High-throughput colocalization pipeline quantifies efficacy of mitochondrial targeting signals across different
Sierra K Lear1,2, Jose A Nunez3, Seth L Shipman1,4,5
1Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, USA.
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.
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