Targeted insertional mutagenesis libraries for deep domain insertion profiling

Author:

Coyote-Maestas Willow1,Nedrud David1,Okorafor Steffan2,He Yungui3,Schmidt Daniel3ORCID

Affiliation:

1. Dept. of Biochemistry, Molecular Biology & Biophysics, University of Minnesota, Minneapolis, MN 55455, USA

2. Dept. of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA

3. Dept. of Genetics, Cell Biology & Development, University of Minnesota, Minneapolis, MN 55455, USA

Abstract

Abstract Domain recombination is a key principle in protein evolution and protein engineering, but inserting a donor domain into every position of a target protein is not easily experimentally accessible. Most contemporary domain insertion profiling approaches rely on DNA transposons, which are constrained by sequence bias. Here, we establish Saturated Programmable Insertion Engineering (SPINE), an unbiased, comprehensive, and targeted domain insertion library generation technique using oligo library synthesis and multi-step Golden Gate cloning. Through benchmarking to MuA transposon-mediated library generation on four ion channel genes, we demonstrate that SPINE-generated libraries are enriched for in-frame insertions, have drastically reduced sequence bias as well as near-complete and highly-redundant coverage. Unlike transposon-mediated domain insertion that was severely biased and sparse for some genes, SPINE generated high-quality libraries for all genes tested. Using the Inward Rectifier K+ channel Kir2.1, we validate the practical utility of SPINE by constructing and comparing domain insertion permissibility maps. SPINE is the first technology to enable saturated domain insertion profiling. SPINE could help explore the relationship between domain insertions and protein function, and how this relationship is shaped by evolutionary forces and can be engineered for biomedical applications.

Funder

National Institutes of Health

National Science Foundation

Howard Hughes Medical Institute

Publisher

Oxford University Press (OUP)

Subject

Genetics

Reference89 articles.

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