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Leveraging biased signaling of G protein-coupled receptors has been proposed as a promising strategy for the development of drugs with higher specificity. However, the consequences of selectively targeting G protein- or β-arrestin-mediated signaling on cellular functions are not comprehensively understood. In this study, we utilized phosphoproteomics to gain a systematic overview of signaling induced by the four biased and balanced dopamine D2 receptor (D

The tumor microenvironment has recently emerged as a critical component of high-grade serous ovarian cancer (HGSC) disease progression. Specifically, cancer-associated fibroblasts (CAFs) have been recognized as key players in various pro-oncogenic processes. Here, we use mass-spectrometry (MS) to characterize the proteomes of HGSC patient-derived CAFs and compare them to those of the epithelial component of HGSC to gain a deeper understanding into their tumor-promoting phenotype. We integrate our data with primary tissue data to define a proteomic signature of HGSC CAFs and uncover multiple novel CAF proteins that are prognostic in an independent HGSC patient cohort. Our data represent the first MS-based global proteomic characterization of CAFs in HGSC and further highlights the clinical significance of HGSC CAFs.

Driven by the lack of targeted therapies, triple-negative breast cancers (TNBCs) have the worst overall survival of all breast cancer subtypes. Considering that cell surface proteins are favorable drug targets and are predominantly glycosylated, glycoproteome profiling has significant potential to facilitate the identification of much-needed drug targets for TNBCs. Here, we performed

Axons are complex subcellular compartments that are extremely long in relation to cell bodies, especially in peripheral nerves. Many processes are required and regulated during axon injury, including anterograde and retrograde transport, glia-to-axon macromolecular transfer, and local axonal protein synthesis. Many in vitro omics approaches have been used to gain insight into these processes, but few have been applied in vivo. Here we adapted the osmotic ex vivo axoplasm isolation method and analyzed the adult rat sciatic-nerve-extruded axoplasm by label-free quantitative proteomics before and after injury. 2087 proteins groups were detected in the axoplasm, revealing translation machinery and microtubule-associated proteins as the most overrepresented biological processes. Ribosomal proteins (73) were detected in the uninjured axoplasm and increased their levels after injury but not within whole sciatic nerves. Meta-analysis showed that detected ribosomal proteins were present in in vitro axonal proteomes. Because local protein synthesis is important for protein localization, we were interested in detecting the most abundant newly synthesized axonal proteins in vivo. With an MS/MS-BONCAT approach, we detected 42 newly synthesized protein groups. Overall, our work indicates that proteomics profiling is useful for local axonal interrogation and suggests that ribosomal proteins may play an important role, especially during injury.

Cells exhibit a broad spectrum of functions driven by differences in molecular phenotype. Understanding the heterogeneity between and within cell types has led to advances in our ability to diagnose and manipulate biological systems. Heterogeneity within and between tumors still poses a challenge to the development and efficacy of therapeutics. In this Perspective we review the toolkit of protein-level experimental approaches for investigating cellular heterogeneity. We describe how innovative approaches and technical developments have supported the advent of bottom-up single-cell proteomic analysis and present opportunities and challenges within cancer research. Finally, we introduce the concept of "precision proteomics" and discuss how the advantages and limitations of various experimental approaches render them suitable for different biological systems and questions.

Bidirectional communication between cells and their microenvironment is crucial for both normal tissue homeostasis and tumor growth. During the development of oral tongue squamous cell carcinoma (OTSCC), cancer-associated fibroblasts (CAFs) create a supporting niche by maintaining a bidirectional crosstalk with cancer cells, mediated by classically secreted factors and various nanometer-sized vesicles, termed as extracellular vesicles (EVs). To better understand the role of CAFs within the tumor stroma and elucidate the mechanism by which secreted proteins contribute to OTSCC progression, we isolated and characterized patient-derived CAFs from resected tumors with matched adjacent tissue fibroblasts (AFs). Our strategy employed shotgun proteomics to comprehensively characterize the proteomes of these matched fibroblast populations. Our goals were to identify CAF-secreted factors (EVs and soluble) that can functionally modulate OTSCC cells in vitro and to identify novel CAF-associated biomarkers. Comprehensive proteomic analysis identified 4247 proteins, the most detailed description of a pro-tumorigenic stroma to date. We demonstrated functional effects of CAF secretomes (EVs and conditioned media) on OTSCC cell growth and migration. Comparative proteomics identified novel proteins associated with a CAF-like state. Specifically, MFAP5, a protein component of extracellular microfibrils, was enriched in CAF secretomes. Using in vitro assays, we demonstrated that MFAP5 activated OTSCC cell growth and migration via activation of MAPK and AKT pathways. Using a tissue microarray of richly annotated primary human OTSCCs, we demonstrated an association of MFAP5 expression with patient survival. In summary, our proteomics data of patient-derived stromal fibroblasts provide a useful resource for future mechanistic and biomarker studies.

Cancer is the second most common cause of death worldwide and its heterogeneity complicates therapy. Standard cytotoxic regiments disrupt rapidly dividing cells, regardless of their neoplastic status. The introduction of less toxic targeted therapies has partially contributed to the observed decrease in cancer-related mortality. Cell-surface proteins represent attractive targets for therapy, due to their easily-accessible localization and their involvement in essential signaling pathways, often dysregulated in cancer. Despite their clinical appeal, cell-surface proteins are often underrepresented in standard proteomic data sets, due to their poor solubility and lower expression levels compared to intracellular proteins. Areas covered: This review will summarize some of the available techniques for enriching the cell-surface proteome, and discuss their advantages, limitations and applicability to clinical sample-testing. Moreover, we discuss currently available strategies for the development of novel targeted therapies in cancer. Expert commentary: The interest in elucidating the cancer-associated surfaceome is growing and will likely benefit from recent advancements in instrument sensitivity, method development, and a growing body of high-quality proteomics databases. Multiomics studies, in combination with functional validations (e.g. dropout screens), and evaluation of the healthy surfaceome, will likely aid in the selection of relevant targets for future therapy development.

The contribution of basal and luminal cells to cancer progression and metastasis is poorly understood. We report generation of reporter systems driven by either keratin-14 (K14) or keratin-8 (K8) promoter that not only express a fluorescent protein but also an inducible suicide gene. Transgenic mice express the reporter genes in the right cell compartments of mammary gland epithelia and respond to treatment with toxins. In addition, we engineered the reporters into 4T1 metastatic mouse tumor cell line and demonstrate that K14+ cells, but not K14− or K8+, are both highly invasive in three-dimensional (3D) culture and metastatic in vivo. Treatment of cells in culture, or tumors in mice, with reporter-targeting toxin inhibited both invasive behavior and metastasis in vivo. RNA sequencing (RNA-seq), secretome, and epigenome analysis of K14+ and K14− cells led to the identification of amphoterin-induced protein 2 (Amigo2) as a new cell invasion driver whose expression correlated with decreased relapse-free survival in patients with TP53 wild-type (WT) breast cancer., Author summary Most, if not all, cancer-related deaths result from metastasis. The differentiation states of the cancer epithelial cells are thought to be a critical determinant of metastasis. Epithelial cancer cells with a basal cell type are more aggressive in forming metastasis than cancer cells with luminal cell type. Very little is known about how the differentiation states impact metastasis or the molecular mechanisms involved. In this study, we develop and characterize new reporters that fluorescently mark cells in luminal or basal status. These reporters are also coupled to “suicide genes,” which can be used to inducibly and selectively eliminate cells expressing the reporters. We find that elimination of the basal cell type dramatically decreases metastasis and identify amphoterin-induced protein 2 (Amigo2) as a new regulator of cell invasion in basal cells.

Venn diagrams are graphical representations of the relationships among multiple sets of objects and are often used to illustrate similarities and differences among genomic and proteomic datasets. All currently existing tools for producing Venn diagrams evince one of two traits; they require expertise in specific statistical software packages (such as R), or lack the flexibility required to produce publication-quality figures. We describe a simple tool that addresses both shortcomings, Venn Diagram Interactive Software (VennDIS), a JavaFX-based solution for producing highly customizable, publication-quality Venn, and Euler diagrams of up to five sets. The strengths of VennDIS are its simple graphical user interface and its large array of customization options, including the ability to modify attributes such as font, style and position of the labels, background color, size of the circle/ellipse, and outline color. It is platform independent and provides real-time visualization of figure modifications. The created figures can be saved as XML files for future modification or exported as high-resolution images for direct use in publications.

The histamine receptors (HRs) represent a subclass of G protein-coupled receptors (GPCRs) and comprise four subtypes. Due to their numerous physiological and pathological effects, HRs are popular drug targets for the treatment of allergic reactions or the regulation of gastric acid secretion. Hence, an understanding of the functional selectivity of HR ligands has gained importance. These ligands can bind to specific GPCRs and selectively activate defined pathways. Supporting the activation of a therapeutically necessary pathway without the activation of other signaling cascades can result in drugs with more specific activity and fewer side effects. To evaluate the cellular consequences resulting from receptor binding, comprehensive analyses of cellular protein alterations upon incubation with ligands are required. For this purpose, endothelial cells were treated with histamine, as the endogenous ligand of HRs, to obtain a global overview of its cellular effects. Quantitative proteomics and pathway analyses of histamine-treated and untreated cells revealed enrichment of the nuclear factor-κB and tumor necrosis factor signaling pathways, cytokine‒cytokine receptor interactions, complement and coagulation cascades and acute inflammatory processes upon histamine treatment. This strategy offers the opportunity to monitor HR-mediated signaling in a multidimensional manner. This article is protected by copyright. All rights reserved

Cells secrete biomolecules into the extracellular space as a way of intercellular communication. Secreted proteins can act as ligands that engage specific receptors-on the same cell, nearby cells, or distant cells-and induce defined signaling pathways. Proteins and other biomolecules can also be packaged as cargo molecules within vesicles that are released to the extracellular space (termed extracellular vesicles or EVs). A subclass of such EVs, exosomes have been shown to horizontally transfer information. In recent years, exosomes have sparked tremendous interest in biological research, both for the discovery of novel biomarkers and for the identification of signaling molecules, as part of their cargo. Although multiple methods have been described for the isolation of exosomes, described here is a simple differential centrifugation approach that is well suited for the isolation of exosomes from conditioned cell culture media and urine. Mass spectrometry provides an ideal method to comprehensively analyze the protein cargo of exosomes. © 2017 by John Wiley & Sons, Inc.

In this study we carried out a mass spectrometry-based proteome analysis of human fetal atria and ventricles. Heart protein lysates were analyzed on the Q-Exactive mass spectrometer in biological triplicates. Protein identification using MaxQuant yielded a total of 2754 atrial protein groups (91%) and 2825 ventricular protein groups (83%) in at least 2 of the 3 runs with ≥ 2 unique peptides. Statistical analyses using fold-enrichment (>2) and p-values (≤ 0.05) selected chamber-enriched atrial (134) and ventricular (81) protein groups. Several previously characterized cardiac chamber-enriched proteins were identified in this study including atrial isoform of myosin light chain 2 (MYL7), atrial natriuretic peptide (NPPA), connexin 40 (GJA5), and peptidylglycine alpha-amidating monooxygenase (PAM) for atria, and ventricular isoforms of myosin light chains (MYL2 and MYL3), myosin heavy chain 7 (MYH7), and connexin 43 (GJA1) for ventricle. Our data was compared to in-house generated and publicly available human microarrays, several human cardiac proteomes, and phenotype ontology databases.

The complexities of tumor genomes are rapidly being uncovered, but how they are regulated into functional proteomes remains poorly understood. Standard proteomics workflows use databases of known proteins, but these databases do not capture the uniqueness of the cancer transcriptome, with its point mutations, unusual splice variants and gene fusions. Onco-proteogenomics integrates mass spectrometry-generated data with genomic information to identify tumor-specific peptides. Linking tumor-derived DNA, RNA and protein measurements into a central-dogma perspective has the potential to improve our understanding of cancer biology.

Molecular communication between cancer cells and its stromal microenvironment is a key factor for cancer progression. Alongside classic secretory pathways, it has recently been proposed that small membranous vesicles are alternative mediators of intercellular communication. Exosomes carry an effector-rich proteome with the ability to modulate various functional properties of the recipient cell. In this study, exosomes isolated from four epithelial ovarian cancer cell lines (OVCAR3, OVCAR433, OVCAR5 and SKOV3) were characterized using mass spectrometry-based proteomics. Using an optimized workflow consisting of efficient exosome solubilization and the latest generation of proteomic instrumentation, we demonstrate improved detection depth. Systematic comparison of our cancer cell line exosome proteome against public data (Exocarta) and the recently published NCI 60 proteome revealed enrichment of functional categories related to signaling biology and biomarker discovery.

Exosomes and microvesicles (MVs) are nanometer-sized, membranous vesicles secreted from many cell types into their surrounding extracellular space and into body fluids. These two classes of extracellular vesicles are regarded as a novel mechanism through which cancer cells, including virally infected cancer cells, regulate their micro-environment via the horizontal transfer of bioactive molecules: proteins, lipids, and nucleic acids (DNA, mRNA, micro-RNAs; oncogenic cargo hence often referred to as oncosomes). In head and neck cancer (HNC), exosomes and MVs have been described in Epstein Barr Virus (EBV)-associated nasopharyngeal cancer (NPC), as well as being positively correlated with oral squamous cell carcinoma (OSCC) progression. It has therefore been suggested that HNC-derived vesicles could represent a useful source for biomarker discovery, enriched in tumor antigens and cargo; hence fundamentally important for cancer progression. This current review offers an overall perspective on the roles of exosomes and MVs in HNC biology, focusing on EBV-associated NPC and OSCC. We also highlight the importance of saliva as a proximal and easily accessible bio-fluid for HNC detection, and propose that salivary vesicles might serve as an alternative model in the discovery of novel HNC biomarkers.

Expressed prostatic secretions (EPS) are proximal fluids of the prostate that are increasingly being utilized as a clinical source for diagnostic and prognostic assays for prostate cancer (PCa). These fluids contain an abundant amount of microvesicles reflecting the secretory function of the prostate gland, and their protein composition remains poorly defined in relation to PCa. Using expressed prostatic secretions in urine (EPS-urine), exosome preparations were characterized by a shotgun proteomics procedure. In pooled EPS-urine exosome samples, ~900 proteins were detected. Many of these have not been previously observed in the soluble proteome of EPS generated by our labs or other related exosome proteomes. We performed systematic comparisons of our data against previously published, prostate-related proteomes, and global annotation analyses to highlight functional processes within the proteome of EPS-urine derived exosomes. The acquired proteomic data have been deposited to the Tranche repository and will lay the foundation for more extensive investigations of PCa derived exosomes in the context of biomarker discovery and cancer biology.

Current protocols for the screening of prostate cancer cannot accurately discriminate clinically indolent tumors from more aggressive ones. One reliable indicator of outcome has been the determination of organ-confined versus nonorgan-confined disease but even this determination is often only made following prostatectomy. This underscores the need to explore alternate avenues to enhance outcome prediction of prostate cancer patients. Fluids that are proximal to the prostate, such as expressed prostatic secretions (EPS), are attractive sources of potential prostate cancer biomarkers as these fluids likely bathe the tumor. Direct-EPS samples from 16 individuals with extracapsular (n = 8) or organ-confined (n = 8) prostate cancer were used as a discovery cohort, and were analyzed in duplicate by a nine-step MudPIT on a LTQ-Orbitrap XL mass spectrometer. A total of 624 unique proteins were identified by at least two unique peptides with a 0.2% false discovery rate. A semiquantitative spectral counting algorithm identified 133 significantly differentially expressed proteins in the discovery cohort. Integrative data mining prioritized 14 candidates, including two known prostate cancer biomarkers: prostate-specific antigen and prostatic acid phosphatase, which were significantly elevated in the direct-EPS from the organ-confined cancer group. These and five other candidates (SFN, MME, PARK7, TIMP1, and TGM4) were verified by Western blotting in an independent set of direct-EPS from patients with biochemically recurrent disease (n = 5) versus patients with no evidence of recurrence upon follow-up (n = 10). Lastly, we performed proof-of-concept SRM-MS-based relative quantification of the five candidates using unpurified heavy isotope-labeled synthetic peptides spiked into pools of EPS-urines from men with extracapsular and organ-confined prostate tumors. This study represents the first efforts to define the direct-EPS proteome from two major subclasses of prostate cancer using shotgun proteomics and verification in EPS-urine by SRM-MS.

In recent years there has been tremendous interest in both the basic biology and applications of extracellular vesicles (EVs) in translational cancer research. This includes a better understanding of their biogenesis and mechanisms of selective cargo packaging, their precise roles in horizontal communication, and their application as non-invasive biomarkers. The rapid advances in next-generation omics technologies are the driving forces for these discoveries. In this review, the authors focus on recent results of EV research in ovarian cancer. A deeper understanding of ovarian cancer-derived EVs, the types of cargo molecules and their biological roles in cancer growth, metastases and drug resistance, could have significant impact on the discovery of novel biomarkers and innovative therapeutics. Insights into the role of EVs in immune regulation could lead to novel approaches built on EV-based immunotherapy.

Renal cell carcinoma comprises 2 to 3% of malignancies in adults with the most prevalent subtype being clear-cell RCC (ccRCC). This type of cancer is well characterized at the genomic and transcriptomic level and is associated with a loss of VHL that results in stabilization of HIF1. The current study focused on evaluating ccRCC stage dependent changes at the proteome level to provide insight into the molecular pathogenesis of ccRCC progression. To accomplish this, label-free proteomics was used to characterize matched tumor and normal-adjacent tissues from 84 patients with stage I to IV ccRCC. Using pooled samples 1551 proteins were identified, of which 290 were differentially abundant, while 783 proteins were identified using individual samples, with 344 being differentially abundant. These 344 differentially abundant proteins were enriched in metabolic pathways and further examination revealed metabolic dysfunction consistent with the Warburg effect. Additionally, the protein data indicated activation of ESRRA and ESRRG, and HIF1A, as well as inhibition of FOXA1, MAPK1 and WISP2. A subset analysis of complementary gene expression array data on 47 pairs of these same tissues indicated similar upstream changes, such as increased HIF1A activation with stage, though ESRRA and ESRRG activation and FOXA1 inhibition were not predicted from the transcriptomic data. The activation of ESRRA and ESRRG implied that HIF2A may also be activated during later stages of ccRCC, which was confirmed in the transcriptional analysis. This combined analysis highlights the importance of HIF1A and HIF2A in developing the ccRCC molecular phenotype as well as the potential involvement of ESRRA and ESRRG in driving these changes. In addition, cofilin-1, profilin-1, nicotinamide N-methyltransferase, and fructose-bisphosphate aldolase A were identified as candidate markers of late stage ccRCC. Utilization of data collected from heterogeneous biological domains strengthened the findings from each domain, demonstrating the complementary nature of such an analysis. Together these results highlight the importance of the VHL/HIF1A/HIF2A axis and provide a foundation and therapeutic targets for future studies. (Data are available via ProteomeXchange with identifier PXD003271 and MassIVE with identifier MSV000079511.).

The ryanodine receptor (RyR) is a large, homotetrameric sarcoplasmic reticulum membrane protein that is essential for Ca(2+) cycling in both skeletal and cardiac muscle. Genetic mutations in RyR1 are associated with severe conditions including malignant hyperthermia (MH) and central core disease. One phosphorylation site (Ser 2843) has been identified in a segment of RyR1 flanked by two RyR motifs, which are found exclusively in all RyR isoforms as closely associated tandem (or paired) motifs, and are named after the protein itself. These motifs also contain six known MH mutations. In this study, we designed, expressed and purified the tandem RyR motifs, and show that this domain contains a putative binding site for the Ca(2+)/calmodulin-dependent protein kinase β isoform. We present a 2.2 Å resolution crystal structure of the RyR domain revealing a two-fold, symmetric, extended four-helix bundle stabilized by a β sheet. Using mathematical modelling, we fit our crystal structure within a tetrameric electron microscopy (EM) structure of native RyR1, and propose that this domain is localized in the RyR clamp region, which is absent in its cousin protein inositol 1,4,5-trisphosphate receptor.

Urinary expressed prostatic secretion or "EPS-urine" is proximal tissue fluid that is collected after a digital rectal exam (DRE). EPS-urine is a rich source of prostate-derived proteins that can be used for biomarker discovery for prostate cancer (PCa) and other prostatic diseases. We previously conducted a comprehensive proteome analysis of direct expressed prostatic secretions (EPS). In the current study, we defined the proteome of EPS-urine employing Multidimensional Protein Identification Technology (MudPIT) and providing a comprehensive catalogue of this body fluid for future biomarker studies. We identified 1022 unique proteins in a heterogeneous cohort of 11 EPS-urines derived from biopsy negative noncancer diagnoses with some benign prostatic diseases (BPH) and low-grade PCa, representative of secreted prostate and immune system-derived proteins in a urine background. We further applied MudPIT-based proteomics to generate and compare the differential proteome from a subset of pooled urines (pre-DRE) and EPS-urines (post-DRE) from noncancer and PCa patients. The direct proteomic comparison of these highly controlled patient sample pools enabled us to define a list of prostate-enriched proteins detectable in EPS-urine and distinguishable from a complex urine protein background. A combinatorial analysis of both proteomics data sets and systematic integration with publicly available proteomics data of related body fluids, human tissue transcriptomic data, and immunohistochemistry images from the Human Protein Atlas database allowed us to demarcate a robust panel of 49 prostate-derived proteins in EPS-urine. Finally, we validated the expression of seven of these proteins using Western blotting, supporting the likelihood that they originate from the prostate. The definition of these prostatic proteins in EPS-urine samples provides a reference for future investigations for prostatic-disease biomarker studies.

DJ-1 is a small but relatively abundant protein of unknown function that may undergo stress-dependent cellular translocation and has been implicated in both neurodegenerative diseases and cancer. As such, DJ-1 may be an excellent study object to elucidate the relative influence of the cellular context on its interactome and for exploring whether acute exposure to oxidative stressors alters its molecular environment. Using quantitative mass spectrometry, we conducted comparative DJ-1 interactome analyses from in vivo cross-linked brains or livers and from hydrogen peroxide-treated or naïve embryonic stem cells. The analysis identified a subset of glycolytic enzymes, heat shock proteins 70 and 90, and peroxiredoxins as interactors of DJ-1. Consistent with a role of DJ-1 in Hsp90 chaperone biology, we document destabilization of Hsp90 clients in DJ-1 knockout cells. We further demonstrate the existence of a C106 sulfinic acid modification within DJ-1 and thereby establish that this previously inferred modification also exists in vivo. Our data suggest that caution has to be exerted in interpreting interactome data obtained from a single biological source material and identify a role of DJ-1 as an oxidative stress sensor and partner of a molecular machinery notorious for its involvement in cell fate decisions.

Epithelial ovarian cancer (EOC) is the most common gynecological cancer and the ninth most common cancer overall. Major problems associated with EOC include poorly characterized disease progression, disease heterogeneity, lack of early detection markers and the development of chemoresistance. Early detection and treatment of EOC would significantly benefit from routine screening tests on available biofluids. We built on our experience in analyzing ovarian cancer ascites and present an analysis pipeline that combines discovery-based proteomics, bioinformatics prioritization and targeted proteomics quantification using Selected Reaction Monitoring Mass Spectrometry (SRM-MS). Ascitic fluids from patients with serous-type epithelial ovarian cancer were analyzed using comprehensive shotgun proteomics and compared to noncancerous ascitic fluids from patients with benign ovarian tumors. Integration of our data with published mRNA transcriptomic and proteomic data sets led to a panel of 51 candidate proteins. Systematic SRM-MS assay development was performed for a subset of these proteins using both synthetic peptides (13 proteins) and stable isotope labeled standards (4 proteins). Subsequently, precise relative quantification by stable isotope dilution-SRM (SID-SRM) in independent ascites and serum samples was performed as a proof-of-concept validation. The analysis strategy outlined here lays the foundation for future experiments using both larger numbers of patient samples and additional candidate proteins, and provides a template for the proteomics-based discovery of cancer biomarkers.

Nonsmall cell lung carcinoma (NSCLC) accounts for 80% of lung cancers. The most prevalent subtypes of NSCLC are adenocarcinoma (ADC) and squamous cell carcinoma (SCC), which combined account for approximately 90%. Ten resected NSCLC patient tumors (5 ADC and 5 SCC) were directly introduced into severely immune deficient (NOD-SCID) mice, and the resulting xenograft tumors were analyzed by standard histology and immunohistochemistry (IHC) and by proteomics profiling. Mass spectrometry (MS) methods involving 1- and 2-dimensional LC-MS/MS, and multiplexed selective reaction monitoring (SRM, or MRM), were applied to identify and quantify the xenograft proteomes. Hierarchical clustering of protein profiles distinguished between the ADC and SCC subtypes. The differential expression of 178 proteins, including a comprehensive panel of intermediate filament keratin proteins, was found to constitute a distinctive proteomic signature associated with the NSCLC subtypes. Epidermal growth factor receptor (EGFR) was expressed in ADC and SCC xenografts, and EGFR network activation was assessed by phosphotyrosine profiling by Western blot analysis and SRM measurement of EGFR levels, and mutation analysis. A multiplexed SRM/MRM method provided relative quantification of several keratin proteins, EGFR and plakophilin-1 in single LC-MS/MS runs. The protein quantifications by SRM and MS/MS spectral counting were associated with superior dynamic range and reproducibility but were otherwise consistent with orthogonal methods including IHC and Western immuno blotting. These findings illustrate the potential to develop a comprehensive MS-based platform in oncologic pathology for better classification and potentially treatment of NSCLC patients.

It is expected that clinically obtainable fluids that are proximal to organs contain a repertoire of secreted proteins and shed cells reflective of the physiological state of that tissue and thus represent potential sources for biomarker discovery, investigation of tissue-specific biology, and assay development. The prostate gland secretes many proteins into a prostatic fluid that combines with seminal vesicle fluids to promote sperm activation and function. Proximal fluids of the prostate that can be collected clinically are seminal plasma and expressed prostatic secretion (EPS) fluids. In the current study, MudPIT-based proteomics was applied to EPS obtained from nine men with prostate cancer and resulted in the confident identification of 916 unique proteins. Systematic bioinformatics analyses using publicly available microarray data of 21 human tissues (Human Gene Atlas), the Human Protein Atlas database, and other published proteomics data of shed/secreted proteins were performed to systematically analyze this comprehensive proteome. Therefore, we believe this data will be a valuable resource for the research community to study prostate biology and potentially assist in the identification of novel prostate cancer biomarkers. To further streamline this process, the entire data set was deposited to the Tranche repository for use by other researchers.

Defining the cell surface proteome has profound importance for understanding cell differentiation and cell–cell interactions, as well as numerous pathogenic abnormalities. Owing to their hydrophobic nature, plasma membrane proteins that reside on the cell surface pose analytical challenges and, despite efforts to overcome difficulties, remain under-represented in proteomic studies. Limitations in the classically employed ultracentrifugation-based approaches have led to the invention of more elaborate techniques for the purification of cell surface proteins. Three of these methods – cell surface coating with cationic colloidal silica beads, biotinylation and chemical capture of surface glycoproteins – allow for marked enrichment of this subcellular proteome, with each approach offering unique advantages and characteristics for different experiments. In this article, we introduce the principles of each purification method and discuss applications from the recent literature.

The low resolution structure of a protein can sometimes be inferred from information about existing disulfide bridges or experimentally introduced chemical crosslinks. Frequently, this task involves enzymatic digestion of a protein followed by mass spectrometry-based identification of covalently linked peptides. To facilitate this task, we developed a method for the enrichment of covalently linked peptides following the chemical cleavage of a protein. The method capitalizes on the availability of homoserine lactone moieties at the C-termini of cyanogen bromide cleavage products which support selective conjugation of affinity tags. The availability of two C-termini within covalently linked peptides allows for the conjugation of two distinct affinity tags and thereby enables subsequent removal of unmodified peptides by tandem affinity chromatography. Here, we demonstrate the stepwise implementation of this method using a polyhistidine tag and a biotin tag for the selective two-step purification of covalently linked cyanogen bromide fragments from increasingly complex protein samples. The method is independent of the nature of the covalent bond, is adaptable to fully denaturing conditions, and requires only low picomole quantities of starting material.

High resolution peptide separation is pivotal for successful shot-gun proteomics. The need for capable techniques propels invention and improvement of ever more sophisticated approaches. Recently, Agilent Technologies has introduced the OFFGEL fractionator, which conducts peptide separation by isoelectric focusing in an off-gel setup. This platform has been shown to accomplish high resolution of peptides for diverse sample types, yielding valuable advantages over comparable separation techniques. In this study, we deliver the first comparison of the newly emerging OFFGEL approach to the well-established on-line MudPIT platform. Samples from a membrane-enriched fraction isolated from murine C2C12 cells were subjected to replicate analysis by OFFGEL (12 fractions, pH 3 – 10) followed by RP-LC-MS/MS or 12-step on-line MudPIT. OFFGEL analyses yielded 1398 proteins (identified by 10,269 peptides) while 1428 proteins (11,078 peptides) were detected with the MudPIT approach. Thus, our data shows that both platforms produce highly comparable results in terms of protein/peptide identifications and reproducibility for the sample type analyzed. We achieve more accurate peptide focusing after OFFGEL fractionation with 88 % of all peptides binned to a single fraction, as compared to 61 % of peptides detected in only one step in MudPIT analyses. Our study suggests that both platforms are equally capable of high quality peptide separation of a sample with medium complexity, rendering them comparably valuable for comprehensive proteomic analyses.

Recent advances in mass spectrometry and bioinformatics have provided the means to characterize complex protein landscapes from a wide variety of organisms and cell types. Development of standard proteomes exhibiting all of the proteins involved in normal physiology will facilitate the delineation of disease mechanisms. Here, we examine the wild-type cardiac proteome using data obtained from a subcellular fractionation protocol in combination with a multidimensional protein identification proteomics approach. We identified 4906 proteins which were allocated to either cytosolic, microsomal, mitochondrial matrix or mitochondrial membrane fractions with relative abundance values in each fraction. We subjected these proteins to hierarchical clustering, gene ontology terms analysis, immunoblotting, comparison to publicly available protein databases, comparison to 4 distinct cardiac transcriptomes, and finally, to 6 other related proteomic data sets. This study provides an exhaustive analysis of the cardiac proteome and is the first large-scale investigation of the subcellular location for over 2000 unannotated proteins. With the use of a subtractive transcriptomics approach, we have also extended our analysis to identify 'cardiac selective' factors in our proteome. Finally, using specific filtering criteria, we identified proteotypic peptides for subsequent use in targeted studies of both mouse and human. Therefore, we offer this as a major contribution to the advancement of the field of proteomics in cardiovascular research.

Epithelial ovarian cancer is the leading cause of cancer-related death among gynecological cancers due to the asymptomatic nature of the disease, a lack of early detection markers and the development of resistance to current chemotherapeutic agents. Currently available tests (CA-125, transvaginal ultrasound or combination of both) lack the sensitivity and specificity to be useful as an efficient screening tool for surveillance of the general population. Thus, there is an urgent need for the development and validation of new molecular markers that would be both specific and sensitive indicators of disease onset, as well as progression. Proteomic profiling has emerged as a powerful tool to study ovarian cancer in an unbiased way at the molecular level, to monitor the effects of given treatment options and for the discovery of biomarkers. In this review we discuss the challenges associated with proteomics-based biomarker discovery and some recent concepts to potentially overcome these hurdles. Recent proteomics work on ovarian cancer cells and tissues will be discussed in light of obtaining new insights into fundamental biological processes, as well as their potential integration with ongoing biomarker discovery pipelines.

Defective mobilization of Ca2+ by cardiomyocytes can lead to cardiac insufficiency, but the causative mechanisms leading to congestive heart failure (HF) remain unclear. In the present study we performed exhaustive global proteomics surveys of cardiac ventricle isolated from a mouse model of cardiomyopathy overexpressing a phospholamban mutant, R9C (PLN-R9C), and exhibiting impaired Ca2+ handling and death at 24 weeks and compared them with normal control littermates. The relative expression patterns of 6190 high confidence proteins were monitored by shotgun tandem mass spectrometry at 8, 16, and 24 weeks of disease progression. Significant differential abundance of 593 proteins was detected. These proteins mapped to select biological pathways such as endoplasmic reticulum stress response, cytoskeletal remodeling, and apoptosis and included known biomarkers of HF (e.g. brain natriuretic peptide/atrial natriuretic factor and angiotensin-converting enzyme) and other indicators of presymptomatic functional impairment. These altered proteomic profiles were concordant with cognate mRNA patterns recorded in parallel using high density mRNA microarrays, and top candidates were validated by RT-PCR and Western blotting. Mapping of our highest ranked proteins against a human diseased explant and to available data sets indicated that many of these proteins could serve as markers of disease. Indeed we showed that several of these proteins are detectable in mouse and human plasma and display differential abundance in the plasma of diseased mice and affected patients. These results offer a systems-wide perspective of the dynamic maladaptions associated with impaired Ca2+ homeostasis that perturb myocyte function and ultimately converge to cause HF.

Epithelial ovarian cancer is the most lethal gynecological malignancy, and disease-specific biomarkers are urgently needed to improve diagnosis, prognosis, and to predict and monitor treatment efficiency. We present an in-depth proteomic analysis of selected biochemical fractions of human ovarian cancer ascites, resulting in the stringent and confident identification of over 2500 proteins. Rigorous filter schemes were applied to objectively minimize the number of false-positive identifications, and we only report proteins with substantial peptide evidence. Integrated computational analysis of the ascites proteome combined with several recently published proteomic data sets of human plasma, urine, 59 ovarian cancer related microarray data sets, and protein-protein interactions from the Interologous Interaction Database I (2)D ( http://ophid.utoronto.ca/i2d) resulted in a short-list of 80 putative biomarkers. The presented proteomics analysis provides a significant resource for ovarian cancer research, and a framework for biomarker discovery.

A few well-characterized protein assemblies aside, little is known about the topology and interfaces of multiconstituent protein complexes. Here we report on a novel indirect strategy for low-resolution topology mapping of protein complexes. Following crosslinking, purified protein complexes are subjected to chemical cleavage with cyanogen bromide (CNBr) and the resulting fragments are resolved by 2-D electrophoresis. The side-by-side comparison of a thus generated and a 2-D CNBr fragment map obtained from uncrosslinked material reveals candidate gel spots harboring crosslinked CNBr fragments. In-gel trypsinization and MALDI MS analysis of these informative spots identify the underlying crosslinked CNBr fragments based on unmodified tryptic peptides. Matching the cumulative theoretical molecular mass and predicted pI of these crosslinked CNBr fragments with original gel spot coordinates is required for confident crosslink assignment. The above strategy was successfully validated with the Escherichia coli RNA polymerase (RNAP) core complex and subsequently applied to query the quaternary structure of components of the yeast Skp1-Cdc53/Cullin-F box (SCF) ubiquitin ligase complex. This protocol requires low picomole sample quantities, can be applied to multisubunit protein complexes, and does not rely on specialized data mining software.

SummaryIn response to genotoxic stress, cells evoke a plethora of physiological responses collectively aimed at enhancing viability and maintaining the integrity of the genome. Here, we report that unspliced tRNA rapidly accumulates in the nuclei of yeast Saccharomyces cerevisiae after DNA damage. This response requires an intact MEC1- and RAD53-dependent signaling pathway that impedes the nuclear export of intron-containing tRNA via differential relocalization of the karyopherin Los1 to the cytoplasm. The accumulation of unspliced tRNA in the nucleus signals the activation of Gcn4 transcription factor, which, in turn, contributes to cell-cycle arrest in G1 in part by delaying accumulation of the cyclin Cln2. The regulated nucleocytoplasmic tRNA trafficking thus constitutes an integral physiological adaptation to DNA damage. These data further illustrate how signal-mediated crosstalk between distinct functional modules, namely, tRNA nucleocytoplasmic trafficking, protein synthesis, and checkpoint execution, allows for functional coupling of tRNA biogenesis and cell-cycle progression.

An Omics Array integrating DNA gene copy number, mRNA transcriptome, and quantified proteome was assembled into a genetic map representing non-small cell lung carcinoma (NSCLC). Data was from patient-matched normal lung, primary tumors, and patient tumor-derived xenograft tumors. Dysregulated proteins not previously implicated as cancer drivers were found encoded throughout the genome including but not limited to regions of recurrent DNA amplification/deletion in NSCLC. Clustering revealed signatures comprising metabolism proteins particularly highly recapitulated between matched primary and PDX tumors. Interrogation of The Cancer Genome Atlas revealed sizeable cohorts of NSCLC patients with DNA alterations in genes encoding the metabolism proteome signatures, and accompanied by differences in survival. Serine hydroxymethyltransferase 2 (SHMT2), a key enzyme in Ser/Gly/folate/1-carbon metabolism, is upregulated in NSCLC proteomes and implicated as a driver of recurrent chromosome 12q14.1 amplification. SH...

Protein expression becomes altered in breast epithelium during malignant transformation. Knowledge of these perturbations should provide insight into the molecular basis of breast cancer, as well as reveal possible new therapeutic targets. To this end, we have performed an extensive comparative proteomic survey of global protein expression patterns in proliferating MCF-7 breast cancer cells and normal human mammary epithelial cells using gel-free shotgun tandem mass spectrometry. Pathophysiological alterations associated with the malignant breast cancer phenotype were detected, including differences in the apparent levels of key regulators of the cell cycle, signal transduction, apoptosis, transcriptional regulation, and cell metabolism. Keywords: mass spectrometry • protein expression profiling • proteomics • breast cancer • cell cycle • proliferation

Protein profiling using high-throughput tandem mass spectrometry has become a powerful method for analyzing changes in global protein expression patterns in cells and tissues as a function of developmental, physiologic and disease processes. This review summarizes the utility and practical application of multidimensional protein identification technology as a platform for comprehensive proteomic profiling of complex biologic samples. The strengths and potential problems and limitations associated with this powerful technology are discussed, with an emphasis placed on one of the biggest challenges currently facing large-scale expression profiling projects -- namely, data analysis. Complementary bioinformatic computational data mining strategies, such as clustering, functional annotation and statistical inference, are also discussed as these are increasingly necessary for interpreting the results of global proteomic profiling studies.

Matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) was used to qualitatively study the formation of early Maillard products of lysozyme, produced upon incubation with seven different sugars (D-ribose, L-rhamnose, D-glucose, D-fructose, D-galactose, D-lactose, D-maltose) in solution, in the presence of oxygen. MALDI-TOF mass spectra of intact lysozyme revealed a heterogeneous distribution of glycation products, detected by significant mass increase and peak broadening. Therefore, to get more detailed information about the nature of the glycation products, we performed MALDI-TOF MS peptide mapping analysis. In each of the peptide mapping spectra we were able to detect the early glycation products (Amadori products/glucosylamines) with high selectivity. We were able to distinguish between the Amadori products of the different sugars, due to the characteristic mass increases of the glycated peptides. Furthermore, variations of the modification pattern were observed, very likely due to the different relativities of the seven reducing sugars. Other, more advanced glycation products of the initially formed Maillard products were also detected. Further studies regarding the nature of these late Maillard products are in progress. Here we report, for the first time, the use of MALDI-TOF MS peptide mapping as a quick and highly selective method for the detection of early stage Maillard products produced upon incubation of lysozyme with seven different reducing sugars.

The discovery of new functions for platelets, particularly in inflammation and immunity, has expanded the role of these anucleate cell fragments beyond their primary hemostatic function. Here, four in-depth human platelet proteomic data sets were generated to explore potential new functions for platelets based on their protein content and this led to the identification of 2559 high confidence proteins. During a more detailed analysis, consistently high expression of the proteasome was discovered, and the composition and function of this complex, whose role in platelets has not been thoroughly investigated, was examined. Data set mining resulted in identification of nearly all members of the 26S proteasome in one or more data sets, except the β5 subunit. However, β5i, a component of the immunoproteasome, was identified. Biochemical analyses confirmed the presence of all catalytically active subunits of the standard 20S proteasome and immunoproteasome in human platelets, including β5, which was predominantly found in its precursor form. It was demonstrated that these components were assembled into the proteasome complex and that standard proteasome as well as immunoproteasome subunits were constitutively active in platelets. These findings suggest potential new roles for platelets in the immune system. For example, the immunoproteasome may be involved in major histocompatibility complex I (MHC I) peptide generation, as the MHC I machinery was also identified in our data sets.

Exosomes and other microvesicles are emerging as rich reservoirs of tumor-specific proteins and biomarkers for cancer detection and progression. For prostate cancer, exosomes secreted by the prostate can be isolated from prostatic secretions, seminal fluid, tissue, urine or blood for further proteomic analysis. Structurally, prostate-derived exosomes are distinct in size, membrane composition and specific prostate protein content, potentially providing a novel and easily isolatable source of biomarkers from clinical biofluids. The key to these isolation strategies will be the targeting of specific prostatic proteins expressed in these exosomes, thus requiring detailed proteomic characterizations. A summary of ongoing efforts to characterize the proteome of these unique prostate cancer-associated exosomes and their potential applications for use in biomarker assays is presented.

N e-Carboxymethyllysine (CML) is an important Maillard product which is formed in vivo and during food processing and heating, and which can therefore be used as a marker for heat damage of foodstuffs. A competitive enzyme-linked immunosorbent assay (ELISA) was developed to detect CML modifications on proteins. CML protein was synthesized and anti-CML antiserum was prepared, which recognized CML modifications specifically on CML proteins and proteins which were incubated with various carbohydrates. Heated milk and milk powder samples could be directly tested by ELISA without further clean-up procedures and the CML contents were determined in relation to reaction time and heating conditions. Positive results were confirmed by SDS-PAGE/immunoblotting using the same antiserum. ELISA proved to be a fast, specific, and easy-to-handle method to evaluate CML formation in heated milk products. Additionally, SDS-PAGE/immunoblotting can be helpful to detect CML also in insoluble food proteins.

Nonsmall cell lung cancer (NSCLC) accounts for 85% of lung cancers, and is subdivided into two major histological subtypes: adenocarcinoma (ADC) and squamous cell carcinoma (SCC). There is an unmet need to further subdivide NSCLC according to distinctive molecular features that may be associated with responsiveness to therapies. Four primary tumor-derived xenograft proteomes (two-each ADC and SCC) were quantitatively compared by using a super-SILAC labeling approach together with ultrahigh-resolution MS. Proteins highly differentially expressed in the two subtypes were identified, including 30 that were validated in an independent cohort of 12 NSCLC primary tumor-derived xenograft tumors whose proteomes were quantified by an alternative, label-free shotgun MS methodology. The 30-protein signature contains metabolism enzymes including phosphoglycerate dehydrogenase, which is more highly expressed in SCC, as well as a comprehensive set of cytokeratins and other components of the epithelial barrier, which is therefore distinctly different between ADC and SCC. These results demonstrate the utility of the super-SILAC method for the characterization of primary tissues, and compatibility with datasets derived from different MS-based platforms. The validation of proteome signatures of NSCLC subtypes supports the further development and application of MS-based quantitative proteomics as a basis for precision classifications and treatments of tumors. All MS data have been deposited in the ProteomeXchange with identifier PXD000438 (http://proteomecentral.proteomexchange.org/dataset/PXD000438).

The serine threonine kinase checkpoint kinase 2 (CHK2) is a DNA damage checkpoint protein important for the ATM-p53 signaling pathway. In addition to its phosphorylation, CHK2 is also ubiquitylated, and both post-translational modifications are important for its function. However, although the mechanisms that regulate CHK2 phosphorylation are well established, those that control its ubiquitylation are not fully understood. In this study, we demonstrate that the ubiquitin E3 ligase PIRH2 (p53-induced protein with a RING (Really Interesting New Gene)-H2 domain) interacts with CHK2 and mediates its polyubiquitylation and proteasomal degradation. We show that the deubiquitylating enzyme USP28 forms a complex with PIRH2 and CHK2 and antagonizes PIRH2-mediated polyubiquitylation and proteasomal degradation of CHK2. We also provide evidence that CHK2 ubiquitylation by PIRH2 is dependent on its phosphorylation status. Cells deficient in Pirh2 displayed accumulation of Chk2 and enhanced hyperactivation of G1/S and G2/M cell-cycle checkpoints. This hyperactivation was, however, no longer observed in Pirh2−/−Chk2−/− cells, providing evidence for the importance of Chk2 regulation by Pirh2. These findings indicate that PIRH2 has central roles in the ubiquitylation of Chk2 and its turnover and in the regulation of its function.

Head and neck squamous cell carcinomas (HNSCC) can arise from the oral cavity, oropharynx, larynx or hypopharynx, and is the sixth leading cancer by incidence worldwide. The 5-year survival rate of HNSCC patients remains static at 40–60%. Hence, biomarkers which can improve detection of HNSCC or early recurrences should improve clinical outcome. Mass spectrometry-based proteomics methods have emerged as promising approaches for biomarker discovery. As one approach, mass-spectrometric identification of proteins shed or secreted from cancer cells can contribute to the identification of potential biomarkers for HNSCC and our understanding of tumor behavior. In the current study, mass spectrometry-based proteomic profiling was performed on the conditioned media (i.e. secretome) of head and neck cancer (HNC) cell lines (FaDu, UTSCC8 and UTSCC42a) in addition to gene expression microarrays to identify over-expressed transcripts in the HNSCC cells in comparison to a normal control cell line. This integrated data set was systematically mined using publicly available resources (Human Protein Atlas and published proteomic/transcriptomic data) to prioritize putative candidates for validation. Subsequently, quantitative real-time PCR (qRT-PCR), Western blotting, immunohistochemistry (IHC), and ELISAs were performed to verify selected markers. Our integrated analyses identified 90 putative protein biomarkers that were secreted or shed to the extracellular space and over-expressed in HNSCC cell lines, relative to controls. Subsequently, the over-expression of five markers was verified in vitro at the transcriptional and translational levels using qRT-PCR and Western blotting, respectively. IHC-based validation conducted in two independent cohorts comprising of 40 and 39 HNSCC biopsies revealed that high tumor expression of PLAU, IGFBP7, MMP14 and THBS1 were associated with inferior disease-free survival, and increased risk of disease progression or relapse. Furthermore, as demonstrated using ELISAs, circulating levels of PLAU and IGFBP7 were significantly higher in the plasma of HNSCC patients compared with healthy individuals.

The freshwater planarian Schmidtea mediterranea has been used in research for over 100 years, and is an emerging stem cell model because of its capability of regenerating large portions of missing body parts. Exteriorly, planarians are covered in mucous secretions of unknown composition, implicated in locomotion, predation, innate immunity, and substrate adhesion. Although the planarian genome has been sequenced, it remains mostly unannotated, challenging both genomic and proteomic analyses. The goal of the current study was to annotate the proteome of the whole planarian and its mucous fraction. The S. mediterranea proteome was analyzed via mass spectrometry by using multidimensional protein identification technology with whole-worm tryptic digests. By using a proteogenomics approach, MS data were searched against an in silico translated planarian transcript database, and by using the Swiss-Prot BLAST algorithm to identify proteins similar to planarian queries. A total of 1604 proteins were identified. The mucous subproteome was defined through analysis of a mucous trail fraction and an extract obtained by treating whole worms with the mucolytic agent N-acetylcysteine. Gene Ontology analysis confirmed that the mucous fractions were enriched with secreted proteins. The S. mediterranea proteome is highly similar to that predicted for the trematode Schistosoma mansoni associated with intestinal schistosomiasis, with the mucous subproteome particularly highly conserved. Remarkably, orthologs of 119 planarian mucous proteins are present in human mucosal secretions and tear fluid. We suggest planarians have potential to be a model system for the characterization of mucous protein function and relevant to parasitic flatworm infections and diseases underlined by mucous aberrancies, such as cystic fibrosis, asthma, and other lung diseases.

RNA polymerase II initiates from low complexity sequences so cells must reliably distinguish “real” from “cryptic” promoters and maintain fidelity to the former. Further, this must be performed under a range of conditions, including those found within inactive and highly transcribed regions. Here, we used genome-scale screening to identify those factors that regulate the use of a specific cryptic promoter and how this is influenced by the degree of transcription over the element. We show that promoter fidelity is most reliant on histone gene transactivators (Spt10, Spt21) and H3-H4 chaperones (Asf1, HIR complex) from the replication-independent deposition pathway. Mutations of Rtt106 that abrogate its interactions with H3-H4 or dsDNA permit extensive cryptic transcription comparable with replication-independent deposition factor deletions. We propose that nucleosome shielding is the primary means to maintain promoter fidelity, and histone replacement is most efficiently mediated in yeast cells by a HIR/Asf1/H3-H4/Rtt106 pathway.

The ryanodine receptor type 1 (RyR1) is a homotetrameric Ca(2+) release channel located in the sarcoplasmic reticulum of skeletal muscle where it plays a role in the initiation of skeletal muscle contraction. A soluble, 6×-histidine affinity-tagged cytosolic fragment of RyR1 (amino acids 1-4243) was expressed in HEK-293 cells, and metal affinity chromatography under native conditions was used to purify the peptide together with interacting proteins. When analyzed by gel-free liquid chromatography mass spectrometry (LC-MS), 703 proteins were identified under all conditions. This group of proteins was filtered to identify putative RyR interacting proteins by removing those proteins found in only 1 RyR purification and proteins for which average spectral counts were enriched by less than 4-fold over control values. This resulted in 49 potential RyR1 interacting proteins, and 4 were selected for additional interaction studies: calcium homeostasis endoplasmic reticulum protein (CHERP), endoplasmic reticulum-Golgi intermediate compartment 53-kDa protein (LMAN1), T-complex protein, and phosphorylase kinase. Western blotting showed that only CHERP co-purified with affinity-tagged RyR1 and was eluted with imidazole. Immunofluorescence showed that endogenous CHERP co-localizes with endogenous RyR1 in the sarcoplasmic reticulum of rat soleus muscle. A combination of overexpression of RyR1 in HEK-293 cells with siRNA-mediated suppression of CHERP showed that CHERP affects Ca(2+) release from the ER via RyR1. Thus, we propose that CHERP is an RyR1 interacting protein that may be involved in the regulation of excitation-contraction coupling.

Chaney and Jacobson first introduced the colloidal silica-bead protocol for the coating of cellular plasma membranes in the early 1980s. Since then, this method has been successfully incorporated into a wide range of in vitro and in vivo applications for the isolation of cell-surface proteins. The principle is simple - cationic colloidal silica microbeads are introduced to a suspension or monolayer of cells in culture. Electrostatic interactions between the beads and the negatively charged plasma membrane, followed by cross-linking to the membrane with an anionic polymer, ensure attachment and maintain the native protein conformation. Cells are subsequently ruptured, and segregation of the resulting plasma membrane sheets from the remaining- cell constituents is achieved by ultracentrifugation through density gradients. The resulting membrane-bead pellet is treated with various detergents or chaotropic agents (i.e., urea) to elute bound proteins. If proteomic profiling by mass spectrometry is desired, proteins are denatured, carbamidomethylated, and digested into peptides prior to chromatography.

Affinity purification coupled to mass spectrometry (AP-MS) is gaining widespread use for the identification of protein-protein interactions. It is unclear, however, whether typical AP sample complexity is limiting for the identification of all protein components using standard one-dimensional LC-MS/MS. Multidimensional sample separation is useful for reducing sample complexity prior to MS analysis and increases peptide and protein coverage of complex samples. Here, we monitored the effects of upstream protein or peptide separation techniques on typical mammalian AP-MS samples, generated by FLAG affinity purification of four baits with different biological functions and/or subcellular distribution. As a first separation step, we employed SDS-PAGE, strong cation exchange LC, or reversed-phase LC at basic pH. We also analyzed the benefits of using an instrument with a faster scan rate, the new TripleTOF 5600 mass spectrometer. While all multidimensional approaches yielded a clear increase in spectral counts, the increase in unique peptides and additional protein identification was modest and came at the cost of increased instrument and handling time. The use of a high duty-cycle instrument achieved similar benefits without these drawbacks. An increase in spectral counts is beneficial when data analysis methods relying on spectral counts, including Significance Analysis of INTeractome (SAINT), are used.