Analysis of Human Gut Microbiome: Taxonomy and Metabolic Functions in Thai Adults.
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ABSTRACT:
SUBMITTER: Raethong N
PROVIDER: S-EPMC7996147 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Protein catabolism by intestinal bacteria is infamous for releasing many harmful compounds, negatively affecting the health status, both locally and systemically. In a previous study, we enriched in protein degraders the fecal microbiota of five subjects, utilizing a medium containing protein and peptides as sole fermentable substrates and we monitored their evolution by 16S rRNA gene profiling. In the present study, we fused the microbiome data and the data obtained by the analysis of the volatile organic compounds (VOCs) in the headspace of the cultures. Then, we utilized ANOVA simultaneous component analysis (ASCA) to establish a relationship between metabolites and bacteria. In particular, ASCA allowed to separately assess the effect of subject, time, inoculum concentration, and their binary interactions on both microbiome and volatilome data. All the ASCA submodels pointed out a consistent association between indole and Escherichia-Shigella, and the relationship of butyric, 3-methyl butanoic, and benzenepropanoic acids with some bacterial taxa that were major determinants of cultures at 6 h, such as Lachnoclostridiaceae (Lachnoclostridium), Clostridiaceae (Clostridium sensu stricto), and Sutterellaceae (Sutterella and Parasutterella). The metagenome reconstruction with PICRUSt2 and its functional annotation indicated that enrichment in a protein-based medium affected the richness and diversity of functional profiles, in the face of a decrease of richness and evenness of the microbial community. Linear discriminant analysis (LDA) effect size indicated a positive differential abundance (p < 0.05) for the modules of amino acid catabolism that may be at the basis of the changes of VOC profile. In particular, predicted genes encoding functions belonging to the superpathways of ornithine, arginine, and putrescine transformation to GABA and eventually to succinyl-CoA, of methionine degradation, and various routes of breakdown of aromatic compounds yielding succinyl-CoA or acetyl-CoA became significantly more abundant in the metagenome of the bacterial community.
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Project description:Little is known regarding the pool of mobile genetic elements associated with the human gut microbiome. In this study we employed the culture independent TRACA system to isolate novel plasmids from the human gut microbiota, and a comparative metagenomic analysis to investigate the distribution and relative abundance of functions encoded by these plasmids in the human gut microbiome.Novel plasmids were acquired from the human gut microbiome, and homologous nucleotide sequences with high identity (>90%) to two plasmids (pTRACA10 and pTRACA22) were identified in the multiple human gut microbiomes analysed here. However, no homologous nucleotide sequences to these plasmids were identified in the murine gut or environmental metagenomes. Functions encoded by the plasmids pTRACA10 and pTRACA22 were found to be more prevalent in the human gut microbiome when compared to microbial communities from other environments. Among the most prevalent functions identified was a putative RelBE toxin-antitoxin (TA) addiction module, and subsequent analysis revealed that this was most closely related to putative TA modules from gut associated bacteria belonging to the Firmicutes. A broad phylogenetic distribution of RelE toxin genes was observed in gut associated bacterial species (Firmicutes, Bacteroidetes, Actinobacteria and Proteobacteria), but no RelE homologues were identified in gut associated archaeal species. We also provide indirect evidence for the horizontal transfer of these genes between bacterial species belonging to disparate phylogenetic divisions, namely Gram negative Proteobacteria and Gram positive species from the Firmicutes division.The application of a culture independent system to capture novel plasmids from the human gut mobile metagenome, coupled with subsequent comparative metagenomic analysis, highlighted the unexpected prevalence of plasmid encoded functions in the gut microbial ecosystem. In particular the increased relative abundance and broad phylogenetic distribution was identified for a putative RelBE toxin/antitoxin addiction module, a putative phosphohydrolase/phosphoesterase, and an ORF of unknown function. Our analysis also indicates that some plasmids or plasmid families are present in the gut microbiomes of geographically isolated human hosts with a broad global distribution (America, Japan and Europe), and are potentially unique to the human gut microbiome. Further investigation of the plasmid population associated with the human gut is likely to provide important insights into the development, functioning and evolution of the human gut microbiota.
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Project description:Investigating metabolic functional capability of a human gut microbiome enables the quantification of microbiome changes, which can cause a phenotypic change of host physiology and disease. One possible way to estimate the functional capability of a microbial community is through inferring metagenomic content from 16S rRNA gene sequences. Genome-scale models (GEMs) can be used as scaffold for functional estimation analysis at a systematic level, however up to date, there is no integrative toolbox based on GEMs for uncovering metabolic functions. Here, we developed the MetGEMs (metagenome-scale models) toolbox, an open-source application for inferring metabolic functions from 16S rRNA gene sequences to facilitate the study of the human gut microbiome by the wider scientific community. The developed toolbox was validated using shotgun metagenomic data and shown to be superior in predicting functional composition in human clinical samples compared to existing state-of-the-art tools. Therefore, the MetGEMs toolbox was subsequently applied for annotating putative enzyme functions and metabolic routes related in human disease using atopic dermatitis as a case study.
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Project description:A multitude of factors contribute to complex diseases and can be measured with 'omics' methods. Databases facilitate data interpretation for underlying mechanisms. Here, we describe the Virtual Metabolic Human (VMH, www.vmh.life) database encapsulating current knowledge of human metabolism within five interlinked resources 'Human metabolism', 'Gut microbiome', 'Disease', 'Nutrition', and 'ReconMaps'. The VMH captures 5180 unique metabolites, 17 730 unique reactions, 3695 human genes, 255 Mendelian diseases, 818 microbes, 632 685 microbial genes and 8790 food items. The VMH's unique features are (i) the hosting of the metabolic reconstructions of human and gut microbes amenable for metabolic modeling; (ii) seven human metabolic maps for data visualization; (iii) a nutrition designer; (iv) a user-friendly webpage and application-programming interface to access its content; (v) user feedback option for community engagement and (vi) the connection of its entities to 57 other web resources. The VMH represents a novel, interdisciplinary database for data interpretation and hypothesis generation to the biomedical community.
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Project description:Bacterial microcompartments are self-assembling subcellular structures surrounded by a semipermeable protein shell and found only in bacteria, but not archaea or eukaryotes. The general functions of the bacterial microcompartments are to concentrate enzymes, metabolites, and cofactors for multistep pathways; maintain the cofactor ratio; protect the cell from toxic metabolic intermediates; and protect the encapsulated pathway from unwanted side reactions. The bacterial microcompartments were suggested to play a significant role in organisms of the human gut microbiome, especially for various pathogens. Here, we used a comparative genomics approach to analyze the bacterial microcompartments in 646 individual genomes of organisms commonly found in the human gut microbiome. The bacterial microcompartments were found in 150 (23.2%) analyzed genomes. These microcompartments include previously known ones for the utilization of ethanolamine, 1,2-propanediol, choline, and fucose/rhamnose. Moreover, we reconstructed two novel pathways associated with the bacterial microcompartments. These pathways are catabolic pathways for the utilization of 1-amino-2-propanol/1-amino-2-propanone and xanthine. Remarkably, the xanthine utilization pathway does not demonstrate similarity to previously known microcompartment-associated pathways. Thus, we describe a novel type of bacterial microcompartment.
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Project description:BackgroundAberrations in the preterm microbiome following antibiotic therapy have been reported in previous studies. The objective of this study was to probe potential underlying mechanisms between this observation and susceptibility to adverse prematurity-related outcomes.ResultsMetagenomic shotgun sequencing was performed on 133 stool and 253 skin samples collected at 1 and 3 weeks of age from 68 infants born at <36 weeks postmenstrual age and birth weight <2000 g. After accounting for gestational age and maternal antibiotics, the distribution of organisms in all samples and the corresponding metabolic pathway abundance were compared between infants exposed to postnatal antibiotics and antibiotics-naïve infants. In antibiotic-naïve infants, gestational and postnatal age imparted similar trajectories on maturation of the microbial community and associated metabolic functional capacity, with postnatal age exerting greater contribution. Antibiotic exposure was associated with reversal in maturation trajectory from the first week to the third week of age (p< 0.001). Butyrate-producing genera, including Clostridium and Blautia, were significantly more abundant in antibiotic-naïve neonates at 3 weeks postnatal age. Correspondingly, metabolic pathways required for short-chain fatty acid synthesis were significantly increased in antibiotic-naïve infants, but not in antibiotic-exposed neonates, at 3 weeks after birth.ConclusionsEarly brief antibiotic exposure markedly disrupts developmental trajectory of the neonatal microbiome and its corresponding functional capacity. Our findings may provide a mechanistic explanation for the known associations between antibiotic use and adverse outcomes in preterm infants. Video Abstract.
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Project description:BackgroundThere is growing recognition of the significance of the gut microbiome to human health, and the association between a perturbed gut microbiome with human diseases has been established. Previous studies also show the role of environmental toxicants in perturbing the gut microbiome and its metabolic functions. The wide agricultural use of diazinon, an organophosphate insecticide, has raised serious environmental health concerns since it is a potent neurotoxicant. With studies demonstrating the presence of a microbiome-gut-brain axis, it is possible that gut microbiome perturbation may also contribute to diazinon toxicity.ObjectivesWe investigated the impact of diazinon exposure on the gut microbiome composition and its metabolic functions in C57BL/6 mice.MethodsWe used a combination of 16S rRNA gene sequencing, metagenomics sequencing, and mass spectrometry-based metabolomics profiling in a mouse model to examine the functional impact of diazinon on the gut microbiome.Results16S rRNA gene sequencing revealed that diazinon exposure significantly perturbed the gut microbiome, and metagenomic sequencing found that diazinon exposure altered the functional metagenome. Moreover, metabolomics profiling revealed an altered metabolic profile arising from exposure. Of particular significance, these changes were more pronounced for male mice than for female mice.ConclusionsDiazinon exposure perturbed the gut microbiome community structure, functional metagenome, and associated metabolic profiles in a sex-specific manner. These findings may provide novel insights regarding perturbations of the gut microbiome and its functions as a potential new mechanism contributing to diazinon neurotoxicity and, in particular, its sex-selective effects. Citation: Gao B, Bian X, Mahbub R, Lu K. 2017. Sex-specific effects of organophosphate diazinon on the gut microbiome and its metabolic functions. Environ Health Perspect 125:198-206; http://dx.doi.org/10.1289/EHP202.
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Project description:BackgroundThe correlation between the physical performance of athletes and their gut microbiota has become of growing interest in the past years, since new evidences have emerged regarding the importance of the gut microbiota as a main driver of the health status of athletes. In addition, it has been postulated that the metabolic activity of the microbial population harbored by the large intestine of athletes might influence their physical performances. Here, we analyzed 418 publicly available shotgun metagenomics datasets obtained from fecal samples of healthy athletes and healthy sedentary adults.ResultsThis study evidenced how agonistic physical activity and related lifestyle can be associated with the modulation of the gut microbiota composition, inducing modifications of the taxonomic profiles with an enhancement of gut microbes able to produce short-fatty acid (SCFAs). In addition, our analyses revealed a correlation between specific bacterial species and high impact biological synthases (HIBSs) responsible for the generation of a range of microbially driven compounds such vitamin B12, amino acidic derivatives, and other molecules linked to cardiovascular and age-related health-risk reduction.ConclusionsNotably, our findings show how subsist an association between competitive athletes, and modulation of the gut microbiota, and how this modulation is reflected in the potential production of microbial metabolites that can lead to beneficial effects on human physical performance and health conditions. Video Abstract.
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Project description:BackgroundParkinson's disease (PD) is a systemic disease clinically defined by the degeneration of dopaminergic neurons in the brain. While alterations in the gut microbiome composition have been reported in PD, their functional consequences remain unclear. Herein, we addressed this question by an analysis of stool samples from the Luxembourg Parkinson's Study (n = 147 typical PD cases, n = 162 controls).ResultsAll individuals underwent detailed clinical assessment, including neurological examinations and neuropsychological tests followed by self-reporting questionnaires. Stool samples from these individuals were first analysed by 16S rRNA gene sequencing. Second, we predicted the potential secretion for 129 microbial metabolites through personalised metabolic modelling using the microbiome data and genome-scale metabolic reconstructions of human gut microbes. Our key results include the following. Eight genera and seven species changed significantly in their relative abundances between PD patients and healthy controls. PD-associated microbial patterns statistically depended on sex, age, BMI, and constipation. Particularly, the relative abundances of Bilophila and Paraprevotella were significantly associated with the Hoehn and Yahr staging after controlling for the disease duration. Furthermore, personalised metabolic modelling of the gut microbiomes revealed PD-associated metabolic patterns in the predicted secretion potential of nine microbial metabolites in PD, including increased methionine and cysteinylglycine. The predicted microbial pantothenic acid production potential was linked to the presence of specific non-motor symptoms.ConclusionOur results suggest that PD-associated alterations of the gut microbiome can translate into substantial functional differences affecting host metabolism and disease phenotype.
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Project description:The recent high-throughput sequencing has enabled the composition of Escherichia coli strains in the human microbial community to be profiled en masse. However, there are two challenges to address: (1) exploring the genetic differences between E. coli strains in human gut and (2) dynamic responses of E. coli to diverse stress conditions. As a result, we investigated the E. coli strains in human gut microbiome using deep sequencing data and reconstructed genome-wide metabolic networks for the three most common E. coli strains, including E. coli HS, UTI89, and CFT073. The metabolic models show obvious strain-specific characteristics, both in network contents and in behaviors. We predicted optimal biomass production for three models on four different carbon sources (acetate, ethanol, glucose, and succinate) and found that these stress-associated genes were involved in host-microbial interactions and increased in human obesity. Besides, it shows that the growth rates are similar among the models, but the flux distributions are different, even in E. coli core reactions. The correlations between human diabetes-associated metabolic reactions in the E. coli models were also predicted. The study provides a systems perspective on E. coli strains in human gut microbiome and will be helpful in integrating diverse data sources in the following study.
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