformatic parameters.
The positive predictive values (PPVs) for mNGS diagnosing of non-mycobacterium, Nontuberculous Mycobacteria (NTM), and Aspergillus were obviously higher in bronchoalveolar lavage fluid (BALF) demonstrating the potency of BALF in mNGS diagnosis. Lung tissues and sputum were acceptable for diagnosis of the Mycobacterium tuberculosis (MTB) infections. Interestingly, significant taxonomy differences were identified in sufficient BALF specimens, and unique bacteriome and virome compositions were found in the BALF specimens of tumor patients. Our pipeline showed comparative diagnostic strength with the clinical microbiological diagnosis.
To achieve reliable mNGS diagnosis result, BALF specimens for suspicious common infections, and lung tissues and sputum for doubtful MTB infections are recommended to avoid the false results given by the complexed respiratory microbiomes. Our developed bioinformatic pipeline successful helps mNGS data interpretation and reduces manual corrections for etiology diagnosis.
Intra-continentally, vaginal microbiome signatures are reported to be significantly different between Black and Caucasian women, with women of African ancestry having the less well defined heterogenous bacterial community state type (CST) deficient of Lactobacillus species (CST IV). The objective of this study was to characterize the vaginal microbiomes across a more diverse intercontinental group of women (N = 151) of different ethnicities (African American, African Kenyan, Afro-Caribbean, Asian Indonesian and Caucasian German) using 16S rRNA gene sequence analysis to determine their structures and offer a comprehensive description of the non-Lactobacillus dominant CSTs and subtypes.
In this study, the bacterial composition of the vaginal microbiomes differed significantly among the ethnic groups. Lactobacillus spp. (L. crispatus and L. iners) dominated the vaginal microbiomes in African American women (91.8%) compared to European (German, 42.4%), Asian (Indonesian, 45.0%), African (Kenyan, 34.4%) and Afro-Caribbean (26.1%) women. Expanding on CST classification, three subtypes of CST IV (CST IV-A, IV-B and IV-C) (N = 56, 37.1%) and four additional CSTs were described: CST VI Gardnerella vaginalis-dominant (N = 6, 21.8%); CST VII (Prevotella-dominant, N = 1, 0.66%); CST VIII (N = 9, 5.96%), resembling aerobic vaginitis, was differentiated by a high proportion of taxa such as Enterococcus, Streptococcus and Staphylococcus (relative abundance [RA] > 50%) and CST IX (N = 7, 4.64%) dominated by genera other than Lactobacillus, Gardnerella or Prevotella (e.g., Bifidobacterium breve and Anaerococcus vaginalis). Within the vaginal microbiomes, 32 "taxa with high pathogenic potential" (THPP) were identified. Collectively, THPP (mean RA ~5.24%) negatively correlated (rs = -0.68, p < 2.2e-16) with Lactobacillus species but not significantly with Gardnerella/Prevotella spp. combined (r = -0.13, p = 0.1). However, at the individual level, Mycoplasma hominis exhibited moderate positive correlations with Gardnerella (r = 0.46, p = 2.6e-09) and Prevotella spp. (r = 0.47, p = 1.4e-09).
These findings while supporting the idea that vaginal microbiomes vary with ethnicity, also suggest that CSTs are more wide-ranging and not exclusive to any particular ethnic group. This study offers additional insight into the structure of the vaginal microbiome and contributes to the description and subcategorization of non-Lactobacillus-dominated CSTs.
This study tracked the co-development of gut microbiomes and metabolomes in mothers and their infants, spanning late pregnancy through the infant's first year of life. Researchers used longitudinal multi-omics data to characterize how microbial communities and their metabolic outputs change and interact over this period. A central focus was mobile genetic elements, the segments of DNA that can move between bacterial species, and how they might transfer from mother to infant. The study also examined infant metabolomes and serum cytokine signatures in relation to feeding type.
The study followed a cohort of 70 mother-infant dyads, or pairs, sampled longitudinally from late pregnancy to the infant's first year. Both maternal and infant gut microbiomes and metabolomes were profiled across this timeframe. Infants were also grouped by feeding method, comparing those who received regular formula, extensively hydrolyzed formula, or exclusive breastfeeding. The abstract does not provide further demographic or geographic details about the cohort.
The researchers discovered large-scale interspecies transfer of mobile genetic elements from mothers to infants, many of which carried genes linked to diet-related adaptations. Infant gut metabolomes were less diverse overall than maternal metabolomes, yet they contained hundreds of unique metabolites and microbe-metabolite associations not seen in the mothers. Metabolomes and serum cytokine signatures differed between infants fed regular formula and those exclusively breastfed, while infants fed extensively hydrolyzed formula did not show this same distinction. These findings indicate that infant gut microbial and metabolic development follows its own distinct trajectory rather than simply mirroring the maternal state.
The findings expand the concept of vertical transmission of the gut microbiome beyond the transfer of whole microbial strains to include mobile genetic elements carrying functionally relevant, diet-related genes. This suggests maternal microbiomes can shape infant microbial capabilities through gene transfer even without direct strain colonization. The feeding-related differences in infant metabolomes and cytokine signatures also point to formula composition, particularly the degree of hydrolysis, as a factor that may influence early immune and metabolic development. Together, these insights could inform how maternal and infant gut ecosystems are considered in supporting healthy immune and cognitive development during the perinatal period.
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.
In this study, we compared the oral microbiome of pregnant women without gingivitis (healthy pregnancy) with pregnant women having gingivitis and nonpregnant healthy women to understand how pregnancy modifies the oral microbiome and induces progression to pregnancy gingivitis.
Subgingival plaque samples were collected from Chinese pregnant women with gingivitis (n = 10), healthy pregnant women (n = 10), and nonpregnant healthy women (n = 10). The Illumina MiSeq platform was used to perform 16S rRNA gene sequencing targeting the V4 region.
The alpha and beta diversity was significantly different between pregnant and nonpregnant women, but minimal differences were observed between pregnant women with and without gingivitis. Interestingly, the oral bacterial community showed higher abundance of pathogenic taxa during healthy pregnancy as compared with nonpregnant women despite similar gingival and plaque index scores. However, when compared with overt pregnancy gingivitis, pathogenic taxa were less abundant during healthy pregnancy. PICRUSt analysis (phylogenetic investigation of communities by reconstruction of unobserved states) also suggested no difference in the functional capabilities of the microbiome during pregnancy, irrespective of gingival disease status. However, metabolic pathways related to amino acid metabolism were significantly increased in healthy pregnant women as compared with nonpregnant women.
The presence of pathogenic taxa in healthy pregnancy and pregnancy gingivitis suggests that bacteria may be necessary for initiating disease development but progression to gingivitis may be influenced by the host environmental factors. More efforts are required to plan interventions aimed at sustaining health before the appearance of overt gingivitis.
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 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.
It has been suggested that rheumatoid arthritis (RA) may originate at the oral mucosa. The aim of the present study was to assess the oral microbiome and periodontal condition in patients with early RA and individuals at risk of developing RA compared to healthy controls.
Three groups were recruited (n = 50 participants per group): 1) patients with early RA (meeting the American College of Rheumatology/European Alliance of Associations for Rheumatology 2010 classification criteria), 2) individuals at risk of developing RA (those with arthralgia who were positive for RA-associated autoantibodies), and 3) healthy controls. A periodontal examination was conducted to assess the presence of bleeding on probing (BOP), pocket probing depth (PPD), and periodontal inflamed surface area (PISA). The microbial composition of subgingival dental plaque, saliva, and tongue coating was assessed using 16S ribosomal DNA amplicon sequencing, and findings were compared between groups with permutational multivariate analysis of variance (PERMANOVA).
There were no significant differences in any of the 3 periodontal variables between patients with early RA, at-risk individuals, and healthy controls (P = 0.70 for BOP, P = 0.30 for PPD, and P = 0.57 for PISA, by Kruskal-Wallis test). PERMANOVA analyses comparing microbial composition between the groups showed significant differences in the microbial composition of saliva (F = 2.08, P = 0.0002) and tongue coating (F = 2.04, P = 0.008), but not subgingival dental plaque (F = 0.948, P = 0.51). However, in post hoc tests, no significant differences in microbial composition of the saliva or tongue coating were observed between the early RA group and the at-risk group (F = 1.12, P = 0.28 for saliva; F = 0.834, P = 0.59 for tongue coating). In assessing microbial diversity based on the number of zero-radius operational taxonomic units per sample, Prevotella in the saliva and Veillonella in the saliva and tongue coating were each found at a higher relative abundance in samples from patients with early RA and at-risk individuals compared to healthy controls.
The results show similarities in the oral microbiome between patients with early RA and at-risk individuals, since in both groups, the oral microbiome was characterized by an increased relative abundance of potentially proinflammatory species when compared to that in healthy controls. These findings suggest a possible association between the oral microbiome and the onset of RA.
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.
As a respiratory tract virus, SARS-CoV-2 infected people through contacting with the upper respiratory tract first. Previous studies indicated that microbiota could modulate immune response against pathogen infection. In the present study, we performed metagenomic sequencing of pharyngeal swabs from eleven patients with COVID-19 and eleven Non-COVID-19 patients who had similar symptoms such as fever and cough. Through metagenomic analysis of the above two groups and a healthy group from the public data, there are 6502 species identified in the samples. Specifically, the Pielou index indicated a lower evenness of the microbiota in the COVID-19 group than that in the Non-COVID-19 group. Combined with the linear discriminant analysis (LDA) and the generalized linear model, eighty-one bacterial species were found with increased abundance in the COVID-19 group, where 51 species were enriched more than 8 folds. The top three enriched genera were Streptococcus, Prevotella and Campylobacter containing some opportunistic pathogens. More interestingly, through experiments, we found that two Streptococcus strains, S. suis and S. agalactiae, could stimulate the expression of ACE2 of Vero cells in vitro, which may promote SARS-CoV-2 infection. Therefore, these enriched pathogens in the pharynxes of COVID-19 patients may involve in the virus-host interactions to affect SARS-CoV-2 infection and cause potential secondary bacterial infections through changing the expression of the viral receptor ACE2 and/or modulate the host's immune system.
This study compared two oral sampling methods, supragingival dental plaque and oral swabs, to see which better predicts severe early childhood caries (S-ECC) versus caries-free status. Researchers used next generation sequencing of the V4-16S rRNA gene (bacteria) and the ITS1 rRNA gene (fungi) to characterize the microbiome and mycobiome at each site. They then applied machine learning to build classification models from the resulting sequencing data.
The cohort consisted of 80 children under 72 months of age, recruited in a cross-sectional design. Of these, 40 children had severe early childhood caries and 40 were caries-free controls. Both dental plaque and oral swab samples were collected from each child, allowing paired comparison of the two sampling sites within the same population.
Dental plaque and oral swab samples showed significantly different alpha and beta diversity for both bacterial and fungal microbiomes. The cariogenic bacterium Streptococcus mutans was more abundant in dental plaque than in oral swabs among children with S-ECC. The fungal species Candida dubliniensis and C. tropicalis were more abundant in oral swab samples from children with S-ECC compared to caries-free controls, and these fungal taxa ranked among the top 20 features for classifying S-ECC status and for distinguishing sample type within the S-ECC group.
The findings suggest that sampling site meaningfully changes which microbial and fungal signals are detected, so plaque and swab samples are not interchangeable for caries research. The prominence of Candida dubliniensis and C. tropicalis in oral swabs points to a fungal, not just bacterial, contribution to severe early childhood caries that could be missed if only plaque is sampled. Combining sampling-site-aware sequencing with machine learning may improve early prediction models for pediatric caries risk.
This study evaluated the role of oral microbiota in colorectal cancer (CRC) progression by comparing bacterial communities in saliva and stool. Researchers used 16S rRNA analysis and next-generation sequencing to characterize both sample types. Linear discriminant analysis effect size (LEfSe) was applied to identify bacterial species that differed significantly between groups and across CRC stages.
The study included 52 patients with colorectal cancer and 51 healthy controls, with saliva and stool samples collected from each participant. CRC patients were further divided into an early-stage group (Stage I or II, n = 26) and an advanced-stage group (Stage III or IV, n = 26). This design allowed comparison not only between CRC patients and healthy subjects but also between disease stages.
Indigenous oral bacteria, including Peptostreptococcus, Streptococcus, and Solobacterium species, were present at significantly higher relative abundance in both saliva and stool of CRC patients compared with healthy controls. Among these, Peptostreptococcus stomatis, Streptococcus anginosus, Streptococcus koreensis, and Streptococcus moorei were identified as oral-cavity-derived species shared between the two body sites in CRC patients. Streptococcus moorei was further found at significantly higher relative abundance in advanced-stage (Stage III, IV) patients compared with early-stage (Stage I, II) patients, and this pattern held consistently in both saliva and stool samples.
The consistent presence of the same four oral-derived bacterial species in both saliva and stool of CRC patients supports a link between oral microbiota and gut microbiota in CRC. The stage-dependent enrichment of Streptococcus moorei suggests these oral bacteria may track with, or contribute to, CRC progression rather than merely being present. These findings raise the possibility that saliva-based microbial signatures could serve as accessible, non-invasive markers related to CRC status or stage.
The association of taste genetics and the oral microbiome in autoimmune diseases such as rheumatoid arthritis (RA) has not been reported. We explored a novel oral mucosal innate immune pathway involving the bitter taste G protein-coupled receptor T2R38. This case-control study aimed to evaluate whether T2R38 polymorphisms associate with the buccal microbial composition in RA. Genomic DNA was obtained from buccal swabs of 35 RA patients and 64 non-RA controls. TAS2R38 genotypes were determined by Sanger sequencing. The buccal microbiome was assessed by Illumina MiSeq sequencing of the V4-16S rRNA gene. Bacterial community differences were analyzed with alpha and beta diversity measures. Linear discriminant analysis effect size identified taxa discriminating between RA versus non-RA and across TAS2R38 genotypes. TAS2R38 genotype frequency was similar between RA and non-RA controls (PAV/PAV; PAV/AVI; AVI/AVI: RA 42.9%; 45.7%; 11.4% versus controls 32.8%; 48.4%; 18.8%, chi-square (2, N = 99) = 2.1, p = 0.35). The relative abundance of Porphyromonas, among others, differed between RA and non-RA controls. The relative abundance of several bacterial species also differed across TAS2R38 genotypes. These findings suggest an association between T2R38 polymorphisms and RA buccal microbial composition. However, further research is needed to understand the impact of T2R38 in oral health and RA development.
Parkinson's disease (PD) is a degenerative disease of the central nervous system (CNS) and is common among the middle-aged and elderly populations. Increasing evidence shows that the gut microbiota may trigger PD through the "gut-microbiota-brain" axis. A previous study revealed that constipation, one of the non-motor symptoms of PD, affects gut microbiota and the progression of PD. However, whether constipation is involved in gut microbiota-associated PD is largely unknown. Therefore, we investigated the relationship between gut microbiota, PD, and constipation in this study. We carried out 16S rRNA sequencing in 15 constipated PD patients (C-PD), 14 non-constipated PD (NC-PD) patients, and 15 healthy controls to evaluate the microbial population. Furthermore, co-occurrence networks were used to assess the gut ecology of the three groups. Spearman analyses were used to analyze the correlation between the differential microbiota and the clinical features. The results showed that there were differences in the composition of the gut microbiota among the C-PD group, the NC-PD group, and the healthy controls. No significant differences were observed in the alpha diversity among the three groups, but the beta diversity differed significantly among the groups. Compared with the healthy controls, the abundance of Hungatella and Collinsella was increased and the abundance of Lachnospira and Fusicatenibacter was reduced in the PD patients' feces. Compared with the NC-PD group, the relative abundance of Megamonas and Holdemanella were lower, while Hungatella, Streptococcus and Anaerotruncus were enriched in the C-PD group. The co-occurrence network analysis showed that the C-PD group presented a different microbial community relationship compared with the NC-PD group and the healthy controls. Our study provides strong evidence that the gut microbiota may be related to constipation in PD. In addition, our data suggest an association between the differential microbiota genera and the clinical features of PD. Therefore, modulating gut microbiota may be another way to monitor and optimize PD treatment.
This study examined whether gut microbiome composition, measured before treatment, is associated with response to immune checkpoint inhibitors in metastatic melanoma. Researchers used metagenomic shotgun sequencing on stool samples collected prior to treatment. The analysis specifically corrected for known confounders of gut microbiome composition, including age, BMI, and antibiotic use, which prior studies had often overlooked. Both taxonomic abundance and survival outcomes were assessed in relation to checkpoint inhibitor response.
The study included 25 patients with unresectable metastatic melanoma who were treated with immune checkpoint inhibitors. Of these, 12 were classified as responders and 13 as non-responders. Pre-treatment stool samples were freshly frozen and analyzed from each of these patients.
Alpha-diversity and overall bacterial prevalence did not differ significantly between responders and non-responders. However, after correcting for confounders in a zero-inflated multivariate analysis, 68 taxa showed differential abundance between the two groups. Carriership of Streptococcus parasanguinis was associated with longer overall survival, and carriership of Bacteroides massiliensis was associated with longer progression-free survival. In contrast, carriership of an unclassified Peptostreptococcaceae species was associated with shorter overall survival.
The findings suggest that simple measures like overall diversity are insufficient to explain gut microbiome links to checkpoint inhibitor outcomes in melanoma, and that confounder-adjusted, species-level analysis reveals associations that broader measures miss. Identifying specific taxa tied to survival, such as Streptococcus parasanguinis and Bacteroides massiliensis, points to candidate biomarkers or mechanistic targets for future investigation. This approach, accounting for confounders like antibiotic use, age, and BMI, may help explain why prior studies lacked consensus on which taxa matter for treatment response.
This study examined the relationship between the gut microbiota and psychiatric symptom severity among inpatients with serious mental illness. Researchers used 16S rRNA gene sequencing and whole genome shotgun sequencing to characterize fecal samples collected early in hospitalization. They then tested whether microbial richness and alpha diversity were associated with depression, anxiety, trauma, and suicide severity measures, and whether these microbial features predicted treatment outcome at discharge.
The study population consisted of 111 adult inpatients with serious mental illness. Diagnoses, suicide severity, trauma, depression, and anxiety were assessed shortly after admission. Participants self-collected fecal swabs early in the course of their hospital stay for microbiota analysis.
Depression and anxiety severity shortly after admission were negatively associated with bacterial richness and alpha diversity, meaning more severe symptoms corresponded to a less rich and less diverse gut microbiota. Specific bacterial taxa were identified as associated with depression and anxiety severity. Gut microbiota richness and alpha diversity measured early in hospitalization also significantly predicted depression remission by the time of discharge.
The findings support a link between gut microbial diversity and psychiatric symptom severity in a clinical inpatient population, extending prior evidence from animal models and small human studies. Because early microbiota measures predicted depression remission at discharge, gut microbiota composition may hold value as a marker of treatment response in serious mental illness. This strengthens the rationale for further investigating the brain-gut relationship as a factor in psychiatric care and outcomes.
Gut microbiome alterations are closely related to human health and linked to a variety of diseases. Although great efforts have been made to understand the risk factors for multiple myeloma (MM), little is known about the role of the gut microbiome and alterations of its metabolic functions in the development of MM.
Here, in a cohort of newly diagnosed patients with MM and healthy controls (HCs), significant differences in metagenomic composition were discovered, for the first time, with higher bacterial diversity in MM. Specifically, nitrogen-recycling bacteria such as Klebsiella and Streptococcus were significantly enriched in MM. Also, the bacteria enriched in MM were significantly correlated with the host metabolome, suggesting strong metabolic interactions between microbes and the host. In addition, the MM-enriched bacteria likely result from the regulation of urea nitrogen accumulated during MM progression. Furthermore, by performing fecal microbiota transplantation (FMT) into 5TGM1 mice, we proposed a mechanistic explanation for the interaction between MM-enriched bacteria and MM progression via recycling urea nitrogen. Further experiments validated that Klebsiella pneumoniae promoted MM progression via de novo synthesis of glutamine in mice and that the mice fed with glutamine-deficient diet exhibited slower MM progression.
Overall, our findings unveil a novel function of the altered gut microbiome in accelerating the malignant progression of MM and open new avenues for novel treatment strategies via manipulation of the intestinal microbiota of MM patients. Video abstract.
The study used shotgun metagenomic sequencing to compare the microbial communities of three ocular surface sites (meibum, eyelid skin, and conjunctiva) between patients with meibomian gland dysfunction (MGD) and healthy controls. The goal was to characterize taxonomic composition, resident pathogens, and functional and virulence features associated with MGD.
The cohort was 76 Chinese Han volunteers recruited at the Dry Eye Center of the Eye Hospital of Wenzhou Medical University, comprising 61 treatment-naive MGD patients and 15 healthy controls, sampled between April and September 2017. After quality control, 117 metagenome datasets were analyzed (58 meibum, 44 eyelid skin, and 15 conjunctiva), generated by whole-genome amplification and paired-end Illumina HiSeq shotgun sequencing (2 x 150 bp).
The MGD meibum microbiome had lower community richness (chao1) than controls while diversity indices (Shannon, Simpson) were similar, and its significant taxonomic changes were largely shared with eyelid skin but not conjunctiva. MGD meibum carried fewer pathogens on average than controls (mean 13 vs 36, p = 0.0014), yet Campylobacter coli, Campylobacter jejuni, and Enterococcus faecium were strongly enriched in MGD meibum (positive rates of about 57%, 51%, and 47% versus 0% in controls, with abundance more than 16-fold higher). Functional profiling showed increased carbohydrate and lipid metabolism enzymes, a microbial capacity to degrade benzoate, and an approximately fivefold increase in the type IV secretion system virulence factor (p = 0.017).
The authors conclude that MGD meibum contains distinct microbiota with stronger immune-evasive virulence, characterizing microbial community changes associated with MGD disease status. Because this is an observational case-control comparison, the results indicate association rather than causation, and the authors call for validation in larger and more geographically diverse populations.
This pilot study examined whether gut microbiome disturbances, gut barrier dysfunction, bacterial translocation, and resulting inflammation are associated with cognitive dysfunction in dementia. Researchers assessed gut microbiome composition, gut barrier integrity, bacterial translocation markers, and inflammatory markers using stool and serum samples. Microbiome composition was profiled through 16S rRNA sequencing, with analysis performed using QIIME 2 and Calypso 7.14 tools. Nutritional status and medication use were also documented to characterize the study population.
The study included 23 patients with dementia and 18 age and sex matched controls without cognitive impairment. Nutritional status was assessed in participants using the Mini Nutritional Assessment Short Form (MNA-SF). Detailed information on drug use was also collected from the cohort. This was a relatively small, matched case control pilot study rather than a large population based investigation.
Dementia was associated with dysbiosis, reflected in differences in beta diversity and shifts in taxonomic composition of the gut microbiome compared to controls. Gut permeability was increased in dementia patients, as shown by elevated serum diamine oxidase (DAO) levels. Systemic inflammation was also confirmed, evidenced by increased soluble cluster of differentiation 14 levels. The abstract does not report findings specific to Faecalibacterium prausnitzii, butyrate, or anti-inflammatory commensals.
These findings support the hypothesis that gut microbiome disturbances, impaired gut barrier function, and resulting systemic inflammation may contribute to cognitive dysfunction in dementia. The results suggest a potential gut-brain axis mechanism linking dysbiosis and barrier dysfunction to the inflammatory processes implicated in cognitive decline. As a pilot study with a modest sample size, these findings point toward the need for larger studies to confirm causal relationships and explore microbiome-targeted interventions for dementia.
Identification of the gut microbiome compositions associated with disease has become a research focus worldwide. Emerging evidence has revealed the presence of gut microbiota dysbiosis in Parkinson's disease. In this study, we aimed to identify the gut microbiome associated with Parkinson's disease and subsequently to screen and to validate potential diagnostic biomarkers of Parkinson's disease. This case-control study investigated gut microbial genes in faeces from 40 volunteer Chinese patients with Parkinson's disease and their healthy spouses using shotgun metagenomic sequencing. Furthermore, the identified specific gut microbial gene markers were validated with real-time PCR in an independent Chinese cohort of 78 Parkinson's disease patients, 75 control subjects, 40 patients with multiple system atrophy and 25 patients with Alzheimer's disease. We developed the first gut microbial gene catalogue associated with Parkinson's disease. Twenty-five gene markers were identified that distinguished Parkinson's disease patients from healthy control subjects, achieving an area under the receiver operating characteristic curve (AUC) of 0.896 (95% confidence interval: 83.1-96.1%). A highly accurate Parkinson's disease index, which was not influenced by disease severity or Parkinson's disease medications, was created. Testing these gene markers using quantitative PCR distinguished Parkinson's disease patients from healthy controls not only in the 40 couples (AUC = 0.922, 95% confidence interval: 86.4-98.0%), but also in an independent group of 78 patients with Parkinson's disease and 75 healthy control subjects (AUC = 0.905, 95% confidence interval: 86.0-95.1%). This classifier also performed a differential diagnosis power in discriminating these 78 patients with Parkinson's disease from a cohort of 40 patients with multiple system atrophy and 25 patients with Alzheimer's disease based on the panel of 25 biomarkers. Based on our results, the identified Parkinson's disease index based on the gene set from the gut microbiome may be a potential diagnostic biomarker of Parkinson's disease.
Sex differences exist in asthma susceptibility and severity. Accumulating evidence has linked airway microbiome dysbiosis to asthma, and airway microbial communities have been found to differ by sex. However, whether sex modifies the link between airway microbiome and asthma has not been investigated. To evaluate sex effects in the association between airway microbiome and asthma.
We analyzed induced sputum samples from 47 subjects (n = 23 patients with asthma and n = 24 normal controls) using 16S ribosomal RNA gene sequencing methods. The bacterial composition was analyzed for sex differences. Bacterial associations with asthma were assessed for each sex at the core taxa and genus levels.
The microbiome in induced sputum differed in women vs men at the community level. A total of 5 core bacterial taxa were found in all samples. No sex-specific core taxa were detected. The most abundant core taxon, Streptococcus salivarius, was significantly enriched in women than in men (P = .02). Within each sex, individuals with relatively lower abundance of S salivarius were more likely to have asthma (P = .006). For both sexes, increased Lactobacillus species were found in sputum samples of patients with patients compared with normal controls (adjusted P = .01). Haemophilus species were associated with asthma in men and not in women.
The airway microbiome differed by sex, and sex effects exist in the association of airway microbial markers and asthma. Future airway microbiome studies may yield better resolution if the context of specific sex is considered. The airway microbiome is a potential mechanism driving sex differences in asthma.
Schizophrenia (SCZ) is a devastating mental disorder with poorly defined underlying molecular mechanisms. The gut microbiome can modulate brain function and behaviors through the microbiota-gut-brain axis. Here, we found that unmedicated and medicated patients with SCZ had a decreased microbiome α-diversity index and marked disturbances of gut microbial composition versus healthy controls (HCs). Several unique bacterial taxa (e.g., Veillonellaceae and Lachnospiraceae) were associated with SCZ severity. A specific microbial panel (Aerococcaceae, Bifidobacteriaceae, Brucellaceae, Pasteurellaceae, and Rikenellaceae) enabled discriminating patients with SCZ from HCs with 0.769 area under the curve. Compared to HCs, germ-free mice receiving SCZ microbiome fecal transplants had lower glutamate and higher glutamine and GABA in the hippocampus and displayed SCZ-relevant behaviors similar to other mouse models of SCZ involving glutamatergic hypofunction. Together, our findings suggest that the SCZ microbiome itself can alter neurochemistry and neurologic function in ways that may be relevant to SCZ pathology.
This study asked whether gut microbiome signatures linked to colorectal cancer (CRC) hold up reliably across different patient cohorts and populations. The researchers meta-analyzed fecal metagenomic sequencing data to identify microbial taxa and functional pathways that consistently distinguish CRC from controls. They also examined the microbiome's functional potential, comparing metabolic pathways such as gluconeogenesis, putrefaction, fermentation, and choline degradation between CRC and control samples. Finally, they built and tested predictive microbiome signatures for CRC diagnosis.
The analysis drew on 969 fecal metagenomes assembled from five publicly available datasets plus two newly collected cohorts, with findings further validated on two additional independent cohorts. The abstract does not specify demographic details such as age, sex, or geographic origin of participants. This design represents a large-scale, multi-population pooling of existing and new CRC and control stool metagenome datasets rather than a single defined patient group.
The gut microbiome in CRC showed reproducibly higher richness than in controls (P < 0.01), partly driven by expansions of species normally derived from the oral cavity. Functional meta-analysis linked gluconeogenesis and putrefaction/fermentation pathways to CRC, while stachyose and starch degradation pathways were associated with controls. A predictive microbiome signature trained across multiple datasets achieved consistently high accuracy in datasets and independent validation cohorts it had not been trained on, with an average area under the curve of 0.84. Pooled raw metagenome analysis also found the choline trimethylamine-lyase gene overabundant in CRC samples (P = 0.001), linking microbiome choline metabolism to CRC.
By validating microbial richness increases, specific functional pathway shifts, and a diagnostic signature across multiple independent cohorts, this study strengthens the case that gut microbiome-based biomarkers for CRC can generalize beyond a single population. The identification of an overabundant choline trimethylamine-lyase gene points to microbiome-driven choline degradation as a mechanistic link worth further investigation in CRC. The high, cross-cohort predictive accuracy (AUC 0.84) supports the feasibility of microbiome-based tools as non-invasive adjuncts for CRC screening or risk stratification.
This study examined how long-term cotrimoxazole prophylaxis reduces systemic inflammation in HIV infection, a known independent driver of HIV-related mortality. Researchers investigated whether cotrimoxazole's clinical benefits could be explained by changes in the gut microbiome and intestinal inflammatory biomarkers, since subclinical enteropathogen carriage and enteropathy can drive systemic inflammation. They also used in vitro models of systemic and intestinal inflammation to isolate direct immune effects of cotrimoxazole from its antibiotic effects on gut bacteria.
The study population was HIV-positive Ugandan and Zimbabwean children receiving antiretroviral therapy. Plasma inflammatory markers were compared between children randomized to continue cotrimoxazole (n = 144) versus stop it (n = 149). A smaller subset underwent gut microbiome and fecal biomarker analysis, with 36 children continuing cotrimoxazole compared to 36 stopping it.
Plasma inflammatory markers were lower in children who continued cotrimoxazole compared to those who stopped, and this difference was not explained by clinical illness, HIV progression, or nutritional status. Overall gut microbiome composition was unchanged, but viridans group Streptococci and streptococcal mevalonate pathway enzymes were lower among children continuing cotrimoxazole. These microbial changes were associated with lower fecal myeloperoxidase, an intestinal inflammatory biomarker, and in vitro experiments showed cotrimoxazole had modest but consistent direct inhibitory effects on proinflammatory cytokine production.
The findings suggest cotrimoxazole prophylaxis reduces systemic inflammation in HIV infection through a combination of altering specific gut bacterial populations and directly dampening immune activation, rather than through broad microbiome restructuring. Targeting streptococcal populations and intestinal inflammation, alongside direct anti-inflammatory drug effects, may be a mechanism underlying reduced HIV-related mortality and morbidity. This dual mechanism could inform strategies to further optimize prophylactic approaches in HIV-positive populations on antiretroviral therapy.
This study examined how mode of delivery affects the earliest colonization of the infant gut microbiota during the neonatal period (up to one month of age) and into infancy. The researchers used longitudinal sampling combined with whole-genome shotgun metagenomic analysis to track which microbial strains and species established themselves in newborns over time. They specifically compared babies born by caesarean section to those born vaginally, and also looked at the effects of maternal antibiotic prophylaxis and breastfeeding status during the neonatal window.
The cohort comprised 596 full-term babies born in UK hospitals, from whom 1,679 gut microbiota samples were collected at multiple time points during the neonatal period and later in infancy. For a subset of these infant-mother pairs, matched maternal samples were also collected, totaling 175 mothers paired with 178 babies. This gave the study both a large infant sample size and a smaller nested set of mother-infant pairs for tracking strain transmission.
Babies delivered by caesarean section showed disrupted transmission of maternal Bacteroides strains, meaning these commensal organisms were less successfully passed from mother to infant compared to vaginal delivery. Caesarean-born infants also showed high-level colonization by opportunistic pathogens associated with the hospital environment, including Enterococcus, Enterobacter, and Klebsiella species. These same disruptions, though to a lesser extent, were also observed in vaginally delivered babies whose mothers received antibiotic prophylaxis and in infants who were not breastfed during the neonatal period.
The findings suggest that both caesarean delivery and antibiotic exposure around birth can independently disrupt the normal, low-risk colonization of the infant gut by maternal commensal strains. This disruption opens the door for opportunistic, hospital-associated pathogens to establish themselves early in life instead. Because early gut microbiota composition has been linked to later childhood and lifelong disease risk, these results point to birth mode, antibiotic use, and breastfeeding as modifiable factors that could be targeted to support healthier early microbiome establishment.
Emollients are a mainstay of treatment in atopic dermatitis (AD), a disease distinguished by skin bacterial dysbiosis. However, changes in skin microbiota when emollients are used as a potential AD preventative measure in infants remain incompletely characterized.
We compared skin barrier parameters, AD development, and bacterial 16S ribosomal RNA gene sequences of cheek, dorsal and volar forearm samples from 6-month-old infants with a family history of atopy randomized to receive emollients (n = 11) or no emollients (controls, n = 12). The emollient group had a lower skin pH than the control group. The number of bacterial taxa in the emollient group was higher than in the control group at all sites. The Streptococcus salivarius proportion was higher in the emollient versus control groups at all sites. S. salivarius proportion appeared higher in infants without AD compared to infants with AD. A decrease in S. salivarius abundance was further identified in a separate larger population of older children demonstrating an inverse correlation between AD severity at sampling sites and S. salivarius proportions.
The decreased skin pH and the increased proportion of S. salivarius after long-term emollient use in infants at risk for developing AD may contribute to the preventative effects of emollients in high-risk infants.
This study investigated whether rheumatoid arthritis (RA) itself alters the subgingival (below-the-gumline) oral microbiome, independent of periodontitis. Prior work linking RA to dysbiotic oral microbiomes had been confounded because those RA patients often also had extensive periodontal disease. Here, researchers isolated the effect of RA by studying only periodontally healthy individuals, comparing those with RA to those without. Subgingival plaque samples underwent 16S rRNA gene sequencing on an Illumina MiSeq platform, and community composition and co-occurrence patterns were analyzed with the QIIME and PhyloToAST bioinformatics pipelines.
The cohort consisted of 41 periodontally healthy individuals: 22 with rheumatoid arthritis and 19 without RA serving as controls. All participants were confirmed periodontally healthy, which removed periodontitis as a confounding variable. The abstract does not provide further demographic details such as age, sex distribution, or geographic origin.
Subgingival microbiomes differed significantly between RA patients and controls, with 41.9% of the community differing in relative abundance and 19% differing in membership (which taxa were present at all). Co-occurrence network analysis showed a striking structural difference: control networks were sparse and made up mostly of congeneric (same-genus) relationships, while RA patient networks formed a highly connected grid anchored by a large intergeneric hub built from known periodontal pathogens. Predictive metagenomic analysis (PICRUSt) suggested that arachidonic acid and ester lipid metabolism pathways may partly explain why this pathogen-anchored network was so tightly clustered in RA patients.
The findings indicate that RA is associated with a distinctly dysbiotic subgingival microbial community structure even in the complete absence of periodontitis, meaning RA itself, not just co-occurring gum disease, may reshape the oral microbiome. The emergence of a periodontal-pathogen-anchored co-occurrence hub in clinically healthy gums suggests these organisms could be functionally primed to promote inflammation before overt disease appears. This supports the oral microbiome, and its lipid-metabolism-linked pathogen networks, as a candidate factor in RA pathogenesis worth further mechanistic and longitudinal investigation.
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 differences in intestinal flora structure between obese and normal-weight school-age children. Researchers used Illumina Miseq next-generation sequencing with 16S rDNA high-throughput sequencing technology to characterize gut bacterial communities. Gut bacteria were classified into Operational Taxonomic Units (OTUs) using the RDP 16S rRNA database and RDP classifier. Both alpha diversity (within-sample diversity) and beta diversity (between-sample dissimilarity) were calculated to compare the two groups.
The study included 39 obese school-age children and 38 normal-weight control children of the same age range. The abstract does not specify the children's exact ages, sex distribution, or geographic location beyond this case-control design. Comparisons were made strictly between these two defined groups based on obesity status.
Intestinal flora in obese children showed lower alpha diversity than in normal-weight controls. Significant differences in the relative abundance of intestinal flora were detected at multiple levels of taxonomic classification. Beta diversity comparisons further confirmed that the microbial community structure differed meaningfully between the obese and normal groups. The abstract does not name specific bacterial taxa or note Faecalibacterium prausnitzii, butyrate, or other anti-inflammatory commensals.
Identifying which specific intestinal bacteria differ between obese and normal-weight children may help clarify the role these organisms play in the development of childhood obesity. This case-control comparison suggests reduced gut microbial diversity could be a feature of pediatric obesity. The findings may support future work aimed at finding new approaches, such as microbiome-targeted strategies, for addressing childhood obesity. Because the abstract's findings section was truncated, further specific implications beyond this general direction cannot be confirmed.
The esophageal microbiome has been proposed to be involved in a range of diseases including the esophageal adenocarcinoma cascade; however, little is currently known about its function and relationship to the host. Here, the esophageal microbiomes of 106 prospectively recruited patients were assessed using 16S rRNA and 18S rRNA amplicon sequencing as well as shotgun sequencing, and associations with age, gender, proton pump inhibitor use, host genetics, and disease were tested.
The esophageal microbiome was found to cluster into functionally distinct community types (esotypes) defined by the relative abundances of Streptococcus and Prevotella. While age was found to be a significant factor driving microbiome composition, bacterial signatures and functions such as enrichment with Gram-negative oral-associated bacteria and microbial lactic acid production were associated with the early stages of the esophageal adenocarcinoma cascade. Non-bacterial microbes such as archaea, Candida spp., and bacteriophages were also identified in low abundance in the esophageal microbiome. Specific host SNPs in NOTCH2, STEAP2-AS1, and NREP were associated with the composition of the esophageal microbiome in our cohort.
This study provides the most comprehensive assessment of the esophageal microbiome to date and identifies novel signatures and host markers that can be investigated further in the context of esophageal adenocarcinoma development.
The gut microbiome plays a central role in inflammatory bowel diseases (IBDs) pathogenesis and propagation. To determine whether the gut microbiome may predict responses to IBD therapy, we conducted a prospective study with Crohn's disease (CD) or ulcerative colitis (UC) patients initiating anti-integrin therapy (vedolizumab). Disease activity and stool metagenomes at baseline, and weeks 14, 30, and 54 after therapy initiation were assessed. Community α-diversity was significantly higher, and Roseburia inulinivorans and a Burkholderiales species were more abundant at baseline among CD patients achieving week 14 remission. Several significant associations were identified with microbial function; 13 pathways including branched chain amino acid synthesis were significantly enriched in baseline samples from CD patients achieving remission. A neural network algorithm, vedoNet, incorporating microbiome and clinical data, provided highest classifying power for clinical remission. We hypothesize that the trajectory of early microbiome changes may be a marker of response to IBD treatment.
This prospective and controlled study elucidates the impact of smoking on the salivary microbiome and its further influence on marginal bone loss (MBL) around an implant during a 3-month bone-healing period.
Saliva samples were collected preoperatively from 20 periodontally healthy patients with single-tooth replacement in the posterior mandible (smokers [n = 10] and non-smokers [n = 10]). Sequencing of 16S recombinant RNA gene amplicons was used to characterize the salivary microbiome. Each patient received implant surgery after oral clinical assessment, and MBL around the implant was measured during a 3-month healing period.
In total, 871,389 sequences were compared against the Human Oral Microbiome Database for bacterial identification. Microbial signatures of smokers exhibited lower diversity and richness, with a significant decrease in uncultured species. The phyla Gracilibacteria and Saccharibacteria showed a significant decrease in smokers. The genera Streptococcus, Lachnoanaerobaculum, Stomatobaculum, and Eubacterium were significantly increased in smokers, whereas Selenomonas, Selenomonas [G-3], and Catonella were significantly decreased. Specifically, Porphyromonas gingivalis was significantly more abundant in smokers, which was positively related to the severity of MBL during bone healing.
Smoking shapes the salivary microbiome in states of clinical health, and further may influence MBL during bone healing by creating high at-risk-for-harm communities. Understanding of the distinctly divergent oral microbiome in smokers and non-smokers is a base for personalized therapeutics for this high-risk cohort and also a base for further study on the pathologic mechanisms.
This study examined how Roux-en-Y gastric bypass (RYGB) surgery changes the gut microbiota of morbidly obese patients over time. The researchers used shotgun metagenomic sequencing of fecal DNA to characterize microbial composition at both the species and gene level. They also performed functional annotation of the microbial genes to understand how the metabolic potential of the gut community shifted after surgery. The goal was to describe the taxonomic and functional changes that accompany the weight loss and metabolic improvements known to follow RYGB.
The study recruited 13 morbidly obese patients scheduled to undergo RYGB surgery. Patients were phenotyped and had stool samples collected before surgery (n = 13), then again at 3 months (n = 12) and 12 months (n = 8) after surgery. This design allowed the same individuals to be followed longitudinally as their own before-and-after comparison.
Gut microbial diversity increased within the first 3 months after RYGB and remained elevated a year later, tracking alongside the weight loss and metabolic improvements the patients experienced. RYGB altered the relative abundance of 31 bacterial species within the first 3 months after surgery. These shifts occurred rapidly and persisted through the 12-month follow-up, indicating the surgery induces a durable restructuring of the individual gut microbiota rather than a transient disturbance.
The findings support the idea that major, lasting changes in gut microbial community structure accompany the metabolic benefits of RYGB, such as improved insulin sensitivity and glucose homeostasis. Because the diversity and compositional changes appear swiftly and persist for at least a year, the gut microbiota may be an active participant in, rather than a passive bystander to, post-surgical metabolic improvement. This raises the possibility that microbiome-targeted strategies could someday complement or mimic some of the benefits currently achieved only through bariatric surgery.
This study examined whether the composition of the gut microbiota in infants differs between those with eczema and those without. Researchers used high-throughput sequencing of the V3-V4 hypervariable regions of the 16S rRNA gene to profile bacterial communities in fecal samples. The analysis identified 12,386 operational taxonomic units (OTUs) at 97% similarity and compared taxa abundance and composition between groups.
The study was a case-control comparison of 50 infants with eczema (cases) and 51 healthy infants without eczema (controls). Fecal samples from these 101 infants were the source material for the 16S rRNA sequencing analysis. No further demographic details are given in the abstract.
Gut microbiota differed between groups in taxa abundance, though not in overall taxonomic composition. Healthy infants showed enrichment of Bifidobacterium, Megasphaera, Haemophilus and Streptococcus. Infants with eczema showed enrichment of Escherichia/Shigella, Veillonella, Faecalibacterium, Lachnospiraceae incertae sedis and Clostridium XlVa, with Faecalibacterium prausnitzii and Ruminococcus gnavus, taxa associated with atopy or inflammation, significantly enriched in the eczema group. Higher abundance of Akkermansia muciniphila in eczematous infants was also noted and may relate to reduced intestinal barrier integrity.
The findings support a link between altered gut bacterial abundance and eczema in infancy, pointing to specific genera and species as candidate markers of the atopic gut. The enrichment of Faecalibacterium prausnitzii alongside other inflammation-associated taxa in eczema cases suggests that microbiota composition changes may accompany, or contribute to, atopic disease processes rather than protect against them in this context. These results could inform future research into microbiota-targeted approaches for eczema risk assessment or intervention in infants.
This study investigated whether the gut microbiota is altered in patients with multiple sclerosis (MS), an autoimmune disease of the brain and spinal cord whose pathogenesis remains poorly understood. Researchers had been guided by findings from experimental autoimmune encephalomyelitis (EAE) animal models suggesting that altered gut microbiota could play a role in MS development. Fecal bacterial communities were profiled using high-throughput, culture-independent pyrosequencing of the 16S ribosomal RNA gene. The analysis compared community structure and species-level relative abundance between MS patients and healthy subjects.
The cohort included 20 Japanese patients with relapsing-remitting multiple sclerosis (MS20), compared against 40 healthy Japanese subjects (HC40). An additional 18 healthy subjects (HC18) contributed repeated fecal samples over the course of months, totaling 158 longitudinal samples, which were used to test whether the MS-associated differences were reproducible against natural fluctuations in a healthy gut microbiota. This design let the researchers distinguish disease-associated dysbiosis from normal within-person variability over time.
Pyrosequencing revealed a moderate dysbiosis in the overall structure of the gut microbiota in patients with MS compared to healthy controls. Twenty-one bacterial species showed significantly different relative abundance between the MS20 and HC40 groups. Notably, when compared against the 158 longitudinal HC18 samples, these differences held up reproducibly, and the abstract highlights a striking depletion of species belonging to the Clostridia XIVa and IV clusters in MS patients.
The findings support the hypothesis that gut microbiota alterations are associated with multiple sclerosis, reinforcing a possible gut-immune axis in MS pathogenesis. The specific depletion of Clostridia XIVa and IV cluster species is notable because these clusters include many commensal, fiber-fermenting bacteria implicated in immune regulation. This work adds human evidence to a link previously suggested mainly by animal EAE models and points toward gut microbiota as a potential avenue for understanding or influencing MS disease processes.
This study examined 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 examined the subgingival bacterial biodiversity of untreated chronic periodontitis patients using 16S rRNA gene sequencing. The primary goal was to compare the oral microbiome found in deep, diseased periodontal pockets against shallow, healthy sites. A secondary goal was to assess whether smoking, race, and dental caries influenced this deep-versus-shallow microbial relationship. A universal primer set targeting the V4-V6 region of the 16S rRNA gene was designed to amplify oral microbial sequences.
A total of 88 subjects were recruited from two clinics for this study. From each subject, paired subgingival plaque samples were collected, one from a deep site with probing depth greater than 5 mm and one from a shallow site with probing depth of 3 mm or less. This paired, within-subject design allowed direct comparison of diseased and healthy pocket microbiomes in the same individuals.
Statistical analysis using a two-part model with false discovery rate correction identified 51 of 170 genera and 200 of 746 species that differed significantly in abundance between deep and shallow sites. Beyond bacterial species already known to be associated with periodontal disease, additional species were found to be markedly changed in the diseased, deep sites. Cluster analysis further showed that the degree of microbiome difference between deep and shallow sites was shaped by patient-level factors, including clinic location, race, and smoking status. No sulfate-reducing bacteria, Desulfovibrio, or sulfur-related metabolism were reported in this abstract.
The findings reinforce that chronic periodontitis involves a broad, multi-species shift in subgingival bacterial communities, extending beyond previously recognized periodontal pathogens. Because patient-level factors such as smoking, race, and clinic location influenced the deep-versus-shallow microbiome difference, these variables may need to be accounted for in future periodontal microbiome research and clinical risk assessment. The paired deep-shallow sampling approach offers a model for identifying disease-associated bacterial signatures within the same patient, which could inform future diagnostic or monitoring strategies.
This study examined whether human intestinal microbes play a role in the autoimmunity that often leads to type 1 diabetes (T1D), building on prior murine and rat models linking gut bacteria to diabetes onset. Researchers used high-throughput, culture-independent sequencing approaches to profile gut bacterial communities over time. They tracked how bacterial composition and diversity changed as autoimmunity developed, comparing children who progressed to T1D-associated autoimmunity with those who did not.
The subjects were young children at high genetic risk for type 1 diabetes. Autoimmune cases were compared over time against age-matched, genotype-matched, nonautoimmune control children. The abstract does not give an exact sample size, but the design followed this at-risk pediatric cohort longitudinally as they moved from infancy toward the toddler stage.
Bacterial diversity diminished over time in children who developed autoimmunity, relative to matched nonautoimmune controls. A single species, Bacteroides ovatus, accounted for nearly 24% of the total increase in the phylum Bacteroidetes in autoimmune cases compared with controls. Conversely, a human Firmicute strain (CO19) represented nearly 20% of the increase in Firmicutes seen in controls over the same period, a pattern opposite to what was seen in cases.
The findings support the idea that healthy infants develop increasingly stable, more diverse microbiomes as they approach toddlerhood, while children destined for autoimmunity show a different, less stable trajectory. This suggests specific microbial shifts, including loss of certain Firmicutes and expansion of Bacteroides ovatus, may be linked to the immune processes preceding type 1 diabetes. The results point toward the gut microbiome as a potential early marker or contributor to autoimmune risk in genetically susceptible children, warranting further work to define an autoimmune-associated microbiome signature.
2026-07-04
Streptococcus salivarius majorTaxon page created: biology (morphology, health role, beneficial factors), its ecological role, context, supportive interventions, the data-derived Conditions table across 80 conditions, and the full research feed.
Peng X, Li Z, Pei Y, Zheng S, Liu J, Wang J, Li R, Xu X.
Streptococcus salivarius K12 alleviates oral mucositis in patients undergoing radiotherapy for malignant head and neck tumors: a randomized controlled trial.J Clin Oncol. 2024
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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