Engineering High-Precision CRISPR-Cas9 Nuclease and Base Editor Technologies

Abstract

The human genome, comprising approximately three billion nucleotides separated across 23 chromosomes, contains a vast amount of sequence space encoding instructions for the production of RNA and protein molecules that make up the functional components of the cell. Some changes in these genetic sequences produce phenotypic changes in organisms, such as genetically-heritable diseases in humans. Genome editing, loosely defined as creating targeted, sequence-specific changes in a desired cellular genome, promises to enable the correction of many disease-causing mutations. To enable these technologies to be used to their full potentials in research and therapeutic settings, it is necessary to engineer genome editing technologies with extreme specificity and fidelity to the desired target sequence compared to all other possible sequences in the target genome. This work focuses on engineering CRISPR-Cas9 RNA-guided nucleases and base editor technologies to enhance their precision and genome-wide specificities, thus enabling researchers to more effectively use these tools to study fundamental biological principles or to translate these technologies into clinical settings. Chapter 1 introduces relevant history of the genetic engineering field, including contemporary genome editing platforms such as CRISPR-Cas9 nuclease and base editor platforms. Chapter 2 describes efforts towards engineering CRISPR-Cas9 systems that are dependent on specific epigenetic contexts adjacent to their target site in order to successfully induce DNA double strand breaks, adding additional layers of complexity and regulation of activity to the CRISPR-Cas9 platform. Chapter 3 focuses on leveraging natural cytidine deaminase protein diversity, coupled with standard protein engineering techniques, to create base editor proteins able to programmably edit single nucleotides at desired on-target sites based on the sequence context of a given target base. The technology described in this chapter greatly enhances the ability of the base editor platform to correct many disease-causing genomic SNPs with fewer or no bystander nucleotide editing events at the on-target site, and greatly reduces the rates of off-target editing compared to the original base editor platform. Importantly, we demonstrate that this technology can be used to more efficiently and precisely correct a disease-causing mutation in a model cell line and in erythroid precursor cells derived from a patient bearing this mutation.