Engineering CRISPR-Based DNA Transversion Editing Technologies

Abstract

Adenine base editors (ABE) and cytosine base editors (CBE) can efficiently install A-to-G and C-to-T transition edits, respectively. However, until recently, the field lacked base editors to efficiently install C-to-G transversion edits in human cells in a programmable manner. We modified the existing CBE architectures to repurpose them into new C-to-G base editors (CGBEs). Our optimized CGBE induced C-to-G alterations with efficiencies as high as ~70%, particularly in AT- rich sequence contexts. CGBE exhibited a narrow editing window within the target site (positions 5-7 in the SpCas9 spacer sequence) but we also showed that incorporation of SpCas9 PAM recognition variants that can recognize NG or NGA PAMs into CGBE are functional, thereby expanding the range of targetable sites. CGBE displayed favorable Cas9-dependent DNA off-target profiles compared to the BE4max C-to-T base editor. We found in side-by-side comparison that CGBE achieves higher efficiencies of C-to-G edits compared with the recently described PE2 and PE3 prime editing technologies across different cell lines. CGBE described here expands the editing capabilities of the base editor platform for both research and therapeutic applications. Chapter 1 lays the foundational introduction into the field of genome editing, prominent tools engineered in chronological order, off-target genome editing, and platforms and methods to assess specificity profiles of genome editing tools. Chapter 2 describes the novel CRISPR-based C-to-G Base Editors (CGBE) that can efficiently install C-to-G transversion edits in human cells in context-dependent manner. Chapter 3 describes the efforts and attempt towards engineering novel CRISPR-based Guanine Base Editors (GBE) that can introduce G-to-T transversion mutations. Chapter 4 describes the efforts to integrate Tn5-based transposition system into the current frameworks of the gold standard in vitro and in vivo off-target methods to increase their scalability, sensitivity, and time-efficiency. Finally, this chapter describes a synthetic self-targeting in cellular off-target library that can be used to score precision or fidelity of CRISPR-based genome editing tools in a high-throughput manner. Chapter 5 discusses the big picture and future of the genome editing field, bigger research relationships, and our contribution to the current field with the work outlined in this thesis.