A Tale of Two Strategies: Evolving and Engineering Biology Across Scales

Engineering biology at the scale of pathways and genomes requires two core capabilities: the precision to install defined changes and the capacity to generate diversity across large genetic elements. In this thesis, we developed complementary strategies that together span this spectrum. First, we introduced SCOPE (Selective Conjugation-mediated Optimization and Passaging for Evolution), a conjugation-based evolution platform that enables continuous diversification and passaging of replicons ranging from 10 kb to over 500 kb. Extending this approach, SCOPE established genome-to-genome “hopping” by evolving CRISPR associated transposase based insertion systems as integrated units, yielding variants with up to 30-fold increased integration efficiency across cargo sizes ranging from 10 kb to 1 Mb. These results illustrate that entire polygenic systems, including genome-editing machines, can be diversified and optimized in vivo. Second, we developed an optimized prime editing framework for E.coli that achieves editing efficiencies above 95% across diverse genomic loci and edit types. Additional intron-based strategies enabled context-dependent template restoration, and together these layers established robust precision editing across diverse loci. Building on this foundation, we created PEACE (Prime Editing Additive Conjugative Engineering), which couples prime editing and conjugative transfer with site-specific recombination to achieve scarless installation of megabase-scale DNA segments across genera. This provides a continuum of editing capabilities ranging from single-nucleotide manipulations to large-scale genomic integrations. Together, SCOPE and PEACE address two longstanding bottlenecks in microbial genome engineering: the inability to efficiently diversify large genetic elements, and the lack of scalable tools for precise genomic integration. The results presented here suggest that these need not remain fundamental limitations. As the complexity of engineering targets grows, from single enzymes to entire biosynthetic pathways to multi-gene regulatory networks, the field will increasingly require tools that operate at matching scales. This thesis provides a foundation for that shift, offering approaches that are not merely incremental improvements but qualitatively different in the size and complexity of genetic systems they can access.