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dc.contributor.advisorWang, Xiao
dc.contributor.advisorLiu, David
dc.contributor.authorHennes, Andrew
dc.date.accessioned2023-07-31T19:46:38Z
dc.date.available2023-07-31T19:46:38Z
dc.date.issued2023-06
dc.date.submitted2023-06-06T16:35:05.217Z
dc.identifier.urihttps://hdl.handle.net/1721.1/151530
dc.description.abstractDeveloping tools for target manipulation of protein chemistry remains a longstanding goal in chemical biology. Trans-splicing inteins fulfill a crucial niche in this area by enabling post translational splicing of separate polypeptides, introduction of post translational modifications, and other chemistry on the amide backbone. This has motivated engineering and evolution of bespoke intein properties, including extein constraints, split site, kinetics, and orthogonality. Rational approaches are highly biased and preexisting directed evolution methods are laborious and often struggle with guaranteeing splicing dependance in a selection. To accelerate intein evolution we introduce a phage assisted continuous evolution (PACE) for intein properties. We show this selection is strictly splicing dependant, discriminates between intein splicing rates from one minute to several hours, discriminates between preferred over unpreferred extein contexts, supports propagation of phage in a multi-passage PANCE format, and circumvents recombination-driven phage cheating through a recombination-resistant helper strain. We anticipate this selection will enable facile, rapid evolution of inteins with bespoke properties.
dc.publisherMassachusetts Institute of Technology
dc.rightsIn Copyright - Educational Use Permitted
dc.rightsCopyright retained by author(s)
dc.rights.urihttps://rightsstatements.org/page/InC-EDU/1.0/
dc.titleA Selection for Intein Splicing inPhage Assisted Continuous Evolution
dc.typeThesis
dc.description.degreeM.Eng.
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
mit.thesis.degreeMaster
thesis.degree.nameMaster of Engineering in Computer Science and Molecular Biology


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