Species-level functional profiling of metagenomes and metatranscriptomes
Open accessAbstract
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.
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The challenge of differentiating globally homologous UniRef90 protein sequences using short sequencing reads results in a reduction of community and per-species accuracy relative to broader gene families.
“As previously noted (Franzosa et al., 2018), the challenge of differentiating globally homologous UniRef90 protein sequences using short sequencing reads results in a reduction of community and per-species accuracy relative to broader gene families.”
From Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3 (2021) · cites this paper as Franzosa et al., 2018
HUMAnN's within-species function sensitivity is naturally lower for species below 1x coverage because many of their genes will not have been sampled.
“As previously noted (Franzosa et al., 2018), HUMAnN’s within-species function sensitivity is naturally lower for species below 1x coverage in a sample, as many of their genes will not have been sampled at all during the sequencing process.”
From Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3 (2021) · cites this paper as Franzosa et al., 2018
bioBakery provides one of very few environments currently capable of integrating both metagenomes and metatranscriptomes to begin overcoming these uncertainties.
“Notably, bioBakery provides one of very few environments currently capable of integrating both metagenomes and metatranscriptomes to begin overcoming these uncertainties (Franzosa et al., 2018).”
From Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3 (2021) · cites this paper as Franzosa et al., 2018
Coverage filtering was already implemented in HUMAnN 2 for post-processing translated search results, where it was shown to increase UniRef90-level specificity considerably at a small cost to sensitivity.
“Coverage filtering (new option 1) was already implemented in HUMAnN 2 for post-processing translated search results, where it was shown to increase UniRef90-level specificity considerably at a small cost to sensitivity (Franzosa et al., 2018).”
From Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3 (2021) · cites this paper as Franzosa et al., 2018
Procedures for community genome annotation developed during HUMAnN2 benchmarking were applied to aid in gold-standard construction.
“We applied procedures for community genome annotation developed during HUMAnN2 benchmarking to aid in gold-standard construction (Franzosa et al., 2018).”
From Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3 (2021) · cites this paper as Franzosa et al., 2018
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- Authors
- Franzosa, E. A., McIver, L. J., Rahnavard, G., Thompson, L. R., Schirmer, M., Weingart, G., Lipson, K. S., Knight, R., Caporaso, J. G., Segata, N., & Huttenhower, C.
- Affiliations
- Broad Institute (US)
- University of California San Diego (US)
- Harvard University (US)
- Northern Arizona University (US)
- University of Trento (IT)
- Corresponding author
- Huttenhower, Curtis
- ORCID
- Venue
- Nature Methods
- Published
- 2018-10-30
- Volume
- 15
- Issue
- 11
- Pages
- 962-968
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- PMC
- PMC6235447
- OpenAlex
- W2897611961
- Cited by
- 1,693
- References
- 51
- Citations by year
- 2026: 188 · 2025: 199 · 2024: 201 · 2023: 201 · 2022: 264 · 2021: 342 · 2020: 204 · 2019: 84 · 2018: 3 · 2017: 1 · 2015: 1
- FWCI
- 58.50
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Methods (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Iris (University of Trento) (submittedVersion, other-oa)
- NOAA Institutional Repository (submittedVersion)
- Funders
- National Institute of Diabetes and Digestive and Kidney Diseases (P30DK043351)
- National Institute of Dental and Craniofacial Research (U54DE023798)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Keywords
- metagenomics, metatranscriptomics, host-associated microbiome, environmental microbial communities, human microbiome
- MeSH terms
- Bacteria, Bacterial Proteins, Humans, Software, Species Specificity, Gene Expression Profiling, Metagenome, High-Throughput Nucleotide Sequencing, Transcriptome, Microbiota
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