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Open AccessJournal ArticleDOI

Compositional and functional differences of the mucosal microbiota along the intestine of healthy individuals

TLDR
This work used shotgun metagenomics of mucosal biopsies to explore the microbial communities’ compositions of terminal ileum and large intestine in 5 healthy individuals, and details which species are involved with the tryptophan/indole pathway and the antimicrobial resistance biogeography along the intestine.
Abstract
Gut mucosal microbes evolved closest to the host, developing specialized local communities. There is, however, insufficient knowledge of these communities as most studies have employed sequencing technologies to investigate faecal microbiota only. This work used shotgun metagenomics of mucosal biopsies to explore the microbial communities' compositions of terminal ileum and large intestine in 5 healthy individuals. Functional annotations and genome-scale metabolic modelling of selected species were then employed to identify local functional enrichments. While faecal metagenomics provided a good approximation of the average gut mucosal microbiome composition, mucosal biopsies allowed detecting the subtle variations of local microbial communities. Given their significant enrichment in the mucosal microbiota, we highlight the roles of Bacteroides species and describe the antimicrobial resistance biogeography along the intestine. We also detail which species, at which locations, are involved with the tryptophan/indole pathway, whose malfunctioning has been linked to pathologies including inflammatory bowel disease. Our study thus provides invaluable resources for investigating mechanisms connecting gut microbiota and host pathophysiology.

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Artificial intelligence to deep learning: machine intelligence approach for drug discovery.

TL;DR: In this article, Artificial Neural Networks and deep learning algorithms have been implemented in several drug discovery processes such as peptide synthesis, structure-based virtual screening, ligand-based screening, toxicity prediction, drug monitoring and release, pharmacophore modeling, quantitative structure-activity relationship, drug repositioning, polypharmacology, and physiochemical activity.
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Predicting TBM penetration rate in hard rock condition: A comparative study among six XGB-based metaheuristic techniques

TL;DR: This research aims to develop six hybrid models of extreme gradient boosting (XGB) which are optimized by gray wolf optimization (GWO), particle swarm optimization (PSO), social spider optimization (SSO), sine cosine algorithm (SCA), multi verse optimization (MVO) and moth flame optimized (MFO) for estimation of the TBM penetration rate (PR).
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3D bioprinting of cells, tissues and organs.

TL;DR: This Collection amalgamates research aimed at 3D bioprinting organs for fulfilling demands of organ shortage, cell patterning for better tissue fabrication, and building better disease models.
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Estimation of the TBM advance rate under hard rock conditions using XGBoost and Bayesian optimization

TL;DR: Improved the accuracy of prediction models by employing a hybrid model of extreme gradient boosting (XGBoost) with Bayesian optimization (BO) to model the TBM AR and demonstrated that machine parameters have the greatest impact as compared to rock mass and material properties.
References
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Journal ArticleDOI

KEGG: Kyoto Encyclopedia of Genes and Genomes

TL;DR: The Kyoto Encyclopedia of Genes and Genomes (KEGG) as discussed by the authors is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules.
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Occurrence of the potent mutagens 2- nitrobenzanthrone and 3-nitrobenzanthrone in fine airborne particles

TL;DR: In the present study, 2-NBA, 3-NBA and selected PAHs and Nitro-PAHs were determined in fine particle samples collected in a bus station and an outdoor site, showing low cancer risk incidence and incremental lifetime cancer risk (ILCR) calculated for both places.
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KEGG as a reference resource for gene and protein annotation

TL;DR: The KEGG GENES database now includes viruses, plasmids, and the addendum category for functionally characterized proteins that are not represented in complete genomes, and new automatic annotation servers, BlastKOalA and GhostKOALA, are made available utilizing the non-redundant pangenome data set generated from theGENES database.
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Richness of human gut microbiome correlates with metabolic markers

TL;DR: The authors' classifications based on variation in the gut microbiome identify subsets of individuals in the general white adult population who may be at increased risk of progressing to adiposity-associated co-morbidities.
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Gut microbiome influences efficacy of PD-1–based immunotherapy against epithelial tumors

Bertrand Routy, +76 more
- 05 Jan 2018 - 
TL;DR: It is found that primary resistance to ICIs can be attributed to abnormal gut microbiome composition, and Antibiotics inhibited the clinical benefit of ICIs in patients with advanced cancer.
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