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Dissecting the dominant hot spring microbial populations based on community-wide sampling at single-cell genomic resolution

With advances in DNA sequencing and miniaturized molecular biology workflows, rapid and affordable sequencing of single-cell genomes has become a reality. Compared to 16S rRNA gene surveys and shotgun metagenomics, large-scale application of single-cell genomics to whole microbial communities provid...

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Autores principales: Bowers, Robert M., Nayfach, Stephen, Schulz, Frederik, Jungbluth, Sean P., Ruhl, Ilona A., Sheremet, Andriy, Lee, Janey, Goudeau, Danielle, Eloe-Fadrosh, Emiley A., Stepanauskas, Ramunas, Malmstrom, Rex R., Kyrpides, Nikos C., Dunfield, Peter F., Woyke, Tanja
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9039060/
https://www.ncbi.nlm.nih.gov/pubmed/34969995
http://dx.doi.org/10.1038/s41396-021-01178-4
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author Bowers, Robert M.
Nayfach, Stephen
Schulz, Frederik
Jungbluth, Sean P.
Ruhl, Ilona A.
Sheremet, Andriy
Lee, Janey
Goudeau, Danielle
Eloe-Fadrosh, Emiley A.
Stepanauskas, Ramunas
Malmstrom, Rex R.
Kyrpides, Nikos C.
Dunfield, Peter F.
Woyke, Tanja
author_facet Bowers, Robert M.
Nayfach, Stephen
Schulz, Frederik
Jungbluth, Sean P.
Ruhl, Ilona A.
Sheremet, Andriy
Lee, Janey
Goudeau, Danielle
Eloe-Fadrosh, Emiley A.
Stepanauskas, Ramunas
Malmstrom, Rex R.
Kyrpides, Nikos C.
Dunfield, Peter F.
Woyke, Tanja
author_sort Bowers, Robert M.
collection PubMed
description With advances in DNA sequencing and miniaturized molecular biology workflows, rapid and affordable sequencing of single-cell genomes has become a reality. Compared to 16S rRNA gene surveys and shotgun metagenomics, large-scale application of single-cell genomics to whole microbial communities provides an integrated snapshot of community composition and function, directly links mobile elements to their hosts, and enables analysis of population heterogeneity of the dominant community members. To that end, we sequenced nearly 500 single-cell genomes from a low diversity hot spring sediment sample from Dewar Creek, British Columbia, and compared this approach to 16S rRNA gene amplicon and shotgun metagenomics applied to the same sample. We found that the broad taxonomic profiles were similar across the three sequencing approaches, though several lineages were missing from the 16S rRNA gene amplicon dataset, likely the result of primer mismatches. At the functional level, we detected a large array of mobile genetic elements present in the single-cell genomes but absent from the corresponding same species metagenome-assembled genomes. Moreover, we performed a single-cell population genomic analysis of the three most abundant community members, revealing differences in population structure based on mutation and recombination profiles. While the average pairwise nucleotide identities were similar across the dominant species-level lineages, we observed differences in the extent of recombination between these dominant populations. Most intriguingly, the creek’s Hydrogenobacter sp. population appeared to be so recombinogenic that it more closely resembled a sexual species than a clonally evolving microbe. Together, this work demonstrates that a randomized single-cell approach can be useful for the exploration of previously uncultivated microbes from community composition to population structure.
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spelling pubmed-90390602022-04-28 Dissecting the dominant hot spring microbial populations based on community-wide sampling at single-cell genomic resolution Bowers, Robert M. Nayfach, Stephen Schulz, Frederik Jungbluth, Sean P. Ruhl, Ilona A. Sheremet, Andriy Lee, Janey Goudeau, Danielle Eloe-Fadrosh, Emiley A. Stepanauskas, Ramunas Malmstrom, Rex R. Kyrpides, Nikos C. Dunfield, Peter F. Woyke, Tanja ISME J Article With advances in DNA sequencing and miniaturized molecular biology workflows, rapid and affordable sequencing of single-cell genomes has become a reality. Compared to 16S rRNA gene surveys and shotgun metagenomics, large-scale application of single-cell genomics to whole microbial communities provides an integrated snapshot of community composition and function, directly links mobile elements to their hosts, and enables analysis of population heterogeneity of the dominant community members. To that end, we sequenced nearly 500 single-cell genomes from a low diversity hot spring sediment sample from Dewar Creek, British Columbia, and compared this approach to 16S rRNA gene amplicon and shotgun metagenomics applied to the same sample. We found that the broad taxonomic profiles were similar across the three sequencing approaches, though several lineages were missing from the 16S rRNA gene amplicon dataset, likely the result of primer mismatches. At the functional level, we detected a large array of mobile genetic elements present in the single-cell genomes but absent from the corresponding same species metagenome-assembled genomes. Moreover, we performed a single-cell population genomic analysis of the three most abundant community members, revealing differences in population structure based on mutation and recombination profiles. While the average pairwise nucleotide identities were similar across the dominant species-level lineages, we observed differences in the extent of recombination between these dominant populations. Most intriguingly, the creek’s Hydrogenobacter sp. population appeared to be so recombinogenic that it more closely resembled a sexual species than a clonally evolving microbe. Together, this work demonstrates that a randomized single-cell approach can be useful for the exploration of previously uncultivated microbes from community composition to population structure. Nature Publishing Group UK 2021-12-30 2022-05 /pmc/articles/PMC9039060/ /pubmed/34969995 http://dx.doi.org/10.1038/s41396-021-01178-4 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Bowers, Robert M.
Nayfach, Stephen
Schulz, Frederik
Jungbluth, Sean P.
Ruhl, Ilona A.
Sheremet, Andriy
Lee, Janey
Goudeau, Danielle
Eloe-Fadrosh, Emiley A.
Stepanauskas, Ramunas
Malmstrom, Rex R.
Kyrpides, Nikos C.
Dunfield, Peter F.
Woyke, Tanja
Dissecting the dominant hot spring microbial populations based on community-wide sampling at single-cell genomic resolution
title Dissecting the dominant hot spring microbial populations based on community-wide sampling at single-cell genomic resolution
title_full Dissecting the dominant hot spring microbial populations based on community-wide sampling at single-cell genomic resolution
title_fullStr Dissecting the dominant hot spring microbial populations based on community-wide sampling at single-cell genomic resolution
title_full_unstemmed Dissecting the dominant hot spring microbial populations based on community-wide sampling at single-cell genomic resolution
title_short Dissecting the dominant hot spring microbial populations based on community-wide sampling at single-cell genomic resolution
title_sort dissecting the dominant hot spring microbial populations based on community-wide sampling at single-cell genomic resolution
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9039060/
https://www.ncbi.nlm.nih.gov/pubmed/34969995
http://dx.doi.org/10.1038/s41396-021-01178-4
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