Harnessing CD3 diversity to optimize CAR T cells.

Current US Food and Drug Administration-approved chimeric antigen receptor (CAR) T cells harbor the T cell receptor (TCR)-derived ζ chain as an intracellular activation domain in addition to costimulatory domains. The functionality in a CAR format of the other chains of the TCR complex, namely CD3δ, CD3ε and CD3γ, instead of ζ, remains unknown. In the present study, we have systematically engineered new CD3 CARs, each containing only one of the CD3 intracellular domains. We found that CARs containing CD3δ, CD3ε or CD3γ cytoplasmic tails outperformed the conventional ζ CAR T cells in vivo. Transcriptomic and proteomic analysis revealed differences in activation potential, metabolism and stimulation-induced T cell dysfunctionality that mechanistically explain the enhanced anti-tumor performance. Furthermore, dimerization of the CARs improved their overall functionality. Using these CARs as minimalistic and synthetic surrogate TCRs, we have identified the phosphatase SHP-1 as a new interaction partner of CD3δ that binds the CD3δ-ITAM on phosphorylation of its C-terminal tyrosine. SHP-1 attenuates and restrains activation signals and might thus prevent exhaustion and dysfunction. These new insights into T cell activation could promote the rational redesign of synthetic antigen receptors to improve cancer immunotherapy.

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

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

DIP-MS: ultra-deep interaction proteomics for the deconvolution of protein complexes.

Most proteins are organized in macromolecular assemblies, which represent key functional units regulating and catalyzing most cellular processes. Affinity purification of the protein of interest combined with liquid chromatography coupled to tandem mass spectrometry (AP-MS) represents the method of choice to identify interacting proteins. The composition of complex isoforms concurrently present in the AP sample can, however, not be resolved from a single AP-MS experiment but requires computational inference from multiple time- and resource-intensive reciprocal AP-MS experiments. Here we introduce deep interactome profiling by mass spectrometry (DIP-MS), which combines AP with blue-native-PAGE separation, data-independent acquisition with mass spectrometry and deep-learning-based signal processing to resolve complex isoforms sharing the same bait protein in a single experiment. We applied DIP-MS to probe the organization of the human prefoldin family of complexes, resolving distinct prefoldin holo- and subcomplex variants, complex-complex interactions and complex isoforms with new subunits that were experimentally validated. Our results demonstrate that DIP-MS can reveal proteome modularity at unprecedented depth and resolution.

Quantitative proteomics analysis of signalosome dynamics in primary T cells identifies the surface receptor CD6 as a Lat adaptor-independent TCR signaling hub.

T cell antigen receptor (TCR)-mediated activation of T cells requires the interaction of dozens of proteins. Here we used quantitative mass spectrometry and activated primary CD4(+) T cells from mice in which a tag for affinity purification was knocked into several genes to determine the composition and dynamics of multiprotein complexes that formed around the kinase Zap70 and the adaptors Lat and SLP-76. Most of the 112 high-confidence time-resolved protein interactions we observed were previously unknown. The surface receptor CD6 was able to initiate its own signaling pathway by recruiting SLP-76 and the guanine nucleotide-exchange factor Vav1 regardless of the presence of Lat. Our findings provide a more complete model of TCR signaling in which CD6 constitutes a signaling hub that contributes to the diversification of TCR signaling.

A chemical probe to modulate human GID4 Pro/N-degron interactions.

The C-terminal to LisH (CTLH) complex is a ubiquitin ligase complex that recognizes substrates with Pro/N-degrons via its substrate receptor Glucose-Induced Degradation 4 (GID4), but its function and substrates in humans remain unclear. Here, we report PFI-7, a potent, selective and cell-active chemical probe that antagonizes Pro/N-degron binding to human GID4. Use of PFI-7 in proximity-dependent biotinylation and quantitative proteomics enabled the identification of GID4 interactors and GID4-regulated proteins. GID4 interactors are enriched for nucleolar proteins, including the Pro/N-degron-containing RNA helicases DDX21 and DDX50. We also identified a distinct subset of proteins whose cellular levels are regulated by GID4 including HMGCS1, a Pro/N-degron-containing metabolic enzyme. These data reveal human GID4 Pro/N-degron targets regulated through a combination of degradative and nondegradative functions. Going forward, PFI-7 will be a valuable research tool for investigating CTLH complex biology and facilitating development of targeted protein degradation strategies that highjack CTLH E3 ligase activity.

Novel biochemical, structural, and systems insights into inflammatory signaling revealed by contextual interaction proteomics.

Protein-protein interactions (PPIs) represent the main mode of the proteome organization in the cell. In the last decade, several large-scale representations of PPI networks have captured generic aspects of the functional organization of network components but mostly lack the context of cellular states. However, the generation of context-dependent PPI networks is essential for structural and systems-level modeling of biological processes-a goal that remains an unsolved challenge. Here we describe an experimental/computational strategy to achieve a modeling of PPIs that considers contextual information. This strategy defines the composition, stoichiometry, temporal organization, and cellular requirements for the formation of target assemblies. We used this approach to generate an integrated model of the formation principles and architecture of a large signalosome, the TNF-receptor signaling complex (TNF-RSC). Overall, we show that the integration of systems- and structure-level information provides a generic, largely unexplored link between the modular proteome and cellular function.

PCprophet: a framework for protein complex prediction and differential analysis using proteomic data.

Despite the availability of methods for analyzing protein complexes, systematic analysis of complexes under multiple conditions remains challenging. Approaches based on biochemical fractionation of intact, native complexes and correlation of protein profiles have shown promise. However, most approaches for interpreting cofractionation datasets to yield complex composition and rearrangements between samples depend considerably on protein-protein interaction inference. We introduce PCprophet, a toolkit built on size exclusion chromatography-sequential window acquisition of all theoretical mass spectrometry (SEC-SWATH-MS) data to predict protein complexes and characterize their changes across experimental conditions. We demonstrate improved performance of PCprophet over state-of-the-art approaches and introduce a Bayesian approach to analyze altered protein-protein interactions across conditions. We provide both command-line and graphical interfaces to support the application of PCprophet to any cofractionation MS dataset, independent of separation or quantitative liquid chromatography-MS workflow, for the detection and quantitative tracking of protein complexes and their physiological dynamics.

Phosphorylation-linked complex profiling identifies assemblies required for Hippo signal integration.

While several computational methods have been developed to predict the functional relevance of phosphorylation sites, experimental analysis of the interdependency between protein phosphorylation and Protein-Protein Interactions (PPIs) remains challenging. Here, we describe an experimental strategy to establish interdependencies between protein phosphorylation and complex formation. This strategy is based on three main steps: (i) systematically charting the phosphorylation landscape of a target protein; (ii) assigning distinct proteoforms of the target protein to different protein complexes by native complex separation (AP-BNPAGE) and protein correlation profiling; and (iii) analyzing proteoforms and complexes in cells lacking regulators of the target protein. We applied this strategy to YAP1, a transcriptional co-activator for the control of organ size and tissue homeostasis that is highly phosphorylated and among the most connected proteins in human cells. We identified multiple YAP1 phosphosites associated with distinct complexes and inferred how both are controlled by Hippo pathway members. We detected a PTPN14/LATS1/YAP1 complex and suggest a model how PTPN14 inhibits YAP1 via augmenting WW domain-dependent complex formation and phosphorylation by LATS1/2.

Covalent Proximity Scanning of a Distal Cysteine to Target PI3Kα.

Covalent protein kinase inhibitors exploit currently noncatalytic cysteines in the adenosine 5'-triphosphate (ATP)-binding site via electrophiles directly appended to a reversible-inhibitor scaffold. Here, we delineate a path to target solvent-exposed cysteines at a distance >10 Å from an ATP-site-directed core module and produce potent covalent phosphoinositide 3-kinase α (PI3Kα) inhibitors. First, reactive warheads are used to reach out to Cys862 on PI3Kα, and second, enones are replaced with druglike warheads while linkers are optimized. The systematic investigation of intrinsic warhead reactivity (kchem), rate of covalent bond formation and proximity (kinact and reaction space volume Vr), and integration of structure data, kinetic and structural modeling, led to the guided identification of high-quality, covalent chemical probes. A novel stochastic approach provided direct access to the calculation of overall reaction rates as a function of kchem, kinact, Ki, and Vr, which was validated with compounds with varied linker lengths. X-ray crystallography, protein mass spectrometry (MS), and NanoBRET assays confirmed covalent bond formation of the acrylamide warhead and Cys862. In rat liver microsomes, compounds 19 and 22 outperformed the rapidly metabolized CNX-1351, the only known PI3Kα irreversible inhibitor. Washout experiments in cancer cell lines with mutated, constitutively activated PI3Kα showed a long-lasting inhibition of PI3Kα. In SKOV3 cells, compounds 19 and 22 revealed PI3Kß-dependent signaling, which was sensitive to TGX221. Compounds 19 and 22 thus qualify as specific chemical probes to explore PI3Kα-selective signaling branches. The proposed approach is generally suited to develop covalent tools targeting distal, unexplored Cys residues in biologically active enzymes.

Elucidating essential kinases of endothelin signalling by logic modelling of phosphoproteomics data.

Endothelins (EDN) are peptide hormones that activate a GPCR signalling system and contribute to several diseases, including hypertension and cancer. Current knowledge about EDN signalling is fragmentary, and no systems level understanding is available. We investigated phosphoproteomic changes caused by endothelin B receptor (ENDRB) activation in the melanoma cell lines UACC257 and A2058 and built an integrated model of EDNRB signalling from the phosphoproteomics data. More than 5,000 unique phosphopeptides were quantified. EDN induced quantitative changes in more than 800 phosphopeptides, which were all strictly dependent on EDNRB. Activated kinases were identified based on high confidence EDN target sites and validated by Western blot. The data were combined with prior knowledge to construct the first comprehensive logic model of EDN signalling. Among the kinases predicted by the signalling model, AKT, JNK, PKC and AMP could be functionally linked to EDN-induced cell migration. The model contributes to the system-level understanding of the mechanisms underlying the pleiotropic effects of EDN signalling and supports the rational selection of kinase inhibitors for combination treatments with EDN receptor antagonists.

Complex-centric proteome profiling by SEC-SWATH-MS.

Proteins are major effectors and regulators of biological processes that can elicit multiple functions depending on their interaction with other proteins. The organization of proteins into macromolecular complexes and their quantitative distribution across these complexes is, therefore, of great biological and clinical significance. In this paper, we describe an integrated experimental and computational technique to quantify hundreds of protein complexes in a single operation. The method consists of size exclusion chromatography (SEC) to fractionate native protein complexes, SWATH/DIA mass spectrometry to precisely quantify the proteins in each SEC fraction, and the computational framework CCprofiler to detect and quantify protein complexes by error-controlled, complex-centric analysis using prior information from generic protein interaction maps. Our analysis of the HEK293 cell line proteome delineates 462 complexes composed of 2,127 protein subunits. The technique identifies novel sub-complexes and assembly intermediates of central regulatory complexes while assessing the quantitative subunit distribution across them. We make the toolset CCprofiler freely accessible and provide a web platform, SECexplorer, for custom exploration of the HEK293 proteome modularity.

AP-SWATH Reveals Direct Involvement of VCP/p97 in Integrated Stress Response Signaling Through Facilitating CReP/PPP1R15B Degradation.

The ubiquitin-directed AAA-ATPase VCP/p97 facilitates degradation of damaged or misfolded proteins in diverse cellular stress response pathways. Resolving the complexity of its interactions with partner and substrate proteins and understanding its links to stress signaling is therefore a major challenge. Here, we used affinity-purification SWATH mass spectrometry (AP-SWATH) to identify proteins that specifically interact with the substrate-trapping mutant, p97-E578Q. AP-SWATH identified differential interactions over a large detection range from abundant p97 cofactors to pathway-specific partners and individual ligases such as RNF185 and MUL1 that were trapped in p97-E578Q complexes. In addition, we identified various substrate proteins and candidates including the PP1 regulator CReP/PPP1R15B that dephosphorylates eIF2α and thus counteracts attenuation of translation by stress-kinases. We provide evidence that p97 with its Ufd1-Npl4 adapter ensures rapid constitutive turnover and balanced levels of CReP in unperturbed cells. Moreover, we show that p97-mediated degradation, together with a reduction in CReP synthesis, is essential for timely stress-induced reduction of CReP levels and, consequently, for robust eIF2α phosphorylation to enforce the stress response. Thus, our results demonstrate that p97 not only facilitates bulk degradation of misfolded proteins upon stress, but also directly modulates the integrated stress response at the level of signaling.

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.

Combined functional genomic and proteomic approaches identify a PP2A complex as a negative regulator of Hippo signaling.

The Hippo (Hpo) pathway is a central determinant of tissue size in both Drosophila and higher organisms. The core of the pathway is a kinase cascade composed of an upstream kinase Hpo (MST1/2 in mammals) and a downstream kinase Warts (Wts, Lats1/2 in mammals), as well as several scaffold proteins, Sav, dRASSF, and Mats. Activation of the core kinase cassette results in phosphorylation and inactivation of the progrowth transcriptional coactivator Yki, leading to increased apoptosis and reduced tissue growth. The mechanisms that prevent inappropriate Hpo activation remain unclear, and in particular, the identity of the phosphatase that antagonizes Hpo is unknown. Using combined proteomic and RNAi screening approaches, we identify the dSTRIPAK PP2A complex as a major regulator of Hpo signaling. dSTRIPAK depletion leads to increased Hpo activatory phosphorylation and repression of Yki target genes in vivo, suggesting this phosphatase complex prevents Hpo activation during development.

An Inducible Retroviral Expression System for Tandem Affinity Purification Mass-Spectrometry-Based Proteomics Identifies Mixed Lineage Kinase Domain-like Protein (MLKL) as an Heat Shock Protein 90 (HSP90) Client.

Tandem affinity purification-mass spectrometry (TAP-MS) is a popular strategy for the identification of protein-protein interactions, characterization of protein complexes, and entire networks. Its employment in cellular settings best fitting the relevant physiology is limited by convenient expression vector systems. We developed an easy-to-handle, inducible, dually selectable retroviral expression vector allowing dose- and time-dependent control of bait proteins bearing the efficient streptavidin-hemagglutinin (SH)-tag at their N- or C termini. Concomitant expression of a reporter fluorophore allows to monitor bait-expressing cells by flow cytometry or microscopy and enables high-throughput phenotypic assays. We used the system to successfully characterize the interactome of the neuroblastoma RAS viral oncogene homolog (NRAS) Gly12Asp (G12D) mutant and exploited the advantage of reporter fluorophore expression by tracking cytokine-independent cell growth using flow cytometry. Moreover, we tested the feasibility of studying cytotoxicity-mediating proteins with the vector system on the cell death-inducing mixed lineage kinase domain-like protein (MLKL) Ser358Asp (S358D) mutant. Interaction proteomics analysis of MLKL Ser358Asp (S358D) identified heat shock protein 90 (HSP90) as a high-confidence interacting protein. Further phenotypic characterization established MLKL as a novel HSP90 client. In summary, this novel inducible expression system enables SH-tag-based interaction studies in the cell line proficient for the respective phenotypic or signaling context and constitutes a valuable tool for experimental approaches requiring inducible or traceable protein expression.

Contribution of Mass Spectrometry-Based Proteomics to the Understanding of TNF-α Signaling.

NF-κB is a family of ubiquitous dimeric transcription factors that play a role in a myriad of cellular processes, ranging from differentiation to stress response and immunity. In inflammation, activation of NF-κB is mediated by pro-inflammatory cytokines, in particular the prototypic cytokines IL-1ß and TNF-α, which trigger the activation of complex signaling cascades. In spite of decades of research, the system level understanding of TNF-α signaling is still incomplete. This is partially due to the limited knowledge at the proteome level. The objective of this review is to summarize and critically evaluate the current status of the proteomic research on TNF-α signaling. We will discuss the merits and flaws of the existing studies as well as the insights that they have generated into the proteomic landscape and architecture connected to this signaling pathway. Besides delineating past and current trends in TNF-α proteomic research, we will identify research directions and new methodologies that can further contribute to characterize the TNF-α associated proteome in space and time.

Quantifying protein interaction dynamics by SWATH mass spectrometry: application to the 14-3-3 system.

Protein complexes and protein interaction networks are essential mediators of most biological functions. Complexes supporting transient functions such as signal transduction processes are frequently subject to dynamic remodeling. Currently, the majority of studies on the composition of protein complexes are carried out by affinity purification and mass spectrometry (AP-MS) and present a static view of the system. For a better understanding of inherently dynamic biological processes, methods to reliably quantify temporal changes of protein interaction networks are essential. Here we used affinity purification combined with sequential window acquisition of all theoretical spectra (AP-SWATH) mass spectrometry to study the dynamics of the 14-3-3ß scaffold protein interactome after stimulation of the insulin-PI3K-AKT pathway. The consistent and reproducible quantification of 1,967 proteins across all stimulation time points provided insights into the 14-3-3ß interactome and its dynamic changes following IGF1 stimulation. We therefore establish AP-SWATH as a tool to quantify dynamic changes in protein-complex interaction networks.

Interlaboratory reproducibility of large-scale human protein-complex analysis by standardized AP-MS.

The characterization of all protein complexes of human cells under defined physiological conditions using affinity purification-mass spectrometry (AP-MS) is a highly desirable step in the quest to understand the phenotypic effects of genomic information. However, such a challenging goal has not yet been achieved, as it requires reproducibility of the experimental workflow and high data consistency across different studies and laboratories. We systematically investigated the reproducibility of a standardized AP-MS workflow by performing a rigorous interlaboratory comparative analysis of the interactomes of 32 human kinases. We show that it is possible to achieve high interlaboratory reproducibility of this standardized workflow despite differences in mass spectrometry configurations and subtle sample preparation-related variations and that combination of independent data sets improves the approach sensitivity, resulting in even more-detailed networks. Our analysis demonstrates the feasibility of obtaining a high-quality map of the human protein interactome with a multilaboratory project.

The CRAPome: a contaminant repository for affinity purification-mass spectrometry data.

Affinity purification coupled with mass spectrometry (AP-MS) is a widely used approach for the identification of protein-protein interactions. However, for any given protein of interest, determining which of the identified polypeptides represent bona fide interactors versus those that are background contaminants (for example, proteins that interact with the solid-phase support, affinity reagent or epitope tag) is a challenging task. The standard approach is to identify nonspecific interactions using one or more negative-control purifications, but many small-scale AP-MS studies do not capture a complete, accurate background protein set when available controls are limited. Fortunately, negative controls are largely bait independent. Hence, aggregating negative controls from multiple AP-MS studies can increase coverage and improve the characterization of background associated with a given experimental protocol. Here we present the contaminant repository for affinity purification (the CRAPome) and describe its use for scoring protein-protein interactions. The repository (currently available for Homo sapiens and Saccharomyces cerevisiae) and computational tools are freely accessible at http://www.crapome.org/.

Applying mass spectrometry-based proteomics to genetics, genomics and network biology.

The systematic and quantitative molecular analysis of mutant organisms that has been pioneered by studies on mutant metabolomes and transcriptomes holds great promise for improving our understanding of how phenotypes emerge. Unfortunately, owing to the limitations of classical biochemical analysis, proteins have previously been excluded from such studies. Here we review how technical advances in mass spectrometry-based proteomics can be applied to measure changes in protein abundance, posttranslational modifications and protein-protein interactions in mutants at the scale of the proteome. We finally discuss examples that integrate proteomics data with genomic and phenomic information to build network-centred models, which provide a promising route for understanding how phenotypes emerge.