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...
| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | en_US |
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Public Library of Science
2012
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| Online Access: | http://hdl.handle.net/1721.1/72411 |
| _version_ | 1826201501261889536 |
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| author | Abubucker, Sahar Segata, Nicola Goll, Johannes Schubert, Alyxandria M. Izard, Jacques Cantarel, Brandi L. Rodriguez-Mueller, Beltran Zucker, Jeremy Thiagarajan, Mathangi Henrissat, Bernard White, Owen Kelley, Scott T. Methe, Barbara Schloss, Patrick D. Gevers, Dirk Mitreva, Makedonka Huttenhower, Curtis |
| author2 | Zucker, Jeremy |
| author_facet | Zucker, Jeremy Abubucker, Sahar Segata, Nicola Goll, Johannes Schubert, Alyxandria M. Izard, Jacques Cantarel, Brandi L. Rodriguez-Mueller, Beltran Zucker, Jeremy Thiagarajan, Mathangi Henrissat, Bernard White, Owen Kelley, Scott T. Methe, Barbara Schloss, Patrick D. Gevers, Dirk Mitreva, Makedonka Huttenhower, Curtis |
| author_sort | Abubucker, Sahar |
| collection | MIT |
| 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. |
| first_indexed | 2024-09-23T11:52:26Z |
| format | Article |
| id | mit-1721.1/72411 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T11:52:26Z |
| publishDate | 2012 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | mit-1721.1/724112022-09-27T22:31:58Z Metabolic Reconstruction for Metagenomic Data and Its Application to the Human Microbiome Abubucker, Sahar Segata, Nicola Goll, Johannes Schubert, Alyxandria M. Izard, Jacques Cantarel, Brandi L. Rodriguez-Mueller, Beltran Zucker, Jeremy Thiagarajan, Mathangi Henrissat, Bernard White, Owen Kelley, Scott T. Methe, Barbara Schloss, Patrick D. Gevers, Dirk Mitreva, Makedonka Huttenhower, Curtis Zucker, Jeremy Zucker, Jeremy 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. National Institutes of Health (U.S.) (U54HG004968) 2012-08-29T14:16:40Z 2012-08-29T14:16:40Z 2012-06 2011-08 Article http://purl.org/eprint/type/JournalArticle 1553-734X 1553-7358 http://hdl.handle.net/1721.1/72411 Abubucker, Sahar et al. “Metabolic Reconstruction for Metagenomic Data and Its Application to the Human Microbiome.” Ed. Jonathan A. Eisen. PLoS Computational Biology 8.6 (2012): e1002358. en_US http://dx.doi.org/10.1371/journal.pcbi.1002358 PLoS Computational Biology Creative Commons Attribution http://creativecommons.org/licenses/by/2.5/ application/pdf Public Library of Science PLoS |
| spellingShingle | Abubucker, Sahar Segata, Nicola Goll, Johannes Schubert, Alyxandria M. Izard, Jacques Cantarel, Brandi L. Rodriguez-Mueller, Beltran Zucker, Jeremy Thiagarajan, Mathangi Henrissat, Bernard White, Owen Kelley, Scott T. Methe, Barbara Schloss, Patrick D. Gevers, Dirk Mitreva, Makedonka Huttenhower, Curtis Metabolic Reconstruction for Metagenomic Data and Its Application to the Human Microbiome |
| title | 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_short | 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 |
| url | http://hdl.handle.net/1721.1/72411 |
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