Yeast Mitochondrial Protein–Protein Interactions Reveal Diverse

Dec 29, 2014 - The integration of these MP complexes with reported genetic interaction data reveals substantial crosstalk between MPs and non-MPs and ...
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Yeast Mitochondrial Protein−Protein Interactions Reveal Diverse Complexes and Disease-Relevant Functional Relationships Ke Jin,†,‡,○ Gabriel Musso,§,∥,○ James Vlasblom,‡,○ Matthew Jessulat,‡,○ Viktor Deineko,‡ Jacopo Negroni,⊥ Roberto Mosca,⊥ Ramy Malty,‡ Diem-Hang Nguyen-Tran,‡ Hiroyuki Aoki,‡ Zoran Minic,‡ Tanya Freywald,# Sadhna Phanse,‡ Qian Xiang,† Andrew Freywald,# Patrick Aloy,⊥,∇ Zhaolei Zhang,*,† and Mohan Babu*,‡ †

Terrence Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada Department of Biochemistry, University of Regina, Regina, Saskatchewan S4S 0A2, Canada § Cardiovascular Division, Brigham and Women’s Hospital, Boston, Massachusetts 02115, United States ∥ Department of Medicine, Harvard Medical School, Boston, Massachusetts 02115, United States ⊥ Joint IRB−BSC Program in Computational Biology, IRB, Barcelona 08028, Spain # Cancer Research Unit, Saskatchewan Cancer Agency, Saskatoon, Saskatchewan S7N 5E5, Canada ∇ Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona 08010, Spain ‡

S Supporting Information *

ABSTRACT: Although detailed, focused, and mechanistic analyses of associations among mitochondrial proteins (MPs) have identified their importance in varied biological processes, a systematic understanding of how MPs function in concert both with one another and with extra-mitochondrial proteins remains incomplete. Consequently, many questions regarding the role of mitochondrial dysfunction in the development of human disease remain unanswered. To address this, we compiled all existing mitochondrial physical interaction data for over 1200 experimentally defined yeast MPs and, through bioinformatic analysis, identified hundreds of heteromeric MP complexes having extensive associations both within and outside the mitochondria. We provide support for these complexes through structure prediction analysis, morphological comparisons of deletion strains, and protein co-immunoprecipitation. The integration of these MP complexes with reported genetic interaction data reveals substantial crosstalk between MPs and non-MPs and identifies novel factors in endoplasmic reticulum−mitochondrial organization, membrane structure, and mitochondrial lipid homeostasis. More than one-third of these MP complexes are conserved in humans, with many containing members linked to clinical pathologies, enabling us to identify genes with putative disease function through guilt-by-association. Although still remaining incomplete, existing mitochondrial interaction data suggests that the relevant molecular machinery is modular, yet highly integrated with nonmitochondrial processes. KEYWORDS: Budding yeast, disease, genetic interactions, mass spectrometry, mitochondria, network, pathway crosstalk, protein complex, protein interactions

1. INTRODUCTION

composition of mitochondria, interaction data among MPs remains sparse. Thus, many disease-relevant associations among MPs likely remain unknown. Although mitochondria possess their own genome,10 the majority of MPs are encoded by the nuclear genome. Mitochondrial processes are executed by an estimated 1000 unique MPs in budding yeast and ∼1500 MPs in human.2,4,10 Thus, approximately 20% of the yeast proteome, and ∼6% of the human proteome, is dedicated to mitochondrial function.

Mitochondria are complex, dynamic organelles that are sites of fundamental cellular processes including respiration and ion homeostasis.1,2 The essentiality of mitochondria to cellular function is underscored by the increasing array of human pathologies known to be caused by mitochondrial dysfunction (e.g., neurodegeneration, cardiomyopathies, metabolic syndromes, and cancer).2−4 While mitochondrial proteins (MPs) have long been studied, ongoing surveys of human physical (i.e., protein−protein) interactions continue to implicate new mitochondrial genes as having roles in complex diseases.2,5−9 However, as a consequence of the unique structure and © 2014 American Chemical Society

Received: November 5, 2014 Published: December 29, 2014 1220

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understanding of mitochondrial disease etiology. The assembled data and derived complexes are publicly accessible as a community resource via a web portal (http://tap.med. utoronto.ca/ypredcmp/).

Since many mitochondrial processes are widely conserved across eukaryotes, studies in the unicellular eukaryote Saccharomyces cerevisiae (budding yeast) have been instrumental in discovering fundamental properties of mitochondrial biology and disease pathogenesis.11 For example, a mutation in the dynamin-related gene OPA1, a mammalian orthologue of a highly conserved yeast mitochondrial fusion protein (Mgm1), has been associated with neurodegenerative disease.12 However, many MPs have not yet been fully characterized and require further exploration to ascertain their potential diagnostic and therapeutic importance.13 MPs that cause the same disease phenotype upon mutation have been found to frequently participate in the same biochemical pathway or complex,7,14 suggesting that disruption of physical interactions can cause morbidity. For example, a mutation affecting the physical interaction between the human MPs superoxide dismutase (SODC, orthologue of yeast Sod1) and VDAC1 (orthologue of yeast OMP2) is linked to amyotrophic lateral sclerosis susceptibility.15 As many interactions, including the example above, are conserved in yeast, identification of physical associations among yeast MPs not only can characterize biochemical functions in eukaryotic mitochondria but can also can identify potential disease mechanisms. Proteomic technologies such as affinity purification coupled with mass spectrometry (AP−MS),16−18 yeast two-hybrid screening,19,20 and protein-fragment complementation21 have identified multiprotein complexes on a global scale in budding yeast, allowing systematic characterization of protein function. Currently, published proteomic studies of yeast mitochondria have shown a tremendous capacity to identify molecular functions for MPs with available interaction data.22−27 Furthermore, integration of previously published large-scale proteomic data with other diverse data sources has enabled the definition of a more comprehensive network of functional interactions for MPs.28 However, these maps do not explicitly survey the global organization of MP complexes within mitochondria and between extra-mitochondrial pathways or processes. Epistatic relationships, observed as genetic interactions (GIs) wherein disruption of two genes within a single organism has a phenotypic effect that is unexpected based on observation of individual constitutive gene disruption effects, provide an additional measure of pathway and complex co-occurrence. Functional association is inferred for pairs of genes having GIs29 or sharing similar genome-wide GI profiles.30 Recent surveys of GIs have revealed extensive functional interactions between MPs,30−32 suggesting an opportunity to systematically characterize MP function through integration of protein and genetic interactions. Here, we used the current catalogue of published yeast mitochondrial protein−protein interaction (PPI) data, including a recent AP−MS screen centered exclusively on membranebound proteins,18 to systematically redefine a comprehensive set of MP complexes. Defined complexes were further confirmed through structural analysis, phenotypic profiling, and co-immunoprecipitation. GIs among complex members highlighted an extensive interactivity among complexes, implicating previously uncharacterized genes in specific mitochondrial processes. Additionally, the mapping of the yeast physical interaction network to human disease-associated genes identified complexes having disease-related biological function, furthering our

2. MATERIALS AND METHODS 2.1. Manual Curation of the Yeast MP Target List

To compile the yeast MP target set for PPI survey, we included mitochondrial ORFs from two large-scale surveys of yeast mitochondrial function24,28 as well as from public databases including UniProt (downloaded ver. 2012−02),33 the Saccharomyces Genome Database (SGD, downloaded February, 2012),34 MitoP2 (downloaded February, 2012),35 and MitoMiner (downloaded ver. 2.0, 2012-01).26 Annotations of dubious ORFs, noncoding RNAs, transposons, and pseudogenes were removed. This yielded a final target inventory of 1208 annotated MPs, which were further categorized as cytosolic and membrane-bound based on transmembrane helix predictions. The additional functional information for these MPs, including transcript and protein expression levels, literature support, gene ontology (GO) functional annotations, and subcellular localizations, is shown in Table S1. 2.2. Orthology Mapping and Assignment of Disease Annotations

A two-pronged approach was used to identify human orthologues for yeast MPs. First, only potentially orthologous human−yeast gene pairs with an InParanoid (ver. 7.0)36 score of 1.0 (best similarity) were considered. This resulted in 47% (552 of 1208) of yeast MPs having potential human orthologues. Next, for the remainder of the yeast proteins, we employed an iterative orthology prediction method based on reciprocal similarity searching that had recently been demonstrated to identify orthologues for mitochondrial genes.37 This allowed us to classify an additional 124 yeast MPs as having human orthologues. Disease associations for the human genes orthologous to our yeast MPs were compiled from four public databases (the Mendelian Inheritance in Man database,38 Genetic Association Database,39 Cancer Gene Census,40 and Human Gene Mutation database).41 After removing disease-linked mitochondrial genes in non-protein-coding regions, we retained 235 human disease-linked genes. These disease-associated genes were further categorized into distinct classes of disorders as previously described.42 2.3. Identifying Physical Interactions for Yeast MPs

Physical interactions for the 1208 yeast MPs were retrieved from public databases (BioGRID, release 3.1.86;43 SGD, downloaded February, 2012;34 IntAct, downloaded March 13, 2012;44 the Molecular Interaction Database, downloaded March 13, 2012;45 the Database of Interacting Proteins, downloaded March 13, 2012;46 and MPact, downloaded March 13, 2012).47 Any interactions including ribosomal proteins or chaperones were filtered out, as these represent potentially nonspecific associations.17 This resulted in 27 252 retained PPIs including at least one MP. The reliability of the PPI data set was assessed through evaluation of GI profiles, transcript coexpression, and localization, as compared to random expectation. Specifically, labels from the original PPI network were shuffled 10 000 times, and properties of the true set were compared against the average from each of the 10 000 random sets to determine an empirical p-value. The external 1221

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each study, and only those with |Z -score| ≥ 1.96 (corresponding to a p-value ≤ 0.05) were retained. In the case of GI scores derived from reciprocal pairs (i.e., query-array pairs), the highest absolute Z-score was retained only if the GI trends for these two pairs were similar (i.e., both GI scores were either positive or negative). Gene pairs with inconsistent phenotypic signatures (i.e., positive GI in one study and negative in the other) were removed. Applying this filtering criteria resulted in 9332 nonredundant digenic interactions (2888 positive or alleviating and 6444 negative or aggravating), involving 842 mitochondrial genes. To compute the enrichment for GIs (positive or negative) between and within complexes, complex labels were shuffled 10 000 times, and the number of GIs between and within complexes was calculated at each iteration. The number of positive or negative GIs, within and between complexes, was calculated from random networks using Z = (N − μ)/σ, where N is the number of positive or negative GIs within or between complexes, μ is the mean for this number derived through random iteration, and σ is the standard deviation of the number of positive or negative GIs in the random networks. In cases where the coreMethod assigned a single protein into multiple complexes, the corresponding GIs between those gene pairs were excluded from this analysis.

data sources used in this study are listed in the Supporting Experimental Procedures. 2.4. Defining a Gold Standard and the Identification of Multiprotein Complexes

Prior to the identification of multimeric complexes, we compiled a gold-standard reference set of MP complexes by combining the CYC2008 complex catalogue48 with recently published literature. Specifically, genes having complex designations in CYC2008 were individually searched in PubMed for evidence of additional binding partners. PubMed was also searched for entire novel complexes reported since the publishing of the CYC2008 catalog. This resulted in 165 nonredundant, mitochondrial-associated complexes (see Supporting Information Table S5 for complex definitions and data sources). Next, since densely connected regions in the PPI network correspond to associative protein units likely to have a unifying function,18,49 we used two well-established clustering algorithms, the coreMethod and the Markov clustering (MCL) algorithms,50−52 to identify these regions from within the MP interaction network. Notably, MCL produces discrete clusters, whereas the coreMethod allows shared membership. The accuracy of these clustering algorithms was evaluated by comparing the predicted complex sets against the reference set of 165 gold-standard MP complexes (see above). Specifically, we adopted a previously published53 overlap-based scoring approach: (ω = Nc2/(NpNk)), where Nc is the number of subunits shared in both predicted and known complexes and Np and Nk represent the number of subunits present in the predicted and known complexes, respectively. After setting a ω score threshold of 0.25, the coreMethod was found to capture ∼33% (54 out of 165) of the goldstandard complexes, whereas MCL captured only ∼22% (36 out of 165; p-value = 0.035, Fisher’s exact test, two-sided). This indicated that the coreMethod performed as well as, if not better than, MCL in predicting protein complexes from the yeast MP interactions. Thus, complexes predicted by the coreMethod were used in all subsequent analyses.

2.7. Functional Enrichment and Expression Analyses

Functional enrichment analyses were conducted using a local version of GO::Term Finder (ver. 0.86). This software contains a suite of tools for retrieving, evaluating, and visualizing gene annotations of GO terms.55 GO annotations for yeast genes were downloaded from SGD,56 and for human, from the GO Web site57 (both downloaded on November 23, 2011). To investigate the tissue-specific expression of human disease orthologues within the predicted yeast MP complexes, expression data was downloaded from the Human Protein Atlas database (ver. 12). We categorized tissue expression levels into two groups (strong and weak) as per the Protein Atlas nomenclature. Expression ratios were computed for diseaseassociated orthologous gene pairs in similar tissues as compared to randomly sampled human MP pairs.

2.5. Structural Analysis and Modeling of MP Binary Interactions

2.8. Generation of Yeast Strains

Each of the 304 putative MP complexes (containing 686 total MPs) were analyzed using the Interactome3D Web server54 to model all possible homo- and heterodimeric interactions between complex subcomponents. In addition, we checked how many of these possible combinations had been previously observed and verified at least once by any experimental method (labeled as experimentally known). Structural coverage of single components and binary interactions within complexes are detailed in the Supporting Experimental Procedures.

The yeast strains and plasmids used in this study are listed in Table S2. For affinity purifications and co-immunoprecipitations, expression plasmids containing Gateway-adapted yeast mitochondrial protein (MP) ORFs were obtained from the Yeast-GFP collection, a gift from Prof. Jodi Nunnari, University of California, Davis, and MORF (moveable ORF) collection through Thermo Scientific. Following transformation, yeast strains were grown in complete glucose (YPD) and nonfermentable ethanol-glycerol (YPEG) media. Standard genetic techniques were used to create fusion and deletion mutant strains.

2.6. Analysis of Mitochondrial GIs within and between Complexes

To organize MP complexes into cellular pathways, we first obtained GI data for MPs, as compiled from two sources: a genome-wide epistasis screen30 and a smaller scale, mitochondria-focused study.32 Due to varying experimental design, growth conditions, screening protocols, and scoring schemes used in reporting these GIs,30,32 these data required standardization. To do so, we used a filtering process based on the observed distribution of GI scores from each experiment. Using this filtered data set, a Z-score was computed for each GI pair based on the distribution of double mutant growth scores from

2.9. Microscopy

Yeast strains harboring deletions of MPs of interest were transformed with OM45p-GFP58 using standard lithium acetate procedures and visualized using a Zeiss Observer epifluorescence microscope. Mitochondrial structures were qualitatively determined visually to be either intact or fragmented, based on the proportion of continuous or noncontinuous mitochondrial cables within the examined cells. 1222

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fractions were obtained through ultracentrifugation at 120 000g for 60 min at 4 °C in a 5−35% sucrose gradient. To isolate peripherally bound membrane proteins, crude mitochondria were swollen by addition of 40 mM HEPES/KOH (pH 7.4) and digested using proteinase K for 20 min at 30 °C. To isolate membrane-bound proteins, equal volumes of 0.1 M Na2CO3 or 1 M NaCl solution were added to the mitochondrial extract and incubated on ice for 30 min. Samples were then centrifuged at 100 000g for 30 min at 4 °C. Membrane-associated and soluble proteins were analyzed by SDS-PAGE and immunodecorated with antisera raised against the Fcj1 MP.

Tandem affinity protein (TAP) or GFP-tagged yeast bait strains were transformed with moveable ORF plasmids59 containing human influenza hemagglutinin (HA)-tagged prey proteins. Cells were grown in selective media overnight before 2 h induction in yeast peptone (YP) media with 2% galactose. Harvested cells were resuspended in chilled immunoprecipitation lysis buffer (IPLB; 20 mM HEPES/KOH, pH 7.4, 150 mM KOAc, 2 mM Mg(Ac)2, 1 mM EDTA, 10% glycerol, 1× protease inhibitor), and incubated with calmodulin sepharose 4B (GE Healthcare) or anti-GFP beads (Miltenyi). Western blotting of immunoprecipitated proteins was performed with a rabbit anti-HA polyclonal antibody (Santa Cruz). AP−MS experiments on predicted complexes were conducted using the yeast GFP-tagged mitochondrial bait proteins as previously described,32 except that the trypsin-digested affinity-purified bait proteins were subject to an Orbitrap Elite mass spectrometer (Thermo Scientific) for protein identification. As with previous studies,18,60 MS/MS spectra were matched against yeast protein sequences using the SEQUEST database search engine, and match quality was evaluated using probabilities generated by the STATQUEST algorithm.61 Copurifying proteins were then filtered with a peptide count ≥ 2 at an MS identification confidence score of ≥90%. For immunoprecipitation in mammalian cells using tagged constructs, full-length, sequence-verified, nonmutated, Gateway-compatible cDNA entry clones of the human diseaselinked MPs (obtained from Harvard PlasmidID) cloned into the lentiviral expression vector62 were transduced into HEK293 cells. After two rounds of puromycin (2 μg/mL) selection, stably expressing cells were expanded as previously described.62 Expression of the FLAG-tagged protein in stable cells was confirmed by immunoblotting using an anti-FLAG antibody. Briefly, immunoprecipitation was performed from ten 150 mm dishes of either the lentiviral mediated FLAG-tagged MPs in HEK293 cells or uninfected HEK293 whole cell lysates, which were harvested and lysed in IPLB containing 1% digitonin for 30 min, followed by centrifugation at 16 000g for 15 min at 4 °C. Either the anti-FLAG M2 beads (i.e., for the FLAG-tagged bait protein) or 3 μg of antibody specific to the endogenous target protein along with μMACS protein-G magnetic beads was incubated with the lysate for 4 h with gentle rotation at 4 °C. After washing the beads 5 times with IPLB (3 times with 0.1% digitonin and 2 times without digitonin), co-precipitated proteins bound to the beads were eluted using 25 μL Laemmli loading buffer at 95 °C and analyzed by SDS-PAGE and immunoblotting using a proteinspecific antibody.

2.13. ATP Production Assay

Fresh crude mitochondria isolated from 1 L of YPEG overnight culture were assayed for ATP production as previously described.65 Briefly, the mitochondrial pellet was resuspended in 2 mL of ice-cold phosphate buffered saline and assayed for protein concentration using the Lowry method. To quantify ATP production, 25 μL of 20 mM ADP and 20 mM succinate were added to a 25 μL mitochondrial suspension and incubated at 28 °C for 2 h. This reaction was arrested by addition of 10 μM sodium azide, and ATP concentrations were determined using an Abcam ATP colorimetric kit (Ab83355) according to the manufacturer’s instructions. 2.14. Phospholipid Extraction, Chromatography, and Mass Spectrometry Analyses

Phospholipid extraction was conducted as previously described,66 with extracts subsequently separated using thinlayer chromatography (TLC) in a 2.3% boric acid/ethanol solution. Development of the TLC plate was performed in a chloroform, ethanol, water, and triethylamine (30:35:7:35; v/v/ v/v) mix, and the plate was visualized using a 10% cupric sulfate, 8% boric acid solution and charred in a drying oven at 180 °C for 20 min. The lipids extracted from the wild-type and mutant cells were analyzed for phospholipid species by direct infusion electrospray ionization (ESI), at a flow rate of 8 μL/min, in an IonMax API ion source coupled to an Orbitrap Elite mass spectrometer. The instrument was calibrated with Pierce ESI negative ion calibration solution. Measurements were carried out in negative ion mode with ion-spray potential of 4 kV and transfer capillary temperature at 325 °C. Full-scan high-resolution mass spectra (R = 60 000 at m/z 400) were collected at a selected m/z range of 200 to 1500, with a maximum injection time of 200 ms. Data acquisition and processing were performed using Xcalibur. Yeast total lipid extract purchased from Avanti Polar Lipids (Alabaster, AL, USA) was used as an internal standard. 2.15. Enzymatic Measurement of Phosphatidylcholine (Pc) and Phosphatidylserine (Ps)

2.11. Phenotypic Measurements

Relevant single or double mutant strains were grown to saturation in standard YPD media (2 days at 30 °C) and then serially diluted in triplicate. For the spot assay, 15 μL of dilutions 1 in 104 to 1 in 106 were plated on YPD or YPEG (nonfermentable) media and were grown at 30 °C. For growth curve analysis, 20 μL of the 1 in 10 and 1 in 103 dilutions was added to 180 μL of YPEG in a standard 96-well plate and monitored at OD600 for 24 h using an automated Bio-Tek Synergy HT multidetection microplate reader.

Phospholipids extracted from the wild-type and mutant samples, following a previously described procedure,66 were dissolved in 200 μL of 1% Triton X-100. The lipid solution was diluted 10-fold, and 2 μL was used for quantification of lipid species. The contents of PS and PC in the lipid extracts were measured by enzymatic assay. The enzymatic activity of PC was measured according to the manufacturer’s protocol (Sigma), whereas PS was quantified using a three-reagent system, following a recently described procedure.67 Briefly, PS activity was measured using reagent A containing 600 units/mL phospholipase D (PLD) from Streptomyces chromofuscus (Enzo Life Science), 20 units/mL L-amino acid oxidase from Crotalus adamanteus (Sigma), 50

2.12. Cellular Fractionation of Yeast Cells

Total yeast cell extracts were prepared using alkaline lysis as previously described.63 Cellular and mitochondrial fractions of yeast cells were isolated as described,64 except that subcellular 1223

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Figure 1. Mitochondrial target selection and integration of physical and functional networks to uncover human disease candidate associations. Mitochondrial proteins (MPs) determined through various sources (shown by number of reported databases in bar graph in top right and grouped by functional annotation in pie chart; Table S1) were used to compile mitochondrial PPIs. These PPIs were used to cluster MPs using the coreMethod algorithm, identifying 304 putative multiprotein complexes. Genetic interactions (GIs) among MPs were overlaid on these putative complexes to identify significantly enriched inter- and intra-module interactions. Multiprotein complex membership was also mapped to human orthologues to identify disease candidates through guilt-by-association.

evidence from small scale mechanistic studies indicates that additional proteins have mitochondrial function.10 We therefore both filtered and supplemented the list of predicted MPs using literature evaluation and mining of PPI databases.18,69,72 To ensure that this list of MPs was accurate, we retained only MPs supported by direct experimentation (Table S1). This yielded a final target inventory of 1208 experimentally defined mitochondrial DNA- and nuclear-encoded MPs (Table S1), ∼89% of which (1075 of 1208) are supported by more than one line of evidence (Figure 1). Nearly 34% of these MPs (402 of 1208) have not been included in previous systematic analyses of MP function28,68 (Figure S1A). Of these 1208 MPs, ∼52% (630) are annotated to a well-defined pathway or multiprotein complex (Figure S1A). As expected,28 we found that these MPs were more abundant at the transcript (1.9-fold; p = 5.0 × 10−7; Figure S1B) and protein (1.8-fold; p = 7.9 × 10−6; Figure S1C) levels and encoded larger proteins (1.1-fold; p = 1.4 × 10−11; Figure S1D) with high conservation across a broad variety of eukarya (p = 1.22 × 10−2; Figure S1E and Table S3) when compared against non-MPs. Consistent with previous observations for other proteins,73,74 yeast MPs conserved in humans were found to be more likely to be essential for yeast growth than nonconserved MPs (p ≤ 2.2 × 10−16) (Figure S1F). Furthermore, mutations in ∼36% (235 of 659) of the human orthologues of yeast MPs are

mM NaCl, and 50 mM Tris-HCl (pH 7.4). Reagent B contained 6.25 units/mL peroxidase (Sigma), 180 μM Amplex red, 0.125% Triton X-100, 50 mM NaCl, and 50 mM Tris-HCl (pH 7.4). PS standard (1-palmitoyl-2-oleoyl-sn-glycero-3[phosphor-L-serine] sodium salt; Avanti Polar Lipid, Inc.) was dissolved in a 1% Triton X-100 aqueous solution. Two microliters of each sample was diluted with 8 μL of 1% Triton X-100, followed by the addition of 10 μL of reagent A to the mixture. After incubation at 25 °C for 240 min, 80 μL of reagent B was added to the mixture and incubated 15 min at room temperature. The reaction was stopped by adding 20 μL of Amplex red reagent to the mixture. The enzymatic levels of PC and PS in wild type and mutant samples were measured using a microplate reader (BioTek Synergy HT).

3. RESULTS 3.1. Selection of Yeast MPs for PPI Analysis

We first sought to derive an updated and definitive set of yeast MPs with which to perform all subsequent analyses. Using machine learning frameworks, two previously published reports28,68 integrated heterogeneous experimental data sets including data resulting from genome-wide epitope tagging,69 MS-based proteomics,23−25 phenotypic screening,11,70 and phylogenetic profiling71 to identify nearly 850 yeast proteins that are likely to localize to mitochondria. However, growing 1224

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Figure 2. Global map of yeast MP complexes. (A) Comparison of the MP complexes predicted by the coreMethod and Markov clustering (MCL) algorithms, as evaluated using overlap with the gold-standard reference complexes (see Materials and Methods). (B) Overlap of curated complexes with coreMethod clusters (I) and vice versa (II). (C) Connectivity of multiprotein complexes, grouped by localization. Blue edges represent physical associations, and node size indicates the relative size of each cluster, with previously reported components in orange and novel members in blue. Some illustrative complexes are highlighted (I−III). IM, inner membrane; OM, outer membrane; IMS, intermembrane space; SCL, subcellular localization.

membrane contact sites.75 This network represents coverage of nearly 90% (1069 of 1208) of our defined mitochondrial proteome and includes 3953 PPI between MP pairs, a subset herein referred to as the mitochondrial network. As previously noted,76,77 we found that physically interacting MPs tend to display more correlated GI (p ≤ 10−6; Figure S2B) and mRNA transcript expression profiles (p ≤ 10−10; Figure S2C) as compared to randomly selected protein pairs. Additionally, MPs are enriched for physical associations among proteins localized within the same cellular compartment, when compared to random pairs of proteins (p ≤ 2.4 × 10−74; Figure S2D). We also observed that MPs essential for yeast growth are more highly connected than nonessential MPs (p ≤ 4.3 × 10−3; Figure S2E). These results suggest that interacting MPs have properties consistent with what has been observed for soluble and membrane-bound proteins.17,18

associated with clinical pathologies, significantly higher than for all other yeast−human orthologues (p ≤ 2.2 × 10−16; Figure S1G, Table S1), underscoring the clinical relevance of these MPs. Many MPs are linked to broadly defined bioprocesses (e.g., metabolism, transport, protein folding, and organization; Figure 1); however, nearly 18% (214 of 1208) have no described function (significantly more than randomly selected proteins; p = 4.97 × 10−16; Table S1), indicating an opportunity for further biological characterization. 3.2. Defining a High-Quality Yeast MP Interaction Network

To gain a global view of MP function, physical associations among MPs were collected from several curated public repositories (see Materials and Methods). Using this data, we built a network of 27 252 nonredundant pairwise associations (i.e., interactions between MPs and between MPs and nonMPs) involving 1069 distinct yeast MPs (Table S4). Non-MPs interacting with MPs were preferentially localized to the cytoplasm, endoplasmic reticulum (ER), and vesicle (p ≤ 0.05; Figure S2A), consistent with the possibility that organelles communicate and coordinate cellular functions through

3.3. Identification of Mitochondrial Multiprotein Complexes

We used the mitochondrial network to define intra-MP complexes, in an effort to maximize the likelihood of defining 1225

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Figure 3. Validation of MP complexes using orthogonal assays. (A) Illustrative example of structural modeling (right) of multiprotein complex membership (left). (B) Schematic showing the strategy for generating yeast mutant complex members with an outer membrane GFP marker that is expressed from an exogenous mitochondrial OM45-GFP plasmid containing a Leu2 selectable marker (I). A representative subnetwork showing mitochondrial defects in mutant cells harboring deletions of individual MP complex subunits as compared to normal mitochondria in wild-type (WT) cells (II, scale bar equals 2 μm), with phenotypic quantification of abnormal mitochondrial cells shown in bar graph. Error bars indicate standard deviation from three independent experiments; asterisk represents a significant (p ≤ 0.05; Student’s t-test) difference between mutants and wild type. (C) Co-immunoprecipitation (I) and AP−MS (II) confirm the interaction between Mir1 and Tom40. Immunoblot analysis was of the indicated GFP fusion proteins in whole cell lysates and anti-HA immunoprecipitates. Untagged strain served as a negative control. Molecular mass (kDa) is indicated at the right.

complexes with related biological functions were enriched (p ≤ 0.05) for both intercompartment (e.g., inner and outer membrane; Figure 2C), and interorganelle (e.g., mitochondria−plasma membrane and mitochondria−ER; Figure 2C) interactions. This observation suggests extensive biochemical communication within the mitochondria and with non-MPs. Further analysis also revealed that ∼18% (54 of 304) of multiprotein complexes overlapped additional previously described clusters by at least 50% of their subunits (p ≤ 2.4 × 10−4 versus randomly derived complexes; Figure S2G). Known complexes include the MICOS (mitochondrial contact site) and ERMES (ER−mitochondria encounter structure) complexes, which are crucial for the maintenance of cristae morphology81,82 and mitochondrial protein import.83 The remaining majority (250) of MP complexes contain fewer than four distinct MPs and include 153 heterodimeric

protein subunits with a unified molecular function.78 To identify complexes, we partitioned the mitochondrial PPI network into densely connected subgraphs using both the coreMethod16,52,79 and Markov clustering algorithms,50,80 finding that the former yielded more functionally cohesive protein subunits (Figure 2A; see Materials and Methods). The coreMethod identified 304 putative multiprotein complexes containing 686 distinct MPs (Table S5), with many small complexes and relatively few large complexes (Figure S2F). To gauge the quality of these complexes, we measured the extent to which they overlapped a set of reference mitochondrial complexes derived from literature curation and the CYC2008 catalogue48 (Table S5). We found that 70 of the 165 reference complexes had better than 50% overlap with a predicted multiprotein complex, with 25 reference complexes exhibiting better than 90% overlap (Figure 2B). Subunits of MP 1226

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Figure 4. Epistatic relationships among multiprotein complexes. GIs were enriched within and between multiprotein complexes across mitochondrial processes. Multiprotein complexes highlighted in individual boxes (I−VI) are indicated numerically in the large network. Node size indicates the number of subunits in each complex. Node color refers to previously reported (orange) or novel subunits (light blue) of the complex, and edge thickness reflects the number of GIs observed between complexes.

space protein Mia40, leading to Tim12 oxidation and release.84,85 This binding is predicted to dock the soluble Tim 9 and 10 MPs to integral subunits of the Tim22 complex (Tim18, Tim22, and Tim54).84,85 Tim22 colocalizes with the inner mitochondrial membrane translocase Tim23 to facilitate protein import into mitochondria.86 The coreMethod identified these components as one mega-complex (Figure 3A), and Interactome3D54 produced a model for the Tim9−12 association. Using this modeled interaction it was possible to reconstruct the less-studied Tim9−10−12 complex (Figure 3A), following the proposed 3:1:2 stoichiometry.85 Next, since alterations in mitochondrial morphology indicate MP function,18,87 we used fluorescence imaging to examine yeast strains expressing a mitochondria-targeted fluorescent marker and lacking individual subunits of 12 predicted MP complexes (Figure 3B and Table S7). We found that loss of components predicted to be in the same complex caused similar morphological phenotypes for most (10 of 12) of the MP complexes tested (Table S7). Notable among these was a previously undefined complex containing proteins expressed at the mitochondrial outer membrane (Hfd1, Om14, Tom70) and cristae junction (Fcj1), as well as a protein of unknown

complexes that had either not been previously curated or showed little overlap (