Title: Using Molecular Grammar to Engineer Large Serine Recombinases

Abstract:  Large serine recombinases (LSRs) are mobile genetic element-derived enzymes capable of inserting kilobases of DNA at specific sequences known as attachment sites; these enzymes have emerged as promising tools for targeted genome engineering. Recently, a growing body of work has identified thousands of novel LSRs with their respective attachment sites and sought to optimize these enzymes, primarily through directed evolution (Durrant et al., 2023; Fanton et al., 2025; Pandey et al., 2025). Taking inspiration from the highly modular evolution of mobile genetic elements and previous work on recombinase domain swapping, we used these recently-discovered enzymes to examine the question of LSR modularity as it pertains to both the biology of these enzymes and their potential use as genetic tools (Botstein, 1980; Akopian et al., 2003; Farruggio & Calos, 2014). We designed a panel of LSR chimeras based on structural analysis and evaluated them in human cells to understand the impact that domain swapping has on the catalytic activity and sequence targeting of these enzymes. These chimeras demonstrated new combinations of phenotypes across several aspects of LSR function which suggested that they are imperfectly modular. To evaluate these findings with respect to a broader landscape of enzyme chimeras, we developed a sequence-agnostic protein domain screening method for higher-throughput testing of LSR chimeras in eukaryotic cells through the use of an intronic adaptor sequence. Using this method, we were able to find LSR chimeras of potential interest for use in human cells. These results were not able to be predicted with several metrics of sequence and structure similarity, indicating the screen is useful for characterizing protein chimeras. We show that LSR domains can be combined in new ways to generate diverse and functional chimeras and provide a new method to screen chimeric proteins; these findings introduce new lines of inquiry in recombinase biology and provide a complementary approach to engineer LSRs for use in gene editing and synthetic biology.

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