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STRONGYLID COINFECTIONS IN SYMPATRIC CHIMPANZEES AND GORILLAS FROM THE REPUBLIC OF THE CONGO REVEALED BY FECAL METAGENOMICS.

Soil-transmitted strongylid nematodes are common intestinal parasites of African great apes, yet most surveys have relied on microscopy or targeted PCR assays that are limited in taxonomic breadth and comparability across hosts. I reanalyzed 46 publicly available shotgun fecal metagenomes from sympatric central chimpanzees (Pan troglodytes troglodytes; n = 18) and western lowland gorillas (Gorilla gorilla gorilla; n = 28) in the Goualougo Triangle, Nouabalé-Ndoki National Park, Republic of the Congo, to test whether host species structures genus-level strongylid community composition and relative read signal. Non-host reads were classified against a custom strongylid-focused database targeting 4 genera repeatedly reported from African apes: Ancylostoma, Necator, Oesophagostomum, and Trichostrongylus. All 4 focal genera were detected in every library under baseline filtering, and multi-genus detection remained robust under increasingly stringent read-count thresholds. However, host species differed strongly in community composition. Chimpanzee libraries had relatively even genus-level profiles, whereas gorilla libraries were consistently Necator-dominated. Gorillas also had substantially higher relative strongylid read abundance. The results show that shotgun metagenomic reanalysis can recover host-structured strongylid community signals from wildlife samples and can complement targeted parasitological surveys in conservation and One Health surveillance.

Animals

Generation of a novel Slc7a9G105R mutant mouse identifies new biomarkers for cystinuria.

INTRODUCTION: Cystinuria is a rare inherited disease characterized by increased urinary cystine levels resulting in the formation of cystine stones in the urinary tract. Mutations in the genes encoding the cystine transporter complex, SLC3A1 and SLC7A9, are the primary drivers of the disease. Current mouse models used to study cystinuria rely on gene deficiency or spontaneous mutations in mice that do not accurately reflect the pathogenic mutations found in humans. METHODS: We generated a novel Slc7a9G105R knock-in mouse model in which glycine at position 105 is replaced by arginine, recapitulating the most common pathogenic mutation in human SLC7A9. Disease onset and progression were assessed using micro-CT imaging, fecal metagenomics, and urine and serum metabolomics and proteomics. RESULTS: Both male and female Slc7a9G105R mice developed a cystinuria phenotype by nine weeks of age, characterized by substantial cystine stone formation and increased urinary cystine, lysine, arginine, and ornithine. Slc7a9G105R mice displayed distinct serum and urinary metabolite profiles, mapped to dibasic amino acid pathways, and serum protein profiles, mapped to disease progression. Fecal metagenomics revealed that Slc7a9G105R mice had a heterogeneous microbiota with altered functional pathways, including increased L-cysteine biosynthesis. Antibiotic-induced depletion of the microbiota did not affect cystine stone burden but reduced urinary tract inflammation. Prophylactic or therapeutic dietary supplementation with alpha-lipoic acid reduced stone burden and inflammation, but it also caused urothelial damage. Untargeted metabolomics analysis following alpha-lipoic acid supplementation identified metabolites that can increase cystine solubility, reduce inflammation, and damage epithelial cells. Correlation analysis revealed novel serum metabolite biomarkers of stone burden, including 2-hydroxybutyric acid and 2-amino-2-thiazoline-4-carboxylic acid, which were also detected in human serum. CONCLUSIONS: Collectively, the Slc7a9G105R mutant mouse model offers a precise, rapid-onset, and translational platform for investigating cystinuria pathogenesis and evaluating potential therapeutic strategies.

SLC7A9

Metagenomic polymorphic toxin effector and immunity profiling predicts microbiome development and disease-related dysbiosis.

Bacteria use antagonistic interbacterial weapons, such as polymorphic toxin secretion systems (TSS), to compete for niches in the human gut microbiome. We hypothesized that TSS influence gut microbiome development and disease-related dysbiosis. We developed a bioinformatic marker gene approach (PolyProf) to quantify TSS including ~200 effector and immunity genes and applied it to ~15,000 publicly available human metagenomes. PolyProf alpha and beta diversity readily distinguished 12 different human disease states and enabled the construction of highly accurate linear regression classifier machine learning models. Elastic net machine learning models integrating bacterial taxonomy with PolyProf had strong predictive value for 12 disease states, outperforming models utilizing taxonomy alone. During microbiome development in the first year of life, PolyProf alpha diversity increases, and beta diversity becomes increasingly like the maternal microbiome, influenced by vertical transfer, delivery mode, and breastfeeding. PolyProf is related to strain sharing among adults through social interactions. In summary, TSS genes strongly correlate with microbiome development and interpersonal strain sharing, suggesting roles for interbacterial antagonism. Since PolyProf distinguishes diverse adult disease statuses, these dynamics may contribute to non-genetic inheritance.IMPORTANCEPrevious research has demonstrated that bacteria compete within the gut microbiome using toxin secretion systems (TSS). How TSS contribute to human microbiome development and the microbiome alterations observed in human diseases is not known. This study develops a new bioinformatic tool for profiling TSS-related genes in metagenomic data. Application of this approach to large-scale human fecal metagenomic data demonstrates the dynamic association of TSS during microbiome development, including the exchange of strains among social contacts. TSS gene abundance patterns are highly predictive of 12 disease states. This study advances the field by enabling TSS profiling in metagenomes and by identifying disease and microbiome development biomarkers that provide hypotheses for future mechanistic studies and may be useful for disease diagnosis.

Dysbiosis

Metagenome-Based Characterization of the Gut Virome Signatures in Patients With Gout.

The gut microbiome has been implicated in the development of autoimmune diseases, including gout. However, the role of the gut virome in gout pathogenesis remains underexplored. We employed a reference-dependent virome approach to analyze fecal metagenomic data from 102 gout patients (77 in the discovery cohort and 25 in the validation cohort) and 86 healthy controls (HCs) (63 and 23 in each cohort). A subset of gout patients in the discovery cohort provided longitudinal samples at Weeks 2, 4, and 24. Our analysis revealed significant alterations in the gut virome of gout patients, including reduced viral richness and shifts in viral family composition. Notably, Siphoviridae, Myoviridae, and Podoviridae were depleted, while Quimbyviridae, Retroviridae, and Schitoviridae were enriched in gout patients. We identified 359 viral operational taxonomic units (vOTUs) associated with gout. Enriched vOTUs in gout patients predominantly consisted of Fusobacteriaceae, Bacteroidaceae, and Selenomonadaceae phages, while control-enriched vOTUs included Ruminococcaceae, Oscillospiraceae, and Enterobacteriaceae phages. Longitudinal analysis revealed that a substantial proportion of these virome signatures remained stable over 6 months. Functional profiling highlighted the enrichment of viral auxiliary metabolic genes, suggesting potential metabolic interactions between viruses and host bacteria. Notably, gut virome signatures effectively discriminated gout patients from HCs, with high classification performance in the validation cohort. This study provides the first comprehensive characterization of the gut virome in gout, revealing its potential role in disease pathogenesis and highlighting virome-based signatures as promising biomarkers for gout diagnosis and future therapeutic strategies.

Humans

The Aggregated Gut Viral Catalogue (AVrC): A unified resource for exploring the viral diversity of the human gut.

The growing interest in the role of the gut virome in human health and disease, has led to several recent large-scale viral catalogue projects mining human gut metagenomes each using varied computational tools and quality control criteria. Importantly, there has been to date no consistent comparison of these catalogues' quality, diversity, and overlap. In this project, we therefore systematically surveyed nine previously published human gut viral catalogues. While these catalogues collectively screened >40,000 human fecal metagenomes, 82% of the recovered 345,613 viral sequences were unique to one catalogue, highlighting limited redundancy between the ressources and suggesting the need for an aggregated resource bringing these viral sequences together. We further expanded these viral catalogues by mining 7,867 infant gut metagenomes from 12 large-scale infant studies collected in 9 different countries. From these datasets, we constructed the Aggregated Gut Viral Catalogue (AVrC), a unified modular resource containing 1,018,941 dereplicated viral sequences (449,859 species-level vOTUs). Using computational inference tools, annotations were obtained for each vOTU representative sequence quality, viral taxonomy, predicted viral lifestyle, and putative host. This project aims to facilitate the reuse of previously published viral catalogues by the research community and follows a modular framework to enable future expansions as novel data becomes available.

Humans

Health-associated key gut microbiota drives the variation in community metabolic interactions in non-human primates.

Gut microbiota often undergo metabolic cross-feeding and resource competition. However, our understanding of global variations in these interactions and their implications for host health remain elusive. By analyzing a microbial genome catalog from 841 fecal metagenomes across 53 primate species worldwide, we identified key microbiota assigned to two taxa, i.e., Bacillota_A and Pseudomonadota, which well predicted the trade-off of community-level interaction types between metabolic competition and cooperation. Specifically, Bacillota_A species were inherently competitive and amino acid auxotrophic and typically found in anaerobic habitats. In contrast, members of Pseudomonadota were inherently cooperative, siderophore producers, and more abundant in aerobic conditions. Random forest models successfully distinguished unhealthy gut samples from healthy samples through the key competitive and cooperative microbiota, suggesting potential links between community metabolic interactions and host health. Together, this study enhances our mechanistic understanding of microbial interaction dynamism within complex gut ecosystems, offering new targets for understanding host health.

Animals

Farming reshapes the gut resistome, virulome, and mobilome of Cervidae.

The rapid expansion of cervid farming raises concerns about antimicrobial resistance (AMR) dissemination, yet its impact on the Cervidae gut microbiome remains poorly characterized. We integrated 89 newly sequenced fecal metagenomes with 599 publicly available datasets, comprising 285 metagenomes from farmed cervids and 370 from wild cervids, to construct a catalog of 15,494 non-redundant metagenome-assembled genomes (MAGs) representing 2,401 species. Our analysis demonstrates that farming profoundly reshapes the gut microbiome's functional composition. Specifically, farmed cervids exhibited significantly higher relative abundance, diversity, and heterogeneity of antimicrobial resistance genes (ARGs) compared to wild counterparts. We observed a robust synergistic relationship between ARGs, virulence factor genes, and mobile genetic element (MGE)-associated genes, identifying 70 ARG-MGE combinations as evidence of potential horizontal gene transfer. Plasmid profiling further suggested that a subset of ARGs may be associated with conjugative plasmids, with plasmid-associated ARGs being significantly more abundant in farmed than in wild cervids. Virome analyses indicated that bacteriophages, particularly Siphoviridae, may serve as mobile reservoirs for ARGs. Notably, Cervidae shared 268 ARG types with humans, including 23 high-risk genes associated with resistance to clinically important antibiotics (e.g. tetX1, vanRD, and bla-CTX-M-178), with Escherichia coli as a key cross-host carrier. These findings highlight that human-impacted cervid gut microbiomes are significant environmental reservoirs of clinically relevant AMR, underscoring the necessity for enhanced antibiotic stewardship and resistance surveillance in managed wildlife within a One Health framework.

Animals

Major depletion of insulin sensitivity-associated taxa in the gut microbiome of persons living with HIV controlled by antiretroviral drugs.

BACKGROUND: Persons living with HIV (PWH) harbor an altered gut microbiome (higher abundance of Prevotella and lower abundance of Bacillota and Ruminococcus lineages) compared to non-infected individuals. Some of these alterations are linked to sexual preference and others to the HIV infection. The relationship between these lineages and metabolic alterations, often present in aging PWH, has been poorly investigated. METHODS: In this study, we compared fecal metagenomes of 25 antiretroviral-treatment (ART)-controlled PWH to three independent control groups of 25 non-infected matched individuals by means of univariate analyses and machine learning methods. Moreover, we used two external datasets to validate predictive models of PWH classification. Next, we searched for associations between clinical and biological metabolic parameters with taxonomic and functional microbiome profiles. Finally, we compare the gut microbiome in 7 PWH after a 17-week ART switch to raltegravir/maraviroc. RESULTS: Three major enterotypes (Prevotella, Bacteroides and Ruminococcaceae) were present in all groups. The first Prevotella enterotype was enriched in PWH, with several of characteristic lineages associated with poor metabolic profiles (low HDL and adiponectin, high insulin resistance (HOMA-IR)). Conversely butyrate-producing lineages were markedly depleted in PWH independently of sexual preference and were associated with a better metabolic profile (higher HDL and adiponectin and lower HOMA-IR). Accordingly with the worst metabolic status of PWH, butyrate production and amino-acid degradation modules were associated with high HDL and adiponectin and low HOMA-IR. Random Forest models trained to classify PWH vs. control on taxonomic abundances displayed high generalization performance on two external holdout datasets (ROC AUC of 80-82%). Finally, no significant alterations in microbiome composition were observed after switching to raltegravir/maraviroc. CONCLUSION: High resolution metagenomic analyses revealed major differences in the gut microbiome of ART-controlled PWH when compared with three independent matched cohorts of controls. The observed marked insulin resistance could result both from enrichment in Prevotella lineages, and from the depletion in species producing butyrate and involved into amino-acid degradation, which depletion is linked with the HIV infection.

Humans

Interconnected influences of diet, gut microbiome, and metabolome on cognition across three metabolomics platforms.

Cognitive impairment is increasing with global aging, yet mechanisms linking diet, the gut microbiome, and metabolism to cognitive function remain unclear. To investigate a diet-microbiome-metabolome axis associated with cognition, we integrated fecal metagenomics, diet, and multi-platform plasma metabolomics in 505 older adults from four ADRCs. Several microbes broadly associated with circulating metabolites were also linked to multiple measures of cognitive performance. These taxa exhibited coordinated metabolic signatures, with cognition-positive microbes associated with antioxidant, lipid, and microbial-host co-metabolites, and microbes negatively associated with cognition were linked to inflammatory and aromatic amino acid-derived metabolites. Dietary patterns, particularly the Healthy Eating Index Greens and Beans component, were associated with microbial composition and metabolomic structure. Mediation analyses supported a diet-microbe-metabolite-cognition pathway, while metabolites remained associated with cognition after accounting for microbial features. These findings highlight the metabolome as a central integrator of diet, microbial activity, and cognitive function.

Journal Article

Microbiome features associated with persistent intestinal carriages of Escherichia coli ST131 in a Southeast Asian cohort study.

Escherichia coli sequence-type 131 (ST131) is the dominant global extraintestinal pathogen capable of asymptomatic intestinal carriage and sustained household transmission, challenging infection control. Despite its clinical significance, the ecological determinants of gut persistence remain poorly understood. We performed shotgun metagenomics on fecal samples to investigate gut microbiome features associated with ST131-positive samples, distinct host carrier statuses (persistent, intermittent and non-carriers) and household risks in a study of a Southeast Asian cohort. Here, we show that ST131 carriage was associated with compositional shifts without reducing species alpha-diversity. Regression analyses identified depletion of commensal taxa and the 1,5-anhydrofructose degradation pathway in ST131-positive samples. Persistent carriers exhibited highly perturbed microbiome enriched with pathobionts, aerobactin- and lipopolysaccharide (LPS)-biosynthesis pathways. Comparing household risk groups to control, revealed that biotin biosynthesis and 1,5-anhydrofructose degradation may influence ST131 co-colonization through both direct and indirect mechanisms. Machine learning analyses identified metabolic pathways as stronger discriminators of persistent carriage than taxonomic features. Genomic-resolved analysis of clinical ST131 isolates revealed conserved genes for iron-acquisition, LPS and antibiotic resistance determinants. Overall, while commensals and metabolism may influence initial ST131 colonization, persistent carriage is associated with specific microbial and metabolic adaptations, providing potential targets to limit intestinal ST131 persistence.

Humans

Maternal secretor status and human milk oligosaccharides influence the infant gut resistome.

The infant gut resistome is established early in life and is shaped by perinatal exposures, yet the mechanisms underlying its modulation remain unclear. We combined shotgun metagenomics of fecal samples from 57 one-month-old infants and paired milk samples from 50 mothers in the MAMI cohort to investigate the influence of maternal secretor status on early-life resistome development. Longitudinal follow-up at 6 and 12 months, and also further validation in the independent Lifelines NEXT (LLNEXT) cohort, support our findings. Cesarean section (C-section) was associated with increased antibiotic resistance gene (ARG) diversity, whereas exclusive breastfeeding reduced ARG abundance and diversity. Maternal secretor status further modified resistome composition among exclusively breastfed infants. Human milk oligosaccharide profiling identified specific glycans underlying these associations, with 2'-fucosyllactose and 6'-sialyllactose showing negative correlations with distinct ARG classes. These findings identify human milk composition as a key determinant of early-life resistome assembly and a potential target for modulating antimicrobial resistance.

Humans

Decreased intestinal abundance of Akkermansia muciniphila is associated with metabolic disorders among people living with HIV.

BACKGROUND: Previous studies have shown changes in gut microbiota after human immunodeficiency virus (HIV) infection, but there is limited research linking the gut microbiota of people living with HIV (PLWHIV) to metabolic diseases. METHODS: A total of 103 PLWHIV were followed for 48 weeks of anti-retroviral therapy (ART), with demographic and clinical data collected. Gut microbiome analysis was conducted using metagenomic sequencing of fecal samples from 12 individuals. Nonalcoholic fatty liver disease (NAFLD) was diagnosed based on controlled attenuation parameter (CAP) values of 238 dB/m from liver fibro-scans. Participants were divided based on the presence of metabolic disorders, including NAFLD, overweight, and hyperlipidemia. Akkermansia abundance in stool samples was measured using RT-qPCR, and Pearson correlation and logistic regression were applied for analysis. RESULTS: Metagenomic sequencing revealed a significant decline in gut Akkermansia abundance in PLWHIV with NAFLD. STAMP analysis of public datasets confirmed this decline after HIV infection, while KEGG pathway analysis identified enrichment of metabolism-related genes. A prospective cohort study with 103 PLWHIV followed for 48 weeks validated these findings. Akkermansia abundance was significantly lower in participants with NAFLD, overweight, and hyperlipidemia at baseline, and it emerged as an independent predictor of NAFLD and overweight. Negative correlations were observed between Akkermansia abundance and both CAP values and body mass index (BMI) at baseline and at week 48. At the 48-week follow-up, Akkermansia remained a predictive marker for NAFLD. CONCLUSIONS: Akkermansia abundance was reduced in PLWHIV with metabolic disorders and served as a predictive biomarker for NAFLD progression over 48 weeks of ART.

Humans

Metagenomic profiling of gut microbiome in post-cholecystectomy patients with diarrhea: a nested case-control study.

BACKGROUND: Cholecystectomy can cause diarrhea, with an incidence as high as 57.2%, seriously impacting patient prognosis. To investigate the gut dysbiosis following cholecystectomy and identify microbial biomarkers and functional genomics associated with post-cholecystectomy diarrhea (PCD), we conducted a nested case-control study within a prospective cohort. METHODS: We enrolled a cohort of 160 patients. At follow-up completion, 30 patients who developed PCD were matched with 30 non-PCD (NPCD) controls. 16 S rRNA sequencing was used to analyze gut microbiota structure and diversity (mainly at genus level). Representative fecal samples underwent metagenomic sequencing for species level and genetic differential analysis. RESULTS: The potentially pathogenic bacterial species Coprococcus comes and Blautia sp. were significantly enriched in the gut microbiota of PCD patients, with their abundance positively correlated with the degree of intestinal inflammation. In contrast, the potentially beneficial bacterial species Bacteroides intestinalis and Prevotella copri, known to contribute to lipid metabolism and play a role in modulating gut immunity and suppressing inflammatory responses, were found to be significantly depleted in PCD patients. Further metagenomic functional analysis revealed significant enrichment of pathways related to cell motility, membrane transport, and sulfur metabolism in PCD patients. CONCLUSIONS: This work identified potential beneficial and pathogenic bacterial species associated with the onset of PCD, as well as significantly enriched functional pathways within the intestinal microbiota. These findings provide a scientific basis for elucidating the relationship between PCD and gut microbiota, and provide candidate microbial signatures and functional pathways that may inform future microbiota-targeted strategies, pending external and mechanistic validation.

Humans

Gut microbiota dynamics and metabolic pathways associated with bleomycin-induced pulmonary fibrosis progression.

BACKGROUND: Pulmonary fibrosis (PF) is a progressive respiratory disease characterized by epithelial injury, aberrant repair and excessive extracellular matrix deposition. Although the gut-lung axis is increasingly implicated in respiratory disorders, stage-resolved characterization of gut microbiota taxonomic and functional potential during PF development is limited. METHODS: We established a bleomycin-induced murine PF model and performed cross-sectional shotgun metagenomic sequencing of fecal samples from separate cohorts at three defined stages: baseline (control), day 7 (early fibrosis; M7), and day 14 (established fibrosis; M14). Microbial taxonomy, alpha/beta diversity, and predicted functional capacity were inferred using Kyoto Encyclopedia of Genes and Genomes (KEGG) and Carbohydrate-Active enZymes (CAZy) annotations; associations were assessed using Procrustes and Spearman correlation analyses. RESULTS: Histopathology and immunohistochemistry confirmed progressive fibrogenesis with increased TGF-β1 and α-SMA expression. Compared with baseline, bleomycin-treated groups exhibited stage-specific shifts in gut microbial composition, including depletion of mucin-associated taxa (e.g., Prevotella, Akkermansia muciniphila) and expansion of Muribaculaceae- and Clostridiaceae-affiliated taxa. Alpha and beta diversity metrics differed across groups. KEGG/CAZy-based annotations revealed predicted, stage-dependent changes in microbial metabolic potential, including early reductions in pathways related to amino acid and glycan metabolism (M7) and later increases in predicted starch/sucrose catabolism, phosphotransferase system (PTS) representation, and secondary bile acid biosynthesis (M14). Correlation analyses linked compositional shifts to these predicted functional changes. CONCLUSION: In a stage-resolved, cross-sectional study, bleomycin-associated pulmonary fibrosis was accompanied by compositional and predicted functional alterations in the gut microbiota. These data identify candidate taxa and predicted pathways for follow-up mechanistic testing, but functional (metabolomic) and causality experiments are required to confirm whether and how microbial changes contribute to PF pathogenesis.

Animals

Hospitalization throws the preterm gut microbiome off-key.

Environmental exposures substantially influence the infant gut microbiome. In this issue of Cell Host & Microbe, Thänert et al.1 characterize how medical interventions in the neonatal intensive care unit (NICU) shape gut microbiome dynamics in the first months of life by analyzing over 2,500 fecal samples with metagenomics and metatranscriptomics.

Gastrointestinal Microbiome

Prevalence and chronology of colibactin-associated mutational processes and their microbiome spectra in Japanese colorectal cancer.

The incidence of colorectal cancer (CRC) has risen in recent decades, with a disproportionate increase observed among younger individuals in Japan and other countries. The etiological contribution of the gut microbiota to CRC pathogenesis is recognized, yet the mechanisms involved remain to be fully clarified. Here we integrated whole-genome sequencing (WGS) and transcriptome profiling of CRC with whole-genome metagenomic sequencing of fecal samples to interrogate host-microbiome interactions at high resolution. Application of interpretable artificial intelligence enabled the stratification of CRC into four distinct microbiome-informed subtypes. WGS analysis identified mutational signatures SBS88 and ID18, linked to colibactin exposure, as early clonal events detected in 44.8% of non-hypermutated patients. Notably, these signatures were significantly more frequent among patients born after the 1960s. Microbiome-based subclassification revealed subtype-specific clinical and molecular features. Collectively, our findings indicate that colibactin exposure constitutes a prevalent and potentially modifiable risk factor for CRC in the Japanese population.

Humans

Exploring the hypothetical role of Bacteroides species in depression progression: insights from metagenomic analysis.

Depression, a psychiatric disorder with significant morbidity and mortality, has a complex etiology. Recent advances in microbiome research have highlighted the potential role of fecal microbiota in depression pathogenesis. This study utilized shotgun metagenomic sequencing to compare the fecal microbiota of 28 depression patients and 26 healthy individuals. Significant differences in fecal microbiota composition were observed between the two groups. We generated 350 non-redundant high-quality metagenome-assembled genomes (MAGs) by binning and conducted comparisons between the depression and control groups. Notably, we found that the MAGs enriched in people with depression mostly belonged to Bacteroides, indicating a close link between Bacteroides abundance and the development of depression, suggesting that Bacteroides might be a potential culprit for depression. In the depression group, we found that the module of nitric oxide synthesis was remarkably enriched, and all Bacteroides MAGs contained genes annotated as nitric oxide synthase, suggesting that increased levels of Bacteroides may contribute to elevated nitric oxide synthesis. A distinct microbial signature consisting of Arthrobacter sp._U41, Bacillus cereus, Campylobacter rectus, and Pasteurella dagmatis accurately discriminates between depressed individuals and healthy controls, achieving an average area under the receiver operating characteristic curve of 0.950. This research sheds light on the potential role of fecal microbiota in depression and highlights specific metabolic pathways and microbial markers for further investigation.IMPORTANCEThis research highlighted significant differences in the composition and function of fecal microbiota between individuals with depression and healthy individuals, particularly the enrichment of Bacteroides metagenome-assembled genomes (MAGs) in depression patients. The upregulation of the nitric oxide synthesis pathway associated with these MAGs belonging to Bacteroides in the gut of depression patients had also been observed. The selected bacterial biomarkers reliably differentiate depression cases from healthy controls with high diagnostic accuracy (mean area under the receiver operating characteristic curve = 0.950). Our results suggest the importance of exploring microbial markers as potential diagnostic and therapeutic targets in managing depression.

Humans

Characterization of gut microbiota signatures in Indian preterm infants with necrotizing enterocolitis: a shotgun metagenomic approach.

INTRODUCTION: Necrotizing enterocolitis (NEC) is an inflammatory bowel disease that primarily affects preterm infants. Predisposing risk factors for NEC include prematurity, formula feeding, anemia, and sepsis. To date, no studies have investigated the gut microbiota of preterm infants with NEC in India. METHOD: In the current study, shotgun metagenomic sequencing was performed on fecal samples from premature infants with NEC and healthy preterm infants (n = 24). Sequencing was conducted using the NovaSeq X Plus platform, generating 2 &#xd7; 150 bp paired-end reads. The infants were matched based on gestational age and postnatal age. RESULT: The median time to NEC diagnosis was 9 days (range: 1-30 days). Taxonomic analysis revealed a high prevalence of Enterobacteriaceae at the family level, with the genera Klebsiella and Escherichia particularly prominent in neonates with NEC. No statistically significant differences in alpha or beta diversity were observed between stool samples from infants with and without NEC. Linear regression analysis demonstrated that Enterobacteriaceae were significantly more abundant in stool samples from infants with NEC than without NEC (q < 0.05). Differential abundance analysis using Linear Discriminant Analysis Effect Size (LEfSe) identified Klebsiella pneumoniae and Escherichia coli as enriched in the gut microbiota of preterm infants with NEC. Functional analysis revealed an increase in genes associated with lipopolysaccharide (LPS) O-antigen, the type IV secretion system (T4SS), the L-rhamnose pathway, quorum sensing, and iron transporters, including ABC transporters, in stool samples from infants with NEC. CONCLUSION: The high prevalence of Enterobacteriaceae and enrichment of LPS O-antigen and T4SS genes may be associated with NEC in Indian preterm infants.

Humans