Diversity within species: interpreting strains in microbiomes

Rossum, Thea Van; Ferretti, Pamela; Maistrenko, Oleksandr M.; Bork, Peer

doi:10.1038/s41579-020-0368-1

Cited by 249 publications

(246 citation statements)

References 167 publications

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“…This supports the notion that strain level variation is important to consider when studying host-microbe interaction in animals, humans, and plants alike (e.g. [15,18,52,77,78]. In particular, in D. melanogaster evidence for the importance of variation between closely related bacteria is accumulating for life history of the host [26,29,[47][48][49][50][51]79].…”

Section: Variation Between Closely Related Microbes Is Important For supporting

confidence: 75%

Horizontal gene transfer-mediated bacterial strain variation affects host fitness

Wang

Baumdicker

Kuenzel

et al. 2020

Preprint

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How microbes affect host fitness and environmental adaptation has become a fundamental research question in evolutionary biology. We tested for associations of bacterial genomic variation and Drosophila melanogaster offspring number in a microbial Genome Wide Association Study (GWAS). Leveraging strain variation in the genus Gluconobacter, a genus of bacteria that are commonly associated with Drosophila under natural conditions, we pinpoint the thiamine biosynthesis pathway (TBP) as contributing to differences in fitness conferred to the fly host. By tracing the evolutionary history of TBP genes in Gluconobacter, we find that TBP genes were most likely lost and reacquired by horizontal gene transfer (HGT). We suggest that HGT might contribute to microbiome flexibility and speculate that it can also more generally contribute to host adaptation.

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Section: Variation Between Closely Related Microbes Is Important For supporting

confidence: 75%

Horizontal gene transfer-mediated bacterial strain variation affects host fitness

Wang

Baumdicker

Kuenzel

et al. 2020

Preprint

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“…The same caveat does of course apply to any current purely bioinformatics strategy for de novo resolution of genomes from metagenomes. Even if a single sample is used for binning and there are no subpopulations, the resulting MAG is still a composite and not a strain in the traditional microbiological sense [39].…”

Section: Discussionmentioning

confidence: 99%

“…The classic example is E. coli, where one strain can be a dangerous pathogen and another a harmless commensal [24]. The best definition of a strain, and the only one that avoids ambiguity, is a set of clonal descendants of a single cell [15,39], but strain genomes by this definition can only reliably be determined by sequencing cultured isolates or single cells [30]. The former is not representative of the community and the latter is still too expensive and low-throughput for many applications as well as producing only fragmentary genomes.…”

Section: Introductionmentioning

confidence: 99%

Metagenomics Strain Resolution on Assembly Graphs

Quince

Nurk

Raguideau

et al. 2020

Preprint

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We introduce a novel bioinformatics pipeline, STrain Resolution ON assembly Graphs (STRONG), which identifies strains de novo, when multiple metagenome samples from the same community are available. STRONG performs coassembly, followed by binning into metagenome assembled genomes (MAGs), but uniquely it stores the coassembly graph prior to simplification of variants. This enables the subgraphs for individual single-copy core genes (SCGs) in each MAG to be extracted. It can then thread back reads from the samples to compute per sample coverages for the unitigs in these graphs. These graphs and their unitig coverages are then used in a Bayesian algorithm, BayesPaths, that determines the number of strains present, their sequences or haplotypes on the SCGs and their abundances in each of the samples. Our approach both avoids the ambiguities of read mapping and allows more of the information on co-occurrence of variants in reads to be utilised than if variants were treated independently, whilst at the same time exploiting the correlation of variants across samples that occurs when they are linked in the same strain. We compare STRONG to the current state of the art on synthetic communities and demonstrate that we can recover more strains, more accurately, and with a realistic estimate of uncertainty deriving from the variational Bayesian algorithm employed for the strain resolution. On a real anaerobic digestor time series we obtained strain-resolved SCGs for over 300 MAGs that for abundant community members match those observed from long Nanopore reads.

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“…Achieving strain level resolution has been challenging because human gut microbiota comprises of numerous bacterial strains in each species 28 , the majority of which have not been isolated or even metagenomically detected before. As a result, previous microbiome analyses 29 have largely focused on species or lower level of resolution because finding delineating features of discrete bacterial strains, a necessary step for FMT strain tracking, remains unresolved.…”

Section: Introductionmentioning

confidence: 99%

Quantification of discrete gut bacterial strains following fecal transplantation for recurrent Clostridioides difficile infection demonstrates long-term stable engraftment in non-relapsing recipients

Aggarwala

Mogno

et al. 2020

Preprint

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Fecal Microbiota Transplantation (FMT), while successful for the treatment of recurrent Clostridioides difficile (rCDI) infection, lacks a quantitative identification of the discrete bacterial strains that transmit and stably engraft in recipients, and their association with clinical outcomes. Using >1,000 unique bacterial strains isolated and sequenced from a combination of 22 FMT donors and recipients, we develop a statistical approach Strainer to detect and track sequenced bacterial strains from low depth metagenomic sequencing data. On application to 14 FMT interventions, we detect stable and high engraftment of ∼71% of gut microbiota strains in recipients at even 5-years post-transplant, a remarkably durable therapeutic from a single administration. We found differential transmission and engraftment efficacy across bacterial taxonomic groups over short and long-time scales. Although ∼80% of the original pre-FMT recipient strains were eliminated by the FMT, those strains that remain persist even 5 years later, along with newer strains acquired from the environment. The precise quantification of donor bacterial strains in recipients independently explained the clinical outcomes of early and late relapse. Our framework identifies the consistently engrafting discrete bacterial strains for use in Live Biotherapeutic Products (LBP) as a safer, scalable alternative to FMT and enables systematic evaluation of different FMT and LBP study designs.

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Diversity within species: interpreting strains in microbiomes

Cited by 249 publications

References 167 publications

Horizontal gene transfer-mediated bacterial strain variation affects host fitness

Horizontal gene transfer-mediated bacterial strain variation affects host fitness

Metagenomics Strain Resolution on Assembly Graphs

Quantification of discrete gut bacterial strains following fecal transplantation for recurrent Clostridioides difficile infection demonstrates long-term stable engraftment in non-relapsing recipients

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