Architecture of the outbred brown fat proteome defines regulators of metabolic physiology.

Brown adipose tissue (BAT) regulates metabolic physiology. However, nearly all mechanistic studies of BAT protein function occur in a single inbred mouse strain, which has limited the understanding of generalizable mechanisms of BAT regulation over physiology. Here, we perform deep quantitative proteomics of BAT across a cohort of 163 genetically defined diversity outbred mice, a model that parallels the genetic and phenotypic variation found in humans. We leverage this diversity to define the functional architecture of the outbred BAT proteome, comprising 10,479 proteins. We assign co-operative functions to 2,578 proteins, enabling systematic discovery of regulators of BAT. We also identify 638 proteins that correlate with protection from, or sensitivity to, at least one parameter of metabolic disease. We use these findings to uncover SFXN5, LETMD1, and ATP1A2 as modulators of BAT thermogenesis or adiposity, and provide OPABAT as a resource for understanding the conserved mechanisms of BAT regulation over metabolic physiology.

Dual proteome-scale networks reveal cell-specific remodeling of the human interactome.

Thousands of interactions assemble proteins into modules that impart spatial and functional organization to the cellular proteome. Through affinity-purification mass spectrometry, we have created two proteome-scale, cell-line-specific interaction networks. The first, BioPlex 3.0, results from affinity purification of 10,128 human proteins-half the proteome-in 293T cells and includes 118,162 interactions among 14,586 proteins. The second results from 5,522 immunoprecipitations in HCT116 cells. These networks model the interactome whose structure encodes protein function, localization, and complex membership. Comparison across cell lines validates thousands of interactions and reveals extensive customization. Whereas shared interactions reside in core complexes and involve essential proteins, cell-specific interactions link these complexes, "rewiring" subnetworks within each cell's interactome. Interactions covary among proteins of shared function as the proteome remodels to produce each cell's phenotype. Viewable interactively online through BioPlexExplorer, these networks define principles of proteome organization and enable unknown protein characterization.

A Quantitative Tissue-Specific Landscape of Protein Redox Regulation during Aging.

Mammalian tissues engage in specialized physiology that is regulated through reversible modification of protein cysteine residues by reactive oxygen species (ROS). ROS regulate a myriad of biological processes, but the protein targets of ROS modification that drive tissue-specific physiology in vivo are largely unknown. Here, we develop Oximouse, a comprehensive and quantitative mapping of the mouse cysteine redox proteome in vivo. We use Oximouse to establish several paradigms of physiological redox signaling. We define and validate cysteine redox networks within each tissue that are tissue selective and underlie tissue-specific biology. We describe a common mechanism for encoding cysteine redox sensitivity by electrostatic gating. Moreover, we comprehensively identify redox-modified disease networks that remodel in aged mice, establishing a systemic molecular basis for the long-standing proposed links between redox dysregulation and tissue aging. We provide the Oximouse compendium as a framework for understanding mechanisms of redox regulation in physiology and aging.

An Epstein-Barr virus protein interaction map reveals NLRP3 inflammasome evasion via MAVS UFMylation.

Epstein-Barr virus (EBV) causes infectious mononucleosis, triggers multiple sclerosis, and is associated with 200,000 cancers/year. EBV colonizes the human B cell compartment and periodically reactivates, inducing expression of 80 viral proteins. However, much remains unknown about how EBV remodels host cells and dismantles key antiviral responses. We therefore created a map of EBV-host and EBV-EBV interactions in B cells undergoing EBV replication, uncovering conserved herpesvirus versus EBV-specific host cell targets. The EBV-encoded G-protein-coupled receptor BILF1 associated with MAVS and the UFM1 E3 ligase UFL1. Although UFMylation of 14-3-3 proteins drives RIG-I/MAVS signaling, BILF1-directed MAVS UFMylation instead triggered MAVS packaging into mitochondrial-derived vesicles and lysosomal proteolysis. In the absence of BILF1, EBV replication activated the NLRP3 inflammasome, which impaired viral replication and triggered pyroptosis. Our results provide a viral protein interaction network resource, reveal a UFM1-dependent pathway for selective degradation of mitochondrial cargo, and highlight BILF1 as a novel therapeutic target.

The BioPlex Network: A Systematic Exploration of the Human Interactome.

Protein interactions form a network whose structure drives cellular function and whose organization informs biological inquiry. Using high-throughput affinity-purification mass spectrometry, we identify interacting partners for 2,594 human proteins in HEK293T cells. The resulting network (BioPlex) contains 23,744 interactions among 7,668 proteins with 86% previously undocumented. BioPlex accurately depicts known complexes, attaining 80%-100% coverage for most CORUM complexes. The network readily subdivides into communities that correspond to complexes or clusters of functionally related proteins. More generally, network architecture reflects cellular localization, biological process, and molecular function, enabling functional characterization of thousands of proteins. Network structure also reveals associations among thousands of protein domains, suggesting a basis for examining structurally related proteins. Finally, BioPlex, in combination with other approaches, can be used to reveal interactions of biological or clinical significance. For example, mutations in the membrane protein VAPB implicated in familial amyotrophic lateral sclerosis perturb a defined community of interactors.

Quantitative temporal viromics: an approach to investigate host-pathogen interaction.

A systematic quantitative analysis of temporal changes in host and viral proteins throughout the course of a productive infection could provide dynamic insights into virus-host interaction. We developed a proteomic technique called "quantitative temporal viromics" (QTV), which employs multiplexed tandem-mass-tag-based mass spectrometry. Human cytomegalovirus (HCMV) is not only an important pathogen but a paradigm of viral immune evasion. QTV detailed how HCMV orchestrates the expression of >8,000 cellular proteins, including 1,200 cell-surface proteins to manipulate signaling pathways and counterintrinsic, innate, and adaptive immune defenses. QTV predicted natural killer and T cell ligands, as well as 29 viral proteins present at the cell surface, potential therapeutic targets. Temporal profiles of >80% of HCMV canonical genes and 14 noncanonical HCMV open reading frames were defined. QTV is a powerful method that can yield important insights into viral infection and is applicable to any virus with a robust in vitro model.

Proteome-wide mapping of short-lived proteins in human cells.

Rapid protein degradation enables cells to quickly modulate protein abundance. Dysregulation of short-lived proteins plays essential roles in disease pathogenesis. A focused map of short-lived proteins remains understudied. Cycloheximide, a translational inhibitor, is widely used in targeted studies to measure degradation kinetics for short-lived proteins. Here, we combined cycloheximide chase assays with advanced quantitative proteomics to map short-lived proteins under translational inhibition in four human cell lines. Among 11,747 quantified proteins, we identified 1,017 short-lived proteins (half-lives ≤ 8 h). These short-lived proteins are less abundant, evolutionarily younger, and less thermally stable than other proteins. We quantified 103 proteins with different stabilities among cell lines. We showed that U2OS and HCT116 cells express truncated forms of ATRX and GMDS, respectively, which have lower stability than their full-length counterparts. This study provides a large-scale resource of human short-lived proteins under translational arrest, leading to untapped avenues of protein regulation for therapeutic interventions.

A multi-scale map of cell structure fusing protein images and interactions.

The cell is a multi-scale structure with modular organization across at least four orders of magnitude1. Two central approaches for mapping this structure-protein fluorescent imaging and protein biophysical association-each generate extensive datasets, but of distinct qualities and resolutions that are typically treated separately2,3. Here we integrate immunofluorescence images in the Human Protein Atlas4 with affinity purifications in BioPlex5 to create a unified hierarchical map of human cell architecture. Integration is achieved by configuring each approach as a general measure of protein distance, then calibrating the two measures using machine learning. The map, known as the multi-scale integrated cell (MuSIC 1.0), resolves 69 subcellular systems, of which approximately half are to our knowledge undocumented. Accordingly, we perform 134 additional affinity purifications and validate subunit associations for the majority of systems. The map reveals a pre-ribosomal RNA processing assembly and accessory factors, which we show govern rRNA maturation, and functional roles for SRRM1 and FAM120C in chromatin and RPS3A in splicing. By integration across scales, MuSIC increases the resolution of imaging while giving protein interactions a spatial dimension, paving the way to incorporate diverse types of data in proteome-wide cell maps.

Profiling Proteins and Phosphorylation Sites During T Cell Activation Using an Integrated Thermal Shift Assay.

T cell activation is a complex biological process of naive cells maturing into effector cells. Proteomic and phospho-proteomic approaches have provided critical insights into this process, yet it is not always clear how changes in individual proteins or phosphorylation sites have functional significance. Here, we developed the Phosphorylation Integrated Thermal Shift Assay (PITSA) that combines the measurement of protein or phosphorylation site abundance and thermal stability into a single tandem mass tags experiment and apply this method to study T cell activation. We quantified the abundance and thermal stability of over 7500 proteins and 5000 phosphorylation sites and identified significant differences in chromatin-related, TCR signaling, DNA repair, and proliferative phosphoproteins. PITSA may be applied to a wide range of biological contexts to generate hypotheses as to which proteins or phosphorylation sites are functionally regulated in a given system as well as the mechanisms by which this regulation may occur.

A multi-purpose, regenerable, proteome-scale, human phosphoserine resource for phosphoproteomics.

Mass-spectrometry-based phosphoproteomics has become indispensable for understanding cellular signaling in complex biological systems. Despite the central role of protein phosphorylation, the field still lacks inexpensive, regenerable, and diverse phosphopeptides with ground-truth phosphorylation positions. Here, we present Iterative Synthetically Phosphorylated Isomers (iSPI), a proteome-scale library of human-derived phosphoserine-containing phosphopeptides that is inexpensive, regenerable, and diverse, with precisely known positions of phosphorylation. We demonstrate possible uses of iSPI, including use as a phosphopeptide standard, a tool to evaluate and optimize phosphorylation-site localization algorithms, and a benchmark to compare performance across data analysis pipelines. We also present AScorePro, an updated version of the AScore algorithm specifically optimized for phosphorylation-site localization in higher energy fragmentation spectra, and the FLR viewer, a web tool for phosphorylation-site localization, to enable community use of the iSPI resource. iSPI and its associated data constitute a useful, multi-purpose resource for the phosphoproteomics community.

A tissue-specific atlas of mouse protein phosphorylation and expression.

Although most tissues in an organism are genetically identical, the biochemistry of each is optimized to fulfill its unique physiological roles, with important consequences for human health and disease. Each tissue's unique physiology requires tightly regulated gene and protein expression coordinated by specialized, phosphorylation-dependent intracellular signaling. To better understand the role of phosphorylation in maintenance of physiological differences among tissues, we performed proteomic and phosphoproteomic characterizations of nine mouse tissues. We identified 12,039 proteins, including 6296 phosphoproteins harboring nearly 36,000 phosphorylation sites. Comparing protein abundances and phosphorylation levels revealed specialized, interconnected phosphorylation networks within each tissue while suggesting that many proteins are regulated by phosphorylation independently of their expression. Our data suggest that the "typical" phosphoprotein is widely expressed yet displays variable, often tissue-specific phosphorylation that tunes protein activity to the specific needs of each tissue. We offer this dataset as an online resource for the biological research community.

BioPlexR and BioPlexPy: integrated data products for the analysis of human protein interactions.

SUMMARY: The BioPlex project has created two proteome scale, cell-line-specific protein-protein interaction (PPI) networks: the first in 293T cells, including 120k interactions among 15k proteins; and the second in HCT116 cells, including 70k interactions between 10k proteins. Here, we describe programmatic access to the BioPlex PPI networks and integration with related resources from within R and Python. Besides PPI networks for 293T and HCT116 cells, this includes access to CORUM protein complex data, PFAM protein domain data, PDB protein structures, and transcriptome and proteome data for the two cell lines. The implemented functionality serves as a basis for integrative downstream analysis of BioPlex PPI data with domain-specific R and Python packages, including efficient execution of maximum scoring sub-network analysis, protein domain-domain association analysis, mapping of PPIs onto 3D protein structures and analysis of BioPlex PPIs at the interface of transcriptomic and proteomic data. AVAILABILITY AND IMPLEMENTATION: The BioPlex R package is available from Bioconductor (bioconductor.org/packages/BioPlex), and the BioPlex Python package is available from PyPI (pypi.org/project/bioplexpy). Applications and downstream analyses are available from GitHub (github.com/ccb-hms/BioPlexAnalysis).

TMTpro reagents: a set of isobaric labeling mass tags enables simultaneous proteome-wide measurements across 16 samples.

Isobaric labeling empowers proteome-wide expression measurements simultaneously across multiple samples. Here an expanded set of 16 isobaric reagents based on an isobutyl-proline immonium ion reporter structure (TMTpro) is presented. These reagents have similar characteristics to existing tandem mass tag reagents but with increased fragmentation efficiency and signal. In a proteome-scale example dataset, we compared eight common cell lines with and without Torin1 treatment with three replicates, quantifying more than 8,800 proteins (mean of 7.5 peptides per protein) per replicate with an analysis time of only 1.1 h per proteome. Finally, we modified the thermal stability assay to examine proteome-wide melting shifts after treatment with DMSO, 1 or 20 µM staurosporine with five replicates. This assay identified and dose-stratified staurosporine binding to 228 cellular kinases in just one, 18-h experiment. TMTpro reagents allow complex experimental designs-all with essentially no missing values across the 16 samples and no loss in quantitative integrity.

Architecture of the human interactome defines protein communities and disease networks.

The physiology of a cell can be viewed as the product of thousands of proteins acting in concert to shape the cellular response. Coordination is achieved in part through networks of protein-protein interactions that assemble functionally related proteins into complexes, organelles, and signal transduction pathways. Understanding the architecture of the human proteome has the potential to inform cellular, structural, and evolutionary mechanisms and is critical to elucidating how genome variation contributes to disease. Here we present BioPlex 2.0 (Biophysical Interactions of ORFeome-derived complexes), which uses robust affinity purification-mass spectrometry methodology to elucidate protein interaction networks and co-complexes nucleated by more than 25% of protein-coding genes from the human genome, and constitutes, to our knowledge, the largest such network so far. With more than 56,000 candidate interactions, BioPlex 2.0 contains more than 29,000 previously unknown co-associations and provides functional insights into hundreds of poorly characterized proteins while enhancing network-based analyses of domain associations, subcellular localization, and co-complex formation. Unsupervised Markov clustering of interacting proteins identified more than 1,300 protein communities representing diverse cellular activities. Genes essential for cell fitness are enriched within 53 communities representing central cellular functions. Moreover, we identified 442 communities associated with more than 2,000 disease annotations, placing numerous candidate disease genes into a cellular framework. BioPlex 2.0 exceeds previous experimentally derived interaction networks in depth and breadth, and will be a valuable resource for exploring the biology of incompletely characterized proteins and for elucidating larger-scale patterns of proteome organization.

Quantitative Proteomic Atlas of Ubiquitination and Acetylation in the DNA Damage Response.

Execution of the DNA damage response (DDR) relies upon a dynamic array of protein modifications. Using quantitative proteomics, we have globally profiled ubiquitination, acetylation, and phosphorylation in response to UV and ionizing radiation. To improve acetylation site profiling, we developed the strategy FACET-IP. Our datasets of 33,500 ubiquitination and 16,740 acetylation sites provide valuable insight into DDR remodeling of the proteome. We find that K6- and K33-linked polyubiquitination undergo bulk increases in response to DNA damage, raising the possibility that these linkages are largely dedicated to DDR function. We also show that Cullin-RING ligases mediate 10% of DNA damage-induced ubiquitination events and that EXO1 is an SCF-Cyclin F substrate in the response to UV radiation. Our extensive datasets uncover additional regulated sites on known DDR players such as PCNA and identify previously unknown DDR targets such as CENPs, underscoring the broad impact of the DDR on cellular physiology.

Defining the consequences of genetic variation on a proteome-wide scale.

Genetic variation modulates protein expression through both transcriptional and post-transcriptional mechanisms. To characterize the consequences of natural genetic diversity on the proteome, here we combine a multiplexed, mass spectrometry-based method for protein quantification with an emerging outbred mouse model containing extensive genetic variation from eight inbred founder strains. By measuring genome-wide transcript and protein expression in livers from 192 Diversity outbred mice, we identify 2,866 protein quantitative trait loci (pQTL) with twice as many local as distant genetic variants. These data support distinct transcriptional and post-transcriptional models underlying the observed pQTL effects. Using a sensitive approach to mediation analysis, we often identified a second protein or transcript as the causal mediator of distant pQTL. Our analysis reveals an extensive network of direct protein-protein interactions. Finally, we show that local genotype can provide accurate predictions of protein abundance in an independent cohort of collaborative cross mice.

Proteomic analysis of cap-dependent translation identifies LARP1 as a key regulator of 5'TOP mRNA translation.

The mammalian target of rapamycin (mTOR) promotes cell growth and proliferation by promoting mRNA translation and increasing the protein synthetic capacity of the cell. Although mTOR globally promotes translation by regulating the mRNA 5' cap-binding protein eIF4E (eukaryotic initiation factor 4E), it also preferentially regulates the translation of certain classes of mRNA via unclear mechanisms. To help fill this gap in knowledge, we performed a quantitative proteomic screen to identify proteins that associate with the mRNA 5' cap in an mTOR-dependent manner. Using this approach, we identified many potential regulatory factors, including the putative RNA-binding protein LARP1 (La-related protein 1). Our results indicate that LARP1 associates with actively translating ribosomes via PABP and that LARP1 stimulates the translation of mRNAs containing a 5' terminal oligopyrimidine (TOP) motif, encoding for components of the translational machinery. We found that LARP1 associates with the mTOR complex 1 (mTORC1) and is required for global protein synthesis as well as cell growth and proliferation. Together, these data reveal important molecular mechanisms involved in TOP mRNA translation and implicate LARP1 as an important regulator of cell growth and proliferation.

Selection of Heating Temperatures Improves the Sensitivity of the Proteome Integral Solubility Alteration Assay.

The thermal shift assay is a robust method of discovering protein-ligand interactions by measuring the alterations in protein thermal stability under various conditions. Several thermal shift assays have been developed and their throughput has been advanced greatly by the rapid progress in tandem mass tag-based quantitative proteomics. A recent paper by Gaetani et al. ( J. Proteome Res. 2019, 18 (11), 4027-4037) introduced the proteome integral solubility alteration (PISA) assay, further increasing throughput and simplifying the data analysis. Both ΔSm (a proxy of the difference between areas under the melting curves) and fold changes (ratios between integral samples) are readouts of the PISA assay and positively related to ΔTm (shift in melting temperatures). Here, we show that the magnitudes of these readouts are inherently small in PISA assay, which is a challenge for quantitation. Both simulation and experimental results show that the selection of a subset of heating temperatures ameliorates the small difference problem and improves the sensitivity of the PISA assay.

Full-Featured, Real-Time Database Searching Platform Enables Fast and Accurate Multiplexed Quantitative Proteomics.

Multiplexed quantitative analyses of complex proteomes enable deep biological insight. While a multitude of workflows have been developed for multiplexed analyses, the most quantitatively accurate method (SPS-MS3) suffers from long acquisition duty cycles. We built a new, real-time database search (RTS) platform, Orbiter, to combat the SPS-MS3 method's longer duty cycles. RTS with Orbiter eliminates SPS-MS3 scans if no peptide matches to a given spectrum. With Orbiter's online proteomic analytical pipeline, which includes RTS and false discovery rate analysis, it was possible to process a single spectrum database search in less than 10 ms. The result is a fast, functional means to identify peptide spectral matches using Comet, filter these matches, and more efficiently quantify proteins of interest. Importantly, the use of Comet for peptide spectral matching allowed for a fully featured search, including analysis of post-translational modifications, with well-known and extensively validated scoring. These data could then be used to trigger subsequent scans in an adaptive and flexible manner. In this work we tested the utility of this adaptive data acquisition platform to improve the efficiency and accuracy of multiplexed quantitative experiments. We found that RTS enabled a 2-fold increase in mass spectrometric data acquisition efficiency. Orbiter's RTS quantified more than 8000 proteins across 10 proteomes in half the time of an SPS-MS3 analysis (18 h for RTS, 36 h for SPS-MS3).