Quantitative methods for multiplexed cellular engineering and directed evolution
Multiplexed screening through pooled libraries has gained traction in engineering biological behavior. In particular, it has been effective at controlling cells, designing proteins, determining targets for gene therapy, and developing small molecule drugs. This thesis contributes to cellular enginee...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2023
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| Online Access: | https://hdl.handle.net/1721.1/147531 |
| _version_ | 1826213130656546816 |
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| author | Padia, Umesh Janak |
| author2 | Church, George M. |
| author_facet | Church, George M. Padia, Umesh Janak |
| author_sort | Padia, Umesh Janak |
| collection | MIT |
| description | Multiplexed screening through pooled libraries has gained traction in engineering biological behavior. In particular, it has been effective at controlling cells, designing proteins, determining targets for gene therapy, and developing small molecule drugs. This thesis contributes to cellular engineering and multiplexed screening in three projects. First, this thesis introduces a sequence-aware probabilistic model for cellular transcription that may be applied to library-scale cellular engineering screens. The model outperforms recently published single-cell models on key classification metrics. Next, this thesis introduces a multiplexed in vivo pipeline to engineer T-cell migration to solid tumors. The application of this pipeline recapitulates known homing factors associated with T-cell migration to melanoma. Finally, this thesis demonstrates a versatile distributed system to guide the design of proteins in directed evolution experiments and is generally applicable to all multiplexed library screens. |
| first_indexed | 2024-09-23T15:43:49Z |
| format | Thesis |
| id | mit-1721.1/147531 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T15:43:49Z |
| publishDate | 2023 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1475312023-01-20T03:07:56Z Quantitative methods for multiplexed cellular engineering and directed evolution Padia, Umesh Janak Church, George M. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Multiplexed screening through pooled libraries has gained traction in engineering biological behavior. In particular, it has been effective at controlling cells, designing proteins, determining targets for gene therapy, and developing small molecule drugs. This thesis contributes to cellular engineering and multiplexed screening in three projects. First, this thesis introduces a sequence-aware probabilistic model for cellular transcription that may be applied to library-scale cellular engineering screens. The model outperforms recently published single-cell models on key classification metrics. Next, this thesis introduces a multiplexed in vivo pipeline to engineer T-cell migration to solid tumors. The application of this pipeline recapitulates known homing factors associated with T-cell migration to melanoma. Finally, this thesis demonstrates a versatile distributed system to guide the design of proteins in directed evolution experiments and is generally applicable to all multiplexed library screens. S.M. 2023-01-19T19:56:32Z 2023-01-19T19:56:32Z 2022-09 2022-10-19T18:58:25.100Z Thesis https://hdl.handle.net/1721.1/147531 In Copyright - Educational Use Permitted Copyright retained by author(s) https://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology |
| spellingShingle | Padia, Umesh Janak Quantitative methods for multiplexed cellular engineering and directed evolution |
| title | Quantitative methods for multiplexed cellular engineering and directed evolution |
| title_full | Quantitative methods for multiplexed cellular engineering and directed evolution |
| title_fullStr | Quantitative methods for multiplexed cellular engineering and directed evolution |
| title_full_unstemmed | Quantitative methods for multiplexed cellular engineering and directed evolution |
| title_short | Quantitative methods for multiplexed cellular engineering and directed evolution |
| title_sort | quantitative methods for multiplexed cellular engineering and directed evolution |
| url | https://hdl.handle.net/1721.1/147531 |
| work_keys_str_mv | AT padiaumeshjanak quantitativemethodsformultiplexedcellularengineeringanddirectedevolution |