Citrobacter

What was studied?

Host-microbiome interactions play essential roles in the development of Alzheimer's disease (AD), yet the host genetic impacts on gut microbial alterations in AD remain poorly understood.

What were the most important findings?

Here, we simultaneously profiled host genotype and gut microbiome in 252 Chinese individuals with varying degrees of cognitive disability. Using the latent Dirichlet allocation topic model, we identified the Anaerostipes-enriched enterosignature (ES-Ana) at the microbial subgroup level as significantly negatively associated with cognitive disability, which could be recapitulated in external cohorts. With the whole-genome sequencing data, we performed microbiome genome-wide association studies for the ES-Ana relative abundance. We prioritized 41 lead genetic variants and confirmed that the high ES-Ana relative abundance showed a negative correlation with the polygenic risk score of AD, indicating its protective effect against AD. Furthermore, we identified 174 ES-Ana-associated genes, which are enriched in AD-related biological functions and phenotypes, and exhibite pervasive underexpression in glial cells during brain aging.

What are the greatest implications of this study?

In summary, our study reveals the complex genetic effects on the gut microbiota in AD, and provides novel evidence for the roles of the gut-brain axis in AD. Video Abstract.

What was studied?

Early diagnosis of Parkinson's disease (PD) and distinguishing it from essential tremor (ET) remains a significant challenge. We analyzed fecal samples (gut microbiota via 16S rRNA gene sequencing with DADA2-denoising/OTU-clustering) and short-chain fatty acids (SCFAs) in 104 drug-naïve early PD patients (73 test/31 validation), 69 ET patients (48/21), and 61 healthy controls (HC; 43/18). Differential taxa were identified using ANCOM, ANCOM-BC, ALDEx2, MaAsLin2, and LEfSe; top diagnostic potential was selected by random forest and assessed by ROC curve analysis. Compared to HC, PD showed reduced Citrobacter/Haemophilus, increased Eggerthella, and elevated isovaleric/isobutyric acids (validation AUC = 0.864). PD vs. ET exhibited decreased Bilophila/Bacteroides/Haemophilus with elevated isovaleric/isobutyric/valeric acids (validation AUC = 0.825). Tremor-dominant PD (TD-PD) was distinguished from ET by lower Lachnoclostridium/Haemophilus/Bilophila and higher isovaleric/isobutyric acids (validation AUC = 0.780), while non-TD-PD differed from TD-PD only in decreased Dialister (validation AUC = 0.802). Gut microbiota and SCFAs might serve as specific, non-invasive candidate biomarkers for early PD diagnosis.

What was studied?

Extranodal natural killer/T-cell lymphoma (ENKTL) predominantly manifests in East Asia and Latin America. Despite shared intrinsic factors, such as ethnic and genetic backgrounds, the progression of ENKTL can be influenced by extrinsic factors related to changing lifestyle patterns.

Who was studied?

This study collected stool samples from newly diagnosed (ND)-ENKTL patients (n=40) and conducted whole genome shotgun sequencing.

What were the most important findings?

ND-ENKTL revealed reduced alpha diversity in ND-ENKTL compared to healthy controls (HCs) (p=0.008), with Enterobacteriaceae abundance significantly contributing to the beta diversity difference between ENKTL and HCs (p < 0.001). Functional analysis indicated upregulated aerobic metabolism and degradation of aromatic compounds in ND-ENKTL. Enterobacteriaceae were associated not only with clinical data explaining disease status (serum C-reactive protein, stage, prognosis index of natural killer cell lymphoma [PINK], and PINK-E) but also with clinical outcomes (early relapse and short progression-free survival). The relative abundance of Enterobacteriaceae at the family level was similar between ENKTL and diffuse large B-cell lymphoma (DLBCL) (p=0.140). However, the ENKTL exhibited a higher abundance of Escherichia, in contrast to the prevalence of Enterobacter and Citrobacter in DLBCL. Linear regression analysis demonstrated a significant association between Escherichia abundance and programmed cell death-ligand-1 (PD-L1) levels in tissue samples (p=0.025), whereas no correlation with PD-L1 was observed for Enterobacteriaceae at the family level (p=0.571).

What are the greatest implications of this study?

ND-ENKTL exhibited an abundance of Enterobacteriaceae and a dominant presence of Escherichia. These microbial characteristics correlated with disease status, treatment outcomes, and PD-L1 expression, suggesting the potential of the ENKTL microbiome as a biomarker and cause of lymphomagenesis, which warrants further exploration.

What was studied?

This study investigated whether alterations in the gut microbiome are associated with allograft rejection in kidney transplant (KT) recipients. Researchers used 16S rRNA gene amplicon sequencing to characterize gut microbiome composition and function over time. They tracked how the microbiome changed from the pre-transplant, chronic kidney disease (CKD) state through recovery, and examined shifts occurring before and after rejection events. Functional analysis focused on the microbiome's capacity to produce short-chain fatty acids, including propionate and butyrate.

Who was studied?

The study analyzed 562 samples collected from 245 individuals as part of a multicenter prospective study. Of these participants, 217 had received a kidney transplant. This design allowed comparison of microbiome trajectories across the CKD-to-post-transplant recovery period and around the time of graft rejection events.

What were the most important findings?

Overall, gut microbiome composition gradually recovered after transplantation, mirroring the CKD-to-health transition, as shown by increasing Shannon diversity. However, prior to graft rejection, microbial diversity decreased along with a reduction in short-chain fatty acid-producing taxa. Functional analysis confirmed a decreased potential for short-chain fatty acid production before rejection, and this was validated using quantitative PCR targeting propionate and butyrate production potential. After rejection, these microbiome features normalized again, and the alterations preceding rejection partially overlapped with microbiome signatures previously reported in CKD patients.

What are the greatest implications of this study?

The findings suggest that gut microbiome changes, particularly loss of diversity and short-chain fatty acid-producing taxa, may precede and potentially help predict graft rejection in kidney transplant recipients. This raises the possibility that monitoring microbiome composition and short-chain fatty acid production capacity could serve as an early warning signal for clinicians. Because these pre-rejection alterations partially resemble CKD-associated microbiome signatures, they may reflect a shared pathway of microbial dysfunction linked to immune dysregulation. This work supports further exploration of the gut microbiome as a noninvasive biomarker source and a potential target for interventions to support graft survival.

What was studied?

This study investigated the smoking paradox, in which smokers tend to have lower body mass index but higher risk of obesity-related disease, through the lens of the gut microbiota. Researchers used 16S rRNA sequencing to identify smoking-related microbial genera and built a smoking-related microbiota index (SMI). They then tested whether SMI was associated with obesity indices and with incident obesity-related diseases, including analyses designed to control for shared familial and environmental confounders.

Who was studied?

The analysis drew on 4000 male participants from two cohorts, the WELL-China cohort and the Lanxi cohort. Obesity indices were derived using dual-energy X-ray absorptiometry (DEXA) scans in these participants. A subset of participants with siblings was used for sibling comparison analyses via a between-within (BW) model, allowing the researchers to account for unmeasured familial confounding.

What were the most important findings?

The smoking-related microbiota index (SMI) was positively associated with BMI and other DEXA-derived obesity indices. Higher SMI was also linked to greater risk of incident obesity-related disease, with hazard ratios of 1.97 for diabetes, 1.31 for major adverse cardiovascular events, and 1.70 for obesity-related cancers. These associations held up in sibling comparison analyses, which help rule out shared family environment or genetics as the explanation.

What are the greatest implications of this study?

The findings suggest that smoking-associated shifts in gut microbiota may help explain why smokers face elevated cardiometabolic and cancer risk despite often having lower BMI. This reframes the smoking-obesity paradox as partly a microbiome-mediated phenomenon rather than a purely anthropometric one. The sibling comparison design strengthens confidence that the microbiota signal is not simply a marker of shared family background. These results point to the gut microbiota as a potential target or biomarker for assessing metabolic and disease risk in people who smoke.

Who was studied?

Using Illumina NextSeq, cDNA libraries were sequenced, and reads were aligned to the human genome and analyzed with DESeq2. Kegg and differential analyses revealed key genes and pathways. Gene sensitivity and specificity were assessed using ROC curves (p < 0.05, AUC > 0.8). Non-aligned reads were used for microbiome analysis with Kraken2 for bacterial identification. Microbial analysis included LDA score, Alpha and Beta diversity metrics, with significance set at p ≤ 0.05. Spearman's correlation between differentially expressed genes (DEGs) and bacteria were also examined.

What were the most important findings?

The data revealed a gene expression pattern in EBV-positive gastric cancer, highlighting immune response, inflammation, and cell proliferation genes (e.g., GBP4, ICAM1, IL32, TNFSF10). ROC analysis identified genes with high specificity and sensitivity for discriminating EBV+ gastric cancer, including GBP5, CMKLR1, GM2A and CXCL11 that play pivotal roles in immune response, inflammation, and cancer. Functional enrichment pointed to cytokine-cytokine receptor interactions, antigen processing, and Th17 immune response, emphasizing the role of the tumor microenvironment, shaped by inflammation and immunomodulation, in EBV-associated GC. Microbial analysis revealed changes in the gastric microbiota in EBV+ samples, with a significant reduction in bacterial taxa. The genera Choristoneura and Bartonella were more abundant in EBV+ GC, while more abundant bacteria in EBV- GC included Citrobacter, Acidithiobacillus and Biochmannia. Spearman's correlation showed a strong link between DE bacterial genera and DEGs involved in processes like cell differentiation, cytokine production, digestion, and cell death.

What are the greatest implications of this study?

These findings suggest a complex interaction between the host (EBV+ GC) and the microbiota, possibly influencing cancer progression, and offering potential therapeutic targets such as microbiota modulation or gene regulation. Comparing with EBV- samples further highlights the specific impact of EBV and the microbiota on gastric cancer pathogenesis.

What was studied?

This study aimed to explore the distinct characteristics of the gut microbiota in tuberculosis (TB) patients who experienced liver injury following anti-TB treatment compared with those who did not.

Who was studied?

We employed a nested case-control study design, recruiting newly diagnosed pulmonary TB patients at Tangshan Infectious Disease Hospital. Participants were categorized into the Antituberculosis Drug-Induced Liver Injury (ADLI) group and the Non-ADLI group based on the occurrence of liver injury after treatment. Both groups received identical anti-TB regimens. Stool samples were collected from patients who developed liver injury within 2-3 weeks of starting treatment, alongside matched controls during the same timeframe. The samples underwent 16S rDNA sequencing, and clinical data and blood samples were also collected for further analysis. At the same time, we constructed mouse models to explore the effects of different anti-tuberculosis drugs on gut microbiota.

What were the most important findings?

Following anti-TB treatment, we observed a decrease in microbial diversity and significant structural changes in the gut microbiota of TB patients (P < 0.05). At T1, the Non_ADLI_T1 group presented relatively high levels of Phascolarctobacterium, Anaerofustis and Mailhella. In contrast, the ADLI_ T1 group presented elevated levels of Bacteroides, Veillonella, Clavibacter, Corynebacterium, Anaerococcus, Gardnerella, Peptostreptococcus and Lautropia. At T2, the ADLI_T2 group presented increased levels of Enterococcus, Faecalibacterium, unclassified_f__Burkholderiaceae, Cardiobacterium, Ruminococcus_gnavus_group and Tyzzerella_4 than did the Non_ADLI_T2 group. Additionally, the ADLI_T2 group presented decreased levels of Prevotella_9, Akkermansia, Erysipelotrichaceae_UCG-003, Rubrobacter and norank_f__Desulfovibrionaceae than did the Non_ADLI_T2 group. In animal experiments, similar changes to those in the human population were observed in the mouse model compared to the control group. Any single anti-tuberculosis drug or two-drug combination or three-drug combination can cause dysbiosis of the mouse gut microbiota. The signature genera between groups are different and related to the type of anti-tuberculosis drug.

What are the greatest implications of this study?

Anti-tuberculosis treatment induces dysbiosis in the gut microbiota of TB patients. Notably, there are significant differences in microbiota characteristics between TB patients with and without liver injury at both onset and during treatment. There are some differences in the characteristics of bacterial flora in liver injury caused by different drugs.

What was studied?

Accumulating evidence indicates that antibiotic exposure may lead to impaired vaccine responses1-4; however, the mechanisms underlying this association remain poorly understood. Here we prospectively followed 191 healthy, vaginally born, term infants from birth to 15 months, using a systems vaccinology approach to assess the effects of antibiotic exposure on immune responses to vaccination. Exposure to direct neonatal but not intrapartum antibiotics was associated with significantly lower antibody titres against various polysaccharides in the 13-valent pneumococcal conjugate vaccine and the Haemophilus influenzae type b polyribosylribitol phosphate and diphtheria toxoid antigens in the combined 6-in-1 Infanrix Hexa vaccine at 7 months of age. Blood from infants exposed to neonatal antibiotics had an inflammatory transcriptional profile before vaccination; in addition, faecal metagenomics showed reduced abundance of Bifidobacterium species in these infants at the time of vaccination, which was correlated with reduced vaccine antibody titres 6 months later. In preclinical models, responses to the 13-valent pneumococcal conjugate vaccine were strongly dependent on an intact microbiota but could be restored in germ-free mice by administering a consortium of Bifidobacterium species or a probiotic already widely used in neonatal units. Our data suggest that microbiota-targeted interventions could mitigate the detrimental effects of early-life antibiotics on vaccine immunogenicity.

What was studied?

Endometriosis is a chronic inflammatory gynecological disease. Previous studies have explored relationships between endometriosis and the microbiota, but none have focused on differences in gut microbiota between early-stage and late-stage endometriosis patients or their connections to dysmenorrhea symptoms. This study compared gut microbiota compositions between early-stage and late-stage endometriosis patients using amplicon sequencing and further analyzed their dysmenorrhea symptoms.

Who was studied?

To minimize seasonal and dietary impacts, we recruited Guangdong residents hospitalized for surgery at Zhujiang Hospital. Participants underwent preoperative screening based on enrollment criteria and fecal samples were collected. Endometriosis was classified according to the American Society for Reproductive Medicine (ASRM) staging system based on surgincal and pathological findings. Stage I-II cases were designated as early-stage endometriosis, and Stage III-IV as late-stage endometriosis.

What were the most important findings?

A total of 112 patient fecal samples were collected, with 75 (median age, 32 years [range, 18-49 years]) meeting the enrollment criteria, including 39 early-stage (32 Stage I and 7 Stage II) and 36 late-stage (16 Stage III and 20 Stage IV) patients. The gut microbiota structure and functions in early-stage patients significantly differed from those in late-stage cases. Dysmenorrhea was associated with specific microbial traits. Late-stage patients with dysmenorrhea displayed distinctly different gut profiles compared to other endometriosis groups. Bartonella, Snodgrassella, and other taxa were enriched in late-stage cases, while Bacteroides, and Prevotella were decreased.

What are the greatest implications of this study?

The gut microbial community structure in early-stage endometriosis patients significantly differs from that in late-stage cases, with late-stage patients experiencing dysmenorrhea displaying particularly distinct gut profiles. Predicted functional analysis indicated suppressed steroid biosynthesis pathways in the gut of late-stage endometriosis patients. In conclusion, it is plausible that the multiple effects of steroids on the lower gastrointestinal tract may involve microbiota alterations, suggesting the need for further investigations.

What was studied?

People living with human immunodeficiency virus (HIV) (PLWH) might have an increased risk of developing coronavirus disease 2019 (COVID-19); however, the impact of their gut microbiota and metabolites on the progress of COVID-19 is unknown. Herein, we analyzed the temporal changes in the gut microbiota composition and metabolites of PLWH at baseline and during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We analyzed the gut microbiota and metabolites by integrating 16 S rRNA gene sequencing and liquid chromatography-mass spectrometry untargeted metabolomics of 36 PLWH at baseline and during SARS-CoV-2 infection periods. Significant changes in the composition of the gut microbiota and an increased ratio of Firmicutes/Bacteroidetes during SARS-CoV-2 infection, relative to the baseline, were observed. At the genus level, the abundances of Lactobacillus and Lactiplantibacillus decreased significantly. Furthermore, seven differentially enriched human metabolic pathways (including protein digestion and absorption, central carbon metabolism in cancer, aminoacyl-tRNA biosynthesis, mineral absorption, ABC transporters, arginine and proline metabolism, and phenylalanine metabolism) were identified by comparing the fecal metabolites at baseline and during SARS-CoV-2 infection. Spearman correlation analysis revealed close relationships between the two differentially abundant microbiota members and the five differentially abundant fecal metabolites that might affect specific human metabolic pathways.This study is the first to characterize the gut microbiota and metabolites in PLWH at baseline and during SARS-CoV-2 infection. The key microbiota and metabolites in the infection process were identified, providing new ideas for treatment.

What was studied?

Crohn's disease (CD) is a chronic non-specific inflammatory bowel disease with an increasing incidence worldwide. Patients with CD are facing elevated risk for mental disorders (MD) than healthy people, and chronic psychological stress is considered to trigger deterioration and relapse of CD. The microbiome-gut-brain axis (MGBA) is recognized as a crucial factor in unraveling this connection. Whereas, so far, few studies have revealed the relationship of the microbiota communities and tryptophan catabolites of the terminal ileum mucosa on gut-brain communication.

Who was studied?

A total of 52 patients with CD, along with 11 patients with colorectal cancers recruited as controls, were enrolled in this study. The participants completed Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7 Questionnaire. The terminal ileal mucosa was collected during surgery. We profiled the microbiota composition of 37 patients and quantified the tryptophan catabolites of 28 patients utilizing 16 S rRNA gene sequencing and liquid chromatography-tandem mass spectrometry, respectively. In addition, bioinformatics methods were used to elucidate the interrelationships between psychological states, microbial communities, and tryptophan catabolites.

What were the most important findings?

CD patients with MD showed a significant reduction in microbial diversity within the ileal mucosa. Regarding microbial composition, Prevotella was relatively enriched in CD patients with MD, along with lower relative abundances of Akkermansia and Faecalibacterium. Furthermore, significant disparities in the levels of Picolinic acid (PA), Kynurenic acid (KYNA), Nicotinic acid (N-Acid), and Indole-3-carbaldehyde (ICAld) were detected within the ileal mucosa of CD patients comorbid with MD. A pronounced correlation was observed between PA levels and anxiety scale scores. The heightened abundance of Prevotella may be closely associated with altered levels of PA, N-Acid, and KYNA.

What are the greatest implications of this study?

Alterations in the microbial composition of the terminal ileum may interact with changes in tryptophan metabolism and are associated with MD in patients with CD undergoing surgery.

What was studied?

This study characterized the microbial DNA profile present in organ preservation solution (OPS) used during liver transplantation, using 16S rRNA sequencing. The researchers asked whether specific microbial taxa detected in the OPS, reflecting the intrahepatic graft's native microbiota, are associated with short-term clinical outcomes after transplant. They also built machine learning models to predict outcomes from these microbial features and used RNA sequencing of matched liver biopsies to validate host-microbiome interactions.

Who was studied?

The discovery cohort consisted of 110 liver transplant donors, with an independent validation cohort of 29 additional donors. Microbial signatures were derived from the organ preservation solution collected in association with each donor's liver, rather than from patient stool or blood samples. Clinical outcome data for recipients were linked to these donor-derived OPS samples using MaAsLin2-adjusted statistical models.

What were the most important findings?

The microbial DNA signature detected in the OPS closely resembled known liver and bile microbiome profiles and was dominated by Proteobacteria. Specific bacterial genera, including Bacillus and Prevotella, were differentially abundant and statistically associated with adverse post-transplant outcomes, being hyperabundant in cases with worse results. Gene pathway enrichment analysis and RNA sequencing of matched liver biopsies were used to explore host-microbiome interactions underlying these associations.

What are the greatest implications of this study?

This work suggests that the intrahepatic graft's own microbiota, detectable in the preservation solution at the time of transplant, carries prognostic information that has previously been overlooked in favor of gut microbiota studies. Machine learning models built on these OPS-derived microbial features could enable early risk stratification for liver transplant recipients before complications arise. If validated further, this approach could support a practical, minimally invasive tool for predicting short-term transplant outcomes.

What was studied?

This study examined cocoa (Theobroma cacao L.) bean fermentation, the spontaneous process that shapes the final flavour of chocolate. The researchers investigated how abiotic factors (pH and temperature) and biotic factors (bacterial and fungal microbiota) interact to produce key flavour attributes in premium chocolate. They used genome-resolved metagenomics to identify the metabolic traits within the fermentation microbial community responsible for flavour development. They then tested whether a defined microbial consortium could reproduce those fine flavour attributes under controlled conditions.

Who was studied?

The study drew on cocoa bean fermentation samples collected from farms in Colombia. From these samples, the researchers characterized the natural bacterial and fungal community and used genome-resolved metagenomics to build a picture of the metabolic capacities present. They then assembled a separate, defined and metabolically competent microbial consortium, rather than studying a human or animal cohort, to test controlled fermentation. A trained tasting panel was also used to evaluate the resulting chocolate.

What were the most important findings?

The pH, temperature, and combined bacterial and fungal microbiota composition of the fermentation samples all influenced key flavour attributes of the resulting premium chocolate. Genome-resolved metagenomics showed that the metabolic traits needed for flavour development were redundantly encoded across multiple members of the fermentation community, not confined to a single organism. Using a defined microbial consortium built from this information, the researchers replicated fine flavour attributes of chocolate under controlled conditions. This was confirmed through omics analyses, metabolic network modeling, and evaluation by a trained tasting panel.

What are the greatest implications of this study?

These findings show that the flavour-relevant functions of spontaneous cocoa fermentation can be captured in a defined, reproducible microbial consortium rather than relying on uncontrolled natural fermentation. This provides a basis for designing standardized fermentation starters that can reliably reproduce fine chocolate flavour characteristics. Such starters could help cocoa producers achieve consistent premium quality across batches and locations. The approach also demonstrates a model for linking metagenomic and metabolic data to sensory outcomes in food fermentation more broadly.

What was studied?

The gut microbiota plays a pivotal role in developing colorectal cancer (CRC) through interactions with host immunity, metabolism, and inflammation. However, microbiome-based studies remain scarce in Middle Eastern populations, limiting regional insights into microbial signatures associated with CRC. This study aimed to characterize the gut microbiota profiles of Jordanian CRC patients using 16S rRNA gene sequencing and compare them to those of healthy controls from the GutFeeling KnowledgeBase (GutFeelingKB). Stool samples from 50 CRC patients were analyzed using Illumina iSeq targeting the V3-V4 region. Taxonomic profiling was conducted with a standardized 16S metagenomics pipeline and compared with GutFeelingKB reference data. CRC samples were enriched in Streptococcus, Enterococcus, Klebsiella, Escherichia, Citrobacter, Veillonella, Megamonas, and Eggerthella, while beneficial butyrate-producing genera such as Roseburia, Ruminococcus, Akkermansia, Faecalibacterium, and Bacteroides were significantly depleted. The absence of Fusobacterium nucleatum and Bacteroides fragilis-commonly seen in global studies-suggests region-specific microbial patterns. This study is the first metagenomic study profiling CRC-associated microbiota in Jordan. The findings reveal a dysbiotic microbial signature that reflects both global changes associated with CRC and local ecological influences. This research emphasizes the importance of population-specific microbiome studies and highlights the need to include appropriately matched controls in future investigations.

What was studied?

This study examined whether rifaximin, a gut-specific non-absorbable antibiotic, could reduce gut-derived systemic inflammation in severe acute pancreatitis (SAP). The researchers combined murine experimental models with a single-center, open-label randomized controlled trial (ChiCTR2100049794). They assessed pancreatic injury, systemic inflammatory markers, and gut microbiota composition, and tested whether rifaximin's effects depended on modulating the microbiota by using antibiotic-treated and germ-free mice.

Who was studied?

The animal component used murine models of severe acute pancreatitis, including antibiotic-treated and germ-free mice used to probe the mechanism. The clinical component enrolled 60 patients with predicted severe acute pancreatitis, randomized to receive rifaximin or standard control treatment. No further demographic details are given in the abstract.

What were the most important findings?

In mice, rifaximin reduced pancreatic injury and systemic inflammation and decreased mucin-degrading gut genera such as Akkermansia, but its protective effects persisted even in antibiotic-treated and germ-free mice, indicating mechanisms beyond microbiota modulation. In patients, rifaximin significantly lowered systemic inflammation, with white blood cell count falling from a median of 11.50 x10^9/L to 8.49 x10^9/L and TNF-alpha falling from 15.05 pg/mL to 11.00 pg/mL. However, the rate of culture-confirmed infection was identical between rifaximin and control groups (13.3% vs 13.3%), and adverse events were comparable between groups.

What are the greatest implications of this study?

The findings suggest rifaximin can dampen systemic inflammation in severe acute pancreatitis through mechanisms that are not solely dependent on reshaping the gut microbiota, pointing to a possible direct anti-inflammatory or barrier-protective effect. Because inflammation markers improved without any change in infection risk, rifaximin may offer a safe adjunct for controlling inflammatory injury in SAP without added infectious risk. This supports further investigation of rifaximin as a therapeutic strategy for gut-derived inflammation in acute pancreatitis, alongside continued study of its non-microbiota-dependent mechanisms.

What was studied?

This study examined whether person-to-person transmission of gut microbes, not just diet, helps explain why traditional microbiomes shift toward an industrialized pattern after immigration. Researchers used germ-free mice colonized with human donor stool to test how sharing air and physical contact between mice carrying different donor microbiomes affects microbial composition. They then exposed the resulting microbiomes to dietary ingredients and food additives common in industrialized diets to see how composition changes translated into metabolic outcomes, including weight gain.

Who was studied?

The study did not involve human subjects directly. Instead, germ-free mice were colonized with human donor stool collected from the United States and from Thailand, creating humanized mouse models representing an industrialized and a traditional microbiome. Transmission and metabolic effects were then measured in these colonized mice under shared-air or co-housing conditions.

What were the most important findings?

Both shared air and physical contact enabled bidirectional microbial transmission between the U.S. and Thai humanized mice. U.S. mucus-degrading taxa such as Akkermansia transferred into Thai microbiomes, while potentially health-promoting Thai-derived bacteria colonized U.S. microbiomes, with the host's baseline microbiome shaping how much remodeling occurred. When exposed to industrialized dietary ingredients and food additives, the U.S. microbiome responded differently than the Thai microbiome, with food additives reducing Akkermansia and the U.S. microbiome showing a predisposition toward weight gain under these dietary conditions.

What are the greatest implications of this study?

The findings suggest that shared living environments, not diet alone, are an underappreciated route by which industrialized-style microbiomes and their metabolic consequences spread between people. Notably, sharing air supply or co-housing with a Thai-derived microbiome mitigated the U.S. microbiome's predisposition toward diet-induced weight gain, pointing to a protective effect of microbial transmission from traditional microbiomes. This implies that interventions aimed at preventing microbiome-related metabolic disease may need to consider household and community-level microbial exposure alongside dietary changes.

What was studied?

UNLABELLED: Mosquito microbiota abundance and composition are modulated by a variety of factors, including pathogen exposure. The microbiome can also influence pathogen infection of the host and thus harbours considerable potential to impact transmission of pathogens. As such, there is a growing interest in using particular bacterial members of the microbiota for novel vector-control strategies. However, before novel microbiota-based approaches can move towards translation, a more complete understanding of the interactions between mosquitoes, their microbiome, and the pathogens they transmit, is required to better appreciate how variation in the microbiome of field mosquitoes affects these interactions. To examine the impact of the mosquito background and the associated diversity of bacterial microbiota within distinct hosts, we exposed several laboratory-reared and field-collected Aedes aegypti mosquito lines to Zika virus (ZIKV) and examined their bacterial load and composition in response to pathogen exposure and viral infection success. Intriguingly, we show that ZIKV exposure and infection had distinct impacts on microbiome composition and density within different mosquito lines. In one laboratory-reared line ZIKV exposure and infection reduced the bacterial load, while conversely in another line load was increased by the virus. Distinct responses of the microbiome were also seen in mosquitoes collected from the field. Sampling site-specific differences in the microbiome of mosquitoes were observed as virus infection altered microbiome alpha and beta diversities in one cohort, while in mosquitoes from other sampling sites, viral progression through the mosquito had minimal effect on the microbiome. We also identified bacterial taxa correlating with either ZIKV infection or a lack of infection. These taxa are potential candidates for future follow-up studies disentangling functional mechanisms and directionality of interactions. Overall, our study highlights that interactions between mosquito, virus, and microbiota are variable and context dependent, and that tripartite interactions among distinct mosquito cohorts and their microbiomes are not universal. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s42523-025-00482-0. The mosquito microbiome composition can vary greatly between individuals and populations. Microbiota profoundly affect pathogen transmission in mosquitoes, while conversely, infection with a pathogen can alter the mosquito microbiome. However, we have a poor understanding of how universally conserved these pathogen-related effects are between mosquito populations. To address this, we infected different lab-reared mosquito lines and examined their microbiomes after exposure to Zika virus (ZIKV) compared to unchallenged mosquitoes. Importantly, we also conducted experiments with field-caught mosquitoes which have markedly different microbiomes compared to their lab-reared counterparts. Here we gave all mosquitoes virus-infected blood meals and compared the microbiomes of individuals that became infected to those that did not. The observed microbiome changes differed between host lines. This could be due to different baseline microbiota in their respective host lines, or differences in the hosts’ response to viral infection which subsequently alters the microbiome in a distinct manner. As members of the microbiota are being evaluated for novel approaches to control mosquito-borne disease, our findings are highly relevant to developing a more complete understanding of host-microbe-pathogen interactions. Variation of the microbiome among different mosquito lines needs to be considered in experimental designs, in the interpretation of infection results, and for the deployment of interventions in the field.

What was studied?

This observational cross-sectional study examined gut microbiota composition and serum inflammatory cytokine levels in people with late-life depression (LLD). The researchers wanted to clarify the relationship between gut microbiota and inflammation in LLD, since diagnosis is complicated by cognitive impairment and clinical features that overlap with adult depression. They analyzed microbiota diversity and composition alongside twelve inflammatory factors, and examined how these related to neuropsychological scale scores. They then used receiver-operating characteristic curve analysis to see whether combining microbiota and cytokine data could yield biomarkers for LLD.

Who was studied?

The study included 29 patients with late-life depression and 33 sex- and age-matched healthy controls. Fecal samples and peripheral blood were collected from all participants to profile gut microbiota and measure the twelve inflammatory factors. The abstract does not provide further demographic or clinical detail beyond this matched case-control design.

What were the most important findings?

Patients with LLD showed elevated systemic inflammatory cytokine levels along with gut microbiota dysbiosis compared with healthy controls. At the phylum level, Verrucomicrobia relative abundance differed in LLD patients, and at the genus level Megamonas, Citrobacter, and Akkermansia abundances were altered. These microbiota and inflammatory changes were evaluated for their relationships to neuropsychological scale scores, and were used to extract potential biomarkers via receiver-operating characteristic curve analysis. The abstract text provided is truncated before the full quantitative results and biomarker performance are given.

What are the greatest implications of this study?

The findings support a combined role for gut microbiota dysbiosis and systemic inflammation in late-life depression, rather than either factor acting alone. Because Verrucomicrobia, Megamonas, Citrobacter, and Akkermansia abundances differed between groups, these taxa may be worth further investigation as candidate biomarkers for LLD. Combining microbiota profiles with inflammatory cytokine measurements could help address the diagnostic challenges that arise when LLD is difficult to distinguish from adult depression due to cognitive impairment. Further work would be needed to validate these biomarkers before any clinical application.

What was studied?

This pilot prospective cohort study examined whether ethnicity influences gut microbiome dysbiosis in pregnancies complicated by gestational diabetes mellitus (GDM). The researchers also investigated whether diet and lifestyle modifications made after a GDM diagnosis could modulate the gut microbiome. Fecal samples were collected at two time points, 24 to 28 weeks and 36 to 40 weeks of gestation, and analyzed using targeted 16S rRNA gene-based amplicon sequencing. Statistical comparisons between groups used PERMANOVA, differential abundance testing used DeSeq2, and functional predictions were generated with PICRUSt2.

Who was studied?

The cohort included 53 women with GDM and 16 women without GDM, all residing in Singapore. Participants belonged to three Asian ethnic groups: Chinese, Malay, and Indian. This design allowed comparison of gut dysbiosis patterns both across GDM status and across ethnic background within the same population.

What were the most important findings?

Among women with GDM, gut microbiomes from the different ethnic groups shared common features rather than diverging by ethnicity. This suggests that GDM-related dysbiosis is a relatively consistent phenomenon across the Chinese, Malay, and Indian groups studied. The abstract indicates that ethnicity was not a major driver of the microbiome differences observed in these GDM pregnancies.

What are the greatest implications of this study?

If GDM-associated gut dysbiosis is largely independent of Asian ethnic background, microbiome-targeted strategies for GDM may generalize across these ethnic groups rather than needing ethnicity-specific approaches. This supports the idea that dietary and lifestyle interventions after a GDM diagnosis could be evaluated and applied similarly across diverse populations. As a pilot study, these findings point to the need for larger cohorts to confirm whether microbiome-based interventions can be standardized across ethnicities.

What was studied?

This study examined how gut microbiota composition differs in children with diarrhea versus children with constipation, compared to healthy children. The researchers used 16S rRNA sequencing on stool samples to profile bacterial communities and looked for microbial diversity changes and specific taxa shifts. They also ran pathway analysis to identify functional mechanisms that might link the two opposite digestive conditions through a shared microbial driver.

Who was studied?

The study included 618 Chinese children aged 0 to 3 years, drawn from a cross-sectional case-control design. Of these, 66 children had diarrhea, 138 had constipation, and 414 were healthy controls. Stool samples were collected from each child for gut microbiota analysis.

What were the most important findings?

Children with diarrhea showed significantly lower gut microbial diversity than healthy controls, while children with constipation showed significantly higher diversity (p < 0.05). Ruminococcus was identified as a key differentiator: it increased in constipation (p = 0.03) and decreased in diarrhea (p < 0.01) relative to healthy children. Pathway analysis linked Ruminococcus to five shared pathways (membrane transport, nervous system, energy metabolism, signal transduction, and endocrine system), suggesting one underlying regulatory mechanism connects both conditions.

What are the greatest implications of this study?

The findings point to Ruminococcus as a core microorganism whose imbalance may disrupt gut steady-state in opposite directions, contributing to either diarrhea or constipation in young children. Because the same genus and overlapping metabolic pathways appear to regulate both conditions, it may serve as a useful reference point for diagnosis. The authors suggest this shared mechanism could inform future treatment approaches that target gut microbial balance rather than treating diarrhea and constipation as unrelated conditions.

What was studied?

This study characterized gastrointestinal microbial communities involved in gastric carcinogenesis by pooling 16S rRNA sequencing data across 11 independent published and open datasets. The researchers compared both intratumoral (gastric biopsy) and fecal microbiota between gastric cancer patients and non-cancer individuals. They used tools including VSEARCH, QIIME, and R packages such as vegan, phyloseq, cooccur, and random forest for diversity analysis, network analysis, and biomarker identification, with PICRUSt used to predict functional pathways.

Who was studied?

The analysis drew on 1,642 gastric biopsy samples and 394 stool samples aggregated across 11 independent studies. The abstract does not give demographic details such as age, sex, or geographic origin of the underlying cohorts. This was a meta-analysis of existing sequencing data rather than a newly recruited single-site cohort.

What were the most important findings?

Alpha-diversity of the intratumoral microbiota differed significantly between gastric cancer patients and non-cancer patients, while fecal microbiota diversity showed no significant difference between groups. Network analysis revealed that positive correlations among gastric cancer-enriched bacteria increased, while positive correlations among gastric cancer-depleted bacteria decreased, compared to healthy individuals. Functional prediction analyses pointed to alterations in pathways related to carbohydrate metabolism, though the abstract text describing these functional results was truncated.

What are the greatest implications of this study?

The findings suggest that local, tumor-site microbial signatures may be more informative for gastric cancer detection than stool-based sampling, since diversity differences were seen intratumorally but not fecally. The shifting co-occurrence network structure around cancer-enriched and cancer-depleted bacteria points to microbial community reorganization as a feature of gastric carcinogenesis. By pooling data across 11 studies, this work moves toward identifying more reproducible microbial markers for early gastric cancer detection across populations.

What was studied?

This study examined whether iron overload in thalassemia patients is linked to gut dysbiosis and cognitive impairment through the gut-brain axis. Researchers assessed iron burden, cognitive function, and both gut and blood microbiome composition across different blood-transfusion regimens. The goal was to determine whether specific microbial shifts track with iron accumulation and cognitive status in this population.

Who was studied?

Sixty participants were recruited, comprising healthy controls, transfusion-dependent thalassemia (TDT) patients, and non-transfusion-dependent thalassemia (NTDT) patients. TDT patients receive more frequent blood transfusions and, consistent with this, showed greater iron overload than NTDT patients. This design allowed comparisons of gut and blood microbiota across a spectrum of iron-overload severity within the same disease population.

What were the most important findings?

Most thalassemia patients developed gut dysbiosis, and about 25% developed minor cognitive impairment. Both TDT and NTDT groups showed increased Fusobacteriota and Verrucomicrobiota with decreased Fibrobacterota, and TDT patients had more abundant Verrucomicrobia, described as beneficial bacteria. Iron overload correlated with cognitive impairment, and increased Butyricimonas with decreased Paraclostridium was associated with higher cognitive function. No blood microbiota was detected, and blood bacterial profiles did not differ significantly between thalassemia patients and controls.

What are the greatest implications of this study?

The findings suggest that iron overload in thalassemia is associated with gut microbial imbalance that may relate to cognitive outcomes through the gut-brain axis. Specific gut taxa such as Butyricimonas and Paraclostridium emerge as candidate markers linked to cognitive function, while the blood compartment appears not to harbor a distinct microbiome signal in this context. This points to the gut, rather than blood, as the more relevant site for future investigation of microbiome-cognition relationships in iron-overloaded thalassemia patients.

What was studied?

This study tested whether a healthy low-carbohydrate diet (HLCD) and time-restricted eating (TRE), alone or combined, affect body weight and the gut microbiome beyond what caloric restriction alone produces. It used a 12-week two-by-two factorial randomized controlled feeding trial with a 28-week follow-up period. The design let researchers isolate the added effects of carbohydrate restriction and eating-window timing on top of isocaloric-restricted feeding.

Who was studied?

The trial enrolled 96 participants with overweight or obesity. Participants were assigned across the two-by-two factorial design to receive isocaloric-restricted feeding with or without HLCD and with or without TRE. The abstract does not give further demographic detail such as age or sex distribution.

What were the most important findings?

Isocaloric-restricted feeding produced significant weight loss ranging from 2.57 to 4.11 kg across groups, and both HLCD and TRE produced additional reductions in body mass index beyond caloric restriction alone. HLCD led to additional fat mass loss, while TRE led to more lean mass loss, showing the two strategies affect body composition differently. HLCD also decreased fecal branched-chain amino acids, and TRE tended to increase the abundance of probiotic species that synthesize short-chain fatty acids. The fat-mass-reducing effect of HLCD persisted through the post-intervention follow-up period.

What are the greatest implications of this study?

The findings suggest that dietary carbohydrate composition and meal timing each add measurable value to weight management beyond simple calorie counting. HLCD and TRE produce distinct effects on body composition (fat versus lean mass) and distinct, profound alterations to the gut microbiome and metabolome. The persistence of HLCD's fat-loss effect after the intervention ended points to potential durability of low-carbohydrate approaches. These results support tailoring weight-management strategies to specific metabolic and microbiome-related goals rather than treating all caloric-restriction approaches as equivalent.

What was studied?

The gut microbiota has emerged as an independent risk factor for diabetes and its complications. This research aimed to delve into the intricate relationship between the gut microbiome and diabetic retinopathy (DR) through a dual approach of cross-sectional and prospective cohort studies. In our cross-sectional study cross-sectional investigation involving ninety-nine individuals with diabetes, distinct microbial signatures associated with DR were identified. Specifically, gut microbiome profiling revealed decreased levels of Butyricicoccus and Ruminococcus torques group, alongside upregulated methanogenesis pathways among DR patients. These individuals concurrently exhibited lower concentrations of short-chain fatty acids in their plasma. Leveraging machine learning models, including random forest classifiers, we constructed a panel of microbial genera and genes that robustly differentiated DR cases. Importantly, these genera also demonstrated significant correlations with dietary patterns and the molecular profiles of peripheral blood mononuclear cells. Building upon these findings, our prospective cohort study followed 62 diabetes patients over a 2-year period to assess the predictive value of these microbial markers. The results underlined the panel's efficacy in predicting DR incidence. By stratifying patients based on the predictive genera and metabolites identified in the cross-sectional phase, we established significant associations between reduced levels of Butyricicoccus, plasma acetate, and increased susceptibility to DR. This investigation not only deepens our understanding of how gut microbiota influences DR but also underscores the potential of microbial markers as early indicators of disease risk. These insights hold promise for developing targeted interventions aimed at mitigating the impact of diabetic complications. KEY POINTS: • Microbial signatures are differed in diabetic patients with and without retinopathy • DR-related taxa are linked to dietary habits and transcriptomic profiles • Lower abundances of Butyricicoccus and acetate were prospectively associated with DR.

What was studied?

Many human-targeted drugs alter the gut microbiome, leading to implications for host health. However, the mechanisms underlying these effects are not well known. Here we combined quantitative microbiome profiling, long-read metagenomics, stable isotope probing and single-cell chemical imaging to investigate the impact of two widely prescribed drugs on the gut microbiome. Physiologically relevant concentrations of entacapone, a treatment for Parkinson's disease, or loxapine succinate, used to treat schizophrenia, were incubated ex vivo with human faecal samples. Both drugs significantly impact microbial activity, more so than microbial abundance. Mechanistically, entacapone can complex and deplete available iron resulting in gut microbiome composition and function changes. Microbial growth can be rescued by replenishing levels of microbiota-accessible iron. Further, entacapone-induced iron starvation selected for iron-scavenging gut microbiome members encoding antimicrobial resistance and virulence genes. These findings reveal the impact of two under-investigated drugs on whole microbiomes and identify metal sequestration as a mechanism of drug-induced microbiome disturbance.

What was studied?

Constipation is a common symptom in maintenance hemodialysis patients and greatly affects the quality of survival of hemodialysis patients. Fecal microbiota transplantation and probiotics are feasible treatments for functional constipation, but there is still a gap in the research on the characteristics of gut flora in patients with maintenance hemodialysis combined with constipation. The aim of this study is to clarify the characteristics of the intestinal flora and its changes in maintenance hemodialysis patients with constipation.

Who was studied?

Fecal samples were collected from 45 participants, containing 15 in the maintenance hemodialysis constipation group,15 in the maintenance hemodialysis non-constipation group and 15 in the healthy control group. These samples were analyzed using 16S rRNA gene sequencing. The feature of the intestinal microbiome of maintenance hemodialysis constipation group and the microbiome differences among the three groups were elucidated by species annotation analysis, α-diversity analysis, β-diversity analysis, species difference analysis, and predictive functional analysis.

What were the most important findings?

The alpha diversity analysis indicated that maintenance hemodialysis constipation group was less diverse and homogeneous than maintenance hemodialysis non-constipation group and healthy control group. At the genus level, the top ten dominant genera in maintenance hemodialysis constipation group patients were Enterococcus, Escherichia-Shigella, Bacteroides, Streptococcus, Bifidobacterium, Ruminococcus_gnavus_group, Lachnospiraceae_unclassified, Faecalibacterium, Akkermansia and UCG-002. Compared with non-constipation group, the Enterococcus, Rhizobiales_unclassified, Filomicrobium, Eggerthella, Allobaculum, Prevotella_7, Gordonibacter, Mitochondria_unclassified, Lachnoanaerobaculum were significantly higher in constipation group (p<0.05). Compared with non-constipation group, the Kineothrix, Rhodopirellula, Weissella were significantly lower in constipation group (p<0.05). The predictive functional analysis revealed that compared with non-constipation group, constipation group was significantly enriched in pathways associated with pyruate metabolism, flavonoid biosynthesis.

What are the greatest implications of this study?

This study describes for the first time the intestinal microbiome characteristics of maintenance hemodialysis patients with constipation. The results of this study suggest that there is a difference in the intestinal flora between maintenance hemodialysis patients with constipation and maintenance hemodialysis patients without constipation.

What was studied?

This study examined the gut microbiome and serum metabolome in patients with functional constipation (FC), a common gastrointestinal disorder that significantly affects physical and mental health. The researchers used 16S rRNA microbial genomics to profile gut microbiota composition and non-target metabolomics based on liquid chromatography-mass spectrometry to characterize serum metabolic profiles. The study was designed to address inconsistent prior findings on the gut microbiome and FC, and to better link microbiome changes to host metabolites.

Who was studied?

The study included 30 patients with functional constipation and 28 healthy individuals as a comparison group. Fecal samples were used for 16S rRNA gut microbiota analysis and serum samples were used for metabolomic profiling in these participants. The abstract does not specify additional demographic details such as age or sex distribution.

What were the most important findings?

FC patients had distinct gut microbiota structures and serum metabolic profiles compared to healthy individuals. Patients with FC showed increased levels of Bacteroides and of several butyrate-producing bacteria, including Roseburia, Faecalibacterium, and Butyricicoccus. Serum levels of upstream products of host arginine biosynthesis, specifically 2-oxoglutaric acid, L-glutamic acid, N-acetylornithine, and L-ornithine, were significantly reduced in FC patients.

What are the greatest implications of this study?

The findings suggest that functional constipation may be associated with an altered gut microbiota, including increased Bacteroidetes, alongside downregulation of host arginine biosynthesis intermediates. This points to a potential link between specific gut bacteria and disrupted host amino acid metabolism in FC. The pairing of microbiome and metabolome data offers a more integrated view of FC pathophysiology than microbiome data alone, which could inform future mechanistic or therapeutic research.

What was studied?

Polycystic ovary syndrome (PCOS) is an endocrine and metabolic disorder characterized by chronic low-grade inflammation. Previous studies have demonstrated that the gut microbiome can affect the host tissue cells' mRNA N6-methyladenosine (m6A) modifications. This study aimed to understand the role of intestinal flora in ovarian cells inflammation by regulating mRNA m6A modification particularly the inflammatory state in PCOS. The gut microbiome composition of PCOS and Control groups was analyzed by 16S rRNA sequencing, and the short chain fatty acids were detected in patients' serum by mass spectrometry methods. The level of butyric acid was found to be decreased in the serum of the obese PCOS group (FAT) compared to other groups, and this was correlated with increased Streptococcaceae and decreased Rikenellaceae based on the Spearman's rank test. Additionally, we identified FOSL2 as a potential METTL3 target using RNA-seq and MeRIP-seq methodologies. Cellular experiments demonstrated that the addition of butyric acid led to a decrease in FOSL2 m6A methylation levels and mRNA expression by suppressing the expression of METTL3, an m6A methyltransferase. Additionally, NLRP3 protein expression and the expression of inflammatory cytokines (IL-6 and TNF-α) were downregulated in KGN cells. Butyric acid supplementation in obese PCOS mice improved ovarian function and decreased the expression of local inflammatory factors in the ovary. Taken together, the correlation between the gut microbiome and PCOS may unveil crucial mechanisms for the role of specific gut microbiota in the pathogenesis of PCOS. Furthermore, butyric acid may present new prospects for future PCOS treatments.

What was studied?

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.

Who was studied?

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.

What were the most important findings?

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.

What are the greatest implications of this study?

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.

What was studied?

The relationship between intestinal microbiome and colorectal cancer (CRC) progression is unclear. This study aims to identify the intestinal microbiome associated with CRC progression and construct predictive labels to support the accurate assessment and treatment of CRC.

Who was studied?

The 192 patients included in the study were divided into stage I-II and stage III-IV CRC patients according to the pathological stages, and preoperative stools were collected from both groups for 16S rDNA sequencing of the intestinal microbiota. Pearson correlation and Spearman correlation coefficient analysis were used to analyze the differential intestinal microbiome and the correlation with tumor microenvironment and to predict the functional pathway. XGBoost model (XGB) and Random Forest model (RF) were used to construct the microbiome-based signature. The total RNA extraction from 17 CRC tumor simples was used for transcriptome sequencing.

What were the most important findings?

The Simpson index of intestinal microbiome in stage III-IV CRC were significantly lower than those in stage I-II CRC. Proteus, Parabacteroides, Alistipes and Ruminococcus etc. are significantly enriched genus in feces of CRC patients with stage III-IV. ko00514: Other types of O - glycan biosynthesis pathway is relevant with CRC progression. Alistipes indistinctus was positively correlated with mast cells, immune activators IL-6 and IL6R, and GOBP_PROTEIN_FOLDING_IN_ENDOPLASMIC_RETICULUM dominantly. The Random Forest (RF) model and eXtreme Gradient Boosting (XGBoost) model constructed with 42 CRC progression-associated differential bacteria were effective in distinguishing CRC patients between stage I-II and stage III-IV.

What are the greatest implications of this study?

The abundance and diversity of intestinal microbiome may increase gradually with the occurrence and progression of CRC. Elevated fetal abundance of Proteus, Parabacteroides, Alistipes and Ruminococcus may contribute to CRC progression. Enhanced synthesis of O - glycans may result in CRC progression. Alistipes indistinctus may play a facilitated role in mast cell maturation by boosting IL-6 production. Alistipes indistinctus may work in the correct folding of endoplasmic reticulum proteins in CRC, reducing ER stress and prompting the survival and deterioration of CRC, which may owe to the enhanced PERK expression and activation of downstream UPR by Alistipes indistinctus. The CRC progression-associated differential intestinal microbiome identified in our study can be served as potential microbial markers for CRC staging prediction.

What was studied?

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.

Who was studied?

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.

What were the most important findings?

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.

What are the greatest implications of this study?

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.

What was studied?

This study examined the uterine microbiome of post-partum dairy cows using deep shotgun metagenomic sequencing. Researchers compared microbial ecology and diversity in cows with metritis, purulent vaginal discharge, and no disease. The goal was to characterize taxonomic composition and identify differences in community structure associated with metritis.

Who was studied?

The study drew on intrauterine swab samples from post-partum dairy cows across 24 commercial California dairy farms. A subset of 95 samples was analyzed out of a larger collection of 307 individual cow samples. Cows within 21 days post-partum were classified into three clinical groups: control (n = 32), metritis (n = 33), and purulent discharge (n = 31), based on the appearance and odor of vaginal discharge.

What were the most important findings?

All three clinical groups showed highly diverse uterine microbial communities, with the top 12 most abundant genera accounting for only about 8.8 to 10.3 percent of mean relative abundance across groups. Alpha diversity was lower in samples from cows with metritis and purulent discharge compared to control cows. PERMANOVA testing showed a statistically significant difference in overall microbial community composition (beta diversity) between groups.

What are the greatest implications of this study?

The findings suggest that uterine disease states in post-partum dairy cows are associated with reduced microbial diversity rather than dominance by a single pathogen, reflecting a broader ecological shift in the uterine environment. Deep shotgun sequencing offers a more complete picture of this community than earlier culture-based or amplicon-based approaches. These results could inform future work on diagnosing and managing metritis through microbiome-based markers rather than single-organism detection.

What was studied?

Microbiomes have immunoregulatory functions and may be involved in the pathophysiology of eye diseases. However, the effects of microbiomes on uveitic glaucoma (UG) and open-angle glaucoma (OAG) have not been sufficiently investigated. This study analysed differences in eyelid and buccal microbiomes between UG and OAG using metagenomic technology.

Who was studied?

Eyelid and buccal specimens were collected from 34 UG and 62 OAG patients. The taxonomic composition of the microbiome was determined via 16S rRNA gene sequencing, operational taxonomic unit analysis and diversity analysis. Differential gene expression analysis (DEG) and principal component analyses (PCoA) determined taxon differences between the microbiomes of the UG and OAG patients. Subgroup analysis according to age and baseline IOP was performed.

What were the most important findings?

There was no significant difference in alpha-diversity between the microbiomes of UG and OAG patients. Further, PCoA revealed no differences in eyelid microbiome between the UG and OAG groups, but significant differences were found in buccal microbiome between the groups, especially in a subgroup of OAG patients with normal IOP. DEG analysis of the eyelid microbiome revealed various taxa differences, including the enrichment of Rhodococcus in UG samples over OAG samples. Taxa such as Lactobacillus and Proteus were significantly depleted (q-value = 9.98e-6 and q-value = 1.38 × 10-4 , respectively) in the buccal microbiome of UG patients, whereas Enterococcus was enriched (q-value = 5.26e-5 ).

What are the greatest implications of this study?

This study showed that the buccal microbiome in UG differs from that in OAG; reduced Lactobacillus was observed in UG. These results suggest that apart than OAG, microbiome composition may be a factor in the pathogenesis of UG.

What was studied?

The microbiome could trigger inflammation leading to epigenetic changes and is involved in the pathophysiology of eye diseases; however, its effect on uveitic glaucoma (UG) has not been fully investigated. This study analysed the differences in eyelid and buccal microbiomes in patients with UG using next-generation sequencing.

Who was studied?

The eyelid and buccal specimens of 34 UG and 25 control patients were collected. The taxonomic composition of the microbiome was obtained via 16S ribosomal DNA sequencing. Diversity and differential gene expression analyses (DEG) determined taxon differences between the microbiomes of UG and control groups.

What were the most important findings?

In both the eyelid and buccal microbiomes, alpha-diversity was lower in UG patients than controls, while beta-diversity in patients with UG was higher than in controls. DEG analysis of the eyelid microbiome revealed various taxa differences, including enrichment of Paenibacillus and Dermacoccus (p-value, 1.31e-6 and 1.55e-7, respectively) and depletion of Morganella and Lactococcus (p-value, 6.26e-12 and 2.55e-6, respectively) in patients with UG. In the buccal microbiome, taxa such as Lactococcus was significantly depleted (p-value, 1.31e-17), whereas Faecalibacterium was enriched in patients with UG (p-value, 6.12e-8).

What are the greatest implications of this study?

The eyelid and buccal microbiomes in patients with UG differ from controls, which raises concerns surrounding environmental influences on the pathogenesis of UG. The reduced Lactococcus in the eyelid and buccal area suggest that microbiota dysbiosis is associated with UG.

What was studied?

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.

Who was studied?

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.

What were the most important findings?

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.

What are the greatest implications of this study?

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.

What was studied?

The microbial population of the intestinal tract and its relationship to specific diseases has been extensively studied during the past decade. However, reports characterizing the bile microbiota are rare. This study aims to investigate the microbiota composition in patients with pancreaticobiliary cancers and benign diseases by 16S rRNA gene amplicon sequencing and to evaluate its potential value as a biomarker for the cancer of the bile duct, pancreas, and gallbladder.

What were the most important findings?

We enrolled patients who were diagnosed with cancer, cystic lesions, and inflammation of the pancreaticobiliary tract. The study cohort comprised 244 patients. We extracted microbiome-derived DNA from the bile juice in surgically resected gallbladders. The microbiome composition was not significantly different according to lesion position and cancer type in terms of alpha and beta diversity. We found a significant difference in the relative abundance of Campylobacter, Citrobacter, Leptotrichia, Enterobacter, Hungatella, Mycolicibacterium, Phyllobacterium and Sphingomonas between patients without and with lymph node metastasis.

What are the greatest implications of this study?

There was a significant association between the relative abundance of certain microbes and overall survival prognosis. These microbes showed association with good prognosis in cholangiocarcinoma, but with poor prognosis in pancreatic adenocarcinoma, and vice versa. Our findings suggest that pancreaticobiliary tract cancer patients have an altered microbiome composition, which might be a biomarker for distinguishing malignancy.

What was studied?

Altered gut microbiome (GM) composition has been established in Parkinson's disease (PD). However, few studies have longitudinally investigated the GM in PD, or the impact of device-assisted therapies. To investigate the temporal stability of GM profiles from PD patients on standard therapies and those initiating device-assisted therapies (DAT) and define multivariate models of disease and progression.

Who was studied?

We evaluated validated clinical questionnaires and stool samples from 74 PD patients and 74 household controls (HCs) at 0, 6, and 12 months. Faster or slower disease progression was defined from levodopa equivalence dose and motor severity measures. 19 PD patients initiating Deep Brain Stimulation or Levodopa-Carbidopa Intestinal Gel were separately evaluated at 0, 6, and 12 months post-therapy initiation.

What were the most important findings?

Persistent underrepresentation of short-chain fatty-acid-producing bacteria, Butyricicoccus, Fusicatenibacter, Lachnospiraceae ND3007 group, and Erysipelotrichaceae UCG-003, were apparent in PD patients relative to controls. A sustained effect of DAT initiation on GM associations with PD was not observed. PD progression analysis indicated that the genus Barnesiella was underrepresented in faster progressing PD patients at t = 0 and t = 12 months. Two-stage predictive modeling, integrating microbiota abundances and nutritional profiles, improved predictive capacity (change in Area Under the Curve from 0.58 to 0.64) when assessed at Amplicon Sequence Variant taxonomic resolution.

What are the greatest implications of this study?

We present longitudinal GM studies in PD patients, showing persistently altered GM profiles suggestive of a reduced butyrogenic production potential. DATs exerted variable GM influences across the short and longer-term. We found that specific GM profiles combined with dietary factors improved prediction of disease progression in PD patients.

What was studied?

This observational study examined the gut microbiota and host immune response in elderly patients with schizophrenia compared to healthy controls. Researchers used 16S rRNA gene sequencing targeting the V3-V4 region to profile fecal bacterial communities. They then correlated these microbial profiles with measures of host immune function, including circulating cytokine levels.

Who was studied?

The study included 161 fecal samples total, comprising 90 samples from elderly patients with schizophrenia and 71 samples from healthy controls. The abstract identifies the population as Chinese elderly individuals, consistent with the study title. No further demographic details are provided in the abstract.

What were the most important findings?

Beta-diversity analysis separated schizophrenia patients and healthy controls into two distinct bacterial community clusters. Linear discriminant analysis effect size (LEfSe) identified compositional shifts in several genera associated with schizophrenia, including Faecalibacterium, Roseburia, Actinomyces, Butyricicoccus, and Prevotella. Alongside these microbial changes, pro-inflammatory cytokines such as IL-1β were markedly elevated in patients, while anti-inflammatory cytokines such as IFN-γ were markedly reduced. Correlation analysis linked these specific bacterial taxa to the observed immune disturbances.

What are the greatest implications of this study?

The findings support a link between gut dysbiosis and immune dysfunction in elderly patients with schizophrenia. The identified bacteria correlated with inflammatory markers could serve as non-invasive biomarkers for this population. This suggests the gut microbiome and host immune signaling may be relevant targets for understanding or monitoring schizophrenia in older adults.

What was studied?

A link between the gut microbiome and Parkinson's disease (PD) has been intensively studied, and more than 100 differential genera were identified across the studies. However, the predominant genera contributing to PD remain poorly understood. Inspired by recent advances showing microbiota distribution in the blood and brain, we, here, comprehensively investigated currently available fecal microbiome data (1,914 samples) to identify significantly altered genera, which were further validated by comparison to the results from microbiome analysis of blood (85 samples) and brain (268 samples). Our data showed that the composition of fecal microbiota was different from that of blood and brain. We found that Blautia was the unique genus consistently depleted across feces, blood, and brain samples of PD patients (P < 0.05), despite using rigorous criteria to remove contaminants. Moreover, enrichment analyses revealed that host genes correlated with Blautia genus abundance were mainly involved in mitochondrial function and energy metabolism, and mapped to neurodegenerative diseases (NDDs) and metabolic diseases. A random forest classifier constructed with fecal microbiota data demonstrated that Blautia genus was an important feature contributing to discriminating PD patients from controls [receiver operating characteristic (ROC)-area under curve (AUC) = 0.704, precision-recall curve (PRC)-AUC = 0.787]. Through the integration of microbiome and transcriptome, our study depicted microbial profiles in the feces, blood, and brain of PD patients, and identified Blautia genus as a potential genus linked to PD. Further studies are greatly encouraged to determine the role of Blautia genus in the pathogenesis of PD.

What was studied?

The purpose of this study was to elucidate the characteristics of the gut microbiome in patients with Polycystic ovary syndrome (PCOS) and analyze the alterations of fecal fatty acid metabolism, so as to further provide the pathogenesis of PCOS.

Who was studied?

Fecal samples from the PCOS group (n = 31) and healthy control group (n = 27) were analyzed by 16S rRNA gene sequencing and untargeted metabolomics. Peripheral venous blood was collected to measure serum inflammation and intestinal permeability. Finally, the correlation analysis of intestinal flora, fecal metabolites, and laboratory indicators was carried out.

What were the most important findings?

Serum D-lactate content in the PCOS group was higher than that in the control group. There was no significant difference in microbial α diversity and β diversity between PCOS patients and healthy controls. Peptostreptococcaceae and Bacteroidales S24-7 group existed significant differences between PCOS patients and healthy controls. Based on linear discriminant analysis selection, 14 genera including Klebsiella, Enterobacteriaceae, and Gammaproteobacteria were dominant in patients with PCOS, while 4 genera, including rumenococcus (Ruminocaccaceae UCG 013), prewortella (Prevotellaceae UCG 001), and erysipelas (Erysipelatoclostridium), were dominant in healthy controls. Compared with PCOS with Body mass index (BMI) < 24, patients with BMI ≥ 24 have multiple dominant genera including Abiotrophia and Peptostreptococcaceae. Moreover, serum levels of free testosterone and androstenedione were positively correlated with Megamonas, while total testosterone was negatively correlated with Alistipes. Additionally, fecal contents of acetic acid and propionic acid in patients with PCOS were significantly higher than those in healthy controls. Eubacterium_coprostanoligenes_group and Alistipes were positively correlated with 6 kinds of fatty acids.

What are the greatest implications of this study?

Specific intestinal flora fecal fatty acids and serum metabolites may mediate the occurrence and development of PCOS. PCOS patients with different body sizes have specific intestinal flora.

What was studied?

CKD is characterized by a sustained proinflammatory response of the immune system, promoting hypertension and cardiovascular disease. The underlying mechanisms are incompletely understood but may be linked to gut dysbiosis. Dysbiosis has been described in adults with CKD; however, comorbidities limit CKD-specific conclusions.

Who was studied?

We analyzed the fecal microbiome, metabolites, and immune phenotypes in 48 children (with normal kidney function, CKD stage G3-G4, G5 treated by hemodialysis [HD], or kidney transplantation) with a mean±SD age of 10.6±3.8 years.

What were the most important findings?

Serum TNF-α and sCD14 were stage-dependently elevated, indicating inflammation, gut barrier dysfunction, and endotoxemia. We observed compositional and functional alterations of the microbiome, including diminished production of short-chain fatty acids. Plasma metabolite analysis revealed a stage-dependent increase of tryptophan metabolites of bacterial origin. Serum from patients on HD activated the aryl hydrocarbon receptor and stimulated TNF-α production in monocytes, corresponding to a proinflammatory shift from classic to nonclassic and intermediate monocytes. Unsupervised analysis of T cells revealed a loss of mucosa-associated invariant T (MAIT) cells and regulatory T cell subtypes in patients on HD.

What are the greatest implications of this study?

Gut barrier dysfunction and microbial metabolite imbalance apparently mediate the proinflammatory immune phenotype, thereby driving the susceptibility to cardiovascular disease. The data highlight the importance of the microbiota-immune axis in CKD, irrespective of confounding comorbidities.

What was studied?

This study examined the early-life gut microbiota of term small for gestational age (SGA) infants compared with appropriate for gestational age (AGA) infants. Fecal samples were collected on days 1, 3, 5, and 7 of life and analyzed using 16S ribosomal DNA amplicon sequencing. The researchers then followed the SGA infants for 6 months to assess whether early gut microbiota characteristics related to neurodevelopmental outcomes. The work was motivated by prior evidence that gut microbiota in early life can influence later neurodevelopment, a relationship that had been little studied in SGA populations specifically.

Who was studied?

A total of 162 term neonates born at Peking University First Hospital between June 2020 and June 2021 were enrolled. Of these, 41 infants (25.3%) were classified as SGA and made up the study group, while 121 infants (74.7%) were classified as AGA and served as the control group. Neurodevelopmental outcomes at 6 months were assessed among the SGA infants using the Ages and Stages Questionnaires-3 (ASQ-3).

What were the most important findings?

Gut microbial diversity was consistently lower in the SGA group than in the AGA group on days 1, 3, 5, and 7 after birth. Non-metric multidimensional scaling and analysis of similarities showed significant differences in the overall composition of the gut microbiota between the two groups. These findings indicate that being born small for gestational age is associated with a distinct and less diverse early gut microbial community from the first days of life.

What are the greatest implications of this study?

The findings support the idea that SGA status shapes the gut microbiota from the earliest days of life, in a pattern distinguishable from AGA infants. Because the study also tracked neurodevelopment at 6 months using the ASQ-3, it points toward the gut microbiota as a possible early biological marker linked to the neurodevelopmental risks already known to affect SGA infants. This underscores the value of monitoring gut microbiota composition in SGA newborns as a potential avenue for identifying infants who may benefit from closer developmental follow-up.

What was studied?

Post-cholecystectomy diarrhea (PCD) frequently occurs in patients following gallbladder removal. PCD is part of the post-cholecystectomy (PC) syndrome, and is difficult to treat. After cholecystectomy, bile enters the duodenum directly, independent of the timing of meals. The interaction between the bile acids and the intestinal microbes is changed. Therefore, the occurrence of PCD may be related to the change in microbiota. However, little is known about the relationship between the gut microbiota and PCD. To better understand the role of the gut microbiota in PCD patients.

Who was studied?

Fecal DNA was isolated. The diversity and profiles of the gut microbiota were analyzed by performing high-throughput 16S rRNA gene sequencing. The gut microbiota were characterized in a healthy control (HC) group and a PC group. Subsequently, the PC group was further divided into a PCD group and a post-cholecystectomy non-diarrhea group (PCND) according to the patients' clinical symptoms. The composition, diversity and richness of microbial communities were determined and compared.

What were the most important findings?

In the PC and HC groups, 720 operational taxonomic units (OTUs) were identified. The PC group had fewer OTUs than the HC group. β-diversity was decreased in the PC group. This indicated decreased microbial diversity in the PC group. Fifteen taxa with differential abundance between the HC and PC groups were identified. In the PCD group compared to the PCND group, significant decreases in microbial diversity, Firmicutes/Bacteroidetes ratio, and richness of probiotic microbiota (Bifidobacterium and Lactococcus), and an increase in detrimental microbiota (Prevotella and Sutterella) were observed. Moreover, a negative correlation was found between Prevotella and Bifidobacterium. Using a Kyoto Encyclopedia of Genes and Genomes functional analysis, it was found that the abundances of gut microbiota involved in lipid metabolism pathways were markedly lower in the PCD group compared to the PCND group.

What are the greatest implications of this study?

This study demonstrated that gut dysbiosis may play a critical role in PCD, which provides new insights into therapeutic options for PCD patients.

What was studied?

This study examined the gut microbiota of patients with COVID-19 pneumonia using 16S rRNA gene sequencing performed on rectal swabs. Researchers compared microbial composition and diversity between patients treated in the intensive care unit (i-COVID19), patients treated in infectious disease wards (w-COVID19), and healthy controls (CTRL). The goal was to characterize how gut microbial communities differ across varying levels of COVID-19 disease severity.

Who was studied?

The study population consisted of patients hospitalized with COVID-19 pneumonia, divided into two groups by care setting: those admitted to the intensive care unit and those managed in infectious disease wards. These two patient groups were compared against a control group without COVID-19. The abstract does not report exact sample sizes, ages, or other demographic details for these cohorts.

What were the most important findings?

Patients in the ICU showed a decrease in the Chao1 index compared to both controls and ward patients, indicating lower microbial richness in the most severely ill patients, while the Shannon index showed no significant change. At the phylum level, ward patients showed an increase in Proteobacteria compared to controls. Fusobacteria and Spirochetes were both decreased relative to controls, with Spirochetes showing the greatest decrease in ICU patients specifically.

What are the greatest implications of this study?

The findings indicate that gut microbial communities shift in composition and richness according to COVID-19 disease severity, with the most pronounced changes occurring in critically ill ICU patients. These preliminary results suggest the gut microbiota may hold promising biomarkers for diagnosing COVID-19 and gauging disease severity. The authors note that validation in larger cohorts could support using microbiota profiles to help stratify patients by severity.

What was studied?

Autism spectrum disorders (ASDs) are a set of complex neurobiological disorders. Growing evidence has shown that the microbiota that resides in the gut can modulate brain development via the gut-brain axis. However, direct clinical evidence of the role of the microbiota-gut-brain axis in ASD is relatively limited.

Who was studied?

A case-control study of 71 boys with ASD and 18 neurotypical controls was conducted at China-Japan Friendship Hospital. Demographic information and fecal samples were collected, and the gut microbiome was evaluated and compared by 16S ribosomal RNA gene sequencing and metagenomic sequencing.

What were the most important findings?

A higher abundance of operational taxonomic units (OTUs) based on fecal bacterial profiling was observed in the ASD group. Significantly different microbiome profiles were observed between the two groups. At the genus level, we observed a decrease in the relative abundance of Escherichia, Shigella, Veillonella, Akkermansia, Provindencia, Dialister, Bifidobacterium, Streptococcus, Ruminococcaceae UCG_002, Megasphaera, Eubacterium_coprostanol, Citrobacter, Ruminiclostridium_5, and Ruminiclostridium_6 in the ASD cohort, while Eisenbergiella, Klebsiella, Faecalibacterium, and Blautia were significantly increased. Ten bacterial strains were selected for clinical discrimination between those with ASD and the neurotypical controls. The highest AUC value of the model was 0.947.

What are the greatest implications of this study?

Significant differences were observed in the composition of the gut microbiome between boys with ASD and neurotypical controls. These findings contribute to the knowledge of the alteration of the gut microbiome in ASD patients, which opens the possibility for early identification of this disease.

What was studied?

This study examined whether gut microbiota composition is associated with fever in patients with moderate COVID-19. Researchers compared clinical features and laboratory results between patients with and without fever, and identified inflammatory markers linked to fever. They then conducted a gut metagenome-wide association study to characterize the microbes and microbial epitopes potentially involved in fever and hyperinflammation.

Who was studied?

The cohort included 187 patients with moderate COVID-19, of whom 127 (67.9 percent) presented with fever and the remainder did not. A subset of 31 individuals from this group underwent gut metagenome-wide association analysis to identify microbial features linked to fever and hyperinflammation. The abstract does not provide further demographic details such as age or sex distribution.

What were the most important findings?

Patients with fever showed significantly reduced lymphocytes, CD3+ T cells, CD4+ T cells, and CD4+ to CD8+ T cell ratios, alongside significantly elevated AST, LDH, CRP, IL-6, and IL-10. Gut microbiome composition differed significantly between patients with fever and those without. Opportunistic pathogens, including Enterococcus faecalis and Saccharomyces cerevisiae, were enriched in patients with fever, and E. faecalis abundance was positively correlated with LDH and D-dimer levels.

What are the greatest implications of this study?

These findings suggest that gut microbiota dysbiosis, particularly enrichment of opportunistic pathogens such as Enterococcus faecalis, may be linked to the abnormal immune responses and inflammation seen in febrile moderate COVID-19 patients. This raises the possibility that gut microbes or their components contribute to fever and hyperinflammation in this population. The results point to gut microbiota as a potential area of interest for understanding COVID-19 severity and prognosis in moderate cases.

What was studied?

Patients with COVID-19 have been reported to experience gastrointestinal symptoms as well as respiratory symptoms, but the effects of COVID-19 on the gut microbiota are poorly understood. We explored gut microbiome profiles associated with the respiratory infection of SARS-CoV-2 during the recovery phase in patients with asymptomatic or mild COVID-19. A longitudinal analysis was performed using the same patients to determine whether the gut microbiota changed after recovery from COVID-19. We applied 16S rRNA amplicon sequencing to analyze two paired fecal samples from 12 patients with asymptomatic or mild COVID-19. Fecal samples were selected at two time points: during SARS-CoV-2 infection (infected state) and after negative conversion of the viral RNA (recovered state). We also compared the microbiome data with those from 36 healthy controls. Microbial evenness of the recovered state was significantly increased compared with the infected state. SARS-CoV-2 infection induced the depletion of Bacteroidetes, while an abundance was observed with a tendency to rapidly reverse in the recovered state. The Firmicutes/Bacteroidetes ratio in the infected state was markedly higher than that in the recovered state. Gut dysbiosis was observed after infection even in patients with asymptomatic or mild COVID-19, while the composition of the gut microbiota was recovered after negative conversion of SARS-CoV-2 RNA. Modifying intestinal microbes in response to COVID-19 might be a useful therapeutic alternative.

What was studied?

Preclinical studies have shown that the gut microbiota can play a role in schizophrenia (SCH) pathogenesis via the gut-brain axis. However, its role in the antipsychotic treatment response is unclear. Here, we present a 24-week follow-up study to identify gut microbial biomarkers for SCH diagnosis and treatment response, using a sample of 107 first-episode, drug-naïve SCH patients, and 107 healthy controls (HCs). We collected biological samples at baseline (all participants) and follow-up time points after risperidone treatment (SCH patients). Treatment response was assessed using the Positive and Negative Symptoms Scale total (PANSS-T) score. False discovery rate was used to correct for multiple testing. We found that SCH patients showed lower α-diversity (the Shannon and Simpson's indices) compared to HCs at baseline (p = 1.21 × 10-9, 1.23 × 10-8, respectively). We also found a significant difference in β-diversity between SCH patients and HCs (p = 0.001). At baseline, using microbes that showed different abundance between patients and controls as predictors, a prediction model can distinguish patients from HCs with an area under the curve (AUC) of 0.867. In SCH patients, after 24 weeks of risperidone treatment, we observed an increase of α-diversity toward the basal level of HCs. At the genus level, we observed decreased abundance of Lachnoclostridium (p = 0.019) and increased abundance Romboutsia (p = 0.067). Moreover, the treatment response in SCH patients was significantly associated with the basal levels of Lachnoclostridium and Romboutsia (p = 0.005 and 0.006, respectively). Our results suggest that SCH patients may present characteristic microbiota, and certain microbiota biomarkers may predict treatment response in this patient population.

What was studied?

Small intestinal bacterial overgrowth (SIBO) has been proposed as an etiologic factor in irritable bowel syndrome, particularly the diarrhea-predominant subtype (IBS-D). We aimed to identify potential intestinal microbial pattern in IBS-D patients with SIBO.

Who was studied?

Diarrhea-predominant irritable bowel syndrome patients fulfilling Rome III criteria were recruited and randomly divided into an exploratory cohort (57 cases) and a validation cohort (20 cases). SIBO was identified according to standard glucose hydrogen breath test. For 16S rRNA gene sequencing, samples of duodenal mucosa, duodenal fluid, rectal mucosa, and fresh feces were collected and performed. The α and β diversity, as well as differences in microbial composition and function, in SIBO+ and SIBO- IBS-D subjects were evaluated.

What were the most important findings?

The microbial diversity and composition obviously differed between SIBO+ and SIBO- IBS-D in duodenal and rectal mucosa but not in duodenal fluid and fresh feces. For rectal mucosal microbiota, it displayed markedly reduced aerobe and Gram-negative bacteria and increased facultative anaerobe and Gram-positive bacteria, moreover, altered functions of microbial metabolism in SIBO+ IBS-D. Significantly higher rectal mucosa-related microbial dysbiosis index was observed in SIBO+ IBS-D, and a cut-off value at -0.37 had a sensitivity of 56.55% and specificity of 90.91% to identify the SIBO in IBS-D subjects.

What are the greatest implications of this study?

Mucosal microbiota, rather than luminal bacteria, has a more apparent dysbiosis in SIBO+ IBS-D patients relative to those without SIBO. Rectal mucosa-associated microbiota may act as a potential predictor of SIBO in IBS-D patients.

What was studied?

Temperature is important to determine physiological status of ectotherms. However, it is still not fully understood how amphibians and their symbiotic microbiota acclimate to ambient temperature. In this study, we investigated the changes of gut microbiota of Xenopus tropicalis at different temperatures under controlled laboratory conditions. The results showed that microbial communities were distinct and shared only a small overlap among froglet guts, culture water and food samples. Furthermore, the dominant taxa harbored in the gut exhibited low relative abundance in water and food. It indicates that bacterial taxa selected by amphibian gut were generally of low abundance in the external environment. Temperature could affect beta-diversity of gut microbiota in terms of phylogenetic distance, but it did not affect alpha diversity. The composition of gut microbiota was similar in warm and cool treatments. However, signature taxa in different temperature environments were identified. The relationships between temperature, gut microbiota and morphology traits of X. tropicalis revealed in this study help us to predict the consequences of environmental changes on ectothermic animals.

What was studied?

The roles of gut microbiota on the natural course of atopic dermatitis (AD) are not yet fully understood. We investigated whether the composition and function of gut microbiota and short-chain fatty acids (SCFAs) at 6 months of age could affect the natural course of AD up to 24 months in early childhood.

Who was studied?

Fecal samples from 132 infants were analyzed using pyrosequencing, including 84 healthy controls, 22 transient AD and 26 persistent AD subjects from the Cohort for Childhood Origin of Asthma and Allergic Diseases (COCOA) birth cohort. The functional profile of the gut microbiome was analyzed by whole-metagenome sequencing. SCFAs were measured using gas chromatography-mass spectrometry.

What were the most important findings?

Low levels of Streptococcus and high amounts of Akkermansia were evident in transient AD cases, and low Clostridium, Akkermansia and high Streptococcus were found in children with persistent AD. The relative abundance of Streptococcus positively correlated with scoring of AD (SCORAD) score, whereas that of Clostridium negatively correlated with SCORAD score. The persistent AD group showed decreased gut microbial functional genes related to oxidative phosphorylation compared with healthy controls. Butyrate and valerate levels were lower in transient AD infants compared with healthy and persistent AD infants.

What are the greatest implications of this study?

Compositions, functions and metabolites of the early gut microbiome are related to natural courses of AD in infants.

What was studied?

The meconium microbiome may provide insight into intrauterine and peripartum exposures and the very earliest intestinal pioneering microbes. Prenatal antibiotics have been associated with later obesity in children, which is thought to be driven by microbiome dependent mechanisms. However, there is little data regarding associations of prenatal or peripartum antibiotic exposure, with or without cesarean section (CS), with the features of the meconium microbiome. In this study, 16S ribosomal RNA gene sequencing was performed on bacterial DNA of meconium samples from 105 infants in a birth cohort study. After multivariable adjustment, delivery mode (p = 0.044), prenatal antibiotic use (p = 0.005) and peripartum antibiotic use (p < 0.001) were associated with beta diversity of the infant meconium microbiome. CS (vs. vaginal delivery) and peripartum antibiotics were also associated with greater alpha diversity of the meconium microbiome (Shannon and Simpson, p < 0.05). Meconium from infants born by CS (vs. vaginal delivery) had lower relative abundance of the genus Escherichia (p < 0.001). Prenatal antibiotic use and peripartum antibiotic use (both in the overall analytic sample and when restricting to vaginally delivered infants) were associated with differential abundance of several bacterial taxa in the meconium. Bacterial taxa in the meconium microbiome were also differentially associated with infant excess weight at 12 months of age, however, sample size was limited for this comparison. In conclusion, prenatal and peripartum antibiotic use along with CS delivery were associated with differences in the diversity and composition of the meconium microbiome. Whether or not these differences in the meconium microbiome portend risk for long-term health outcomes warrants further exploration.

What was studied?

This study investigated the composition of the gut microbiome in renal transplant recipients (RTRs) and compared it with that of healthy controls. The researchers used 16S rRNA sequencing of fecal samples to characterize microbiome composition and diversity. They then applied multivariate association with linear models (MaAsLin) to identify clinical and pharmacological determinants of the gut microbiome in RTRs, including immunosuppressive drugs and antibiotic exposure.

Who was studied?

The study included 139 renal transplant recipients (50% male, mean age 58.3 plus or minus 12.8 years) and 105 healthy controls (57% male, mean age 59.2 plus or minus 10.6 years), all participants in the TransplantLines Biobank and Cohort Study (NCT03272841). The median time since transplantation among RTRs was 6.0 years, with a range of 1.5 to 12.5 years. Fecal samples were collected from both groups for microbiome analysis.

What were the most important findings?

The gut microbiome composition of RTRs was significantly different from that of healthy controls, and RTRs had significantly lower gut microbiome diversity (p less than 0.01). Proton-pump inhibitors, mycophenolate mofetil, and estimated glomerular filtration rate (eGFR) were identified as significant determinants of the gut microbiome in RTRs (p less than 0.05). These findings point to specific medications and kidney function as key factors shaping post-transplant dysbiosis, rather than transplantation alone.

What are the greatest implications of this study?

The findings indicate that renal transplant recipients experience measurable intestinal dysbiosis linked to specific modifiable factors, particularly proton-pump inhibitor use and mycophenolate mofetil therapy. This suggests that clinicians managing RTRs might consider the gut microbiome impact of routine medication choices as part of post-transplant care. Further research could explore whether adjusting these determinants influences microbiome recovery or long-term transplant outcomes.

What was studied?

To date, the microbiota of the human penis has been studied mostly in connection with circumcision, HIV risk and female partner bacterial vaginosis (BV). These studies have shown that male circumcision reduces penile anaerobic bacteria, that greater abundance of penile anaerobic bacteria is correlated with increased cytokine levels and greater risk of HIV infection, and that the penile microbiota is an important harbour for BV-associated bacteria. While circumcision has been shown to significantly reduce the risk of acquiring human papillomavirus (HPV) infection, the relationship of the penile microbiota with HPV is still unknown. In this study, we examined the penile microbiota of HPV-infected men as well as the impact of HIV status.

What were the most important findings?

The penile skin microbiota of 238 men from Cape Town (South Africa) were profiled using Illumina sequencing of the V3-V4 hypervariable regions of the 16S rRNA gene. Corynebacterium and Prevotella were found to be the most abundant genera. Six distinct community state types (CSTs) were identified. CST-1, dominated by Corynebacterium, corresponded to less infections with high-risk HPV (HR-HPV) relative to CSTs 2-6. Men in CST-5 had greater relative abundances of Prevotella, Clostridiales, and Porphyromonas and a lower relative abundance of Corynebacterium. Moreover, they were significantly more likely to have HPV or HR-HPV infections than men in CST-1. Using a machine learning approach, we identified greater relative abundances of the anaerobic BV-associated bacteria (Prevotella, Peptinophilus, and Dialister) and lower relative abundance of Corynebacterium in HR-HPV-infected men compared to HR-HPV-uninfected men. No association was observed between HIV and CST, although the penile microbiota of HIV-infected men had greater relative abundances of Staphylococcus compared to HIV-uninfected men.

What are the greatest implications of this study?

We found significant differences in the penile microbiota composition of men with and without HPV and HIV infections. HIV and HR-HPV infections were strongly associated with greater relative abundances of Staphylococcus and BV-associated bacterial taxa (notably Prevotella, Peptinophilus and Dialister), respectively. It is possible that these taxa could increase susceptibility to HIV and HR-HPV acquisition, in addition to creating conditions in which infections persist. Further longitudinal studies are required to establish causal relationships and to determine the extent of the effect.

What was studied?

Discriminating depressive episodes of bipolar disorder (BD) from major depressive disorder (MDD) is a major clinical challenge. Recently, gut microbiome alterations are implicated in these two mood disorders; however, little is known about the shared and distinct microbial characteristics in MDD versus BD. Here, using 16S ribosomal RNA (rRNA) gene sequencing, the microbial compositions of 165 subjects with MDD are compared with 217 BD, and 217 healthy controls (HCs). It is found that the microbial compositions are different between the three groups. Compared to HCs, MDD is characterized by altered covarying operational taxonomic units (OTUs) assigned to the Bacteroidaceae family, and BD shows disturbed covarying OTUs belonging to Lachnospiraceae, Prevotellaceae, and Ruminococcaceae families. Furthermore, a signature of 26 OTUs is identified that can distinguish patients with MDD from those with BD or HCs, with area under the curve (AUC) values ranging from 0.961 to 0.986 in discovery sets, and 0.702 to 0.741 in validation sets. Moreover, 4 of 26 microbial markers correlate with disease severity in MDD or BD. Together, distinct gut microbial compositions are identified in MDD compared to BD and HCs, and a novel marker panel is provided for distinguishing MDD from BD based on gut microbiome signatures.

What was studied?

This cross-sectional study used shotgun metagenomic sequencing of fecal samples to identify gut microbial species associated with polycystic ovary syndrome (PCOS). Researchers compared the gut microbiota composition of women with PCOS to that of women without the condition. They also collected clinical parameters, including body mass index, endocrine hormone levels, and glycemia, to test for correlations with the microbial findings.

Who was studied?

The study included 14 reproductive-aged women diagnosed with PCOS and 14 control women, all recruited from an academic Centre for Reproductive Medicine. Fecal samples from these 28 participants underwent shotgun metagenomic sequencing. Clinical and metabolic data were gathered from the same women for correlation analysis.

What were the most important findings?

Several microbial strains were significantly more abundant in the PCOS group, including Parabacteroides merdae, Bacteroides fragilis, and strains of Escherichia and Shigella, while Faecalibacterium prausnitzii was enriched in controls. Metagenomic species analysis showed that the microbial profiles of the PCOS group were negatively correlated with those of the control group. Microbial species associated with PCOS were positively correlated with endocrine disturbances, including higher body mass index and elevated serum testosterone levels.

What are the greatest implications of this study?

The findings support a pathological association between gut dysbiosis and PCOS, linking specific bacterial taxa to hormonal and metabolic disturbances seen in the condition. The enrichment of Escherichia and Shigella strains alongside depletion of the beneficial species Faecalibacterium prausnitzii suggests a shift toward a more pro-inflammatory gut environment in PCOS. These results point to the gut microbiome as a potential target for understanding or managing the endocrine and metabolic features of PCOS, though further work is needed to establish causality.

What was studied?

Endometriosis (EMS) is a chronic inflammatory disease with unclear pathogenesis. Three studies have uncovered the influence of gut microbiota on mice with EMS, but no study has investigated the characteristics of fecal metabolomics to determine some important clues on EMS. This research aims to uncover the interaction between fecal metabolomics and gut microbiota in EMS mice.

Who was studied?

Female C57BL/6J mice were used to construct the EMS model. Non-target metabolomics was applied to detect the fecal metabolites of EMS mice. The 16s rRNA sequencing was used for clarifying the composition of the gut microbiota. The functional characteristics of gut microbiota were analyzed using the PICRUSt. The receiver operator characteristic curve (ROC) analysis was utilized for determining the potential important differential metabolites, and the Spearman correlation coefficient was applied for expressing the correlation between the important differential metabolites and gut microbiota.

What were the most important findings?

A total of 156 named differential metabolites were screened. The diversity and the abundance of gut microbiota in EMS mice decreased. Eleven pathways were involved in the differential metabolites and the functional prediction of gut microbiota, among which the second bile acid biosynthesis and alpha-linolenic acid (ALA) metabolism were the significant enrichment pathways. The increased abundance of chenodeoxycholic and ursodeoxycholic acids and the decreased abundance of ALA and 12,13-EOTrE were found in the feces of EMS mice.

What are the greatest implications of this study?

The abnormal fecal metabolites, which are influenced by dysbacteriosis, may be the characteristics of EMS mice and can be the potential important indices to distinguish the disease.

What was studied?

This study characterized alterations in the gut microbiome associated with chronic kidney disease (CKD). The researchers analyzed fecal samples to compare microbial diversity, community composition, and predicted microbial functions between CKD patients and healthy controls. They also constructed and validated diagnostic classifiers for CKD based on microbial markers using a random forest model, and examined relationships between specific taxa, disease progression, and clinical indicators.

Who was studied?

A total of 520 fecal samples were collected from different regions of China. The discovery and comparison cohort included 110 patients with CKD and 210 healthy controls (HC). The classifier was further tested in a validation cohort of 49 CKD cases versus 63 HC, and in an extra diagnosis cohort from Hangzhou.

What were the most important findings?

Gut microbial diversity was significantly decreased in CKD patients compared with healthy controls, and the overall microbial community composition was distinctly different between groups. The genera Klebsiella and Enterobacteriaceae were enriched in CKD, while Blautia and Roseburia were reduced. Fifty predicted microbial functions, including tryptophan and phenylalanine metabolism, increased in CKD, while 36 functions, including arginine and proline metabolism, decreased. A five-marker microbial classifier achieved an area under the curve (AUC) of 0.9887 in the discovery cohort, 0.9512 in the validation cohort, and 0.8986 in the extra Hangzhou diagnosis cohort, and Thalassospira and Akkermansia increased with CKD progression.

What are the greatest implications of this study?

These findings indicate that CKD is associated with a distinct, less diverse gut microbial community and altered amino acid metabolism pathways. The high diagnostic accuracy of the identified microbial markers across discovery, validation, and independent cohorts suggests gut microbiome signatures could serve as a non-invasive tool for CKD detection. The correlation between specific taxa and clinical indicators, along with taxa that shift with disease progression, points to the gut microbiome as a potential avenue for monitoring CKD severity.

What was studied?

This study examined how HIV infection and men who have sex with men (MSM) status are each associated with changes in the gut microbiome. The researchers conducted a meta-analysis of 16S rRNA gene amplicon sequencing data related to HIV/AIDS. They evaluated alpha diversity, beta diversity, differentially enriched bacterial genera and species, and KEGG functional pathways to identify consistent patterns across studies.

Who was studied?

The meta-analysis screened 12 published studies from the NCBI and EBI databases, six of which contained data relevant to MSM status. The HIV analysis included 1,288 gut microbiome samples, comprising 744 HIV-positive individuals and 544 HIV-negative individuals. The MSM analysis included 632 samples, comprising 328 MSM and 304 non-MSM individuals.

What were the most important findings?

HIV-positive status was associated with decreased alpha diversity of the gut microbiome compared to HIV-negative status. MSM status was identified as an important factor affecting the gut microbiome independent of HIV infection status. The abstract does not provide the specific differentially enriched genera, species, or KEGG pathway results before being cut off, so those details cannot be reported here.

What are the greatest implications of this study?

By pooling multiple studies, this meta-analysis helps clarify a consistent pattern of gut microbiome change associated with HIV infection, namely reduced alpha diversity. Recognizing MSM status as an independent influencing factor suggests that future gut microbiome research on HIV must account for sexual orientation as a confounding variable rather than attributing all differences to HIV infection itself. This distinction could improve the design and interpretation of future microbiome studies in HIV populations.

What was studied?

Background: Offspring of mothers with gestational diabetes mellitus (GDM) have increased risk of developing metabolic disorders as they grow up. Microbial colonization of the newborn gut and environmental exposures affecting the configuration of the gut microbiota during infancy have been linked to increased risk of developing disease during childhood and adulthood. In a convenience sample, we examined whether the intestinal tract of children born to mothers with GDM is differentially colonized in early life compared to offspring of mothers with normal gestational glucose regulation. Secondly, we examined whether any such difference persists during infancy, thus potentially conferring increased risk of developing metabolic disease later in life. Methods: Fecal samples were collected from children of mothers with (n = 43) and without GDM (n = 82) during the first week of life and again at an average age of 9 months. The gut microbiota was characterized by 16S rRNA gene amplicon sequencing (V1-V2). Differences in diversity and composition according to maternal GDM status were assessed, addressing potential confounding by mode of delivery, perinatal antibiotics treatment, feeding and infant sex. Results: Children of mothers with GDM were featured by a differential composition of the gut microbiota, both during the first week of life and at 9 months, at higher taxonomic and OTU levels. Sixteen and 15 OTUs were differentially abundant after correction for multiple testing during the first week of life and at 9 months, respectively. Two OTUs remained differentially abundant after adjustment for potential confounders both during the first week of life and at 9 months. Richness (OTU) was decreased in neonates born to mothers with GDM; however, at 9 months no difference in richness was observed. There was no difference in Shannon's diversity or Pielou's evenness at any timepoint. Longitudinally, we detected differential changes in the gut microbiota composition from birth to infancy according to GDM status. Conclusion: Differences in glycaemic regulation in late pregnancy is linked with relatively modest variation in the gut microbiota composition of the offspring during the first week of life and 9 months after birth.

What was studied?

Background: Diabetes mellitus (DM) has become one of the most common chronic metabolic diseases worldwide. Due to the increasing prevalence and various complications, diabetes brings about a huge financial burden to DM patients. Nowadays, more and more studies reveal the relationship between diseases and gut microbial community. We aimed to explore the alteration in composition and function of the gut microbiome in T2DM patients. Methods: A total of 137 patients with diabetes and 179 age- and gender-matched healthy controls selected from the healthy people sample center in the First Affiliated Hospital of Zhengzhou University were divided into the DM group and the Con group, respectively. We collected their venous blood for laboratory tests and stool samples for 16S rRNA sequencing. The comparison between the two groups including both composition and function of the gut microbiome is presented. Results: We found that the α-diversity of bacterial taxa in the DM group had an evident decrease compared to that in the Con group. At the phylum level, the DM group had an obvious decrease of Bacteroidetes and a marked increase of Proteobacteria, Actinobacteria, and Verrucomicrobia. At the genus level, Bacteroides and Prevotella decreased the most while Escherichia-Shigella, Lachnospiraceae_incertae_sedis, Subdoligranulum, Enterococcus, and Klebsiella had different degrees of expansion in the DM group. The ROC based on 246 optimum OTUs had very high test efficiency with an AUC of 92.25% in the training set and 90.48% in the test set. As for prediction of metabolic function, the gut microbiome of DM patients was predicted to be more active in environmental information processing and human diseases but less in metabolism. Conclusion: We observed alteration of composition and function of the gut microbiome in the DM group. These changes may provide a new treatment strategy for DM patients and new research targets.

What was studied?

Chronic constipation is one of the most prevalent functional gastrointestinal disorders, yet its etiology is multifactorial, and the pathophysiological mechanism is still unclear. Previous studies have shown that the gut microbiota of constipated patients differs from healthy controls; however, many discrepancies exist in the findings, and no clear link has been confirmed between chronic constipation and changes in the gut microbiota. Growing evidence indicates that age, gender, and hormone levels can affect the composition of gut microbiota. The aim of this study is to examine the overall changes in gut microbiota within a specific sub-population of patients, namely, constipated women of reproductive age.

Who was studied?

We carried out a cross-sectional study comparing the fecal microbial composition of 30 healthy women and 29 constipated women using 16S rRNA gene sequencing. Only women of reproductive age were recruited to reduce the effects of age, gender, and hormone levels on the microbiome, and to prevent conflating the impact of these factors with the effects of constipation.

What were the most important findings?

There were obvious differences in the gut microbiota in constipated women of reproductive age compared with the healthy controls, manifesting mainly as a significant increase in the abundance of Bacteroides (p < 0.05) and a significant decrease in the abundance of Proteobacteria (p < 0.01). The overall composition of the gut microbiota in each group was different, which was reflected in the ratios of Firmicutes to Bacteroidetes (F/B), which was 1.52 in the constipated group vs. 2.21 in the healthy group. Additionally, there was a significant decrease in butyrate-producing bacteria, like Roseburia and Fusicatenibacter (p < 0.01).

What are the greatest implications of this study?

The overall composition of the gut microbiota changed in constipated women of reproductive age, characterized by a loss in Proteobacteria and an increase in Bacteroidetes. Furthermore, the abundance of some butyrate-producing bacteria also reduced. These changes may reflect the unique interactions between host and some bacteria, or some bacterial metabolic products, which may be important targets for future studies to explore the pathogenesis of constipation.

What was studied?

Diet is a major determinant of intestinal microbiome composition. While studies have evaluated microbiome responses to diet variation, less is understood about how the act of feeding influences the microbiome, independent of diet type. Here, we use the clownfish Premnas biaculeatus, a species reared commonly in ornamental marine aquaculture, to test how the diversity, predicted gene content, and gene transcription of the microbiome vary over a 2-day diurnal period with a single daily feeding event. This study used fish fed four times daily, once daily, or every 3 days prior to the diurnal period, allowing us also to test how feeding frequency affected microbiome diversity. The amount of time between feedings had no effect on baseline diversity of the microbiome. In contrast, the act of feeding itself caused a significant short-term change in the microbiome, with microbiome diversity, predicted gene content, and gene transcription varying significantly between time points immediately before and 1.5 hours postfeeding. Variation was driven by abundance shifts involving exact sequence variants (ESVs), with one ESV identified as Photobacterium sp. increasing from <0.5% of sequences immediately prefeeding to 34% at 1.5 h postfeeding. Other ESVs from a range of microbial groups also increased dramatically after feeding, with the majority also detected in the food. One ESV identified as Clostridium perfringens represented up to 55% of sequences but did not vary significantly over the diurnal period and was not detected in the food. Postfeeding samples were enriched in transcripts and predicted genes for social interactions, cell motility, and coping with foreign DNA, whereas time points farther from feeding were enriched in genes of diverse catabolic and biosynthetic functions. These results confirm feeding as a significant destabilizing force in clownfish intestinal microbiomes, likely due to both input of cells attached to food and stimulation of resident microbes. Microbes such as Photobacterium may episodically transition from environmental reservoirs to growth in the gut, likely in association with food particles. This transition may be facilitated by functions for navigating a new environment and interacting with neighboring microbes and host cells. Other taxa, such as Clostridium, are comparatively stable intestinal members and less likely to be affected by passing food. Conclusions about microbiome ecology may therefore differ based on when samples were collected relative to the last feeding.IMPORTANCE Despite extensive study of intestinal microbiome diversity and the role of diet type in structuring gut microbial communities, we know very little about short-term changes in the intestinal microbiome as a result of feeding alone. Sampling microbiomes over a feeding cycle will allow us to differentiate opportunistic, feeding-responsive microbes from resident, potentially commensal members of the gut community. Also, since feeding has the potential to alter microbiome structure, sampling at different points relative to the last feeding event will likely yield different conclusions about microbiome composition and function. This variation should be addressed in comparative microbiome studies. Our study contributes to knowledge of short-term changes in the gut microbiome associated with feeding events.

What was studied?

The effect of infection of pigs with Ascaris suum on the microbial composition in the proximal colon and fecal matter was investigated using 16S rRNA gene sequencing. The infection significantly decreased various microbial diversity indices including Chao1 richness, but the effect on Chao1 in the colon luminal contents was worm burden-independent. The abundance of 49 genera present in colon contents, such as Prevotella and Faecalibacterium, and 179 operational taxonomic units was significantly changed as a result of infection. Notably, infection was also associated with a significant shift in the metabolic potential of the proximal colon microbiome, where the relative abundance of at least 30 metabolic pathways including carbohydrate metabolism and amino acid metabolism was reduced, while the abundance of 28 pathways was increased by infection. Furthermore, the microbial co-occurrence network in infected pigs was highly modular. Two of 52 modules or subnetworks were negatively correlated with fecal butyrate concentrations (r < -0.7; P < 0.05) while one module with 18 members was negatively correlated with fecal acetate, propionate and total short-chain fatty acids. A partial Mantel test identified a strong positive correlation between node connectivity of the operational taxonomic units assigned to β-Proteobacteria (especially the family Alcaligenaceae) and fecal acetate and propionate levels (r = 0.82 and 0.74, respectively), while that of the family Porphyromonadaceae was positively correlated with fecal egg counts. Overall, Ascaris infection was associated with a profound change in the gut microbiome, especially in the proximity of the initial site of larval infection, and should facilitate our understanding of the pathophysiological consequence of gastrointestinal nematode infections.

What was studied?

As the global population ages, and rates of dementia rise, understanding lifestyle factors that play a role in the development and acceleration of cognitive decline is vital to creating therapies and recommendations to improve quality of later life. Obesity has been shown to increase risk for dementia. However, the specific mechanisms for obesity-induced cognitive decline remain unclear. One potential contributor to diet-induced cognitive changes is neuroinflammation. Furthermore, a source of diet-induced inflammation to potentially increase neuroinflammation is via gut dysbiosis. We hypothesized that a high fat diet would cause gut microbe dysbiosis, and subsequently: neuroinflammation and cognitive decline. Using 7-month old male Sprague Dawley rats, this study examined whether 8 weeks on a high fat diet could impact performance on the water radial arm maze, gut microbe diversity and abundance, and microgliosis. We found that a high fat diet altered gut microbe populations compared to a low fat, control diet. However, we did not observe any significant differences between dietary groups on maze performance (a measure of spatial working memory) or microgliosis. Our data reveal a significant change to the gut microbiome without subsequent effects to neuroinflammation (as measured by microglia characterization and counts in the cortex, hippocampus, and hypothalamus) or cognitive performance under the parameters of our study. However, future studies that explore duration of the diet, composition of the diet, age of animal model, and strain of animal model, must be explored.

What was studied?

This study investigated dysbiosis of the gut microbiota in Parkinson's disease (PD) patients from Central Italy. The researchers used 16s ribosomal RNA gene amplicon sequencing to characterize fecal microbiota composition. They also examined dietary and lifestyle data alongside clinical variables to identify confounders and predictors that might correlate with clinical phenotypes. The aim was to find potential microbiota-based correlates of PD status and severity.

Who was studied?

The study included 152 fecal samples collected from 80 PD patients and 72 healthy controls. Patients were enrolled according to tight inclusion criteria, though the abstract does not specify the exact nature of those criteria. Age, sex, and weight loss were treated as confounding factors in the analysis, while PD status, age, Body Mass Index, cereal consumption, weight gain, and physical activity were treated as predictors.

What were the most important findings?

Fecal levels of Lactobacillaceae, Enterobacteriaceae, and Enterococcaceae were significantly higher in PD patients than in healthy controls. Lachnospiraceae, by contrast, were significantly reduced in PD patients. Lower Lachnospiraceae and higher Enterobacteriaceae levels also correlated with increased disease severity, linking this specific bacterial family shift to clinical progression.

What are the greatest implications of this study?

The findings reinforce the hypothesis that gut microbiota dysbiosis is associated with Parkinson's disease, with the Enterobacteriaceae family emerging as a marker that tracks with disease severity. This suggests dysbiosis is not just present in PD but may relate to how advanced the disease is in a given patient. The results support continued investigation of specific bacterial families, particularly Enterobacteriaceae and Lachnospiraceae, as potential biomarkers or targets tied to clinical phenotype in PD.

What was studied?

The dysbiosis of human gut microbiota is strongly associated with the development of colorectal cancer (CRC). The dysbiotic features of the transition from advanced polyp to early-stage CRC are largely unknown. We performed a 16S rRNA gene sequencing and enterotype-based gut microbiota analysis study. In addition to Bacteroides- and Prevotella-dominated enterotypes, we identified an Escherichia-dominated enterotype. We found that the dysbiotic features of CRC were dissimilar in overall samples and especially Escherichia-dominated enterotype. Besides a higher abundance of Fusobacterium, Enterococcus, and Aeromonas in all CRC faecal microbiota, we found that the most notable characteristic of CRC faecal microbiota was a decreased abundance of potential beneficial butyrate-producing bacteria. Notably, Oscillospira was depleted in the transition from advanced adenoma to stage 0 CRC, whereas Haemophilus was depleted in the transition from stage 0 to early-stage CRC. We further identified 7 different CAGs by analysing bacterial clusters. The abundance of microbiota in cluster 3 significantly increased in the CRC group, whereas that of cluster 5 decreased. The abundance of both cluster 5 and cluster 7 decreased in the Escherichia-dominated enterotype of the CRC group. We present the first enterotype-based faecal microbiota analysis. The gut microbiota of colorectal neoplasms can be influenced by its enterotype.

What was studied?

The Westernized diet has been associated with the pathogenesis of metabolic diseases, whereas a Korean diet has been reported to exert beneficial effects on health in several studies. However, the effects of Western and Korean diets on the gut microbiome and host metabolome are unclear. To examine the diet-specific effects on microbiome and metabolome, we conducted a randomized crossover clinical trial of typical Korean diet (TKD), typical American diet (TAD), and recommended American diet (RAD). The trial involved a 4-week consumption of an experimental diet followed by a 2-week interval before diet crossover. 16S rRNA sequencing analysis identified 16, 10, and 14 differential bacteria genera specific to TKD, RAD, and TAD, respectively. The Firmucutes-Bacteroidetes ratio was increased by TKD. Nuclear magnetic resonance metabolome profiling revealed that TKD enriched branched chain amino acid metabolism, whereas ketone body metabolism was evident in RAD and TAD. Microbiome and metabolome responses to the experimental diets varied with individual enterotypes. These findings provide evidence that the gut microbiome and host metabolome rapidly respond to different cultural diets. The findings will inform clarification of the diet-related communication networks of the gut microbiome and host metabolome in humans.

What was studied?

The importance of the intestinal microbiota for the onset and clinical course of many diseases, including liver diseases like non-alcoholic steatohepatitis and cirrhosis, is increasingly recognized. However, the role of intestinal microbiota in chronic hepatitis C virus (HCV) infection remains unclear.

Who was studied?

In a cross-sectional approach, the intestinal microbiota of 95 patients chronically infected with HCV (n=57 without cirrhosis [NO-CIR]; n=38 with cirrhosis [CIR]) and 50 healthy controls (HC) without documented liver diseases was analysed.

What were the most important findings?

Alpha diversity, measured by number of phylotypes (S) and Shannon diversity index (H'), decreased significantly from HC to NO-CIR to CIR. S and H' correlated negatively with liver elastography. Analysis of similarities revealed highly statistically significant differences in the microbial communities between HC, NO-CIR and CIR (R=.090; P<1.0×10-6 ). Stratifying for HCV genotypes even increased the differences. In addition, we observed distinct patterns in the relative abundance of genera being either positive or negative correlated with diseases status.

What are the greatest implications of this study?

This study shows that not only the stage of liver disease but also HCV infection is associated with a reduced alpha diversity and different microbial community patterns. These differences might be caused by direct interactions between HCV and the microbiota or indirect interactions facilitated by the immune system.

What was studied?

Alterations in the intestinal microbiome are prospectively associated with the development of asthma; less is known regarding the role of microbiome alterations in food allergy development.

Who was studied?

Intestinal microbiome samples were collected at age 3-6 months in children participating in the follow-up phase of an interventional trial of high-dose vitamin D given during pregnancy. At age 3, sensitization to foods (milk, egg, peanut, soy, wheat, walnut) was assessed. Food allergy was defined as caretaker report of healthcare provider-diagnosed allergy to the above foods prior to age 3 with evidence of IgE sensitization. Analysis was performed using Phyloseq and DESeq2; P-values were adjusted for multiple comparisons.

What were the most important findings?

Complete data were available for 225 children; there were 87 cases of food sensitization and 14 cases of food allergy. Microbial diversity measures did not differ between food sensitization and food allergy cases and controls. The genera Haemophilus (log2 fold change -2.15, P=.003), Dialister (log2 fold change -2.22, P=.009), Dorea (log2 fold change -1.65, P=.02), and Clostridium (log2 fold change -1.47, P=.002) were underrepresented among subjects with food sensitization. The genera Citrobacter (log2 fold change -3.41, P=.03), Oscillospira (log2 fold change -2.80, P=.03), Lactococcus (log2 fold change -3.19, P=.05), and Dorea (log2 fold change -3.00, P=.05) were underrepresented among subjects with food allergy.

What are the greatest implications of this study?

The temporal association between bacterial colonization and food sensitization and allergy suggests that the microbiome may have a causal role in the development of food allergy. Our findings have therapeutic implications for the prevention and treatment of food allergy.

What was studied?

The mucosa-associated gut microbiota directly modulates epithelial and mucosal function. In this study, we investigated the mucosa-associated microbial community in patients with inflammatory bowel disease (IBD), using endoscopic brush samples.

Who was studied?

A total of 174 mucus samples from 43 patients with ulcerative colitis (UC), 26 with Crohn's disease (CD) and 14 non-IBD controls were obtained by gentle brushing of mucosal surfaces using endoscopic cytology brushes. The gut microbiome was analyzed using 16S rRNA gene sequencing.

What were the most important findings?

There were no significant differences in microbial structure among different anatomical sites (the ileum, cecum and sigmoid colon) within individuals. There was, however, a significant difference in microbial structure between CD, UC and non-IBD controls. The difference between CD and non-IBD controls was more marked than that between UC patients and non-IBD controls. α-Diversity was significantly lower in UC and CD patients than non-IBD controls. When comparing CD patients with non-IBD controls, the phylum Proteobacteria was significantly increased and the phyla Firmicutes and Bacteroidetes were significantly reduced. These included a significant increase in the genera Escherichia, Ruminococcus (R. gnavus), Cetobacterium, Actinobacillus and Enterococcus, and a significant decrease in the genera Faecalibacterium, Coprococcus, Prevotella and Roseburia. Comparisons between CD and UC patients revealed a greater abundance of the genera Escherichia, Ruminococcus (R. gnavus), Clostridium, Cetobacterium, Peptostreptococcus in CD patients, and the genera Faecalibacterium, Blautia, Bifidobacterium, Roseburia and Citrobacter in UC patients.

What are the greatest implications of this study?

Mucosa-associated dysbiosis was identified in IBD patients. CD and UC may be distinguishable from the mucosa-associated microbial community structure.

What was studied?

This cross-sectional study examined differences in gut microbiota composition between people with schizophrenia and healthy controls using 16S rRNA sequencing. The researchers compared microbial abundance at the phylum and genus levels and then tested whether the resulting microbiota profile could serve as a diagnostic biomarker. Functional potential of the microbiota was also explored using PICRUSt predictive analysis.

Who was studied?

The study included 64 patients diagnosed with schizophrenia and 53 healthy controls. Inclusion criteria were applied strictly to limit confounding bias between the two groups. No further demographic details, such as age or sex distribution, are given in the abstract.

What were the most important findings?

At the phylum level, Proteobacteria was significantly more abundant in schizophrenia patients than in healthy controls. At the genus level, Succinivibrio, Megasphaera, Collinsella, Clostridium, Klebsiella, and Methanobrevibacter were elevated, while Blautia, Coprococcus, and Roseburia were reduced compared with controls. A panel of 12 microbiota biomarkers distinguished the schizophrenia group from controls with an AUC of 0.837, indicating fairly strong discriminatory performance. Sulfate-reducing bacteria, Desulfovibrio, and hydrogen sulfide or sulfur metabolism are not mentioned in this abstract.

What are the greatest implications of this study?

These findings support the idea that gut microbiota alterations are associated with schizophrenia and could potentially aid diagnosis alongside clinical assessment. The identified biomarker panel suggests a possible auxiliary, non-invasive tool for distinguishing schizophrenia patients from healthy individuals. Because this is a cross-sectional, single-population study, the findings describe association rather than causation and would need validation in independent and more diverse cohorts before clinical use.

What was studied?

This study used next generation sequencing-based 16S rRNA gene analysis to characterize the gut microbiota composition in colorectal cancer (CRC) patients following anti-cancer treatment. The researchers specifically compared microbial communities across patients treated with surgery versus those treated with chemotherapy. The goal was to identify how these treatments reshape the microbiome and whether specific bacteria are linked to chemoresistance during CRC therapy.

Who was studied?

The analysis was based on a total of 69 fecal samples collected across four clinical groups. These groups included healthy individuals, untreated CRC patients, CRC patients treated with surgery, and CRC patients treated with chemotherapy. The abstract does not provide further demographic details such as age or sex distribution.

What were the most important findings?

Surgery was found to greatly reduce bacterial diversity in the gut microbiota of CRC patients. Fusobacterium nucleatum was shown to confer chemoresistance during CRC therapy. Additionally, certain bacterial strains or genera, including the genus Sutterella and the species Veillonella dispar, were specifically associated with CRC patients treated with chemotherapeutic cocktails, suggesting a potential relationship with chemoresistance.

What are the greatest implications of this study?

These findings suggest that specific gut bacteria, such as Fusobacterium nucleatum, Sutterella, and Veillonella dispar, could serve as candidate biomarkers for monitoring or predicting chemoresistance in CRC patients. The marked loss of bacterial diversity after surgery also points to a treatment-related microbiome disruption that may warrant clinical attention. Together, these results support further investigation into the gut microbiota as a tool for guiding or evaluating CRC therapy.

What was studied?

The assessment and characterization of the gut microbiome has become a focus of research in the area of human autoimmune diseases. Ankylosing spondylitis is an inflammatory autoimmune disease and evidence showed that ankylosing spondylitis may be a microbiome-driven disease.

What were the most important findings?

To investigate the relationship between the gut microbiome and ankylosing spondylitis, a quantitative metagenomics study based on deep shotgun sequencing was performed, using gut microbial DNA from 211 Chinese individuals. A total of 23,709 genes and 12 metagenomic species were shown to be differentially abundant between ankylosing spondylitis patients and healthy controls. Patients were characterized by a form of gut microbial dysbiosis that is more prominent than previously reported cases with inflammatory bowel disease. Specifically, the ankylosing spondylitis patients demonstrated increases in the abundance of Prevotella melaninogenica, Prevotella copri, and Prevotella sp. C561 and decreases in Bacteroides spp. It is noteworthy that the Bifidobacterium genus, which is commonly used in probiotics, accumulated in the ankylosing spondylitis patients. Diagnostic algorithms were established using a subset of these gut microbial biomarkers.

What are the greatest implications of this study?

Alterations of the gut microbiome are associated with development of ankylosing spondylitis. Our data suggest biomarkers identified in this study might participate in the pathogenesis or development process of ankylosing spondylitis, providing new leads for the development of new diagnostic tools and potential treatments.

What was studied?

The human gut microbiome plays a crucial role in the compositional development of gut microbiota. Though well documented in western pediatrics population, little is known about how various host conditions affect populations in different geographic locations such as the Indian subcontinent. Given the impact of distinct environmental conditions, our study assess the gut bacterial diversity of a small cohort of Indian and Finnish children and investigated the influence of FUT2 secretor status and birth mode on the gut microbiome of these populations. Using multiple profiling techniques, we show that the gut bacterial community structure in 13-14-year-old Indian (n = 47) and Finnish (n = 52) children differs significantly. Specifically, Finnish children possessed higher Blautia and Bifidobacterium, while genera Prevotella and Megasphaera were predominant in Indian children. Our study also demonstrates a strong influence of FUT2 and birth mode variants on specific gut bacterial taxa, influence of which was noticed to differ between the two populations under study.

What was studied?

This study examined whether the enteric virome, alongside the bacterial microbiome, contributes to HIV-associated immunodeficiency and gut disease. Researchers characterized viral and bacterial communities in stool to see how they relate to HIV infection, antiretroviral therapy (ART) status, and CD4 T cell counts. The goal was to determine whether virome alterations track with immune decline independent of treatment.

Who was studied?

The cohort consisted of Ugandan patients, including individuals without HIV infection and individuals with HIV infection who were either on ART or untreated. The abstract does not give an exact sample size or additional demographic detail. Findings are grouped by HIV status, treatment status, and peripheral CD4 T cell count level.

What were the most important findings?

Low peripheral CD4 T cell counts were associated with an expansion of enteric adenovirus sequences, and this pattern held regardless of ART treatment. Patients with lower CD4 counts also had a bacterial microbiome with reduced phylogenetic diversity and richness. Specific bacterial taxa showed differential abundance, notably an increase in Enterobacteriaceae, a group linked to inflammation.

What are the greatest implications of this study?

The findings suggest that immunodeficiency in progressive HIV infection is accompanied by coordinated shifts in both the enteric virome and bacterial microbiome, not bacterial changes alone. Because the adenovirus expansion occurred regardless of ART status, viral alterations may persist even in treated patients and could still contribute to gut dysfunction. These combined viral and bacterial changes may help drive AIDS-associated enteropathy and disease progression, pointing to the virome as an underexplored factor in HIV-related gut pathology.

What was studied?

Chemotherapy is commonly used as myeloablative conditioning treatment to prepare patients for haematopoietic stem cell transplantation (HSCT). Chemotherapy leads to several side effects, with gastrointestinal (GI) mucositis being one of the most frequent. Current models of GI mucositis pathophysiology are generally silent on the role of the intestinal microbiome. To identify functional mechanisms by which the intestinal microbiome may play a key role in the pathophysiology of GI mucositis, we applied high-throughput DNA-sequencing analysis to identify microbes and microbial functions that are modulated following chemotherapy.

Who was studied?

We amplified and sequenced 16S rRNA genes from faecal samples before and after chemotherapy in 28 patients with non-Hodgkin's lymphoma who received the same myeloablative conditioning regimen and no other concomitant therapy such as antibiotics.

What were the most important findings?

We found that faecal samples collected after chemotherapy exhibited significant decreases in abundances of Firmicutes (P = 0.0002) and Actinobacteria (P = 0.002) and significant increases in abundances of Proteobacteria (P = 0.0002) compared to samples collected before chemotherapy. Following chemotherapy, patients had reduced capacity for nucleotide metabolism (P = 0.0001), energy metabolism (P = 0.001), metabolism of cofactors and vitamins (P = 0.006), and increased capacity for glycan metabolism (P = 0.0002), signal transduction (P = 0.0002) and xenobiotics biodegradation (P = 0.002).

What are the greatest implications of this study?

Our study identifies a severe compositional and functional imbalance in the gut microbial community associated with chemotherapy-induced GI mucositis. The functional pathways implicated in our analysis suggest potential directions for the development of intestinal microbiome-targeted interventions in cancer patients.

What was studied?

Preterm birth is the second leading cause of death in children under the age of five years worldwide, but the etiology of many cases remains enigmatic. The dogma that the fetus resides in a sterile environment is being challenged by recent findings and the question has arisen whether microbes that colonize the fetus may be related to preterm birth. It has been posited that meconium reflects the in-utero microbial environment. In this study, correlations between fetal intestinal bacteria from meconium and gestational age were examined in order to suggest underlying mechanisms that may contribute to preterm birth.

Who was studied?

Meconium from 52 infants ranging in gestational age from 23 to 41 weeks was collected, the DNA extracted, and 16S rRNA analysis performed. Resulting taxa of microbes were correlated to clinical variables and also compared to previous studies of amniotic fluid and other human microbiome niches.

What were the most important findings?

Increased detection of bacterial 16S rRNA in meconium of infants of <33 weeks gestational age was observed. Approximately 61·1% of reads sequenced were classified to genera that have been reported in amniotic fluid. Gestational age had the largest influence on microbial community structure (R = 0·161; p = 0·029), while mode of delivery (C-section versus vaginal delivery) had an effect as well (R = 0·100; p = 0·044). Enterobacter, Enterococcus, Lactobacillus, Photorhabdus, and Tannerella, were negatively correlated with gestational age and have been reported to incite inflammatory responses, suggesting a causative role in premature birth.

What are the greatest implications of this study?

This provides the first evidence to support the hypothesis that the fetal intestinal microbiome derived from swallowed amniotic fluid may be involved in the inflammatory response that leads to premature birth.

What was studied?

Eighty-one stool samples from Taiwanese were collected for analysis of the association between the gut flora and obesity. The supervised analysis showed that the most, abundant genera of bacteria in normal samples (from people with a body mass index (BMI) ≤ 24) were Bacteroides (27.7%), Prevotella (19.4%), Escherichia (12%), Phascolarctobacterium (3.9%), and Eubacterium (3.5%). The most abundant genera of bacteria in case samples (with a BMI ≥ 27) were Bacteroides (29%), Prevotella (21%), Escherichia (7.4%), Megamonas (5.1%), and Phascolarctobacterium (3.8%). A principal coordinate analysis (PCoA) demonstrated that normal samples were clustered more compactly than case samples. An unsupervised analysis demonstrated that bacterial communities in the gut were clustered into two main groups: N-like and OB-like groups. Remarkably, most normal samples (78%) were clustered in the N-like group, and most case samples (81%) were clustered in the OB-like group (Fisher's P  value = 1.61E - 07). The results showed that bacterial communities in the gut were highly associated with obesity. This is the first study in Taiwan to investigate the association between human gut flora and obesity, and the results provide new insights into the correlation of bacteria with the rising trend in obesity.

What was studied?

Chronic obstructive pulmonary disease (COPD) is an inflammatory disorder characterized by incompletely reversible airflow obstruction. Bacterial infection of the lower respiratory tract contributes to approximately 50% of COPD exacerbations. Even during periods of stable lung function, the lung harbors a community of bacteria, termed the microbiome. The role of the lung microbiome in the pathogenesis of COPD remains unknown. The COPD lung microbiome, like the healthy lung microbiome, appears to reflect microaspiration of oral microflora. Here we describe the COPD lung microbiome of 22 patients with Moderate or Severe COPD compared to 10 healthy control patients. The composition of the lung microbiomes was determined using 454 pyrosequencing of 16S rDNA found in bronchoalveolar lavage fluid. Sequences were analyzed using mothur, Ribosomal Database Project, Fast UniFrac, and Metastats. Our results showed a significant increase in microbial diversity with the development of COPD. The main phyla in all samples were Actinobacteria, Firmicutes, and Proteobacteria. Principal coordinate analyses demonstrated separation of control and COPD samples, but samples did not cluster based on disease severity. However, samples did cluster based on the use of inhaled corticosteroids and inhaled bronchodilators. Metastats analyses demonstrated an increased abundance of several oral bacteria in COPD samples.

What was studied?

This study examined how diet shapes gut microbial composition by comparing the fecal microbiota of children eating different diets. Researchers used high-throughput 16S rDNA sequencing together with biochemical analyses to characterize bacterial community composition and short-chain fatty acid output. The design set a fiber-rich, agrarian-style diet against a modern European diet to test whether microbiota differ along with dietary pattern.

Who was studied?

The study compared fecal samples from European children (EU) with those from children living in a rural African village in Burkina Faso (BF). The BF children's diet was high in fiber content and described as similar to the diet of early human settlements around the birth of agriculture. Exact sample sizes are not given in the abstract, but the comparison was structured as two defined pediatric cohorts, one European and one rural Burkinabe.

What were the most important findings?

BF children showed significant enrichment in Bacteroidetes and depletion in Firmicutes compared to EU children (P < 0.001). BF children also had a unique abundance of Prevotella and Xylanibacter, genera known to carry genes for cellulose and xylan hydrolysis, which were completely absent in EU children. BF children produced significantly more short-chain fatty acids than EU children (P < 0.001). Enterobacteriaceae, specifically Shigella and Escherichia, were significantly underrepresented in BF children relative to EU children (P < 0.05).

What are the greatest implications of this study?

The findings support the idea that gut microbiota coevolved with a polysaccharide-rich diet, helping BF children extract more energy from fiber through bacterial fermentation to short-chain fatty acids. The reduced abundance of Enterobacteriaceae, including Shigella and Escherichia, in the high-fiber BF group suggests diet may also influence the balance between beneficial fiber-degrading bacteria and potentially pathogenic Enterobacteriaceae. Together these results indicate that dietary pattern is a major driver of gut microbial ecology in children, with possible downstream effects on metabolic energy harvest and gut colonization resistance.