Designing Fidelity of CRISPR-Cas Endonucleases by Kinetic Insights

Exploring the Evolutionary Landscape with Targeted In Vivo Hypermutations

Directed evolution has revolutionized protein engineering by applying the principles of natural selection to the laboratory. However, traditional in vitro methods are quite labor-intensive, while common in vivo methods suffer from low mutation rates and high rates of off-target mutations. To address these issues, researchers have developed targeted mutagenesis tools for rapid in vivo evolution of biomolecules. In this review, we discuss recent in vivo hypermutation tools that enable rapid sampling of the vast evolutionary landscape, all while supporting simultaneous selection of the best proteins within living organisms. We focus on three main mechanisms of hypermutation: (i) orthogonal replication, which uses error-prone replication machinery to replicate the target gene with low fidelity; (ii) CRISPR-Cas-guided mutators, where mutagenic proteins are localized to virtually any user-defined loci; and (iii) transcription-coupled mutagenesis, a simple, yet elegant tool that exploits the innate processivity of orthogonal ribonucleic acid (RNA) polymerases to guide mutagenic proteins along the target gene during transcription. We highlight key advantages of these systems, as well as some clinically- and biotechnology-relevant applications. We discuss important limitations and how they could be addressed in the future to make hypermutation tools with broad mutational spectra and windows that span entire genes with minimal off-target effects.

Structure and evolution-guided design of minimal RNA-guided nucleases.

The design of RNA-guided nucleases with properties not limited by evolution can expand programmable genome-editing capabilities. However, generating diverse multidomain proteins with robust enzymatic properties remains challenging. Here, we use a protein design strategy that couples a structure-guided inverse-folding model with evolution-informed residue constraints to generate active, divergent variants of TnpB, a minimal CRISPR-Cas12-like nuclease, termed SynTnpBs. High-throughput screening of artificial intelligence-generated variants yielded editors that retained or exceeded wild-type activity in bacterial, plant, and human cells. Cryo-electron microscopy-based structure determination of the most divergent variant revealed stabilizing contacts in the RNA-DNA interfaces across conformations, demonstrating the design potential of this approach. Together, these results establish a strategy for creating non-natural RNA-guided nucleases and conformationally active nucleic acid binders, enlarging the designable protein space.

Rational and computation-assisted engineering of a compact and efficient StaCas9 genome editor

Optimized parameters for CRISPR-Cas9 interference library design.

CRISPR interference (CRISPRi) is a powerful technology for studying loss-of-function phenotypes, enabling transient and reversible control of gene expression without the introduction of double-stranded DNA breaks. The cost of conducting large-scale CRISPR screens necessitates the selection of effective and specific single-guide RNAs for the design of compact libraries. While several genome-wide CRISPRi-Cas9 libraries have been created, updates to transcript annotations, the generation of higher-resolution chromatin accessibility datasets, and the development of newer on-target prediction models motivate an updated CRISPRi library design approach. Here, we generate large CRISPRi datasets tiling essential and nonessential genes. We compare the performance of multiple KRAB domain systems, develop an updated CRISPRi-specific on-target scoring scheme, and quantitatively characterize off-target effects associated with seed-sequence patterns. We leverage these findings to design an optimized CRISPRi-Cas9 library, Katsano, and validate its performance with genome-wide viability screens.

CRISPR/Cas9-Mediated Site-Directed Mutagenesis of Genes in Klebsiella pneumoniae.

This protocol minimizes off-target editing, shortens experimental timelines, reduces screening workload, and provides a reliable platform for investigating resistance mechanisms, validating candidate genes, and supporting functional genomics studies in clinically relevant bacterial pathogens.

Evaluating high-fidelity CRISPR-Cas nucleases in nucleosomal contexts using a quantitative framework

It is demonstrated that local nucleosome sequence and structure profoundly influence Cas nuclease accessibility and specificity, with HIFIv1 emerging as the top-performing nuclease for nucleosomal targets, while evoSpCas9 excelled in exposed contexts.