Systematic discovery of recombinases for efficient integration of large DNA sequences into the human genome
Matthew G. Durranta b c, Alison Fantonb d, Josh Tyckoc, Michaela M. Hinkse, Sita S. Chandrasekaranb d, Nicholas Thomas Perryb d, Julia M. Schaepee, Peter P. Duc f, Peter Lotfyg, Michael Cory Bassikc h✉, Lacramioara Bintue i✉
- aArc Institute, Palo Alto, CA, USA
- bDepartment of Bioengineering, University of California, Berkeley, Berkeley, CA, USA
- cDepartment of Genetics, Stanford University, Stanford, CA, USA
- dUniversity of California, Berkeley-University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA, USA
- eDepartment of Bioengineering, Stanford University, Stanford, CA, USA
- fCancer Biology Program, Stanford University, Stanford, CA, USA
- gLaboratory of Molecular and Cell Biology, Salk Institute for Biological Studies, La Jolla, CA, USA
- hDepartment of Genetics, Stanford University, Stanford, CA, USA. bassik@stanford.edu
- iDepartment of Bioengineering, Stanford University, Stanford, CA, USA. lbintu@stanford.edu
- jDepartment of Genetics, Stanford University, Stanford, CA, USA. asbhatt@stanford.edu
- kDepartment of Medicine (Hematology), Stanford University, Stanford, CA, USA. asbhatt@stanford.edu
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Abstract
Abstract Large serine recombinases (LSRs) are DNA integrases that facilitate the site-specific integration of mobile genetic elements into bacterial genomes. Only a few LSRs, such as Bxb1 and PhiC31, have been characterized to date, with limited efficiency as tools for DNA integration in human cells. In this study, we developed a computational approach to identify thousands of LSRs and their DNA attachment sites, expanding known LSR diversity by >100-fold and enabling the prediction of their insertion site specificities. We tested their recombination activity in human cells, classifying them as landing pad, genome-targeting or multi-targeting LSRs. Overall, we achieved up to seven-fold higher recombination than Bxb1 and genome integration efficiencies of 40–75% with cargo sizes over 7 kb. We also demonstrate virus-free, direct integration of plasmid or amplicon libraries for improved functional genomics applications. This systematic discovery of recombinases directly from microbial sequencing data provides a resource of over 60 LSRs experimentally characterized in human cells for large-payload genome insertion without exposed DNA double-stranded breaks.
TL;DRA computational approach is developed to identify thousands of large serine recombinases and their DNA attachment sites, expanding known LSR diversity by >100-fold and enabling the prediction of their insertion site specificities, and provides a resource of over 60 LSRs experimentally characterized in human cells for large-payload genome insertion without exposed DNA double-stranded breaks. (Semantic Scholar)