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Nano-flow liquid chromatography tandem mass spectrometry (nano-flow LC–MS/MS) is the mainstay in proteome research because of its excellent sensitivity but often comes at the expense of robustness. Here we show that micro-flow LC–MS/MS using a 1 × 150 mm column shows excellent reproducibility of chromatographic retention time (<0.3% coefficient of variation, CV) and protein quantification (<7.5% CV) using data from >2000 samples of human cell lines, tissues and body fluids. Deep proteome analysis identifies >9000 proteins and >120,000 peptides in 16 h and sample multiplexing using tandem mass tags increases throughput to 11 proteomes in 16 h. The system identifies >30,000 phosphopeptides in 12 h and protein-protein or protein-drug interaction experiments can be analyzed in 20 min per sample. We show that the same column can be used to analyze >7500 samples without apparent loss of performance. This study demonstrates that micro-flow LC–MS/MS is suitable for a broad range of proteomic applications. Mass spectrometry-based proteomics typically relies on highly sensitive nano-flow liquid chromatography (LC) but this can reduce robustness and reproducibility. Here, the authors show that micro-flow LC enables robust and reproducible high-throughput proteomics experiments at a very moderate loss of sensitivity.

The computational workflow of DIA-Umpire allows untargeted peptide identificationdirectly from DIA (data-independent acquisition) proteomics data without dependence on a spectral library for data extraction As a result of recent improvements in mass spectrometry (MS), there is increased interest in data-independent acquisition (DIA) strategies in which all peptides are systematically fragmented using wide mass-isolation windows ('multiplex fragmentation'). DIA-Umpire ( http://diaumpire.sourceforge.net/ ), a comprehensive computational workflow and open-source software for DIA data, detects precursor and fragment chromatographic features and assembles them into pseudo–tandem MS spectra. These spectra can be identified with conventional database-searching and protein-inference tools, allowing sensitive, untargeted analysis of DIA data without the need for a spectral library. Quantification is done with both precursor- and fragment-ion intensities. Furthermore, DIA-Umpire enables targeted extraction of quantitative information based on peptides initially identified in only a subset of the samples, resulting in more consistent quantification across multiple samples. We demonstrated the performance of the method with control samples of varying complexity and publicly available glycoproteomics and affinity purification–MS data.

The RAF family kinases function in the RAS–ERK pathway to transmit signals from activated RAS to the downstream kinases MEK and ERK. This pathway regulates cell proliferation, differentiation and survival, enabling mutations in RAS and RAF to act as potent drivers of human cancers. Drugs targeting the prevalent oncogenic mutant BRAF(V600E) have shown great efficacy in the clinic, but long-term effectiveness is limited by resistance mechanisms that often exploit the dimerization-dependent process by which RAF kinases are activated. Here, we investigated a proteolysis-targeting chimera (PROTAC) approach to BRAF inhibition. The most effective PROTAC, termed P4B, displayed superior specificity and inhibitory properties relative to non-PROTAC controls in BRAF (V600E) cell lines. In addition, P4B displayed utility in cell lines harboring alternative BRAF mutations that impart resistance to conventional BRAF inhibitors. This work provides a proof of concept for a substitute to conventional chemical inhibition to therapeutically constrain oncogenic BRAF. A PROTAC termed P4B targeting BRAF V600E mutant has been developed, which displays enhanced inhibitory function in cell lines carrying BRAF mutations that impart resistance to conventional BRAF inhibitors.

Quantitative proteomics employing mass spectrometry is an indispensable tool in life science research. Targeted proteomics has emerged as a powerful approach for reproducible quantification but is limited in the number of proteins quantified. SWATH-mass spectrometry consists of data-independent acquisition and a targeted data analysis strategy that aims to maintain the favorable quantitative characteristics (accuracy, sensitivity, and selectivity) of targeted proteomics at large scale. While previous SWATH-mass spectrometry studies have shown high intra-lab reproducibility, this has not been evaluated between labs. In this multi-laboratory evaluation study including 11 sites worldwide, we demonstrate that using SWATH-mass spectrometry data acquisition we can consistently detect and reproducibly quantify >4000 proteins from HEK293 cells. Using synthetic peptide dilution series, we show that the sensitivity, dynamic range and reproducibility established with SWATH-mass spectrometry are uniformly achieved. This study demonstrates that the acquisition of reproducible quantitative proteomics data by multiple labs is achievable, and broadly serves to increase confidence in SWATH-mass spectrometry data acquisition as a reproducible method for large-scale protein quantification. SWATH-mass spectrometry consists of a data-independent acquisition and a targeted data analysis strategy that aims to maintain the favorable quantitative characteristics on the scale of thousands of proteins. Here, using data generated by eleven groups worldwide, the authors show that SWATH-MS is capable of generating highly reproducible data across different laboratories.

Guanine nucleotide exchange factors (RhoGEFs) and GTPase-activating proteins (RhoGAPs) coordinate the activation state of the Rho family of GTPases for binding to effectors. Here, we exploited proximity-dependent biotinylation to systematically define the Rho family proximity interaction network from 28 baits to produce 9,939 high-confidence proximity interactions in two cell lines. Exploiting the nucleotide states of Rho GTPases, we revealed the landscape of interactions with RhoGEFs and RhoGAPs. We systematically defined effectors of Rho proteins to reveal candidates for classical and atypical Rho proteins. We used optogenetics to demonstrate that KIAA0355 (termed GARRE here) is a RAC1 interactor. A functional screen of RHOG candidate effectors identified PLEKHG3 as a promoter of Rac-mediated membrane ruffling downstream of RHOG. We identified that active RHOA binds the kinase SLK in Drosophila and mammalian cells to promote Ezrin–Radixin–Moesin phosphorylation. Our proximity interactions data pave the way for dissecting additional Rho signalling pathways, and the approaches described here are applicable to the Ras family.Using a BioID approach, Bagci et al. systematically analyse the Rho-family GTPase interactome and reveal previously unappreciated interactions with RhoGEFs and RhoGAPs and effectors for Rho proteins.

Rho GTPases are central regulators of the cytoskeleton and, in humans, are controlled by 145 multidomain guanine nucleotide exchange factors (RhoGEFs) and GTPase-activating proteins (RhoGAPs). How Rho signalling patterns are established in dynamic cell spaces to control cellular morphogenesis is unclear. Through a family-wide characterization of substrate specificities, interactomes and localization, we reveal at the systems level how RhoGEFs and RhoGAPs contextualize and spatiotemporally control Rho signalling. These proteins are widely autoinhibited to allow local regulation, form complexes to jointly coordinate their networks and provide positional information for signalling. RhoGAPs are more promiscuous than RhoGEFs to confine Rho activity gradients. Our resource enabled us to uncover a multi-RhoGEF complex downstream of G-protein-coupled receptors controlling CDC42–RHOA crosstalk. Moreover, we show that integrin adhesions spatially segregate GEFs and GAPs to shape RAC1 activity zones in response to mechanical cues. This mechanism controls the protrusion and contraction dynamics fundamental to cell motility. Our systems analysis of Rho regulators is key to revealing emergent organization principles of Rho signalling.Müller et al. provide a comprehensive resource depicting cellular substrates, localization and interacting partners of RhoGEF and RhoGAP proteins regulating the canonical Rho family of GTPases.

The spatial organization of proteins within eukaryotic cells underlies essential biological processes and can be mapped by identifying nearby proteins using proximity-dependent biotinylation approaches such as BioID. When applied systematically to hundreds of bait proteins, BioID has localized thousands of endogenous proteins in human cells, generating a comprehensive view of subcellular organization. However, the need for large bait sets limits the scalability of BioID for context-dependent spatial profiling across different cell types, states, or perturbations. To address this, we develop a benchmarking framework with multiple complementary metrics to assess how well a given bait subset recapitulates the structure and coverage of a reference BioID dataset. We also introduce GENBAIT, a genetic algorithm-based method that identifies optimized bait subsets predicted to retain maximal spatial information while reducing the total number of baits. Applied to three large BioID datasets, GENBAIT consistently selected subsets representing less than one-third of the original baits while preserving high coverage and network integrity. This flexible, data-driven approach enables intelligent bait selection for targeted, context-specific studies, thereby expanding the accessibility of large-scale subcellular proteome mapping. Proximity-dependent biotinylation maps protein locations using multiple bait proteins, limiting scalability. Here, the authors present GENBAIT, a computational tool that selects optimal baits to reduce the number of experiments required while preserving subcellular organization.

Protein arginine methyltransferases (PRMTs) regulate diverse biological processes and are increasingly being recognized for their potential as drug targets. Here we report the discovery of a potent, selective, and cell-active chemical probe for PRMT7. SGC3027 is a cell permeable prodrug, which in cells is converted to SGC8158, a potent, SAM-competitive PRMT7 inhibitor. Inhibition or knockout of cellular PRMT7 results in drastically reduced levels of arginine monomethylated HSP70 family stress-associated proteins. Structural and biochemical analyses reveal that PRMT7-driven in vitro methylation of HSP70 at R469 requires an ATP-bound, open conformation of HSP70. In cells, SGC3027 inhibits methylation of both constitutive and inducible forms of HSP70, and leads to decreased tolerance for perturbations of proteostasis including heat shock and proteasome inhibitors. These results demonstrate a role for PRMT7 and arginine methylation in stress response. Protein arginine methyltransferases (PRMTs) are increasingly recognized as potential therapeutic targets but PRMT7 remains an understudied member of this enzyme family. Here, the authors develop a chemical probe for PRMT7 and apply it to elucidate the role of PRMT7 in the cellular stress response.

Key Points In this article, we review the current status of affinity purification and mass spectrometry (AP–MS) and its promise for better understanding protein complexes, complex structure and the dynamics of complex formation. We describe the general AP–MS strategy, with an emphasis on generic approaches (flag-tag, tandem AP) and how AP–MS of multiple components (that is, high-density AP–MS) can help to reveal the true composition of protein complexes. Recent high-throughput studies with flag-tagging or tandem AP significantly improved our understanding of protein–protein interactions in yeast. AP–MS can be combined with classical biochemical purification approaches to reveal complex composition and to resolve the problem of mutually exclusive complexes co-precipitating with the same tagged protein. Crosslinkers can contribute to AP–MS strategies by stabilizing weak or transient protein interactions and by revealing details concerning complex organization and interacting surfaces. Stoichiometry of protein complexes can be obtained using intact-complex mass measurement and absolute quantitative proteomics tools. Quantitative proteomics approaches can help to decipher the dynamics of protein-complex formation. The combination of affinity purification and mass spectrometry (AP–MS) has recently been applied to the detailed characterization of protein complexes and large protein-interaction networks. Emerging AP–MS approaches promise a better understanding of protein-complex stoichiometry, structural organization and the dynamics of protein-complex composition. The versatile combination of affinity purification and mass spectrometry (AP–MS) has recently been applied to the detailed characterization of many protein complexes and large protein-interaction networks. The combination of AP–MS with other techniques, such as biochemical fractionation, intact mass measurement and chemical crosslinking, can help to decipher the supramolecular organization of protein complexes. AP–MS can also be combined with quantitative proteomics approaches to better understand the dynamics of protein–complex assembly.