High-throughput colocalization pipeline quantifies efficacy of mitochondrial targeting signals across different protein types

Abstract

Efficient metabolic engineering and the development of mitochondrial therapeutics often rely upon the specific and strong import of foreign proteins into mitochondria. Fusing a protein to a mitochondria-bound signal peptide is a common method to localize proteins to mitochondria, but this strategy is not universally effective with particular proteins empirically failing to localize. To help overcome this barrier, this work develops a generalizable and open-source framework to design proteins for mitochondrial import and quantify their specific localization. By using a Python-based pipeline to quantitatively assess the colocalization of different proteins previously used for precise genome editing in a high-throughput manner, we reveal signal peptide-protein combinations that localize well in mitochondria and, more broadly, general trends about the overall reliability of commonly used mitochondrial targeting signals.