Explore the vast range of titles available.

p38 and c-Jun N-terninal kinase (JNK) are activated in response to acute stress and inflammatory signals. Through modification of a plethora of substrates, these kinases profoundly re-shape cellular physiology for the optimal response to a harmful environment and/or an inflammatory state. Here, we utilized phospho-proteomics to identify several hundred substrates for both kinases. Our results indicate that the scale of signaling from p38 and JNK are of a similar magnitude. Among the many new targets, we highlight the regulation of the transcriptional regulators grb10-interacting GYF protein 1 and 2 (GIGYF1/2) by p38-dependent MAP kinase-activated protein kinase 2 (MK2) phosphorylation and 14–3–3 binding. We also show that the Golgi apparatus contains numerous substrates, and is a major target for regulation by p38 and JNK. When activated, these kinases mediate structural rearrangement of the Golgi apparatus, which positively affects protein flux through the secretory system. Our work expands on our knowledge about p38 and JNK signaling with important biological ramifications.

Quantitative phosphoproteomics has transformed investigations of cell signaling, but it remains challenging to scale the technology for high-throughput analyses. Here we report a rapid and reproducible approach to analyze hundreds of phosphoproteomes using data-independent acquisition (DIA) with an accurate site localization score incorporated into Spectronaut. DIA-based phosphoproteomics achieves an order of magnitude broader dynamic range, higher reproducibility of identification, and improved sensitivity and accuracy of quantification compared to state-of-the-art data-dependent acquisition (DDA)-based phosphoproteomics. Notably, direct DIA without the need of spectral libraries performs close to analyses using project-specific libraries, quantifying > 20,000 phosphopeptides in 15 min single-shot LC-MS analysis per condition. Adaptation of a 3D multiple regression model-based algorithm enables global determination of phosphorylation site stoichiometry in DIA. Scalability of the DIA approach is demonstrated by systematically analyzing the effects of thirty kinase inhibitors in context of epidermal growth factor (EGF) signaling showing that specific protein kinases mediate EGF-dependent phospho-regulation. Localizing phosphorylation sites by data-independent acquisition (DIA)-based proteomics is still challenging. Here, the authors develop algorithms for phosphosite localization and stoichiometry determination, and incorporate them into single-shot DIA-phosphoproteomics workflows.

Dynamic change in subcellular localization of signaling proteins is a general concept that eukaryotic cells evolved for eliciting a coordinated response to stimuli. Mass spectrometry-based proteomics in combination with subcellular fractionation can provide comprehensive maps of spatio-temporal regulation of protein networks in cells, but involves laborious workflows that does not cover the phospho-proteome level. Here we present a high-throughput workflow based on sequential cell fractionation to profile the global proteome and phospho-proteome dynamics across six distinct subcellular fractions. We benchmark the workflow by studying spatio-temporal EGFR phospho-signaling dynamics in vitro in HeLa cells and in vivo in mouse tissues. Finally, we investigate the spatio-temporal stress signaling, revealing cellular relocation of ribosomal proteins in response to hypertonicity and muscle contraction. Proteomics data generated in this study can be explored through https://SpatialProteoDynamics.github.io . Protein activity regulated by phosphorylation can result in subcellular relocation. Here, the authors present a high throughput spatial phosphoproteomics approach to profile six subcellular compartments, providing insights into EGFR and stress signalling dynamics.

Notch1 is a crucial oncogenic driver in T-cell acute lymphoblastic leukemia (T-ALL), making it an attractive therapeutic target. However, the success of targeted therapy using γ-secretase inhibitors (GSIs), small molecules blocking Notch cleavage and subsequent activation, has been limited due to development of resistance, thus restricting its clinical efficacy. Here, we systematically compare GSI resistant and sensitive cell states by quantitative mass spectrometry-based phosphoproteomics, using complementary models of resistance, including T-ALL patient-derived xenografts (PDX) models. Our datasets reveal common mechanisms of GSI resistance, including a distinct kinase signature that involves protein kinase C delta. We demonstrate that the PKC inhibitor sotrastaurin enhances the anti-leukemic activity of GSI in PDX models and completely abrogates the development of acquired GSI resistance in vitro. Overall, we highlight the potential of proteomics to dissect alterations in cellular signaling and identify druggable pathways in cancer. NOTCH1 is a driver of T-cell acute lymphoblastic leukemia that can be inhibited by γ-secretase inhibitors (GSIs), but their clinical efficacy is limited. Here, the authors compare the phosphoproteomes of GSI resistant and sensitive models, and identify potential kinase targets to overcome GSI resistance.

Atherosclerosis, a major cause of adverse cardiovascular events and mortality rates worldwide, stems from sustained lipid accumulation and subsequent chronic inflammation within the arterial walls. An early identification of patients at risk is crucial to prevent life-threatening thrombotic events and provide effective and personalized treatments. Leveraging the power of machine learning (ML) to enhance diagnostics and biomarker discovery, we applied a high-throughput approach using five ML classification algorithms (MLCA), integrating clinical and serum proteomic data from patients with carotid atherosclerotic stenosis (AT, n:60), dyslipidemic patients (DLP, n:55), and healthy controls (HC, n:66). As a result, a robust 6-protein panel (B2M, GPV, MMP9, PLF4, TSP1, and FB isoforms) was identified with a ROC-AUC value > 0.9 for all algorithms applied, highly discriminating AT patients compared to DLP or CTRL. The levels of these proteins were further validated in an independent external cohort, including patients presenting with acute atherothrombotic stroke, corroborating the potential of this panel as biomarker for atherosclerosis severity. In addition, the combined clinical-proteomic ML approach provided a more accurate patient stratification than the clinical or proteomic analysis alone. Mechanistically, the identified biomarkers highlight the importance of platelet activation, uncontrolled angiogenesis and intraplaque haemorrhage in the atherosclerotic process, underscoring the need for multipathway therapies to prevent unwanted thrombotic events.

Embryonic stem cells (ESCs) can be maintained in the naïve state through inhibition of Mek1/2 and Gsk3 (2i). A relevant effect of 2i is the inhibition of Cdk8/19, which are negative regulators of the Mediator complex, responsible for the activity of enhancers. Inhibition of Cdk8/19 (Cdk8/19i) stimulates enhancers and, similar to 2i, stabilizes ESCs in the naïve state. Here, we use mass spectrometry to describe the molecular events (phosphoproteome, proteome, and metabolome) triggered by 2i and Cdk8/19i on ESCs. Our data reveal widespread commonalities between these two treatments, suggesting overlapping processes. We find that post-transcriptional de-repression by both 2i and Cdk8/19i might support the mitochondrial capacity of naive cells. However, proteome reprogramming in each treatment is achieved by different mechanisms. Cdk8/19i acts directly on the transcriptional machinery, activating key identity genes to promote the naïve program. In contrast, 2i stabilizes the naïve circuitry through, in part, de-phosphorylation of downstream transcriptional effectors. Naïve pluripotency can be stabilized through different pharmacological approaches. Here, the authors profile temporal changes of protein phosphorylation, proteome and metabolome as mESCs transition to the naïve state in response to two pharmacological treatments, revealing general and treatment-specific processes.

Achieving sufficient coverage of regulatory phosphorylation sites by mass spectrometry (MS)-based phosphoproteomics for signaling pathway reconstitution is challenging, especially when analyzing tiny sample amounts. To address this, we present a hybrid data-independent acquisition (DIA) strategy (hybrid-DIA) that combines targeted and discovery proteomics through an Application Programming Interface (API) to dynamically intercalate DIA scans with accurate triggering of multiplexed tandem mass spectrometry (MSx) scans of predefined (phospho)peptide targets. By spiking-in heavy stable isotope labeled phosphopeptide standards covering seven major signaling pathways, we benchmark hybrid-DIA against state-of-the-art targeted MS methods (i.e., SureQuant) using EGF-stimulated HeLa cells and find the quantitative accuracy and sensitivity to be comparable while hybrid-DIA also profiles the global phosphoproteome. To demonstrate the robustness, sensitivity, and biomedical potential of hybrid-DIA, we profile chemotherapeutic agents in single colon carcinoma multicellular spheroids and evaluate the phospho-signaling difference of cancer cells in 2D vs 3D culture. Standard mass spectrometry analyses often miss key targets required for phospho-signalling reconstruction. Here, authors present an intelligent data acquisition strategy that combines discovery and targeted analysis in one run and apply it to maximize the information from single spheroids drug screenings.

The TNF receptor-interacting protein kinases (RIPK)-1 and 3 are regulators of extrinsic cell death response pathways, where RIPK1 makes the cell survival or death decisions by associating with distinct complexes mediating survival signaling, caspase activation or RIPK3-dependent necroptotic cell death in a context-dependent manner. Using a mass spectrometry-based screen to find new components of the ripoptosome/necrosome, we discovered the protein-arginine methyltransferase (PRMT)-5 as a direct interaction partner of RIPK1. Interestingly, RIPK3 but not RIPK1 was then found to be a target of PRMT5-mediated symmetric arginine dimethylation. A conserved arginine residue in RIPK3 (R486 in human, R415 in mouse) was identified as the evolutionarily conserved target for PRMT5-mediated symmetric dimethylation and the mutations R486A and R486K in human RIPK3 almost completely abrogated its methylation. Rescue experiments using these non-methylatable mutants of RIPK3 demonstrated PRMT5-mediated RIPK3 methylation to act as an efficient mechanism of RIPK3-mediated feedback control on RIPK1 activity and function. Therefore, this study reveals PRMT5-mediated RIPK3 methylation as a novel modulator of RIPK1-dependent signaling.

Background Critical limb-threatening ischemia (CLTI) constitutes the most severe manifestation of peripheral artery disease, usually induced by atherosclerosis. CLTI patients suffer from high risk of amputation of the lower extremities and elevated mortality rates, while they have low options for surgical revascularization due to associated comorbidities. Alternatively, cell-based therapeutic strategies represent an effective and safe approach to promote revascularization. However, the variability seen in several factors such as cell combinations or doses applied, have limited their success in clinical trials, being necessary to reach a consensus regarding the optimal “cellular-cocktail” prior further application into the clinic. To achieve so, it is essential to understand the mechanisms by which these cells exert their regenerative properties. Herein, we have evaluated, for the first time, the regenerative and vasculogenic potential of a combination of endothelial colony forming cells (ECFCs) and mesenchymal stem cells (MSCs) isolated from adipose-tissue (AT), compared with ECFCs from umbilical cord blood (CB-ECFCs) and AT-MSCs, in a murine model of CLTI. Methods Balb-c nude mice (n:32) were distributed in four different groups (n:8/group): control shams, and ischemic mice (after femoral ligation) that received 50 µl of physiological serum alone or a cellular combination of AT-MSCs with either CB-ECFCs or AT-ECFCs. Follow-up of blood flow reperfusion and ischemic symptoms was carried out for 21 days, when mice were sacrificed to evaluate vascular density formation. Moreover, the long-term molecular changes in response to CLTI and both cell combinations were analyzed in a proteomic quantitative approach. Results AT-MSCs with either AT- or CB-ECFCs, promoted a significant recovery of blood flow in CLTI mice 21 days post-ischemia. Besides, they modulated the inflammatory and necrotic related processes, although the CB group presented the slowest ischemic progression along the assay. Moreover, many proteins involved in the repairing mechanisms promoted by cell treatments were identified. Conclusions The combination of AT-MSCs with AT-ECFCs or with CB-ECFCs promoted similar revascularization in CLTI mice, by restoring blood flow levels, together with the modulation of the inflammatory and necrotic processes, and reduction of muscle damage. The protein changes identified are representative of the molecular mechanisms involved in ECFCs and MSCs-induced revascularization (immune response, vascular repair, muscle regeneration, etc.).

Mass spectrometry (MS)-based proteomics aims to characterize comprehensive proteomes in a fast and reproducible manner. Here we present the narrow-window data-independent acquisition (nDIA) strategy consisting of high-resolution MS1 scans with parallel tandem MS (MS/MS) scans of ~200 Hz using 2-Th isolation windows, dissolving the differences between data-dependent and -independent methods. This is achieved by pairing a quadrupole Orbitrap mass spectrometer with the asymmetric track lossless (Astral) analyzer which provides >200-Hz MS/MS scanning speed, high resolving power and sensitivity, and low-ppm mass accuracy. The nDIA strategy enables profiling of >100 full yeast proteomes per day, or 48 human proteomes per day at the depth of ~10,000 human protein groups in half-an-hour or ~7,000 proteins in 5 min, representing 3× higher coverage compared with current state-of-the-art MS. Multi-shot acquisition of offline fractionated samples provides comprehensive coverage of human proteomes in ~3 h. High quantitative precision and accuracy are demonstrated in a three-species proteome mixture, quantifying 14,000+ protein groups in a single half-an-hour run. A new mass spectrometry strategy combines the advantages of data-dependent and data-independent acquisition.