Co-fractionation–mass spectrometry to characterize native mitochondrial protein assemblies in mammalian neurons and brain

Mara Zilocchi, Matineh Rahmatbakhsh, Mohamed Taha Moutaoufik, Kirsten Broderick, Alla Gagarinova, Matthew Jessulat, Sadhna Phanse, Hiroyuki Aoki, Khaled A. Aly, Mohan Babu

Published: 2023-11-19 DOI: 10.1038/s41596-023-00901-z

mass spectrometry

proteomic sample preparation

mitochondrial protein assemblies

neuronal function

PPI networks

AI 解读

Supplementary information

Reporting Summary

Supplementary Data 1

High-quality mt protein interactions predicted in mouse brain.

Supplementary Data 2

Mt protein complexes derived from protein interactions in mouse brain.

Supplementary Data 3

Mt subunits of putative protein complexes enriched for GO annotations, human disorders and phenotypic aberrations in human disease.

Generation of mouse–human chimeric embryos

Genome-wide quantification of transcription factor binding at single-DNA-molecule resolution using methyl-transferase footprinting

Generation of CRISPR–Cas9-mediated genetic knockout human intestinal tissue–derived enteroid lines by lentivirus transduction and single-cell cloning

A puromycin-dependent activity-based sensing probe for histochemical staining of hydrogen peroxide in cells and animal tissues

Decoding personal biotic and abiotic airborne exposome

A clinically relevant model of focal embolic cerebral ischemia by thrombus and thrombolysis in rhesus monkeys

Bioengineering human intestinal mucosal grafts using patient-derived organoids, fibroblasts and scaffolds

Biomimetic tail-to-head terpene cyclizations using the resorcin[4]arene capsule catalyst

Neuroscience robotics for controlled induction and real-time assessment of hallucinations

Scanorama: integrating large and diverse single-cell transcriptomic datasets

Single-cell RNA sequencing (scRNA-seq)（单细胞RNA测序）

Data integration（数据集成）

Heterogeneity（异质性）

查看全部

Sections

Figures

References

Supplementary information

Walhout, A. J. & Vidal, M. Protein interaction maps for model organisms. Nat. Rev. Mol. Cell Biol. 2, 55–62 (2001).
Cho, N. H. et al. OpenCell: endogenous tagging for the cartography of human cellular organization. Science. 375, eabi6983 (2022).
Hu, L. Z. et al. EPIC: software toolkit for elution profile-based inference of protein complexes. Nat. Methods 16, 737–742 (2019).
Gupta, R., Karczewski, K. J., Howrigan, D., Neale, B. M. & Mootha, V. K. Human genetic analyses of organelles highlight the nucleus in age-related trait heritability. eLife 10, e68610 (2021).
Uher, R. The role of genetic variation in the causation of mental illness: an evolution-informed framework. Mol. Psychiatry 14, 1072–1082 (2009).
Pang, S. Y. et al. The interplay of aging, genetics and environmental factors in the pathogenesis of Parkinson’s disease. Transl. Neurodegener. 8, 23 (2019).
Kuzmanov, U. & Emili, A. Protein–protein interaction networks: probing disease mechanisms using model systems. Genome Med. 5, 37 (2013).
Hartwell, L. H., Hopfield, J. J., Leibler, S. & Murray, A. W. From molecular to modular cell biology. Nature 402, C47–C52 (1999).
Malty, R. H. et al. A map of human mitochondrial protein interactions linked to neurodegeneration reveals new mechanisms of redox homeostasis and NF-kappaB signaling. Cell Syst. 5, 1–14 (2017).
Pourhaghighi, R. et al. BraInMap elucidates the macromolecular connectivity landscape of mammalian brain. Cell Syst. 10, 333–350.e14 (2020).
Barabasi, A. L., Gulbahce, N. & Loscalzo, J. Network medicine: a network-based approach to human disease. Nat. Rev. Genet. 12, 56–68 (2011).
Babu, M. et al. Global landscape of cell envelope protein complexes in Escherichia coli. Nat. Biotechnol. 36, 103–112 (2018).
Babu, M. et al. Interaction landscape of membrane-protein complexes in Saccharomyces cerevisiae. Nature 489, 585–589 (2012).
Krogan, N. J. et al. Global landscape of protein complexes in the yeast Saccharomyces cerevisiae. Nature 440, 637–643 (2006).
Malovannaya, A. et al. Analysis of the human endogenous coregulator complexome. Cell 145, 787–799 (2011).
Huttlin, E. L. et al. Architecture of the human interactome defines protein communities and disease networks. Nature. 545, 505–509 (2017).
Huttlin, E. L. et al. The BioPlex network: a systematic exploration of the human interactome. Cell 162, 425–440 (2015).
Huttlin, E. L. et al. Dual proteome-scale networks reveal cell-specific remodeling of the human interactome. Cell 184, 3022–3040 (2021).
Guruharsha, K. G. et al. A protein complex network of Drosophila melanogaster. Cell 147, 690–703 (2011).
Cho, K. F. et al. Proximity labeling in mammalian cells with TurboID and split-TurboID. Nat. Protoc. 15, 3971–3999 (2020).
Havugimana, P. C. et al. A census of human soluble protein complexes. Cell 150, 1068–1081 (2012).
Bludau, I. et al. Complex-centric proteome profiling by SEC-SWATH-MS for the parallel detection of hundreds of protein complexes. Nat. Protoc. 15, 2341–2386 (2020).
Liu, X. et al. An AP-MS- and BioID-compatible MAC-tag enables comprehensive mapping of protein interactions and subcellular localizations. Nat. Commun. 9, 1188 (2018).
Hung, V. et al. Proteomic mapping of the human mitochondrial intermembrane space in live cells via ratiometric APEX tagging. Mol. Cell 55, 332–341 (2014).
Branon, T. C. et al. Efficient proximity labeling in living cells and organisms with TurboID. Nat. Biotechnol. 36, 880–887 (2018).
Go, C. D. et al. A proximity-dependent biotinylation map of a human cell. Nature 595, 120–124 (2021).
Samavarchi-Tehrani, P., Samson, R. & Gingras, A. C. Proximity dependent biotinylation: key enzymes and adaptation to proteomics approaches. Mol. Cell Proteomics 19, 757–773 (2020).
Wan, C. et al. Panorama of ancient metazoan macromolecular complexes. Nature 525, 339–344 (2015).
Skinnider, M. A. et al. An atlas of protein–protein interactions across mouse tissues. Cell 184, 4073–4089.e17 (2021).
Skinnider, M. A. & Foster, L. J. Meta-analysis defines principles for the design and analysis of co-fractionation mass spectrometry experiments. Nat. Methods 18, 806–815 (2021).
Lee, Y. C. et al. Impact of detergents on membrane protein complex isolation. J. Proteome Res. 17, 348–358 (2018).
Magistretti, P. J. & Allaman, I. A cellular perspective on brain energy metabolism and functional imaging. Neuron 86, 883–901 (2015).
Picard, M. & McEwen, B. S. Mitochondria impact brain function and cognition. Proc. Natl Acad. Sci. USA 111, 7–8 (2014).
Aly, K. A., Moutaoufik, M. T., Phanse, S., Zhang, Q. & Babu, M. From fuzziness to precision medicine: on the rapidly evolving proteomics with implications in mitochondrial connectivity to rare human disease. iScience 24, 102030 (2021).
Norat, P. et al. Mitochondrial dysfunction in neurological disorders: exploring mitochondrial transplantation. NPJ Regen. Med. 5, 22 (2020).
Zilocchi, M., Broderick, K., Phanse, S., Aly, K. A. & Babu, M. Mitochondria under the spotlight: on the implications of mitochondrial dysfunction and its connectivity to neuropsychiatric disorders. Comput. Struct. Biotechnol. J 18, 2535–2546 (2020).
DiMauro, S. & Schon, E. A. Mitochondrial disorders in the nervous system. Annu. Rev. Neurosci. 31, 91–123 (2008).
Floyd, B. J. et al. Mitochondrial protein interaction mapping identifies regulators of respiratory chain function. Mol. Cell 63, 621–632 (2016).
Moutaoufik, M. T. et al. Rewiring of the human mitochondrial interactome during neuronal reprogramming reveals regulators of the respirasome and neurogenesis. iScience 19, 1114–1132 (2019).
Antonicka, H. et al. A high-density human mitochondrial proximity interaction network. Cell Metab. 32, 479–497.e9 (2020).
Rath, S. et al. MitoCarta3.0: an updated mitochondrial proteome now with sub-organelle localization and pathway annotations. Nucleic Acids Res. 49, D1541–D1547 (2021).
Salas, D., Stacey, R. G., Akinlaja, M. & Foster, L. J. Next-generation interactomics: considerations for the use of co-elution to measure protein interaction networks. Mol. Cell. Proteomics 19, 1–10 (2020).
Scott, N. E. et al. Interactome disassembly during apoptosis occurs independent of caspase cleavage. Mol. Syst. Biol. 13, 906 (2017).
Gonzalez-Franquesa, A. et al. Mass-spectrometry-based proteomics reveals mitochondrial supercomplexome plasticity. Cell Rep. 35, 109180 (2021).
Hevler, J. F. et al. Selective cross-linking of coinciding protein assemblies by in-gel cross-linking mass spectrometry. EMBO J. 40, e106174 (2021).
Heusel, M. et al. Complex-centric proteome profiling by SEC-SWATH-MS. Mol. Syst. Biol. 15, e8438 (2019).
Kristensen, A. R., Gsponer, J. & Foster, L. J. A high-throughput approach for measuring temporal changes in the interactome. Nat. Methods 9, 907–909 (2012).
O’Meara, T. R. et al. Global proteomic analyses define an environmentally contingent Hsp90 interactome and reveal chaperone-dependent regulation of stress granule proteins and the R2TP complex in a fungal pathogen. PLoS Biol. 17, e3000358 (2019).
Stacey, R. G., Skinnider, M. A., Scott, N. E. & Foster, L. J. A rapid and accurate approach for prediction of interactomes from co-elution data (PrInCE). BMC Bioinformatics 18, 457 (2017).
Cogliati, S., Herranz, F., Ruiz-Cabello, J. & Enriquez, J. A. Digitonin concentration is determinant for mitochondrial supercomplexes analysis by BlueNative page. Biochim. Biophys. Acta Bioenerg. 1862, 148332 (2021).
Ford, H. C. et al. Towards a molecular mechanism underlying mitochondrial protein import through the TOM and TIM23 complexes. eLife 11, e75426 (2022).
Liao, P. C., Bergamini, C., Fato, R., Pon, L. A. & Pallotti, F. Isolation of mitochondria from cells and tissues. Methods Cell. Biol. 155, 3–31 (2020).
Lanza, I. R. & Nair, K. S. Functional assessment of isolated mitochondria in vitro. Methods Enzymol. 457, 349–372 (2009).
Wettmarshausen, J. & Perocchi, F. Isolation of functional mitochondria from cultured cells and mouse tissues. Methods Mol. Biol. 1567, 15–32 (2017).
Kunji, E. R., Harding, M., Butler, P. J. & Akamine, P. Determination of the molecular mass and dimensions of membrane proteins by size exclusion chromatography. Methods 46, 62–72 (2008).
Havugimana, P. C., Wong, P. & Emili, A. Improved proteomic discovery by sample pre-fractionation using dual-column ion-exchange high performance liquid chromatography. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 847, 54–61 (2007).
Li, J. et al. TMTpro-18plex: the expanded and complete set of TMTpro reagents for sample multiplexing. J. Proteome Res. 20, 2964–2972 (2021).
Li, J. et al. TMTpro reagents: a set of isobaric labeling mass tags enables simultaneous proteome-wide measurements across 16 samples. Nat. Methods 17, 399–404 (2020).
McWhite, C. D. et al. A pan-plant protein complex map reveals deep conservation and novel assemblies. Cell 181, 460–474.e14 (2020).
Kislinger, T. et al. PRISM, a generic large scale proteomic investigation strategy for mammals. Mol. Cell. Proteomics 2, 96–106 (2003).
Kwon, T., Choi, H., Vogel, C., Nesvizhskii, A. I. & Marcotte, E. M. Msblender: a probabilistic approach for integrating peptide identifications from multiple database search engines. J. Proteome Res. 10, 2949–2958 (2011).
Choi, H., Glatter, T., Gstaiger, M. & Nesvizhskii, A. I. SAINT-MS1: protein–protein interaction scoring using label-free intensity data in affinity purification–mass spectrometry experiments. J. Proteome Res. 11, 2619–2624 (2012).
Gingras, A. C., Gstaiger, M., Raught, B. & Aebersold, R. Analysis of protein complexes using mass spectrometry. Nat. Rev. Mol. Cell. Biol. 8, 645–654 (2007).
Giurgiu, M. et al. CORUM: the comprehensive resource of mammalian protein complexes-2019. Nucleic Acids Res. 47, D559–D563 (2019).
Zhang, T. & Wong, G. Gene expression data analysis using Hellinger correlation in weighted gene co-expression networks (WGCNA). Comput. Struct. Biotechnol. J 20, 3851–3863 (2022).
Song, L., Langfelder, P. & Horvath, S. Comparison of co-expression measures: mutual information, correlation, and model based indices. BMC Bioinformatics 13, 328 (2012).
Pang, C. N. I. et al. Analytical guidelines for co-fractionation mass spectrometry obtained through global profiling of gold standard saccharomyces cerevisiae protein complexes. Mol. Cell. Proteomics 19, 1876–1895 (2020).
Correia, F. B., Coelho, E. D., Oliveira, J. L. & Arrais, J. P. Handling noise in protein interaction networks. BioMed Res. Int. 2019, 8984248 (2019).
Orre, L. M. et al. SubCellBarCode: Proteome-wide Mapping of Protein Localization and Relocalization. Mol. Cell 73, 166–182.e7 (2019).
Nepusz, T., Yu, H. & Paccanaro, A. Detecting overlapping protein complexes in protein–protein interaction networks. Nat. Methods 9, 471–472 (2012).
Leitner, A. et al. Probing native protein structures by chemical cross-linking, mass spectrometry, and bioinformatics. Mol. Cell. Proteomics 9, 1634–1649 (2010).
McWhite, C. D. et al. Co-fractionation/mass spectrometry to identify protein complexes. STAR Protoc. 2, 100370 (2021).
Hutchinson-Bunch, C. et al. Assessment of TMT labeling efficiency in large-scale quantitative proteomics: the critical effect of sample pH. ACS Omega 6, 12660–12666 (2021).
Skinnider, M. A., Stacey, R. G. & Foster, L. J. Genomic data integration systematically biases interactome mapping. PLoS Comput. Biol. 14, e1006474 (2018).
Li, Z. & Graham, B. H. Measurement of mitochondrial oxygen consumption using a Clark electrode. Methods Mol. Biol. 837, 63–72 (2012).
Li, T. et al. A scored human protein–protein interaction network to catalyze genomic interpretation. Nat. Methods 14, 61–64 (2017).
Pan, J. et al. Interrogation of mammalian protein complex structure, function, and membership using genome-scale fitness screens. Cell Syst. 6, 555–568.e7 (2018).
Pagliarini, D. J. et al. A mitochondrial protein compendium elucidates complex I disease biology. Cell 134, 112–123 (2008).
Le Vasseur, M. et al. Genome-wide CRISPRi screening identifies OCIAD1 as a prohibitin client and regulatory determinant of mitochondrial complex III assembly in human cells. eLife 10, e67624 (2021).
Shetty, D. K., Kalamkar, K. P. & Inamdar, M. S. OCIAD1 controls electron transport chain complex I activity to regulate energy metabolism in human pluripotent stem cells. Stem Cell Rep. 11, 128–141 (2018).
Guarani, V. et al. TIMMDC1/C3orf1 functions as a membrane-embedded mitochondrial complex I assembly factor through association with the MCIA complex. Mol. Cell Biol. 34, 847–861 (2014).
Nazli, A. et al. A mutation in the TMEM65 gene results in mitochondrial myopathy with severe neurological manifestations. Eur. J. Hum. Genet. 25, 744–751 (2017).