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Systematic discovery of recombinases for efficient integration of large DNA sequences into the human genome.


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.

SUBMITTER: Durrant MG 

PROVIDER: S-EPMC10083194 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature

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Systematic discovery of recombinases for efficient integration of large DNA sequences into the human genome.

Durrant Matthew G MG   Fanton Alison A   Tycko Josh J   Hinks Michaela M   Chandrasekaran Sita S SS   Perry Nicholas T NT   Schaepe Julia J   Du Peter P PP   Lotfy Peter P   Bassik Michael C MC   Bintu Lacramioara L   Bhatt Ami S AS   Hsu Patrick D PD  

Nature biotechnology 20221010 4


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 si  ...[more]

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