Microbial strain-level population structure and genetic diversity from metagenomes
Open accessAbstract
Among the human health conditions linked to microbial communities, phenotypes are often associated with only a subset of strains within causal microbial groups. Although it has been critical for decades in microbial physiology to characterize individual strains, this has been challenging when using culture-independent high-throughput metagenomics. We introduce StrainPhlAn, a novel metagenomic strain identification approach, and apply it to characterize the genetic structure of thousands of strains from more than 125 species in more than 1500 gut metagenomes drawn from populations spanning North and South American, European, Asian, and African countries. The method relies on per-sample dominant sequence variant reconstruction within species-specific marker genes. It identified primarily subject-specific strain variants (<5% inter-subject strain sharing), and we determined that a single strain typically dominated each species and was retained over time (for >70% of species). Microbial population structure was correlated in several distinct ways with the geographic structure of the host population. In some cases, discrete subspecies (e.g., for Eubacterium rectale and Prevotella copri ) or continuous microbial genetic variations (e.g., for Faecalibacterium prausnitzii ) were associated with geographically distinct human populations, whereas few strains occurred in multiple unrelated cohorts. We further estimated the genetic variability of gut microbes, with Bacteroides species appearing remarkably consistent (0.45% median number of nucleotide variants between strains), whereas P. copri was among the most plastic gut colonizers. We thus characterize here the population genetics of previously inaccessible intestinal microbes, providing a comprehensive strain-level genetic overview of the gut microbial diversity.
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A large fraction of the gut microbiome's individual uniqueness is encoded at the level of single strains.
“and a large fraction of this uniqueness is encoded at the level of single strains36–38.”
From Cross-cohort gut microbiome associations with immune checkpoint inhibitor response in advanced melanoma (2022) · cites this paper as [36]
Strain-level characterization of taxa directly from metagenomes is an effective cultivation-free means to profile population structure across geography or other conditions and to track strain transmission.
“Strain-level characterization of taxa directly from metagenomes is an effective cultivation-free means to profile the population structure of a microbial species across geography or other conditions (Scholz et al., 2016; Truong et al., 2017) and to track strain transmission (Ferretti et al., 2018).”
From Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3 (2021) · cites this paper as Truong et al., 2017
StrainPhlAn performs genotyping at the strain level by reconstructing sample-specific consensus sequences of MetaPhlAn markers and using them for multiple-sequence alignment and phylogenetic modeling.
“StrainPhlAn performs genotyping at the strain level by reconstructing sample-specific consensus sequences of MetaPhlAn markers and using them for multiple-sequence alignment and phylogenetic modeling (Truong et al., 2017).”
From Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3 (2021) · cites this paper as Truong et al., 2017
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- Authors
- Truong, D. T., Tett, A., Pasolli, E., Huttenhower, C., & Segata, N.
- Affiliations
- University of Trento (IT)
- Broad Institute (US)
- Corresponding author
- Segata, Nicola
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2017-02-06
- Volume
- 27
- Issue
- 4
- Pages
- 626-638
- ISSN
- 1088-9051 (ISSN-L)
- 1549-5469
- PMC
- PMC5378180
- OpenAlex
- W2586360538
- Cited by
- 839
- References
- 73
- Citations by year
- 2026: 81 · 2025: 105 · 2024: 112 · 2023: 73 · 2022: 87 · 2021: 158 · 2020: 87 · 2019: 65 · 2018: 46 · 2017: 23 · 2015: 1 · 2014: 1
- Type
- posted content
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Genome Research (publishedVersion)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Iris (University of Trento) (submittedVersion, cc-by)
- HighWire Press Open Archive (submittedVersion)
- Funders
- National Institutes of Health (R01HG005969, U54DE023798)
- National Science Foundation (DBI-1053486)
- Army Research Office (W911NF-11-1-0473)
- Fondazione Caritro (Rif. Int.2014.0325, Rif. Int.2013.0239)
- EuropeanUnion H2020Marie Skłodowska-Curie Actions ((707345)
- European Union FP7 Marie-Curie (PCIG13-618833)
- Ministero dell'Istruzione, dell'Università e della Ricerca (FIR RBFR13EWWI)
- LEO Pharma Research Foundation
- Terme di Comano
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
- Keywords
- gut microbiota, microbial population structure, human population genetics, Eubacterium rectale, Prevotella copri, Faecalibacterium prausnitzii, Bacteroides
- MeSH terms
- Algorithms, Bacteroides, Eubacterium, Humans, Polymorphism, Genetic, Genome, Human, Sequence Analysis, DNA, Prevotella, Metagenome, Molecular Typing, Microbiota
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