Massively parallel screening of synthetic microbial communities
Microbial communities have numerous potential applications in biotechnology, agriculture, and medicine. Nevertheless, the limited accuracy with which we can predict interspecies interactions and environmental dependencies hinders efforts to rationally engineer beneficial consortia. Empirical screeni...
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| Format: | Article |
| Language: | English |
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Proceedings of the National Academy of Sciences
2020
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| Online Access: | https://hdl.handle.net/1721.1/124422 |
| _version_ | 1826191482463191040 |
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| author | Kehe, Jared Scott Kulesa, Anthony Benjamin Ortiz, Anthony Gore, Jeff Blainey, Paul C |
| author2 | Massachusetts Institute of Technology. Department of Biological Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Biological Engineering Kehe, Jared Scott Kulesa, Anthony Benjamin Ortiz, Anthony Gore, Jeff Blainey, Paul C |
| author_sort | Kehe, Jared Scott |
| collection | MIT |
| description | Microbial communities have numerous potential applications in biotechnology, agriculture, and medicine. Nevertheless, the limited accuracy with which we can predict interspecies interactions and environmental dependencies hinders efforts to rationally engineer beneficial consortia. Empirical screening is a complementary approach wherein synthetic communities are combinatorially constructed and assayed in high throughput. However, assembling many combinations of microbes is logistically complex and difficult to achieve on a timescale commensurate with microbial growth. Here, we introduce the kChip, a droplets-based platform that performs rapid, massively parallel, bottom-up construction and screening of synthetic microbial communities. We first show that the kChip enables phenotypic characterization of microbes across environmental conditions. Next, in a screen of ∼100,000 multispecies communities comprising up to 19 soil isolates, we identified sets that promote the growth of the model plant symbiont Herbaspirillum frisingense in a manner robust to carbon source variation and the presence of additional species. Broadly, kChip screening can identify multispecies consortia possessing any optically assayable function, including facilitation of biocontrol agents, suppression of pathogens, degradation of recalcitrant substrates, and robustness of these functions to perturbation, with many applications across basic and applied microbial ecology. |
| first_indexed | 2024-09-23T08:56:33Z |
| format | Article |
| id | mit-1721.1/124422 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T08:56:33Z |
| publishDate | 2020 |
| publisher | Proceedings of the National Academy of Sciences |
| record_format | dspace |
| spelling | mit-1721.1/1244222022-09-26T09:23:55Z Massively parallel screening of synthetic microbial communities Kehe, Jared Scott Kulesa, Anthony Benjamin Ortiz, Anthony Gore, Jeff Blainey, Paul C Massachusetts Institute of Technology. Department of Biological Engineering Massachusetts Institute of Technology. Department of Biology Multidisciplinary Microbial communities have numerous potential applications in biotechnology, agriculture, and medicine. Nevertheless, the limited accuracy with which we can predict interspecies interactions and environmental dependencies hinders efforts to rationally engineer beneficial consortia. Empirical screening is a complementary approach wherein synthetic communities are combinatorially constructed and assayed in high throughput. However, assembling many combinations of microbes is logistically complex and difficult to achieve on a timescale commensurate with microbial growth. Here, we introduce the kChip, a droplets-based platform that performs rapid, massively parallel, bottom-up construction and screening of synthetic microbial communities. We first show that the kChip enables phenotypic characterization of microbes across environmental conditions. Next, in a screen of ∼100,000 multispecies communities comprising up to 19 soil isolates, we identified sets that promote the growth of the model plant symbiont Herbaspirillum frisingense in a manner robust to carbon source variation and the presence of additional species. Broadly, kChip screening can identify multispecies consortia possessing any optically assayable function, including facilitation of biocontrol agents, suppression of pathogens, degradation of recalcitrant substrates, and robustness of these functions to perturbation, with many applications across basic and applied microbial ecology. National Science Foundation (U.S.). Graduate Research Fellowship (Fellow ID 2016220942) National Science Foundation (U.S.). Graduate Research Fellowship (Fellow ID 2013164251) Burroughs Wellcome Fund (Career Award at the Scientific Interface Grant 1010240) Simons Foundation (Grant 542385) 2020-03-30T19:22:13Z 2020-03-30T19:22:13Z 2019-06-11 2020-02-12T19:07:51Z Article http://purl.org/eprint/type/JournalArticle 0027-8424 1091-6490 https://hdl.handle.net/1721.1/124422 Kehe, Jared et al. "Massively parallel screening of synthetic microbial communities." Proceedings of the National Academy of Sciences of the United States of America 116 (2019):12804-12809 © 2019 The Author(s) en 10.1073/pnas.1900102116 Proceedings of the National Academy of Sciences of the United States of America Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf Proceedings of the National Academy of Sciences PNAS |
| spellingShingle | Multidisciplinary Kehe, Jared Scott Kulesa, Anthony Benjamin Ortiz, Anthony Gore, Jeff Blainey, Paul C Massively parallel screening of synthetic microbial communities |
| title | Massively parallel screening of synthetic microbial communities |
| title_full | Massively parallel screening of synthetic microbial communities |
| title_fullStr | Massively parallel screening of synthetic microbial communities |
| title_full_unstemmed | Massively parallel screening of synthetic microbial communities |
| title_short | Massively parallel screening of synthetic microbial communities |
| title_sort | massively parallel screening of synthetic microbial communities |
| topic | Multidisciplinary |
| url | https://hdl.handle.net/1721.1/124422 |
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