Linking sequence to function in microbial genomics
Thesis: Ph. D., Massachusetts Institute of Technology, Computational and Systems Biology Program, 2017.
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| מחברים אחרים: | |
| פורמט: | Thesis |
| שפה: | eng |
| יצא לאור: |
Massachusetts Institute of Technology
2018
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| גישה מקוונת: | http://hdl.handle.net/1721.1/113437 |
| _version_ | 1826195383869505536 |
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| author | Spencer, Sarah Jean |
| author2 | Eric Alm. |
| author_facet | Eric Alm. Spencer, Sarah Jean |
| author_sort | Spencer, Sarah Jean |
| collection | MIT |
| description | Thesis: Ph. D., Massachusetts Institute of Technology, Computational and Systems Biology Program, 2017. |
| first_indexed | 2024-09-23T10:11:49Z |
| format | Thesis |
| id | mit-1721.1/113437 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T10:11:49Z |
| publishDate | 2018 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1134372019-04-10T13:57:46Z Linking sequence to function in microbial genomics Spencer, Sarah Jean Eric Alm. Massachusetts Institute of Technology. Computational and Systems Biology Program. Massachusetts Institute of Technology. Computational and Systems Biology Program. Computational and Systems Biology Program. Thesis: Ph. D., Massachusetts Institute of Technology, Computational and Systems Biology Program, 2017. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student-submitted PDF version of thesis. Includes bibliographical references (pages 129-140). Microbial genomes show high plasticity due to horizontal transfer, large community sizes, and rapid growth paired with adaptive mutations. Despite this mutability of gene content, most studies of microbial communities still rely on bulk, single-gene amplicon sequencing. In this thesis, I present methods that interrogate the gene content of single cells derived from complex natural communities. In the first project, I present a novel molecular biology method to link a bacterial functional gene to its host species with single-cell resolution. This high-throughput protocol is applied to assess the distribution of anaerobic respiration genes in a lake ecosystem. In the second project, I demonstrate extensions of this methodology to link genes between spatially proximal microbial cells, and apply this approach to probe the spatial organization of human dental plaque using DNA sequencing. In the final project, I completed whole-genome sequencing of environmental isolates derived from single, cultivable cells and employ mutational and horizontal transfer analysis to demonstrate adaptation to harsh environmental conditions in contaminated groundwater. These projects demonstrate the rich information stored within each microbial genome and the impact of spatial distribution in the environment. Each effort also contributes or highlights new molecular biology techniques to generate genomic data from individual microbial cells. by Sarah Jean Spencer. Ph. D. 2018-02-08T15:57:42Z 2018-02-08T15:57:42Z 2017 2017 Thesis http://hdl.handle.net/1721.1/113437 1020068595 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 140 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Computational and Systems Biology Program. Spencer, Sarah Jean Linking sequence to function in microbial genomics |
| title | Linking sequence to function in microbial genomics |
| title_full | Linking sequence to function in microbial genomics |
| title_fullStr | Linking sequence to function in microbial genomics |
| title_full_unstemmed | Linking sequence to function in microbial genomics |
| title_short | Linking sequence to function in microbial genomics |
| title_sort | linking sequence to function in microbial genomics |
| topic | Computational and Systems Biology Program. |
| url | http://hdl.handle.net/1721.1/113437 |
| work_keys_str_mv | AT spencersarahjean linkingsequencetofunctioninmicrobialgenomics |