Quantitative profile of five murine core proteomes using label-free functional proteomics

Principles of phosphoproteomics and applications in cancer research

Phosphorylation constitutes the most common and best-studied regulatory post-translational modification in biological systems and archetypal signalling pathways driven by protein and lipid kinases are disrupted in essentially all cancer types. Thus, the study of the phosphoproteome stands to provide unique biological information on signalling pathway activity and on kinase network circuitry that is not captured by genetic or transcriptomic technologies. Here, we discuss the methods and tools used in phosphoproteomics and highlight how this technique has been used, and can be used in the future, for cancer research. Challenges still exist in mass spectrometry phosphoproteomics and in the software required to provide biological information from these datasets. Nevertheless, improvements in mass spectrometers with enhanced scan rates, separation capabilities and sensitivity, in biochemical methods for sample preparation and in computational pipelines are enabling an increasingly deep analysis of the phosphoproteome, where previous bottlenecks in data acquisition, processing and interpretation are being relieved. These powerful hardware and algorithmic innovations are not only providing exciting new mechanistic insights into tumour biology, from where new drug targets may be derived, but are also leading to the discovery of phosphoproteins as mediators of drug sensitivity and resistance and as classifiers of disease subtypes. These studies are, therefore, uncovering phosphoproteins as a new generation of disruptive biomarkers to improve personalised anti-cancer therapies.

Low HER2 expression in normal breast epithelium enables dedifferentiation and malignant transformation via chromatin opening

Overexpression of the HER2 protein in breast cancer patients is a predictor of poor prognosis and resistance to therapies. We used an inducible breast cancer transformation system that allows investigation of early molecular changes. HER2 overexpression to similar levels as those observed in a subtype of HER2-positive breast cancer patients induced transformation of MCF10A cells and resulted in gross morphological changes, increased anchorage-independent growth of cells, and altered the transcriptional programme of genes associated with oncogenic transformation. Global phosphoproteomic analysis during HER2 induction predominantly detected an increase in protein phosphorylation. Intriguingly, this correlated with chromatin opening, as measured by ATAC-seq on acini isolated from 3D cell culture. HER2 overexpression resulted in opening of many distal regulatory regions and promoted reprogramming-associated heterogeneity. We found that a subset of cells acquired a dedifferentiated breast stem-like phenotype, making them likely candidates for malignant transformation. Our data show that this population of cells, which counterintuitively enriches for relatively low HER2 protein abundance and increased chromatin accessibility, possesses transformational drive, resulting in increased anchorage-independent growth in vitro compared to cells not displaying a stem-like phenotype.

Driving role of head and neck cancer cell secretome on the invasion of stromal fibroblasts: Mechanistic insights by phosphoproteomics

BACKGROUND

Cancer-associated fibroblasts (CAFs) are major players in tumor-stroma communication, and participate in several cancer hallmarks to drive tumor progression and metastatic dissemination. This study investigates the driving effects of tumor-secreted factors on CAF biology, with the ultimate goal of identifying effective therapeutic targets/strategies for head and neck squamous cell carcinomas (HNSCC).

METHODS

Functionally, conditioned media (CM) from different HNSCC-derived cell lines and normal keratinocytes (Kc) were tested on the growth and invasion of populations of primary CAFs and normal fibroblasts (NFs) using 3D invasion assays in collagen matrices. The changes in MMPs expression were evaluated by RT-qPCR and kinase enrichment was analyzed using mass spectrometry phosphoproteomics.

RESULTS

Our results consistently demonstrate that HNSCC-secreted factors (but not Kc CM) specifically and robustly promoted pro-invasive properties in both CAFs and NFs, thereby reflecting the plasticity of fibroblast subtypes. Concomitantly, HNSCC-secreted factors massively increased metalloproteinases levels in CAFs and NFs. By contrast, HNSCC CM and Kc CM exhibited comparable growth-promoting effects on stromal fibroblasts. Mechanistically, phosphoproteomic analysis predominantly revealed phosphorylation changes in fibroblasts upon treatment with HNSCC CM, and various promising kinases were identified: MKK7, MKK4, ASK1, RAF1, BRAF, ARAF, COT, PDK1, RSK2 and AKT1. Interestingly, pharmacologic inhibition of RAF1/BRAF using sorafenib emerged as the most effective drug to block tumor-promoted fibroblast invasion without affecting fibroblast viability CONCLUSIONS: Our findings demonstrate that HNSCC-secreted factors specifically fine tune the invasive potential of stromal fibroblasts, thereby generating tumor-driven pro-invasive niches, which in turn to ultimately facilitate cancer cell dissemination. Furthermore, the RAF/BRAF inhibitor sorafenib was identified as a promising candidate to effectively target the onset of pro-invasive clusters of stromal fibroblasts in the HNSCC microenvironment.

Elucidating the role of the kinase activity of endothelial cell focal adhesion kinase in angiocrine signalling and tumour growth

A common limitation of cancer treatments is chemotherapy resistance. We have previously identified that endothelial cell (EC)-specific deletion of focal adhesion kinase (FAK) sensitises tumour cells to DNA-damaging therapies, reducing tumour growth in mice. The present study addressed the kinase activity dependency of EC FAK sensitisation to the DNA-damaging chemotherapeutic drug, doxorubicin. FAK is recognised as a therapeutic target in tumour cells, leading to the development of a range of inhibitors, the majority being ATP competitive kinase inhibitors. We demonstrate that inactivation of EC FAK kinase domain (kinase dead; EC FAK-KD) in established subcutaneous B16F0 tumours improves melanoma cell sensitisation to doxorubicin. Doxorubicin treatment in EC FAK-KD mice reduced the percentage change in exponential B16F0 tumour growth further than in wild-type mice. There was no difference in tumour blood vessel numbers, vessel perfusion or doxorubicin delivery between genotypes, suggesting a possible angiocrine effect on the regulation of tumour growth. Doxorubicin reduced perivascular malignant cell proliferation, while enhancing perivascular tumour cell apoptosis and DNA damage in tumours grown in EC FAK-KD mice 48 h after doxorubicin injection. Human pulmonary microvascular ECs treated with the pharmacological FAK kinase inhibitors defactinib, PF-562,271 or PF-573,228 in combination with doxorubicin also reduced cytokine expression levels. Together, these data suggest that targeting EC FAK kinase activity may alter angiocrine signals that correlate with improved acute tumour cell chemosensitisation. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

New advances in quantitative proteomics research and current applications in asthma

INTRODUCTION

Asthma is the most common chronic respiratory disease and has been declared a global public health problem by the World Health Organization. Due to the high heterogeneity and complexity, asthma can be classified into different 'phenotypes' and it is still difficult to assess the phenotypes and stages of asthma by traditional methods. In recent years, mass spectrometry-based proteomics studies have made significant progress in sensitivity and accuracy of protein identification and quantitation, and are able to obtain differences in protein expression across samples, which provides new insights into the mechanisms and classification of asthma.

AREAS COVERED

In this article, we summarize research strategies in quantitative proteomics, including labeled, label-free and targeted quantification, and highlight the advantages and disadvantages of each. In addition, new applications of quantitative proteomics and the current status of research in asthma have also been discussed. In this study, online resources such as PubMed and Google Scholar were used for literature retrieval.

EXPERT OPINION

The application of quantitative proteomics in asthma has an important role in identifying asthma subphenotypes, revealing potential pathogenesis and therapeutic targets. But the proteomic studies on asthma are not sufficient, as most of them are in the phase of biomarker discovery.

Implementation of Clinical Phosphoproteomics and Proteomics for Personalized Medicine

The identification of biomarkers for companion diagnostics is revolutionizing the development of treatments tailored to individual patients in different disease areas including cancer. Precision medicine is most frequently based on the detection of genomic markers that correlate with the efficacy of selected targeted therapies. However, since nongenetic mechanisms also contribute to disease biology, there is a considerable interest of using proteomic techniques as additional source of biomarkers to personalize therapies. In this chapter, we describe label-free mass spectrometry methods for proteomic and phosphoproteomic analysis compatible with routine analysis of clinical samples. We also outline bioinformatic pipelines based on statistical learning that use these proteomics datasets as input to quantify kinase activities and predict drug responses in cancer cells.

Upregulation of C/EBPα Inhibits Suppressive Activity of Myeloid Cells and Potentiates Antitumor Response in Mice and Patients with Cancer

PURPOSE

To evaluate the mechanisms of how therapeutic upregulation of the transcription factor, CCAAT/enhancer-binding protein alpha (C/EBPα), prevents tumor progression in patients with advanced hepatocellular carcinoma (HCC) and in different mouse tumor models.

EXPERIMENTAL DESIGN

We conducted a phase I trial in 36 patients with HCC (NCT02716012) who received sorafenib as part of their standard care, and were given therapeutic C/EBPα small activating RNA (saRNA; MTL-CEBPA) as either neoadjuvant or adjuvant treatment. In the preclinical setting, the effects of MTL-CEBPA were assessed in several mouse models, including BNL-1ME liver cancer, Lewis lung carcinoma (LLC), and colon adenocarcinoma (MC38).

RESULTS

MTL-CEBPA treatment caused radiologic regression of tumors in 26.7% of HCC patients with an underlying viral etiology with 3 complete responders. MTL-CEBPA treatment in those patients caused a marked decrease in peripheral blood monocytic myeloid-derived suppressor cell (M-MDSC) numbers and an overall reduction in the numbers of protumoral M2 tumor-associated macrophages (TAM). Gene and protein analysis of patient leukocytes following treatment showed CEBPA activation affected regulation of factors involved in immune-suppressive activity. To corroborate this observation, treatment of all the mouse tumor models with MTL-CEBPA led to a reversal in the suppressive activity of M-MDSCs and TAMs, but not polymorphonuclear MDSCs (PMN-MDSC). The antitumor effects of MTL-CEBPA in these tumor models showed dependency on T cells. This was accentuated when MTL-CEBPA was combined with checkpoint inhibitors or with PMN-MDSC-targeted immunotherapy.

CONCLUSIONS

This report demonstrates that therapeutic upregulation of the transcription factor C/EBPα causes inactivation of immune-suppressive myeloid cells with potent antitumor responses across different tumor models and in cancer patients. MTL-CEBPA is currently being investigated in combination with pembrolizumab in a phase I/Ib multicenter clinical study (NCT04105335).

FAK activity in cancer-associated fibroblasts is a prognostic marker and a druggable key metastatic player in pancreatic cancer

Cancer-associated fibroblasts (CAFs) are considered the most abundant type of stromal cells in pancreatic ductal adenocarcinoma (PDAC), playing a critical role in tumour progression and chemoresistance; however, a druggable target on CAFs has not yet been identified. Here we report that focal adhesion kinase (FAK) activity (evaluated based on 397 tyrosine phosphorylation level) in CAFs is highly increased compared to its activity in fibroblasts from healthy pancreas. Fibroblastic FAK activity is an independent prognostic marker for disease-free and overall survival of PDAC patients (cohort of 120 PDAC samples). Genetic inactivation of FAK within fibroblasts (FAK kinase-dead, KD) reduces fibrosis and immunosuppressive cell number within primary tumours and dramatically decreases tumour spread. FAK pharmacologic or genetic inactivation reduces fibroblast migration/invasion, decreases extracellular matrix (ECM) expression and deposition by CAFs, modifies ECM track generation and negatively impacts M2 macrophage polarization and migration. Thus, FAK activity within CAFs appears as an independent PDAC prognostic marker and a druggable driver of tumour cell invasion.

The breast cancer oncogene IKKε coordinates mitochondrial function and serine metabolism

IκB kinase ε (IKKε) is a key molecule at the crossroads of inflammation and cancer. Known to regulate cytokine secretion via NFκB and IRF3, the kinase is also a breast cancer oncogene, overexpressed in a variety of tumours. However, to what extent IKKε remodels cellular metabolism is currently unknown. Here, we used metabolic tracer analysis to show that IKKε orchestrates a complex metabolic reprogramming that affects mitochondrial metabolism and consequently serine biosynthesis independently of its canonical signalling role. We found that IKKε upregulates the serine biosynthesis pathway (SBP) indirectly, by limiting glucose‐derived pyruvate utilisation in the TCA cycle, inhibiting oxidative phosphorylation. Inhibition of mitochondrial function induces activating transcription factor 4 (ATF4), which in turn drives upregulation of the expression of SBP genes. Importantly, pharmacological reversal of the IKKε‐induced metabolic phenotype reduces proliferation of breast cancer cells. Finally, we show that in a highly proliferative set of ER negative, basal breast tumours, IKKε and PSAT1 are both overexpressed, corroborating the link between IKKε and the SBP in the clinical context.

Reconstructing kinase network topologies from phosphoproteomics data reveals cancer-associated rewiring

Understanding how oncogenic mutations rewire regulatory-protein networks is important for rationalizing the mechanisms of oncogenesis and for individualizing anticancer treatments. We report a chemical phosphoproteomics method to elucidate the topology of kinase-signaling networks in mammalian cells. We identified >6,000 protein phosphorylation sites that can be used to infer >1,500 kinase-kinase interactions and devised algorithms that can reconstruct kinase network topologies from these phosphoproteomics data. Application of our methods to primary acute myeloid leukemia and breast cancer tumors quantified the relationship between kinase expression and activity, and enabled the identification of hitherto unknown kinase network topologies associated with drug-resistant phenotypes or specific genetic mutations. Using orthogonal methods we validated that PIK3CA wild-type cells adopt MAPK-dependent circuitries in breast cancer cells and that the kinase TTK is important in acute myeloid leukemia. Our phosphoproteomic signatures of network circuitry can identify kinase topologies associated with both phenotypes and genotypes of cancer cells.

Cerium Oxide Nanoparticles Protect against Oxidant Injury and Interfere with Oxidative Mediated Kinase Signaling in Human-Derived Hepatocytes

Cerium oxide nanoparticles (CeO₂NPs) possess powerful antioxidant properties, thus emerging as a potential therapeutic tool in non-alcoholic fatty liver disease (NAFLD) progression, which is characterized by a high presence of reactive oxygen species (ROS). The aim of this study was to elucidate whether CeO₂NPs can prevent or attenuate oxidant injury in the hepatic human cell line HepG2 and to investigate the mechanisms involved in this phenomenon. The effect of CeO₂NPs on cell viability and ROS scavenging was determined, the differential expression of pro-inflammatory and oxidative stress-related genes was analyzed, and a proteomic analysis was performed to assess the impact of CeO₂NPs on cell phosphorylation in human hepatic cells under oxidative stress conditions. CeO₂NPs did not modify HepG2 cell viability in basal conditions but reduced H₂O₂- and lipopolysaccharide (LPS)-induced cell death and prevented H₂O₂-induced overexpression of MPO, PTGS1 and iNOS. Phosphoproteomic analysis showed that CeO₂NPs reverted the H₂O₂-mediated increase in the phosphorylation of peptides related to cellular proliferation, stress response, and gene transcription regulation, and interfered with H₂O₂ effects on mTOR, MAPK/ERK, CK2A1 and PKACA signaling pathways. In conclusion, CeO₂NPs protect HepG2 cells from cell-induced oxidative damage, reducing ROS generation and inflammatory gene expression as well as regulation of kinase-driven cell survival pathways.

Liver Activation of Hepatocellular Nuclear Factor-4α by Small Activating RNA Rescues Dyslipidemia and Improves Metabolic Profile

Non-alcoholic fatty liver disease (NAFLD) culminates in insulin resistance and metabolic syndrome. Because there are no approved pharmacological treatment agents for non-alcoholic steatohepatitis (NASH) and NAFLD, different signaling pathways are under investigation for drug development with the focus on metabolic pathways. Hepatocyte nuclear factor 4-alpha (HNF4A) is at the center of a complex transcriptional network where its disruption is directly linked to glucose and lipid metabolism. Resetting HNF4A expression in NAFLD is therefore crucial for re-establishing normal liver function. Here, small activating RNA (saRNA) specific for upregulating HNF4A was injected into rats fed a high-fat diet for 16 weeks. Intravenous delivery was carried out using 5-(G₅)-triethanolamine-core polyamidoamine (PAMAM) dendrimers. We observed a significant reduction in liver triglyceride, increased high-density lipoprotein/low-density lipoprotein (HDL/LDL) ratio, and decreased white adipose tissue/body weight ratio, all parameters to suggest that HNF4A-saRNA treatment induced a favorable metabolic profile. Proteomic analysis showed significant regulation of genes involved in sphingolipid metabolism, fatty acid β-oxidation, ketogenesis, detoxification of reactive oxygen species, and lipid transport. We demonstrate that HNF4A activation by oligonucleotide therapy may represent a novel single agent for the treatment of NAFLD and insulin resistance.

Host-directed kinase inhibitors act as novel therapies against intracellular Staphylococcus aureus

Host-directed therapeutics are a promising anti-infective strategy against intracellular bacterial pathogens. Repurposing host-targeted drugs approved by the FDA in the US, the MHRA in the UK and/or regulatory equivalents in other countries, is particularly interesting because these drugs are commercially available, safe doses are documented and they have been already approved for other clinical purposes. In this study, we aimed to identify novel therapies against intracellular Staphylococcus aureus, an opportunistic pathogen that is able to exploit host molecular and metabolic pathways to support its own intracellular survival. We screened 133 host-targeting drugs and found three host-directed tyrosine kinase inhibitors (Ibrutinib, Dasatinib and Crizotinib) that substantially impaired intracellular bacterial survival. We found that Ibrutinib significantly increased host cell viability after S. aureus infection via inhibition of cell invasion and intracellular bacterial proliferation. Using phosphoproteomics data, we propose a putative mechanism of action of Ibrutinib involving several host factors, including EPHA2, C-JUN and NWASP. We confirmed the importance of EPHA2 for staphylococcal infection in an EPHA2-knock-out cell line. Our study serves as an important example of feasibility for identifying host-directed therapeutics as candidates for repurposing.

Factors Secreted by Cancer-Associated Fibroblasts that Sustain Cancer Stem Properties in Head and Neck Squamous Carcinoma Cells as Potential Therapeutic Targets

This study investigates for the first time the crosstalk between stromal fibroblasts and cancer stem cell (CSC) biology in head and neck squamous cell carcinomas (HNSCC), with the ultimate goal of identifying effective therapeutic targets. The effects of conditioned media from cancer-associated fibroblasts (CAFs) and normal fibroblasts (NFs) on the CSC phenotype were assessed by combining functional and expression analyses in HNSCC-derived cell lines. Further characterization of CAFs and NFs secretomes by mass spectrometry was followed by pharmacologic target inhibition. We demonstrate that factors secreted by CAFs but not NFs, in the absence of serum/supplements, robustly increased anchorage-independent growth, tumorsphere formation, and CSC-marker expression. Modulators of epidermal growth factor receptor (EGFR), insulin-like growth factor receptor (IGFR), and platelet-derived growth factor receptor (PDGFR) activity were identified as paracrine cytokines/factors differentially secreted between CAFs and NFs, in a mass spectrometry analysis. Furthermore, pharmacologic inhibition of EGFR, IGFR, and PDGFR significantly reduced CAF-induced tumorsphere formation and anchorage-independent growth suggesting a role of these receptor tyrosine kinases in sustaining the CSC phenotype. These findings provide novel insights into tumor stroma⁻CSC communication, and potential therapeutic targets to effectively block the CAF-enhanced CSC niche signaling circuit.

Phosphoproteomics-Based Profiling of Kinase Activities in Cancer Cells

Cellular signaling, predominantly mediated by phosphorylation through protein kinases, is found to be deregulated in most cancers. Accordingly, protein kinases have been subject to intense investigations in cancer research, to understand their role in oncogenesis and to discover new therapeutic targets. Despite great advances, an understanding of kinase dysfunction in cancer is far from complete.A powerful tool to investigate phosphorylation is mass-spectrometry (MS)-based phosphoproteomics, which enables the identification of thousands of phosphorylated peptides in a single experiment. Since every phosphorylation event results from the activity of a protein kinase, high-coverage phosphoproteomics data should indirectly contain comprehensive information about the activity of protein kinases.In this chapter, we discuss the use of computational methods to predict kinase activity scores from MS-based phosphoproteomics data. We start with a short explanation of the fundamental features of the phosphoproteomics data acquisition process from the perspective of the computational analysis. Next, we briefly review the existing databases with experimentally verified kinase-substrate relationships and present a set of bioinformatic tools to discover novel kinase targets. We then introduce different methods to infer kinase activities from phosphoproteomics data and these kinase-substrate relationships. We illustrate their application with a detailed protocol of one of the methods, KSEA (Kinase Substrate Enrichment Analysis). This method is implemented in Python within the framework of the open-source Kinase Activity Toolbox (kinact), which is freely available at http://github.com/saezlab/kinact/ .

Kinase activity ranking using phosphoproteomics data (KARP) quantifies the contribution of protein kinases to the regulation of cell viability

Cell survival is regulated by a signaling network driven by the activity of protein kinases; however, determining the contribution that each kinase in the network makes to such regulation remains challenging. Here, we report a computational approach that uses mass spectrometry-based phosphoproteomics data to rank protein kinases based on their contribution to cell regulation. We found that the scores returned by this algorithm, which we have termed kinase activity ranking using phosphoproteomics data (KARP), were a quantitative measure of the contribution that individual kinases make to the signaling output. Application of KARP to the analysis of eight hematological cell lines revealed that cyclin-dependent kinase (CDK) 1/2, casein kinase (CK) 2, extracellular signal-related kinase (ERK), and p21-activated kinase (PAK) were the most frequently highly ranked kinases in these cell models. The patterns of kinase activation were cell-line specific yet showed a significant association with cell viability as a function of kinase inhibitor treatment. Thus, our study exemplifies KARP as an untargeted approach to empirically and systematically identify regulatory kinases within signaling networks.

Label-Free Phosphoproteomic Approach for Kinase Signaling Analysis

Phosphoproteomics is a powerful platform for the unbiased profiling of kinase-driven signaling pathways. Quantitation of phosphorylation can be performed by means of either labeling or label-free mass spectrometry (MS) methods. Because of their simplicity and universality, label-free methodology is gaining acceptance and popularity in molecular biology research. Analytical workflows for label-free quantification of phosphorylation, however, need to overcome several hurdles for the technique to be accurate and precise. These include the use of biochemical extraction procedures that efficiently and reproducibly isolate phosphopeptides from complex peptide matrices and an analytical strategy that can cope with missing MS/MS phosphopeptide spectra in a subset of the samples being compared. Testing the accuracy of the developed workflows is an essential prerequisite in the analysis of small molecules by MS, and this is achieved by constructing calibration curves to demonstrate linearity of quantification for each analyte. This level of analytical rigor is rarely shown in large-scale quantification of proteins using either label-based or label-free techniques. In this chapter we show an approach to test linearity of quantification of each phosphopeptide quantified by liquid chromatography (LC)-MS without the need to synthesize standards or label proteins. We further describe the appropriate sample handling techniques required for the reproducible recovery of phosphopeptides and explore the essential algorithmic features that enable the handling of missing MS/MS spectra and thus make label-free data suitable for such analyses. The combined technology described in this chapter expands the applicability of phosphoproteomics to questions not previously tractable with other methodologies.

NCK Associated Protein 1 Modulated by miRNA-214 Determines Vascular Smooth Muscle Cell Migration, Proliferation, and Neointima Hyperplasia

BACKGROUND

MicroRNA miR-214 has been implicated in many biological cellular functions, but the impact of miR-214 and its target genes on vascular smooth muscle cell (VSMC) proliferation, migration, and neointima smooth muscle cell hyperplasia is unknown.

METHODS AND RESULTS

Expression of miR-214 was closely regulated by different pathogenic stimuli in VSMCs through a transcriptional mechanism and decreased in response to vascular injury. Overexpression of miR-214 in serum-starved VSMCs significantly decreased VSMC proliferation and migration, whereas knockdown of miR-214 dramatically increased VSMC proliferation and migration. Gene and protein biochemical assays, including proteomic analyses, showed that NCK associated protein 1 (NCKAP1)-a major component of the WAVE complex that regulates lamellipodia formation and cell motility-was negatively regulated by miR-214 in VSMCs. Luciferase assays showed that miR-214 substantially repressed wild-type but not the miR-214 binding site mutated version of NCKAP1 3' untranslated region luciferase activity in VSMCs. This result confirmed that NCKAP1 is the functional target of miR-214 in VSMCs. NCKAP1 knockdown in VSMCs recapitulates the inhibitory effects of miR-214 overexpression on actin polymerization, cell migration, and proliferation. Data from cotransfection experiments also revealed that inhibition of NCKAP1 is required for miR-214-mediated lamellipodia formation, cell motility, and growth. Importantly, locally enforced expression of miR-214 in the injured vessels significantly reduced NCKAP1 expression levels, inhibited VSMC proliferation, and prevented neointima smooth muscle cell hyperplasia after injury.

CONCLUSIONS

We uncovered an important role of miR-214 and its target gene NCKAP1 in modulating VSMC functions and neointima hyperplasia. Our findings suggest that miR-214 represents a potential therapeutic target for vascular diseases.

Targeted In-Depth Quantification of Signaling Using Label-Free Mass Spectrometry

Protein phosphorylation encodes information on the activity of kinase-driven signaling pathways that regulate cell biology. This chapter discusses an approach, named TIQUAS (targeted in-depth quantification of signaling), to quantify cell signaling comprehensively and without bias. The workflow-based on mass spectrometry (MS) and computational science-consists of targeting the analysis of phosphopeptides previously identified by shotgun liquid chromatography tandem MS (LC-MS/MS) across the samples that are being compared. TIQUAS therefore takes advantage of concepts derived from both targeted (data-independent) and data-dependent acquisition methods; phosphorylation sites are quantified in all experimental samples regardless of whether or not these phosphopeptides were identified by MS/MS in all runs. As a result, datasets are obtained containing quantitative information on several thousand phosphorylation sites in as many samples and replicates as required in the experimental design, and these rich datasets are devoid of a significant number of missing data points. This chapter discussed the biochemical, analytical, and computational procedures required to apply the approach and for obtaining a biological interpretation of the data in the context of our understanding of cell signaling regulation and kinase-substrate relationships.

Fumarate is an epigenetic modifier that elicits epithelial-to-mesenchymal transition

Mutations of the tricarboxylic acid cycle enzyme fumarate hydratase cause hereditary leiomyomatosis and renal cell cancer. Fumarate hydratase-deficient renal cancers are highly aggressive and metastasize even when small, leading to a very poor clinical outcome. Fumarate, a small molecule metabolite that accumulates in fumarate hydratase-deficient cells, plays a key role in cell transformation, making it a bona fide oncometabolite. Fumarate has been shown to inhibit α-ketoglutarate-dependent dioxygenases that are involved in DNA and histone demethylation. However, the link between fumarate accumulation, epigenetic changes, and tumorigenesis is unclear. Here we show that loss of fumarate hydratase and the subsequent accumulation of fumarate in mouse and human cells elicits an epithelial-to-mesenchymal-transition (EMT), a phenotypic switch associated with cancer initiation, invasion, and metastasis. We demonstrate that fumarate inhibits Tet-mediated demethylation of a regulatory region of the antimetastatic miRNA cluster mir-200ba429, leading to the expression of EMT-related transcription factors and enhanced migratory properties. These epigenetic and phenotypic changes are recapitulated by the incubation of fumarate hydratase-proficient cells with cell-permeable fumarate. Loss of fumarate hydratase is associated with suppression of miR-200 and the EMT signature in renal cancer and is associated with poor clinical outcome. These results imply that loss of fumarate hydratase and fumarate accumulation contribute to the aggressive features of fumarate hydratase-deficient tumours.

Integrated transcriptomic and proteomic analysis identifies protein kinase CK2 as a key signaling node in an inflammatory cytokine network in ovarian cancer cells

We previously showed how key pathways in cancer-related inflammation and Notch signaling are part of an autocrine malignant cell network in ovarian cancer. This network, which we named the "TNF network", has paracrine actions within the tumor microenvironment, influencing angiogenesis and the immune cell infiltrate.The aim of this study was to identify critical regulators in the signaling pathways of the TNF network in ovarian cancer cells that might be therapeutic targets. To achieve our aim, we used a systems biology approach, combining data from phospho-proteomic mass spectrometry and gene expression array analysis. Among the potential therapeutic kinase targets identified was the protein kinase Casein kinase II (CK2).Knockdown of CK2 expression in malignant cells by siRNA or treatment with the specific CK2 inhibitor CX-4945 significantly decreased Notch signaling and reduced constitutive cytokine release in ovarian cancer cell lines that expressed the TNF network as well as malignant cells isolated from high grade serous ovarian cancer ascites. The expression of the same cytokines was also inhibited after treatment with CX-4945 in a 3D organotypic model. CK2 inhibition was associated with concomitant inhibition of proliferative activity, reduced angiogenesis and experimental peritoneal ovarian tumor growth.In conclusion, we have identified kinases, particularly CK2, associated with the TNF network that may play a central role in sustaining the cytokine network and/or mediating its effects in ovarian cancer.

Application of Proteomics in Cancer Biomarker Discovery: GeLC-MS/MS

Proteomic approaches are being increasingly applied to study multiple facets of healthy and diseased processes. In particular, the application of global proteome profiling in the field of oncology is already starting to shape the diagnostic, prognostic, monitoring, and therapeutic approaches. At the heart of such approaches lies a quest for clinically relevant biomarkers, particularly arising from global analyses of body fluids, as, in major part, they represent easily accessible and noninvasive matrices. A detailed protocol of one of the popular approaches for global proteome profiling, SDS-PAGE-liquid chromatography-tandem mass spectrometry or GeLC-MS/MS, and its application for biomarker discovery in urine is provided here.

Large-scale models of signal propagation in human cells derived from discovery phosphoproteomic data

Mass spectrometry is widely used to probe the proteome and its modifications in an untargeted manner, with unrivalled coverage. Applied to phosphoproteomics, it has tremendous potential to interrogate phospho-signalling and its therapeutic implications. However, this task is complicated by issues of undersampling of the phosphoproteome and challenges stemming from its high-content but low-sample-throughput nature. Hence, methods using such data to reconstruct signalling networks have been limited to restricted data sets and insights (for example, groups of kinases likely to be active in a sample). We propose a new method to handle high-content discovery phosphoproteomics data on perturbation by putting it in the context of kinase/phosphatase-substrate knowledge, from which we derive and train logic models. We show, on a data set obtained through perturbations of cancer cells with small-molecule inhibitors, that this method can study the targets and effects of kinase inhibitors, and reconcile insights obtained from multiple data sets, a common issue with these data.

Phosphoproteomics can offer significant insight into cell signalling and how signalling is modified in response to perturbations. Here the authors develop a new tool for the analysis of high-content phosphoproteomics in the context of kinase/phosphatase-substrate knowledge, which is used to train logic models.

mTOR regulates MAPKAPK2 translation to control the senescence-associated secretory phenotype

Senescent cells secrete a combination of factors collectively known as the senescence-associated secretory phenotype (SASP). The SASP reinforces senescence and activates an immune surveillance response, but it can also show pro-tumorigenic properties and contribute to age-related pathologies. In a drug screen to find new SASP regulators, we uncovered the mTOR inhibitor rapamycin as a potent SASP suppressor. Here we report a mechanism by which mTOR controls the SASP by differentially regulating the translation of the MK2 (also known as MAPKAPK2) kinase through 4EBP1. In turn, MAPKAPK2 phosphorylates the RNA-binding protein ZFP36L1 during senescence, inhibiting its ability to degrade the transcripts of numerous SASP components. Consequently, mTOR inhibition or constitutive activation of ZFP36L1 impairs the non-cell-autonomous effects of senescent cells in both tumour-suppressive and tumour-promoting contexts. Altogether, our results place regulation of the SASP as a key mechanism by which mTOR could influence cancer, age-related diseases and immune responses.

Targeted label-free approach for quantification of epoxide hydrolase and glutathione transferases in microsomes

The aim of this study was to investigate the expression and organ distribution of cytochrome P450 (CYP450) enzymes, microsomal epoxide hydrolase (MEH), and microsomal glutathione-S-transferase (MGST 1, 2, 3) in human liver, lung, intestinal, and kidney microsomes by targeted peptide-based quantification using nano liquid chromatography-tandem multiple reaction monitoring (nano LC-MRM). Applying this method, we analyzed 16 human liver microsomes and pooled lung, kidney, and intestine microsomes. Nine of the CYP450s (CYP1A2, 2B6, 2C8, 2C9, 2C19, 2D6, 2E1, 3A4, 3A5) could be quantified in liver. Except for CYP3A4 and 3A5 existing in intestine, other CYP450s had little content (<0.1 pmol/mg protein) in extrahepatic tissues. MEH and MGSTs could be quantified both in hepatic and in extrahepatic tissues. The highest concentrations of MEH and MGST 1, 2 were found in liver; conversely MGST 3 was abundant in human kidney and intestine compared to liver. The targeted proteomics assay described here can be broadly and efficiently utilized as a tool for investigating the targeted proteins. The method also provides novel CYP450s, MEH, and MGSTs expression data in human hepatic and extrahepatic tissues that will benefit rational approaches to evaluate metabolism in drug development.

The urinary proteome and metabonome differ from normal in adults with mitochondrial disease

We studied the extent and nature of renal involvement in a cohort of 117 adult patients with mitochondrial disease, by measuring urinary retinol-binding protein (RBP) and albumin; established markers of tubular and glomerular dysfunction, respectively. Seventy-five patients had the m.3243A>G mutation and the most frequent phenotypes within the entire cohort were 14 with MELAS, 33 with MIDD, and 17 with MERRF. Urinary RBP was increased in 29 of 75 of m.3243A>G patients, whereas albumin was increased in 23 of the 75. The corresponding numbers were 16 and 14, respectively, in the 42 non-m.3243A>G patients. RBP and albumin were higher in diabetic m.3243A>G patients than in nondiabetics, but there were no significant differences across the three major clinical phenotypes. The urine proteome (mass spectrometry) and metabonome (nuclear magnetic resonance) in a subset of the m.3243A>G patients were markedly different from controls, with the most significant alterations occurring in lysosomal proteins, calcium-binding proteins, and antioxidant defenses. Differences were also found between asymptomatic m.3243A>G carriers and controls. No patients had an elevated serum creatinine level, but 14% had hyponatremia, 10% had hypophosphatemia, and 14% had hypomagnesemia. Thus, abnormalities in kidney function are common in adults with mitochondrial disease, exist in the absence of elevated serum creatinine, and are not solely explained by diabetes.

Role of phosphoproteomics in the development of personalized cancer therapies

Cell signalling pathways driven by protein and lipid kinases contribute to the onset and progression of virtually all cancer types. Consequently, several inhibitors against these enzymes have clinical utility for the treatment of different forms of cancer. A problem that hampers further development is that not all patients respond equally well to kinase inhibitors and a significant proportion of those that initially respond eventually develop resistance. This review considers how an integrative analysis of kinase signalling may be used to address this issue. Advances in the biophysics of mass spectrometry, in biochemical procedures for phosphopeptide enrichment, and in computational approaches for label-free quantification have contributed to the development of phosphoproteomics workflows compatible with the analysis of clinical material. These developments, together with new bioinformatics tools to derive information on signalling circuitry from phosphoproteomics data, allow investigating kinase networks with unprecedented depth. Phosphoproteomics technology is starting to be used in translational research and, with further developments, such methods may also be able to measure the circuitry of cancer signalling networks in routine clinical assays. This review reflects on how this information could be used to accurately predict the best kinase inhibitor for each individual cancer patient.

Ginsenoside Rb1 prevents hypoxia-reoxygenation-induced apoptosis in H9c2 cardiomyocytes via an estrogen receptor-dependent crosstalk among the Akt, JNK, and ERK 1/2 pathways using a label-free quantitative proteomics analysis

Rb1 prevents H/R-induced apoptosis of H9c2 cells via an estrogen receptor-dependent crosstalk among the Akt, JNK, and ERK 1/2 pathways.

Integrating phosphoproteome and transcriptome reveals new determinants of macrophage multinucleation

Macrophage multinucleation (MM) is essential for various biological processes such as osteoclast-mediated bone resorption and multinucleated giant cell-associated inflammatory reactions. Here we study the molecular pathways underlying multinucleation in the rat through an integrative approach combining MS-based quantitative phosphoproteomics (LC-MS/MS) and transcriptome (high-throughput RNA-sequencing) to identify new regulators of MM. We show that a strong metabolic shift toward HIF1-mediated glycolysis occurs at transcriptomic level during MM, together with modifications in phosphorylation of over 50 proteins including several ARF GTPase activators and polyphosphate inositol phosphatases. We use shortest-path analysis to link differential phosphorylation with the transcriptomic reprogramming of macrophages and identify LRRFIP1, SMARCA4, and DNMT1 as novel regulators of MM. We experimentally validate these predictions by showing that knock-down of these latter reduce macrophage multinucleation. These results provide a new framework for the combined analysis of transcriptional and post-translational changes during macrophage multinucleation, prioritizing essential genes, and revealing the sequential events leading to the multinucleation of macrophages.

Cross-species proteomics reveals specific modulation of signaling in cancer and stromal cells by phosphoinositide 3-kinase (PI3K) inhibitors

The tumor microenvironment plays key roles in cancer biology, but its impact on the regulation of signaling pathway activity in cancer cells has not been systemically investigated. We designed an analytical strategy that allows differential analysis of signaling between cancer and stromal cells present in tumor xenografts. We used this approach to investigate how in vivo growth conditions and PI3K inhibitors regulate pathway activities in both cancer and stromal cell populations. We found that, despite inducing more modest changes in protein expression, in vivo growing conditions extensively rewired protein kinase networks in cancer cells. As a result, different sets of phosphorylation sites were modulated by PI3K inhibitors in cancer cells growing in tumors relative to when these cells were in culture. The p110δ PI3K-selective compound CAL-101 (Idelalisib) did not inhibit markers of PI3K activity in cancer or stromal cells; however, unexpectedly, it induced phosphorylation on SQ motifs in both subpopulations of tumor cells in vivo but not in vitro. Thus, the interaction between cancer cells and the stroma modulated the ability of PI3K inhibitors to induce the activation of apoptosis in solid tumors. Our study provides proof-of-principle of a proteomics workflow for measuring signaling specifically in cancer and stromal cells and for investigating how cancer biochemistry is modulated in vivo.

Environmental stress affects the activity of metabolic and growth factor signaling networks and induces autophagy markers in MCF7 breast cancer cells

Phosphoproteomic techniques are contributing to our understanding of how signaling pathways interact and regulate biological processes. This technology is also being used to characterize how signaling networks are remodeled during disease progression and to identify biomarkers of signaling pathway activity and of responses to cancer therapy. A potential caveat in these studies is that phosphorylation is a very dynamic modification that can substantially change during the course of an experiment or the retrieval and processing of cellular samples. Here, we investigated how exposure of cells to ambient conditions modulates phosphorylation and signaling pathway activity in the MCF7 breast cancer cell line. About 1.5% of 3,500 sites measured showed a significant change in phosphorylation extent upon exposure of cells to ambient conditions for 15 min. The effects of this perturbation in modifying phosphorylation patterns did not involve random changes due to stochastic activation of kinases and phosphatases. Instead, exposure of cells to ambient conditions elicited an environmental stress reaction that involved a coordinated response to a metabolic stress situation, which included: (1) the activation of AMPK; (2) the inhibition of PI3K, AKT, and ERK; (3) an increase in markers of protein synthesis inhibition at the level of translation elongation; and (4) an increase in autophagy markers. We also observed that maintaining cells in ice modified but did not completely abolish this metabolic stress response. In summary, exposure of cells to ambient conditions affects the activity of signaling networks previously implicated in metabolic and growth factor signaling. Mass spectrometry data have been deposited to the ProteomeXchange with identifier PXD000472.

Proteomics of endosomal compartments from plants case study: isolation of trans-Golgi network vesicles

A detailed understanding of endomembrane processes and their biological roles is vital for a complete picture of plant growth and development; however their highly dynamic nature has complicated comprehensive and rigorous studies so far. Recent pioneering efforts have demonstrated that isolation of vesicles in their native state, paired with a quantitative identification of their cargo, offers a viable and practicable approach for the dissection of endomembrane trafficking pathways. The protocol presented in this chapter describes in detail the isolation of the SYP61 trans-Golgi network vesicles from Arabidopsis. With minor alterations, in a few key parameters, it can be adopted to yield a universal procedure for the broad spectrum of plant vesicles.

Salinity-induced regulation of the myo-inositol biosynthesis pathway in tilapia gill epithelium

The myo-inositol biosynthesis (MIB) pathway converts glucose-6-phosphate to the compatible osmolyte myo-inositol that protects cells from osmotic stress. Using proteomics, the enzymes that constitute the MIB pathway, myo-inositol phosphate synthase (MIPS) and inositol monophosphatase 1 (IMPA1), are identified in tilapia (Oreochromis mossambicus) gill epithelium. Targeted, quantitative, label-free proteomics reveals that they are both upregulated during salinity stress. Upregulation is stronger when fish are exposed to severe (34 ppt acute and 90 ppt gradual) relative to moderate (70 ppt gradual) salinity stress. IMPA1 always responds more strongly than MIPS, suggesting that MIPS is more stable during salinity stress. MIPS is N-terminally acetylated and the corresponding peptide increases proportionally to MIPS protein, while non-acetylated N-terminal peptide is not detectable, indicating that MIPS acetylation is constitutive and may serve to stabilize the protein. Hyperosmotic induction of MIPS and IMPA1 is confirmed using western blot and real-time qPCR and is much higher at the mRNA than at the protein level. Two distinct MIPS mRNA variants are expressed in the gill, but one is more strongly regulated by salinity than the other. A single MIPS gene is encoded in the tilapia genome whereas the zebrafish genome lacks MIPS entirely. The genome of euryhaline tilapia contains four IMPA genes, two of which are expressed, but only one is salinity regulated in gill epithelium. The genome of stenohaline zebrafish contains a single IMPA gene. We conclude that the MIB pathway represents a major salinity stress coping mechanism that is regulated at multiple levels in euryhaline fish but absent in stenohaline zebrafish.

Quantitative molecular phenotyping of gill remodeling in a cichlid fish responding to salinity stress

A two-tiered label-free quantitative (LFQ) proteomics workflow was used to elucidate how salinity affects the molecular phenotype, i.e. proteome, of gills from a cichlid fish, the euryhaline tilapia (Oreochromis mossambicus). The workflow consists of initial global profiling of relative tryptic peptide abundances in treated versus control samples followed by targeted identification (by MS/MS) and quantitation (by chromatographic peak area integration) of validated peptides for each protein of interest. Fresh water acclimated tilapia were independently exposed in separate experiments to acute short-term (34 ppt) and gradual long-term (70 ppt, 90 ppt) salinity stress followed by molecular phenotyping of the gill proteome. The severity of salinity stress can be deduced with high technical reproducibility from the initial global label-free quantitative profiling step alone at both peptide and protein levels. However, an accurate regulation ratio can only be determined by targeted label-free quantitative profiling because not all peptides used for protein identification are also valid for quantitation. Of the three salinity challenges, gradual acclimation to 90 ppt has the most pronounced effect on gill molecular phenotype. Known salinity effects on tilapia gills, including an increase in the size and number of mitochondria-rich ionocytes, activities of specific ion transporters, and induction of specific molecular chaperones are reflected in the regulation of abundances of the corresponding proteins. Moreover, specific protein isoforms that are responsive to environmental salinity change are resolved and it is revealed that salinity effects on the mitochondrial proteome are nonuniform. Furthermore, protein NDRG1 has been identified as a novel key component of molecular phenotype restructuring during salinity-induced gill remodeling. In conclusion, besides confirming known effects of salinity on gills of euryhaline fish, molecular phenotyping reveals novel insight into proteome changes that underlie the remodeling of tilapia gill epithelium in response to environmental salinity change.

Maximizing peptide identification events in proteomic workflows using data-dependent acquisition (DDA)

Current analytical strategies for collecting proteomic data using data-dependent acquisition (DDA) are limited by the low analytical reproducibility of the method. Proteomic discovery efforts that exploit the benefits of DDA, such as providing peptide sequence information, but that enable improved analytical reproducibility, represent an ideal scenario for maximizing measureable peptide identifications in "shotgun"-type proteomic studies. Therefore, we propose an analytical workflow combining DDA with retention time aligned extracted ion chromatogram (XIC) areas obtained from high mass accuracy MS1 data acquired in parallel. We applied this workflow to the analyses of sample matrixes prepared from mouse blood plasma and brain tissues and observed increases in peptide detection of up to 30.5% due to the comparison of peptide MS1 XIC areas following retention time alignment of co-identified peptides. Furthermore, we show that the approach is quantitative using peptide standards diluted into a complex matrix. These data revealed that peptide MS1 XIC areas provide linear response of over three orders of magnitude down to low femtomole (fmol) levels. These findings argue that augmenting "shotgun" proteomic workflows with retention time alignment of peptide identifications and comparative analyses of corresponding peptide MS1 XIC areas improve the analytical performance of global proteomic discovery methods using DDA.

Recent advances in quantitative neuroproteomics

The field of proteomics is undergoing rapid development in a number of different areas including improvements in mass spectrometric platforms, peptide identification algorithms and bioinformatics. In particular, new and/or improved approaches have established robust methods that not only allow for in-depth and accurate peptide and protein identification and modification, but also allow for sensitive measurement of relative or absolute quantitation. These methods are beginning to be applied to the area of neuroproteomics, but the central nervous system poses many specific challenges in terms of quantitative proteomics, given the large number of different neuronal cell types that are intermixed and that exhibit distinct patterns of gene and protein expression. This review highlights the recent advances that have been made in quantitative neuroproteomics, with a focus on work published over the last five years that applies emerging methods to normal brain function as well as to various neuropsychiatric disorders including schizophrenia and drug addiction as well as of neurodegenerative diseases including Parkinson's disease and Alzheimer's disease. While older methods such as two-dimensional polyacrylamide electrophoresis continued to be used, a variety of more in-depth MS-based approaches including both label (ICAT, iTRAQ, TMT, SILAC, SILAM), label-free (label-free, MRM, SWATH) and absolute quantification methods, are rapidly being applied to neurobiological investigations of normal and diseased brain tissue as well as of cerebrospinal fluid (CSF). While the biological implications of many of these studies remain to be clearly established, that there is a clear need for standardization of experimental design and data analysis, and that the analysis of protein changes in specific neuronal cell types in the central nervous system remains a serious challenge, it appears that the quality and depth of the more recent quantitative proteomics studies is beginning to shed light on a number of aspects of neuroscience that relates to normal brain function as well as of the changes in protein expression and regulation that occurs in neuropsychiatric and neurodegenerative disorders.

LFQuant: a label-free fast quantitative analysis tool for high-resolution LC-MS/MS proteomics data

Database searching based methods for label-free quantification aim to reconstruct the peptide extracted ion chromatogram based on the identification information, which can limit the search space and thus make the data processing much faster. The random effect of the MS/MS sampling can be remedied by cross-assignment among different runs. Here, we present a new label-free fast quantitative analysis tool, LFQuant, for high-resolution LC-MS/MS proteomics data based on database searching. It is designed to accept raw data in two common formats (mzXML and Thermo RAW), and database search results from mainstream tools (MASCOT, SEQUEST, and X!Tandem), as input data. LFQuant can handle large-scale label-free data with fractionation such as SDS-PAGE and 2D LC. It is easy to use and provides handy user interfaces for data loading, parameter setting, quantitative analysis, and quantitative data visualization. LFQuant was compared with two common quantification software packages, MaxQuant and IDEAL-Q, on the replication data set and the UPS1 standard data set. The results show that LFQuant performs better than them in terms of both precision and accuracy, and consumes significantly less processing time. LFQuant is freely available under the GNU General Public License v3.0 at http://sourceforge.net/projects/lfquant/.

Kinase-substrate enrichment analysis provides insights into the heterogeneity of signaling pathway activation in leukemia cells

Kinases determine the phenotypes of many cancer cells, but the frequency with which individual kinases are activated in primary tumors remains largely unknown. We used a computational approach, termed kinase-substrate enrichment analysis (KSEA), to systematically infer the activation of given kinase pathways from mass spectrometry-based phosphoproteomic analysis of acute myeloid leukemia (AML) cells. Experiments conducted in cell lines validated the approach and, furthermore, revealed that DNA-dependent protein kinase (DNA-PK) was activated as a result of inhibiting the phosphoinositide 3-kinase (PI3K)-mammalian target of rapamycin (mTOR) signaling pathway. Application of KSEA to primary AML cells identified PI3K, casein kinases (CKs), cyclin-dependent kinases (CDKs), and p21-activated kinases (PAKs) as the kinase substrate groups most frequently enriched in this cancer type. Substrates phosphorylated by extracellular signal-regulated kinase (ERK) and cell division cycle 7 (CDC7) were enriched in primary AML cells that were resistant to inhibition of PI3K-mTOR signaling, whereas substrates of the kinases Abl, Lck, Src, and CDK1 were increased in abundance in inhibitor-sensitive cells. Modeling based on the abundances of these substrate groups accurately predicted sensitivity to a dual PI3K and mTOR inhibitor in two independent sets of primary AML cells isolated from patients. Thus, our study demonstrates KSEA as an untargeted method for the systematic profiling of kinase pathway activities and for increasing our understanding of diseases caused by the dysregulation of signaling pathways.

Proteome analysis of the fathead minnow (Pimephales promelas) reproductive testes

Proteomics is becoming more widely used as a tool in fish physiology and toxicology and can offer mechanistic insight into organism responses to environmental signals and stressors. Using a LTQ Orbitrap Velos MS/MS, we detected 1075 proteins in the reproductive testis of fathead minnow. Proteins localized to the testis included those with a role in spermatogenesis, DNA repair, gamete meiosis, and proteins that have methylation and phosporylation activity, which are important regulatory mechanisms required for sperm maturation. Enrichment analysis revealed that proteins involved in translation, excision DNA repair, and chromatin remodeling were significantly enriched in the testis (>25% protein coverage of the cellular pathways). Proteins involved in RNA metabolism, spliceosome assembly, metabolism, and DNA unwinding were localized to the testis, and the DEAD (Asp-Glu-Ala-Asp) box RNA-dependent helicase family was well represented in this reproductive tissue. Based upon common detected proteins and functional processes between FHMs and the more ancient sharks, other ray-finned fishes, and mammals, we hypothesize that biological processes involved in the testis (DNA unwinding, RNA processing, spliceosome assembly) have been conserved throughout vertebrate evolution. This study provides the foundation for more in depth proteomics studies investigating the effects of hormones and endocrine disruptors in the teleostean testes.

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

Mass spectrometry-based proteomics has evolved as a high-throughput research field over the past decade. Significant advances in instrumentation, and the ability to produce huge volumes of data, have emphasized the need for adequate data analysis tools, which are nowadays often considered the main bottleneck for proteomics development. This review highlights important issues that directly impact the effectiveness of proteomic quantitation and educates software developers and end-users on available computational solutions to correct for the occurrence of these factors. Potential sources of errors specific for stable isotope-based methods or label-free approaches are explicitly outlined. The overall aim focuses on a generic proteomic workflow.

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

Mass spectrometry-based proteomics has evolved as a high-throughput research field over the past decade. Significant advances in instrumentation, and the ability to produce huge volumes of data, have emphasized the need for adequate data analysis tools, which are nowadays often considered the main bottleneck for proteomics development. This review highlights important issues that directly impact the effectiveness of proteomic quantitation and educates software developers and end-users on available computational solutions to correct for the occurrence of these factors. Potential sources of errors specific for stable isotope-based methods or label-free approaches are explicitly outlined. The overall aim focuses on a generic proteomic workflow.