Tau interactome maps synaptic and mitochondrial processes associated with neurodegeneration.

Tau (MAPT) drives neuronal dysfunction in Alzheimer disease (AD) and other tauopathies. To dissect the underlying mechanisms, we combined an engineered ascorbic acid peroxidase (APEX) approach with quantitative affinity purification mass spectrometry (AP-MS) followed by proximity ligation assay (PLA) to characterize Tau interactomes modified by neuronal activity and mutations that cause frontotemporal dementia (FTD) in human induced pluripotent stem cell (iPSC)-derived neurons. We established interactions of Tau with presynaptic vesicle proteins during activity-dependent Tau secretion and mapped the Tau-binding sites to the cytosolic domains of integral synaptic vesicle proteins. We showed that FTD mutations impair bioenergetics and markedly diminished Tau's interaction with mitochondria proteins, which were downregulated in AD brains of multiple cohorts and correlated with disease severity. These multimodal and dynamic Tau interactomes with exquisite spatial resolution shed light on Tau's role in neuronal function and disease and highlight potential therapeutic targets to block Tau-mediated pathogenesis.

Transcription factor protein interactomes reveal genetic determinants in heart disease.

Congenital heart disease (CHD) is present in 1% of live births, yet identification of causal mutations remains challenging. We hypothesized that genetic determinants for CHDs may lie in the protein interactomes of transcription factors whose mutations cause CHDs. Defining the interactomes of two transcription factors haplo-insufficient in CHD, GATA4 and TBX5, within human cardiac progenitors, and integrating the results with nearly 9,000 exomes from proband-parent trios revealed an enrichment of de novo missense variants associated with CHD within the interactomes. Scoring variants of interactome members based on residue, gene, and proband features identified likely CHD-causing genes, including the epigenetic reader GLYR1. GLYR1 and GATA4 widely co-occupied and co-activated cardiac developmental genes, and the identified GLYR1 missense variant disrupted interaction with GATA4, impairing in vitro and in vivo function in mice. This integrative proteomic and genetic approach provides a framework for prioritizing and interrogating genetic variants in heart disease.

The Global Phosphorylation Landscape of SARS-CoV-2 Infection.

The causative agent of the coronavirus disease 2019 (COVID-19) pandemic, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has infected millions and killed hundreds of thousands of people worldwide, highlighting an urgent need to develop antiviral therapies. Here we present a quantitative mass spectrometry-based phosphoproteomics survey of SARS-CoV-2 infection in Vero E6 cells, revealing dramatic rewiring of phosphorylation on host and viral proteins. SARS-CoV-2 infection promoted casein kinase II (CK2) and p38 MAPK activation, production of diverse cytokines, and shutdown of mitotic kinases, resulting in cell cycle arrest. Infection also stimulated a marked induction of CK2-containing filopodial protrusions possessing budding viral particles. Eighty-seven drugs and compounds were identified by mapping global phosphorylation profiles to dysregulated kinases and pathways. We found pharmacologic inhibition of the p38, CK2, CDK, AXL, and PIKFYVE kinases to possess antiviral efficacy, representing potential COVID-19 therapies.

The Psychiatric Cell Map Initiative: A Convergent Systems Biological Approach to Illuminating Key Molecular Pathways in Neuropsychiatric Disorders.

Although gene discovery in neuropsychiatric disorders, including autism spectrum disorder, intellectual disability, epilepsy, schizophrenia, and Tourette disorder, has accelerated, resulting in a large number of molecular clues, it has proven difficult to generate specific hypotheses without the corresponding datasets at the protein complex and functional pathway level. Here, we describe one path forward-an initiative aimed at mapping the physical and genetic interaction networks of these conditions and then using these maps to connect the genomic data to neurobiology and, ultimately, the clinic. These efforts will include a team of geneticists, structural biologists, neurobiologists, systems biologists, and clinicians, leveraging a wide array of experimental approaches and creating a collaborative infrastructure necessary for long-term investigation. This initiative will ultimately intersect with parallel studies that focus on other diseases, as there is a significant overlap with genes implicated in cancer, infectious disease, and congenital heart defects.

Comparative Flavivirus-Host Protein Interaction Mapping Reveals Mechanisms of Dengue and Zika Virus Pathogenesis.

Mosquito-borne flaviviruses, including dengue virus (DENV) and Zika virus (ZIKV), are a growing public health concern. Systems-level analysis of how flaviviruses hijack cellular processes through virus-host protein-protein interactions (PPIs) provides information about their replication and pathogenic mechanisms. We used affinity purification-mass spectrometry (AP-MS) to compare flavivirus-host interactions for two viruses (DENV and ZIKV) in two hosts (human and mosquito). Conserved virus-host PPIs revealed that the flavivirus NS5 protein suppresses interferon stimulated genes by inhibiting recruitment of the transcription complex PAF1C and that chemical modulation of SEC61 inhibits DENV and ZIKV replication in human and mosquito cells. Finally, we identified a ZIKV-specific interaction between NS4A and ANKLE2, a gene linked to hereditary microcephaly, and showed that ZIKV NS4A causes microcephaly in Drosophila in an ANKLE2-dependent manner. Thus, comparative flavivirus-host PPI mapping provides biological insights and, when coupled with in vivo models, can be used to unravel pathogenic mechanisms.

An Approach to Spatiotemporally Resolve Protein Interaction Networks in Living Cells.

Cells operate through protein interaction networks organized in space and time. Here, we describe an approach to resolve both dimensions simultaneously by using proximity labeling mediated by engineered ascorbic acid peroxidase (APEX). APEX has been used to capture entire organelle proteomes with high temporal resolution, but its breadth of labeling is generally thought to preclude the higher spatial resolution necessary to interrogate specific protein networks. We provide a solution to this problem by combining quantitative proteomics with a system of spatial references. As proof of principle, we apply this approach to interrogate proteins engaged by G-protein-coupled receptors as they dynamically signal and traffic in response to ligand-induced activation. The method resolves known binding partners, as well as previously unidentified network components. Validating its utility as a discovery pipeline, we establish that two of these proteins promote ubiquitin-linked receptor downregulation after prolonged activation.

Brahma safeguards canalization of cardiac mesoderm differentiation.

Differentiation proceeds along a continuum of increasingly fate-restricted intermediates, referred to as canalization1,2. Canalization is essential for stabilizing cell fate, but the mechanisms that underlie robust canalization are unclear. Here we show that the BRG1/BRM-associated factor (BAF) chromatin-remodelling complex ATPase gene Brm safeguards cell identity during directed cardiogenesis of mouse embryonic stem cells. Despite the establishment of a well-differentiated precardiac mesoderm, Brm-/- cells predominantly became neural precursors, violating germ layer assignment. Trajectory inference showed a sudden acquisition of a non-mesodermal identity in Brm-/- cells. Mechanistically, the loss of Brm prevented de novo accessibility of primed cardiac enhancers while increasing the expression of neurogenic factor POU3F1, preventing the binding of the neural suppressor REST and shifting the composition of BRG1 complexes. The identity switch caused by the Brm mutation was overcome by increasing BMP4 levels during mesoderm induction. Mathematical modelling supports these observations and demonstrates that Brm deletion affects cell fate trajectory by modifying saddle-node bifurcations2. In the mouse embryo, Brm deletion exacerbated mesoderm-deleted Brg1-mutant phenotypes, severely compromising cardiogenesis, and reveals an in vivo role for Brm. Our results show that Brm is a compensable safeguard of the fidelity of mesoderm chromatin states, and support a model in which developmental canalization is not a rigid irreversible path, but a highly plastic trajectory.

Profiling the proximal proteome of the activated µ-opioid receptor.

The µ-opioid receptor (µOR) represents an important target of therapeutic and abused drugs. So far, most understanding of µOR activity has focused on a subset of known signal transducers and regulatory molecules. Yet µOR signaling is coordinated by additional proteins in the interaction network of the activated receptor, which have largely remained invisible given the lack of technologies to interrogate these networks systematically. Here we describe a proteomics and computational approach to map the proximal proteome of the activated µOR and to extract subcellular location, trafficking and functional partners of G-protein-coupled receptor (GPCR) activity. We demonstrate that distinct opioid agonists exert differences in the µOR proximal proteome mediated by endocytosis and endosomal sorting. Moreover, we identify two new µOR network components, EYA4 and KCTD12, which are recruited on the basis of receptor-triggered G-protein activation and might form a previously unrecognized buffering system for G-protein activity broadly modulating cellular GPCR signaling.

A systems approach to infectious disease.

Ongoing social, political and ecological changes in the 21st century have placed more people at risk of life-threatening acute and chronic infections than ever before. The development of new diagnostic, prophylactic, therapeutic and curative strategies is critical to address this burden but is predicated on a detailed understanding of the immensely complex relationship between pathogens and their hosts. Traditional, reductionist approaches to investigate this dynamic often lack the scale and/or scope to faithfully model the dual and co-dependent nature of this relationship, limiting the success of translational efforts. With recent advances in large-scale, quantitative omics methods as well as in integrative analytical strategies, systems biology approaches for the study of infectious disease are quickly forming a new paradigm for how we understand and model host-pathogen relationships for translational applications. Here, we delineate a framework for a systems biology approach to infectious disease in three parts: discovery - the design, collection and analysis of omics data; representation - the iterative modelling, integration and visualization of complex data sets; and application - the interpretation and hypothesis-based inquiry towards translational outcomes.

A SARS-CoV-2 protein interaction map reveals targets for drug repurposing.

A newly described coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the causative agent of coronavirus disease 2019 (COVID-19), has infected over 2.3 million people, led to the death of more than 160,000 individuals and caused worldwide social and economic disruption1,2. There are no antiviral drugs with proven clinical efficacy for the treatment of COVID-19, nor are there any vaccines that prevent infection with SARS-CoV-2, and efforts to develop drugs and vaccines are hampered by the limited knowledge of the molecular details of how SARS-CoV-2 infects cells. Here we cloned, tagged and expressed 26 of the 29 SARS-CoV-2 proteins in human cells and identified the human proteins that physically associated with each of the SARS-CoV-2 proteins using affinity-purification mass spectrometry, identifying 332 high-confidence protein-protein interactions between SARS-CoV-2 and human proteins. Among these, we identify 66 druggable human proteins or host factors targeted by 69 compounds (of which, 29 drugs are approved by the US Food and Drug Administration, 12 are in clinical trials and 28 are preclinical compounds). We screened a subset of these in multiple viral assays and found two sets of pharmacological agents that displayed antiviral activity: inhibitors of mRNA translation and predicted regulators of the sigma-1 and sigma-2 receptors. Further studies of these host-factor-targeting agents, including their combination with drugs that directly target viral enzymes, could lead to a therapeutic regimen to treat COVID-19.

A proximity proteomics pipeline with improved reproducibility and throughput.

Proximity labeling (PL) via biotinylation coupled with mass spectrometry (MS) captures spatial proteomes in cells. Large-scale processing requires a workflow minimizing hands-on time and enhancing quantitative reproducibility. We introduced a scalable PL pipeline integrating automated enrichment of biotinylated proteins in a 96-well plate format. Combining this with optimized quantitative MS based on data-independent acquisition (DIA), we increased sample throughput and improved protein identification and quantification reproducibility. We applied this pipeline to delineate subcellular proteomes across various compartments. Using the 5HT2A serotonin receptor as a model, we studied temporal changes of proximal interaction networks induced by receptor activation. In addition, we modified the pipeline for reduced sample input to accommodate CRISPR-based gene knockout, assessing dynamics of the 5HT2A network in response to perturbation of selected interactors. This PL approach is universally applicable to PL proteomics using biotinylation-based PL enzymes, enhancing throughput and reproducibility of standard protocols.

Smoothened transduces Hedgehog signals via activity-dependent sequestration of PKA catalytic subunits.

The Hedgehog (Hh) pathway is essential for organ development, homeostasis, and regeneration. Dysfunction of this cascade drives several cancers. To control expression of pathway target genes, the G protein-coupled receptor (GPCR) Smoothened (SMO) activates glioma-associated (GLI) transcription factors via an unknown mechanism. Here, we show that, rather than conforming to traditional GPCR signaling paradigms, SMO activates GLI by binding and sequestering protein kinase A (PKA) catalytic subunits at the membrane. This sequestration, triggered by GPCR kinase (GRK)-mediated phosphorylation of SMO intracellular domains, prevents PKA from phosphorylating soluble substrates, releasing GLI from PKA-mediated inhibition. Our work provides a mechanism directly linking Hh signal transduction at the membrane to GLI transcription in the nucleus. This process is more fundamentally similar between species than prevailing hypotheses suggest. The mechanism described here may apply broadly to other GPCR- and PKA-containing cascades in diverse areas of biology.

Transcription Factor GATA4 Regulates Cell Type-Specific Splicing Through Direct Interaction With RNA in Human Induced Pluripotent Stem Cell-Derived Cardiac Progenitors.

BACKGROUND: GATA4 (GATA-binding protein 4), a zinc finger-containing, DNA-binding transcription factor, is essential for normal cardiac development and homeostasis in mice and humans, and mutations in this gene have been reported in human heart defects. Defects in alternative splicing are associated with many heart diseases, yet relatively little is known about how cell type- or cell state-specific alternative splicing is achieved in the heart. Here, we show that GATA4 regulates cell type-specific splicing through direct interaction with RNA and the spliceosome in human induced pluripotent stem cell-derived cardiac progenitors. METHODS: We leveraged a combination of unbiased approaches including affinity purification of GATA4 and mass spectrometry, enhanced cross-linking with immunoprecipitation, electrophoretic mobility shift assays, in vitro splicing assays, and unbiased transcriptomic analysis to uncover GATA4's novel function as a splicing regulator in human induced pluripotent stem cell-derived cardiac progenitors. RESULTS: We found that GATA4 interacts with many members of the spliceosome complex in human induced pluripotent stem cell-derived cardiac progenitors. Enhanced cross-linking with immunoprecipitation demonstrated that GATA4 also directly binds to a large number of mRNAs through defined RNA motifs in a sequence-specific manner. In vitro splicing assays indicated that GATA4 regulates alternative splicing through direct RNA binding, resulting in functionally distinct protein products. Correspondingly, knockdown of GATA4 in human induced pluripotent stem cell-derived cardiac progenitors resulted in differential alternative splicing of genes involved in cytoskeleton organization and calcium ion import, with functional consequences associated with the protein isoforms. CONCLUSIONS: This study shows that in addition to its well described transcriptional function, GATA4 interacts with members of the spliceosome complex and regulates cell type-specific alternative splicing via sequence-specific interactions with RNA. Several genes that have splicing regulated by GATA4 have functional consequences and many are associated with dilated cardiomyopathy, suggesting a novel role for GATA4 in achieving the necessary cardiac proteome in normal and stress-responsive conditions.

MassIVE.quant: a community resource of quantitative mass spectrometry-based proteomics datasets.

MassIVE.quant is a repository infrastructure and data resource for reproducible quantitative mass spectrometry-based proteomics, which is compatible with all mass spectrometry data acquisition types and computational analysis tools. A branch structure enables MassIVE.quant to systematically store raw experimental data, metadata of the experimental design, scripts of the quantitative analysis workflow, intermediate input and output files, as well as alternative reanalyses of the same dataset.

CRL4AMBRA1 targets Elongin C for ubiquitination and degradation to modulate CRL5 signaling.

Multi-subunit cullin-RING ligases (CRLs) are the largest family of ubiquitin E3 ligases in humans. CRL activity is tightly regulated to prevent unintended substrate degradation or autocatalytic degradation of CRL subunits. Using a proteomics strategy, we discovered that CRL4AMBRA1 (CRL substrate receptor denoted in superscript) targets Elongin C (ELOC), the essential adapter protein of CRL5 complexes, for polyubiquitination and degradation. We showed that the ubiquitin ligase function of CRL4AMBRA1 is required to disrupt the assembly and attenuate the ligase activity of human CRL5SOCS3 and HIV-1 CRL5VIF complexes as AMBRA1 depletion leads to hyperactivation of both CRL5 complexes. Moreover, CRL4AMBRA1 modulates interleukin-6/STAT3 signaling and HIV-1 infectivity that are regulated by CRL5SOCS3 and CRL5VIF, respectively. Thus, by discovering a substrate of CRL4AMBRA1, ELOC, the shared adapter of CRL5 ubiquitin ligases, we uncovered a novel CRL cross-regulation pathway.

Proteomic Approaches to Study SARS-CoV-2 Biology and COVID-19 Pathology.

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), was declared a pandemic infection in March 2020. As of December 2020, two COVID-19 vaccines have been authorized for emergency use by the U.S. Food and Drug Administration, but there are no effective drugs to treat COVID-19, and pandemic mitigation efforts like physical distancing have had acute social and economic consequences. In this perspective, we discuss how the proteomic research community can leverage technologies and expertise to address the pandemic by investigating four key areas of study in SARS-CoV-2 biology. Specifically, we discuss how (1) mass spectrometry-based structural techniques can overcome limitations and complement traditional structural approaches to inform the dynamic structure of SARS-CoV-2 proteins, complexes, and virions; (2) virus-host protein-protein interaction mapping can identify the cellular machinery required for SARS-CoV-2 replication; (3) global protein abundance and post-translational modification profiling can characterize signaling pathways that are rewired during infection; and (4) proteomic technologies can aid in biomarker identification, diagnostics, and drug development in order to monitor COVID-19 pathology and investigate treatment strategies. Systems-level high-throughput capabilities of proteomic technologies can yield important insights into SARS-CoV-2 biology that are urgently needed during the pandemic, and more broadly, can inform coronavirus virology and host biology.

A Targeted Mass Spectrometry Strategy for Developing Proteomic Biomarkers: A Case Study of Epithelial Ovarian Cancer.

Protein biomarkers for epithelial ovarian cancer are critical for the early detection of the cancer to improve patient prognosis and for the clinical management of the disease to monitor treatment response and to detect recurrences. Unfortunately, the discovery of protein biomarkers is hampered by the limited availability of reliable and sensitive assays needed for the reproducible quantification of proteins in complex biological matrices such as blood plasma. In recent years, targeted mass spectrometry, exemplified by selected reaction monitoring (SRM) has emerged as a method, capable of overcoming this limitation. Here, we present a comprehensive SRM-based strategy for developing plasma-based protein biomarkers for epithelial ovarian cancer and illustrate how the SRM platform, when combined with rigorous experimental design and statistical analysis, can result in detection of predictive analytes.Our biomarker development strategy first involved a discovery-driven proteomic effort to derive potential N-glycoprotein biomarker candidates for plasma-based detection of human ovarian cancer from a genetically engineered mouse model of endometrioid ovarian cancer, which accurately recapitulates the human disease. Next, 65 candidate markers selected from proteins of different abundance in the discovery dataset were reproducibly quantified with SRM assays across a large cohort of over 200 plasma samples from ovarian cancer patients and healthy controls. Finally, these measurements were used to derive a 5-protein signature for distinguishing individuals with epithelial ovarian cancer from healthy controls. The sensitivity of the candidate biomarker signature in combination with CA125 ELISA-based measurements currently used in clinic, exceeded that of CA125 ELISA-based measurements alone. The SRM-based strategy in this study is broadly applicable. It can be used in any study that requires accurate and reproducible quantification of selected proteins in a high-throughput and multiplexed fashion.

Targeted peptide measurements in biology and medicine: best practices for mass spectrometry-based assay development using a fit-for-purpose approach.

Adoption of targeted mass spectrometry (MS) approaches such as multiple reaction monitoring (MRM) to study biological and biomedical questions is well underway in the proteomics community. Successful application depends on the ability to generate reliable assays that uniquely and confidently identify target peptides in a sample. Unfortunately, there is a wide range of criteria being applied to say that an assay has been successfully developed. There is no consensus on what criteria are acceptable and little understanding of the impact of variable criteria on the quality of the results generated. Publications describing targeted MS assays for peptides frequently do not contain sufficient information for readers to establish confidence that the tests work as intended or to be able to apply the tests described in their own labs. Guidance must be developed so that targeted MS assays with established performance can be made widely distributed and applied by many labs worldwide. To begin to address the problems and their solutions, a workshop was held at the National Institutes of Health with representatives from the multiple communities developing and employing targeted MS assays. Participants discussed the analytical goals of their experiments and the experimental evidence needed to establish that the assays they develop work as intended and are achieving the required levels of performance. Using this "fit-for-purpose" approach, the group defined three tiers of assays distinguished by their performance and extent of analytical characterization. Computational and statistical tools useful for the analysis of targeted MS results were described. Participants also detailed the information that authors need to provide in their manuscripts to enable reviewers and readers to clearly understand what procedures were performed and to evaluate the reliability of the peptide or protein quantification measurements reported. This paper presents a summary of the meeting and recommendations.

N-glycoprotein SRMAtlas: a resource of mass spectrometric assays for N-glycosites enabling consistent and multiplexed protein quantification for clinical applications.

Protein biomarkers have the potential to transform medicine as they are clinically used to diagnose diseases, stratify patients, and follow disease states. Even though a large number of potential biomarkers have been proposed over the past few years, almost none of them have been implemented so far in the clinic. One of the reasons for this limited success is the lack of technologies to validate proposed biomarker candidates in larger patient cohorts. This limitation could be alleviated by the use of antibody-independent validation methods such as selected reaction monitoring (SRM). Similar to measurements based on affinity reagents, SRM-based targeted mass spectrometry also requires the generation of definitive assays for each targeted analyte. Here, we present a library of SRM assays for 5568 N-glycosites enabling the multiplexed evaluation of clinically relevant N-glycoproteins as biomarker candidates. We demonstrate that this resource can be utilized to select SRM assay sets for cancer-associated N-glycoproteins for their subsequent multiplexed and consistent quantification in 120 human plasma samples. We show that N-glycoproteins spanning 5 orders of magnitude in abundance can be quantified and that previously reported abundance differences in various cancer types can be recapitulated. Together, the established N-glycoprotein SRMAtlas resource facilitates parallel, efficient, consistent, and sensitive evaluation of proposed biomarker candidates in large clinical sample cohorts.

mProphet: automated data processing and statistical validation for large-scale SRM experiments.

Selected reaction monitoring (SRM) is a targeted mass spectrometric method that is increasingly used in proteomics for the detection and quantification of sets of preselected proteins at high sensitivity, reproducibility and accuracy. Currently, data from SRM measurements are mostly evaluated subjectively by manual inspection on the basis of ad hoc criteria, precluding the consistent analysis of different data sets and an objective assessment of their error rates. Here we present mProphet, a fully automated system that computes accurate error rates for the identification of targeted peptides in SRM data sets and maximizes specificity and sensitivity by combining relevant features in the data into a statistical model.