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Targeted insertional mutagenesis libraries for deep domain insertion profiling

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 b...

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Autores principales: Coyote-Maestas, Willow, Nedrud, David, Okorafor, Steffan, He, Yungui, Schmidt, Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6954442/
https://www.ncbi.nlm.nih.gov/pubmed/31745561
http://dx.doi.org/10.1093/nar/gkz1110
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author Coyote-Maestas, Willow
Nedrud, David
Okorafor, Steffan
He, Yungui
Schmidt, Daniel
author_facet Coyote-Maestas, Willow
Nedrud, David
Okorafor, Steffan
He, Yungui
Schmidt, Daniel
author_sort Coyote-Maestas, Willow
collection PubMed
description 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.
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spelling pubmed-69544422020-01-16 Targeted insertional mutagenesis libraries for deep domain insertion profiling Coyote-Maestas, Willow Nedrud, David Okorafor, Steffan He, Yungui Schmidt, Daniel Nucleic Acids Res Methods Online 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. Oxford University Press 2020-01-24 2019-11-20 /pmc/articles/PMC6954442/ /pubmed/31745561 http://dx.doi.org/10.1093/nar/gkz1110 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methods Online
Coyote-Maestas, Willow
Nedrud, David
Okorafor, Steffan
He, Yungui
Schmidt, Daniel
Targeted insertional mutagenesis libraries for deep domain insertion profiling
title Targeted insertional mutagenesis libraries for deep domain insertion profiling
title_full Targeted insertional mutagenesis libraries for deep domain insertion profiling
title_fullStr Targeted insertional mutagenesis libraries for deep domain insertion profiling
title_full_unstemmed Targeted insertional mutagenesis libraries for deep domain insertion profiling
title_short Targeted insertional mutagenesis libraries for deep domain insertion profiling
title_sort targeted insertional mutagenesis libraries for deep domain insertion profiling
topic Methods Online
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6954442/
https://www.ncbi.nlm.nih.gov/pubmed/31745561
http://dx.doi.org/10.1093/nar/gkz1110
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