Actionable Cytopathogenic Host Responses of Human Alveolar Type 2 Cells to SARS-CoV-2.

Human transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causative pathogen of the COVID-19 pandemic, exerts a massive health and socioeconomic crisis. The virus infects alveolar epithelial type 2 cells (AT2s), leading to lung injury and impaired gas exchange, but the mechanisms driving infection and pathology are unclear. We performed a quantitative phosphoproteomic survey of induced pluripotent stem cell-derived AT2s (iAT2s) infected with SARS-CoV-2 at air-liquid interface (ALI). Time course analysis revealed rapid remodeling of diverse host systems, including signaling, RNA processing, translation, metabolism, nuclear integrity, protein trafficking, and cytoskeletal-microtubule organization, leading to cell cycle arrest, genotoxic stress, and innate immunity. Comparison to analogous data from transformed cell lines revealed respiratory-specific processes hijacked by SARS-CoV-2, highlighting potential novel therapeutic avenues that were validated by a high hit rate in a targeted small molecule screen in our iAT2 ALI system.

A census of human soluble protein complexes.

Cellular processes often depend on stable physical associations between proteins. Despite recent progress, knowledge of the composition of human protein complexes remains limited. To close this gap, we applied an integrative global proteomic profiling approach, based on chromatographic separation of cultured human cell extracts into more than one thousand biochemical fractions that were subsequently analyzed by quantitative tandem mass spectrometry, to systematically identify a network of 13,993 high-confidence physical interactions among 3,006 stably associated soluble human proteins. Most of the 622 putative protein complexes we report are linked to core biological processes and encompass both candidate disease genes and unannotated proteins to inform on mechanism. Strikingly, whereas larger multiprotein assemblies tend to be more extensively annotated and evolutionarily conserved, human protein complexes with five or fewer subunits are far more likely to be functionally unannotated or restricted to vertebrates, suggesting more recent functional innovations.

The conserved Tpk1 regulates non-homologous end joining double-strand break repair by phosphorylation of Nej1, a homolog of the human XLF.

The yeast cyclic AMP-dependent protein kinase A (PKA) is a ubiquitous serine-threonine kinase, encompassing three catalytic (Tpk1-3) and one regulatory (Bcy1) subunits. Evidence suggests PKA involvement in DNA damage checkpoint response, but how DNA repair pathways are regulated by PKA subunits remains inconclusive. Here, we report that deleting the tpk1 catalytic subunit reduces non-homologous end joining (NHEJ) efficiency, whereas tpk2-3 and bcy1 deletion does not. Epistatic analyses revealed that tpk1, as well as the DNA damage checkpoint kinase (dun1) and NHEJ factor (nej1), co-function in the same pathway, and parallel to the NHEJ factor yku80. Chromatin immunoprecipitation and resection data suggest that tpk1 deletion influences repair protein recruitments and DNA resection. Further, we show that Tpk1 phosphorylation of Nej1 at S298 (a Dun1 phosphosite) is indispensable for NHEJ repair and nuclear targeting of Nej1 and its binding partner Lif1. In mammalian cells, loss of PRKACB (human homolog of Tpk1) also reduced NHEJ efficiency, and similarly, PRKACB was found to phosphorylate XLF (a Nej1 human homolog) at S263, a corresponding residue of the yeast Nej1 S298. Together, our results uncover a new and conserved mechanism for Tpk1 and PRKACB in phosphorylating Nej1 (or XLF), which is critically required for NHEJ repair.

Development of a Method Combining Peptidiscs and Proteomics to Identify, Stabilize, and Purify a Detergent-Sensitive Membrane Protein Assembly.

The peptidisc membrane mimetic enables global reconstitution of the bacterial membrane proteome into water-soluble detergent-free particles, termed peptidisc libraries. We present here a method that combines peptidisc libraries and chromosomal-level gene tagging technology with affinity purification and mass spectrometry (AP/MS) to stabilize and identify fragile membrane protein complexes that exist at native expression levels. This method circumvents common artifacts caused by bait protein overproduction and protein complex dissociation due to lengthy exposure to detergents during protein isolation. Using the Escherichia coli Sec system as a case study, we identify an expanded version of the translocon, termed the HMD complex, consisting of nine different integral membrane subunits. This complex is stable in peptidiscs but dissociates in detergents. Guided by this native-level proteomic information, we design and validate a procedure that enables purification of the HMD complex with minimal protein dissociation. These results highlight the utility of peptidiscs and AP/MS to discover and stabilize fragile membrane protein assemblies. Data are available via ProteomeXchange with identifier PXD032315.

ZapG (YhcB/DUF1043), a novel cell division protein in gamma-proteobacteria linking the Z-ring to septal peptidoglycan synthesis.

YhcB, a poorly understood protein conserved across gamma-proteobacteria, contains a domain of unknown function (DUF1043) and an N-terminal transmembrane domain. Here, we used an integrated approach including X-ray crystallography, genetics, and molecular biology to investigate the function and structure of YhcB. The Escherichia coli yhcB KO strain does not grow at 45 °C and is hypersensitive to cell wall-acting antibiotics, even in the stationary phase. The deletion of yhcB leads to filamentation, abnormal FtsZ ring formation, and aberrant septum development. The Z-ring is essential for the positioning of the septa and the initiation of cell division. We found that YhcB interacts with proteins of the divisome (e.g., FtsI, FtsQ) and elongasome (e.g., RodZ, RodA). Seven of these interactions are also conserved in Yersinia pestis and/or Vibrio cholerae. Furthermore, we mapped the amino acid residues likely involved in the interactions of YhcB with FtsI and RodZ. The 2.8 Å crystal structure of the cytosolic domain of Haemophilus ducreyi YhcB shows a unique tetrameric α-helical coiled-coil structure likely to be involved in linking the Z-ring to the septal peptidoglycan-synthesizing complexes. In summary, YhcB is a conserved and conditionally essential protein that plays a role in cell division and consequently affects envelope biogenesis. Based on these findings, we propose to rename YhcB to ZapG (Z-ring-associated protein G). This study will serve as a starting point for future studies on this protein family and on how cells transit from exponential to stationary survival.

EPIC: software toolkit for elution profile-based inference of protein complexes.

Protein complexes are key macromolecular machines of the cell, but their description remains incomplete. We and others previously reported an experimental strategy for global characterization of native protein assemblies based on chromatographic fractionation of biological extracts coupled to precision mass spectrometry analysis (chromatographic fractionation-mass spectrometry, CF-MS), but the resulting data are challenging to process and interpret. Here, we describe EPIC (elution profile-based inference of complexes), a software toolkit for automated scoring of large-scale CF-MS data to define high-confidence multi-component macromolecules from diverse biological specimens. As a case study, we used EPIC to map the global interactome of Caenorhabditis elegans, defining 612 putative worm protein complexes linked to diverse biological processes. These included novel subunits and assemblies unique to nematodes that we validated using orthogonal methods. The open source EPIC software is freely available as a Jupyter notebook packaged in a Docker container (https://hub.docker.com/r/baderlab/bio-epic/).

In vitro toxicity screening of amorphous silica nanoparticles using mitochondrial fraction exposure followed by MS-based proteomic analysis.

Silica nanoparticles (SiNPs) are used in consumer products, engineering and medical technologies. Attractive properties of SiNPs (e.g. size/surface-modification) enhance usage and thus the likelihood of environmental/human exposures. The assessment of health risks associated with exposures to SiNPs requires information on their relative potencies and toxicity mechanisms. In this work, phagocytic J774 cells were exposed to amorphous pristine (15, 30, 75 nm) and surface-modified (-NH2, -C3COOH, -C11COOH, -PEG) SiNP variants, and internalization was assessed by transmission electron microscopy (TEM), while cellular ATP was measured as a cytotoxicity endpoint. Furthermore, mitochondrial fractions from J774 cells were exposed to these SiNP variants (5, 15 µg mL-1), as well as two reference particles (SiNP 12 nm and TiO2), and proteomic changes were analyzed by mass spectrometry. Ingenuity Pathway Analysis was used to identify toxicity pathways. TEM analyses showed SiNP internalization and distribution along with some changes in mitochondrial structure. SiNP size- and surface-modification and chemical composition-related changes in mitochondrial proteins, including key proteins of the respiratory complex and oxidative stress, were evident based on high content mass spectrometry data. In addition, the dose-related decrease in cellular ATP levels in SiNP-exposed cells was consistent with related mitochondrial protein profiles. These findings suggest that physicochemical properties can be determinants of SiNP exposure-related mitochondrial effects, and mitochondrial exposures combined with proteomic analysis can be valuable as a new approach methodology in the toxicity screening of SiNPs for risk assessment, with added insight into related toxicity mechanisms.

Human-Soybean Allergies: Elucidation of the Seed Proteome and Comprehensive Protein-Protein Interaction Prediction.

The soybean crop, Glycine max (L.) Merr., is consumed by humans, Homo sapiens, worldwide. While the respective bodies of literature and -omics data for each of these organisms are extensive, comparatively few studies investigate the molecular biological processes occurring between the two. We are interested in elucidating the network of protein-protein interactions (PPIs) involved in human-soybean allergies. To this end, we leverage state-of-the-art sequence-based PPI predictors amenable to predicting the enormous comprehensive interactome between human and soybean. A network-based analytical approach is proposed, leveraging similar interaction profiles to identify candidate allergens and proteins involved in the allergy response. Interestingly, the predicted interactome can be explored from two complementary perspectives: which soybean proteins are predicted to interact with specific human proteins and which human proteins are predicted to interact with specific soybean proteins. A total of eight proteins (six specific to the human proteome and two to the soy proteome) have been identified and supported by the literature to be involved in human health, specifically related to immunological and neurological pathways. This study, beyond generating the most comprehensive human-soybean interactome to date, elucidated a soybean seed interactome and identified several proteins putatively consequential to human health.

A Gaussian process-based definition reveals new and bona fide genetic interactions compared to a multiplicative model in the Gram-negative Escherichia coli.

MOTIVATION: A digenic genetic interaction (GI) is observed when mutations in two genes within the same organism yield a phenotype that is different from the expected, given each mutation's individual effects. While multiplicative scoring is widely applied to define GIs, revealing underlying gene functions, it remains unclear if it is the most suitable choice for scoring GIs in Escherichia coli. Here, we assess many different definitions, including the multiplicative model, for mapping functional links between genes and pathways in E.coli. RESULTS: Using our published E.coli GI datasets, we show computationally that a machine learning Gaussian process (GP)-based definition better identifies functional associations among genes than a multiplicative model, which we have experimentally confirmed on a set of gene pairs. Overall, the GP definition improves the detection of GIs, biological reasoning of epistatic connectivity, as well as the quality of GI maps in E.coli, and, potentially, other microbes. AVAILABILITY AND IMPLEMENTATION: The source code and parameters used to generate the machine learning models in WEKA software were provided in the Supplementary information. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Panorama of ancient metazoan macromolecular complexes.

Macromolecular complexes are essential to conserved biological processes, but their prevalence across animals is unclear. By combining extensive biochemical fractionation with quantitative mass spectrometry, here we directly examined the composition of soluble multiprotein complexes among diverse metazoan models. Using an integrative approach, we generated a draft conservation map consisting of more than one million putative high-confidence co-complex interactions for species with fully sequenced genomes that encompasses functional modules present broadly across all extant animals. Clustering reveals a spectrum of conservation, ranging from ancient eukaryotic assemblies that have probably served cellular housekeeping roles for at least one billion years, ancestral complexes that have accrued contemporary components, and rarer metazoan innovations linked to multicellularity. We validated these projections by independent co-fractionation experiments in evolutionarily distant species, affinity purification and functional analyses. The comprehensiveness, centrality and modularity of these reconstructed interactomes reflect their fundamental mechanistic importance and adaptive value to animal cell systems.

Misconnecting the dots: altered mitochondrial protein-protein interactions and their role in neurodegenerative disorders.

Introduction: Mitochondria (mt) are protein-protein interaction (PPI) hubs in the cell where mt-localized and associated proteins interact in a fashion critical for cell fitness. Altered mtPPIs are linked to neurodegenerative disorders (NDs) and drivers of pathological associations to mediate ND progression. Mapping altered mtPPIs will reveal how mt dysfunction is linked to NDs.Areas covered: This review discusses how database sources reflect on the number of mt protein or interaction predictions, and serves as an update on mtPPIs in mt dynamics and homeostasis. Emphasis is given to mRNA expression profiles for mt proteins in human tissues, cellular models relevant to NDs, and altered mtPPIs in NDs such as Parkinson's disease (PD), Amyotrophic lateral sclerosis (ALS) and Alzheimer's disease (AD).Expert opinion: We highlight the scarcity of biomarkers to improve diagnostic accuracy and tracking of ND progression, obstacles in recapitulating NDs using human cellular models to underpin the pathophysiological mechanisms of disease, and the shortage of mt protein interactome reference database(s) of neuronal cells. These bottlenecks are addressed by improvements in induced pluripotent stem cell creation and culturing, patient-derived 3D brain organoids to recapitulate structural arrangements of the brain, and cell sorting to elucidate mt proteome disparities between cell types.

Assessment of a method to characterize antibody selectivity and specificity for use in immunoprecipitation.

Antibodies are used in multiple cell biology applications, but there are no standardized methods to assess antibody quality-an absence that risks data integrity and reproducibility. We describe a mass spectrometry-based standard operating procedure for scoring immunoprecipitation antibody quality. We quantified the abundance of all the proteins in immunoprecipitates of 1,124 new recombinant antibodies for 152 chromatin-related human proteins by comparing normalized spectral abundance factors from the target antigen with those of all other proteins. We validated the performance of the standard operating procedure in blinded studies in five independent laboratories. Antibodies for which the target antigen or a member of its known protein complex was the most abundant protein were classified as 'IP gold standard'. This method generates quantitative outputs that can be stored and archived in public databases, and it represents a step toward a platform for community benchmarking of antibody quality.

Interaction landscape of membrane-protein complexes in Saccharomyces cerevisiae.

Macromolecular assemblies involving membrane proteins (MPs) serve vital biological roles and are prime drug targets in a variety of diseases. Large-scale affinity purification studies of soluble-protein complexes have been accomplished for diverse model organisms, but no global characterization of MP-complex membership has been described so far. Here we report a complete survey of 1,590 putative integral, peripheral and lipid-anchored MPs from Saccharomyces cerevisiae, which were affinity purified in the presence of non-denaturing detergents. The identities of the co-purifying proteins were determined by tandem mass spectrometry and subsequently used to derive a high-confidence physical interaction map encompassing 1,726 membrane protein-protein interactions and 501 putative heteromeric complexes associated with the various cellular membrane systems. Our analysis reveals unexpected physical associations underlying the membrane biology of eukaryotes and delineates the global topological landscape of the membrane interactome.

Insights from protein-protein interaction studies on bacterial pathogenesis.

INTRODUCTION: The threat bacterial pathogens pose to human health is increasing with the number and distribution of antibiotic-resistant bacteria, while the rate of discovery of new antimicrobials dwindles. Proteomics is playing key roles in understanding the molecular mechanisms of bacterial pathogenesis, and in identifying disease outcome determinants. The physical associations identified by proteomics can provide the means to develop pathogen-specific treatment methods that reduce the spread of antibiotic resistance and alleviate the negative effects of broad-spectrum antibiotics on beneficial bacteria. Areas covered: This review discusses recent trends in proteomics and introduces new and developing approaches that can be applied to the study of protein-protein interactions (PPIs) underlying bacterial pathogenesis. The approaches examined encompass options for mapping proteomes as well as stable and transient interactions in vivo and in vitro. We also explored the coverage of bacterial and human-bacterial PPIs, knowledge gaps in this area, and how they can be filled. Expert commentary: Identifying potential antimicrobial candidates is confounded by the complex molecular biology of bacterial pathogenesis and the lack of knowledge about PPIs underlying this process. Proteomics approaches can offer new perspectives for mechanistic insights and identify essential targets for guiding the discovery of next generation antimicrobials.

Quantitative genome-wide genetic interaction screens reveal global epistatic relationships of protein complexes in Escherichia coli.

Large-scale proteomic analyses in Escherichia coli have documented the composition and physical relationships of multiprotein complexes, but not their functional organization into biological pathways and processes. Conversely, genetic interaction (GI) screens can provide insights into the biological role(s) of individual gene and higher order associations. Combining the information from both approaches should elucidate how complexes and pathways intersect functionally at a systems level. However, such integrative analysis has been hindered due to the lack of relevant GI data. Here we present a systematic, unbiased, and quantitative synthetic genetic array screen in E. coli describing the genetic dependencies and functional cross-talk among over 600,000 digenic mutant combinations. Combining this epistasis information with putative functional modules derived from previous proteomic data and genomic context-based methods revealed unexpected associations, including new components required for the biogenesis of iron-sulphur and ribosome integrity, and the interplay between molecular chaperones and proteases. We find that functionally-linked genes co-conserved among γ-proteobacteria are far more likely to have correlated GI profiles than genes with divergent patterns of evolution. Overall, examining bacterial GIs in the context of protein complexes provides avenues for a deeper mechanistic understanding of core microbial systems.

Novel function discovery with GeneMANIA: a new integrated resource for gene function prediction in Escherichia coli.

MOTIVATION: The model bacterium Escherichia coli is among the best studied prokaryotes, yet nearly half of its proteins are still of unknown biological function. This is despite a wealth of available large-scale physical and genetic interaction data. To address this, we extended the GeneMANIA function prediction web application developed for model eukaryotes to support E.coli. RESULTS: We integrated 48 distinct E.coli functional interaction datasets and used the GeneMANIA algorithm to produce thousands of novel functional predictions and prioritize genes for further functional assays. Our analysis achieved cross-validation performance comparable to that reported for eukaryotic model organisms, and revealed new functions for previously uncharacterized genes in specific bioprocesses, including components required for cell adhesion, iron-sulphur complex assembly and ribosome biogenesis. The GeneMANIA approach for network-based function prediction provides an innovative new tool for probing mechanisms underlying bacterial bioprocesses. CONTACT: gary.bader@utoronto.ca; mohan.babu@uregina.ca SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Mitochondrial targets for pharmacological intervention in human disease.

Over the past several years, mitochondrial dysfunction has been linked to an increasing number of human illnesses, making mitochondrial proteins (MPs) an ever more appealing target for therapeutic intervention. With 20% of the mitochondrial proteome (312 of an estimated 1500 MPs) having known interactions with small molecules, MPs appear to be highly targetable. Yet, despite these targeted proteins functioning in a range of biological processes (including induction of apoptosis, calcium homeostasis, and metabolism), very few of the compounds targeting MPs find clinical use. Recent work has greatly expanded the number of proteins known to localize to the mitochondria and has generated a considerable increase in MP 3D structures available in public databases, allowing experimental screening and in silico prediction of mitochondrial drug targets on an unprecedented scale. Here, we summarize the current literature on clinically active drugs that target MPs, with a focus on how existing drug targets are distributed across biochemical pathways and organelle substructures. Also, we examine current strategies for mitochondrial drug discovery, focusing on genetic, proteomic, and chemogenomic assays, and relevant model systems. As cell models and screening techniques improve, MPs appear poised to emerge as relevant targets for a wide range of complex human diseases, an eventuality that can be expedited through systematic analysis of MP function.

Yeast mitochondrial protein-protein interactions reveal diverse complexes and disease-relevant functional relationships.

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 non-mitochondrial processes.

Efficient prediction of human protein-protein interactions at a global scale.

BACKGROUND: Our knowledge of global protein-protein interaction (PPI) networks in complex organisms such as humans is hindered by technical limitations of current methods. RESULTS: On the basis of short co-occurring polypeptide regions, we developed a tool called MP-PIPE capable of predicting a global human PPI network within 3 months. With a recall of 23% at a precision of 82.1%, we predicted 172,132 putative PPIs. We demonstrate the usefulness of these predictions through a range of experiments. CONCLUSIONS: The speed and accuracy associated with MP-PIPE can make this a potential tool to study individual human PPI networks (from genomic sequences alone) for personalized medicine.