Dynamic mapping of proteome trafficking within and between living cells by TransitID.

The ability to map trafficking for thousands of endogenous proteins at once in living cells would reveal biology currently invisible to both microscopy and mass spectrometry. Here, we report TransitID, a method for unbiased mapping of endogenous proteome trafficking with nanometer spatial resolution in living cells. Two proximity labeling (PL) enzymes, TurboID and APEX, are targeted to source and destination compartments, and PL with each enzyme is performed in tandem via sequential addition of their small-molecule substrates. Mass spectrometry identifies the proteins tagged by both enzymes. Using TransitID, we mapped proteome trafficking between cytosol and mitochondria, cytosol and nucleus, and nucleolus and stress granules (SGs), uncovering a role for SGs in protecting the transcription factor JUN from oxidative stress. TransitID also identifies proteins that signal intercellularly between macrophages and cancer cells. TransitID offers a powerful approach for distinguishing protein populations based on compartment or cell type of origin.

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 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.

Quantitative Proteomics of the Cancer Cell Line Encyclopedia.

Proteins are essential agents of biological processes. To date, large-scale profiling of cell line collections including the Cancer Cell Line Encyclopedia (CCLE) has focused primarily on genetic information whereas deep interrogation of the proteome has remained out of reach. Here, we expand the CCLE through quantitative profiling of thousands of proteins by mass spectrometry across 375 cell lines from diverse lineages to reveal information undiscovered by DNA and RNA methods. We observe unexpected correlations within and between pathways that are largely absent from RNA. An analysis of microsatellite instable (MSI) cell lines reveals the dysregulation of specific protein complexes associated with surveillance of mutation and translation. These and other protein complexes were associated with sensitivity to knockdown of several different genes. These data in conjunction with the wider CCLE are a broad resource to explore cellular behavior and facilitate cancer research.

FAMIN Is a Multifunctional Purine Enzyme Enabling the Purine Nucleotide Cycle.

Mutations in FAMIN cause arthritis and inflammatory bowel disease in early childhood, and a common genetic variant increases the risk for Crohn's disease and leprosy. We developed an unbiased liquid chromatography-mass spectrometry screen for enzymatic activity of this orphan protein. We report that FAMIN phosphorolytically cleaves adenosine into adenine and ribose-1-phosphate. Such activity was considered absent from eukaryotic metabolism. FAMIN and its prokaryotic orthologs additionally have adenosine deaminase, purine nucleoside phosphorylase, and S-methyl-5'-thioadenosine phosphorylase activity, hence, combine activities of the namesake enzymes of central purine metabolism. FAMIN enables in macrophages a purine nucleotide cycle (PNC) between adenosine and inosine monophosphate and adenylosuccinate, which consumes aspartate and releases fumarate in a manner involving fatty acid oxidation and ATP-citrate lyase activity. This macrophage PNC synchronizes mitochondrial activity with glycolysis by balancing electron transfer to mitochondria, thereby supporting glycolytic activity and promoting oxidative phosphorylation and mitochondrial H+ and phosphate recycling.

Integrative Structure Modeling: Overview and Assessment.

Integrative structure modeling computationally combines data from multiple sources of information with the aim of obtaining structural insights that are not revealed by any single approach alone. In the first part of this review, we survey the commonly used sources of structural information and the computational aspects of model building. Throughout the past decade, integrative modeling was applied to various biological systems, with a focus on large protein complexes. Recent progress in the field of cryo-electron microscopy (cryo-EM) has resolved many of these complexes to near-atomic resolution. In the second part of this review, we compare a range of published integrative models with their higher-resolution counterparts with the aim of critically assessing their accuracy. This comparison gives a favorable view of integrative modeling and demonstrates its ability to yield accurate and informative results. We discuss possible roles of integrative modeling in the new era of cryo-EM and highlight future challenges and directions.

Biophysical Techniques in Structural Biology.

Over the past six decades, steadily increasing progress in the application of the principles and techniques of the physical sciences to the study of biological systems has led to remarkable insights into the molecular basis of life. Of particular significance has been the way in which the determination of the structures and dynamical properties of proteins and nucleic acids has so often led directly to a profound understanding of the nature and mechanism of their functional roles. The increasing number and power of experimental and theoretical techniques that can be applied successfully to living systems is now ushering in a new era of structural biology that is leading to fundamentally new information about the maintenance of health, the origins of disease, and the development of effective strategies for therapeutic intervention. This article provides a brief overview of some of the most powerful biophysical methods in use today, along with references that provide more detailed information about recent applications of each of them. In addition, this article acts as an introduction to four authoritative reviews in this volume. The first shows the ways that a multiplicity of biophysical methods can be combined with computational techniques to define the architectures of complex biological systems, such as those involving weak interactions within ensembles of molecular components. The second illustrates one aspect of this general approach by describing how recent advances in mass spectrometry, particularly in combination with other techniques, can generate fundamentally new insights into the properties of membrane proteins and their functional interactions with lipid molecules. The third reviewdemonstrates the increasing power of rapidly evolving diffraction techniques, employing the very short bursts of X-rays of extremely high intensity that are now accessible as a result of the construction of free-electron lasers, in particular to carry out time-resolved studies of biochemical reactions. The fourth describes in detail the application of such approaches to probe the mechanism of the light-induced changes associated with bacteriorhodopsin's ability to convert light energy into chemical energy.

Membrane Protein-Lipid Interactions Probed Using Mass Spectrometry.

Membrane proteins that exist in lipid bilayers are not isolated molecular entities. The lipid molecules that surround them play crucial roles in maintaining their full structural and functional integrity. Research directed at investigating these critical lipid-protein interactions is developing rapidly. Advancements in both instrumentation and software, as well as in key biophysical and biochemical techniques, are accelerating the field. In this review, we provide a brief outline of structural techniques used to probe protein-lipid interactions and focus on the molecular aspects of these interactions obtained from native mass spectrometry (native MS). We highlight examples in which lipids have been shown to modulate membrane protein structure and show how native MS has emerged as a complementary technique to X-ray crystallography and cryo-electron microscopy. We conclude with a short perspective on future developments that aim to better understand protein-lipid interactions in the native environment.

Oncogenic Mutations Rewire Signaling Pathways by Switching Protein Recruitment to Phosphotyrosine Sites.

Tyrosine phosphorylation regulates multi-layered signaling networks with broad implications in (patho)physiology, but high-throughput methods for functional annotation of phosphotyrosine sites are lacking. To decipher phosphotyrosine signaling directly in tissue samples, we developed a mass-spectrometry-based interaction proteomics approach. We measured the in vivo EGF-dependent signaling network in lung tissue quantifying >1,000 phosphotyrosine sites. To assign function to all EGF-regulated sites, we determined their recruited protein signaling complexes in lung tissue by interaction proteomics. We demonstrated how mutations near tyrosine residues introduce molecular switches that rewire cancer signaling networks, and we revealed oncogenic properties of such a lung cancer EGFR mutant. To demonstrate the scalability of the approach, we performed >1,000 phosphopeptide pulldowns and analyzed them by rapid mass spectrometric analysis, revealing tissue-specific differences in interactors. Our approach is a general strategy for functional annotation of phosphorylation sites in tissues, enabling in-depth mechanistic insights into oncogenic rewiring of signaling networks.

Protein Barcodes Enable High-Dimensional Single-Cell CRISPR Screens.

CRISPR pools are being widely employed to identify gene functions. However, current technology, which utilizes DNA as barcodes, permits limited phenotyping and bulk-cell resolution. To enable novel screening capabilities, we developed a barcoding system operating at the protein level. We synthesized modules encoding triplet combinations of linear epitopes to generate >100 unique protein barcodes (Pro-Codes). Pro-Code-expressing vectors were introduced into cells and analyzed by CyTOF mass cytometry. Using just 14 antibodies, we detected 364 Pro-Code populations; establishing the largest set of protein-based reporters. By pairing each Pro-Code with a different CRISPR, we simultaneously analyzed multiple phenotypic markers, including phospho-signaling, on dozens of knockouts. Pro-Code/CRISPR screens found two interferon-stimulated genes, the immunoproteasome component Psmb8 and a chaperone Rtp4, are important for antigen-dependent immune editing of cancer cells and identified Socs1 as a negative regulator of Pd-l1. The Pro-Code technology enables simultaneous high-dimensional protein-level phenotyping of 100s of genes with single-cell resolution.

Proteomics of the heart.

Mass spectrometry-based proteomics is a sophisticated identification tool specializing in portraying protein dynamics at a molecular level. Proteomics provides biologists with a snapshot of context-dependent protein and proteoform expression, structural conformations, dynamic turnover, and protein-protein interactions. Cardiac proteomics can offer a broader and deeper understanding of the molecular mechanisms that underscore cardiovascular disease, and it is foundational to the development of future therapeutic interventions. This review encapsulates the evolution, current technologies, and future perspectives of proteomic-based mass spectrometry as it applies to the study of the heart. Key technological advancements have allowed researchers to study proteomes at a single-cell level and employ robot-assisted automation systems for enhanced sample preparation techniques, and the increase in fidelity of the mass spectrometers has allowed for the unambiguous identification of numerous dynamic posttranslational modifications. Animal models of cardiovascular disease, ranging from early animal experiments to current sophisticated models of heart failure with preserved ejection fraction, have provided the tools to study a challenging organ in the laboratory. Further technological development will pave the way for the implementation of proteomics even closer within the clinical setting, allowing not only scientists but also patients to benefit from an understanding of protein interplay as it relates to cardiac disease physiology.

Quantitative interactomics in primary T cells unveils TCR signal diversification extent and dynamics.

The activation of T cells by the T cell antigen receptor (TCR) results in the formation of signaling protein complexes (signalosomes), the composition of which has not been analyzed at a systems level. Here, we isolated primary CD4+ T cells from 15 gene-targeted mice, each expressing one tagged form of a canonical protein of the TCR-signaling pathway. Using affinity purification coupled with mass spectrometry, we analyzed the composition and dynamics of the signalosomes assembling around each of the tagged proteins over 600 s of TCR engagement. We showed that the TCR signal-transduction network comprises at least 277 unique proteins involved in 366 high-confidence interactions, and that TCR signals diversify extensively at the level of the plasma membrane. Integrating the cellular abundance of the interacting proteins and their interaction stoichiometry provided a quantitative and contextual view of each documented interaction, permitting anticipation of whether ablation of a single interacting protein can impinge on the whole TCR signal-transduction network.

Mass Cytometry: Single Cells, Many Features.

Technology development in biological research often aims to either increase the number of cellular features that can be surveyed simultaneously or enhance the resolution at which such observations are possible. For decades, flow cytometry has balanced these goals to fill a critical need by enabling the measurement of multiple features in single cells, commonly to examine complex or hierarchical cellular systems. Recently, a format for flow cytometry has been developed that leverages the precision of mass spectrometry. This fusion of the two technologies, termed mass cytometry, provides measurement of over 40 simultaneous cellular parameters at single-cell resolution, significantly augmenting the ability of cytometry to evaluate complex cellular systems and processes. In this Primer, we review the current state of mass cytometry, providing an overview of the instrumentation, its present capabilities, and methods of data analysis, as well as thoughts on future developments and applications.

Systematic discovery of Xist RNA binding proteins.

Noncoding RNAs (ncRNAs) function with associated proteins to effect complex structural and regulatory outcomes. To reveal the composition and dynamics of specific noncoding RNA-protein complexes (RNPs) in vivo, we developed comprehensive identification of RNA binding proteins by mass spectrometry (ChIRP-MS). ChIRP-MS analysis of four ncRNAs captures key protein interactors, including a U1-specific link to the 3' RNA processing machinery. Xist, an essential lncRNA for X chromosome inactivation (XCI), interacts with 81 proteins from chromatin modification, nuclear matrix, and RNA remodeling pathways. The Xist RNA-protein particle assembles in two steps coupled with the transition from pluripotency to differentiation. Specific interactors include HnrnpK, which participates in Xist-mediated gene silencing and histone modifications but not Xist localization, and Drosophila Split ends homolog Spen, which interacts via the A-repeat domain of Xist and is required for gene silencing. Thus, Xist lncRNA engages with proteins in a modular and developmentally controlled manner to coordinate chromatin spreading and silencing.

Unbiased spatial proteomics with single-cell resolution in tissues.

Mass spectrometry (MS)-based proteomics has become a powerful technology to quantify the entire complement of proteins in cells or tissues. Here, we review challenges and recent advances in the LC-MS-based analysis of minute protein amounts, down to the level of single cells. Application of this technology revealed that single-cell transcriptomes are dominated by stochastic noise due to the very low number of transcripts per cell, whereas the single-cell proteome appears to be complete. The spatial organization of cells in tissues can be studied by emerging technologies, including multiplexed imaging and spatial transcriptomics, which can now be combined with ultra-sensitive proteomics. Combined with high-content imaging, artificial intelligence and single-cell laser microdissection, MS-based proteomics provides an unbiased molecular readout close to the functional level. Potential applications range from basic biological questions to precision medicine.

A tri-functional amino acid enables mapping of binding sites for posttranslational-modification-mediated protein-protein interactions.

Posttranslational modification (PTM), through the recruitment of effector proteins (i.e., "readers") that signal downstream events, plays key roles in regulating a variety of cellular processes. To understand how a PTM is recognized, it is necessary to find its readers and, importantly, the location of the binding pockets responsible for PTM recognition. Although various methods have been developed to identify PTM readers, it remains a challenge to directly map the PTM-binding regions, especially for intrinsically disordered domains. Here, we demonstrate a photo-crosslinkable, clickable, and cleavable tri-functional amino acid, ADdis-Cys, that when coupled with mass spectrometry (ADdis-Cys-MS) can not only identify PTM readers from complex proteomes but also simultaneously map their PTM-recognition modules. Using ADdis-Cys-MS, we successfully identify the binding sites of several reader-PTM interactions, among which we discover human C1QBP as a histone chaperone. This robust method should find wide applications in examining other histone or non-histone PTM-mediated protein-protein interactions.

Defining HLA-II Ligand Processing and Binding Rules with Mass Spectrometry Enhances Cancer Epitope Prediction.

Increasing evidence indicates CD4+ T cells can recognize cancer-specific antigens and control tumor growth. However, it remains difficult to predict the antigens that will be presented by human leukocyte antigen class II molecules (HLA-II), hindering efforts to optimally target them therapeutically. Obstacles include inaccurate peptide-binding prediction and unsolved complexities of the HLA-II pathway. To address these challenges, we developed an improved technology for discovering HLA-II binding motifs and conducted a comprehensive analysis of tumor ligandomes to learn processing rules relevant in the tumor microenvironment. We profiled >40 HLA-II alleles and showed that binding motifs were highly sensitive to HLA-DM, a peptide-loading chaperone. We also revealed that intratumoral HLA-II presentation was dominated by professional antigen-presenting cells (APCs) rather than cancer cells. Integrating these observations, we developed algorithms that accurately predicted APC ligandomes, including peptides from phagocytosed cancer cells. These tools and biological insights will enable improved HLA-II-directed cancer therapies.

Protein complexes are under evolutionary selection to assemble via ordered pathways.

Is the order in which proteins assemble into complexes important for biological function? Here, we seek to address this by searching for evidence of evolutionary selection for ordered protein complex assembly. First, we experimentally characterize the assembly pathways of several heteromeric complexes and show that they can be simply predicted from their three-dimensional structures. Then, by mapping gene fusion events identified from fully sequenced genomes onto protein complex assembly pathways, we demonstrate evolutionary selection for conservation of assembly order. Furthermore, using structural and high-throughput interaction data, we show that fusion tends to optimize assembly by simplifying protein complex topologies. Finally, we observe protein structural constraints on the gene order of fusion that impact the potential for fusion to affect assembly. Together, these results reveal the intimate relationships among protein assembly, quaternary structure, and evolution and demonstrate on a genome-wide scale the biological importance of ordered assembly pathways.

Mass spectrometry-based proteomics and network biology.

In the life sciences, a new paradigm is emerging that places networks of interacting molecules between genotype and phenotype. These networks are dynamically modulated by a multitude of factors, and the properties emerging from the network as a whole determine observable phenotypes. This paradigm is usually referred to as systems biology, network biology, or integrative biology. Mass spectrometry (MS)-based proteomics is a central life science technology that has realized great progress toward the identification, quantification, and characterization of the proteins that constitute a proteome. Here, we review how MS-based proteomics has been applied to network biology to identify the nodes and edges of biological networks, to detect and quantify perturbation-induced network changes, and to correlate dynamic network rewiring with the cellular phenotype. We discuss future directions for MS-based proteomics within the network biology paradigm.