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Strain-level dissection of the contribution of the gut microbiome to human metabolic disease
The gut microbiota has been linked with metabolic diseases in humans, but demonstration of causality remains a challenge. The gut microbiota, as a complex microbial ecosystem, consists of hundreds of individual bacterial species, each of which contains many strains with high genetic diversity. Recen...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4839137/ https://www.ncbi.nlm.nih.gov/pubmed/27098841 http://dx.doi.org/10.1186/s13073-016-0304-1 |
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author | Zhang, Chenhong Zhao, Liping |
author_facet | Zhang, Chenhong Zhao, Liping |
author_sort | Zhang, Chenhong |
collection | PubMed |
description | The gut microbiota has been linked with metabolic diseases in humans, but demonstration of causality remains a challenge. The gut microbiota, as a complex microbial ecosystem, consists of hundreds of individual bacterial species, each of which contains many strains with high genetic diversity. Recent advances in genomic and metabolomic technologies are facilitating strain-level dissection of the contribution of the gut microbiome to metabolic diseases. Interventional studies and correlation analysis between variations in the microbiome and metabolome, captured by longitudinal sampling, can lead to the identification of specific bacterial strains that may contribute to human metabolic diseases via the production of bioactive metabolites. For example, high-quality draft genomes of prevalent gut bacterial strains can be assembled directly from metagenomic datasets using a canopy-based algorithm. Specific metabolites associated with a disease phenotype can be identified by nuclear magnetic resonance-based metabolomics of urine and other samples. Such multi-omics approaches can be employed to identify specific gut bacterial genomes that are not only correlated with detected metabolites but also encode the genes required for producing the precursors of those metabolites in the gut. Here, we argue that if a causative role can be demonstrated in follow-up mechanistic studies—for example, using gnotobiotic models—such functional strains have the potential to become biomarkers for diagnostics and targets for therapeutics. |
format | Online Article Text |
id | pubmed-4839137 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-48391372016-04-22 Strain-level dissection of the contribution of the gut microbiome to human metabolic disease Zhang, Chenhong Zhao, Liping Genome Med Opinion The gut microbiota has been linked with metabolic diseases in humans, but demonstration of causality remains a challenge. The gut microbiota, as a complex microbial ecosystem, consists of hundreds of individual bacterial species, each of which contains many strains with high genetic diversity. Recent advances in genomic and metabolomic technologies are facilitating strain-level dissection of the contribution of the gut microbiome to metabolic diseases. Interventional studies and correlation analysis between variations in the microbiome and metabolome, captured by longitudinal sampling, can lead to the identification of specific bacterial strains that may contribute to human metabolic diseases via the production of bioactive metabolites. For example, high-quality draft genomes of prevalent gut bacterial strains can be assembled directly from metagenomic datasets using a canopy-based algorithm. Specific metabolites associated with a disease phenotype can be identified by nuclear magnetic resonance-based metabolomics of urine and other samples. Such multi-omics approaches can be employed to identify specific gut bacterial genomes that are not only correlated with detected metabolites but also encode the genes required for producing the precursors of those metabolites in the gut. Here, we argue that if a causative role can be demonstrated in follow-up mechanistic studies—for example, using gnotobiotic models—such functional strains have the potential to become biomarkers for diagnostics and targets for therapeutics. BioMed Central 2016-04-20 /pmc/articles/PMC4839137/ /pubmed/27098841 http://dx.doi.org/10.1186/s13073-016-0304-1 Text en © Zhang and Zhao. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Opinion Zhang, Chenhong Zhao, Liping Strain-level dissection of the contribution of the gut microbiome to human metabolic disease |
title | Strain-level dissection of the contribution of the gut microbiome to human metabolic disease |
title_full | Strain-level dissection of the contribution of the gut microbiome to human metabolic disease |
title_fullStr | Strain-level dissection of the contribution of the gut microbiome to human metabolic disease |
title_full_unstemmed | Strain-level dissection of the contribution of the gut microbiome to human metabolic disease |
title_short | Strain-level dissection of the contribution of the gut microbiome to human metabolic disease |
title_sort | strain-level dissection of the contribution of the gut microbiome to human metabolic disease |
topic | Opinion |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4839137/ https://www.ncbi.nlm.nih.gov/pubmed/27098841 http://dx.doi.org/10.1186/s13073-016-0304-1 |
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