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Microbiome single cell atlases generated with a commercial instrument
Single cell sequencing is useful for resolving complex systems into their composite cell types and computationally mining them for unique features that are masked in pooled sequencing. However, while commercial instruments have made single cell analysis widespread for mammalian cells, analogous tool...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Journal Experts
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10543498/ https://www.ncbi.nlm.nih.gov/pubmed/37790580 http://dx.doi.org/10.21203/rs.3.rs-3253785/v1 |
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author | Abate, Adam Li, Xiangpeng Xu, Linfeng Demaree, Benjamin Noecker, Cecilia Bisanz, Jordan Weisgerber, Daniel Modavi, Cyrus Turnbaugh, Peter |
author_facet | Abate, Adam Li, Xiangpeng Xu, Linfeng Demaree, Benjamin Noecker, Cecilia Bisanz, Jordan Weisgerber, Daniel Modavi, Cyrus Turnbaugh, Peter |
author_sort | Abate, Adam |
collection | PubMed |
description | Single cell sequencing is useful for resolving complex systems into their composite cell types and computationally mining them for unique features that are masked in pooled sequencing. However, while commercial instruments have made single cell analysis widespread for mammalian cells, analogous tools for microbes are limited. Here, we present EASi-seq (Easily Accessible Single microbe sequencing). By adapting the single cell workflow of the commercial Mission Bio Tapestri instrument, this method allows for efficient sequencing of individual microbes’ genomes. EASi-seq allows thousands of microbes to be sequenced per run and, as we show, can generate detailed atlases of human and environmental microbiomes. The ability to capture large shotgun genome datasets from thousands of single microbes provides new opportunities in discovering and analyzing species subpopulations. To facilitate this, we develop a companion bioinformatic pipeline that clusters microbes by similarity, improving whole genome assembly, strain identification, taxonomic classification, and gene annotation. In addition, we demonstrate integration of metagenomic contigs with the EASi-seq datasets to reduce capture bias and increase coverage. Overall, EASi-seq enables high quality single cell genomic data for microbiome samples using an accessible workflow that can be run on a commercially available platform. |
format | Online Article Text |
id | pubmed-10543498 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Journal Experts |
record_format | MEDLINE/PubMed |
spelling | pubmed-105434982023-10-03 Microbiome single cell atlases generated with a commercial instrument Abate, Adam Li, Xiangpeng Xu, Linfeng Demaree, Benjamin Noecker, Cecilia Bisanz, Jordan Weisgerber, Daniel Modavi, Cyrus Turnbaugh, Peter Res Sq Article Single cell sequencing is useful for resolving complex systems into their composite cell types and computationally mining them for unique features that are masked in pooled sequencing. However, while commercial instruments have made single cell analysis widespread for mammalian cells, analogous tools for microbes are limited. Here, we present EASi-seq (Easily Accessible Single microbe sequencing). By adapting the single cell workflow of the commercial Mission Bio Tapestri instrument, this method allows for efficient sequencing of individual microbes’ genomes. EASi-seq allows thousands of microbes to be sequenced per run and, as we show, can generate detailed atlases of human and environmental microbiomes. The ability to capture large shotgun genome datasets from thousands of single microbes provides new opportunities in discovering and analyzing species subpopulations. To facilitate this, we develop a companion bioinformatic pipeline that clusters microbes by similarity, improving whole genome assembly, strain identification, taxonomic classification, and gene annotation. In addition, we demonstrate integration of metagenomic contigs with the EASi-seq datasets to reduce capture bias and increase coverage. Overall, EASi-seq enables high quality single cell genomic data for microbiome samples using an accessible workflow that can be run on a commercially available platform. American Journal Experts 2023-09-14 /pmc/articles/PMC10543498/ /pubmed/37790580 http://dx.doi.org/10.21203/rs.3.rs-3253785/v1 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article Abate, Adam Li, Xiangpeng Xu, Linfeng Demaree, Benjamin Noecker, Cecilia Bisanz, Jordan Weisgerber, Daniel Modavi, Cyrus Turnbaugh, Peter Microbiome single cell atlases generated with a commercial instrument |
title | Microbiome single cell atlases generated with a commercial instrument |
title_full | Microbiome single cell atlases generated with a commercial instrument |
title_fullStr | Microbiome single cell atlases generated with a commercial instrument |
title_full_unstemmed | Microbiome single cell atlases generated with a commercial instrument |
title_short | Microbiome single cell atlases generated with a commercial instrument |
title_sort | microbiome single cell atlases generated with a commercial instrument |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10543498/ https://www.ncbi.nlm.nih.gov/pubmed/37790580 http://dx.doi.org/10.21203/rs.3.rs-3253785/v1 |
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