MitoEdit: A pipeline for optimizing mtDNA base editing and predicting bystander effects

Human mitochondrial DNA (mtDNA) mutations are causally implicated in maternally inherited mitochondrial respiratory disorders; however, the role of somatic mtDNA mutations in both late-onset chronic diseases and cancer remains less clear. Recent advances in mtDNA base editing technologies offer exciting opportunities to model and study these mutations. However, current approaches are hindered by the challenge of unintended bystander edits, which are often identified only through labor-intensive empirical testing, leading to inefficiencies in construct development. To address this limitation, we developed MitoEdit, an innovative computational tool designed to optimize mtDNA base editing by leveraging empirical base editor patterns. MitoEdit enables users to input DNA sequences in a simple text-based format, specify the target base position and define the desired modification. The tool outputs a list of candidate target windows, predicts the number and functional impact of bystander edits and provides flanking nucleotide sequences tailored for TALE (transcription activator-like effectors) array protein binding. In silico evaluations demonstrate that MitoEdit accurately predicts the majority of bystander edits, reducing the number of constructs that need to be tested empirically. By streamlining the design process, MitoEdit accelerates the development of mitochondrial base editing constructs, thereby facilitating functional studies and enabling faster discovery. Ultimately, MitoEdit has the potential to advance disease modeling and support the development of therapeutic strategies for mitochondrial-related disorders.