Human Gut Microbiota Research Articles

Dietary fibre optimisation in support of global health.

The human gut microbiota influences its host via multiple molecular pathways, including immune system interactions, the provision of nutrients and regulation of host physiology. Dietary fibre plays a crucial role in maintaining a healthy microbiota as its primary nutrient and energy source. Industrialisation has led to a massive decrease of habitual fibre intake in recent times, and fibre intakes across the world are below the national recommendations. This goes hand in hand with other factors in industrialised societies that may negatively affect the gut microbiota, such as medication and increased hygiene. Non-communicable diseases are on the rise in urbanised societies and the optimisation of dietary fibre intake can help to improve global health and prevent disease. Early life interventions shape the developing microbiota to counteract malnutrition, both in the context of industrialised nations with an overabundance of cheap, highly processed foods, as well as in Low- and Middle-Income Countries (LMICs). Adequate fibre intake should, however, be maintained across the life course to promote health. Here we will discuss the current state of dietary fibre research in the global context and consider different intervention approaches.

Clostridioides difficile and Gut Microbiota: From Colonization to Infection and Treatment.

Clostridioides difficile is the main causative agent of antibiotic-associated diarrhea (AAD) in hospitals in the developed world. Both infected patients and asymptomatic colonized individuals represent important transmission sources of C. difficile. C. difficile infection (CDI) shows a large range of symptoms, from mild diarrhea to severe manifestations such as pseudomembranous colitis. Epidemiological changes in CDIs have been observed in the last two decades, with the emergence of highly virulent types and more numerous and severe CDI cases in the community. C. difficile interacts with the gut microbiota throughout its entire life cycle, and the C. difficile's role as colonizer or invader largely depends on alterations in the gut microbiota, which C. difficile itself can promote and maintain. The restoration of the gut microbiota to a healthy state is considered potentially effective for the prevention and treatment of CDI. Besides a fecal microbiota transplantation (FMT), many other approaches to re-establishing intestinal eubiosis are currently under investigation. This review aims to explore current data on C. difficile and gut microbiota changes in colonized individuals and infected patients with a consideration of the recent emergence of highly virulent C. difficile types, with an overview of the microbial interventions used to restore the human gut microbiota.

Human gut microbiota composition associated with international travels

ObjectiveThe objective of this study was to evaluate whether long stays in non-European countries influence the composition, diversity, and dynamics of gut microbiota, considering the potential impact of travelling, close contact with new people, and consumption of water and food. MethodsTwo prospective cohorts were analyzed: (i) A longitudinal cohort comprising long-term travellers who provided fecal samples before and after their travels. (ii) A cohort consisting of long-term travellers and recently arrived migrants from non-European countries, which was compared with non-traveller controls. Each participant self-collected fecal samples and provided demographic and epidemiological data. Microbiota was characterized through 16 S rRNA gene sequencing. ResultsThe longitudinal cohort comprised 17 subjects. A trend toward higher bacterial diversity was observed after travelling (Shannon index 3.12vs3.26). When comparing 84 travellers/migrants with 97 non-travellers, a confirmed association of higher diversity levels with travelling was observed (Phylogenetic diversity: 22.1vs20.9). Specific genera enriched in travellers' gut microbiota were identified, including Escherichia/Shigella, Bacteroides, and Parabacteroides. The analysis revealed three major clusters with profound differences in their bacterial composition, which exhibited differential distribution between travellers and non-travellers (Adonis P < 0.001; R2 = 30.6 %). Two clusters were more frequently observed in travellers: The first cluster, characterized by dominance of Escherichia/Shigella, exhibited the lowest levels of richness and diversity. The second cluster, dominated by Faecalibacterium and Bacteroides, displayed the highest richness and diversity patterns. ConclusionThese findings highlight the diverse impact of international travel on gut microbiota composition and underscore the importance of considering microbiota resilience and diversity in understanding the health implications.

Hierarchical multi-task deep learning-assisted construction of human gut microbiota reactive oxygen species-scavenging enzymes database.

In the process of oxygen reduction, reactive oxygen species (ROS) are generated as intermediates, including superoxide anion (O2-), hydrogen peroxide (H2O2), and hydroxyl radicals (OH-). ROS can be destructive, and an imbalance between oxidants and antioxidants in the body can lead to pathological inflammation. Inappropriate ROS production can cause oxidative damage, disrupting the balance in the body and potentially leading to DNA damage in intestinal epithelial cells and beneficial bacteria. Microorganisms have evolved various enzymes to mitigate the harmful effects of ROS. Accurately predicting the types of ROS-scavenging enzymes (ROSes) is crucial for understanding the oxidative stress mechanisms and formulating strategies to combat diseases related to the "gut-organ axis." Currently, there are no available ROSes databases (DBs). In this study, we propose a systematic workflow comprising three modules and employ a hierarchical multi-task deep learning approach to collect, expand, and explore ROSes-related entries. Based on this, we have developed the human gut microbiota ROSes DB (http://39.101.72.186/), which includes 7,689 entries. This DB provides user-friendly browsing and search features to support various applications. With the assistance of ROSes DB, various communication-based microbial interactions can be explored, further enabling the construction and analysis of the evolutionary and complex networks of ROSes DB in human gut microbiota species.IMPORTANCEReactive oxygen species (ROS) is generated during the process of oxygen reduction, including superoxide anion, hydrogen peroxide, and hydroxyl radicals. ROS can potentially cause damage to cells and DNA, leading to pathological inflammation within the body. Microorganisms have evolved various enzymes to mitigate the harmful effects of ROS, thereby maintaining a balance of microorganisms within the host. The study highlights the current absence of a ROSes DB, emphasizing the crucial importance of accurately predicting the types of ROSes for understanding oxidative stress mechanisms and developing strategies for diseases related to the "gut-organ axis." This research proposes a systematic workflow and employs a multi-task deep learning approach to establish the human gut microbiota ROSes DB. This DB comprises 7,689 entries and serves as a valuable tool for researchers to delve into the role of ROSes in the human gut microbiota.

Prosthetic joint infection caused by Mediterraneibacter gnavus following total knee arthroplasty, challenges in anaerobic bacteria identification

BackgroundMediterraneibacter gnavus is a Gram positive, non-sporulated, obligate anaerobe diplococci. It was first described in 1974 by Moore et al. (under the name Ruminococcus gnavus) from faeces and contents of the gastrointestinal tract of humans. It is a relatively common member of the human gut microbiota, nevertheless its role as a pathogenic bacterium has not been completely elucidated yet and it seems to depend on numerous factors, including those of the host. Here we present a case of prosthetic joint infection following total knee arthroplasty by M. gnavus.Case presentationA 74 years old patient was admitted to the emergency department presenting with acute onset of left knee pain and swelling 20 days after total left knee arthroplasty. Follow-up revealed erythema and oedema without signs of fluctuation or purulent discharge from the surgical wound and elevated inflammatory reactants. Synovial fluid was taken for bacterial culture and antibiotic treatment with ceftazidime and daptomycin was established. Examination of the synovial fluid revealed abundant polymorphonuclear leucocytes, without visualizing bacteria. After four days of incubation, anaerobic culture exhibit growth of small, grey, umbilicated colonies in pure culture on Schaedler agar. The microorganism was identified as R. gnavus by MALDI-TOF (Bruker Daltonics) and M. gnavus by 16S ribosomal bacterial sequencing. The isolated showed susceptibility to the most commonly used anaerobicidal antibiotics except for clindamycin. Surgical treatment and infection source control included DAIR (debridement, antibiotics, and implant retention) and vacuum assisted therapy. The patient was discharged after six weeks with a 3-month course of oral amoxicillin as consolidation therapy. Subsequent follow-up revealed adequate wound healing with no signs of infection.ConclusionsMediterraneibacter gnavus have been reported as the causal microorganism in a range of human infections, nevertheless its identification remains challenging. Infection of prosthetic joints by anaerobic microorganisms is uncommon and is not considered in its empirical antibiotic treatment, thus, correct and swift identification of anaerobic bacteria in these cases is paramount.

Comparison between 16S rRNA and shotgun sequencing in colorectal cancer, advanced colorectal lesions, and healthy human gut microbiota

BackgroundGut dysbiosis has been associated with colorectal cancer (CRC), the third most prevalent cancer in the world. This study compares microbiota taxonomic and abundance results obtained by 16S rRNA gene sequencing (16S) and whole shotgun metagenomic sequencing to investigate their reliability for bacteria profiling. The experimental design included 156 human stool samples from healthy controls, advanced (high-risk) colorectal lesion patients (HRL), and CRC cases, with each sample sequenced using both 16S and shotgun methods. We thoroughly compared both sequencing technologies at the species, genus, and family annotation levels, the abundance differences in these taxa, sparsity, alpha and beta diversities, ability to train prediction models, and the similarity of the microbial signature derived from these models.ResultsAs expected, the results showed that 16S detects only part of the gut microbiota community revealed by shotgun, although some genera were only profiled by 16S. The 16S abundance data was sparser and exhibited lower alpha diversity. In lower taxonomic ranks, shotgun and 16S highly differed, partially due to a disagreement in reference databases. When considering only shared taxa, the abundance was positively correlated between the two strategies. We also found a moderate correlation between the shotgun and 16S alpha-diversity measures, as well as their PCoAs. Regarding the machine learning models, only some of the shotgun models showed some degree of predictive power in an independent test set, but we could not demonstrate a clear superiority of one technology over the other. Microbial signatures from both sequencing techniques revealed taxa previously associated with CRC development, e.g., Parvimonas micra.ConclusionsShotgun and 16S sequencing provide two different lenses to examine microbial communities. While we have demonstrated that they can unravel common patterns (including microbial signatures), shotgun often gives a more detailed snapshot than 16S, both in depth and breadth. Instead, 16S will tend to show only part of the picture, giving greater weight to dominant bacteria in a sample. Therefore, we recommend choosing one or another sequencing technique before launching a study. Specifically, shotgun sequencing is preferred for stool microbiome samples and in-depth analyses, while 16S is more suitable for tissue samples and studies with targeted aims.

Gut colonization with antibiotic-resistant Escherichia coli pathobionts leads to disease severity in ulcerative colitis

Escherichia coli is a Gram-negative commensal of human gut. Surprisingly, the role of E. coli in the pathogenesis of ulcerative colitis (UC) has not been explored until now. Human gut microbiota composition and meta-gut resistome were evaluated using metagenomics. Antibiotic susceptibility of E. coli isolates against different class of antibiotics was investigated. Further, the genome sequence analysis of E. coli isolates was performed to gain insight into the antimicrobial resistance (AMR) mechanism and virulence factors. Gut proteome of UC and non-UC was examined to understand the effect of resistant bacteria on host physiology. In UC patients, meta-gut resistome was found to be dominated by AMR genes (829) compared to healthy controls (HC) [518]. The metagenome study revealed a higher prevalence of AMR genes in the rural population (378 in HC; 607 in UC) compared to the urban (340 in HC; 578 in UC). Approximately, 40% of all E. coli isolates were multi-drug resistant (MDR), with higher prevalence in UC (43.75%) compared to HC (33.33%). Up-regulated expression of antimicrobial human proteins (lactotransferrin, azurocidin, cathepsin G, neutrophil elastase, and neutrophil defensin 3) and inflammatory mediator (Protein S100-A9 and Protein S100-A8) suggest microbial infection in UC gut. In addition to the conventional culturomics method, a multi-omics strategy provides deeper insights into the disease etiology, emergence of MDR pathobionts, and their roles in the disruption of the healthy gut environment in UC patients.

Enteropathway: the metabolic pathway database for the human gut microbiota.

The human gut microbiota produces diverse, extensive metabolites that have the potential to affect host physiology. Despite significant efforts to identify metabolic pathways for producing these microbial metabolites, a comprehensive metabolic pathway database for the human gut microbiota is still lacking. Here, we present Enteropathway, a metabolic pathway database that integrates 3269 compounds, 3677 reactions, and 876 modules that were obtained from 1012 manually curated scientific literature. Notably, 698 modules of these modules are new entries and cannot be found in any other databases. The database is accessible from a web application (https://enteropathway.org) that offers a metabolic diagram for graphical visualization of metabolic pathways, a customization interface, and an enrichment analysis feature for highlighting enriched modules on the metabolic diagram. Overall, Enteropathway is a comprehensive reference database that can complement widely used databases, and a tool for visual and statistical analysis in human gut microbiota studies and was designed to help researchers pinpoint new insights into the complex interplay between microbiota and host metabolism.

Effects of Lactocaseibacillus paracasei subsp. paracasei NTU 101 on gut microbiota: a randomized, double-blind, placebo-controlled clinical study.

Lactocaseibacillus paracasei subsp. paracasei NTU 101 (NTU101) is a well-known commercial probiotic with multiple health beneficial effects. In this study, the gut microbiota modulation effect of an NTU 101 product, Vigiis 101-LAB, on healthy human was investigated in a randomized, double-blind, placebo-controlled human trial. Vigiis 101-LAB significantly modulated human gut microbiota at fourth and sixth weeks of trial (anosim analysis, P = 0.001). It also significantly improved peristalsis (P = 0.003) and shortened defecation interval of subjects. The shift of gut microbiota is significantly fit with defecation interval (P = 0.009) and stool shape (P = 0.001) of subjects. Our results suggest that Vigiis 101-LAB promotes human intestinal health with improvement of peristalsis and fecal quality. The gut modulation effects of Vigiis 101-LAB subsequently raised the abundance of vitamin B7, vitamin K, pyrimidine and purine biosynthesis pathways. Vigiis 101-LAB may promote peristalsis via purinergic pathway and possibly conferring prophylactic benefits against irritable bowel syndrome with constipation. © 2024 Society of Chemical Industry.

Gut microbiota: a potential influencer of insomnia occurring after COVID-19 infection.

The prevalence of insomnia has increased in recent years, significantly affecting the lives of many individuals. Coronavirus disease 2019 (COVID-19) infection has been found to have a substantial impact on the human gut microbiota (GM). Clinical studies have shown that the high prevalence, prolonged duration, and refractory treatment of insomnia symptoms following the COVID-19 pandemic may be related to the effect of COVID-19 infection on the GM. Therefore, the GM may be a potential target for the treatment of insomnia following COVID-19 infection. However, relevant studies have not been well-documented, and the GM has not been sufficiently analyzed in the context of insomnia treatment. Herein, we review the interaction between sleep and the GM, summarize the characteristics of COVID-19-induced abnormal changes in the GM and metabolites in patients with insomnia, and discuss potential mechanisms, including metabolic, immune, and neural pathways, by which these abnormal changes in the GM cause insomnia as well as the factors affecting the GM. Finally, we discuss the prospect of modulating the host GM community for the effective treatment of insomnia after COVID-19 infection and the need for further clinical studies.

Exploring the Gut Microbiota: Key Insights Into Its Role in Obesity, Metabolic Syndrome, and Type 2 Diabetes.

The gut microbiota (GM), comprising trillions of microorganisms in the gastrointestinal tract, is a key player in the development of obesity and related metabolic disorders, such as type 2 diabetes (T2D), metabolic syndrome (MS), and cardiovascular diseases. This mini-review delves into the intricate roles and mechanisms of the GM in these conditions, offering insights into potential therapeutic strategies targeting the microbiota. The review elucidates the diversity and development of the human GM, highlighting its pivotal functions in host physiology, including nutrient absorption, immune regulation, and energy metabolism. Studies show that GM dysbiosis is linked to increased energy extraction, altered metabolic pathways, and inflammation, contributing to obesity, MS, and T2D. The interplay between dietary habits and GM composition is explored, underscoring the influence of diet on microbial diversity and metabolic functions. Additionally, the review addresses the impact of common medications and therapeutic interventions like fecal microbiota transplantation on GM composition. The evidence so far advocates for further research to delineate the therapeutic potential of GM modulation in mitigating obesity and metabolic diseases, emphasizing the necessity of clinical trials to establish effective and sustainable treatment protocols.

Association between major depressive disorder and gut microbiota dysbiosis.

Major depressive disorder (MDD) affects 300 million people globally. Because dysbiosis may alter the central nervous system, it plays a potential role in this disorder. Dysbiosis is characterized by a decrease in microbial diversity and an increase in proinflammatory species. The human gut microbiota refers to the trillions of microbes, such as bacteria, that live in the human gut. The purpose of this study was to compare the gut microbiota of patients with MDD with that of healthy controls. This case-control study involved 35 MDD cases and 35 healthy age- and sex-matched controls. Stool samples were collected and subjected to quantitative real-time PCR. Four intestinal bacterial phyla (firmicutes, bacteroidetes, actinobacteria, and proteobacteria) were investigated by 16SrRNA analysis. The findings indicated a relative abundance of bacteroidetes to firmicutes in the control and case groups was 0.66 vs. 1.33, respectively (p < .05). There were no significant differences in actinobacteria or proteobacteria among those in the MDD group compared to the healthy control group. Gut microbiota dysbiosis may contribute to the onset of depression, underscoring the importance of understanding the relationship between MDD and gut microbiota. Firmicutes, which produce short-chain fatty acids, are crucial for intestinal health. However, dysbiosis can disrupt the gut microbiota, impacting the central nervous system and contributing to the onset of depression.

Development of a Recombineering System for the Acetogen Eubacterium limosum with Cas9 Counterselection for Markerless Genome Engineering.

Eubacterium limosum is a Clostridial acetogen that efficiently utilizes a wide range of single-carbon substrates and contributes to metabolism of health-associated compounds in the human gut microbiota. These traits have led to interest in developing it as a platform for sustainable CO2-based biofuel production to combat carbon emissions, and for exploring the importance of the microbiota in human health. However, synthetic biology and metabolic engineering in E. limosum have been hindered by the inability to rapidly make precise genomic modifications. Here, we screened a diverse library of recombinase proteins to develop a highly efficient oligonucleotide-based recombineering system based on the viral recombinase RecT. Following optimization, the system is capable of catalyzing ssDNA recombination at an efficiency of up to 2%. Addition of a Cas9 counterselection system eliminated unrecombined cells, with up to 100% of viable cells encoding the desired mutation, enabling creation of genomic point mutations in a scarless and markerless manner. We deployed this system to create a clean knockout of the extracellular polymeric substance (EPS) gene cluster, generating a strain incapable of biofilm formation. This approach is rapid and simple, not requiring laborious homology arm cloning, and can readily be retargeted to almost any genomic locus. This work overcomes a major bottleneck in E. limosum genetic engineering by enabling precise genomic modifications, and provides both a roadmap and associated recombinase plasmid library for developing similar systems in other Clostridia of interest.

Exploring the diagnostic potential of immunoglobulin A-microbiota interplay in liver cirrhosis and spontaneous bacterial peritonitis.

The human gut microbiota significantly impacts health, including liver conditions like liver cirrhosis (LC) and spontaneous bacterial peritonitis (SBP). Immunoglobulin A (IgA) plays a central role in maintaining gut microbial balance. Understanding IgA's interplay with gut microbiota and liver health is crucial. This study explores the relationship between fecal IgA levels, gut microbiota, and liver injury severity. A total of 69 LC patients and 30 healthy controls were studied. Fecal IgA levels were measured using ELISA, and IgA-coated bacteria were quantified via flow cytometry. Microbiota diversity and composition were assessed through 16S rRNA sequencing. Liver injury severity was graded using the Child-Pugh score. Statistical analyses determined correlations. LC patients had higher fecal IgA levels than controls, correlating positively with liver injury severity. Microbiota diversity decreased with severity, accompanied by shifts in composition favoring pro-inflammatory species. Ralstonia abundance positively correlated with liver injury, whereas Faecalibacterium showed a negative correlation. Specific microbial markers for SBP were identified. Functional profiling revealed altered microbial functionalities in LC and SBP. Elevated fecal IgA levels, coupled with microbiota alterations, correlate with liver injury severity in LC patients. Modulating gut microbiota could be a promising strategy for managing liver-related conditions. Further research is needed to understand underlying mechanisms and translate findings into clinical practice, potentially improving patient outcomes.

Human gut microbiota interactions shape the long-term growth dynamics and evolutionary adaptations of Clostridioides difficile.

Clostridioides difficile can transiently or persistently colonize the human gut, posing a risk factor for infections. This colonization is influenced by complex molecular and ecological interactions with human gut microbiota. By investigating C. difficile dynamics in human gut communities over hundreds of generations, we show patterns of stable coexistence, instability, or competitive exclusion. Lowering carbohydrate concentration shifted a community containing C. difficile and the prevalent human gut symbiont Phocaeicola vulgatus from competitive exclusion to coexistence, facilitated by increased cross-feeding. In this environment, C. difficile adapted via single-point mutations in key metabolic genes, altering its metabolic niche from proline to glucose utilization. These metabolic changes substantially impacted inter-species interactions and reduced disease severity in the mammalian gut. In sum, human gut microbiota interactions are crucial in shaping the long-term growth dynamics and evolutionary adaptations of C. difficile, offering key insights for developing anti-C. difficile strategies.

Scoring Microbiota Function: A Proposal to Use Features of Evolutionary, Symbiotic Innovation to Recognize a “Healthy” Human Gut Microbiota

Scoring Microbiota Function: A Proposal to Use Features of Evolutionary, Symbiotic Innovation to Recognize a “Healthy” Human Gut Microbiota

Q2-metnet: QIIME2 package to analyze 16S rRNA data via high-quality metabolic reconstructions of the human gut microbiota.

16S rRNA gene sequencing is the most frequent approach for the characterization of the human gut microbiota. Despite different efforts in the literature, the inference of functional and metabolic interpretations from 16S rRNA gene sequencing data is still a challenging task. High-quality metabolic reconstructions of the human gut microbiota, such as AGORA and AGREDA, constitute a curated resource to improve functional inference from 16S rRNA data, but they are not typically integrated into standard bioinformatics tools. Here, we present q2-metnet, a QIIME2 plugin that enables the contextualization of 16S rRNA gene sequencing data into AGORA and AGREDA. In particular, based on relative abundances of taxa, q2-metnet determines normalized activity scores for the reactions and subsystems involved in the selected metabolic reconstruction. Using these scores, q2-metnet allows the user to conduct differential activity analysis for reactions and subsystems, as well as exploratory analysis using PCA and hierarchical clustering. We apply q2-metnet to a dataset from our group that involves 16S rRNA data from stool samples from lean, allergic to cow's milk, obese and celiac children, and the Belgian Flemish Gut Flora Project cohort, which includes faecal 16S rRNA data from obese and normal-weight adult individuals. In the first case, q2-metnet outperforms existing algorithms in separating different clinical conditions based on predicted pathway abundances and subsystem scores. In the second case, q2-metnet complements competing approaches in predicting functional alterations in the gut microbiota of obese individuals. Overall, q2-metnet constitutes a powerful bioinformatics tool to provide metabolic context to 16S rRNA data from the human gut microbiota. Python code of q2-metnet is available in https://github.com/PlanesLab/q2-metnet and https://figshare.com/articles/dataset/q2-metnet_package/26180446. Supplementary data are available at Bioinformatics online.

Phylogenetically diverse bacterial species produce histamine

Histamine is an important biogenic amine known to impact a variety of patho-physiological processes ranging from allergic reactions, gut-mediated anti-inflammatory responses, and neurotransmitter activity. Histamine is found both endogenously within specialized host cells and exogenously in microbes. Exogenous histamine is produced through the decarboxylation of the amino acid L-histidine by bacterial-derived histidine decarboxylase enzymes. To investigate how widespread histamine production is across bacterial species, we examined 102,018 annotated genomes in the Integrated Microbial Genomes Database and identified 3,679 bacterial genomes (3.6 %) which possess the enzymatic machinery to generate histamine. These bacteria belonged to 10 phyla: Bacillota, Bacteroidota, Actinomycetota, Pseudomonadota, Lentisphaerota, Fusobacteriota, Armatimonadota, Cyanobacteriota, Thermodesulfobacteriota, and Verrucomicrobiota. The majority of the identified bacteria were terrestrial or aquatic in origin, although several bacteria originated in the human gut microbiota. We used liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based targeted metabolomics to confirm our genome discoveries correlated with L-histidine-to-histamine conversion in a chemically defined bacterial growth medium by a cohort of select environmental and human gut bacteria. We found that environmental microbes Vibrio harveyi, Pseudomonas fluorescens and Streptomyces griseus generated considerable levels of histamine (788 – 8,730 ng/mL). Interestingly, we found higher concentrations of histamine produced by gut-associated Fusobacterium varium, Clostridium perfringens, Limosilactobacillus reuteri and Morganella morganii (8,510––82,400 ng/mL). This work expands our knowledge of histamine production by diverse microbes.

Gut microbiome diversity within Clostridia is negatively associated with human obesity.

The gut microbiota is diverse across various taxonomic levels. At the intra-species level, it comprises multiple strains, some of which may be host-specific. However, our understanding of fine-grained diversity has been hindered by the use of the conserved 16S rRNA gene. While shotgun metagenomics offers higher resolution, it remains costly, may fail to identify specific microbes in complex samples, and requires extensive computational resources and expertise. To address this, we employed a simple and cost-effective analysis of alternative genetic markers to explore diversity within Clostridia, a crucial group within the human gut microbiota whose diversity may be underestimated. We found high intra-species diversity for certain groups and associations with obesity. Notably, we identified Vescimonas, an understudied group. Making use of metagenomic data, we inferred functionality, uncovering potential beneficial roles in dietary fiber and carbohydrate degradation, as well as in short-chain fatty acid production.

Unveiling metabolic pathways of selected plant-derived glycans by Bifidobacterium pseudocatenulatum.

Bifidobacteria are commonly encountered members of the human gut microbiota that possess the enzymatic machinery necessary for the metabolism of certain plant-derived, complex carbohydrates. In the current study we describe differential growth profiles elicited by a panel of 21 newly isolated Bifidobacterium pseudocatenulatum strains on various plant-derived glycans. Using a combination of gene-trait matching and comparative genome analysis, we identified two distinct xylanases responsible for the degradation of xylan. Furthermore, three distinct extracellular α-amylases were shown to be involved in starch degradation by certain strains of B. pseudocatenulatum. Biochemical characterization showed that all three α-amylases can cleave the related substrates amylose, amylopectin, maltodextrin, glycogen and starch. The genes encoding these enzymes are variably found in the species B. pseudocatenulatum, therefore constituting a strain-specific adaptation to the gut environment as these glycans constitute common plant-derived carbohydrates present in the human diet. Overall, our study provides insights into the metabolism of these common dietary carbohydrates by a human-derived bifidobacterial species.