Metabolic reconstruction for metagenomic data and its application to the human microbiome.

Microbial communities carry out the majority of the biochemical activity on the planet, and they play integral roles in processes including metabolism and immune homeostasis in the human microbiome. Shotgun sequencing of such communities' metagenomes provides information complementary to organi...

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Autores principales:	Sahar Abubucker, Nicola Segata, Johannes Goll, Alyxandria M Schubert, Jacques Izard, Brandi L Cantarel, Beltran Rodriguez-Mueller, Jeremy Zucker, Mathangi Thiagarajan, Bernard Henrissat, Owen White, Scott T Kelley, Barbara Methé, Patrick D Schloss, Dirk Gevers, Makedonka Mitreva, Curtis Huttenhower
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/c8bebf0300734591876c8dc5a3534b24
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spelling	oai:doaj.org-article:c8bebf0300734591876c8dc5a3534b242021-11-18T05:51:16ZMetabolic reconstruction for metagenomic data and its application to the human microbiome.1553-734X1553-735810.1371/journal.pcbi.1002358https://doaj.org/article/c8bebf0300734591876c8dc5a3534b242012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22719234/pdf/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Microbial communities carry out the majority of the biochemical activity on the planet, and they play integral roles in processes including metabolism and immune homeostasis in the human microbiome. Shotgun sequencing of such communities' metagenomes provides information complementary to organismal abundances from taxonomic markers, but the resulting data typically comprise short reads from hundreds of different organisms and are at best challenging to assemble comparably to single-organism genomes. Here, we describe an alternative approach to infer the functional and metabolic potential of a microbial community metagenome. We determined the gene families and pathways present or absent within a community, as well as their relative abundances, directly from short sequence reads. We validated this methodology using a collection of synthetic metagenomes, recovering the presence and abundance both of large pathways and of small functional modules with high accuracy. We subsequently applied this method, HUMAnN, to the microbial communities of 649 metagenomes drawn from seven primary body sites on 102 individuals as part of the Human Microbiome Project (HMP). This provided a means to compare functional diversity and organismal ecology in the human microbiome, and we determined a core of 24 ubiquitously present modules. Core pathways were often implemented by different enzyme families within different body sites, and 168 functional modules and 196 metabolic pathways varied in metagenomic abundance specifically to one or more niches within the microbiome. These included glycosaminoglycan degradation in the gut, as well as phosphate and amino acid transport linked to host phenotype (vaginal pH) in the posterior fornix. An implementation of our methodology is available at http://huttenhower.sph.harvard.edu/humann. This provides a means to accurately and efficiently characterize microbial metabolic pathways and functional modules directly from high-throughput sequencing reads, enabling the determination of community roles in the HMP cohort and in future metagenomic studies.Sahar AbubuckerNicola SegataJohannes GollAlyxandria M SchubertJacques IzardBrandi L CantarelBeltran Rodriguez-MuellerJeremy ZuckerMathangi ThiagarajanBernard HenrissatOwen WhiteScott T KelleyBarbara MethéPatrick D SchlossDirk GeversMakedonka MitrevaCurtis HuttenhowerPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 8, Iss 6, p e1002358 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Sahar Abubucker Nicola Segata Johannes Goll Alyxandria M Schubert Jacques Izard Brandi L Cantarel Beltran Rodriguez-Mueller Jeremy Zucker Mathangi Thiagarajan Bernard Henrissat Owen White Scott T Kelley Barbara Methé Patrick D Schloss Dirk Gevers Makedonka Mitreva Curtis Huttenhower Metabolic reconstruction for metagenomic data and its application to the human microbiome.
description	Microbial communities carry out the majority of the biochemical activity on the planet, and they play integral roles in processes including metabolism and immune homeostasis in the human microbiome. Shotgun sequencing of such communities' metagenomes provides information complementary to organismal abundances from taxonomic markers, but the resulting data typically comprise short reads from hundreds of different organisms and are at best challenging to assemble comparably to single-organism genomes. Here, we describe an alternative approach to infer the functional and metabolic potential of a microbial community metagenome. We determined the gene families and pathways present or absent within a community, as well as their relative abundances, directly from short sequence reads. We validated this methodology using a collection of synthetic metagenomes, recovering the presence and abundance both of large pathways and of small functional modules with high accuracy. We subsequently applied this method, HUMAnN, to the microbial communities of 649 metagenomes drawn from seven primary body sites on 102 individuals as part of the Human Microbiome Project (HMP). This provided a means to compare functional diversity and organismal ecology in the human microbiome, and we determined a core of 24 ubiquitously present modules. Core pathways were often implemented by different enzyme families within different body sites, and 168 functional modules and 196 metabolic pathways varied in metagenomic abundance specifically to one or more niches within the microbiome. These included glycosaminoglycan degradation in the gut, as well as phosphate and amino acid transport linked to host phenotype (vaginal pH) in the posterior fornix. An implementation of our methodology is available at http://huttenhower.sph.harvard.edu/humann. This provides a means to accurately and efficiently characterize microbial metabolic pathways and functional modules directly from high-throughput sequencing reads, enabling the determination of community roles in the HMP cohort and in future metagenomic studies.
format	article
author	Sahar Abubucker Nicola Segata Johannes Goll Alyxandria M Schubert Jacques Izard Brandi L Cantarel Beltran Rodriguez-Mueller Jeremy Zucker Mathangi Thiagarajan Bernard Henrissat Owen White Scott T Kelley Barbara Methé Patrick D Schloss Dirk Gevers Makedonka Mitreva Curtis Huttenhower
author_facet	Sahar Abubucker Nicola Segata Johannes Goll Alyxandria M Schubert Jacques Izard Brandi L Cantarel Beltran Rodriguez-Mueller Jeremy Zucker Mathangi Thiagarajan Bernard Henrissat Owen White Scott T Kelley Barbara Methé Patrick D Schloss Dirk Gevers Makedonka Mitreva Curtis Huttenhower
author_sort	Sahar Abubucker
title	Metabolic reconstruction for metagenomic data and its application to the human microbiome.
title_short	Metabolic reconstruction for metagenomic data and its application to the human microbiome.
title_full	Metabolic reconstruction for metagenomic data and its application to the human microbiome.
title_fullStr	Metabolic reconstruction for metagenomic data and its application to the human microbiome.
title_full_unstemmed	Metabolic reconstruction for metagenomic data and its application to the human microbiome.
title_sort	metabolic reconstruction for metagenomic data and its application to the human microbiome.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/c8bebf0300734591876c8dc5a3534b24
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Metabolic reconstruction for metagenomic data and its application to the human microbiome.

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