bioRxivCell BiologyPreprint
MitoAtlas: a Domain-Resolved Spatial Map of the HumanMitochondrial Proteome
Jiwoong Kang, Shin Sh, Chulhwan S. KwakiD, Song-Yi LeeiD, Minkyo JungiD, Hanseul Lee, Myeong‐Gyun KangiD, Jiho Sim, Seung-Jae V. Lee, Ji Young MuniD, Jong‐Seo KimiD, Hyun‐Woo RheeiD
Abstract
Mitochondrial function depends on the precise sub-organellar localization and topological orientation of its proteome. However, mapping this architecture with domain-level precision across the double-membrane system has remained challenging. Here, we present MitoAtlas, a spatial systems biology resource built on SR-PL (super-resolution proximity labeling) that resolves the sub-mitochondrial architecture of 861 proteins at domain-level resolution. By deploying 42 spatially restricted APEX2 and BioID/BioID2 baits across mitochondrial compartments and cytosol in HEK293T-REx cells, we mapped 13,440 unique proximity-labeled sites. Integrating high-density spatial data with a machine-learning classification pipeline and AlphaFold structural modeling, we resolved membrane topologies for 196 transmembrane proteins and assigned sub-mitochondrial localizations to 160 previously unannotated mitochondrial proteins absent from MitoCarta3.0, including MINPP1 as an intermembrane space resident. Coupling bait-specific proximity labeling signatures with AlphaFold structure prediction and metabolite docking identified 47 protein-protein interactions, including the LETM1-Citrate Synthase complex, and 155 protein-metabolite interactions. MitoAtlas is available at mitoatlas.org as a domain-resolution spatial map of mitochondrial architecture and metabolism.
- organism: human
- assay: proteomics
- research focus: cell type annotation
- research focus: protein folding & dynamics
- approach: deep learning
- approach: statistical model
- Citations
- 1
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