Massively parallel sequencing of single cells by epicPCR links functional genes with phylogenetic markers
Many microbial communities are characterized by high genetic diversity. 16S ribosomal RNA sequencing can determine community members, and metagenomics can determine the functional diversity, but resolving the functional role of individual cells in high throughput remains an unsolved challenge. Here,...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | en_US |
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Nature Publishing Group
2017
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| Online Access: | http://hdl.handle.net/1721.1/108419 https://orcid.org/0000-0002-2744-8994 https://orcid.org/0000-0001-5891-7653 |
| _version_ | 1811077619834159104 |
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| author | Guo, Mira T Briggs, Adrian W A Weitz, David Pitkänen, Leena K Vigneault, Francois Virta, Marko PJuhani Spencer, Sarah J. Tamminen, Manu V. Preheim, Sarah P. Brito, Ilana Lauren |
| author2 | Massachusetts Institute of Technology. Computational and Systems Biology Program |
| author_facet | Massachusetts Institute of Technology. Computational and Systems Biology Program Guo, Mira T Briggs, Adrian W A Weitz, David Pitkänen, Leena K Vigneault, Francois Virta, Marko PJuhani Spencer, Sarah J. Tamminen, Manu V. Preheim, Sarah P. Brito, Ilana Lauren |
| author_sort | Guo, Mira T |
| collection | MIT |
| description | Many microbial communities are characterized by high genetic diversity. 16S ribosomal RNA sequencing can determine community members, and metagenomics can determine the functional diversity, but resolving the functional role of individual cells in high throughput remains an unsolved challenge. Here, we describe epicPCR (Emulsion, Paired Isolation and Concatenation PCR), a new technique that links functional genes and phylogenetic markers in uncultured single cells, providing a throughput of hundreds of thousands of cells with costs comparable to one genomic library preparation. We demonstrate the utility of our technique in a natural environment by profiling a sulfate-reducing community in a freshwater lake, revealing both known sulfate reducers and discovering new putative sulfate reducers. Our method is adaptable to any conserved genetic trait and translates genetic associations from diverse microbial samples into a sequencing library that answers targeted ecological questions. Potential applications include identifying functional community members, tracing horizontal gene transfer netw |
| first_indexed | 2024-09-23T10:45:54Z |
| format | Article |
| id | mit-1721.1/108419 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T10:45:54Z |
| publishDate | 2017 |
| publisher | Nature Publishing Group |
| record_format | dspace |
| spelling | mit-1721.1/1084192022-09-27T14:51:31Z Massively parallel sequencing of single cells by epicPCR links functional genes with phylogenetic markers Guo, Mira T Briggs, Adrian W A Weitz, David Pitkänen, Leena K Vigneault, Francois Virta, Marko PJuhani Spencer, Sarah J. Tamminen, Manu V. Preheim, Sarah P. Brito, Ilana Lauren Massachusetts Institute of Technology. Computational and Systems Biology Program Massachusetts Institute of Technology. Department of Biological Engineering Massachusetts Institute of Technology. Department of Civil and Environmental Engineering Spencer, Sarah J. Tamminen, Manu V. Preheim, Sarah P. Brito, Ilana Lauren Many microbial communities are characterized by high genetic diversity. 16S ribosomal RNA sequencing can determine community members, and metagenomics can determine the functional diversity, but resolving the functional role of individual cells in high throughput remains an unsolved challenge. Here, we describe epicPCR (Emulsion, Paired Isolation and Concatenation PCR), a new technique that links functional genes and phylogenetic markers in uncultured single cells, providing a throughput of hundreds of thousands of cells with costs comparable to one genomic library preparation. We demonstrate the utility of our technique in a natural environment by profiling a sulfate-reducing community in a freshwater lake, revealing both known sulfate reducers and discovering new putative sulfate reducers. Our method is adaptable to any conserved genetic trait and translates genetic associations from diverse microbial samples into a sequencing library that answers targeted ecological questions. Potential applications include identifying functional community members, tracing horizontal gene transfer netw Academy of Finland (Project 257612) National Institute of Environmental Health Sciences (Award P30-ES002109) 2017-04-26T16:09:24Z 2017-04-26T16:09:24Z 2015-09 2015-06 Article http://purl.org/eprint/type/JournalArticle 1751-7362 1751-7370 http://hdl.handle.net/1721.1/108419 Spencer, Sarah J et al. “Massively Parallel Sequencing of Single Cells by epicPCR Links Functional Genes with Phylogenetic Markers.” The ISME Journal 10.2 (2016): 427–436. © 2016 International Society for Microbial Ecology https://orcid.org/0000-0002-2744-8994 https://orcid.org/0000-0001-5891-7653 en_US http://dx.doi.org/10.1038/ismej.2015.124 The ISME Journal Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/ application/pdf Nature Publishing Group Nature |
| spellingShingle | Guo, Mira T Briggs, Adrian W A Weitz, David Pitkänen, Leena K Vigneault, Francois Virta, Marko PJuhani Spencer, Sarah J. Tamminen, Manu V. Preheim, Sarah P. Brito, Ilana Lauren Massively parallel sequencing of single cells by epicPCR links functional genes with phylogenetic markers |
| title | Massively parallel sequencing of single cells by epicPCR links functional genes with phylogenetic markers |
| title_full | Massively parallel sequencing of single cells by epicPCR links functional genes with phylogenetic markers |
| title_fullStr | Massively parallel sequencing of single cells by epicPCR links functional genes with phylogenetic markers |
| title_full_unstemmed | Massively parallel sequencing of single cells by epicPCR links functional genes with phylogenetic markers |
| title_short | Massively parallel sequencing of single cells by epicPCR links functional genes with phylogenetic markers |
| title_sort | massively parallel sequencing of single cells by epicpcr links functional genes with phylogenetic markers |
| url | http://hdl.handle.net/1721.1/108419 https://orcid.org/0000-0002-2744-8994 https://orcid.org/0000-0001-5891-7653 |
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