Somatic mitochon­dr­ial DNA (mtDNA) mutations are associ­ated with a wide range of human disor­ders, yet it has been diffi­cult to reliably estab­lish mitochon­dr­ial genotype-pheno­type associ­a­tions. There­fore, we aim to integrate metabolic profil­ing readouts with single-cell multi-omics sequenc­ing techniques to charac­terise the conse­quences of patho­genic mtDNA mutations and increased mitochon­dr­ial mutational burden at the cellu­lar and genomic level.

Mitochon­dria carry their own multi-copy genome and are central to cellu­lar metabolic processes. Germline inher­ited mutations in mitochon­dr­ial DNA (mtDNA) have been associ­ated with differ­ent metabolic disor­ders charac­terised by a wide variety of pheno­types (known as mitochon­dri­opathies). Likewise, somatic mtDNA mutations accumu­late with age and this increased mutational burden can lead to age-related mitochon­dr­ial dysfunc­tion. While it is well appre­ci­ated that mutations in mtDNA can impact cellu­lar metab­o­lism, the mecha­nisms of molec­u­lar adapta­tion are less well under­stood and may further be cell-type specific. There­fore, we aim to integrate metabolic profil­ing readouts with single-cell multi-omics sequenc­ing techniques to charac­terise the conse­quences of mtDNA mutations on cellu­lar metab­o­lism and gene regula­tion. We envision these efforts to signif­i­cantly aid our under­stand­ing of altered cellu­lar states due to mtDNA mutation related dysfunc­tion that has been broadly impli­cated to affect cellu­lar function in for example cancer and ageing contexts.