Parallel engineering and activity profiling of a base editor system.

Selecting the most suitable existing base editors and engineering new variants for installing specific base conversions with maximal efficiency and minimal undesired edits are pivotal for precise genome editing applications. Here, we present a platform for creating and analyzing a library of engineered base editor variants to enable head-to-head evaluation of their editing performance at scale. Our comprehensive comparison provides quantitative measures on each variant's editing efficiency, purity, motif preference, and bias in generating single and multiple base conversions, while uncovering undesired higher indel generation rate and noncanonical base conversion for some of the existing base editors. In addition to engineering the base editor protein, we further applied this platform to investigate a hitherto underexplored engineering route and created guide RNA scaffold variants that augment the editor's base-editing activity. With the unknown performance and compatibility of the growing number of engineered parts including deaminase, CRISPR-Cas enzyme, and guide RNA scaffold variants for assembling the expanding collection of base editor systems, our platform addresses the unmet need for an unbiased, scalable method to benchmark their editing outcomes and accelerate the engineering of next-generation precise genome editors.

High-Throughput Protein Engineering by Massively Parallel Combinatorial Mutagenesis.

Exploring how combinatorial mutations can be combined to optimize protein functions is important to guide protein engineering. Given the vast combinatorial space of changing multiple amino acids, identifying the top-performing variants from a large number of mutants might not be possible without a high-throughput gene assembly and screening strategy. Here we describe the CombiSEAL platform, a strategy that allows for modularization of any protein sequence into multiple segments for mutagenesis and barcoding, and seamless single-pot ligations of different segments to generate a library of combination mutants linked with concatenated barcodes at one end. By reading the barcodes using next-generation sequencing, activities of each protein variant during the protein selection process can be easily tracked in a high-throughput manner. CombiSEAL not only allows the identification of better protein variants but also enables the systematic analyses to distinguish the beneficial, deleterious, and neutral effects of combining different mutations on protein functions.