Dynamic 3D proteomes reveal protein functional alterations at high resolution in situ.

Biological processes are regulated by intermolecular interactions and chemical modifications that do not affect protein levels, thus escaping detection in classical proteomic screens. We demonstrate here that a global protein structural readout based on limited proteolysis-mass spectrometry (LiP-MS) detects many such functional alterations, simultaneously and in situ, in bacteria undergoing nutrient adaptation and in yeast responding to acute stress. The structural readout, visualized as structural barcodes, captured enzyme activity changes, phosphorylation, protein aggregation, and complex formation, with the resolution of individual regulated functional sites such as binding and active sites. Comparison with prior knowledge, including other 'omics data, showed that LiP-MS detects many known functional alterations within well-studied pathways. It suggested distinct metabolite-protein interactions and enabled identification of a fructose-1,6-bisphosphate-based regulatory mechanism of glucose uptake in E. coli. The structural readout dramatically increases classical proteomics coverage, generates mechanistic hypotheses, and paves the way for in situ structural systems biology.

Maturation Kinetics of a Multiprotein Complex Revealed by Metabolic Labeling.

All proteins interact with other cellular components to fulfill their function. While tremendous progress has been made in the identification of protein complexes, their assembly and dynamics remain difficult to characterize. Here, we present a high-throughput strategy to analyze the native assembly kinetics of protein complexes. We apply our approach to characterize the co-assembly for 320 pairs of nucleoporins (NUPs) constituting the ≈50 MDa nuclear pore complex (NPC) in yeast. Some NUPs co-assemble fast via rapid exchange whereas others require lengthy maturation steps. This reveals a hierarchical principle of NPC biogenesis where individual subcomplexes form on a minute timescale and then co-assemble from center to periphery in a ∼1 h-long maturation process. Intriguingly, the NUP Mlp1 stands out as joining very late and associating preferentially with aged NPCs. Our approach is readily applicable beyond the NPC, making it possible to analyze the intracellular dynamics of a variety of multiprotein assemblies.

Genetic effects on molecular network states explain complex traits.

The complexity of many cellular and organismal traits results from the integration of genetic and environmental factors via molecular networks. Network structure and effect propagation are best understood at the level of functional modules, but so far, no concept has been established to include the global network state. Here, we show when and how genetic perturbations lead to molecular changes that are confined to small parts of a network versus when they lead to modulation of network states. Integrating multi-omics profiling of genetically heterogeneous budding and fission yeast strains with an array of cellular traits identified a central state transition of the yeast molecular network that is related to PKA and TOR (PT) signaling. Genetic variants affecting this PT state globally shifted the molecular network along a single-dimensional axis, thereby modulating processes including energy and amino acid metabolism, transcription, translation, cell cycle control, and cellular stress response. We propose that genetic effects can propagate through large parts of molecular networks because of the functional requirement to centrally coordinate the activity of fundamental cellular processes.

Combining CRISPRi and metabolomics for functional annotation of compound libraries.

Molecular profiling of small molecules offers invaluable insights into the function of compounds and allows for hypothesis generation about small-molecule direct targets and secondary effects. However, current profiling methods are limited in either the number of measurable parameters or throughput. Here we developed a multiplexed, unbiased framework that, by linking genetic to drug-induced changes in nearly a thousand metabolites, allows for high-throughput functional annotation of compound libraries in Escherichia coli. First, we generated a reference map of metabolic changes from CRISPR interference (CRISPRi) with 352 genes in all major essential biological processes. Next, on the basis of the comparison of genetic changes with 1,342 drug-induced metabolic changes, we made de novo predictions of compound functionality and revealed antibacterials with unconventional modes of action (MoAs). We show that our framework, combining dynamic gene silencing with metabolomics, can be adapted as a general strategy for comprehensive high-throughput analysis of compound functionality from bacteria to human cell lines.

The impact of genomic variation on protein phosphorylation states and regulatory networks.

Genomic variation impacts on cellular networks by affecting the abundance (e.g., protein levels) and the functional states (e.g., protein phosphorylation) of their components. Previous work has focused on the former, while in this context, the functional states of proteins have largely remained neglected. Here, we generated high-quality transcriptome, proteome, and phosphoproteome data for a panel of 112 genomically well-defined yeast strains. Genetic effects on transcripts were generally transmitted to the protein layer, but specific gene groups, such as ribosomal proteins, showed diverging effects on protein levels compared with RNA levels. Phosphorylation states proved crucial to unravel genetic effects on signaling networks. Correspondingly, genetic variants that cause phosphorylation changes were mostly different from those causing abundance changes in the respective proteins. Underscoring their relevance for cell physiology, phosphorylation traits were more strongly correlated with cell physiological traits such as chemical compound resistance or cell morphology, compared with transcript or protein abundance. This study demonstrates how molecular networks mediate the effects of genomic variants to cellular traits and highlights the particular importance of protein phosphorylation.

Early diagnosis and better rhythm management to improve outcomes in patients with atrial fibrillation: the 8th AFNET/EHRA consensus conference.

Despite marked progress in the management of atrial fibrillation (AF), detecting AF remains difficult and AF-related complications cause unacceptable morbidity and mortality even on optimal current therapy. This document summarizes the key outcomes of the 8th AFNET/EHRA Consensus Conference of the Atrial Fibrillation NETwork (AFNET) and the European Heart Rhythm Association (EHRA). Eighty-three international experts met in Hamburg for 2 days in October 2021. Results of the interdisciplinary, hybrid discussions in breakout groups and the plenary based on recently published and unpublished observations are summarized in this consensus paper to support improved care for patients with AF by guiding prevention, individualized management, and research strategies. The main outcomes are (i) new evidence supports a simple, scalable, and pragmatic population-based AF screening pathway; (ii) rhythm management is evolving from therapy aimed at improving symptoms to an integrated domain in the prevention of AF-related outcomes, especially in patients with recently diagnosed AF; (iii) improved characterization of atrial cardiomyopathy may help to identify patients in need for therapy; (iv) standardized assessment of cognitive function in patients with AF could lead to improvement in patient outcomes; and (v) artificial intelligence (AI) can support all of the above aims, but requires advanced interdisciplinary knowledge and collaboration as well as a better medico-legal framework. Implementation of new evidence-based approaches to AF screening and rhythm management can improve outcomes in patients with AF. Additional benefits are possible with further efforts to identify and target atrial cardiomyopathy and cognitive impairment, which can be facilitated by AI.

Sensitive Quantitative Proteomics of Human Hematopoietic Stem and Progenitor Cells by Data-independent Acquisition Mass Spectrometry.

Physiological processes in multicellular organisms depend on the function and interactions of specialized cell types operating in context. Some of these cell types are rare and thus obtainable only in minute quantities. For example, tissue-specific stem and progenitor cells are numerically scarce, but functionally highly relevant, and fulfill critical roles in development, tissue maintenance, and disease. Whereas low numbers of cells are routinely analyzed by genomics and transcriptomics, corresponding proteomic analyses have so far not been possible due to methodological limitations. Here we describe a sensitive and robust quantitative technique based on data-independent acquisition mass spectrometry. We quantified the proteome of sets of 25,000 human hematopoietic stem/multipotent progenitor cells (HSC/MPP) and three committed progenitor cell subpopulations of the myeloid differentiation pathway (common myeloid progenitors, megakaryocyte-erythrocyte progenitors, and granulocyte-macrophage progenitors), isolated by fluorescence-activated cell sorting from five healthy donors. On average, 5,851 protein groups were identified per sample. A subset of 4,131 stringently filtered protein groups was quantitatively compared across the 20 samples, defining unique signatures for each subpopulation. A comparison of proteomic and transcriptomic profiles indicated HSC/MPP-specific divergent regulation of biochemical functions such as telomerase maintenance and quiescence-inducing enzymes, including isocitrate dehydrogenases. These are essential for maintaining stemness and were detected at proteome, but not transcriptome, level. The method is equally applicable to almost any rare cell type, including healthy and cancer stem cells or physiologically and pathologically infiltrating cell populations. It thus provides essential new information toward the detailed biochemical understanding of cell development and functionality in health and disease.

TRIC: an automated alignment strategy for reproducible protein quantification in targeted proteomics.

Next-generation mass spectrometric (MS) techniques such as SWATH-MS have substantially increased the throughput and reproducibility of proteomic analysis, but ensuring consistent quantification of thousands of peptide analytes across multiple liquid chromatography-tandem MS (LC-MS/MS) runs remains a challenging and laborious manual process. To produce highly consistent and quantitatively accurate proteomics data matrices in an automated fashion, we developed TRIC (http://proteomics.ethz.ch/tric/), a software tool that utilizes fragment-ion data to perform cross-run alignment, consistent peak-picking and quantification for high-throughput targeted proteomics. TRIC reduced the identification error compared to a state-of-the-art SWATH-MS analysis without alignment by more than threefold at constant recall while correcting for highly nonlinear chromatographic effects. On a pulsed-SILAC experiment performed on human induced pluripotent stem cells, TRIC was able to automatically align and quantify thousands of light and heavy isotopic peak groups. Thus, TRIC fills a gap in the pipeline for automated analysis of massively parallel targeted proteomics data sets.

Data-independent acquisition-based SWATH-MS for quantitative proteomics: a tutorial.

Many research questions in fields such as personalized medicine, drug screens or systems biology depend on obtaining consistent and quantitatively accurate proteomics data from many samples. SWATH-MS is a specific variant of data-independent acquisition (DIA) methods and is emerging as a technology that combines deep proteome coverage capabilities with quantitative consistency and accuracy. In a SWATH-MS measurement, all ionized peptides of a given sample that fall within a specified mass range are fragmented in a systematic and unbiased fashion using rather large precursor isolation windows. To analyse SWATH-MS data, a strategy based on peptide-centric scoring has been established, which typically requires prior knowledge about the chromatographic and mass spectrometric behaviour of peptides of interest in the form of spectral libraries and peptide query parameters. This tutorial provides guidelines on how to set up and plan a SWATH-MS experiment, how to perform the mass spectrometric measurement and how to analyse SWATH-MS data using peptide-centric scoring. Furthermore, concepts on how to improve SWATH-MS data acquisition, potential trade-offs of parameter settings and alternative data analysis strategies are discussed.

Reproducible and consistent quantification of the Saccharomyces cerevisiae proteome by SWATH-mass spectrometry.

Targeted mass spectrometry by selected reaction monitoring (S/MRM) has proven to be a suitable technique for the consistent and reproducible quantification of proteins across multiple biological samples and a wide dynamic range. This performance profile is an important prerequisite for systems biology and biomedical research. However, the method is limited to the measurements of a few hundred peptides per LC-MS analysis. Recently, we introduced SWATH-MS, a combination of data independent acquisition and targeted data analysis that vastly extends the number of peptides/proteins quantified per sample, while maintaining the favorable performance profile of S/MRM. Here we applied the SWATH-MS technique to quantify changes over time in a large fraction of the proteome expressed in Saccharomyces cerevisiae in response to osmotic stress. We sampled cell cultures in biological triplicates at six time points following the application of osmotic stress and acquired single injection data independent acquisition data sets on a high-resolution 5600 tripleTOF instrument operated in SWATH mode. Proteins were quantified by the targeted extraction and integration of transition signal groups from the SWATH-MS datasets for peptides that are proteotypic for specific yeast proteins. We consistently identified and quantified more than 15,000 peptides and 2500 proteins across the 18 samples. We demonstrate high reproducibility between technical and biological replicates across all time points and protein abundances. In addition, we show that the abundance of hundreds of proteins was significantly regulated upon osmotic shock, and pathway enrichment analysis revealed that the proteins reacting to osmotic shock are mainly involved in the carbohydrate and amino acid metabolism. Overall, this study demonstrates the ability of SWATH-MS to efficiently generate reproducible, consistent, and quantitatively accurate measurements of a large fraction of a proteome across multiple samples.

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.

Quantitative variability of 342 plasma proteins in a human twin population.

The degree and the origins of quantitative variability of most human plasma proteins are largely unknown. Because the twin study design provides a natural opportunity to estimate the relative contribution of heritability and environment to different traits in human population, we applied here the highly accurate and reproducible SWATH mass spectrometry technique to quantify 1,904 peptides defining 342 unique plasma proteins in 232 plasma samples collected longitudinally from pairs of monozygotic and dizygotic twins at intervals of 2-7 years, and proportioned the observed total quantitative variability to its root causes, genes, and environmental and longitudinal factors. The data indicate that different proteins show vastly different patterns of abundance variability among humans and that genetic control and longitudinal variation affect protein levels and biological processes to different degrees. The data further strongly suggest that the plasma concentrations of clinical biomarkers need to be calibrated against genetic and temporal factors. Moreover, we identified 13 cis-SNPs significantly influencing the level of specific plasma proteins. These results therefore have immediate implications for the effective design of blood-based biomarker studies.

Conserved peptide fragmentation as a benchmarking tool for mass spectrometers and a discriminating feature for targeted proteomics.

Quantifying the similarity of spectra is an important task in various areas of spectroscopy, for example, to identify a compound by comparing sample spectra to those of reference standards. In mass spectrometry based discovery proteomics, spectral comparisons are used to infer the amino acid sequence of peptides. In targeted proteomics by selected reaction monitoring (SRM) or SWATH MS, predetermined sets of fragment ion signals integrated over chromatographic time are used to identify target peptides in complex samples. In both cases, confidence in peptide identification is directly related to the quality of spectral matches. In this study, we used sets of simulated spectra of well-controlled dissimilarity to benchmark different spectral comparison measures and to develop a robust scoring scheme that quantifies the similarity of fragment ion spectra. We applied the normalized spectral contrast angle score to quantify the similarity of spectra to objectively assess fragment ion variability of tandem mass spectrometric datasets, to evaluate portability of peptide fragment ion spectra for targeted mass spectrometry across different types of mass spectrometers and to discriminate target assays from decoys in targeted proteomics. Altogether, this study validates the use of the normalized spectral contrast angle as a sensitive spectral similarity measure for targeted proteomics, and more generally provides a methodology to assess the performance of spectral comparisons and to support the rational selection of the most appropriate similarity measure. The algorithms used in this study are made publicly available as an open source toolset with a graphical user interface.

Glycoproteomic analysis of prostate cancer tissues by SWATH mass spectrometry discovers N-acylethanolamine acid amidase and protein tyrosine kinase 7 as signatures for tumor aggressiveness.

The identification of biomarkers indicating the level of aggressiveness of prostate cancer (PCa) will address the urgent clinical need to minimize the general overtreatment of patients with non-aggressive PCa, who account for the majority of PCa cases. Here, we isolated formerly N-linked glycopeptides from normal prostate (n = 10) and from non-aggressive (n = 24), aggressive (n = 16), and metastatic (n = 25) PCa tumor tissues and analyzed the samples using SWATH mass spectrometry, an emerging data-independent acquisition method that generates a single file containing fragment ion spectra of all ionized species of a sample. The resulting datasets were searched using a targeted data analysis strategy in which an a priori spectral reference library representing known N-glycosites of the human proteome was used to identify groups of signals in the SWATH mass spectrometry data. On average we identified 1430 N-glycosites from each sample. Out of those, 220 glycoproteins showed significant quantitative changes associated with diverse biological processes involved in PCa aggressiveness and metastasis and indicated functional relationships. Two glycoproteins, N-acylethanolamine acid amidase and protein tyrosine kinase 7, that were significantly associated with aggressive PCa in the initial sample cohort were further validated in an independent set of patient tissues using tissue microarray analysis. The results suggest that N-acylethanolamine acid amidase and protein tyrosine kinase 7 may be used as potential tissue biomarkers to avoid overtreatment of non-aggressive PCa.

PDZ domain-binding motif regulates cardiomyocyte compartment-specific NaV1.5 channel expression and function.

BACKGROUND: Sodium channel NaV1.5 underlies cardiac excitability and conduction. The last 3 residues of NaV1.5 (Ser-Ile-Val) constitute a PDZ domain-binding motif that interacts with PDZ proteins such as syntrophins and SAP97 at different locations within the cardiomyocyte, thus defining distinct pools of NaV1.5 multiprotein complexes. Here, we explored the in vivo and clinical impact of this motif through characterization of mutant mice and genetic screening of patients. METHODS AND RESULTS: To investigate in vivo the regulatory role of this motif, we generated knock-in mice lacking the SIV domain (ΔSIV). ΔSIV mice displayed reduced NaV1.5 expression and sodium current (INa), specifically at the lateral myocyte membrane, whereas NaV1.5 expression and INa at the intercalated disks were unaffected. Optical mapping of ΔSIV hearts revealed that ventricular conduction velocity was preferentially decreased in the transversal direction to myocardial fiber orientation, leading to increased anisotropy of ventricular conduction. Internalization of wild-type and ΔSIV channels was unchanged in HEK293 cells. However, the proteasome inhibitor MG132 rescued ΔSIV INa, suggesting that the SIV motif is important for regulation of NaV1.5 degradation. A missense mutation within the SIV motif (p.V2016M) was identified in a patient with Brugada syndrome. The mutation decreased NaV1.5 cell surface expression and INa when expressed in HEK293 cells. CONCLUSIONS: Our results demonstrate the in vivo significance of the PDZ domain-binding motif in the correct expression of NaV1.5 at the lateral cardiomyocyte membrane and underline the functional role of lateral NaV1.5 in ventricular conduction. Furthermore, we reveal a clinical relevance of the SIV motif in cardiac disease.

Suppression of PPARß, and DHA treatment, inhibit NaV1.5 and NHE-1 pro-invasive activities.

Peroxisome proliferator-activated receptor ß (PPARß) and NaV1.5 voltage-gated sodium channels have independently been shown to regulate human breast cancer cell invasiveness. The n-3 polyunsaturated docosahexaenoic acid (DHA, 22:6n-3), a natural ligand of PPAR, is effective in increasing survival and chemotherapy efficacy in breast cancer patient with metastasis. DHA reduces breast cancer cell invasiveness and it also inhibits PPARß expression. We have shown previously that NaV1.5 promotes MDA-MB-231 breast cancer cells invasiveness by potentiating the activity of Na(+)/H(+) exchanger type 1 (NHE-1), the major regulator of H(+) efflux in these cells. We report here that DHA inhibited NaV1.5 current and NHE-1 activity in human breast cancer cells, and in turn reduced NaV1.5-dependent cancer cell invasiveness. For the first time, we show that antagonizing PPARß, or inhibiting its expression, reduced NaV1.5 mRNA and protein expression and NaV1.5 current, as well as NHE-1 activity and cell invasiveness. Consistent with these results, the DHA-induced reduction of both NaV1.5 expression and NHE-1 activity was abolished in cancer cells knocked-down for the expression of PPARß (shPPARß). This demonstrates a direct link between the inhibition of PPARß expression and the inhibition of Nav1.5/NHE-1 activities and breast cancer cell invasiveness. This study provides new mechanistic data advocating for the use of natural fatty acids such as DHA to block the development of breast cancer metastases.

Phosphoproteomic analyses reveal novel cross-modulation mechanisms between two signaling pathways in yeast.

Cells respond to environmental stimuli via specialized signaling pathways. Concurrent stimuli trigger multiple pathways that integrate information, predominantly via protein phosphorylation. Budding yeast responds to NaCl and pheromone via two mitogen-activated protein kinase cascades, the high osmolarity, and the mating pathways, respectively. To investigate signal integration between these pathways, we quantified the time-resolved phosphorylation site dynamics after pathway co-stimulation. Using shotgun mass spectrometry, we quantified 2,536 phosphopeptides across 36 conditions. Our data indicate that NaCl and pheromone affect phosphorylation events within both pathways, which thus affect each other at more levels than anticipated, allowing for information exchange and signal integration. We observed a pheromone-induced down-regulation of Hog1 phosphorylation due to Gpd1, Ste20, Ptp2, Pbs2, and Ptc1. Distinct Ste20 and Pbs2 phosphosites responded differently to the two stimuli, suggesting these proteins as key mediators of the information exchange. A set of logic models was then used to assess the role of measured phosphopeptides in the crosstalk. Our results show that the integration of the response to different stimuli requires complex interconnections between signaling pathways.

Cardiac sodium channel NaV1.5 distribution in myocytes via interacting proteins: the multiple pool model.

The cardiac sodium current (INa) is responsible for the rapid depolarization of cardiac cells, thus allowing for their contraction. It is also involved in regulating the duration of the cardiac action potential (AP) and propagation of the impulse throughout the myocardium. Cardiac INa is generated by the voltage-gated Na(+) channel, NaV1.5, a 2016-residue protein which forms the pore of the channel. Over the past years, hundreds of mutations in SCN5A, the human gene coding for NaV1.5, have been linked to many cardiac electrical disorders, including the congenital and acquired long QT syndrome, Brugada syndrome, conduction slowing, sick sinus syndrome, atrial fibrillation, and dilated cardiomyopathy. Similar to many membrane proteins, NaV1.5 has been found to be regulated by several interacting proteins. In some cases, these different proteins, which reside in distinct membrane compartments (i.e. lateral membrane vs. intercalated disks), have been shown to interact with the same regulatory domain of NaV1.5, thus suggesting that several pools of NaV1.5 channels may co-exist in cardiac cells. The aim of this review article is to summarize the recent works that demonstrate its interaction with regulatory proteins and illustrate the model that the sodium channel NaV1.5 resides in distinct and different pools in cardiac cells. This article is part of a Special Issue entitled: Cardiomyocyte Biology: Cardiac Pathways of Differentiation, Metabolism and Contraction.

Ranolazine inhibits NaV1.5-mediated breast cancer cell invasiveness and lung colonization.

BACKGROUND: Na(V)1.5 voltage-gated sodium channels are abnormally expressed in breast tumours and their expression level is associated with metastatic occurrence and patients' death. In breast cancer cells, Na(V)1.5 activity promotes the proteolytic degradation of the extracellular matrix and enhances cell invasiveness. FINDINGS: In this study, we showed that the extinction of Na(V)1.5 expression in human breast cancer cells almost completely abrogated lung colonisation in immunodepressed mice (NMRI nude). Furthermore, we demonstrated that ranolazine (50 µM) inhibited Na(V)1.5 currents in breast cancer cells and reduced Na(V)1.5-related cancer cell invasiveness in vitro. In vivo, the injection of ranolazine (50 mg/kg/day) significantly reduced lung colonisation by Na(V)1.5-expressing human breast cancer cells. CONCLUSIONS: Taken together, our results demonstrate the importance of Na(V)1.5 in the metastatic colonisation of organs by breast cancer cells and indicate that small molecules interfering with Na(V) activity, such as ranolazine, may represent powerful pharmacological tools to inhibit metastatic development and improve cancer treatments.