PAM-flexible genome editing with an engineered chimeric Cas9

Lin Zhao(Duke University), Sabrina Koseki(Duke University), Rachel A. Silverstein(Harvard University), Nadia Amrani(University of Massachusetts Chan Medical School), Christina Peng(McMaster University), Christian Kramme(Harvard University), Natasha Savic(McMaster University), Martin Pačesa(University of Zurich), Tomás Rodríguez(University of Massachusetts Chan Medical School), Teodora Stan(Duke University), Emma Tysinger(Duke University), Lauren Hong(Duke University), Vivian Yudistyra(Duke University), Manvitha Ponnapati(Massachusetts Institute of Technology), Joseph M. Jacobson(Massachusetts Institute of Technology), George M. Church(Harvard University), Noah Jakimo(Massachusetts Institute of Technology), Ray Truant(McMaster University), Martin Jínek(University of Zurich), Benjamin P. Kleinstiver(Harvard University), Erik J. Sontheimer(University of Massachusetts Chan Medical School), Pranam Chatterjee(Duke University)
Nature Communications
October 4, 2023
Cited by 56Open Access
Full Text

Abstract

CRISPR enzymes require a defined protospacer adjacent motif (PAM) flanking a guide RNA-programmed target site, limiting their sequence accessibility for robust genome editing applications. In this study, we recombine the PAM-interacting domain of SpRY, a broad-targeting Cas9 possessing an NRN > NYN (R = A or G, Y = C or T) PAM preference, with the N-terminus of Sc + +, a Cas9 with simultaneously broad, efficient, and accurate NNG editing capabilities, to generate a chimeric enzyme with highly flexible PAM preference: SpRYc. We demonstrate that SpRYc leverages properties of both enzymes to specifically edit diverse PAMs and disease-related loci for potential therapeutic applications. In total, the approaches to generate SpRYc, coupled with its robust flexibility, highlight the power of integrative protein design for Cas9 engineering and motivate downstream editing applications that require precise genomic positioning.


Related Papers

No related papers found

Powered by citation graph analysis