Massively parallel combinatorial microbiology
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, May, 2020
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2020
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| Online Access: | https://hdl.handle.net/1721.1/127886 |
| _version_ | 1826189950096244736 |
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| author | Kehe, Jared Scott. |
| author2 | Paul C. Blainey. |
| author_facet | Paul C. Blainey. Kehe, Jared Scott. |
| author_sort | Kehe, Jared Scott. |
| collection | MIT |
| description | Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, May, 2020 |
| first_indexed | 2024-09-23T08:31:49Z |
| format | Thesis |
| id | mit-1721.1/127886 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T08:31:49Z |
| publishDate | 2020 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1278862022-09-22T11:29:40Z Massively parallel combinatorial microbiology Kehe, Jared Scott. Paul C. Blainey. Massachusetts Institute of Technology. Department of Biological Engineering. Massachusetts Institute of Technology. Department of Biological Engineering Biological Engineering. Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, May, 2020 Cataloged from PDF version of thesis. Includes bibliographical references (pages 203-216). Reductionist biology of the 20th century rooted pure culture methods and antibiotics as pillars of humankind's interaction with microbiology, igniting a revolution in medicine and biotechnology. The revolution was not without cost. By overlooking complex biological interactions, it introduced new problems--from the sharp rise in immune disorders to the antibiotic resistance crisis--that 21st century tools must address. While 'omics methods have fundamentally expanded our understanding of biological complexity, we lack a generalized method for measuring how the parts of a complex system, such as the individual strains of a microbial community, interact with each other. In this thesis, I present kChip, a new platform for constructing massively parallel combinatorial arrays of these parts in order to measure their interactions directly. I describe how kChip has been used to reveal patterns in microbial community assembly, unearth minimal microbial combinations with desirable functions, and screen for compounds that potentiate antibiotic activity. I demonstrate how kChip can advance the development of new technologies like microbial consortia and combinatorial drug therapies. by Jared Scott Kehe. Ph. D. Ph.D. Massachusetts Institute of Technology, Department of Biological Engineering 2020-10-08T21:28:50Z 2020-10-08T21:28:50Z 2020 2020 Thesis https://hdl.handle.net/1721.1/127886 1197071541 eng MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided. http://dspace.mit.edu/handle/1721.1/7582 216 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Biological Engineering. Kehe, Jared Scott. Massively parallel combinatorial microbiology |
| title | Massively parallel combinatorial microbiology |
| title_full | Massively parallel combinatorial microbiology |
| title_fullStr | Massively parallel combinatorial microbiology |
| title_full_unstemmed | Massively parallel combinatorial microbiology |
| title_short | Massively parallel combinatorial microbiology |
| title_sort | massively parallel combinatorial microbiology |
| topic | Biological Engineering. |
| url | https://hdl.handle.net/1721.1/127886 |
| work_keys_str_mv | AT kehejaredscott massivelyparallelcombinatorialmicrobiology |