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Species-level functional profiling of metagenomes and metatranscriptomes

Nature Methods · 2018 · Vol. 15(11) · pp. 962–968
Eric A. FranzosaLauren J. McIverAli RahnavardLuke ThompsonMelanie SchirmerGeorge WeingartKaren Schwarzberg LipsonRob KnightJ. Gregory CaporasoNicola SegataCurtis Huttenhower

Abstract

Functional profiles of microbial communities are typically generated using comprehensive metagenomic or metatranscriptomic sequence read searches, which are time-consuming, prone to spurious mapping, and often limited to community-level quantification. We developed HUMAnN2, a tiered search strategy that enables fast, accurate, and species-resolved functional profiling of host-associated and environmental communities. HUMAnN2 identifies a community's known species, aligns reads to their pangenomes, performs translated search on unclassified reads, and finally quantifies gene families and pathways. Relative to pure translated search, HUMAnN2 is faster and produces more accurate gene family profiles. We applied HUMAnN2 to study clinal variation in marine metabolism, ecological contribution patterns among human microbiome pathways, variation in species' genomic versus transcriptional contributions, and strain profiling. Further, we introduce 'contributional diversity' to explain patterns of ecological assembly across different microbial community types.

Genomics and Phylogenetic StudiesMicrobial Community Ecology and PhysiologyGut microbiota and healthMetagenomicsBiologyProfiling (computer programming)Computational biologyMicrobiomeSpurious relationshipHuman Microbiome ProjectHuman microbiomeEvolutionary biologyFunctional diversity

MeSH terms

BacteriaBacterial ProteinsHumansSoftwareSpecies SpecificityGene Expression ProfilingMetagenomeHigh-Throughput Nucleotide SequencingTranscriptomeMicrobiota
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