An atlas of protein homo-oligomerization across domains of life.

Protein structures are essential to understanding cellular processes in molecular detail. While advances in artificial intelligence revealed the tertiary structure of proteins at scale, their quaternary structure remains mostly unknown. We devise a scalable strategy based on AlphaFold2 to predict homo-oligomeric assemblies across four proteomes spanning the tree of life. Our results suggest that approximately 45% of an archaeal proteome and a bacterial proteome and 20% of two eukaryotic proteomes form homomers. Our predictions accurately capture protein homo-oligomerization, recapitulate megadalton complexes, and unveil hundreds of homo-oligomer types, including three confirmed experimentally by structure determination. Integrating these datasets with omics information suggests that a majority of known protein complexes are symmetric. Finally, these datasets provide a structural context for interpreting disease mutations and reveal coiled-coil regions as major enablers of quaternary structure evolution in human. Our strategy is applicable to any organism and provides a comprehensive view of homo-oligomerization in proteomes.

KCNE1 is an auxiliary subunit of two distinct ion channel superfamilies.

Determination of what is the specificity of subunits composing a protein complex is essential when studying gene variants on human pathophysiology. The pore-forming α-subunit KCNQ1, which belongs to the voltage-gated ion channel superfamily, associates to its ß-auxiliary subunit KCNE1 to generate the slow cardiac potassium IKs current, whose dysfunction leads to cardiac arrhythmia. Using pharmacology, gene invalidation, and single-molecule fluorescence assays, we found that KCNE1 fulfils all criteria of a bona fide auxiliary subunit of the TMEM16A chloride channel, which belongs to the anoctamin superfamily. Strikingly, assembly with KCNE1 switches TMEM16A from a calcium-dependent to a voltage-dependent ion channel. Importantly, clinically relevant inherited mutations within the TMEM16A-regulating domain of KCNE1 abolish the TMEM16A modulation, suggesting that the TMEM16A-KCNE1 current may contribute to inherited pathologies. Altogether, these findings challenge the dogma of the specificity of auxiliary subunits regarding protein complexes and questions ion channel classification.

A Pan-plant Protein Complex Map Reveals Deep Conservation and Novel Assemblies.

Plants are foundational for global ecological and economic systems, but most plant proteins remain uncharacterized. Protein interaction networks often suggest protein functions and open new avenues to characterize genes and proteins. We therefore systematically determined protein complexes from 13 plant species of scientific and agricultural importance, greatly expanding the known repertoire of stable protein complexes in plants. By using co-fractionation mass spectrometry, we recovered known complexes, confirmed complexes predicted to occur in plants, and identified previously unknown interactions conserved over 1.1 billion years of green plant evolution. Several novel complexes are involved in vernalization and pathogen defense, traits critical for agriculture. We also observed plant analogs of animal complexes with distinct molecular assemblies, including a megadalton-scale tRNA multi-synthetase complex. The resulting map offers a cross-species view of conserved, stable protein assemblies shared across plant cells and provides a mechanistic, biochemical framework for interpreting plant genetics and mutant phenotypes.

The In Vivo Architecture of the Exocyst Provides Structural Basis for Exocytosis.

The structural characterization of protein complexes in their native environment is challenging but crucial for understanding the mechanisms that mediate cellular processes. We developed an integrative approach to reconstruct the 3D architecture of protein complexes in vivo. We applied this approach to the exocyst, a hetero-octameric complex of unknown structure that is thought to tether secretory vesicles during exocytosis with a poorly understood mechanism. We engineered yeast cells to anchor the exocyst on defined landmarks and determined the position of its subunit termini at nanometer precision using fluorescence microscopy. We then integrated these positions with the structural properties of the subunits to reconstruct the exocyst together with a vesicle bound to it. The exocyst has an open hand conformation made of rod-shaped subunits that are interlaced in the core. The exocyst architecture explains how the complex can tether secretory vesicles, placing them in direct contact with the plasma membrane.

Proteomic discovery of chemical probes that perturb protein complexes in human cells.

Most human proteins lack chemical probes, and several large-scale and generalizable small-molecule binding assays have been introduced to address this problem. How compounds discovered in such "binding-first" assays affect protein function, nonetheless, often remains unclear. Here, we describe a "function-first" proteomic strategy that uses size exclusion chromatography (SEC) to assess the global impact of electrophilic compounds on protein complexes in human cells. Integrating the SEC data with cysteine-directed activity-based protein profiling identifies changes in protein-protein interactions that are caused by site-specific liganding events, including the stereoselective engagement of cysteines in PSME1 and SF3B1 that disrupt the PA28 proteasome regulatory complex and stabilize a dynamic state of the spliceosome, respectively. Our findings thus show how multidimensional proteomic analysis of focused libraries of electrophilic compounds can expedite the discovery of chemical probes with site-specific functional effects on protein complexes in human cells.

Nuclear organization.

This article discusses three reviews on the theme of nuclear organization.

Mechanisms and significance of tissue-specific MICU regulation of the mitochondrial calcium uniporter complex.

Mitochondrial Ca2+ uptake, mediated by the mitochondrial Ca2+ uniporter, regulates oxidative phosphorylation, apoptosis, and intracellular Ca2+ signaling. Previous studies suggest that non-neuronal uniporters are exclusively regulated by a MICU1-MICU2 heterodimer. Here, we show that skeletal-muscle and kidney uniporters also complex with a MICU1-MICU1 homodimer and that human/mouse cardiac uniporters are largely devoid of MICUs. Cells employ protein-importation machineries to fine-tune the relative abundance of MICU1 homo- and heterodimers and utilize a conserved MICU intersubunit disulfide to protect properly assembled dimers from proteolysis by YME1L1. Using the MICU1 homodimer or removing MICU1 allows mitochondria to more readily take up Ca2+ so that cells can produce more ATP in response to intracellular Ca2+ transients. However, the trade-off is elevated ROS, impaired basal metabolism, and higher susceptibility to death. These results provide mechanistic insights into how tissues can manipulate mitochondrial Ca2+ uptake properties to support their unique physiological functions.

XRCC1 prevents toxic PARP1 trapping during DNA base excision repair.

Mammalian DNA base excision repair (BER) is accelerated by poly(ADP-ribose) polymerases (PARPs) and the scaffold protein XRCC1. PARPs are sensors that detect single-strand break intermediates, but the critical role of XRCC1 during BER is unknown. Here, we show that protein complexes containing DNA polymerase ß and DNA ligase III that are assembled by XRCC1 prevent excessive engagement and activity of PARP1 during BER. As a result, PARP1 becomes "trapped" on BER intermediates in XRCC1-deficient cells in a manner similar to that induced by PARP inhibitors, including in patient fibroblasts from XRCC1-mutated disease. This excessive PARP1 engagement and trapping renders BER intermediates inaccessible to enzymes such as DNA polymerase ß and impedes their repair. Consequently, PARP1 deletion rescues BER and resistance to base damage in XRCC1-/- cells. These data reveal excessive PARP1 engagement during BER as a threat to genome integrity and identify XRCC1 as an "anti-trapper" that prevents toxic PARP1 activity.

Kinase Interaction Network Expands Functional and Disease Roles of Human Kinases.

Protein kinases are essential for signal transduction and control of most cellular processes, including metabolism, membrane transport, motility, and cell cycle. Despite the critical role of kinases in cells and their strong association with diseases, good coverage of their interactions is available for only a fraction of the 535 human kinases. Here, we present a comprehensive mass-spectrometry-based analysis of a human kinase interaction network covering more than 300 kinases. The interaction dataset is a high-quality resource with more than 5,000 previously unreported interactions. We extensively characterized the obtained network and were able to identify previously described, as well as predict new, kinase functional associations, including those of the less well-studied kinases PIM3 and protein O-mannose kinase (POMK). Importantly, the presented interaction map is a valuable resource for assisting biomedical studies. We uncover dozens of kinase-disease associations spanning from genetic disorders to complex diseases, including cancer.

Tunability of DNA Polymerase Stability during Eukaryotic DNA Replication.

Structural and biochemical studies have revealed the basic principles of how the replisome duplicates genomic DNA, but little is known about its dynamics during DNA replication. We reconstitute the 34 proteins needed to form the S. cerevisiae replisome and show how changing local concentrations of the key DNA polymerases tunes the ability of the complex to efficiently recycle these proteins or to dynamically exchange them. Particularly, we demonstrate redundancy of the Pol α-primase DNA polymerase activity in replication and show that Pol α-primase and the lagging-strand Pol δ can be re-used within the replisome to support the synthesis of large numbers of Okazaki fragments. This unexpected malleability of the replisome might allow it to deal with barriers and resource challenges during replication of large genomes.

Characterization of the REC114-MEI4-IHO1 complex regulating meiotic DNA double-strand break formation.

Meiotic recombination is initiated by the formation of DNA double-strand breaks (DSBs), essential for fertility and genetic diversity. In the mouse, DSBs are formed by the catalytic TOPOVIL complex consisting of SPO11 and TOPOVIBL. To preserve genome integrity, the activity of the TOPOVIL complex is finely controlled by several meiotic factors including REC114, MEI4, and IHO1, but the underlying mechanism is poorly understood. Here, we report that mouse REC114 forms homodimers, that it associates with MEI4 as a 2:1 heterotrimer that further dimerizes, and that IHO1 forms coiled-coil-based tetramers. Using AlphaFold2 modeling combined with biochemical characterization, we uncovered the molecular details of these assemblies. Finally, we show that IHO1 directly interacts with the PH domain of REC114 by recognizing the same surface as TOPOVIBL and another meiotic factor ANKRD31. These results provide strong evidence for the existence of a ternary IHO1-REC114-MEI4 complex and suggest that REC114 could act as a potential regulatory platform mediating mutually exclusive interactions with several partners.

Targeting protein conformations with small molecules to control protein complexes.

Dynamic protein complexes function in all cellular processes, from signaling to transcription, using distinct conformations that regulate their activity. Conformational switching of proteins can turn on or off their activity through protein-protein interactions, catalytic function, cellular localization, or membrane interaction. Recent advances in structural, computational, and chemical methodologies have enabled the discovery of small-molecule activators and inhibitors of conformationally dynamic proteins by using a more rational design than a serendipitous screening approach. Here, we discuss such recent examples, focusing on the mechanism of protein conformational switching and its regulation by small molecules. We emphasize the rational approaches to control protein oligomerization with small molecules that offer exciting opportunities for investigation of novel biological mechanisms and drug discovery.

Global Interactome Mapping Reveals Pro-tumorigenic Interactions of NF-κB in Breast Cancer.

NF-κB pathway is involved in inflammation; however, recent data shows its role also in cancer development and progression, including metastasis. To understand the role of NF-κB interactome dynamics in cancer, we study the complexity of breast cancer interactome in luminal A breast cancer model and its rearrangement associated with NF-κB modulation. Liquid chromatography-mass spectrometry measurement of 160 size-exclusion chromatography fractions identifies 5460 protein groups. Seven thousand five hundred sixty eight interactions among these proteins have been reconstructed by PrInCE algorithm, of which 2564 have been validated in independent datasets. NF-κB modulation leads to rearrangement of protein complexes involved in NF-κB signaling and immune response, cell cycle regulation, and DNA replication. Central NF-κB transcription regulator RELA co-elutes with interactors of NF-κB activator PRMT5, and these complexes are confirmed by AlphaPulldown prediction. A complementary immunoprecipitation experiment recapitulates RELA interactions with other NF-κB factors, associating NF-κB inhibition with lower binding of NF-κB activators to RELA. This study describes a network of pro-tumorigenic protein interactions and their rearrangement upon NF-κB inhibition with potential therapeutic implications in tumors with high NF-κB activity.

Diverse Molecular Mechanisms Underlying Pathogenic Protein Mutations: Beyond the Loss-of-Function Paradigm.

Most known disease-causing mutations occur in protein-coding regions of DNA. While some of these involve a loss of protein function (e.g., through premature stop codons or missense changes that destabilize protein folding), many act via alternative molecular mechanisms and have dominant-negative or gain-of-function effects. In nearly all cases, these non-loss-of-function mutations can be understood by considering interactions of the wild-type and mutant protein with other molecules, such as proteins, nucleic acids, or small ligands and substrates. Here, we review the diverse molecular mechanisms by which pathogenic mutations can have non-loss-of-function effects, including by disrupting interactions, increasing binding affinity, changing binding specificity, causing assembly-mediated dominant-negative and dominant-positive effects, creating novel interactions, and promoting aggregation and phase separation. We believe that increased awareness of these diverse molecular disease mechanisms will lead to improved diagnosis (and ultimately treatment) of human genetic disorders.

Selective cross-linking of coinciding protein assemblies by in-gel cross-linking mass spectrometry.

Cross-linking mass spectrometry has developed into an important method to study protein structures and interactions. The in-solution cross-linking workflows involve time and sample consuming steps and do not provide sensible solutions for differentiating cross-links obtained from co-occurring protein oligomers, complexes, or conformers. Here we developed a cross-linking workflow combining blue native PAGE with in-gel cross-linking mass spectrometry (IGX-MS). This workflow circumvents steps, such as buffer exchange and cross-linker concentration optimization. Additionally, IGX-MS enables the parallel analysis of co-occurring protein complexes using only small amounts of sample. Another benefit of IGX-MS, demonstrated by experiments on GroEL and purified bovine heart mitochondria, is the substantial reduction of undesired over-length cross-links compared to in-solution cross-linking. We next used IGX-MS to investigate the complement components C5, C6, and their hetero-dimeric C5b6 complex. The obtained cross-links were used to generate a refined structural model of the complement component C6, resembling C6 in its inactivated state. This finding shows that IGX-MS can provide new insights into the initial stages of the terminal complement pathway.

Structural coverage of the human interactome.

Complex biological processes in cells are embedded in the interactome, representing the complete set of protein-protein interactions. Mapping and analyzing the protein structures are essential to fully comprehending these processes' molecular details. Therefore, knowing the structural coverage of the interactome is important to show the current limitations. Structural modeling of protein-protein interactions requires accurate protein structures. In this study, we mapped all experimental structures to the reference human proteome. Later, we found the enrichment in structural coverage when complementary methods such as homology modeling and deep learning (AlphaFold) were included. We then collected the interactions from the literature and databases to form the reference human interactome, resulting in 117 897 non-redundant interactions. When we analyzed the structural coverage of the interactome, we found that the number of experimentally determined protein complex structures is scarce, corresponding to 3.95% of all binary interactions. We also analyzed known and modeled structures to potentially construct the structural interactome with a docking method. Our analysis showed that 12.97% of the interactions from HuRI and 73.62% and 32.94% from the filtered versions of STRING and HIPPIE could potentially be modeled with high structural coverage or accuracy, respectively. Overall, this paper provides an overview of the current state of structural coverage of the human proteome and interactome.

Native Size-Exclusion Chromatography-Based Mass Spectrometry Reveals New Components of the Early Heat Shock Protein 90 Inhibition Response Among Limited Global Changes.

The molecular chaperone heat shock protein 90 (HSP90) works in concert with co-chaperones to stabilize its client proteins, which include multiple drivers of oncogenesis and malignant progression. Pharmacologic inhibitors of HSP90 have been observed to exert a wide range of effects on the proteome, including depletion of client proteins, induction of heat shock proteins, dissociation of co-chaperones from HSP90, disruption of client protein signaling networks, and recruitment of the protein ubiquitylation and degradation machinery-suggesting widespread remodeling of cellular protein complexes. However, proteomics studies to date have focused on inhibitor-induced changes in total protein levels, often overlooking protein complex alterations. Here, we use size-exclusion chromatography in combination with mass spectrometry (SEC-MS) to characterize the early changes in native protein complexes following treatment with the HSP90 inhibitor tanespimycin (17-AAG) for 8 h in the HT29 colon adenocarcinoma cell line. After confirming the signature cellular response to HSP90 inhibition (e.g., induction of heat shock proteins, decreased total levels of client proteins), we were surprised to find only modest perturbations to the global distribution of protein elution profiles in inhibitor-treated HT29 cells at this relatively early time-point. Similarly, co-chaperones that co-eluted with HSP90 displayed no clear difference between control and treated conditions. However, two distinct analysis strategies identified multiple inhibitor-induced changes, including known and unknown components of the HSP90-dependent proteome. We validate two of these-the actin-binding protein Anillin and the mitochondrial isocitrate dehydrogenase 3 complex-as novel HSP90 inhibitor-modulated proteins. We present this dataset as a resource for the HSP90, proteostasis, and cancer communities (https://www.bioinformatics.babraham.ac.uk/shiny/HSP90/SEC-MS/), laying the groundwork for future mechanistic and therapeutic studies related to HSP90 pharmacology. Data are available via ProteomeXchange with identifier PXD033459.

Optimizing the PROTREC network-based missing protein prediction algorithm.

This article summarizes the PROTREC method and investigates the impact that the different hyper-parameters have on the task of missing protein prediction using PROTREC. We evaluate missing protein recovery rates using different PROTREC score selection approaches (MAX, MIN, MEDIAN, and MEAN), different PROTREC score thresholds, as well as different complex size thresholds. In addition, we included two additional cancer datasets in our analysis and introduced a new validation method to check both the robustness of the PROTREC method as well as the correctness of our analysis. Our analysis showed that the missing protein recovery rate can be improved by adopting PROTREC score selection operations of MIN, MEDIAN, and MEAN instead of the default MAX. However, this may come at a cost of reduced numbers of proteins predicted and validated. The users should therefore choose their hyper-parameters carefully to find a balance in the accuracy-quantity trade-off. We also explored the possibility of combining PROTREC with a p-value-based method (FCS) and demonstrated that PROTREC is able to perform well independently without any help from a p-value-based method. Furthermore, we conducted a downstream enrichment analysis to understand the biological pathways and protein networks within the cancerous tissues using the recovered proteins. Missing protein recovery rate using PROTREC can be improved by selecting a different PROTREC score selection method. Different PROTREC score selection methods and other hyper-parameters such as PROTREC score threshold and complex size threshold introduce accuracy-quantity trade-off. PROTREC is able to perform well independently of any filtering using a p-value-based method. Verification of the PROTREC method on additional cancer datasets. Downstream Enrichment Analysis to understand the biological pathways and protein networks in cancerous tissues.

Capillary electrophoresis-mass spectrometry for protein analyses under native conditions: Current progress and perspectives.

Native mass spectrometry is a rapidly emerging technique for fast and sensitive structural analysis of protein constructs, maintaining the protein higher order structure. The coupling with electromigration separation techniques under native conditions enables the characterization of proteoforms and highly complex protein mixtures. In this review, we present an overview of current native CE-MS technology. First, the status of native separation conditions is described for capillary zone electrophoresis (CZE), affinity capillary electrophoresis (ACE), and capillary isoelectric focusing (CIEF), as well as their chip-based formats, including essential parameters such as electrolyte composition and capillary coatings. Further, conditions required for native ESI-MS of (large) protein constructs, including instrumental parameters of QTOF and Orbitrap systems, as well as requirements for native CE-MS interfacing are presented. On this basis, methods and applications of the different modes of native CE-MS are summarized and discussed in the context of biological, medical, and biopharmaceutical questions. Finally, key achievements are highlighted and concluded, while remaining challenges are pointed out.

A deep learning framework for predicting disease-gene associations with functional modules and graph augmentation.

BACKGROUND: The exploration of gene-disease associations is crucial for understanding the mechanisms underlying disease onset and progression, with significant implications for prevention and treatment strategies. Advances in high-throughput biotechnology have generated a wealth of data linking diseases to specific genes. While graph representation learning has recently introduced groundbreaking approaches for predicting novel associations, existing studies always overlooked the cumulative impact of functional modules such as protein complexes and the incompletion of some important data such as protein interactions, which limits the detection performance. RESULTS: Addressing these limitations, here we introduce a deep learning framework called ModulePred for predicting disease-gene associations. ModulePred performs graph augmentation on the protein interaction network using L3 link prediction algorithms. It builds a heterogeneous module network by integrating disease-gene associations, protein complexes and augmented protein interactions, and develops a novel graph embedding for the heterogeneous module network. Subsequently, a graph neural network is constructed to learn node representations by collectively aggregating information from topological structure, and gene prioritization is carried out by the disease and gene embeddings obtained from the graph neural network. Experimental results underscore the superiority of ModulePred, showcasing the effectiveness of incorporating functional modules and graph augmentation in predicting disease-gene associations. This research introduces innovative ideas and directions, enhancing the understanding and prediction of gene-disease relationships.