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Guild-based analysis for understanding gut microbiome in human health and diseases

To demonstrate the causative role of gut microbiome in human health and diseases, we first need to identify, via next-generation sequencing, potentially important functional members associated with specific health outcomes and disease phenotypes. However, due to the strain-level genetic complexity o...

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Autores principales: Wu, Guojun, Zhao, Naisi, Zhang, Chenhong, Lam, Yan Y., Zhao, Liping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7874449/
https://www.ncbi.nlm.nih.gov/pubmed/33563315
http://dx.doi.org/10.1186/s13073-021-00840-y
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author Wu, Guojun
Zhao, Naisi
Zhang, Chenhong
Lam, Yan Y.
Zhao, Liping
author_facet Wu, Guojun
Zhao, Naisi
Zhang, Chenhong
Lam, Yan Y.
Zhao, Liping
author_sort Wu, Guojun
collection PubMed
description To demonstrate the causative role of gut microbiome in human health and diseases, we first need to identify, via next-generation sequencing, potentially important functional members associated with specific health outcomes and disease phenotypes. However, due to the strain-level genetic complexity of the gut microbiota, microbiome datasets are highly dimensional and highly sparse in nature, making it challenging to identify putative causative agents of a particular disease phenotype. Members of an ecosystem seldomly live independently from each other. Instead, they develop local interactions and form inter-member organizations to influence the ecosystem’s higher-level patterns and functions. In the ecological study of macro-organisms, members are defined as belonging to the same “guild” if they exploit the same class of resources in a similar way or work together as a coherent functional group. Translating the concept of “guild” to the study of gut microbiota, we redefine guild as a group of bacteria that show consistent co-abundant behavior and likely to work together to contribute to the same ecological function. In this opinion article, we discuss how to use guilds as the aggregation unit to reduce dimensionality and sparsity in microbiome-wide association studies for identifying candidate gut bacteria that may causatively contribute to human health and diseases. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13073-021-00840-y.
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spelling pubmed-78744492021-02-11 Guild-based analysis for understanding gut microbiome in human health and diseases Wu, Guojun Zhao, Naisi Zhang, Chenhong Lam, Yan Y. Zhao, Liping Genome Med Opinion To demonstrate the causative role of gut microbiome in human health and diseases, we first need to identify, via next-generation sequencing, potentially important functional members associated with specific health outcomes and disease phenotypes. However, due to the strain-level genetic complexity of the gut microbiota, microbiome datasets are highly dimensional and highly sparse in nature, making it challenging to identify putative causative agents of a particular disease phenotype. Members of an ecosystem seldomly live independently from each other. Instead, they develop local interactions and form inter-member organizations to influence the ecosystem’s higher-level patterns and functions. In the ecological study of macro-organisms, members are defined as belonging to the same “guild” if they exploit the same class of resources in a similar way or work together as a coherent functional group. Translating the concept of “guild” to the study of gut microbiota, we redefine guild as a group of bacteria that show consistent co-abundant behavior and likely to work together to contribute to the same ecological function. In this opinion article, we discuss how to use guilds as the aggregation unit to reduce dimensionality and sparsity in microbiome-wide association studies for identifying candidate gut bacteria that may causatively contribute to human health and diseases. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13073-021-00840-y. BioMed Central 2021-02-09 /pmc/articles/PMC7874449/ /pubmed/33563315 http://dx.doi.org/10.1186/s13073-021-00840-y Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.
spellingShingle Opinion
Wu, Guojun
Zhao, Naisi
Zhang, Chenhong
Lam, Yan Y.
Zhao, Liping
Guild-based analysis for understanding gut microbiome in human health and diseases
title Guild-based analysis for understanding gut microbiome in human health and diseases
title_full Guild-based analysis for understanding gut microbiome in human health and diseases
title_fullStr Guild-based analysis for understanding gut microbiome in human health and diseases
title_full_unstemmed Guild-based analysis for understanding gut microbiome in human health and diseases
title_short Guild-based analysis for understanding gut microbiome in human health and diseases
title_sort guild-based analysis for understanding gut microbiome in human health and diseases
topic Opinion
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7874449/
https://www.ncbi.nlm.nih.gov/pubmed/33563315
http://dx.doi.org/10.1186/s13073-021-00840-y
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