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• W2972039360 abstract "•Rewiring of mitochondrial (mt) protein interaction network in distinct cell states•Dramatic changes in site-specific phosphorylation during neuronal differentiation•C20orf24 is a respirasome assembly factor depleted in patients deficient in CIV•NENF binding with DJ-1/PINK1 promotes neurotrophic activity and neuronal survival Mitochondrial protein (MP) assemblies undergo alterations during neurogenesis, a complex process vital in brain homeostasis and disease. Yet which MP assemblies remodel during differentiation remains unclear. Here, using mass spectrometry-based co-fractionation profiles and phosphoproteomics, we generated mitochondrial interaction maps of human pluripotent embryonal carcinoma stem cells and differentiated neuronal-like cells, which presented as two discrete cell populations by single-cell RNA sequencing. The resulting networks, encompassing 6,442 high-quality associations among 600 MPs, revealed widespread changes in mitochondrial interactions and site-specific phosphorylation during neuronal differentiation. By leveraging the networks, we show the orphan C20orf24 as a respirasome assembly factor whose disruption markedly reduces respiratory chain activity in patients deficient in complex IV. We also find that a heme-containing neurotrophic factor, neuron-derived neurotrophic factor [NENF], couples with Parkinson disease-related proteins to promote neurotrophic activity. Our results provide insights into the dynamic reorganization of mitochondrial networks during neuronal differentiation and highlights mechanisms for MPs in respirasome, neuronal function, and mitochondrial diseases. Mitochondrial protein (MP) assemblies undergo alterations during neurogenesis, a complex process vital in brain homeostasis and disease. Yet which MP assemblies remodel during differentiation remains unclear. Here, using mass spectrometry-based co-fractionation profiles and phosphoproteomics, we generated mitochondrial interaction maps of human pluripotent embryonal carcinoma stem cells and differentiated neuronal-like cells, which presented as two discrete cell populations by single-cell RNA sequencing. The resulting networks, encompassing 6,442 high-quality associations among 600 MPs, revealed widespread changes in mitochondrial interactions and site-specific phosphorylation during neuronal differentiation. By leveraging the networks, we show the orphan C20orf24 as a respirasome assembly factor whose disruption markedly reduces respiratory chain activity in patients deficient in complex IV. We also find that a heme-containing neurotrophic factor, neuron-derived neurotrophic factor [NENF], couples with Parkinson disease-related proteins to promote neurotrophic activity. Our results provide insights into the dynamic reorganization of mitochondrial networks during neuronal differentiation and highlights mechanisms for MPs in respirasome, neuronal function, and mitochondrial diseases. Mitochondria (mt) are dynamic organelles crucial for a number of essential cellular functions in neurons, including oxidative phosphorylation (OXPHOS), neuronal differentiation, and synapse formation (Nunnari and Suomalainen, 2012Nunnari J. Suomalainen A. Mitochondria: in sickness and in health.Cell. 2012; 148: 1145-1159Abstract Full Text Full Text PDF PubMed Scopus (1846) Google Scholar). Disruptions of mt functions can cause neuronal degeneration, leading to rare inherited metabolic (e.g., complex IV [CIV] or cytochrome c oxidase deficiency) or neurodegenerative (e.g., Parkinson disease [PD]) disorders (DiMauro and Schon, 2008DiMauro S. Schon E.A. Mitochondrial disorders in the nervous system.Annu. Rev. Neurosci. 2008; 31: 91-123Crossref PubMed Scopus (434) Google Scholar). In normally functioning neurons, mt are crucial for neurogenesis, a dynamic process in which neural stem cells differentiate into neurons via a neurogenic gene expression program (Khacho et al., 2018Khacho M. Harris R. Slack R.S. Mitochondria as central regulators of neural stem cell fate and cognitive function.Nat. Rev. Neurosci. 2018; 20: 34-48Crossref Scopus (147) Google Scholar). Conversely, the decline in neurogenesis leads to cognitive impairment associated with various degenerative disorders, and impaired mt may contribute to such deterioration (Fernandez et al., 2019Fernandez A. Meechan D.W. Karpinski B.A. Paronett E.M. Bryan C.A. Rutz H.L. Radin E.A. Lubin N. Bonner E.R. Popratiloff A. et al.Mitochondrial dysfunction leads to cortical under-connectivity and cognitive impairment.Neuron. 2019; 102: 1127-1142.e3Abstract Full Text Full Text PDF PubMed Scopus (66) Google Scholar, Khacho et al., 2018Khacho M. Harris R. Slack R.S. Mitochondria as central regulators of neural stem cell fate and cognitive function.Nat. Rev. Neurosci. 2018; 20: 34-48Crossref Scopus (147) Google Scholar); however, the underlying mechanisms triggering these changes are poorly understood. Global changes in gene expression (Busskamp et al., 2014Busskamp V. Lewis N.E. Guye P. Ng A.H. Shipman S.L. Byrne S.M. Sanjana N.E. Murn J. Li Y. Li S. et al.Rapid neurogenesis through transcriptional activation in human stem cells.Mol. Syst. Biol. 2014; 10: 760Crossref PubMed Scopus (133) Google Scholar) and proteome dynamics (Frese et al., 2017Frese C.K. Mikhaylova M. Stucchi R. Gautier V. Liu Q. Mohammed S. Heck A.J. Altelaar A.F. Hoogenraad C.C. Quantitative map of proteome dynamics during neuronal differentiation.Cell Rep. 2017; 18: 1527-1542Abstract Full Text Full Text PDF PubMed Scopus (50) Google Scholar) have been observed across various stages of neuronal development in multiple cell types. Large-scale protein-protein interaction (PPI) networks generated by several proteomic methods (Hein et al., 2015Hein M.Y. Hubner N.C. Poser I. Cox J. Nagaraj N. Toyoda Y. Gak I.A. Weisswange I. Mansfeld J. Buchholz F. et al.A human interactome in three quantitative dimensions organized by stoichiometries and abundances.Cell. 2015; 163: 712-723Abstract Full Text Full Text PDF PubMed Scopus (757) Google Scholar, Huttlin et al., 2017Huttlin E.L. Bruckner R.J. Paulo J.A. Cannon J.R. Ting L. Baltier K. Colby G. Gebreab F. Gygi M.P. Parzen H. et al.Architecture of the human interactome defines protein communities and disease networks.Nature. 2017; 545: 505-509Crossref PubMed Scopus (800) Google Scholar, Wan et al., 2015Wan C. Borgeson B. Phanse S. Tu F. Drew K. Clark G. Xiong X. Kagan O. Kwan J. Bezginov A. et al.Panorama of ancient metazoan macromolecular complexes.Nature. 2015; 525: 339-344Crossref PubMed Scopus (317) Google Scholar) from whole cell, nuclear, or cytosolic extracts have provided a glimpse of the stably associated human complexome in non-neuronal cells. Yet, the physiological functions of mt proteins (MPs), as well as the organization of the full repertoire of cell-context-dependent, native human mtPPIs and resulting multiprotein complexes (MPCs) before and after neuronal differentiation are far from complete. Accumulating evidence suggests that post-translational modifications (PTMs), including phosphorylation or dephosphorylation, regulate many aspects of mt processes (Grimsrud et al., 2012Grimsrud P.A. Carson J.J. Hebert A.S. Hubler S.L. Niemi N.M. Bailey D.J. Jochem A. Stapleton D.S. Keller M.P. Westphall M.S. et al.A quantitative map of the liver mitochondrial phosphoproteome reveals posttranslational control of ketogenesis.Cell Metab. 2012; 16: 672-683Abstract Full Text Full Text PDF PubMed Scopus (116) Google Scholar). Mass spectrometry (MS)-based proteomics has allowed the identification of the human mt proteome that is phosphorylated, as well as mt kinases that phosphorylate a number of different cellular protein substrates, and enabled the monitoring of changes in the phosphoproteome of human embryonic stem cells upon differentiation (Grimsrud et al., 2012Grimsrud P.A. Carson J.J. Hebert A.S. Hubler S.L. Niemi N.M. Bailey D.J. Jochem A. Stapleton D.S. Keller M.P. Westphall M.S. et al.A quantitative map of the liver mitochondrial phosphoproteome reveals posttranslational control of ketogenesis.Cell Metab. 2012; 16: 672-683Abstract Full Text Full Text PDF PubMed Scopus (116) Google Scholar, Van Hoof et al., 2009Van Hoof D. Munoz J. Braam S.R. Pinkse M.W. Linding R. Heck A.J. Mummery C.L. Krijgsveld J. Phosphorylation dynamics during early differentiation of human embryonic stem cells.Cell Stem Cell. 2009; 5: 214-226Abstract Full Text Full Text PDF PubMed Scopus (271) Google Scholar). Although these efforts in tissues and cell lines have enhanced our knowledge of the regulation of human proteins by PTMs, much remains to be learned about alterations in phosphorylation during neuronal differentiation. This includes how phosphorylation sites are distributed within MP complexes and which sites are targeted by mt kinases during neuronal differentiation. Here, we address these gaps by performing an extensive biochemical fractionation (BF) with in-depth MS profiling in both mt extracts of cultured human NTera2 embryonal carcinoma stem cells (ECSCs or undifferentiated state) and retinoic acid (RA)-induced differentiated neuronal-like cells (DNLCs), two cell populations differentiable using single-cell RNA sequencing (scRNA-seq). The resulting network reveals that the majority of observed native mtPPIs were previously unreported and undergo considerable changes upon differentiation. Also, phosphoproteome characterization in the mt extracts from ECSCs and DNLCs shows a sizable fraction of MPs to be phosphorylated at serine residues and that the activity of mt pyruvate dehydrogenase E1α 2 subunit (PDHA2), phosphorylated on S291/S293 residues in ECSCs, is increased in DNLCs via dephosphorylation. By leveraging the high-quality mtPPI network, we provide evidence that the orphan MP C20orf24, which has a less frequent heterozygous 3′ UTR variant in patients with mt respiratory chain deficiencies, functions as an assembly factor, causing a marked reduction in respirasome levels when disrupted. As well, we establish that the binding between a neuron-derived neurotrophic factor (NENF) and the PD-associated proteins (DJ-1/PARK7, PINK1), required for loading heme from mt, enhances neurotrophic activity to promote neuronal survival. Overall, this experimentally derived catalog of human mtPPIs assembled during the reprogramming of ECSCs to DNLCs will enhance our understanding of the functional significance of the mt in the intricate process of human neurogenesis and in the manifestation of mt diseases. To establish a map of native human mt macromolecular assemblies involved in neurogenesis, we applied our BF/MS strategy (Havugimana et al., 2012Havugimana P.C. Hart G.T. Nepusz T. Yang H. Turinsky A.L. Li Z. Wang P.I. Boutz D.R. Fong V. Phanse S. et al.A census of human soluble protein complexes.Cell. 2012; 150: 1068-1081Abstract Full Text Full Text PDF PubMed Scopus (588) Google Scholar) to mt extracts isolated from chemically cross-linked (i.e., dithiobis-succinimidyl propionate, which allows identification of weak or transient PPIs; Malty et al., 2017Malty R.H. Aoki H. Kumar A. Phanse S. Amin S. Zhang Q. Minic Z. Goebels F. Musso G. Wu Z. et al.A map of human mitochondrial protein interactions linked to neurodegeneration reveals new mechanisms of redox homeostasis and NF-kappaB signaling.Cell Syst. 2017; 5: 1-14PubMed Google Scholar) cultures of NTera2 ECSCs and DNLCs (Figure 1A ). This human cell line was chosen because it is widely used in the study of neurogenesis and neurodegenerative disorders as an attractive progenitor that retains many human embryonic stem cell features, with the capacity to generate DNLCs (Gonzalez-Burguera et al., 2016Gonzalez-Burguera I. Ricobaraza A. Aretxabala X. Barrondo S. Garcia del Cano G. Lopez de Jesus M. Salles J. Highly efficient generation of glutamatergic/cholinergic NT2-derived postmitotic human neurons by short-term treatment with the nucleoside analogue cytosine beta-D-arabinofuranoside.Stem Cell Res. 2016; 16: 541-551Crossref PubMed Scopus (7) Google Scholar). Besides confirming the expression of stemness and/or neuronal markers in ECSCs and DNLCs by immunoblotting (Figure 1B), immunofluorescence assays exhibited typical neuronal morphology for TAU-positive axons and MAP2-positive dendrites in DNLCs (Figures S1A and S1B). We next assessed the global changes in transcriptome profiles during differentiation by performing bulk RNA sequencing (RNA-seq) in biological triplicates from ECSCs and DNLCs. The average correlation of transcriptomic profiles between replicates in each cell state was high (r = 0.99; Figure S1C), indicating good reproducibility. In total, we found that 10% (1,889) of the total transcripts (19,587) in DNLCs were significantly (q ≤ 0.01; Table S1) altered with a more than 2-fold change in expression when compared with ECSCs, resulting in 1,176 downregulated and 713 upregulated genes. Key pluripotency (POU5F1, POU2F1, NANOG, TDGF1, LIN28A) and stem cell maintenance (SOX2, SOX5) genes were downregulated, whereas neuronal cytoskeletal elements (NEFM, TUBB3) or regulators of neural precursors (PAX6, NYAP2, NRN1) exhibited an increase (3.4- to 8.1-fold, q = 4.5 × 10−2 to 1.7 × 10−6) in transcription (Figure 1C). These events suggest that NTera2 cells can faithfully model in vivo neuronal differentiation. As incomplete differentiation from ECSCs to DNLCs or other causes of cell heterogeneity within a population of DNLCs can confound observation of interactions that are cell type specific, we performed scRNA-seq on live DNLCs relative to ECSCs and examined the gene expression dynamics of individual subpopulations. After processing the cells for quality control (see Transparent Methods), the sequenced data showed an average depth of 76,473 reads per cell and detected a median of 3,831 genes per cell. Cells analyzed in a two-dimensional t-distributed stochastic neighbor embedding (Figure 1A) plot showed a clear separation of cell states as two discrete populations, with 3,631 single cells from ECSCs and 2,952 from DNLCs. Although RA exposure to ECSCs essentially facilitates irreversible differentiation, like any other differentiated cell lines, NTera2 DNLCs contain a mixed populations of neurons and other cell types. We therefore used previously described marker genes (Lake et al., 2016Lake B.B. Ai R. Kaeser G.E. Salathia N.S. Yung Y.C. Liu R. Wildberg A. Gao D. Fung H.L. Chen S. et al.Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain.Science. 2016; 352: 1586-1590Crossref PubMed Scopus (488) Google Scholar, Zhong et al., 2018Zhong S. Zhang S. Fan X. Wu Q. Yan L. Dong J. Zhang H. Li L. Sun L. Pan N. et al.A single-cell RNA-seq survey of the developmental landscape of the human prefrontal cortex.Nature. 2018; 555: 524-528Crossref PubMed Scopus (323) Google Scholar) to predict cell type identity for all DNLCs, resulting in four transcriptionally distinct clusters (Table S1). Our analysis showed that three-fourths (2,180, 74%; Figure 1D) of the cells within the DNLCs correspond to the neuronal cell type (at 95% confidence by hypergeometric test); the rest identified as microglia (235, 8%), oligodendrocyte precursor (374, 13%), or neural progenitor (163, 6%) cells, suggesting that the interactions we identify in DNLCs will tend to be characteristic of the neuronal cell type. We then performed differential gene expression analysis between DNLCs and ECSCs and identified 7,023 genes with significant (q ≤ 0.01; Table S1) differences in expression in DNLCs (4,503 upregulated and 2,520 downregulated) when compared with ECSCs (Figures 1E and S1D). As for marker genes from immunoblotting or RNA-seq for ECSCs and DNLCs (Figures 1B and 1C), the overall average expression level of single cells correlated well (r = 0.8) with the bulk cell populations (Figure 1F). An illustrative example is the involvement of an ARSACS (autosomal recessive spastic ataxia of Charlevoix-Saguenay)-causing SACS gene in the regulation of class III (PRPH) and IV (NF-L/M/H; INA) intermediate filament genes expressed in neurons (Gentil et al., 2019Gentil B.J. Lai G.T. Menade M. Lariviere R. Minotti S. Gehring K. Chapple J.P. Brais B. Durham H.D. Sacsin, mutated in the ataxia ARSACS, regulates intermediate filament assembly and dynamics.FASEB J. 2019; 33: 2982-2994Crossref PubMed Scopus (22) Google Scholar). Consistent with this observation, bulk RNA-seq and scRNA-seq showed an increased expression of classes III and IV genes in DNLCs, except SACS and INA, which exhibited decreased expression (Figure 1F), revealing a cell type-specific outcome. After confirming morphological and transcriptional changes as expected in ECSCs and DNLCs, we sought to co-fractionate the stably interacting proteins by performing BFs using complementary size-exclusion and ion-exchange chromatographic (SEC, IEC) separation techniques (Figure 1A). A total of 700 distinct fractions were collected in duplicate from the cross-linked mt extracts of four fractionation experiments (two ECSCs, two DNLCs). These fractions were then subjected to MS to define MP complex membership. Examination of the co-elution profiles and average correlation of proteins (peptide counts) detected by MS between replicate experiments suggested high reproducibility (r = 0.99; Figures 1A and S2A). As expected, elution profiles were also consistent with average molecular weights and isoelectric points by SEC and IEC methods (Figure S2B), respectively, reinforcing the utility of BF/MS approach. To generate high-quality mtPPIs in each cell state, the tandem MS spectra from each replicate chromatographic fraction was searched against reference human protein sequences using Sequest and several alternate search engines (X! Tandem, MS-GF+, Comet) to increase the sensitivity and accuracy of peptide identification. The resulting peptide-spectral matches were integrated into a single probability score using MSblender (Kwon et al., 2011Kwon 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. 2011; 10: 2949-2958Crossref PubMed Scopus (66) Google Scholar) and then filtered to a 0.1% protein-level false discovery rate, with two or more distinct peptides used to define human proteins that reliably co-elute in each fraction. The chromatographic profiles of proteins co-eluted across collected fractions from both replicates were measured using three complementary scoring procedures (Pearson correlation coefficient, weighted cross-correlation, co-apex score, Havugimana et al., 2012Havugimana P.C. Hart G.T. Nepusz T. Yang H. Turinsky A.L. Li Z. Wang P.I. Boutz D.R. Fong V. Phanse S. et al.A census of human soluble protein complexes.Cell. 2012; 150: 1068-1081Abstract Full Text Full Text PDF PubMed Scopus (588) Google Scholar) to identify pairwise protein associations. To maximize coverage and accuracy (Figure S2C), we integrated the correlation and co-apex scores from different separation techniques into a single unified log likelihood score (LLS) for each putatively interacting protein pair in ECSCs (ΣLLSECSCs) and DNLCs (ΣLLSDNLCs), respectively. High-confidence mtPPIs for each cell state were derived by eliminating associations below a stringent cutoff (ΣLLS ≤1.45), where most of the reference mtPPIs curated in CORUM human protein complexes (Ruepp et al., 2010Ruepp A. Waegele B. Lechner M. Brauner B. Dunger-Kaltenbach I. Fobo G. Frishman G. Montrone C. Mewes H.W. CORUM: the comprehensive resource of mammalian protein complexes–2009.Nucleic Acids Res. 2010; 38: D497-D501Crossref PubMed Scopus (544) Google Scholar) were recovered, as evaluated using area under the receiver operating characteristic curve (Figure 2A ). After employing an appropriate threshold, we considered as physiologically relevant the interactions between MPs, and between the cytosolic and outer mt membrane (OMM) proteins (Walther and Rapaport, 2009Walther D.M. Rapaport D. Biogenesis of mitochondrial outer membrane proteins.Biochim. Biophys. Acta. 2009; 1793: 42-51Crossref PubMed Scopus (97) Google Scholar), for defining two static mtPPI networks. These included 3,320 interactions (2,973 between MPs; 347 between cytosolic and OMM) among 408 unique human MPs in ECSCs and 3,567 (3,233 between MPs; 334 between cytosolic and OMM) interactions among 467 MPs in DNLCs, covering 36% (600 of 1,672 MPs) of the estimated human mt proteome (Table S2). In addition to confirming the physical associations observed in previous large-scale interaction studies in humans and other metazoans (Floyd et al., 2016Floyd B.J. Wilkerson E.M. Veling M.T. Minogue C.E. Xia C. Beebe E.T. Wrobel R.L. Cho H. Kremer L.S. Alston C.L. et al.Mitochondrial protein interaction mapping identifies regulators of respiratory chain function.Mol. Cell. 2016; 63: 621-632Abstract Full Text Full Text PDF PubMed Scopus (166) Google Scholar, Havugimana et al., 2012Havugimana P.C. Hart G.T. Nepusz T. Yang H. Turinsky A.L. Li Z. Wang P.I. Boutz D.R. Fong V. Phanse S. et al.A census of human soluble protein complexes.Cell. 2012; 150: 1068-1081Abstract Full Text Full Text PDF PubMed Scopus (588) Google Scholar, Hein et al., 2015Hein M.Y. Hubner N.C. Poser I. Cox J. Nagaraj N. Toyoda Y. Gak I.A. Weisswange I. Mansfeld J. Buchholz F. et al.A human interactome in three quantitative dimensions organized by stoichiometries and abundances.Cell. 2015; 163: 712-723Abstract Full Text Full Text PDF PubMed Scopus (757) Google Scholar, Huttlin et al., 2017Huttlin E.L. Bruckner R.J. Paulo J.A. Cannon J.R. Ting L. Baltier K. Colby G. Gebreab F. Gygi M.P. Parzen H. et al.Architecture of the human interactome defines protein communities and disease networks.Nature. 2017; 545: 505-509Crossref PubMed Scopus (800) Google Scholar, Liu et al., 2018Liu F. Lossl P. Rabbitts B.M. Balaban R.S. Heck A.J.R. The interactome of intact mitochondria by cross-linking mass spectrometry provides evidence for coexisting respiratory supercomplexes.Mol. Cell. Proteomics. 2018; 17: 216-232Crossref PubMed Scopus (92) Google Scholar, Malty et al., 2017Malty R.H. Aoki H. Kumar A. Phanse S. Amin S. Zhang Q. Minic Z. Goebels F. Musso G. Wu Z. et al.A map of human mitochondrial protein interactions linked to neurodegeneration reveals new mechanisms of redox homeostasis and NF-kappaB signaling.Cell Syst. 2017; 5: 1-14PubMed Google Scholar, Schweppe et al., 2017Schweppe D.K. Chavez J.D. Lee C.F. Caudal A. Kruse S.E. Stuppard R. Marcinek D.J. Shadel G.S. Tian R. Bruce J.E. Mitochondrial protein interactome elucidated by chemical cross-linking mass spectrometry.Proc. Natl. Acad. Sci. U S A. 2017; 114: 1732-1737Crossref PubMed Scopus (113) Google Scholar, Wan et al., 2015Wan C. Borgeson B. Phanse S. Tu F. Drew K. Clark G. Xiong X. Kagan O. Kwan J. Bezginov A. et al.Panorama of ancient metazoan macromolecular complexes.Nature. 2015; 525: 339-344Crossref PubMed Scopus (317) Google Scholar) or small-scale biochemical experiments (BioGRID), we found that most of the mtPPIs in ECSCs (3,086, 93%) and DNLCs (3,199, 90%) had not been previously reported (Figure 2B). Notably, these PPIs encompassed an order of magnitude more MPs (Figure S2D) than our recent study (Malty et al., 2017Malty R.H. Aoki H. Kumar A. Phanse S. Amin S. Zhang Q. Minic Z. Goebels F. Musso G. Wu Z. et al.A map of human mitochondrial protein interactions linked to neurodegeneration reveals new mechanisms of redox homeostasis and NF-kappaB signaling.Cell Syst. 2017; 5: 1-14PubMed Google Scholar) performed in differentiated SH-SY5Y human neuronal cells. The overall reliability, data quality, and biological relevance of mtPPIs in the filtered static (ECSCs, DNLCs) networks was further assessed by composites of various experimental and computational sources (Figure 2C; Table S2). Half (1,745, 53% in ECSCs; 2,014, 56% in DNLCs) of our observed interactions were verified in other cell types and/or mouse brain, or by independent experimental evaluation. These include mtPPIs supported by (1) immunoprecipitation (IP) combined with MS (IP/MS) using protein-specific antibodies in the NTera2 or SH-SY5Y DNLCs or mouse brain, (2) BF/MS in mouse brain or in both NTera2 cell states, (3) alternate SEC separation and MS in NTera2 DNLCs, and (4) previous high-throughput or literature-curated interaction reports (withholding PPIs from CORUM reference set). The validity of the remaining mtPPIs from BF/MS was further independently verified by computational approaches. Specifically, less than one-quarter (474, 14% in ECSCs; 495, 14% in DNLCs) of our interactors have shared functional associations predicted in HumanNet (Lee et al., 2011Lee I. Blom U.M. Wang P.I. Shim J.E. Marcotte E.M. Prioritizing candidate disease genes by network-based boosting of genome-wide association data.Genome Res. 2011; 21: 1109-1121Crossref PubMed Scopus (519) Google Scholar), STRING (Szklarczyk et al., 2017Szklarczyk D. Morris J.H. Cook H. Kuhn M. Wyder S. Simonovic M. Santos A. Doncheva N.T. Roth A. Bork P. et al.The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible.Nucleic Acids Res. 2017; 45: D362-D368Crossref PubMed Scopus (4325) Google Scholar), or GeneMANIA (Warde-Farley et al., 2010Warde-Farley D. Donaldson S.L. Comes O. Zuberi K. Badrawi R. Chao P. Franz M. Grouios C. Kazi F. Lopes C.T. et al.The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function.Nucleic Acids Res. 2010; 38: W214-W220Crossref PubMed Scopus (2406) Google Scholar), or are known or predicted to localize to the same mt subcellular compartment. Altogether, two-thirds (2,219, 67% in ECSCs; 2,509, 70% in DNLCs) of the total, non-redundant physical associations confirmed by these experimental or computational sources are consistent with the validation rates seen for human soluble PPIs (Havugimana et al., 2012Havugimana P.C. Hart G.T. Nepusz T. Yang H. Turinsky A.L. Li Z. Wang P.I. Boutz D.R. Fong V. Phanse S. et al.A census of human soluble protein complexes.Cell. 2012; 150: 1068-1081Abstract Full Text Full Text PDF PubMed Scopus (588) Google Scholar). When benchmarked against literature-curated interactors (CORUM), the performance measures of our mtPPI networks (using 5-fold cross-validation) showed high sensitivity and specificity (Figure S2E), when compared with previous human interaction datasets (Floyd et al., 2016Floyd B.J. Wilkerson E.M. Veling M.T. Minogue C.E. Xia C. Beebe E.T. Wrobel R.L. Cho H. Kremer L.S. Alston C.L. et al.Mitochondrial protein interaction mapping identifies regulators of respiratory chain function.Mol. Cell. 2016; 63: 621-632Abstract Full Text Full Text PDF PubMed Scopus (166) Google Scholar, Havugimana et al., 2012Havugimana P.C. Hart G.T. Nepusz T. Yang H. Turinsky A.L. Li Z. Wang P.I. Boutz D.R. Fong V. Phanse S. et al.A census of human soluble protein complexes.Cell. 2012; 150: 1068-1081Abstract Full Text Full Text PDF PubMed Scopus (588) Google Scholar, Hein et al., 2015Hein M.Y. Hubner N.C. Poser I. Cox J. Nagaraj N. Toyoda Y. Gak I.A. Weisswange I. Mansfeld J. Buchholz F. et al.A human interactome in three quantitative dimensions organized by stoichiometries and abundances.Cell. 2015; 163: 712-723Abstract Full Text Full Text PDF PubMed Scopus (757) Google Scholar, Huttlin et al., 2017Huttlin E.L. Bruckner R.J. Paulo J.A. Cannon J.R. Ting L. Baltier K. Colby G. Gebreab F. Gygi M.P. Parzen H. et al.Architecture of the human interactome defines protein communities and disease networks.Nature. 2017; 545: 505-509Crossref PubMed Scopus (800) Google Scholar, Wan et al., 2015Wan C. Borgeson B. Phanse S. Tu F. Drew K. Clark G. Xiong X. Kagan O. Kwan J. Bezginov A. et al.Panorama of ancient metazoan macromolecular complexes.Nature. 2015; 525: 339-344Crossref PubMed Scopus (317) Google Scholar). The putative interacting MPs were also significantly (4.7 × 10−64 < p < 1.9 × 10−59) enriched for shared phenotypic annotations and higher (7.0 × 10−52 < p < 1.0 × 10−14) functional coherence and similarity (based on Gene Ontology annotations) compared with existing large-scale PPI studies (Figure S3A). The ranked list of mtPPIs within the top or bottom 20th percentile of ΣLLS scores showed significant (5.3 × 10−46 < p < 2.6 × 10−33) enrichment for membership in the same CORUM protein complex (Figure S3B), indicating that the subunits of these complexes were more likely to co-elute in the same biochemical fractions. MP interactors also tended to show enrichment (3.0 × 10−6 < p < 5.0 × 10−2) for shared Pfam domains (Figure S3C; Table S2). This includes the cytochrome b5 domain-containing proteins that function as electron carriers for membrane-bound oxygenases, and the heat shock protein (HSP70, HSP90) domain families involved in proteostasis and quality control. Finally, stably interacting proteins that co-fractionated together were strongly (6.7 × 10−131 < p < 2.2 × 10−14; Figure S3D) co-expressed or co-translated in NTera2 (ECSCs, DNLCs) or mouse brain (Sharma et al., 2015Sharma K. Schmitt S. Bergner C.G. Tyanova S. Kannaiyan N. Manrique-Hoyos N. Kongi K. Cantuti L. Hanisch U.K. Philips M.A. et al.Cell type- and brain region-resolved mouse brain proteome.Nat. Neurosci. 2015; 18: 1819-1831Crossref PubMed Scopus (445) Google Scholar, Zhang et al., 2014Zhang Y. Chen K. Sloan S.A. Bennett M.L. Scholze A.R. O'Keeffe S. Phatnani H.P. Guarnieri P. Caneda C. Ruderisch N. et al.An RNA-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex.J. Neurosci. 2014; 34: 11929-11947Crossref PubMed Scopus (2922) Google Scholar) and exhibited significantly (8.4 × 10−71 < p < 5.6 × 10−42) positively correlated mRNA co-expression profiles (Figure S3E) in human cortical neurons (van de Leemput et al., 2014van de Leemput J. Boles N.C. Kiehl T.R. Corneo B. Lederman P. Menon V. Lee" @default.
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• W2972039360 date "2019-09-01" @default.
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• W2972039360 title "Rewiring of the Human Mitochondrial Interactome during Neuronal Reprogramming Reveals Regulators of the Respirasome and Neurogenesis" @default.
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• W2972039360 doi "https://doi.org/10.1016/j.isci.2019.08.057" @default.
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