DRAM for distilling microbial metabolism to automate the curation of microbiome function

Microbial and viral communities transform the chemistry of Earth's ecosystems, yet the specific reactions catalyzed by these biological engines are hard to decode due to the absence of a scalable, metabolically resolved, annotation software. Here, we present DRAM (Distilled and Refined Annotati...

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Veröffentlicht in:Nucleic acids research Jg. 48; H. 16; S. 8883 - 8900
Hauptverfasser: Shaffer, Michael, Borton, Mikayla A, McGivern, Bridget B, Zayed, Ahmed A, La Rosa, Sabina Leanti, Solden, Lindsey M, Liu, Pengfei, Narrowe, Adrienne B, Rodríguez-Ramos, Josué, Bolduc, Benjamin, Gazitúa, M Consuelo, Daly, Rebecca A, Smith, Garrett J, Vik, Dean R, Pope, Phil B, Sullivan, Matthew B, Roux, Simon, Wrighton, Kelly C
Format: Journal Article
Sprache:Englisch
Veröffentlicht: England Oxford University Press 18.09.2020
Schlagworte:
Bacteria - classification
BASIC BIOLOGICAL SCIENCES
Computational Biology
Computational Methods
Gastrointestinal Microbiome
Genomics - methods
Humans
Metabolomics - methods
Metagenome
Molecular Sequence Annotation - methods
Software
Soil Microbiology
Viruses - classification
ISSN:0305-1048, 1362-4962, 1362-4962
Online-Zugang:Volltext
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Zusammenfassung:Microbial and viral communities transform the chemistry of Earth's ecosystems, yet the specific reactions catalyzed by these biological engines are hard to decode due to the absence of a scalable, metabolically resolved, annotation software. Here, we present DRAM (Distilled and Refined Annotation of Metabolism), a framework to translate the deluge of microbiome-based genomic information into a catalog of microbial traits. To demonstrate the applicability of DRAM across metabolically diverse genomes, we evaluated DRAM performance on a defined, in silico soil community and previously published human gut metagenomes. We show that DRAM accurately assigned microbial contributions to geochemical cycles and automated the partitioning of gut microbial carbohydrate metabolism at substrate levels. DRAM-v, the viral mode of DRAM, established rules to identify virally-encoded auxiliary metabolic genes (AMGs), resulting in the metabolic categorization of thousands of putative AMGs from soils and guts. Together DRAM and DRAM-v provide critical metabolic profiling capabilities that decipher mechanisms underpinning microbiome function.
Bibliographie:ObjectType-Article-1
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USDOE
SC0019746; SC0018022; AC02-05CH11231
National Institutes of Health (NIH)
USDOE Office of Science (SC), Biological and Environmental Research (BER)
National Sciences Foundation (NSF)
The authors wish it to be known that, in their opinion, the first two authors should be regarded as Joint First Authors.
ISSN:0305-1048
1362-4962
1362-4962
DOI:10.1093/nar/gkaa621