Comparison of label-free methods for quantifying human proteins by shotgun proteomics

A Protocol for Isolation and Proteomic Characterization of Distinct Extracellular Vesicle Subtypes by Sequential Centrifugal Ultrafiltration

Scientific and clinical interest in extracellular vesicles (EVs) has increased rapidly as evidence mounts that they may constitute a new signaling paradigm. Recent studies have highlighted EVs carry preassembled complex biological information that elicit pleiotropic responses in target cells. It is well recognized that cells secrete essentially two EV subtypes that can be partially separated by differential centrifugation (DC): the larger size class (referred to as "microvesicles" or "shed microvesicles," sMVs) is heterogeneous (100-1500 nm), while the smaller size class (referred to as "exosomes") is relatively homogeneous in size (50-150 nm). A key issue hindering progress in understanding underlying mechanisms of EV subtype biogenesis and cargo selectivity has been the technical challenge of isolating homogeneous EV subpopulations suitable for molecular analysis. In this protocol we reveal a novel method for the isolation, purification, and characterization of distinct EV subtypes: exosomes and sMVs. This method, based on sequential centrifugal ultrafiltration (SCUF), affords unbiased isolation of EVs from conditioned medium from a human colon cancer cell model. For both EV subtypes, this protocol details extensive purification and characterization based on dynamic light scattering, cryoelectron microscopy, quantitation, immunoblotting, and comparative label-free proteome profiling. This analytical SCUF method developed is potentially scalable using tangential flow filtration and provides a solid foundation for future in-depth functional studies of EV subtypes from diverse cell types.

Efficient Quantitative Comparisons of Plasma Proteomes Using Label-Free Analysis with MaxQuant

Mass spectrometry (MS)-based quantitation of plasma proteomes is challenging due to the extremely wide dynamic range and molecular heterogeneity of plasma samples. However, recent advances in technology, MS instrumentation, and bioinformatics have enabled in-depth quantitative analyses of very complex proteomes, including plasma. Specifically, recent improvements in both label-based and label-free quantitation strategies have allowed highly accurate quantitative comparisons of expansive proteome datasets. Here we present a method for in-depth label-free analysis of human plasma samples using MaxQuant.

Functional proteomics-aided selection of protease inhibitors for herbivore insect control

Studies have reported the potential of protease inhibitors to engineer insect resistance in transgenic plants but the general usefulness of this approach in crop protection still remains to be established. Insects have evolved strategies to cope with dietary protease inhibitors, such as the use of proteases recalcitrant to inhibition, that often make the selection of effective inhibitors very challenging. Here, we used a functional proteomics approach for the ‘capture’ of Cys protease targets in crude protein extracts as a tool to identify promising cystatins for plant improvement. Two cystatins found to differ in their efficiency to capture Cys proteases of the coleopteran pest Leptinotarsa decemlineata also differed in their usefulness to produce transgenic potato lines resistant to this insect. Plants expressing the most potent cystatin at high level had a strong repressing effect on larval growth and leaf intake, while plants expressing the weakest cystatin showed no effect on both two parameters compared to untransformed parental line used for genetic transformation. Our data underline the relevance of considering the whole range of possible protease targets when selecting an inhibitor for plant pest control. They also confirm the feasibility of developing cystatin-expressing transgenics resistant to a major pest of potato.

On the Dependency of Cellular Protein Levels on mRNA Abundance

The question of how genomic information is expressed to determine phenotypes is of central importance for basic and translational life science research and has been studied by transcriptomic and proteomic profiling. Here, we review the relationship between protein and mRNA levels under various scenarios, such as steady state, long-term state changes, and short-term adaptation, demonstrating the complexity of gene expression regulation, especially during dynamic transitions. The spatial and temporal variations of mRNAs, as well as the local availability of resources for protein biosynthesis, strongly influence the relationship between protein levels and their coding transcripts. We further discuss the buffering of mRNA fluctuations at the level of protein concentrations. We conclude that transcript levels by themselves are not sufficient to predict protein levels in many scenarios and to thus explain genotype-phenotype relationships and that high-quality data quantifying different levels of gene expression are indispensable for the complete understanding of biological processes.

A peptide-retrieval strategy enables significant improvement of quantitative performance without compromising confidence of identification

Reliable quantification of low-abundance proteins in complex proteomes is challenging largely owing to the limited number of spectra/peptides identified. In this study we developed a straightforward method to improve the quantitative accuracy and precision of proteins by strategically retrieving the less confident peptides that were previously filtered out using the standard target-decoy search strategy. The filtered-out MS/MS spectra matched to confidently-identified proteins were recovered, and the peptide-spectrum-match FDR were re-calculated and controlled at a confident level of FDR≤1%, while protein FDR maintained at ~1%. We evaluated the performance of this strategy in both spectral count- and ion current-based methods. >60% increase of total quantified spectra/peptides was respectively achieved for analyzing a spike-in sample set and a public dataset from CPTAC. Incorporating the peptide retrieval strategy significantly improved the quantitative accuracy and precision, especially for low-abundance proteins (e.g. one-hit proteins). Moreover, the capacity of confidently discovering significantly-altered proteins was also enhanced substantially, as demonstrated with two spike-in datasets. In summary, improved quantitative performance was achieved by this peptide recovery strategy without compromising confidence of protein identification, which can be readily implemented in a broad range of quantitative proteomics techniques including label-free or labeling approaches.

SIGNIFICANCE

We hypothesize that more quantifiable spectra and peptides in a protein, even including less confident peptides, could help reduce variations and improve protein quantification. Hence the peptide retrieval strategy was developed and evaluated in two spike-in sample sets with different LC-MS/MS variations using both MS1- and MS2-based quantitative approach. The list of confidently identified proteins using the standard target-decoy search strategy was fixed and more spectra/peptides with less confidence matched to confident proteins were retrieved. However, the total peptide-spectrum-match false discovery rate (PSM FDR) after retrieval analysis was still controlled at a confident level of FDR≤1%. As expected, the penalty for occasionally incorporating incorrect peptide identifications is negligible by comparison with the improvements in quantitative performance. More quantifiable peptides, lower missing value rate, better quantitative accuracy and precision were significantly achieved for the same protein identifications by this simple strategy. This strategy is theoretically applicable for any quantitative approaches in proteomics and thereby provides more quantitative information, especially on low-abundance proteins.

Evaluation of Spectral Counting for Relative Quantitation of Proteoforms in Top-Down Proteomics

Spectral counting is a straightforward label-free quantitation strategy used in bottom-up proteomics workflows. The application of spectral counting in label-free top-down proteomics workflows can be similarly straightforward but has not been applied as widely as quantitation by chromatographic peak areas or peak intensities. In this study, we evaluate spectral counting for quantitative comparisons in label-free top-down proteomics workflows by comparison with chromatographic peak areas and intensities. We tested these quantitation approaches by spiking standard proteins into a complex protein background and comparing relative quantitation by spectral counts with normalized chromatographic peak areas and peak intensities from deconvoluted extracted ion chromatograms of the spiked proteins. Ratio estimates and statistical significance of differential abundance from each quantitation technique are evaluated against the expected ratios and each other. In this experiment, spectral counting was able to detect differential abundance of spiked proteins for expected ratios ≥2, with comparable or higher sensitivity than normalized areas and intensities. We also found that while ratio estimates using peak areas and intensities are usually more accurate, the spectral-counting-based estimates are not substantially worse. Following the evaluation and comparison of these label-free top-down quantitation strategies using spiked proteins, spectral counting, along with normalized chromatographic peak areas and intensities, were used to analyze the complex protein cargo of exosomes shed by myeloid-derived suppressor cells collected under high and low conditions of inflammation, revealing statistically significant differences in abundance for several proteoforms, including the active pro-inflammatory proteins S100A8 and S100A9.

Deciphering lymphoma pathogenesis via state-of-the-art mass spectrometry-based quantitative proteomics

Mass spectrometry-based quantitative proteomics specifically applied to comprehend the pathogenesis of lymphoma has incremental value in deciphering the heterogeneity in complex deregulated molecular mechanisms/pathways of the lymphoma entities, implementing the current diagnostic and therapeutic strategies. Essential global, targeted and functional differential proteomics analyses although still evolving, have been successfully implemented to shed light on lymphoma pathogenesis to discover and explore the role of potential lymphoma biomarkers and drug targets. This review aims to outline and appraise the present status of MS-based quantitative proteomic approaches in lymphoma research, introducing the current state-of-the-art MS-based proteomic technologies, the opportunities they offer in biological discovery in human lymphomas and the related limitation issues arising from sample preparation to data evaluation. It is a synopsis containing information obtained from recent research articles, reviews and public proteomics repositories (PRIDE). We hope that this review article will aid, assimilate and assess all the information aiming to accelerate the development and validation of diagnostic, prognostic or therapeutic targets for an improved and empowered clinical proteomics application in lymphomas in the nearby future.

Quantitative Proteomics of the E. coli Membranome

Due to their physicochemical properties, membrane protein proteomics analyses often require extensive sample preparation protocols resulting in sample loss and introducing technical variation. Several methods for membrane proteomics have been described, designed to meet the needs of specific sample types and experimental designs. Here, we present a complete membrane proteomics pipeline starting from the membrane sample preparation to the protein identification/quantification and also discuss about annotation of proteomics data. The protocol has been developed using Escherichia coli samples but is directly adaptable to other bacteria including pathogens. We describe a method for the preparation of E. coli inner membrane vesicles (IMVs) central to our pipeline. IMVs are functional membrane vesicles that can also be used for biochemical studies. Next, we propose methods for membrane protein digestion and describe alternative experimental approaches that have been previously tested in our lab. We highlight a surface proteolysis protocol for the identification of inner membrane and membrane-bound proteins. This is a simple, fast, and reproducible method for the membrane sample characterization that has been previously used for the E. coli inner membrane proteome characterization (Papanastasiou et al., 2013) and the experimental validation of E. coli membrane proteome (Orfanoudaki & Economou, 2014). It provides a reduced load on MS-time and allows for multiple repeats. Then we discuss membrane protein quantification approaches and tools that can be used for the functional annotation of identified proteins. Overall, membrane proteome quantification can be fast, simplified, and reproducible; however, optimization steps should be performed for a given sample type.

Identification of novel candidate circulating biomarkers for malignant soft tissue sarcomas: Correlation with metastatic progression

Soft tissue sarcomas (STS) are a heterogeneous group of rare tumors for which identification and validation of biological markers may improve clinical management. The fraction of low-molecular-weight (LMW) circulating proteins and fragments of proteins is a rich source of new potential biomarkers. To identify circulating biomarkers useful for STS early diagnosis and prognosis, we analyzed 53 high-grade STS sera using hydrogel core-shell nanoparticles that selectively entrap LMW proteins by size exclusion and affinity chromatography, protect them from degradation and amplify their concentration for mass spectrometry detection. Twenty-two analytes mostly involved in inflammatory and immunological response, showed a progressive increase from benign to malignant STS with a relative difference in abundance, more than 50% when compared to healthy control. 16 of these were higher in metastatic compared to non-metastatic tumors. Cox's regression analysis revealed a statistical significant association between the abundance of lactotransferrin (LTF) and complement factor H-related 5 (CFHR5) and risk of metastasis. In particular, CFHR5 was associated with the risk of metastasis. The role of circulating proteins involved in metastatic progression will be crucial for a better understanding of STS biology and patient management.

Tag-Count Analysis of Large-Scale Proteomic Data

Label-free quantitative methods are advantageous in bottom-up (shotgun) proteomics because they are robust and can easily be applied to different workflows without additional cost. Both label-based and label-free approaches are routinely applied to discovery-based proteomics experiments and are widely accepted as semiquantitative. Label-free quantitation approaches are segregated into two distinct approaches: peak-abundance-based approaches and spectral counting (SpC). Peak abundance approaches like MaxLFQ, which is integrated into the MaxQuant environment, require precursor peak alignment that is computationally intensive and cannot be routinely applied to low-resolution data. Not limited by these constraints, SpC approaches simply use the number of peptide identifications corresponding to a given protein as a measurement of protein abundance. We show here that spectral counts from multidimensional proteomic data sets have a mean-dispersion relationship that can be modeled in edgeR. Furthermore, by simulating spectral counts, we show that this approach can routinely be applied to large-scale discovery proteomics data sets to determine differential protein expression.

Mycobacterium tuberculosis Infection Manipulates the Glycosylation Machinery and the N-Glycoproteome of Human Macrophages and Their Microparticles

Tuberculosis (TB) remains a prevalent and lethal infectious disease. The glycobiology associated with Mycobacterium tuberculosis infection of frontline alveolar macrophages is still unresolved. Herein, we investigated the regulation of protein N-glycosylation in human macrophages and their secreted microparticles (MPs) used for intercellular communication upon M. tb infection. LC-MS/MS-based proteomics and glycomics were performed to monitor the regulation of glycosylation enzymes and receptors and the N-glycome in in vitro-differentiated macrophages and in isolated MPs upon M. tb infection. Infection promoted a dramatic regulation of the macrophage proteome. Most notably, significant infection-dependent down-regulation (4-26 fold) of 11 lysosomal exoglycosidases, e.g., β-galactosidase, β-hexosaminidases and α-/β-mannosidases, was observed. Relative weak infection-driven transcriptional regulation of these exoglycosidases and a stronger augmentation of the extracellular hexosaminidase activity demonstrated that the lysosome-centric changes may originate predominantly from infection-induced secretion of the lysosomal content. The macrophages showed heterogeneous N-glycan profiles and displayed significant up-regulation of complex-type glycosylation and concomitant down-regulation of paucimannosylation upon infection. Complementary intact N-glycopeptide analysis supported a subcellular-specific manipulation of the glycosylation machinery and altered glycosylation patterns of lysosomal N-glycoproteins within infected macrophages. Interestingly, the corresponding macrophage-derived MPs displayed unique N-glycome and proteome signatures supporting a preferential packaging from plasma membranes. The MPs were devoid of infection-dependent N-glycosylation signatures, but interestingly displayed increased levels of the glyco-initiating oligosaccharyltransferase complex and associated α-glucosidases that correlated with increased formation, N-glycan precursor levels and N-glycan density of infected MPs. In conclusion, this system-wide study provides new insight into the host- and pathogen-driven N-glycoproteome manipulation of macrophages in TB.

Transcriptome and proteome analyses provide insight into laticifer's defense of Euphorbia tirucalli against pests

The cytoplasm of laticifers, which are plant cells specialized for rubber production and defense against microbes and herbivores, is a latex. Although laticifers share common functions, the protein constituents of latexes are highly variable among plant species and even among organs. In this study, transcriptomic and proteomic analyses of Euphorbia tirucalli's (Euphorbiaceae) latex were conducted to determine the molecular basis of the laticifer's functions in this plant. The hybrid de novo assembly of Illumina mRNA-seq and expressed sequence tags obtained by Sanger's sequencing revealed 26,447 unigenes. A unigene similar to Arabidopsis embryo-specific protein 3 (AT5G62200), which is a PLAT domain-containing protein, and rubber elongation factor showed the highest expression levels. The proteome analysis, studied by liquid chromatography-mass spectrometry with the de novo assembled unigenes as the database, revealed 161 proteins in the latex, 107 of which were not detected in the stem. A gene ontology analysis indicated that the laticifer's proteome was enriched with proteins related to proteolysis, phosphatase, defense against various environmental stresses and lipid metabolisms. D-mannose-binding lectin, ricin (which lacked the N-terminal conserved ribosome-inactivating protein domain), chitinase and peroxidase were highly accumulated, as confirmed by two-dimensional polyacrylamide gel electrophoresis. Thus, the lectins and chitinase may be the major defensive proteins against pests, and the other defense-related proteins and transcripts detected in latex may work in coordination with them. Highly expressing unigenes with unknown functions are candidate novel defense- or rubber production-related genes.

Label-free quantitative proteomic analysis of tolerance to drought in Pisum sativum

Abiotic stresses caused by adverse environmental conditions are responsible for heavy economic losses on pea crop, being drought one of the most important abiotic constraints. Development of pea cultivars well adapted to dry conditions has been one of the major tasks in breeding programs. The increasing food requirements drive the necessity to broaden the molecular basis of tolerance to drought to develop pea cultivars well adapted to dry conditions. We have used a shotgun proteomic approach (nLC-MSMS) to study the tolerance to drought in three pea genotypes that were selected based on differences in the level of water deficit tolerance. Multivariate statistical analysis of data unraveled 367 significant differences of 700 identified when genotypes and/or treatment were compared. More than half of the significantly changed proteins belong to primary metabolism and protein regulation categories. We propose different mechanisms to cope drought in the genotypes studied. Maintenance of the primary metabolism and protein protection seems a strategy for drought tolerance. On the other hand susceptibility might be related to maintenance of the homeostatic equilibrium, a very energy consuming process. Data are available via ProteomeXchange with identifier PXD004587.

Increased expression of PDIA3 and its association with cancer cell proliferation and poor prognosis in hepatocellular carcinoma

The prognosis of hepatocellular carcinoma (HCC) is unfavorable following complete tumor resection. The aim of the present study was to identify a molecule able to predict HCC prognosis through comprehensive protein profiling and to elucidate its clinicopathological significance. Comprehensive protein profiling of HCC was performed by liquid chromatography-tandem mass spectrometry. Through the bioinformatic analysis of proteins expressed differentially in HCC and non-HCC tissues, protein disulfide-isomerase A3 (PDIA3) was identified as a candidate for the prediction of prognosis. PDIA3 expression was subsequently examined in 86 cases of HCC by immunostaining and associations between PDIA3 expression levels and clinicopathological characteristics were evaluated. The Ki-67 index and apoptotic cell death of carcinoma cells were examined by immunostaining and terminal deoxynucleotidyl transferase dUTP nick-end labeling assay in 24 cases. The results demonstrated that PDIA3 was expressed in all 86 HCC cases; 56 HCC cases (65%) exhibited high expression of PDIA3 and 30 (35%) exhibited low expression. The disease-free and overall survival times of HCC patients with high PDIA3 expression were significantly shorter than in HCC patients with low expression. Furthermore, increased expression of PDIA3 was associated with an elevated Ki-67 index, indicating increased cancer cell proliferation and a reduction in apoptotic cell death. Taken together, these results suggest that PDIA3 expression is associated with tumor proliferation and decreased apoptosis in HCC, and that increased expression of PDIA3 predicts poor prognosis. PDIA3 may therefore be a key molecule in the development of novel targeting therapies for patients with HCC.

Mass Spectrometry-Based Approaches to Understand the Molecular Basis of Memory

The central nervous system is responsible for an array of cognitive functions such as memory, learning, language, and attention. These processes tend to take place in distinct brain regions; yet, they need to be integrated to give rise to adaptive or meaningful behavior. Since cognitive processes result from underlying cellular and molecular changes, genomics and transcriptomics assays have been applied to human and animal models to understand such events. Nevertheless, genes and RNAs are not the end products of most biological functions. In order to gain further insights toward the understanding of brain processes, the field of proteomics has been of increasing importance in the past years. Advancements in liquid chromatography-tandem mass spectrometry (LC-MS/MS) have enabled the identification and quantification of thousands of proteins with high accuracy and sensitivity, fostering a revolution in the neurosciences. Herein, we review the molecular bases of explicit memory in the hippocampus. We outline the principles of mass spectrometry (MS)-based proteomics, highlighting the use of this analytical tool to study memory formation. In addition, we discuss MS-based targeted approaches as the future of protein analysis.

Comparative proteomic profiling identifies potential prognostic factors for human clear cell renal cell carcinoma

The identification of markers for disease diagnostic, prognostic, or predictive purposes will have a great effect in improving patient management. Proteomic‑based approaches for biomarker discovery are promising strategies used in cancer research. In this study, we performed quantitative proteomic analysis on four patients including clear cell renal cell carcinoma (ccRCC) and paired adjacent non‑cancerous renal tissues using label‑free quantitative proteomics and liquid chromatography‑tandem mass spectrometry (LC‑MS/MS) to identify differentially expressed proteins. Among 3,061 identified non‑redundant proteins, we found that 210 proteins were differentially expressed (83 overexpressed and 127 underexpressed) in ccRCC tissue when compared with normal kidney tissues. Two most significantly dysregulated proteins (PCK1 and SNRPF) were chosen to be confirmed by western blotting. Pathway analysis of 210 differentially expressed proteins showed that dysregulated proteins are related to many cancer‑related biological processes such as oxidative phosphorylation, glycolysis and amino acid synthetic pathways. Online survival analysis indicated the prognostic value of these dysregulated proteins. In conclusion, we identified some potential diagnostic biomarkers for ccRCC and an in‑depth understanding of their involved biological pathways may help pave the way to discover new therapeutic strategies for ccRCC.

Serum protein profiling in diffuse large B-cell lymphoma

PURPOSE

The aim of this pilot study was to conduct a nontargeted exploratory proteomics profiling analysis on sera obtained from patients diagnosed with diffuse large B-cell lymphoma (DLBCL) with the goal of identifying disease-specific biomarkers.

EXPERIMENTAL DESIGN

Sera from 87 participants (57 chemotherapy-naïve diffuse DLBCL patients, 30 controls frequency-matched by age group and World Health Organization (WHO) BMI categories) that were part of a large San Francisco Bay Area case-control study of non-Hodgkin lymphoma were analyzed by liquid chromatography combined with tandem mass spectrometry.

RESULTS

Thirty-five proteins (p-adjusted <0.05) were identified as differentially abundant between the DLBCL patients at various disease stages as compared to the controls. Of these, five proteins were randomly selected for further confirmation by ELISA: adiponectin (AdipoQ), cluster of differentiation 14 (CD14), heparin sulfate proteoglycan core protein (HSPG2), extracellular matrix 1 (ECM1), and alpha-1-antichymotrypsin (ACT). These proteins were statistically significantly elevated by 68.8, 37.0, 61.6, 68.0, and 32.0%, respectively, in DLBCL patient sera as compared to controls.

CONCLUSION AND CLINICAL RELEVANCE

These preliminary data when combined with other cancer-related data regarding these proteins warrant continued research in clinical and large prospective studies to clarify the role for these biomarkers in DLBCL pathogenesis and/or prognosis.

Differential Gel Electrophoresis (DIGE) Evaluation of Naphthoimidazoles Mode of Action: A Study in Trypanosoma cruzi Bloodstream Trypomastigotes

Background

The obligate intracellular protozoan Trypanosoma cruzi is the causative agent of Chagas disease, a neglected illness affecting millions of people in Latin America that recently entered non-endemic countries through immigration, as a consequence of globalization. The chemotherapy for this disease is based mainly on benznidazole and nifurtimox, which are very efficient nitroderivatives against the acute stage but present limited efficacy during the chronic phase. Our group has been studying the trypanocidal effects of naturally occurring quinones and their derivatives, and naphthoimidazoles derived from β-lapachone N1, N2 and N3 were the most active. To assess the molecular mechanisms of action of these compounds, we applied proteomic techniques to analyze treated bloodstream trypomastigotes, which are the clinically relevant stage of the parasite.

Methodology/Principal Findings

The approach consisted of quantification by 2D-DIGE followed by MALDI-TOF/TOF protein identification. A total of 61 differentially abundant protein spots were detected when comparing the control with each N1, N2 or N3 treatment, for 34 identified spots. Among the differentially abundant proteins were activated protein kinase C receptor, tubulin isoforms, asparagine synthetase, arginine kinase, elongation factor 2, enolase, guanine deaminase, heat shock proteins, hypothetical proteins, paraflagellar rod components, RAB GDP dissociation inhibitor, succinyl-CoA ligase, ATP synthase subunit B and methionine sulfoxide reductase.

Conclusion/Significance

Our results point to different modes of action for N1, N2 and N3, which indicate a great variety of metabolic pathways involved and allow for novel perspectives on the development of trypanocidal agents.

Trypanosoma cruzi is the etiological agent of Chagas disease, an important illness for Latin American countries that is now afflicting other continents due to the immigration of infected people. The available chemotherapy is limited to the chronic phase of the disease, being the development of novel active compounds essential, and the search for specific molecular targets for drugs in T. cruzi is necessary. In this context, our group has synthesized and screened many compounds ranging from natural to semi-synthetic naphthoquinones and derivatives on T. cruzi, displaying naphthoimidazoles N1, N2 and N3 the highest activity. Previous studies correlated phenotypic alterations by cell biology techniques as well as investigated mode of action by proteomic approaches in insect stage epimastigotes as a model. However, T. cruzi presents three morphologically distinct life stages with their own specific biological peculiarities and requirements that could be potential targets to drug intervention. Here, we evaluated the mechanism of action of N1, N2 and N3 in clinical relevant form of the parasite, bloodstream trypomastigotes, by proteomics. Our data pointed to 61 differentially abundant protein spots, being these proteins involved with cellular trafficking, protein synthesis, transduction signaling and energetic metabolism, among others, open interesting perspectives for trypanocidal strategies.

Ion Current-Based Proteomic Profiling for Understanding the Inhibitory Effect of Tumor Necrosis Factor Alpha on Myogenic Differentiation

Despite a demonstrated role for TNF-α in promoting muscle wasting and cachexia, the associated molecular mechanisms and signaling pathways of myoblast differentiation dysregulated by TNF-α remain poorly understood. This study presents well-controlled proteomic profiling as a means to investigate the mechanisms of TNF-α-regulated myogenic differentiation. Primary human muscle precursor cells (MPCs) cultured in growth medium (GM), differentiation medium (DM) to induce myogenic differentiation, and DM with 20 ng/mL of TNF-α (n = 5/group) were comparatively analyzed by an ion current-based quantitative platform consisting of reproducible sample preparation/on-pellet digestion, a long-column nano-LC separation, and ion current-based differential analysis. The inhibition of myogenic differentiation by TNF-α was confirmed by reduced formation of multinucleated myotubes and the recovered expression of altered myogenic proteins such as MYOD and myogenin during myogenic differentiation. Functional analysis and validation by immunoassay analysis suggested that the cooperation of NF-κB and STAT proteins is responsible for dysregulated differentiation in MPCs by TNF-α treatment. Increased MHC class I components such as HLA-A, HLA-B, HLA-C, and beta-2-microglobulin were also observed in cultures in DM treated with TNF-α. Interestingly, inhibition of the cholesterol biosynthesis pathway during myogenic differentiation induced by serum starvation was not recovered by TNF-α treatment, which combined with previous reports, implies that this process may be an early event of myogenesis. This finding could lay the foundation for the potential use of statins in modulating myogenesis through cholesterol, for example, in stem cell-based myocardial infarction treatment, where differentiation of myoblasts and stem cells into force-generating mature muscle cells is a key step to the therapeutic capacity. In conclusion, the landscapes of altered transcription regulators, metabolic processes, and signaling pathways in MPCs are revealed in the regulation of myogenic differentiation by TNF-α, which is valuable for myogenic cellular therapeutics.

Identification of aldolase A as a potential diagnostic biomarker for colorectal cancer based on proteomic analysis using formalin-fixed paraffin-embedded tissue

Colorectal cancer (CRC) is one of the most common cancers worldwide, and many patients are already at an advanced stage when they are diagnosed. Therefore, novel biomarkers for early detection of colorectal cancer are required. In this study, we performed a global shotgun proteomic analysis using formalin-fixed and paraffin-embedded (FFPE) CRC tissue. We identified 84 candidate proteins whose expression levels were differentially expressed in cancer and non-cancer regions. A label-free semiquantitative method based on spectral counting and gene ontology (GO) analysis led to a total of 21 candidate proteins that could potentially be detected in blood. Validation studies revealed cyclophilin A, annexin A2, and aldolase A mRNA and protein expression levels were significantly higher in cancer regions than in non-cancer regions. Moreover, an in vitro study showed that secretion of aldolase A into the culture medium was clearly suppressed in CRC cells compared to normal colon epithelium. These findings suggest that decreased aldolase A in blood may be a novel biomarker for the early detection of CRC.

The eukaryote-specific N-terminal extension of ribosomal protein S31 contributes to the assembly and function of 40S ribosomal subunits

The archaea-/eukaryote-specific 40S-ribosomal-subunit protein S31 is expressed as an ubiquitin fusion protein in eukaryotes and consists of a conserved body and a eukaryote-specific N-terminal extension. In yeast, S31 is a practically essential protein, which is required for cytoplasmic 20S pre-rRNA maturation. Here, we have studied the role of the N-terminal extension of the yeast S31 protein. We show that deletion of this extension partially impairs cell growth and 40S subunit biogenesis and confers hypersensitivity to aminoglycoside antibiotics. Moreover, the extension harbours a nuclear localization signal that promotes active nuclear import of S31, which associates with pre-ribosomal particles in the nucleus. In the absence of the extension, truncated S31 inefficiently assembles into pre-40S particles and two subpopulations of mature small subunits, one lacking and another one containing truncated S31, can be identified. Plasmid-driven overexpression of truncated S31 partially suppresses the growth and ribosome biogenesis defects but, conversely, slightly enhances the hypersensitivity to aminoglycosides. Altogether, these results indicate that the N-terminal extension facilitates the assembly of S31 into pre-40S particles and contributes to the optimal translational activity of mature 40S subunits but has only a minor role in cytoplasmic cleavage of 20S pre-rRNA at site D.

A Pair of Oviduct-Born Pickpocket Neurons Important for Egg-Laying in Drosophila melanogaster

During copulation, male Drosophila transfers Sex Peptide (SP) to females where it acts on internal sensory neurons expressing pickpocket (ppk). These neurons induce a post-mating response (PMR) that includes elevated egg-laying and refractoriness to re-mating. Exactly how ppk neurons regulate the different aspects of the PMR, however, remains unclear. Here, we identify a small subset of the ppk neurons which requires expression of a pre-mRNA splicing factor CG3542 for egg-laying, but not refractoriness to mating. We identify two CG3542-ppk expressing neurons that innervate the upper oviduct and appear to be responsible for normal egg-laying. Our results suggest specific subsets of the ppk neurons are responsible for each PMR component.

Shotgun Proteomics of Tomato Fruits: Evaluation, Optimization and Validation of Sample Preparation Methods and Mass Spectrometric Parameters

An optimized protocol was developed for shotgun proteomics of tomato fruit, which is a recalcitrant tissue due to a high percentage of sugars and secondary metabolites. A number of protein extraction and fractionation techniques were examined for optimal protein extraction from tomato fruits followed by peptide separation on nanoLCMS. Of all evaluated extraction agents, buffer saturated phenol was the most efficient. In-gel digestion [SDS-PAGE followed by separation on LCMS (GeLCMS)] of phenol-extracted sample yielded a maximal number of proteins. For in-solution digested samples, fractionation by strong anion exchange chromatography (SAX) also gave similar high proteome coverage. For shotgun proteomic profiling, optimization of mass spectrometry parameters such as automatic gain control targets (5E+05 for MS, 1E+04 for MS/MS); ion injection times (500 ms for MS, 100 ms for MS/MS); resolution of 30,000; signal threshold of 500; top N-value of 20 and fragmentation by collision-induced dissociation yielded the highest number of proteins. Validation of the above protocol in two tomato cultivars demonstrated its reproducibility, consistency, and robustness with a CV of < 10%. The protocol facilitated the detection of five-fold higher number of proteins compared to published reports in tomato fruits. The protocol outlined would be useful for high-throughput proteome analysis from tomato fruits and can be applied to other recalcitrant tissues.

Modulating the endometrial epithelial proteome and secretome in preparation for pregnancy: The role of ovarian steroid and pregnancy hormones

Dialogue between an appropriately developed embryo and hormonally-primed endometrium is essential to achieve implantation and establish pregnancy. Importantly, the point-of-first-contact between the embryo and the maternal endometrium occurs at the endometrial luminal epithelium (LE). Implantation events occur within the uterine cavity microenvironment regulated by local factors. Defects in embryo-endometrial communication likely underlie unexplained infertility; enhanced knowledge of this communication, specifically at initial maternal-fetal contact may reveal targets to improve fertility. Using a human endometrial luminal-epithelial (LE) cell line (ECC1), this targeted proteomic study reveals unique protein changes in both cellular (98% unique identifications) and secreted (96% unique identifications) proteins in the transition to the progesterone-dominated secretory (receptive) phase and subsequently to pregnancy, mediated by embryo-derived human chorionic gonadotropin (hCG). This analysis identified 157 progesterone-regulated cellular proteins, with further 193 significantly altered in response to hCG. Cellular changes were associated with metabolism, basement membrane and cell connectivity, proliferation and differentiation. Secretome analysis identified 1059 proteins; 123 significantly altered by progesterone, and 43 proteins altered by hCG, including proteins associated with cellular adhesion, extracellular-matrix organization, developmental growth, growth factor regulation, and cell signaling. Collectively, our findings reveal dynamic intracellular and secreted protein changes in the endometrium that may modulate successful establishment of pregnancy.

BIOLOGICAL SIGNIFICANCE

This study provides unique insights into the developmental biology of embryo implantation using targeted proteomics by identifying endometrial epithelial cellular and secreted protein changes in response to ovarian steroid hormones and pregnancy hormones that are essential for receptivity and implantation.

A multi-model statistical approach for proteomic spectral count quantitation

The rapid development of mass spectrometry (MS) technologies has solidified shotgun proteomics as the most powerful analytical platform for large-scale proteome interrogation. The ability to map and determine differential expression profiles of the entire proteome is the ultimate goal of shotgun proteomics. Label-free quantitation has proven to be a valid approach for discovery shotgun proteomics, especially when sample is limited. Label-free spectral count quantitation is an approach analogous to RNA sequencing whereby count data is used to determine differential expression. Here we show that statistical approaches developed to evaluate differential expression in RNA sequencing experiments can be applied to detect differential protein expression in label-free discovery proteomics. This approach, termed MultiSpec, utilizes open-source statistical platforms; namely edgeR, DESeq and baySeq, to statistically select protein candidates for further investigation. Furthermore, to remove bias associated with a single statistical approach a single ranked list of differentially expressed proteins is assembled by comparing edgeR and DESeq q-values directly with the false discovery rate (FDR) calculated by baySeq. This statistical approach is then extended when applied to spectral count data derived from multiple proteomic pipelines. The individual statistical results from multiple proteomic pipelines are integrated and cross-validated by means of collapsing protein groups.

BIOLOGICAL SIGNIFICANCE

Spectral count data from shotgun proteomics experiments is semi-quantitative and semi-random, yet a robust way to estimate protein concentration. Tag-count approaches are routinely used to analyze RNA sequencing data sets. This approach, termed MultiSpec, utilizes multiple tag-count based statistical tests to determine differential protein expression from spectral counts. The statistical results from these tag-count approaches are combined in order to reach a final MultiSpec q-value to re-rank protein candidates. This re-ranking procedure is completed to remove bias associated with a single approach in order to better understand the true proteomic differences driving the biology in question. The MultiSpec approach can be extended to multiple proteomic pipelines. In such an instance, MultiSpec statistical results are integrated by collapsing protein groups across proteomic pipelines to provide a single ranked list of differentially expressed proteins. This integration mechanism is seamlessly integrated with the statistical analysis and provides the means to cross-validate protein inferences from multiple proteomic pipelines.

Plasma-derived Extracellular Vesicles Contain Predictive Biomarkers and Potential Therapeutic Targets for Myocardial Ischemic (MI) Injury

Myocardial infarction (MI) triggers a potent inflammatory response via the release of circulatory mediators, including extracellular vesicles (EVs) by damaged cardiac cells, necessary for myocardial healing. Timely repression of inflammatory response are critical to prevent and minimize cardiac tissue injuries, nonetheless, progression in this aspect remains challenging. The ability of EVs to trigger a functional response upon delivery of carried bioactive cargos, have made them clinically attractive diagnostic biomarkers and vectors for therapeutic interventions. Using label-free quantitative proteomics approach, we compared the protein cargo of plasma EVs between patients with MI and from patients with stable angina (NMI). We report, for the first time, the proteomics profiling on 252 EV proteins that were modulated with >1.2-fold after MI. We identified six up-regulated biomarkers with potential for clinical applications; these reflected post-infarct pathways of complement activation (Complement C1q subcomponent subunit A (C1QA), 3.23-fold change, p = 0.012; Complement C5 (C5), 1.27-fold change, p = 0.087), lipoprotein metabolism (Apoliporotein D (APOD), 1.86-fold change, p = 0.033; Apolipoprotein C-III (APOCC3), 2.63-fold change, p = 0.029) and platelet activation (Platelet glycoprotein Ib alpha chain (GP1BA), 9.18-fold change, p < 0.0001; Platelet basic protein (PPBP), 4.72-fold change, p = 0.027). The data have been deposited to the ProteomeXchange with identifier PXD002950. This novel biomarker panel was validated in 43 patients using antibody-based assays (C1QA (p = 0.005); C5 (p = 0.0047), APOD (p = 0.0267); APOC3 (p = 0.0064); GP1BA (p = 0.0031); PPBP (p = 0.0465)). We further present that EV-derived fibrinogen components were paradoxically down-regulated in MI, suggesting that a compensatory mechanism may suppress post-infarct coagulation pathways, indicating potential for therapeutic targeting of this mechanism in MI. Taken together, these data demonstrated that plasma EVs contain novel diagnostic biomarkers and therapeutic targets that can be further developed for clinical use to benefit patients with coronary artery diseases (CADs).

Single-cell-type quantitative proteomic and ionomic analysis of epidermal bladder cells from the halophyte model plant Mesembryanthemum crystallinum to identify salt-responsive proteins

BACKGROUND

Epidermal bladder cells (EBC) are large single-celled, specialized, and modified trichomes found on the aerial parts of the halophyte Mesembryanthemum crystallinum. Recent development of a simple but high throughput technique to extract the contents from these cells has provided an opportunity to conduct detailed single-cell-type analyses of their molecular characteristics at high resolution to gain insight into the role of these cells in the salt tolerance of the plant.

RESULTS

In this study, we carry out large-scale complementary quantitative proteomic studies using both a label (DIGE) and label-free (GeLC-MS) approach to identify salt-responsive proteins in the EBC extract. Additionally we perform an ionomics analysis (ICP-MS) to follow changes in the amounts of 27 different elements. Using these methods, we were able to identify 54 proteins and nine elements that showed statistically significant changes in the EBC from salt-treated plants. GO enrichment analysis identified a large number of transport proteins but also proteins involved in photosynthesis, primary metabolism and Crassulacean acid metabolism (CAM). Validation of results by western blot, confocal microscopy and enzyme analysis helped to strengthen findings and further our understanding into the role of these specialized cells. As expected EBC accumulated large quantities of sodium, however, the most abundant element was chloride suggesting the sequestration of this ion into the EBC vacuole is just as important for salt tolerance.

CONCLUSIONS

This single-cell type omics approach shows that epidermal bladder cells of M. crystallinum are metabolically active modified trichomes, with primary metabolism supporting cell growth, ion accumulation, compatible solute synthesis and CAM. Data are available via ProteomeXchange with identifier PXD004045.

Vulnerability of newly synthesized proteins to proteostasis stress

The capacity of the cell to produce, fold and degrade proteins relies on components of the proteostasis network. Multiple types of insults can impose a burden on this network, causing protein misfolding. Using thermal stress, a classic example of acute proteostatic stress, we demonstrate that ∼5-10% of the soluble cytosolic and nuclear proteome in human HEK293 cells is vulnerable to misfolding when proteostatic function is overwhelmed. Inhibiting new protein synthesis for 30 min prior to heat-shock dramatically reduced the amount of heat-stress induced polyubiquitylation, and reduced the misfolding of proteins identified as vulnerable to thermal stress. Following prior studies in C. elegans in which mutant huntingtin (Q103) expression was shown to cause the secondary misfolding of cytosolic proteins, we also demonstrate that mutant huntingtin causes similar 'secondary' misfolding in human cells. Similar to thermal stress, inhibiting new protein synthesis reduced the impact of mutant huntingtin on proteostatic function. These findings suggest that newly made proteins are vulnerable to misfolding when proteostasis is disrupted by insults such as thermal stress and mutant protein aggregation.

Extracellular vesicle proteomes reflect developmental phases of Bacillus subtilis

BACKGROUND

Extracellular vesicles (EV) are spherical membrane-bound vesicles with nano-scale diameters, which are shed to the extracellular region by most eukaryotic and prokaryotic cells. Bacterial EV are proposed to contribute to intercellular communication, bacterial survival and human pathogenesis as a novel secretion system. EV have been characterized from many Gram-negative species and, more recently, from several vegetative Gram-positive bacteria. Further characterization of EV and their molecular cargos will contribute to understanding bacterial physiology and to developing therapeutic approaches.

RESULTS

Bacillus subtilis were observed to release EV to a similar extent during sporulation as during the vegetative growth phase. However, the two vesicular cargos show qualitatively and quantitatively different proteomes. Among 193 total proteins identified across both samples, 61 were shown to be significantly more abundant in EV shed by sporulating cells, with (log) ratio of spectral counts RSC > 1 and Fisher-exact test FDR < 5 %. Sixty-two proteins were found to be significantly more abundant in EV shed by vegetative cells. Membrane fusion was shown to take place between these EVs and Gram-positive cells.

CONCLUSION

Biogenesis of EV is a continuous process over the entire life cycle of this sporulating bacterium. The formation of EV during sporulation is strongly supported by the delineation of protein content that differs from the proteome of EV formed by vegetative spores.

Integrative Omics Analysis Reveals Post-Transcriptionally Enhanced Protective Host Response in Colorectal Cancers with Microsatellite Instability

Microsatellite instability (MSI) is a frequent and clinically relevant molecular phenotype in colorectal cancer. MSI cancers have favorable survival compared with microsatellite stable cancers (MSS), possibly due to the pronounced tumor-infiltrating lymphocytes observed in MSI cancers. Consistent with the strong immune response that MSI cancers trigger in the host, previous transcriptome expression studies have identified mRNA signatures characteristic of immune response in MSI cancers. However, proteomics features of MSI cancers and the extent to which the mRNA signatures are reflected at the protein level remain largely unknown. Here, we performed a comprehensive comparison of global proteomics profiles between MSI and MSS colorectal cancers in The Cancer Genome Atlas (TCGA) cohort. We found that protein signatures of MSI are also associated with increased immunogenicity. To reliably quantify post-transcription regulation in MSI cancers, we developed a resampling-based regression method by integrative modeling of transcriptomics and proteomics data sets. Compared with the popular simple method, which detects post-transcriptional regulation by either identifying genes differentially expressed at the mRNA level but not at the protein level or vice versa, our method provided a quantitative, more sensitive, and accurate way to identify genes subject to differential post-transcriptional regulation. With this method, we demonstrated that post-transcriptional regulation, coordinating protein expression with key players, initiates de novo and enhances protective host response in MSI cancers.

Tetramer-organizing polyproline-rich peptides differ in CHO cell-expressed and plasma-derived human butyrylcholinesterase tetramers

Tetrameric butyrylcholinesterase (BChE) in human plasma is the product of multiple genes, namely one BCHE gene on chromosome 3q26.1 and multiple genes that encode polyproline-rich peptides. The function of the polyproline-rich peptides is to assemble BChE into tetramers. CHO cells transfected with human BChE cDNA express BChE monomers and dimers, but only low quantities of tetramers. Our goal was to identify the polyproline-rich peptides in CHO-cell derived human BChE tetramers. CHO cell-produced human BChE tetramers were purified from serum-free culture medium. Peptides embedded in the tetramerization domain were released from BChE tetramers by boiling and identified by liquid chromatography-tandem mass spectrometry. A total of 270 proline-rich peptides were sequenced, ranging in size from 6-41 residues. The peptides originated from 60 different proteins that reside in multiple cell compartments including the nucleus, cytoplasm, and endoplasmic reticulum. No single protein was the source of the polyproline-rich peptides in CHO cell-expressed human BChE tetramers. In contrast, 70% of the tetramer-organizing peptides in plasma-derived BChE tetramers originate from lamellipodin. No protein source was identified for polyproline peptides containing up to 41 consecutive proline residues. In conclusion, the use of polyproline-rich peptides as a tetramerization motif is documented only for the cholinesterases, but is expected to serve other tetrameric proteins as well. The CHO cell data suggest that the BChE tetramer-organizing peptide can arise from a variety of proteins.

A beacon of hope in stroke therapy-Blockade of pathologically activated cellular events in excitotoxic neuronal death as potential neuroprotective strategies

Excitotoxicity, a pathological process caused by over-stimulation of ionotropic glutamate receptors, is a major cause of neuronal loss in acute and chronic neurological conditions such as ischaemic stroke, Alzheimer's and Huntington's diseases. Effective neuroprotective drugs to reduce excitotoxic neuronal loss in patients suffering from these neurological conditions are urgently needed. One avenue to achieve this goal is to clearly define the intracellular events mediating the neurotoxic signals originating from the over-stimulated glutamate receptors in neurons. In this review, we first focus on the key cellular events directing neuronal death but not involved in normal physiological processes in the neurotoxic signalling pathways. These events, referred to as pathologically activated events, are potential targets for the development of neuroprotectant therapeutics. Inhibitors blocking some of the known pathologically activated cellular events have been proven to be effective in reducing stroke-induced brain damage in animal models. Notable examples are inhibitors suppressing the ion channel activity of neurotoxic glutamate receptors and those disrupting interactions of specific cellular proteins occurring only in neurons undergoing excitotoxic cell death. Among them, Tat-NR2B9c and memantine are clinically effective in reducing brain damage caused by some acute and chronic neurological conditions. Our second focus is evaluation of the suitability of the other inhibitors for use as neuroprotective therapeutics. We also discuss the experimental approaches suitable for bridging our knowledge gap in our current understanding of the excitotoxic signalling mechanism in neurons and discovery of new pathologically activated cellular events as potential targets for neuroprotection.

The Distribution of Prion Protein Allotypes Differs Between Sporadic and Iatrogenic Creutzfeldt-Jakob Disease Patients

Sporadic Creutzfeldt-Jakob disease (sCJD) is the most prevalent of the human prion diseases, which are fatal and transmissible neurodegenerative diseases caused by the infectious prion protein (PrP^Sc). The origin of sCJD is unknown, although the initiating event is thought to be the stochastic misfolding of endogenous prion protein (PrP^C) into infectious PrP^Sc. By contrast, human growth hormone-associated cases of iatrogenic CJD (iCJD) in the United Kingdom (UK) are associated with exposure to an exogenous source of PrP^Sc. In both forms of CJD, heterozygosity at residue 129 for methionine (M) or valine (V) in the prion protein gene may affect disease phenotype, onset and progression. However, the relative contribution of each PrP^C allotype to PrP^Sc in heterozygous cases of CJD is unknown. Using mass spectrometry, we determined that the relative abundance of PrP^Sc with M or V at residue 129 in brain specimens from MV cases of sCJD was highly variable. This result is consistent with PrP^C containing an M or V at residue 129 having a similar propensity to misfold into PrP^Sc thus causing sCJD. By contrast, PrP^Sc with V at residue 129 predominated in the majority of the UK human growth hormone associated iCJD cases, consistent with exposure to infectious PrP^Sc containing V at residue 129. In both types of CJD, the PrP^Sc allotype ratio had no correlation with CJD type, age at clinical onset, or disease duration. Therefore, factors other than PrP^Sc allotype abundance must influence the clinical progression and phenotype of heterozygous cases of CJD.

In Creutzfeldt-Jakob disease (CJD), heterozygosity at residue 129 for methionine or valine in normal prion protein may affect disease phenotype, onset and progression. However, the relative contribution of each prion protein allotype to the infectious, disease associated form of prion protein (PrP^Sc) is unknown. Here we report the novel observation that in heterozygous cases of sporadic CJD the PrP^Sc allotype ratio is highly variable. This case-by-case variability is consistent with the origin of sporadic CJD being the spontaneous, but random, misfolding of either host prion protein allotype into infectious PrP^Sc. By contrast, in heterozygous cases of iatrogenic CJD in the United Kingdom resulting from exposure to contaminated human growth hormone, the PrP^Sc allotype ratio is much more homogeneous and consistent with exposure to infectious PrP^Sc containing valine at residue 129. Surprisingly, the PrP^Sc allotype ratio did not correlate with disease onset or duration in either disease type. Thus, factors other than PrP^Sc allotype ratio likely influence the clinical progression of heterozygous cases of CJD. Moreover, our results suggest that the ratio of methionine to valine in PrP^Sc may be a means of determining the origin of prion infection.

Methods and applications of absolute protein quantification in microbial systems

In the last years the scientific community faced an increased need to provide high-quality data on the concentration of single proteins within a cell. Especially against the background of the fast evolving field of systems biology this does not only apply for a few proteins but preferably for the whole proteome of the organism. Therefore there has been a rapid development from pure identification of proteins via characterization of changes between different conditions by relative protein quantification towards determination of absolute protein amounts for hundreds of protein species in a cell. This review aims for discussion of different small-scale and large-scale approaches for absolute protein quantification in bacterial cells to picture biological processes and explore life in deeper detail. The presented advantages and limitations of various methods may provide interested researchers help to appraise available methods, select the most appropriate technique and avoid common pitfalls during determination of protein concentration in a complex sample.

Advances in mass spectrometry-based clinical biomarker discovery

The greatest unmet needs in biomarker discovery are those discoveries that lead to the development of clinical diagnostic tests. These clinical diagnostic tests can provide early intervention when a patient would present otherwise healthy (e.g., cancer or cardiovascular disease) and aid clinical decision making with improved clinical outcomes. The past two decades have seen significant technological improvements in the analytical capabilities of mass spectrometers. Mass spectrometers are unique in that they can directly analyze any biological molecule susceptible to ionization. The biological studies of human metabolites and proteins using contemporary mass spectrometry technology (metabolomics and proteomics, respectively) has been ongoing for over a decade. Some of these studies have resulted in exciting insights into human biology. However, relatively few biomarkers have been translated into clinical tests. This review will discuss some key technological developments that have occurred over this time with an emphasis on technologies that will create new avenues for biomarker discovery.

Proteome Dynamics of the Specialist Oxalate Degrader Oxalobacter formigenes

Oxalobacter formigenes is a unique intestinal organism that relies on oxalate degradation to meet most of its energy and carbon needs. A lack of colonization is a risk factor for calcium oxalate kidney stone disease. The release of the genome sequence of O. formigenes has provided an opportunity to increase our understanding of the biology of O. formigenes. This study used mass spectrometry based shotgun proteomics to examine changes in protein levels associated with the transition of growth from log to stationary phase. Of the 1867 unique protein coding genes in the genome of O. formigenes strain OxCC13, 1822 proteins were detected, which is at the lower end of the range of 1500–7500 proteins found in free-living bacteria. From the protein datasets presented here it is clear that O. formigenes contains a repertoire of metabolic pathways expected of an intestinal microbe that permit it to survive and adapt to new environments. Although further experimental testing is needed to confirm the physiological and regulatory processes that mediate adaptation with nutrient shifts, the O. formigenes protein datasets presented here can be used as a reference for studying proteome dynamics under different conditions and have significant potential for hypothesis development.

Quantitative Analysis of Cancer Metabolism: From pSIRM to MFA

Metabolic reprogramming is a required step during oncogenesis and essential for cellular proliferation. It is triggered by activation of oncogenes and loss of tumor suppressor genes. Beside the combinatorial events leading to cancer, common changes within the central metabolism are reported. Increase of glycolysis and subsequent lactic acid formation has been a focus of cancer metabolism research for almost a century. With the improvements of bioanalytical techniques within the last decades, a more detailed analysis of metabolism is possible and recent studies demonstrate a wide range of metabolic rearrangements in various cancer types. However, a systematic and mechanistic understanding is missing thus far. Therefore, analytical and computational tools have to be developed allowing for a dynamic and quantitative analysis of cancer metabolism. In this chapter, we outline the application of pulsed stable isotope resolved metabolomics (pSIRM) and describe the interface toward computational analysis of metabolism.

Computational Methods in Mass Spectrometry-Based Proteomics

This chapter introduces computational methods used in mass spectrometry-based proteomics, including those for addressing the critical problems such as peptide identification and protein inference, peptide and protein quantification, characterization of posttranslational modifications (PTMs), and data-independent acquisitions (DIA). The chapter concludes with emerging applications of proteomic techniques, such as metaproteomics, glycoproteomics, and proteogenomics.

Label-Free Quantitative Proteomics in Yeast

Label-free bottom-up shotgun MS-based proteomics is an extremely powerful and simple tool to provide high quality quantitative analyses of the yeast proteome with only microgram amounts of total protein. Although the experimental design of this approach is rather straightforward and does not require the modification of growth conditions, proteins or peptides, several factors must be taken into account to benefit fully from the power of this method. Key factors include the choice of an appropriate method for the preparation of protein extracts, careful evaluation of the instrument design and available analytical capabilities, the choice of the quantification method (intensity-based vs. spectral count), and the proper manipulation of the selected quantification algorithm. The elaboration of this robust workflow for data acquisition, processing, and analysis provides unprecedented insight into the dynamics of the yeast proteome.

Reproducibility of Differential Proteomic Technologies in CPTAC Fractionated Xenografts

The NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) employed a pair of reference xenograft proteomes for initial platform validation and ongoing quality control of its data collection for The Cancer Genome Atlas (TCGA) tumors. These two xenografts, representing basal and luminal-B human breast cancer, were fractionated and analyzed on six mass spectrometers in a total of 46 replicates divided between iTRAQ and label-free technologies, spanning a total of 1095 LC-MS/MS experiments. These data represent a unique opportunity to evaluate the stability of proteomic differentiation by mass spectrometry over many months of time for individual instruments or across instruments running dissimilar workflows. We evaluated iTRAQ reporter ions, label-free spectral counts, and label-free extracted ion chromatograms as strategies for data interpretation (source code is available from http://homepages.uc.edu/~wang2x7/Research.htm ). From these assessments, we found that differential genes from a single replicate were confirmed by other replicates on the same instrument from 61 to 93% of the time. When comparing across different instruments and quantitative technologies, using multiple replicates, differential genes were reproduced by other data sets from 67 to 99% of the time. Projecting gene differences to biological pathways and networks increased the degree of similarity. These overlaps send an encouraging message about the maturity of technologies for proteomic differentiation.

Simulation of the Protein-Shedding Kinetics of a Fully Vascularized Tumor

Circulating biomarkers are of significant interest for cancer detection and treatment personalization. However, the biophysical processes that determine how proteins are shed from cancer cells or their microenvironment, diffuse through tissue, enter blood vasculature, and persist in circulation remain poorly understood. Since approaches primarily focused on experimental evaluation are incapable of measuring the shedding and persistence for every possible marker candidate, we propose an interdisciplinary computational/experimental approach that includes computational modeling of tumor tissue heterogeneity. The model implements protein production, transport, and shedding based on tumor vascularization, cell proliferation, hypoxia, and necrosis, thus quantitatively relating the tumor and circulating proteomes. The results highlight the dynamics of shedding as a function of protein diffusivity and production. Linking the simulated tumor parameters to clinical tumor and vascularization measurements could potentially enable this approach to reveal the tumor-specific conditions based on the protein detected in circulation and thus help to more accurately manage cancer diagnosis and treatment.

A protocol for exosome isolation and characterization: evaluation of ultracentrifugation, density-gradient separation, and immunoaffinity capture methods

Exosomes are 40-150 nm extracellular vesicles that are released from a multitude of cell types, and perform diverse cellular functions including intercellular communication, antigen presentation, and transfer of tumorigenic proteins, mRNA and miRNA. Exosomes are important regulators of the cellular niche, and their altered characteristics in many diseases, such as cancer, suggest their importance for diagnostic and therapeutic applications, and as drug delivery vehicles. Exosomes have been purified from biological fluids and in vitro cell cultures using a variety of strategies and techniques. In this chapter, we reveal the protocol and key insights into the isolation, purification and characterization of exosomes, distinct from shed microvesicles and apoptotic blebs. Using the colorectal cancer cell line LIM1863 as a cell model, a comprehensive evaluation of exosome isolation methods including ultracentrifugation (UC-Exos), OptiPrep™ density-based separation (DG-Exos), and immunoaffinity capture using anti-EpCAM-coated magnetic beads (IAC-Exos) were examined. All exosome isolation methodologies contained 40-150 nm vesicles based on electron microscopy, and positive for exosome markers (Alix, TSG101, HSP70) based on immunoblotting. This protocol employed a proteomic profiling approach to characterize the protein composition of exosomes, and label-free spectral counting to evaluate the effectiveness of each method in exosome isolation. Based on the number of MS/MS spectra identified for exosome markers and proteins associated with their biogenesis, trafficking, and release, IAC-Exos was shown to be the most effective method to isolate exosomes. However, the use of density-based separation (DG-Exos) provides significant advantages for exosome isolation when the use of immunoaffinity capture is limited (due to antibody availability and suitability of exosome markers).