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 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.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2022

Author dc:creator

• Padia, Umesh Janak

Advisor dc:contributor.advisor

• Church, George M.

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/147531

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/147531