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Abstract
Proteins evolve through the modular rearrangement of elements known as domains. Extant, multidomain proteins are hypothesized to be the result of domain accretion, but there has been limited experimental validation of this idea. Here, we introduce a technique for genetic minimization by iterative size-exclusion and recombination (MISER) for comprehensively making all possible deletions of a protein. Using MISER, we generate a deletion landscape for the CRISPR protein Cas9. We find that the catalytically-dead Streptococcus pyogenes Cas9 can tolerate large single deletions in the REC2, REC3, HNH, and RuvC domains, while still functioning in vitro and in vivo, and that these deletions can be stacked together to engineer minimal, DNA-binding effector proteins. In total, our results demonstrate that extant proteins retain significant modularity from the accretion process and, as genetic size is a major limitation for viral delivery systems, establish a general technique to improve genome editing and gene therapy-based therapeutics.
Proteins evolve through the modular rearrangement of domains. Here the authors introduce MISER, a minimization by iterative size-exclusion and recombination method to make all possible deletions of a protein, uncovering functions for Cas9 domains involved in DNA binding.
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1 University of California, Berkeley, Department of Molecular and Cell Biology, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878)
2 University of California, Berkeley, Department of Molecular and Cell Biology, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878); University of California, Berkeley, Innovative Genomics Institute, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878); Scribe Therapeutics, Alameda, USA (GRID:grid.47840.3f)
3 University of California, Berkeley, Department of Molecular and Cell Biology, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878); Gladstone Institutes, San Francisco, USA (GRID:grid.249878.8) (ISNI:0000 0004 0572 7110); University of California, San Francisco, Department of Cellular and Molecular Pharmacology, San Francisco, USA (GRID:grid.266102.1) (ISNI:0000 0001 2297 6811)
4 University of California, Berkeley, Department of Molecular and Cell Biology, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878); University of California, San Diego, Division of Biological Sciences, San Diego, USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242)
5 Gladstone Institutes, San Francisco, USA (GRID:grid.249878.8) (ISNI:0000 0004 0572 7110)
6 University of California, Berkeley, Department of Molecular and Cell Biology, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878); University of California, Berkeley, Innovative Genomics Institute, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878)
7 University of California, Berkeley, Department of Molecular and Cell Biology, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878); University of California, Berkeley, Innovative Genomics Institute, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878); Gladstone Institutes, San Francisco, USA (GRID:grid.249878.8) (ISNI:0000 0004 0572 7110); University of California, Berkeley, Graduate Group in Biophysics, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878); University of California, Berkeley, Department of Bioengineering, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878); University of California, Berkeley, Howard Hughes Medical Institute, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878); Lawrence Berkeley National Laboratory, Molecular Biophysics and Integrated Bioimaging Division, Berkeley, USA (GRID:grid.184769.5) (ISNI:0000 0001 2231 4551); University of California, Berkeley, Department of Chemistry, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878)