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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. ISSN:1548-7105 ISSN:1548-7091

Purpose: The clinical standard treatment for patients with malignant pleural mesothelioma (MPM) includes a cisplatin-based chemotherapy, leading to reduction of tumor size in only a minority of patients. Predicting response to chemotherapy in patients with MPM by using a genetic marker would, therefore, enable patient stratification. Experimental Design: In this retrospective biomarker study, eligible patients had resectable MPM, measurable disease, and available primary MPM tissue. All patients underwent first-line treatment with cisplatin and pemetrexed, followed by surgery. Thorough molecular analysis was performed (whole-exome and targeted deep sequencing, and copy-number analyses), and also mechanistic in vitro data (viability assays, Western blots, and immunoprecipitation) using mesothelioma cell lines with and without siRNA-mediated BRCA1-associated protein 1 (BAP1) knockdown were provided. Results: In a training cohort of patients with MPM (n = 28), mutations or deletions of BAP1 each predicted resistance to chemotherapy in patients with primary MPM. The negative predictive value of BAP1 loss in patients with MPM was confirmed by amplicon sequencing and copy-number array technology in an independent test cohort (n = 39). Preliminary mechanistic studies using siRNA-based knockdown of BAP1 in MPM cell culture models along with immunoprecipitation assays confirmed chemoresistance in vitro, possibly through inhibition of apoptosis and transcriptional regulation of the BAP1/HCF1/E2F1 axis. Conclusions: Alterations in BAP1 in MPM were a negative predictor for response to chemotherapy and could possibly be used as a companion biomarker for treatment decision.

The molecular nanoscale organization of the surfaceome is a fundamental regulator of cellular signaling in health and disease. Technologies for mapping the spatial relationships of cell surface receptors and their extracellular signaling synapses would unlock theranostic opportunities to target protein communities and the possibility to engineer extracellular signaling. Here, we develop an optoproteomic technology termed LUX-MS that enables the targeted elucidation of acute protein interactions on and in between living cells using light-controlled singlet oxygen generators (SOG). By using SOG-coupled antibodies, small molecule drugs, biologics and intact viral particles, we demonstrate the ability of LUX-MS to decode ligand receptor interactions across organisms and to discover surfaceome receptor nanoscale organization with direct implications for drug action. Furthermore, by coupling SOG to antigens we achieved light-controlled molecular mapping of intercellular signaling within functional immune synapses between antigen-presenting cells and CD8+ T cells providing insights into T cell activation with spatiotemporal specificity. LUX-MS based decoding of surfaceome signaling architectures thereby provides a molecular framework for the rational development of theranostic strategies., Nature Communications, 12 (1), ISSN:2041-1723

Listeria monocytogenesis an opportunistic foodborne pathogen responsible for listeriosis, a potentially fatal foodborne disease. Many differentListeriastrains and serotypes exist, but a proteogenomic resource that bridges the gap in our molecular understanding of the relationships between theListeriagenotypes and phenotypes via proteotypes is still missing. Here we devised a next-generation proteogenomics strategy that enables the community to rapidly proteotypeListeriastrains and relate this information back to the genotype. Based on sequencing andde novoassembly of the two most commonly usedListeriamodel strains, EGD-e and ScottA, we established two comprehensiveListeriaproteogenomic databases. A genome comparison established core- and strain-specific genes potentially responsible for virulence differences. Next, we established a DIA/SWATH-based proteotyping strategy, including a new and robust sample preparation workflow, that enables the reproducible, sensitive, and relative quantitative measurement ofListeriaproteotypes. This reusable and publically available DIA/SWATH library covers 70% of open reading frames ofListeriaand represents the most extensive spectral library forListeriaproteotype analysis to date. We used these two new resources to investigate theListeriaproteotype in states mimicking the upper gastrointestinal passage. Exposure ofListeriato bile salts at 37 °C, which simulates conditions encountered in the duodenum, showed significant proteotype perturbations including an increase of FlaA, the structural protein of flagella. Given thatListeriais known to lose its flagella above 30 °C, this was an unexpected finding. The formation of flagella, which might have implications on infectivity, was validated by parallel reaction monitoring and light and scanning electron microscopy.flaAtranscript levels were not significantly different with and without exposure to bile salts at 37 °C, suggesting regulation at the post-transcriptional level. Together, these analyses provide a comprehensive proteogenomic resource and toolbox for theListeriacommunity enabling the analysis ofListeriagenotype-proteotype-phenotype relationships.

Advancements in mass spectrometry‐based proteomics have enabled experiments encompassing hundreds of samples. While these large sample sets deliver much‐needed statistical power, handling them introduces technical variability known as batch effects. Here, we present a step‐by‐step protocol for the assessment, normalization, and batch correction of proteomic data. We review established methodologies from related fields and describe solutions specific to proteomic challenges, such as ion intensity drift and missing values in quantitative feature matrices. Finally, we compile a set of techniques that enable control of batch effect adjustment quality. We provide an R package, "proBatch", containing functions required for each step of the protocol. We demonstrate the utility of this methodology on five proteomic datasets each encompassing hundreds of samples and consisting of multiple experimental designs. In conclusion, we provide guidelines and tools to make the extraction of true biological signal from large proteomic studies more robust and transparent, ultimately facilitating reliable and reproducible research in clinical proteomics and systems biology., In mass spectrometry‐based proteomics, handling large sample sets introduces technical variability known as batch effects. This tutorial provides guidelines and tools for the assessment, normalization, and batch correction of proteomics data.

Proteases are among the largest protein families and critical regulators of biochemical processes like apoptosis and blood coagulation. Knowledge of proteases has been expanded by the development of proteomic approaches, however, technology for multiplexed screening of proteases within native environments is currently lacking behind. Here we introduce a simple method to profile protease activity based on isolation of protease products from native lysates using a 96FASP filter, their analysis in a mass spectrometer and a custom data analysis pipeline. The method is significantly faster, cheaper, technically less demanding, easy to multiplex and produces accurate protease fingerprints. Using the blood cascade proteases as a case study, we obtain protease substrate profiles that can be used to map specificity, cleavage entropy and allosteric effects and to design protease probes. The data further show that protease substrate predictions enable the selection of potential physiological substrates for targeted validation in biochemical assays., Nature Communications, 12 (1), ISSN:2041-1723

The application and integration of molecular profiling technologies create novel opportunities for personalized medicine. Here, we introduce the Tumor Profiler Study, an observational trial combining a prospective diagnostic approach to assess the relevance of in-depth tumor profiling to support clinical decision-making with an exploratory approach to improve the biological understanding of the disease.

Cancer has no borders: Generation and analysis of molecular data across multiple centers worldwide is necessary to gain statistically significant clinical insights for the benefit of patients. Here we conceived and standardized a proteotype data generation and analysis workflow enabling distributed data generation and evaluated the quantitative data generated across laboratories of the international Cancer Moonshot consortium. Using harmonized mass spectrometry (MS) instrument platforms and standardized data acquisition procedures, we demonstrate robust, sensitive, and reproducible data generation across eleven international sites on seven consecutive days in a 24/7 operation mode. The data presented from the high-resolution MS1-based quantitative data-independent acquisition (HRMS1-DIA) workflow shows that coordinated proteotype data acquisition is feasible from clinical specimens using such standardized strategies. This work paves the way for the distributed multi-omic digitization of large clinical specimen cohorts across multiple sites as a prerequisite for turning molecular precision medicine into reality., Distributed multi-omic digitization of clinical specimen across multiple sites is a prerequisite for turning molecular precision medicine into reality. Here, the authors show that coordinated proteotype data acquisition is feasible using standardized MS data acquisition and analysis strategies.

MassIVE.quant is a repository infrastructure and data resource for reproducible quantitative mass spectrometry-based proteomics, which is compatible with all mass spectrometry data acquisition types and computational analysis tools. A branch structure enables MassIVE.quant to systematically store raw experimental data, metadata of the experimental design, scripts of the quantitative analysis workflow, intermediate input and output files, as well as alternative reanalyses of the same dataset. This work was supported in part by NSF CAREER award no. DBI-1054826, grant no. NSF DBI-1759736 and the Chan-Zuckerberg foundation to O.V., grant no. NIH-NLM 1R01LM013115 to N.B. and O.V., NSF award no. ABI 1759980, NIH award nos. P41GM103484 and R24GM127667 to N.B. and the Personalized Health and Related Technologies (grant no. PHRT 0-21411-18) strategic focus area of ETH to B.W. The CRG/UPF Proteomics Unit is part of the Spanish Infrastructure for Omics Technologies (ICTS OmicsTech) and it is a member of the ProteoRed PRB3 consortium that is supported by grant no. PT17/0019 of the PE I+D+i 2013–2016 from the Instituto de Salud Carlos III (ISCIII) and ERDF. We acknowledge support from the Spanish Ministry of Science, Innovation and Universities, ‘Centro de Excelencia Severo Ochoa 2013–2017’, SEV-2012–0208 and Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement de la Generalitat de Catalunya (grant no. 2017SGR595). This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement no. 823839 (EPIC-XS). Y.P.-R. acknowledges the Wellcome Trust (grant no. 208391/Z/17/Z).

Pulsed electromagnetic fields (PEMFs) are capable of specifically activating a TRPC1‐mitochondrial axis underlying cell expansion and mitohormetic survival adaptations. This study characterizes cell‐derived vesicles (CDVs) generated from C2C12 murine myoblasts and shows that they are equipped with the sufficient molecular machinery to confer mitochondrial respiratory capacity and associated proliferative responses upon their fusion with recipient cells. CDVs derived from wild type C2C12 myoblasts include the cation‐permeable transient receptor potential (TRP) channels, TRPC1 and TRPA1, and directly respond to PEMF exposure with TRPC1‐mediated calcium entry. By contrast, CDVs derived from C2C12 muscle cells in which TRPC1 has been genetically knocked‐down using CRISPR/Cas9 genome editing, do not. Wild type C2C12‐derived CDVs are also capable of restoring PEMF‐induced proliferative and mitochondrial activation in two C2C12‐derived TRPC1 knockdown clonal cell lines in accordance to their endogenous degree of TRPC1 suppression. C2C12 wild type CDVs respond to menthol with calcium entry and accumulation, likewise verifying TRPA1 functional gating and further corroborating compartmental integrity. Proteomic and lipidomic analyses confirm the surface membrane origin of the CDVs providing an initial indication of the minimal cellular machinery required to recover mitochondrial function. CDVs hence possess the potential of restoring respiratory and proliferative capacities to senescent cells and tissues., Advanced Biosystems, 4 (11), ISSN:2366-7478

To orchestrate context-dependent signalling programmes, poxviruses encode two dual-specificity enzymes, the F10 kinase and the H1 phosphatase. These signalling mediators are essential for poxvirus production, yet their substrate profiles and systems-level functions remain enigmatic. Using a phosphoproteomic screen of cells infected with wild-type, F10 and H1 mutant vaccinia viruses, we systematically defined the viral signalling network controlled by these enzymes. Quantitative cross-comparison revealed 33 F10 and/or H1 phosphosites within 17 viral proteins. Using this proteotype dataset to inform genotype-phenotype relationships, we found that H1-deficient virions harbour a hidden hypercleavage phenotype driven by reversible phosphorylation of the virus protease I7 (S134). Quantitative phosphoproteomic profiling further revealed that the phosphorylation-dependent activity of the viral early transcription factor, A7 (Y367), underlies the transcription-deficient phenotype of H1 mutant virions. Together, these results highlight the utility of combining quantitative proteotype screens with mutant viruses to uncover proteotype-phenotype-genotype relationships that are masked by classical genetic studies.

Summary The identification of cell surface proteins on stem cells or stem cell derivatives is a key strategy for the functional characterization, isolation, and understanding of stem cell population dynamics. Here, using an integrated mass spectrometry- and microarray-based approach, we analyzed the surface proteome and transcriptome of cardiac progenitor cells (CPCs) generated from the stage-specific differentiation of mouse and human pluripotent stem cells. Through bioinformatics analysis, we have identified and characterized FZD4 as a marker for lateral plate mesoderm. Additionally, we utilized FZD4, in conjunction with FLK1 and PDGFRA, to further purify CPCs and increase cardiomyocyte (CM) enrichment in both mouse and human systems. Moreover, we have shown that NORRIN presented to FZD4 further increases CM output via proliferation through the canonical WNT pathway. Taken together, these findings demonstrate a role for FZD4 in mammalian cardiac development., Highlights • Identified and characterized FZD4 as a new marker for lateral plate mesoderm • FZD4, in conjunction with FLK1 and PDGFRA, increases cardiomyocyte enrichment • FZD4 is expressed in the human system and shows enrichment in cardiomyocytes • NORRIN addition shows increase in cardiomyocyte output from FZD4 progenitor cells, In this article, Zandstra and colleagues have identified FZD4 as a new marker for lateral plate mesoderm. Using FZD4, they showed an increase in cardiac progenitor cell purity and a subsequent increase in cardiomyocyte induction in both the mouse and human systems. These findings demonstrate a role for FZD4 in mammalian cardiac development.

Cancer has no borders: Generation and analysis of molecular data across multiple centers worldwide is necessary to gain statistically significant clinical insights for the benefit of patients. Here we conceived and standardized a proteotype data generation and analysis workflow enabling distributed data generation and evaluated the quantitative data generated across laboratories of the international Cancer Moonshot consortium. Using harmonized mass spectrometry (MS) instrument platforms and standardized data acquisition procedures, we demonstrated robust, sensitive, and reproducible data generation across eleven sites in nine countries on seven consecutive days in a 24/7 operation mode. The data presented from the high-resolution MS1-based quantitative data-independent acquisition (HRMS1-DIA) workflow shows that coordinated proteotype data acquisition is feasible from clinical specimens using such standardized strategies. This work paves the way for the distributed multi-omic digitization of large clinical specimen cohorts across multiple sites as a prerequisite for turning molecular precision medicine into reality.

High-density lipoproteins (HDL) contain hundreds of lipid species and proteins and exert many potentially vasoprotective and antidiabetogenic activities on cells. To resolve structure-function-disease relationships of HDL, we characterized HDL of 51 healthy subjects and 98 patients with diabetes (T2DM), coronary heart disease (CHD), or both for protein and lipid composition, as well as functionality in 5 cell types. The integration of 40 clinical characteristics, 34 nuclear magnetic resonance (NMR) features, 182 proteins, 227 lipid species, and 12 functional read-outs by high-dimensional statistical modeling revealed, first, that CHD and T2DM are associated with different changes of HDL in size distribution, protein and lipid composition, and function. Second, different cellular functions of HDL are weakly correlated with each other and determined by different structural components. Cholesterol efflux capacity (CEC) was no proxy of other functions. Third, 3 potentially novel determinants of HDL function were identified and validated by the use of artificially reconstituted HDL, namely the sphingadienine-based sphingomyelin SM 42:3 and glycosylphosphatidylinositol-phospholipase D1 for the ability of HDL to inhibit starvation-induced apoptosis of human aortic endothelial cells and apolipoprotein F for the ability of HDL to promote maximal respiration of brown adipocytes.

Neurons are highly compartmentalized cells with tightly controlled subcellular protein organization. While brain transcriptome, connectome and global proteome maps are being generated, system-wide analysis of temporal protein dynamics at the subcellular level are currently lacking. Here, we perform a temporally-resolved surfaceome analysis of primary neuron cultures and reveal dynamic surface protein clusters that reflect the functional requirements during distinct stages of neuronal development. Direct comparison of surface and total protein pools during development and homeostatic synaptic scaling demonstrates system-wide proteostasis-independent remodeling of the neuronal surface, illustrating widespread regulation on the level of surface trafficking. Finally, quantitative analysis of the neuronal surface during chemical long-term potentiation (cLTP) reveals fast externalization of diverse classes of surface proteins beyond the AMPA receptor, providing avenues to investigate the requirement of exocytosis for LTP. Our resource (neurosurfaceome.ethz.ch) highlights the importance of subcellular resolution for systems-level understanding of cellular processes., Nature Communications, 11 (1), ISSN:2041-1723

There is an urgent need for new antibiotics against Gram-negative pathogens that are resistant to carbapenem and third-generation cephalosporins, against which antibiotics of last resort have lost most of their efficacy. Here we describe a class of synthetic antibiotics inspired by scaffolds derived from natural products. These chimeric antibiotics contain a β-hairpin peptide macrocycle linked to the macrocycle found in the polymyxin and colistin family of natural products. They are bactericidal and have a mechanism of action that involves binding to both lipopolysaccharide and the main component (BamA) of the β-barrel folding complex (BAM) that is required for the folding and insertion of β-barrel proteins into the outer membrane of Gram-negative bacteria. Extensively optimized derivatives show potent activity against multidrug-resistant pathogens, including all of the Gram-negative members of the ESKAPE pathogens1. These derivatives also show favourable drug properties and overcome colistin resistance, both in vitro and in vivo. The lead candidate is currently in preclinical toxicology studies that—if successful—will allow progress into clinical studies that have the potential to address life-threatening infections by the Gram-negative pathogens, and thus to resolve a considerable unmet medical need. A class of chimeric synthetic antibiotics that bind to lipopolysaccharide and BamA shows potent activity against multidrug-resistant Gram-negative bacteria, with the potential to address life-threatening infections.

Exposure to complex chemical mixtures requires a tiered strategy for efficient mixture risk assessment. As a part of the EuroMix project we developed an adverse outcome pathway (AOP)-based assay toolbox to investigate the combined effects of the liver steatosis-inducing compounds imazalil, thiacloprid, and clothianidin in human HepaRG hepatocarcinoma cells. Compound-specific relative potency factors were determined using a benchmark dose approach. Equipotent mixtures were tested for nuclear receptor activation, gene and protein expression, and triglyceride accumulation, according to the molecular initiating events and key events proposed in the steatosis AOP. All three compounds affected the activity of nuclear receptors, but not key genes/proteins as proposed. Triglyceride accumulation was observed with three different methods. Mixture effects were in agreement with the assumption of dose additivity for all the combinations and endpoints tested. Compound-specific RPFs remained similar over the different endpoints studied downstream the AOP. Therefore, it might be possible to reduce testing to a smaller battery of key tests. The results demonstrate the suitability of our in vitro assay toolbox, integrated within an AOP framework and combined with the RPF approach, for the analysis of steatotic effects of chemical mixtures. However, mRNA results suggest that the steatosis AOP still needs improvement.

In analogy to biosynthetic pathways leading to bioactive natural products, synthetic fermentation generates mixtures of molecules from simple building blocks under aqueous, biocompatible conditions, allowing the resulting cultures to be directly screened for biological activity. In this work, a novel β-peptide antibiotic was successfully identified using the synthetic fermentation platform. Phenotypic screening was carried out in an initially random fashion, allowing simple identification of active cultures. Subsequent deconvolution, focused screening, and structure-activity relationship studies led to the identification of a potent antimicrobial peptide, showing strong selectivity for our model system Bacillus subtilis over human HEK293 cells. To determine the antibacterial mechanism of action, a peptide probe bearing a photoaffinity tag was readily synthesized through the use of appropriate synthetic fermentation building blocks and utilized for target identification using a quantitative mass spectrometry-based strategy. The chemoproteomic approach led to the identification of a number of bacterial membrane proteins as prospective targets. These findings were validated through binding affinity studies with penicillin-binding protein 4 using microscale thermophoresis, with the bioactive peptide showing a dissociation constant ( K

System-wide quantification of the cell surface proteotype and identification of extracellular glycosylation sites is challenging when samples are limited. Here, we miniaturize and automate the previously described Cell Surface Capture (CSC) technology, increasing sensitivity, reproducibility and throughput. We use this technology, which we call autoCSC, to create population-specific surfaceome maps of developing mouse B cells and use targeted flow cytometry to uncover developmental cell subpopulations., Nature Communications, 10 (1), ISSN:2041-1723

Cell-surface proteins are of great biomedical importance, as demonstrated by the fact that 66% of approved human drugs listed in the DrugBank database target a cell-surface protein. Despite this biomedical relevance, there has been no comprehensive assessment of the human surfaceome, and only a fraction of the predicted 5,000 human transmembrane proteins have been shown to be located at the plasma membrane. To enable analysis of the human surfaceome, we developed the surfaceome predictor SURFY, based on machine learning. As a training set, we used experimentally verified high-confidence cell-surface proteins from the Cell Surface Protein Atlas (CSPA) and trained a random forest classifier on 131 features per protein and, specifically, per topological domain. SURFY was used to predict a human surfaceome of 2,886 proteins with an accuracy of 93.5%, which shows excellent overlap with known cell-surface protein classes (i.e., receptors). In deposited mRNA data, we found that between 543 and 1,100 surfaceome genes were expressed in cancer cell lines and maximally 1,700 surfaceome genes were expressed in embryonic stem cells and derivative lines. Thus, the surfaceome diversity depends on cell type and appears to be more dynamic than the nonsurface proteome. To make the predicted surfaceome readily accessible to the research community, we provide visualization tools for intuitive interrogation (wlab.ethz.ch/surfaceome). The in silico surfaceome enables the filtering of data generated by multiomics screens and supports the elucidation of the surfaceome nanoscale organization., Proceedings of the National Academy of Sciences of the United States of America, 115 (46), ISSN:0027-8424, ISSN:1091-6490

With the increasing resistance of many Gram-negative bacteria to existing classes of antibiotics, identifying new paradigms in antimicrobial discovery is an important research priority. Of special interest are the proteins required for the biogenesis of the asymmetric Gram-negative bacterial outer membrane (OM). Seven Lpt proteins (LptA to LptG) associate in most Gram-negative bacteria to form a macromolecular complex spanning the entire envelope, which transports lipopolysaccharide (LPS) molecules from their site of assembly at the inner membrane to the cell surface, powered by adenosine 5′-triphosphate hydrolysis in the cytoplasm. The periplasmic protein LptA comprises the protein bridge across the periplasm, which connects LptB2FGC at the inner membrane to LptD/E anchored in the OM. We show here that the naturally occurring, insect-derived antimicrobial peptide thanatin targets LptA and LptD in the network of periplasmic protein-protein interactions required to assemble the Lpt complex, leading to the inhibition of LPS transport and OM biogenesis in Escherichia coli., Science Advances, 4 (11), ISSN:2375-2548

Adverse outcome pathways (AOPs) describe causal relationships between molecular perturbation and adverse cellular effects and are being increasingly adopted for linking in vitro mechanistic toxicology to in vivo data from regulatory toxicity studies. In this work, a case study was performed by developing a bioassay toolbox to assess key events in the recently proposed AOP for chemically induced liver steatosis. The toolbox is comprised of in vitro assays to measure nuclear receptor activation, gene and protein expression, lipid accumulation, mitochondrial respiration, and formation of fatty liver cells. Assay evaluation was performed in human HepaRG hepatocarcinoma cells exposed to the model compound cyproconazole, a fungicide inducing steatosis in rodents. Cyproconazole dose-dependently activated RARα and PXR, two molecular initiating events in the steatosis AOP. Moreover, cyproconazole provoked a disruption of mitochondrial functions and induced triglyceride accumulation and the formation of fatty liver cells as described in the AOP. Gene and protein expression analysis, however, showed expression changes different from those proposed in the AOP, thus suggesting that the current version of the AOP might not fully reflect the complex mechanisms linking nuclear receptor activation and liver steatosis. Our study shows that cyproconazole induces steatosis in human liver cells in vitro and demonstrates the utility of systems-based approaches in the mechanistic assessment of molecular and cellular key events in an AOP. AOP-driven in vitro testing as demonstrated can further improve existing AOPs, provide insight regarding molecular mechanisms of toxicity, and inform predictive risk assessment

The reductionist view of ‘one target-one drug’ has fueled the development of therapeutic agents to treat human disease. However, many compounds that have efficacy in vitro are inactive in complex in vivo systems. It has become clear that a molecular understanding of signaling networks is needed to address disease phenotypes in the human body. Protein signaling networks function at the molecular level through information transfer via protein-protein interactions. Cell surface exposed proteins, termed the surfaceome, are the gatekeepers between the intra- and extracellular signaling networks, translating extracellular cues into intracellular responses and vice versa. As 66% of drugs in the DrugBank target the surfaceome, these proteins are a key source for potential diagnostic and therapeutic agents. In this review article, we will discuss current knowledge about the spatial organization and molecular interactions of the surfaceome and provide a perspective on the technologies available for studying the extracellular surfaceome interaction network.

The outer membrane (OM) in Gram-negative bacteria is an asymmetric bilayer with mostly lipopolysaccharide (LPS) molecules in the outer leaflet. During OM biogenesis, new LPS molecules are transported from their site of assembly on the inner membrane to the OM by seven LPS transport proteins (LptA-G). The complex formed between the integral β-barrel OM protein LptD and the lipoprotein LptE is responsible for transporting LPS from the periplasmic side of the OM to its final location on the cell surface. Because of its essential function in many Gram-negative bacteria, the LPS transport pathway is an interesting target for the development of new antibiotics. A family of macrocyclic peptidomimetics was discovered recently that target LptD and inhibit LPS transport specifically in Pseudomonas spp. The related molecule Murepavadin is in clinical development for the treatment of life-threatening infections caused by P. aeruginosa. To characterize the interaction of these antibiotics with LptD from P. aeruginosa, we characterized the binding site by cross-linking to a photolabeling probe. We used a hypothesis-free mass spectrometry-based proteomic approach to provide evidence that the antibiotic cross-links to the periplasmic segment of LptD, containing a β-jellyroll domain and an N-terminal insert domain characteristic of Pseudomonas spp. Binding of the antibiotic to the periplasmic segment is expected to block LPS transport, consistent with the proposed mode of action and observed specificity of these antibiotics. These insights may prove valuable for the discovery of new antibiotics targeting the LPS transport pathway in other Gram-negative bacteria.

Listeria monocytogenes is a pathogenic bacterium that invades epithelial cells by activating host signaling cascades, which promote bacterial engulfment within a phagosome. The pore-forming toxin listeriolysin O (LLO), which is required for bacteria phagosomal escape, has also been associated with the activation of several signaling pathways when secreted by extracellular bacteria, including Ca2+ influx and promotion of L. monocytogenes entry. Quantitative host surfaceome analysis revealed significant quantitative remodeling of a defined set of cell surface glycoproteins upon LLO treatment, including a subset previously identified to play a role in the L. monocytogenes infection process. Our data further shows that the lysosomal-associated membrane proteins LAMP-1 and LAMP-2 are translocated to the cellular surface and those LLO-induced Ca2+ fluxes are required to trigger the surface relocalization of LAMP-1. Finally, we identify late endosomes/lysosomes as the major donor compartments of LAMP-1 upon LLO treatment and by perturbing their function, we suggest that these organelles participate in L. monocytogenes invasion., Host surfaceome remodeling modulates Listeria infection

Background Exposure of the developing brain to immune mediators, including antibodies, is postulated to increase risk for neurodevelopmental disorders and neurodegenerative disease. It has been suggested that immunoglobulin G-immune complexes (IgG-IC) activate Fc gamma receptors (FcγR) expressed on neurons to modify signaling events in these cells. However, testing this hypothesis is hindered by a paucity of data regarding neuronal FcγR expression and function. Methods FcγR transcript expression in the hippocampus, cortex, and cerebellum of neonatal male and female rats was investigated ex vivo and in mixed cultures of primary hippocampal and cortical neurons and astrocytes using quantitative PCR analyses. Expression at the protein level in mixed cultures of primary hippocampal and cortical neurons and astrocytes was determined by immunocytochemistry, western blotting, proteotype analysis, and flow cytometry. The functionality of these receptors was assessed by measuring changes in intracellular calcium levels, Erk phosphorylation, and IgG internalization following stimulation with IgG-immune complexes. Results FcgrIa, FcgrIIa, FcgrIIb, FcgrIIIa, and Fcgrt transcripts were detectable in the cortex, hippocampus, and cerebellum at postnatal days 1 and 7. These transcripts were also present in primary hippocampal and cortical cell cultures, where their expression was modulated by IFNγ. Expression of FcγRIa, FcγRIIb, and FcγRIIIa, but not FcγRIIa or FcRn proteins, was confirmed in cultured hippocampal and cortical neurons and astrocytes at the single cell level. A subpopulation of these cells co-expressed the activating FcγRIa and the inhibitory FcγRIIb. Functional analyses demonstrated that exposure of hippocampal and cortical cell cultures to IgG-IC increases intracellular calcium and Erk phosphorylation and triggers FcγR-mediated internalization of IgG. Conclusions Our data demonstrate that developing neurons and astrocytes in the hippocampus and the cortex express signaling competent FcγR. These findings suggest that IgG antibodies may influence normal neurodevelopment or function via direct interactions with FcγR on non-immune cells in the brain. ISSN:1742-2094

Accurate annotation of all protein-coding sequences (CDSs) is an essential prerequisite to fully exploit the rapidly growing repertoire of completely sequenced prokaryotic genomes. However, large discrepancies among the number of CDSs annotated by different resources, missed functional short open reading frames (sORFs), and overprediction of spurious ORFs represent serious limitations. Our strategy toward accurate and complete genome annotation consolidates CDSs from multiple reference annotation resources, ab initio gene prediction algorithms and in silico ORFs (a modified six-frame translation considering alternative start codons) in an integrated proteogenomics database (iPtgxDB) that covers the entire protein-coding potential of a prokaryotic genome. By extending the PeptideClassifier concept of unambiguous peptides for prokaryotes, close to 95% of the identifiable peptides imply one distinct protein, largely simplifying downstream analysis. Searching a comprehensive Bartonella henselae proteomics data set against such an iPtgxDB allowed us to unambiguously identify novel ORFs uniquely predicted by each resource, including lipoproteins, differentially expressed and membrane-localized proteins, novel start sites and wrongly annotated pseudogenes. Most novelties were confirmed by targeted, parallel reaction monitoring mass spectrometry, including unique ORFs and single amino acid variations (SAAVs) identified in a re-sequenced laboratory strain that are not present in its reference genome. We demonstrate the general applicability of our strategy for genomes with varying GC content and distinct taxonomic origin. We release iPtgxDBs for B. henselae, Bradyrhizobium diazoefficiens and Escherichia coli and the software to generate both proteogenomics search databases and integrated annotation files that can be viewed in a genome browser for any prokaryote., Genome Research, 27 (12), ISSN:1088-9051, ISSN:1549-5469

Cellular responses depend on the interactions of extracellular ligands, such as nutrients, growth factors, or drugs, with specific cell-surface receptors. The sensitivity of these interactions to non-physiological conditions, however, makes them challenging to study using in vitro assays. Here we present HATRIC-based ligand receptor capture (HATRIC-LRC), a chemoproteomic technology that successfully identifies target receptors for orphan ligands on living cells ranging from small molecules to intact viruses. HATRIC-LRC combines a click chemistry-based, protein-centric workflow with a water-soluble catalyst to capture ligand-receptor interactions at physiological pH from as few as 1 million cells. We show HATRIC-LRC utility for general antibody target validation within the native nanoscale organization of the surfaceome, as well as receptor identification for a small molecule ligand. HATRIC-LRC further enables the identification of complex extracellular interactomes, such as the host receptor panel for influenza A virus (IAV), the causative agent of the common flu., Nature Communications, 9 (1), ISSN:2041-1723

The in silico prediction of the best-observable “proteotypic” peptides in mass spectrometry-based workflows is a challenging problem. Being able to accurately predict such peptides would enable the informed selection of proteotypic peptides for targeted quantification of previously observed and non-observed proteins for any organism, with a significant impact for clinical proteomics and systems biology studies. Current prediction algorithms rely on physicochemical parameters in combination with positive and negative training sets to identify those peptide properties that most profoundly affect their general detectability. Here we present PeptideRank, an approach that uses learning to rank algorithm for peptide detectability prediction from shotgun proteomics data, and that eliminates the need to select a negative dataset for the training step. A large number of different peptide properties are used to train ranking models in order to predict a ranking of the best-observable peptides within a protein. Empirical evaluation with rank accuracy metrics showed that PeptideRank complements existing prediction algorithms. Our results indicate that the best performance is achieved when it is trained on organism-specific shotgun proteomics data, and that PeptideRank is most accurate for short to medium-sized and abundant proteins, without any loss in prediction accuracy for the important class of membrane proteins. Biological significance Targeted proteomics approaches have been gaining a lot of momentum and hold immense potential for systems biology studies and clinical proteomics. However, since only very few complete proteomes have been reported to date, for a considerable fraction of a proteome there is no experimental proteomics evidence that would allow to guide the selection of the best-suited proteotypic peptides (PTPs), i.e. peptides that are specific to a given proteoform and that are repeatedly observed in a mass spectrometer. We describe a novel, rank-based approach for the prediction of the best-suited PTPs for targeted proteomics applications. By building on methods developed in the field of information retrieval (e.g. web search engines like Google's PageRank), we circumvent the delicate step of selecting positive and negative training sets and at the same time also more closely reflect the experimentalist´s need for selecting e.g. the 5 most promising peptides for targeting a protein of interest. This approach allows to predict PTPs for not yet observed proteins or for organisms without prior experimental proteomics data such as many non-model organisms.

Summary Detailed knowledge of cell-surface proteins for isolating well-defined populations of human pluripotent stem cells (hPSCs) would significantly enhance their characterization and translational potential. Through a chemoproteomic approach, we developed a cell-surface proteome inventory containing 496 N-linked glycoproteins on human embryonic (hESCs) and induced PSCs (hiPSCs). Against a backdrop of human fibroblasts and 50 other cell types, >100 surface proteins of interest for hPSCs were revealed. The >30 positive and negative markers verified here by orthogonal approaches provide experimental justification for the rational selection of pluripotency and lineage markers, epitopes for cell isolation, and reagents for the characterization of putative hiPSC lines. Comparative differences between the chemoproteomic-defined surfaceome and the transcriptome-predicted surfaceome directly led to the discovery that STF-31, a reported GLUT-1 inhibitor, is toxic to hPSCs and efficient for selective elimination of hPSCs from mixed cultures., Graphical Abstract, Highlights • 496 cell surface N-glycoproteins on hPSCs • N-glycosylation site identification dictates accessible epitopes • >30 positive and negative selection markers for hPSCs are validated • STF-31 is selectively toxic to hPSCs, Gundry, Boheler, and colleagues reveal a cell surfaceome containing 496 N-linked glycoproteins identified by mass spectrometry on human pluripotent stem cells. More than 30 positive and negative markers were verified by orthogonal approaches. This resource led to the discovery that a small molecule, STF-31, is efficient for the selective elimination of pluripotent cells from mixed cultures.

Physiological responses to ligands such as peptides, proteins, pharmaceutical drugs or whole pathogens are generally mediated through interactions with specific cell surface protein receptors. Here we describe the application of TRICEPS, a specifically designed chemoproteomic reagent that can be coupled to a ligand of interest for the subsequent ligand-based capture of corresponding receptors on living cells and tissues. This is achieved by three orthogonal functionalities in TRICEPS-one that enables conjugation to an amino group containing ligands, a second for the ligand-based capture of glycosylated receptors on gently oxidized living cells and a biotin tag for purifying receptor peptides for analysis by quantitative mass spectrometry (MS). Specific receptors for the ligand of interest are identified through quantitative comparison of the identified peptides with a sample generated by a control probe with known (e.g., insulin) or no binding preferences (e.g., TRICEPS quenched with glycine). In combination with powerful statistical models, this ligand-based receptor capture (LRC) technology enables the unbiased and sensitive identification of one or several specific receptors for a given ligand under near-physiological conditions and without the need for genetic manipulations. LRC has been designed for applications with proteins but can easily be adapted for ligands ranging from peptides to intact viruses. In experiments with small ligands that bind to receptors with comparatively large extracellular domains, LRC can also reveal approximate ligand-binding sites owing to the defined spacer length of TRICEPS. Provided that sufficient quantities of the ligand and target cells are available, LRC can be carried out within 1 week.

Protein biomarkers have the potential to transform medicine as they are clinically used to diagnose diseases, stratify patients, and follow disease states. Even though a large number of potential biomarkers have been proposed over the past few years, almost none of them have been implemented so far in the clinic. One of the reasons for this limited success is the lack of technologies to validate proposed biomarker candidates in larger patient cohorts. This limitation could be alleviated by the use of antibody-independent validation methods such as selected reaction monitoring (SRM). Similar to measurements based on affinity reagents, SRM-based targeted mass spectrometry also requires the generation of definitive assays for each targeted analyte. Here, we present a library of SRM assays for 5568 N-glycosites enabling the multiplexed evaluation of clinically relevant N-glycoproteins as biomarker candidates. We demonstrate that this resource can be utilized to select SRM assay sets for cancer-associated N-glycoproteins for their subsequent multiplexed and consistent quantification in 120 human plasma samples. We show that N-glycoproteins spanning 5 orders of magnitude in abundance can be quantified and that previously reported abundance differences in various cancer types can be recapitulated. Together, the established N-glycoprotein SRMAtlas resource facilitates parallel, efficient, consistent, and sensitive evaluation of proposed biomarker candidates in large clinical sample cohorts.

Target-blind activity-based screening of molecular libraries is often used to develop first-generation compounds, but subsequent target identification is rate-limiting to developing improved agents with higher specific affinity and lower off-target binding. A fluorescently labeled nerve-binding peptide, NP41, selected by phage display, highlights peripheral nerves in vivo. Nerve highlighting has the potential to improve surgical outcomes by facilitating intraoperative nerve identification, reducing accidental nerve transection, and facilitating repair of damaged nerves. To enable screening of molecular target-specific molecules for higher nerve contrast and to identify potential toxicities, NP41's binding target was sought. Laminin-421 and -211 were identified by proximity-based labeling using singlet oxygen and by an adapted version of TRICEPS-based ligand-receptor capture to identify glycoprotein receptors via ligand cross-linking. In proximity labeling, photooxidation of a ligand-conjugated singlet oxygen generator is coupled to chemical labeling of locally oxidized residues. Photooxidation of methylene blue-NP41-bound nerves, followed by biotin hydrazide labeling and purification, resulted in light-induced enrichment of laminin subunits α4 and α2, nidogen 1, and decorin (FDR-adjusted P value < 10-7) and minor enrichment of laminin-γ1 and collagens I and VI. Glycoprotein receptor capture also identified laminin-α4 and -γ1. Laminins colocalized with NP41 within nerve sheath, particularly perineurium, where laminin-421 is predominant. Binding assays with phage expressing NP41 confirmed binding to purified laminin-421, laminin-211, and laminin-α4. Affinity for these extracellular matrix proteins explains the striking ability of NP41 to highlight degenerated nerve "ghosts" months posttransection that are invisible to the unaided eye but retain hollow laminin-rich tubular structures.

Human brown adipose tissue (BAT) has become an attractive target to combat the current epidemical spread of obesity and its associated co-morbidities. Currently, information on its functional role is primarily derived from rodent studies. Here, we present the first comparative proteotype analysis of primary human brown adipose tissue versus adjacent white adipose tissue, which reveals significant quantitative differences in protein abundances and in turn differential functional capabilities. The majority of the 318 proteins with increased abundance in BAT are associated with mitochondrial metabolism and confirm the increased oxidative capacity. In addition to uncoupling protein 1 (UCP1), the main functional effector for uncoupled respiration, we also detected the mitochondrial creatine kinases (CKMT1A/B, CKMT2), as effective modulators of ATP synthase coupled respiration, to be exclusively expressed in BAT. The abundant expression and utilization of both energy expenditure pathways in parallel highlights the complex functional involvement of BAT in human physiology., Scientific Reports, 6, ISSN:2045-2322

Mutations in dynamin 2 (DNM2) lead to dominant intermediate Charcot-Marie-Tooth neuropathy type B, while a different set of DNM2 mutations cause autosomal dominant centronuclear myopathy. In this study, we aimed to elucidate the disease mechanisms in dominant intermediate Charcot-Marie-Tooth neuropathy type B and to find explanations for the tissue-specific defects that are associated with different DNM2 mutations in dominant intermediate Charcot-Marie-Tooth neuropathy type B versus autosomal dominant centronuclear myopathy. We used tissue derived from Dnm2-deficient mice to establish an appropriate peripheral nerve model and found that dominant intermediate Charcot-Marie-Tooth neuropathy type B-associated dynamin 2 mutants, but not autosomal dominant centronuclear myopathy mutants, impaired myelination. In contrast to autosomal dominant centronuclear myopathy mutants, Schwann cells and neurons from the peripheral nervous system expressing dominant intermediate Charcot-Marie-Tooth neuropathy mutants showed defects in clathrin-mediated endocytosis. We demonstrate that, as a consequence, protein surface levels are altered in Schwann cells. Furthermore, we discovered that myelination is strictly dependent on Dnm2 and clathrin-mediated endocytosis function. Thus, we propose that altered endocytosis is a major contributing factor to the disease mechanisms in dominant intermediate Charcot-Marie-Tooth neuropathy type B.

Endogenous regeneration and repair mechanisms are responsible for replacing dead and damaged cells to maintain or enhance tissue and organ function, and one of the best examples of endogenous repair mechanisms involves skeletal muscle. Although the molecular mechanisms that regulate the differentiation of satellite cells and myoblasts toward myofibers are not fully understood, cell surface proteins that sense and respond to their environment play an important role. The cell surface capturing technology was used here to uncover the cell surface N-linked glycoprotein subproteome of myoblasts and to identify potential markers of myoblast differentiation. 128 bona fide cell surface-exposed N-linked glycoproteins, including 117 transmembrane, four glycosylphosphatidylinositol-anchored, five extracellular matrix, and two membrane-associated proteins were identified from mouse C2C12 myoblasts. The data set revealed 36 cluster of differentiation-annotated proteins and confirmed the occupancy for 235 N-linked glycosylation sites. The identification of the N-glycosylation sites on the extracellular domain of the proteins allowed for the determination of the orientation of the identified proteins within the plasma membrane. One glycoprotein transmembrane orientation was found to be inconsistent with Swiss-Prot annotations, whereas ambiguous annotations for 14 other proteins were resolved. Several of the identified N-linked glycoproteins, including aquaporin-1 and β-sarcoglycan, were found in validation experiments to change in overall abundance as the myoblasts differentiate toward myotubes. Therefore, the strategy and data presented shed new light on the complexity of the myoblast cell surface subproteome and reveal new targets for the clinically important characterization of cell intermediates during myoblast differentiation into myotubes.

Clathrin-associated endocytic adapters recruit cargoes to coated pits as a first step in endocytosis. We developed an unbiased quantitative proteomics approach to identify and quantify glycoprotein cargoes for an endocytic adapter, Dab2. Surface levels of integrins beta1, alpha1, alpha2, and alpha3 but not alpha5 or alphav chains were specifically increased on Dab2-deficient HeLa cells. Dab2 colocalizes with integrin beta1 in coated pits that are dispersed over the cell surface, suggesting that it regulates bulk endocytosis of inactive integrins. Depletion of Dab2 inhibits cell migration and polarized movement of integrin beta1 and vinculin to the leading edge. By manipulating intracellular and surface integrin beta1 levels, we show that migration speed correlates with the intracellular integrin pool but not the surface level. Together, these results suggest that Dab2 internalizes integrins freely diffusing on the cell surface and that Dab2 regulates migration, perhaps by maintaining an internal pool of integrins that can be recycled to create new adhesions at the leading edge.

Objective Adipose tissue shows a high degree of plasticity, and adipocyte hyperplasia is an important mechanism for adipose tissue expansion. Different adipose depots respond differently to an increased demand for lipid storage. Orchestrating cellular expansion in vivo requires extracellular matrix (ECM) remodeling and a high degree of interaction between cells and ECM. Methods We studied decellularized primary adipose stromal cell derived ECM of different adipose depots and reseeded them with primary adipose precursors. We tested ECM effect on adipocyte differentiation and analyzed ECM composition using proteomic and immunohistochemical approaches to identify factors in the ECM influencing adipogenesis. Results We show that the ECM of an adipose depot is the major determinant for the differentiation capacity of primary preadipocytes. Visceral adipose tissue stromal cells differentiate less than subcutaneous cells, which, in turn, are less adipogenic than BAT-derived cells. This effect is based on the ECM composition of the respective depot and not dependent on the precursor origin. Addition of vitamin C pronounces the pro-adipogenic effects of the ECM, indicating the importance of collagenous ECM in mediating the effect. Using a proteomic global and a targeted downstream analysis, we identify Flotillin 2 as a protein enriched in pro-adipogenic ECM, which is involved in orchestrating ECM to preadipocyte signaling. Conclusions We show that adipose tissue SVF secretes collagenous ECM, which directly modulates terminal differentiation of adipocyte precursors in a depot specific manner. These data demonstrate the importance of the tissue microenvironment in preadipocyte differentiation., Molecular Metabolism, 5 (10)

Bioinformatics, 30 (6), ISSN:1367-4803, ISSN:1460-2059

Background Serum biomarkers can improve diagnosis and treatment of malignant pleural mesothelioma (MPM). However, the evaluation of potential new serum biomarker candidates is hampered by a lack of assay technologies for their clinical evaluation. Here we followed a hypothesis-driven targeted proteomics strategy for the identification and clinical evaluation of MPM candidate biomarkers in serum of patient cohorts. Results Based on the hypothesis that cell surface exposed glycoproteins are prone to be released from tumor-cells to the circulatory system, we screened the surfaceome of model cell lines for potential MPM candidate biomarkers. Selected Reaction Monitoring (SRM) assay technology allowed for the direct evaluation of the newly identified candidates in serum. Our evaluation of 51 candidate biomarkers in the context of a training and an independent validation set revealed a reproducible glycopeptide signature of MPM in serum which complemented the MPM biomarker mesothelin. Conclusions Our study shows that SRM assay technology enables the direct clinical evaluation of protein-derived candidate biomarker panels for which clinically reliable ELISA’s currently do not exist.

Experience from different fields of life sciences suggests that accessible, complete reference maps of the components of the system under study are highly beneficial research tools. Examples of such maps include libraries of the spectroscopic properties of molecules, or databases of drug structures in analytical or forensic chemistry. Such maps, and methods to navigate them, constitute reliable assays to probe any sample for the presence and amount of molecules contained in the map. So far, attempts to generate such maps for any proteome have failed to reach complete proteome coverage. Here we use a strategy based on high-throughput peptide synthesis and mass spectrometry to generate an almost complete reference map (97% of the genome-predicted proteins) of the Saccharomyces cerevisiae proteome. We generated two versions of this mass-spectrometric map, one supporting discovery-driven (shotgun) and the other supporting hypothesis-driven (targeted) proteomic measurements. Together, the two versions of the map constitute a complete set of proteomic assays to support most studies performed with contemporary proteomic technologies. To show the utility of the maps, we applied them to a protein quantitative trait locus (QTL) analysis, which requires precise measurement of the same set of peptides over a large number of samples. Protein measurements over 78 S. cerevisiae strains revealed a complex relationship between independent genetic loci, influencing the levels of related proteins. Our results suggest that selective pressure favours the acquisition of sets of polymorphisms that adapt protein levels but also maintain the stoichiometry of functionally related pathway members.

Host cell entry of vaccinia virus, the prototypic poxvirus, involves a membrane fusion event delivering the viral core and two proteinaceous lateral bodies (LBs) into the cytosol. Uncoating of viral cores is poorly characterized, and the composition and function of LBs remains enigmatic. We found that cytosolic cores rapidly dissociated from LBs and expanded in volume, which coincided with reduction of disulfide-bonded core proteins. We identified the abundant phosphoprotein F17, the dual-specificity phosphatase VH1, and the oxidoreductase G4 as bona fide LB components. After reaching the cytosol, F17 was degraded in a proteasome-dependent manner. Proteasome activity, and presumably LB disassembly, was required for the immediate immunomodulatory activity of VH1: dephosphorylation of STAT1 to prevent interferon-γ-mediated antiviral responses. These results reveal a mechanism used by poxviruses to deliver viral enzymes to the host cell cytosol and are likely to facilitate the identification of additional LB-resident viral effectors. ISSN:2666-3864 ISSN:2211-1247

A better description of the leukemia cell surface proteome (surfaceome) is a prerequisite for the development of diagnostic and therapeutic tools. Insights into the complexity of the surfaceome have been limited by the lack of suitable methodologies. We combined a leukemia xenograft model with the discovery-driven chemoproteomic Cell Surface Capture technology to explore the B-cell precursor acute lymphoblastic leukemia (BCP-ALL) surfaceome; 713 cell surface proteins, including 181 CD proteins, were detected through combined analysis of 19 BCP-ALL cases. Diagnostic immunophenotypes were recapitulated in each case, and subtype specific markers were detected. To identify new leukemia-associated markers, we filtered the surfaceome data set against gene expression information from sorted, normal hematopoietic cells. Nine candidate markers (CD18, CD63, CD31, CD97, CD102, CD157, CD217, CD305, and CD317) were validated by flow cytometry in patient samples at diagnosis and during chemotherapy. CD97, CD157, CD63, and CD305 accounted for the most informative differences between normal and malignant cells. The ALL surfaceome constitutes a valuable resource to assist the functional exploration of surface markers in normal and malignant lymphopoiesis. This unbiased approach will also contribute to the development of strategies that rely on complex information for multidimensional flow cytometry data analysis to improve its diagnostic applications.

Glioblastoma is the most common primary brain tumor in adults with low average survival time after diagnosis. In order to improve glioblastoma treatment, new drug-accessible targets need to be identified. Cell surface glycoproteins are prime drug targets due to their accessibility at the surface of cancer cells. To overcome the limited availability of suitable antibodies for cell surface protein detection, we performed a comprehensive mass spectrometric investigation of the glioblastoma surfaceome. Our combined cell surface capturing analysis of primary ex vivo glioblastoma cell lines in combination with established glioblastoma cell lines revealed 633 N-glycoproteins, which vastly extends the known data of surfaceome drug targets at subcellular resolution. We provide direct evidence of common glioblastoma cell surface glycoproteins and an approximate estimate of their abundances, information that could not be derived from genomic and/or transcriptomic glioblastoma studies. Apart from our pharmaceutically valuable repertoire of already and potentially drug-accessible cell surface glycoproteins, we built a mass-spectrometry-based toolbox enabling directed, sensitive, and repetitive glycoprotein measurements for clinical follow-up studies. The included Skyline Glioblastoma SRM assay library provides an elevated starting point for parallel testing of the abundance level of the detected glioblastoma surfaceome members in future drug perturbation experiments.

Many cellular responses are triggered by proteins, drugs or pathogens binding to cell-surface receptors, but it can be challenging to identify which receptors are bound by a given ligand. Here we describe TRICEPS, a chemoproteomic reagent with three moieties--one that binds ligands containing an amino group, a second that binds glycosylated receptors on living cells and a biotin tag for purifying the receptor peptides for identification by quantitative mass spectrometry. We validated this ligand-based, receptor-capture (LRC) technology using insulin, transferrin, apelin, epidermal growth factor, the therapeutic antibody trastuzumab and two DARPins targeting ErbB2. In some cases, we could also determine the approximate ligand-binding sites on the receptors. Using TRICEPS to label intact mature vaccinia viruses, we identified the cell surface proteins AXL, M6PR, DAG1, CSPG4 and CDH13 as binding factors on human cells. This technology enables the identification of receptors for many types of ligands under near-physiological conditions and without the need for genetic manipulations.

The development of plasma biomarkers has proven to be more challenging than initially anticipated. Many studies have reported lists of candidate proteins rather than validated candidate markers with an assigned performance to a specific clinical objective. Biomarker research necessitates a clear rational framework with requirements on a multitude of levels. On the technological front, the platform needs to be effective to detect low abundant plasma proteins and be able to measure them in a high throughput manner over a large amount of samples reproducibly. At a conceptual level, the choice of the technological platform and available samples should be part of an overall clinical study design that depends on a joint effort between basic and clinical research. Solutions to these needs are likely to facilitate more feasible studies. Targeted proteomic workflows based on SRM mass spectrometry show the potential of fast verification of biomarker candidates in plasma and thereby closing the gap between discovery and validation in the biomarker development pipeline. Biological samples need to be carefully chosen based on well-established guidelines either for candidate discovery in the form of disease models with optimal fidelity to human disease or for candidate evaluation as well-designed and annotated clinical cohort groups. Most importantly, they should be representative of the target population and directly address the investigated clinical question. A conceptual structure of a biomarker study can be provided in the form of several sequential phases, each having clear objectives and predefined goals. Furthermore, guidelines for reporting the outcome of biomarker studies are critical to adequately assess the quality of the research, interpretation and generalization of the results. By being attentive to and applying these considerations, biomarker research should become more efficient and lead to directly translatable biomarker candidates into clinical evaluation.

Nogo-A has been extensively studied as a myelin-associated neurite outgrowth inhibitor in the lesioned adult central nervous system. However, its role in the intact central nervous system has not yet been clarified. Analysis of the intact adult nervous system of C57BL/6 Nogo-A knock-out (KO) versus wild-type (WT) mice by a combined two-dimensional gel electrophoresis and isotope-coded affinity tagging approach revealed regulation of cytoskeleton-, transport-, and signaling growth-related proteins, pointing to regulation of the actin cytoskeleton, the neuronal growth machinery, and in particular the Rho-GTPase/LIMK1/cofilin pathway. Nogo-A KO adult neurons showed enlarged, more motile growth cones compared with WT neurons. The phenotype was reproduced by acute in vitro neutralization of neuronal Nogo-A. LIMK1 phosphorylation was increased in Nogo-A KO growth cones, and its reduction caused the decrease of KO growth cone motility to WT levels. Our study suggests that in the unlesioned adult nervous system, neuronal Nogo-A can restrict neuronal growth through negative modulation of growth cone motility.

There has been considerable recent interest in proteomic analyses of plasma for the purpose of discovering biomarkers. Profiling N-linked glycopeptides is a particularly promising method because the population of N-linked glycosites represents the proteomes of plasma, the cell surface, and secreted proteins at very low redundancy and provides a compelling link between the tissue and plasma proteomes. Here, we describe UniPep http://www.unipep.org - a database of human N-linked glycosites - as a resource for biomarker discovery.

A crucial aim upon the completion of the human genome is the verification and functional annotation of all predicted genes and their protein products. Here we describe the mapping of peptides derived from accurate interpretations of protein tandem mass spectrometry (MS) data to eukaryotic genomes and the generation of an expandable resource for integration of data from many diverse proteomics experiments. Furthermore, we demonstrate that peptide identifications obtained from high-throughput proteomics can be integrated on a large scale with the human genome. This resource could serve as an expandable repository for MS-derived proteome information.