Showing papers in "Proteome in 2013"

Comparative and Quantitative Global Proteomics Approaches: An Overview

Abstract: Proteomics became a key tool for the study of biological systems. The comparison between two different physiological states allows unravelling the cellular and molecular mechanisms involved in a biological process. Proteomics can confirm the presence of proteins suggested by their mRNA content and provides a direct measure of the quantity present in a cell. Global and targeted proteomics strategies can be applied. Targeted proteomics strategies limit the number of features that will be monitored and then optimise the methods to obtain the highest sensitivity and throughput for a huge amount of samples. The advantage of global proteomics strategies is that no hypothesis is required, other than a measurable difference in one or more protein species between the samples. Global proteomics methods attempt to separate quantify and identify all the proteins from a given sample. This review highlights only the different techniques of separation and quantification of proteins and peptides, in view of a comparative and quantitative global proteomics analysis. The in-gel and off-gel quantification of proteins will be discussed as well as the corresponding mass spectrometry technology. The overview is focused on the widespread techniques while keeping in mind that each approach is modular and often recovers the other.

Exosomal Proteome Profiling: A Potential Multi-Marker Cellular Phenotyping Tool to Characterize Hypoxia-Induced Radiation Resistance in Breast Cancer.

Abstract: Radiation and drug resistance are significant challenges in the treatment of locally advanced, recurrent and metastatic breast cancer that contribute to mortality. Clinically, radiotherapy requires oxygen to generate cytotoxic free radicals that cause DNA damage and allow that damage to become fixed in the genome rather than repaired. However, approximately 40% of all breast cancers have hypoxic tumor microenvironments that render cancer cells significantly more resistant to irradiation. Hypoxic stimuli trigger changes in the cell death/survival pathway that lead to increased cellular radiation resistance. As a result, the development of noninvasive strategies to assess tumor hypoxia in breast cancer has recently received considerable attention. Exosomes are secreted nanovesicles that have roles in paracrine signaling during breast tumor progression, including tumor-stromal interactions, activation of proliferative pathways and immunosuppression. The recent development of protocols to isolate and purify exosomes, as well as advances in mass spectrometry-based proteomics have facilitated the comprehensive analysis of exosome content and function. Using these tools, studies have demonstrated that the proteome profiles of tumor-derived exosomes are indicative of the oxygenation status of patient tumors. They have also demonstrated that exosome signaling pathways are potentially targetable drivers of hypoxia-dependent intercellular signaling during tumorigenesis. This article provides an overview of how proteomic tools can be effectively used to characterize exosomes and elucidate fundamental signaling pathways and survival mechanisms underlying hypoxia-mediated radiation resistance in breast cancer.

Impact of Solar Radiation on Gene Expression in Bacteria

Abstract: Microorganisms often regulate their gene expression at the level of transcription and/or translation in response to solar radiation. In this review, we present the use of both transcriptomics and proteomics to advance knowledge in the field of bacterial response to damaging radiation. Those studies pertain to diverse application areas such as fundamental microbiology, water treatment, microbial ecology and astrobiology. Even though it has been demonstrated that mRNA abundance is not always consistent with the protein regulation, we present here an exhaustive review on how bacteria regulate their gene expression at both transcription and translation levels to enable biomarkers identification and comparison of gene regulation from one bacterial species to another.

Effect of External Electric Field Stress on Gliadin Protein Conformation

Abstract: A molecular dynamic (MD) modeling approach was applied to evaluate the effect of external electric field on gliadin protein structure and surface properties. Static electric field strengths of 0.001 V/nm and 0.002 V/nm induced conformational changes in the protein but had no significant effect on its surface properties. The study of hydrogen bond evolution during the course of simulation revealed that the root mean square deviation, radius of gyration and secondary structure formation, all depend significantly on the number hydrogen bonds formed. This study demonstrated that it is necessary to gain insight into protein dynamics under external electric field stress, in order to develop the novel food processing techniques that can be potentially used to reduce or eradicate food allergens.

Quantitative Analysis of the Human Milk Whey Proteome Reveals Developing Milk and Mammary-Gland Functions across the First Year of Lactation

Abstract: In-depth understanding of the changing functions of human milk (HM) proteins and the corresponding physiological adaptions of the lactating mammary gland has been inhibited by incomplete knowledge of the HM proteome. We analyzed the HM whey proteome (n = 10 women with samples at 1 week and 1, 3, 6, 9 and 12 months) using a quantitative proteomic approach. One thousand three hundred and thirty three proteins were identified with 615 being quantified. Principal component analysis revealed a transition in the HM whey proteome-throughout the first year of lactation. Abundance changes in IgG, sIgA and sIgM display distinct features during the first year. Complement components and other acute-phase proteins are generally at higher levels in early lactation. Proteomic analysis further suggests that the sources of milk fatty acids (FA) shift from more direct blood influx to more de novo mammary synthesis over lactation. The abundances of the majority of glycoproteins decline over lactation, which is consistent with increased enzyme expression in glycoprotein degradation and decreased enzyme expression in glycoprotein synthesis. Cellular detoxification machinery may be transformed as well, thereby accommodating increased metabolic activities in late lactation. The multiple developing functions of HM proteins and the corresponding mammary adaption become more apparent from this study.

Label-free LC-MS profiling of skeletal muscle reveals heart-type fatty acid binding protein as a candidate biomarker of aerobic capacity

Abstract: Two-dimensional gel electrophoresis provides robust comparative analysis of skeletal muscle, but this technique is laborious and limited by its inability to resolve all proteins. In contrast, orthogonal separation by SDS-PAGE and reverse-phase liquid chromatography (RPLC) coupled to mass spectrometry (MS) affords deep mining of the muscle proteome, but differential analysis between samples is challenging due to the greater level of fractionation and the complexities of quantifying proteins based on the abundances of their tryptic peptides. Here we report simple, semi-automated and time efficient (i.e., 3 h per sample) proteome profiling of skeletal muscle by 1-dimensional RPLC electrospray ionisation tandem MS. Solei were analysed from rats (n = 5, in each group) bred as either high- or low-capacity runners (HCR and LCR, respectively) that exhibited a 6.4-fold difference (1,625 ± 112 m vs. 252 ± 43 m, p < 0.0001) in running capacity during a standardized treadmill test. Soluble muscle proteins were extracted, digested with trypsin and individual biological replicates (50 ng of tryptic peptides) subjected to LC-MS profiling. Proteins were identified by triplicate LC-MS/MS analysis of a pooled sample of each biological replicate. Differential expression profiling was performed on relative abundances (RA) of parent ions, which spanned three orders of magnitude. In total, 207 proteins were analysed, which encompassed almost all enzymes of the major metabolic pathways in skeletal muscle. The most abundant protein detected was type I myosin heavy chain (RA = 5,843 ± 897) and the least abundant protein detected was heat shock 70 kDa protein (RA = 2 ± 0.5). Sixteen proteins were significantly (p < 0.05) more abundant in HCR muscle and hierarchal clustering of the profiling data highlighted two protein subgroups, which encompassed proteins associated with either the respiratory chain or fatty acid oxidation. Heart-type fatty acid binding protein (FABPH) was 1.54-fold (p = 0.0064) more abundant in HCR than LCR soleus. This discovery was verified using selective reaction monitoring (SRM) of the y5 ion (551.21 m/z) of the doubly-charged peptide SLGVGFATR (454.19 m/z) of residues 23–31 of FABPH. SRM was conducted on technical replicates of each biological sample and exhibited a coefficient of variation of 20%. The abundance of FABPH measured by SRM was 2.84-fold greater (p = 0.0095) in HCR muscle. In addition, SRM of FABPH was performed in vastus lateralis samples of young and elderly humans with different habitual activity levels (collected during a previous study) finding FABPH abundance was 2.23-fold greater (p = 0.0396) in endurance-trained individuals regardless of differences in age. In summary, our findings in HCR/LCR rats provide protein-level confirmation for earlier transcriptome profiling work and show LC-MS is a viable means of profiling the abundance of almost all major metabolic enzymes of skeletal muscle in a highly parallel manner. Moreover, our approach is relatively more time efficient than techniques relying on orthogonal separations, and we demonstrate LC-MS profiling of the HCR/LCR selection model was able to highlight biomarkers that also exhibit differences in trained and untrained human muscle.

Proteomic Workflows for Biomarker Identification Using Mass Spectrometry - Technical and Statistical Considerations during Initial Discovery.

Abstract: Identification of biomarkers capable of differentiating between pathophysiological states of an individual is a laudable goal in the field of proteomics. Protein biomarker discovery generally employs high throughput sample characterization by mass spectrometry (MS), being capable of identifying and quantifying thousands of proteins per sample. While MS-based technologies have rapidly matured, the identification of truly informative biomarkers remains elusive, with only a handful of clinically applicable tests stemming from proteomic workflows. This underlying lack of progress is attributed in large part to erroneous experimental design, biased sample handling, as well as improper statistical analysis of the resulting data. This review will discuss in detail the importance of experimental design and provide some insight into the overall workflow required for biomarker identification experiments. Proper balance between the degree of biological vs. technical replication is required for confident biomarker identification.

Shared and Unique Proteins in Human, Mouse and Rat Saliva Proteomes: Footprints of Functional Adaptation

Abstract: The overall goal of our study was to compare the proteins found in the saliva proteomes of three mammals: human, mouse and rat. Our first objective was to compare two human proteomes with very different analysis depths. The 89 shared proteins in this comparison apparently represent a core of highly-expressed human salivary proteins. Of the proteins unique to each proteome, one-half to 2/3 lack signal peptides and probably are contaminants instead of less highly-represented salivary proteins. We recently published the first rodent saliva proteomes with salivas collected from the genome mouse (C57BL/6) and the genome rat (BN/SsNHsd/Mcwi). Our second objective was to compare the proteins in the human proteome with those we identified in the genome mouse and rat to determine those common to all three mammals as well as the specialized rodent subset. We also identified proteins unique to each of the three mammals because differences in the secreted protein constitutions can provide clues to differences in the evolutionary adaptation of the secretions in the three different mammals.

Serum Proteome Analysis for Profiling Predictive Protein Markers Associated with the Severity of Skin Lesions Induced by Ionizing Radiation.

Abstract: The finding of new diagnostic and prognostic markers of local radiation injury, and particularly of the cutaneous radiation syndrome, is crucial for its medical management, in the case of both accidental exposure and radiotherapy side effects. Especially, a fast high-throughput method is still needed for triage of people accidentally exposed to ionizing radiation. In this study, we investigated the impact of localized irradiation of the skin on the early alteration of the serum proteome of mice in an effort to discover markers associated with the exposure and severity of impending damage. Using two different large-scale quantitative proteomic approaches, 2D-DIGE-MS and SELDI-TOF-MS, we performed global analyses of serum proteins collected in the clinical latency phase (days 3 and 7) from non-irradiated and locally irradiated mice exposed to high doses of 20, 40 and 80 Gy which will develop respectively erythema, moist desquamation and necrosis. Unsupervised and supervised multivariate statistical analyses (principal component analysis, partial-least square discriminant analysis and Random Forest analysis) using 2D-DIGE quantitative protein data allowed us to discriminate early between non-irradiated and irradiated animals, and between uninjured/slightly injured animals and animals that will develop severe lesions. On the other hand, despite a high number of animal replicates, PLS-DA and Random Forest analyses of SELDI-TOF-MS data failed to reveal sets of MS peaks able to discriminate between the different groups of animals. Our results show that, unlike SELDI-TOF-MS, the 2D-DIGE approach remains a powerful and promising method for the discovery of sets of proteins that could be used for the development of clinical tests for triage and the prognosis of the severity of radiation-induced skin lesions. We propose a list of 15 proteins which constitutes a set of candidate proteins for triage and prognosis of skin lesion outcomes.

PAPE (Prefractionation-Assisted Phosphoprotein Enrichment): A Novel Approach for Phosphoproteomic Analysis of Green Tissues from Plants

Abstract: Phosphorylation is an important post-translational protein modification with regulatory roles in diverse cellular signaling pathways. Despite recent advances in mass spectrometry, the detection of phosphoproteins involved in signaling is still challenging, as protein phosphorylation is typically transient and/or occurs at low levels. In green plant tissues, the presence of highly abundant proteins, such as the subunits of the RuBisCO complex, further complicates phosphoprotein analysis. Here, we describe a simple, but powerful, method, which we named prefractionation-assisted phosphoprotein enrichment (PAPE), to increase the yield of phosphoproteins from Arabidopsis thaliana leaf material. The first step, a prefractionation via ammonium sulfate precipitation, not only depleted RuBisCO almost completely, but, serendipitously, also served as an efficient phosphoprotein enrichment step. When coupled with a subsequent metal oxide affinity chromatography (MOAC) step, the phosphoprotein content was highly enriched. The reproducibility and efficiency of phosphoprotein enrichment was verified by phospho-specific staining and, further, by mass spectrometry, where it could be shown that the final PAPE fraction contained a significant number of known and additionally novel (potential) phosphoproteins. Hence, this facile two-step procedure is a good prerequisite to probe the phosphoproteome and gain deeper insight into plant phosphorylation-based signaling events.

Bioinformatic Analysis of Differential Protein Expression in Calu-3 Cells Exposed to Carbon Nanotubes

Abstract: Carbon nanomaterials are widely produced and used in industry, medicine and scientific research. To examine the impact of exposure to nanoparticles on human health, the human airway epithelial cell line, Calu-3, was used to evaluate changes in the cellular proteome that could account for alterations in cellular function of airway epithelia after 24 hexposure to 10 μg/mL and 100 ng/mLof two common carbon nanoparticles, single- and multi-wall carbon nanotubes (SWCNT, MWCNT). After exposure to the nanoparticles, label-free quantitative mass spectrometry (LFQMS) was used to study the differential protein expression. Ingenuity Pathway Analysis (IPA) was used to conduct a bioinformaticanalysis of proteins identified in LFQMS. Interestingly, after exposure to ahigh concentration (10 mg/mL; 0.4 mg/cm2) of MWCNT or SWCNT, only 8 and 13 proteins, respectively, exhibited changes in abundance. In contrast, the abundance of hundreds of proteins was altered in response to a low concentration (100 ng/mL; 4 ng/cm2) of either CNT. Of the 281 and 282 proteins that were significantly altered in response to MWCNT or SWCNT respectively, 231 proteins were the same. Bioinformatic analyses found that the proteins in common to both nanotubes occurred within the cellular functions of cell death and survival, cell-to-cell signaling and interaction, cellular assembly and organization, cellular growth and proliferation, infectious disease, molecular transport and protein synthesis. The majority of the protein changes represent a decrease in amount suggesting a general stress response to protect cells. The STRING database was used to analyze the various functional protein networks. Interestingly, some proteins like cadherin 1 (CDH1), signal transducer and activator of transcription 1 (STAT1), junction plakoglobin (JUP), and apoptosis-associated speck-like protein containing a CARD (PYCARD), appear in several functional categories and tend to be in the center of the networks. This central positioning suggests they may play important roles in multiple cellular functions and activities that are altered in response to carbon nanotube exposure.

Proteomic Analysis of Matched Formalin-Fixed, Paraffin-Embedded Specimens in Patients with Advanced Serous Ovarian Carcinoma.

Abstract: Objective: The biology of high grade serous ovarian carcinoma (HGSOC) is poorly understood. Little has been reported on intratumoral homogeneity or heterogeneity of primary HGSOC tumors and their metastases. We evaluated the global protein expression profiles of paired primary and metastatic HGSOC from formalin-fixed, paraffin-embedded (FFPE) tissue samples. Methods: After IRB approval, six patients with advanced HGSOC were identified with tumor in both ovaries at initial surgery. Laser capture microdissection (LCM) was used to extract tumor for protein digestion. Peptides were extracted and analyzed by reversed-phase liquid chromatography coupled to a linear ion trap mass spectrometer. Tandem mass spectra were searched against the UniProt human protein database. Differences in protein abundance between samples were assessed and analyzed by Ingenuity Pathway Analysis software. Immunohistochemistry (IHC) for select proteins from the original and an additional validation set of five patients was performed. Results: Unsupervised clustering of the abundance profiles placed the paired specimens adjacent to each other. IHC H-score analysis of the validation set revealed a strong correlation between paired samples for all proteins. For the similarly expressed proteins, the estimated correlation coefficients in two of three experimental samples and all validation samples were statistically significant (p < 0.05). The estimated correlation coefficients in the experimental sample proteins classified as differentially expressed were not statistically significant. Conclusion: A global proteomic screen of primary HGSOC tumors and their metastatic lesions identifies tumoral homogeneity and heterogeneity and provides preliminary insight into these protein profiles and the cellular pathways they constitute.

Protein-Protein Interactions: Gene Acronym Redundancies and Current Limitations Precluding Automated Data Integration

Abstract: Understanding protein interaction networks and their dynamic changes is a major challenge in modern biology. Currently, several experimental and in silico approaches allow the screening of protein interactors in a large-scale manner. Therefore, the bulk of information on protein interactions deposited in databases and peer-reviewed published literature is constantly growing. Multiple databases interfaced from user-friendly web tools recently emerged to facilitate the task of protein interaction data retrieval and data integration. Nevertheless, as we evidence in this report, despite the current efforts towards data integration, the quality of the information on protein interactions retrieved by in silico approaches is frequently incomplete and may even list false interactions. Here we point to some obstacles precluding confident data integration, with special emphasis on protein interactions, which include gene acronym redundancies and protein synonyms. Three human proteins (choline kinase, PPIase and uromodulin) and three different web-based data search engines focused on protein interaction data retrieval (PSICQUIC, DASMI and BIPS) were used to explain the potential occurrence of undesired errors that should be considered by researchers in the field. We demonstrate that, despite the recent initiatives towards data standardization, manual curation of protein interaction networks based on literature searches are still required to remove potential false positives. A three-step workflow consisting of: (i) data retrieval from multiple databases, (ii) peer-reviewed literature searches, and (iii) data curation and integration, is proposed as the best strategy to gather updated information on protein interactions. Finally, this strategy was applied to compile bona fide information on human DREAM protein interactome, which constitutes liable training datasets that can be used to improve computational predictions.

High-Throughput Proteomic Approaches to the Elucidation of Potential Biomarkers of Chronic Allograft Injury (CAI)

Abstract: This review focuses on the role of OMICs technologies, concentrating in particular on proteomics, in biomarker discovery in chronic allograft injury (CAI). CAI is the second most prevalent cause of allograft dysfunction and loss in the first decade post-transplantation, after death with functioning graft (DWFG). The term CAI, sometimes referred to as chronic allograft nephropathy (CAN), describes the deterioration of renal allograft function and structure as a result of immunological processes (chronic antibody-mediated rejection), and other non-immunological factors such as calcineurin inhibitor (CNI) induced nephrotoxicity, hypertension and infection. Current methods for assessing allograft function are costly, insensitive and invasive; traditional kidney function measurements such as serum creatinine and glomerular filtration rate (GFR) display poor predictive abilities, while the current ―gold-standard‖ involving histological diagnosis with a renal biopsy presents its own inherent risks to the overall health of the allograft. As early as two years post-transplantation, protocol biopsies have shown more than 50% of allograft recipients have mild CAN; ten years post-transplantation more than 50% of the allograft recipients have progressed to severe CAN which is associated with diminishing graft function. Thus, there is a growing medical requirement for minimally invasive biomarkers capable of identifying the early stages of the disease which would allow for timely