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Updated: Jun 8, 2025

Author Spotlight: Two-Step Tag-Free Isolation of Mitochondria for Improved Protein Discovery and Quantification
Published on: June 2, 2023
Mass spectrometry-based proteomics to study mutants and interactomes of mitochondrial translocation proteins
Silke Oeljeklaus1, Lakshita Sharma1, Julian Bender1
1Biochemistry II, Theodor Boveri-Institute, Biocenter, University of Würzburg, Würzburg, Germany.
Abstract:
The multiple functions of mitochondria are governed by their proteome comprising 1000-1500 proteins depending on the organism. However, only few proteins are synthesized inside mitochondria, whereas most are "born" outside mitochondria. To reach their destined location, these mitochondrial proteins follow specific import routes established by a mitochondrial translocase network. A detailed understanding of the role and interplay of the different translocases is imperative to understand mitochondrial biology and how mitochondria are integrated into the cellular network. Mass spectrometry (MS) proved to be effective to study the translocase network regarding composition, functions, interplay, and cellular responses evoked by dysfunction. In this chapter, we provide protocols tailored to MS-enabled functional analysis of mutants and interactomes of mitochondrial translocation proteins. In the first part, we exemplify the MS-based proteomics analysis of translocation mutants for delineating the human mitochondrial importome following depletion of the central translocation protein TOMM40. The protocol comprises metabolic stable isotope labeling, TOMM40 knockdown, preparation of mitochondrial fractions, and sample preparation for liquid chromatography (LC)-MS. For deep MS analysis, prefractionation of peptide mixtures by high pH reversed-phase LC is described. In the second part, we outline an affinity purification MS approach to reveal the association of an orphaned protein with the translocase TIM23. The protocol covers FLAG-tag affinity purification of protein complexes from mitochondrial fractions and downstream sample preparation for interactome analysis. In the last unifying part, we describe methods for LC-MS, data processing, statistical analysis and visualization of quantitative MS data, and provide a Python code for effective, customizable analysis.
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