A lectin-coupled, targeted proteomic mass spectrometry (MRM MS) platform for identification of multiple liver cancer biomarkers in human plasma.

PubMed

Ahn, Yeong Hee; Shin, Park Min; Oh, Na Ree; Park, Gun Wook; Kim, Hoguen; Yoo, Jong Shin

2012-09-18

Aberrantly glycosylated proteins related to liver cancer progression were captured with specific lectin and identified from human plasma by multiple reaction monitoring (MRM) mass spectrometry as multiple biomarkers for hepatocellular carcinoma (HCC). The lectin fractionation for fucosylated protein glycoforms in human plasma was conducted with a fucose-specific aleuria aurantia lectin (AAL). Following tryptic digestion of the lectin-captured fraction, plasma samples from 30 control cases (including 10 healthy, 10 hepatitis B virus [HBV], and 10 cirrhosis cases) and 10 HCC cases were quantitatively analyzed by MRM to identify which glycoproteins are viable HCC biomarkers. A1AG1, AACT, A1AT, and CERU were found to be potent biomarkers to differentiate HCC plasma from control plasmas. The AUROC generated independently from these four biomarker candidates ranged from 0.73 to 0.92. However, the lectin-coupled MRM assay with multiple combinations of biomarker candidates is superior statistically to those generated from the individual candidates with AUROC more than 0.95, which can be an alternative to the immunoassay inevitably requiring tedious development of multiple antibodies against biomarker candidates to be verified. Eventually the lectin-coupled, targeted proteomic mass spectrometry (MRM MS) platform was found to be efficient to identify multiple biomarkers from human plasma according to cancer progression. Copyright © 2012 Elsevier B.V. All rights reserved.

Expression proteomics study to determine metallodrug targets and optimal drug combinations.

PubMed

Lee, Ronald F S; Chernobrovkin, Alexey; Rutishauser, Dorothea; Allardyce, Claire S; Hacker, David; Johnsson, Kai; Zubarev, Roman A; Dyson, Paul J

2017-05-08

The emerging technique termed functional identification of target by expression proteomics (FITExP) has been shown to identify the key protein targets of anti-cancer drugs. Here, we use this approach to elucidate the proteins involved in the mechanism of action of two ruthenium(II)-based anti-cancer compounds, RAPTA-T and RAPTA-EA in breast cancer cells, revealing significant differences in the proteins upregulated. RAPTA-T causes upregulation of multiple proteins suggesting a broad mechanism of action involving suppression of both metastasis and tumorigenicity. RAPTA-EA bearing a GST inhibiting ethacrynic acid moiety, causes upregulation of mainly oxidative stress related proteins. The approach used in this work could be applied to the prediction of effective drug combinations to test in cancer chemotherapy clinical trials.

Chemical proteomics approaches for identifying the cellular targets of natural products

PubMed Central

Sieber, S. A.

2016-01-01

Covering: 2010 up to 2016 Deconvoluting the mode of action of natural products and drugs remains one of the biggest challenges in chemistry and biology today. Chemical proteomics is a growing area of chemical biology that seeks to design small molecule probes to understand protein function. In the context of natural products, chemical proteomics can be used to identify the protein binding partners or targets of small molecules in live cells. Here, we highlight recent examples of chemical probes based on natural products and their application for target identification. The review focuses on probes that can be covalently linked to their target proteins (either via intrinsic chemical reactivity or via the introduction of photocrosslinkers), and can be applied “in situ” – in living systems rather than cell lysates. We also focus here on strategies that employ a click reaction, the copper-catalysed azide–alkyne cycloaddition reaction (CuAAC), to allow minimal functionalisation of natural product scaffolds with an alkyne or azide tag. We also discuss ‘competitive mode’ approaches that screen for natural products that compete with a well-characterised chemical probe for binding to a particular set of protein targets. Fuelled by advances in mass spectrometry instrumentation and bioinformatics, many modern strategies are now embracing quantitative proteomics to help define the true interacting partners of probes, and we highlight the opportunities this rapidly evolving technology provides in chemical proteomics. Finally, some of the limitations and challenges of chemical proteomics approaches are discussed. PMID:27098809

Chemical proteomics approaches for identifying the cellular targets of natural products.

PubMed

Wright, M H; Sieber, S A

2016-05-04

Covering: 2010 up to 2016Deconvoluting the mode of action of natural products and drugs remains one of the biggest challenges in chemistry and biology today. Chemical proteomics is a growing area of chemical biology that seeks to design small molecule probes to understand protein function. In the context of natural products, chemical proteomics can be used to identify the protein binding partners or targets of small molecules in live cells. Here, we highlight recent examples of chemical probes based on natural products and their application for target identification. The review focuses on probes that can be covalently linked to their target proteins (either via intrinsic chemical reactivity or via the introduction of photocrosslinkers), and can be applied "in situ" - in living systems rather than cell lysates. We also focus here on strategies that employ a click reaction, the copper-catalysed azide-alkyne cycloaddition reaction (CuAAC), to allow minimal functionalisation of natural product scaffolds with an alkyne or azide tag. We also discuss 'competitive mode' approaches that screen for natural products that compete with a well-characterised chemical probe for binding to a particular set of protein targets. Fuelled by advances in mass spectrometry instrumentation and bioinformatics, many modern strategies are now embracing quantitative proteomics to help define the true interacting partners of probes, and we highlight the opportunities this rapidly evolving technology provides in chemical proteomics. Finally, some of the limitations and challenges of chemical proteomics approaches are discussed.

Unbiased and targeted mass spectrometry for the HDL proteome.

PubMed

Singh, Sasha A; Aikawa, Masanori

2017-02-01

Mass spectrometry is an ever evolving technology that is equipped with a variety of tools for protein research. Some lipoprotein studies, especially those pertaining to HDL biology, have been exploiting the versatility of mass spectrometry to understand HDL function through its proteome. Despite the role of mass spectrometry in advancing research as a whole, however, the technology remains obscure to those without hands on experience, but still wishing to understand it. In this review, we walk the reader through the coevolution of common mass spectrometry workflows and HDL research, starting from the basic unbiased mass spectrometry methods used to profile the HDL proteome to the most recent targeted methods that have enabled an unprecedented view of HDL metabolism. Unbiased global proteomics have demonstrated that the HDL proteome is organized into subgroups across the HDL size fractions providing further evidence that HDL functional heterogeneity is in part governed by its varying protein constituents. Parallel reaction monitoring, a novel targeted mass spectrometry method, was used to monitor the metabolism of HDL apolipoproteins in humans and revealed that apolipoproteins contained within the same HDL size fraction exhibit diverse metabolic properties. Mass spectrometry provides a variety of tools and strategies to facilitate understanding, through its proteins, the complex biology of HDL.

PeptidePicker: a scientific workflow with web interface for selecting appropriate peptides for targeted proteomics experiments.

PubMed

Mohammed, Yassene; Domański, Dominik; Jackson, Angela M; Smith, Derek S; Deelder, André M; Palmblad, Magnus; Borchers, Christoph H

2014-06-25

One challenge in Multiple Reaction Monitoring (MRM)-based proteomics is to select the most appropriate surrogate peptides to represent a target protein. We present here a software package to automatically generate these most appropriate surrogate peptides for an LC/MRM-MS analysis. Our method integrates information about the proteins, their tryptic peptides, and the suitability of these peptides for MRM which is available online in UniProtKB, NCBI's dbSNP, ExPASy, PeptideAtlas, PRIDE, and GPMDB. The scoring algorithm reflects our knowledge in choosing the best candidate peptides for MRM, based on the uniqueness of the peptide in the targeted proteome, its physiochemical properties, and whether it previously has been observed. The modularity of the workflow allows further extension and additional selection criteria to be incorporated. We have developed a simple Web interface where the researcher provides the protein accession number, the subject organism, and peptide-specific options. Currently, the software is designed for human and mouse proteomes, but additional species can be easily be added. Our software improved the peptide selection by eliminating human error, considering multiple data sources and all of the isoforms of the protein, and resulted in faster peptide selection - approximately 50 proteins per hour compared to 8 per day. Compiling a list of optimal surrogate peptides for target proteins to be analyzed by LC/MRM-MS has been a cumbersome process, in which expert researchers retrieved information from different online repositories and used their own reasoning to find the most appropriate peptides. Our scientific workflow automates this process by integrating information from different data sources including UniProt, Global Proteome Machine, NCBI's dbSNP, and PeptideAtlas, simulating the researchers' reasoning, and incorporating their knowledge of how to select the best proteotypic peptides for an MRM analysis. The developed software can help to

Clinical proteomics-driven precision medicine for targeted cancer therapy: current overview and future perspectives.

PubMed

Zhou, Li; Wang, Kui; Li, Qifu; Nice, Edouard C; Zhang, Haiyuan; Huang, Canhua

2016-01-01

Cancer is a common disease that is a leading cause of death worldwide. Currently, early detection and novel therapeutic strategies are urgently needed for more effective management of cancer. Importantly, protein profiling using clinical proteomic strategies, with spectacular sensitivity and precision, offer excellent promise for the identification of potential biomarkers that would direct the development of targeted therapeutic anticancer drugs for precision medicine. In particular, clinical sample sources, including tumor tissues and body fluids (blood, feces, urine and saliva), have been widely investigated using modern high-throughput mass spectrometry-based proteomic approaches combined with bioinformatic analysis, to pursue the possibilities of precision medicine for targeted cancer therapy. Discussed in this review are the current advantages and limitations of clinical proteomics, the available strategies of clinical proteomics for the management of precision medicine, as well as the challenges and future perspectives of clinical proteomics-driven precision medicine for targeted cancer therapy.

Targeted proteomics guided by label-free global proteome analysis in saliva reveal transition signatures from health to periodontal disease.

PubMed

Bostanci, Nagihan; Selevsek, Nathalie; Wolski, Witold; Grossmann, Jonas; Bao, Kai; Wahlander, Asa; Trachsel, Christian; Schlapbach, Ralph; Özturk, Veli Özgen; Afacan, Beral; Emingil, Gulnur; Belibasakis, Georgios N

2018-04-02

Periodontal diseases are among the most prevalent worldwide, but largely silent, chronic diseases. They affect the tooth-supporting tissues with multiple ramifications on life quality. Their early diagnosis is still challenging, due to lack of appropriate molecular diagnostic methods. Saliva offers a non-invasively collectable reservoir of clinically relevant biomarkers, which, if utilized efficiently, could facilitate early diagnosis and monitoring of ongoing disease. Despite several novel protein markers being recently enlisted by discovery proteomics, their routine diagnostic application is hampered by the lack of validation platforms that allow for rapid, accurate and simultaneous quantification of multiple proteins in large cohorts. We carried out a pipeline of two proteomic platforms; firstly, we applied open ended label-free quantitative (LFQ) proteomics for discovery in saliva (n=67, health, gingivitis, and periodontitis), followed by selected-reaction monitoring (SRM)-targeted proteomics for validation in an independent cohort (n=82). The LFQ platform led to the discovery of 119 proteins with at least two-fold significant difference between health and disease. The 65 proteins chosen for the subsequent SRM platform included 50 related proteins derived from the significantly enriched processes of the LFQ data, 11 from literature-mining, and four house-keeping ones. Among those, 60 were reproducibly quantifiable proteins (92% success rate), represented by a total of 143 peptides. Machine-learning modeling led to a narrowed-down panel of five proteins of high predictive value for periodontal diseases (higher in disease: Matrix metalloproteinase-9, Ras-related protein-1, Actin-related protein 2/3 complex subunit 5; lower in disease: Clusterin, Deleted in Malignant Brain Tumors 1), with maximum area under the receiver operating curve >0.97. This panel enriches the pool of credible clinical biomarker candidates for diagnostic assay development. Yet, the quantum

CPTAC Collaborates with Molecular & Cellular Proteomics to Address Reproducibility in Targeted Assay Development | Office of Cancer Clinical Proteomics Research

Cancer.gov

The journal Molecular & Cellular Proteomics (MCP), in collaboration with the Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI), part of the National Institutes of Health, announce new guidelines and requirements for papers describing the development and application of targeted mass spectrometry measurements of peptides, modified peptides and proteins (Mol Cell Proteomics 2017; PMID: 28183812).  NCI’s participation is part of NIH’s overall effort to address the r

Biomarker Discovery and Mechanistic Studies of Prostate Cancer Using Targeted Proteomic Approaches

DTIC Science & Technology

2010-07-01

1-0431 TITLE: Biomarker Discovery and Mechanistic Studies of Prostate Cancer Using Targeted Proteomic Approaches PRINCIPAL INVESTIGATOR...June 2010 4. TITLE AND SUBTITLE Biomarker Discovery and Mechanistic Studies of Prostate Cancer Using Targeted Proteomic 5a. CONTRACT NUMBER...1-0430; W81XWH-08-1-0431; Grant sponsor: NIH/NCRR COBRE Grant; Grant number: 1P20RR020171; Grant sponsor: NIH/NIDDK Grant; Grant number: R01DK053525

CPTAC Assay Portal: a repository of targeted proteomic assays

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whiteaker, Jeffrey R.; Halusa, Goran; Hoofnagle, Andrew N.

2014-06-27

To address these issues, the Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI) has launched an Assay Portal (http://assays.cancer.gov) to serve as a public repository of well-characterized quantitative, MS-based, targeted proteomic assays. The purpose of the CPTAC Assay Portal is to facilitate widespread adoption of targeted MS assays by disseminating SOPs, reagents, and assay characterization data for highly characterized assays. A primary aim of the NCI-supported portal is to bring together clinicians or biologists and analytical chemists to answer hypothesis-driven questions using targeted, MS-based assays. Assay content is easily accessed through queries and filters, enabling investigatorsmore » to find assays to proteins relevant to their areas of interest. Detailed characterization data are available for each assay, enabling researchers to evaluate assay performance prior to launching the assay in their own laboratory.« less

Multiple testing corrections in quantitative proteomics: A useful but blunt tool.

PubMed

Pascovici, Dana; Handler, David C L; Wu, Jemma X; Haynes, Paul A

2016-09-01

Multiple testing corrections are a useful tool for restricting the FDR, but can be blunt in the context of low power, as we demonstrate by a series of simple simulations. Unfortunately, in proteomics experiments low power can be common, driven by proteomics-specific issues like small effects due to ratio compression, and few replicates due to reagent high cost, instrument time availability and other issues; in such situations, most multiple testing corrections methods, if used with conventional thresholds, will fail to detect any true positives even when many exist. In this low power, medium scale situation, other methods such as effect size considerations or peptide-level calculations may be a more effective option, even if they do not offer the same theoretical guarantee of a low FDR. Thus, we aim to highlight in this article that proteomics presents some specific challenges to the standard multiple testing corrections methods, which should be employed as a useful tool but not be regarded as a required rubber stamp. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparative Analysis of Predicted Plastid-Targeted Proteomes of Sequenced Higher Plant Genomes

PubMed Central

Schaeffer, Scott; Harper, Artemus; Raja, Rajani; Jaiswal, Pankaj; Dhingra, Amit

2014-01-01

Plastids are actively involved in numerous plant processes critical to growth, development and adaptation. They play a primary role in photosynthesis, pigment and monoterpene synthesis, gravity sensing, starch and fatty acid synthesis, as well as oil, and protein storage. We applied two complementary methods to analyze the recently published apple genome (Malus × domestica) to identify putative plastid-targeted proteins, the first using TargetP and the second using a custom workflow utilizing a set of predictive programs. Apple shares roughly 40% of its 10,492 putative plastid-targeted proteins with that of the Arabidopsis (Arabidopsis thaliana) plastid-targeted proteome as identified by the Chloroplast 2010 project and ∼57% of its entire proteome with Arabidopsis. This suggests that the plastid-targeted proteomes between apple and Arabidopsis are different, and interestingly alludes to the presence of differential targeting of homologs between the two species. Co-expression analysis of 2,224 genes encoding putative plastid-targeted apple proteins suggests that they play a role in plant developmental and intermediary metabolism. Further, an inter-specific comparison of Arabidopsis, Prunus persica (Peach), Malus × domestica (Apple), Populus trichocarpa (Black cottonwood), Fragaria vesca (Woodland Strawberry), Solanum lycopersicum (Tomato) and Vitis vinifera (Grapevine) also identified a large number of novel species-specific plastid-targeted proteins. This analysis also revealed the presence of alternatively targeted homologs across species. Two separate analyses revealed that a small subset of proteins, one representing 289 protein clusters and the other 737 unique protein sequences, are conserved between seven plastid-targeted angiosperm proteomes. Majority of the novel proteins were annotated to play roles in stress response, transport, catabolic processes, and cellular component organization. Our results suggest that the current state of knowledge regarding

Quantitative changes in proteins responsible for flavonoid and anthocyanin biosynthesis in strawberry fruit at different ripening stages: A targeted quantitative proteomic investigation employing multiple reaction monitoring.

PubMed

Song, Jun; Du, Lina; Li, Li; Kalt, Wilhelmina; Palmer, Leslie Campbell; Fillmore, Sherry; Zhang, Ying; Zhang, ZhaoQi; Li, XiHong

2015-06-03

To better understand the regulation of flavonoid and anthocyanin biosynthesis, a targeted quantitative proteomic investigation employing LC-MS with multiple reaction monitoring was conducted on two strawberry cultivars at three ripening stages. This quantitative proteomic workflow was improved through an OFFGEL electrophoresis to fractionate peptides from total protein digests. A total of 154 peptide transitions from 47 peptides covering 21 proteins and isoforms related to anthocyanin biosynthesis were investigated. The normalized protein abundance, which was measured using isotopically-labeled standards, was significantly changed concurrently with increased anthocyanin content and advanced fruit maturity. The protein abundance of phenylalanine ammonia-lyase; anthocyanidin synthase, chalcone isomerase; flavanone 3-hydroxylase; dihydroflavonol 4-reductase, UDP-glucose:flavonoid-3-O-glucosyltransferase, cytochrome c and cytochrome C oxidase subunit 2, was all significantly increased in fruit of more advanced ripeness. An interaction between cultivar and maturity was also shown with respect to chalcone isomerase. The good correlation between protein abundance and anthocyanin content suggested that a metabolic control point may exist for anthocyanin biosynthesis. This research provides insights into the process of anthocyanin formation in strawberry fruit at the level of protein concentration and reveals possible candidates in the regulation of anthocyanin formation during fruit ripening. To gain insight into the molecular mechanisms contributing to flavonoids and anthocyanin biosynthesis and regulation of strawberry fruit during ripening is challenging due to limited molecular biology tools and established hypothesis. Our targeted proteomic approach employing LC-MS/MS analysis and MRM technique to quantify proteins in relation to flavonoids and anthocyanin biosynthesis and regulation in strawberry fruit during fruit ripening is novel. The identification of peptides

Chemical Proteomic Approaches Targeting Cancer Stem Cells: A Review of Current Literature.

PubMed

Jung, Hye Jin

2017-01-01

Cancer stem cells (CSCs) have been proposed as central drivers of tumor initiation, progression, recurrence, and therapeutic resistance. Therefore, identifying stem-like cells within cancers and understanding their properties is crucial for the development of effective anticancer therapies. Recently, chemical proteomics has become a powerful tool to efficiently determine protein networks responsible for CSC pathophysiology and comprehensively elucidate molecular mechanisms of drug action against CSCs. This review provides an overview of major methodologies utilized in chemical proteomic approaches. In addition, recent successful chemical proteomic applications targeting CSCs are highlighted. Future direction of potential CSC research by integrating chemical genomic and proteomic data obtained from a single biological sample of CSCs are also suggested in this review. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Simultaneous Proteomic Discovery and Targeted Monitoring using Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry*

PubMed Central

Burnum-Johnson, Kristin E.; Nie, Song; Casey, Cameron P.; Monroe, Matthew E.; Orton, Daniel J.; Ibrahim, Yehia M.; Gritsenko, Marina A.; Clauss, Therese R. W.; Shukla, Anil K.; Moore, Ronald J.; Purvine, Samuel O.; Shi, Tujin; Qian, Weijun; Liu, Tao; Baker, Erin S.; Smith, Richard D.

2016-01-01

Current proteomic approaches include both broad discovery measurements and quantitative targeted analyses. In many cases, discovery measurements are initially used to identify potentially important proteins (e.g. candidate biomarkers) and then targeted studies are employed to quantify a limited number of selected proteins. Both approaches, however, suffer from limitations. Discovery measurements aim to sample the whole proteome but have lower sensitivity, accuracy, and quantitation precision than targeted approaches, whereas targeted measurements are significantly more sensitive but only sample a limited portion of the proteome. Herein, we describe a new approach that performs both discovery and targeted monitoring (DTM) in a single analysis by combining liquid chromatography, ion mobility spectrometry and mass spectrometry (LC-IMS-MS). In DTM, heavy labeled target peptides are spiked into tryptic digests and both the labeled and unlabeled peptides are detected using LC-IMS-MS instrumentation. Compared with the broad LC-MS discovery measurements, DTM yields greater peptide/protein coverage and detects lower abundance species. DTM also achieved detection limits similar to selected reaction monitoring (SRM) indicating its potential for combined high quality discovery and targeted analyses, which is a significant step toward the convergence of discovery and targeted approaches. PMID:27670688

Absolute Quantification of Middle- to High-Abundant Plasma Proteins via Targeted Proteomics.

PubMed

Dittrich, Julia; Ceglarek, Uta

2017-01-01

The increasing number of peptide and protein biomarker candidates requires expeditious and reliable quantification strategies. The utilization of liquid chromatography coupled to quadrupole tandem mass spectrometry (LC-MS/MS) for the absolute quantitation of plasma proteins and peptides facilitates the multiplexed verification of tens to hundreds of biomarkers from smallest sample quantities. Targeted proteomics assays derived from bottom-up proteomics principles rely on the identification and analysis of proteotypic peptides formed in an enzymatic digestion of the target protein. This protocol proposes a procedure for the establishment of a targeted absolute quantitation method for middle- to high-abundant plasma proteins waiving depletion or enrichment steps. Essential topics as proteotypic peptide identification and LC-MS/MS method development as well as sample preparation and calibration strategies are described in detail.

A Targeted Quantitative Proteomics Strategy for Global Kinome Profiling of Cancer Cells and Tissues*

PubMed Central

Xiao, Yongsheng; Guo, Lei; Wang, Yinsheng

2014-01-01

Kinases are among the most intensively pursued enzyme superfamilies as targets for anti-cancer drugs. Large data sets on inhibitor potency and selectivity for more than 400 human kinases became available recently, offering the opportunity to design rationally novel kinase-based anti-cancer therapies. However, the expression levels and activities of kinases are highly heterogeneous among different types of cancer and even among different stages of the same cancer. The lack of effective strategy for profiling the global kinome hampers the development of kinase-targeted cancer chemotherapy. Here, we introduced a novel global kinome profiling method, based on our recently developed isotope-coded ATP-affinity probe and a targeted proteomic method using multiple-reaction monitoring (MRM), for assessing simultaneously the expression of more than 300 kinases in human cells and tissues. This MRM-based assay displayed much better sensitivity, reproducibility, and accuracy than the discovery-based shotgun proteomic method. Approximately 250 kinases could be routinely detected in the lysate of a single cell line. Additionally, the incorporation of iRT into MRM kinome library rendered our MRM kinome assay easily transferrable across different instrument platforms and laboratories. We further employed this approach for profiling kinase expression in two melanoma cell lines, which revealed substantial kinome reprogramming during cancer progression and demonstrated an excellent correlation between the anti-proliferative effects of kinase inhibitors and the expression levels of their target kinases. Therefore, this facile and accurate kinome profiling assay, together with the kinome-inhibitor interaction map, could provide invaluable knowledge to predict the effectiveness of kinase inhibitor drugs and offer the opportunity for individualized cancer chemotherapy. PMID:24520089

Screening of missing proteins in the human liver proteome by improved MRM-approach-based targeted proteomics.

PubMed

Chen, Chen; Liu, Xiaohui; Zheng, Weimin; Zhang, Lei; Yao, Jun; Yang, Pengyuan

2014-04-04

To completely annotate the human genome, the task of identifying and characterizing proteins that currently lack mass spectrometry (MS) evidence is inevitable and urgent. In this study, as the first effort to screen missing proteins in large scale, we developed an approach based on SDS-PAGE followed by liquid chromatography-multiple reaction monitoring (LC-MRM), for screening of those missing proteins with only a single peptide hit in the previous liver proteome data set. Proteins extracted from normal human liver were separated in SDS-PAGE and digested in split gel slice, and the resulting digests were then subjected to LC-schedule MRM analysis. The MRM assays were developed through synthesized crude peptides for target peptides. In total, the expressions of 57 target proteins were confirmed from 185 MRM assays in normal human liver tissues. Among the proved 57 one-hit wonders, 50 proteins are of the minimally redundant set in the PeptideAtlas database, 7 proteins even have none MS-based information previously in various biological processes. We conclude that our SDS-PAGE-MRM workflow can be a powerful approach to screen missing or poorly characterized proteins in different samples and to provide their quantity if detected. The MRM raw data have been uploaded to ISB/SRM Atlas/PASSEL (PXD000648).

Simultaneous Proteomic Discovery and Targeted Monitoring using Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry.

PubMed

Burnum-Johnson, Kristin E; Nie, Song; Casey, Cameron P; Monroe, Matthew E; Orton, Daniel J; Ibrahim, Yehia M; Gritsenko, Marina A; Clauss, Therese R W; Shukla, Anil K; Moore, Ronald J; Purvine, Samuel O; Shi, Tujin; Qian, Weijun; Liu, Tao; Baker, Erin S; Smith, Richard D

2016-12-01

Current proteomic approaches include both broad discovery measurements and quantitative targeted analyses. In many cases, discovery measurements are initially used to identify potentially important proteins (e.g. candidate biomarkers) and then targeted studies are employed to quantify a limited number of selected proteins. Both approaches, however, suffer from limitations. Discovery measurements aim to sample the whole proteome but have lower sensitivity, accuracy, and quantitation precision than targeted approaches, whereas targeted measurements are significantly more sensitive but only sample a limited portion of the proteome. Herein, we describe a new approach that performs both discovery and targeted monitoring (DTM) in a single analysis by combining liquid chromatography, ion mobility spectrometry and mass spectrometry (LC-IMS-MS). In DTM, heavy labeled target peptides are spiked into tryptic digests and both the labeled and unlabeled peptides are detected using LC-IMS-MS instrumentation. Compared with the broad LC-MS discovery measurements, DTM yields greater peptide/protein coverage and detects lower abundance species. DTM also achieved detection limits similar to selected reaction monitoring (SRM) indicating its potential for combined high quality discovery and targeted analyses, which is a significant step toward the convergence of discovery and targeted approaches. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Optimal de novo design of MRM experiments for rapid assay development in targeted proteomics.

PubMed

Bertsch, Andreas; Jung, Stephan; Zerck, Alexandra; Pfeifer, Nico; Nahnsen, Sven; Henneges, Carsten; Nordheim, Alfred; Kohlbacher, Oliver

2010-05-07

Targeted proteomic approaches such as multiple reaction monitoring (MRM) overcome problems associated with classical shotgun mass spectrometry experiments. Developing MRM quantitation assays can be time consuming, because relevant peptide representatives of the proteins must be found and their retention time and the product ions must be determined. Given the transitions, hundreds to thousands of them can be scheduled into one experiment run. However, it is difficult to select which of the transitions should be included into a measurement. We present a novel algorithm that allows the construction of MRM assays from the sequence of the targeted proteins alone. This enables the rapid development of targeted MRM experiments without large libraries of transitions or peptide spectra. The approach relies on combinatorial optimization in combination with machine learning techniques to predict proteotypicity, retention time, and fragmentation of peptides. The resulting potential transitions are scheduled optimally by solving an integer linear program. We demonstrate that fully automated construction of MRM experiments from protein sequences alone is possible and over 80% coverage of the targeted proteins can be achieved without further optimization of the assay.

Comprehensive quantitative analysis of central carbon and amino-acid metabolism in Saccharomyces cerevisiae under multiple conditions by targeted proteomics

PubMed Central

Costenoble, Roeland; Picotti, Paola; Reiter, Lukas; Stallmach, Robert; Heinemann, Matthias; Sauer, Uwe; Aebersold, Ruedi

2011-01-01

Decades of biochemical research have identified most of the enzymes that catalyze metabolic reactions in the yeast Saccharomyces cerevisiae. The adaptation of metabolism to changing nutritional conditions, in contrast, is much less well understood. As an important stepping stone toward such understanding, we exploit the power of proteomics assays based on selected reaction monitoring (SRM) mass spectrometry to quantify abundance changes of the 228 proteins that constitute the central carbon and amino-acid metabolic network in the yeast Saccharomyces cerevisiae, at five different metabolic steady states. Overall, 90% of the targeted proteins, including families of isoenzymes, were consistently detected and quantified in each sample, generating a proteomic data set that represents a nutritionally perturbed biological system at high reproducibility. The data set is near comprehensive because we detect 95–99% of all proteins that are required under a given condition. Interpreted through flux balance modeling, the data indicate that S. cerevisiae retains proteins not necessarily used in a particular environment. Further, the data suggest differential functionality for several metabolic isoenzymes. PMID:21283140

Identification of lactoferricin B intracellular targets using an Escherichia coli proteome chip.

PubMed

Tu, Yu-Hsuan; Ho, Yu-Hsuan; Chuang, Ying-Chih; Chen, Po-Chung; Chen, Chien-Sheng

2011-01-01

Lactoferricin B (LfcinB) is a well-known antimicrobial peptide. Several studies have indicated that it can inhibit bacteria by affecting intracellular activities, but the intracellular targets of this antimicrobial peptide have not been identified. Therefore, we used E. coli proteome chips to identify the intracellular target proteins of LfcinB in a high-throughput manner. We probed LfcinB with E. coli proteome chips and further conducted normalization and Gene Ontology (GO) analyses. The results of the GO analyses showed that the identified proteins were associated with metabolic processes. Moreover, we validated the interactions between LfcinB and chip assay-identified proteins with fluorescence polarization (FP) assays. Sixteen proteins were identified, and an E. coli interaction database (EcID) analysis revealed that the majority of the proteins that interact with these 16 proteins affected the tricarboxylic acid (TCA) cycle. Knockout assays were conducted to further validate the FP assay results. These results showed that phosphoenolpyruvate carboxylase was a target of LfcinB, indicating that one of its mechanisms of action may be associated with pyruvate metabolism. Thus, we used pyruvate assays to conduct an in vivo validation of the relationship between LfcinB and pyruvate level in E. coli. These results showed that E. coli exposed to LfcinB had abnormal pyruvate amounts, indicating that LfcinB caused an accumulation of pyruvate. In conclusion, this study successfully revealed the intracellular targets of LfcinB using an E. coli proteome chip approach.

Identification of Lactoferricin B Intracellular Targets Using an Escherichia coli Proteome Chip

PubMed Central

Chen, Po-Chung; Chen, Chien-Sheng

2011-01-01

Lactoferricin B (LfcinB) is a well-known antimicrobial peptide. Several studies have indicated that it can inhibit bacteria by affecting intracellular activities, but the intracellular targets of this antimicrobial peptide have not been identified. Therefore, we used E. coli proteome chips to identify the intracellular target proteins of LfcinB in a high-throughput manner. We probed LfcinB with E. coli proteome chips and further conducted normalization and Gene Ontology (GO) analyses. The results of the GO analyses showed that the identified proteins were associated with metabolic processes. Moreover, we validated the interactions between LfcinB and chip assay-identified proteins with fluorescence polarization (FP) assays. Sixteen proteins were identified, and an E. coli interaction database (EcID) analysis revealed that the majority of the proteins that interact with these 16 proteins affected the tricarboxylic acid (TCA) cycle. Knockout assays were conducted to further validate the FP assay results. These results showed that phosphoenolpyruvate carboxylase was a target of LfcinB, indicating that one of its mechanisms of action may be associated with pyruvate metabolism. Thus, we used pyruvate assays to conduct an in vivo validation of the relationship between LfcinB and pyruvate level in E. coli. These results showed that E. coli exposed to LfcinB had abnormal pyruvate amounts, indicating that LfcinB caused an accumulation of pyruvate. In conclusion, this study successfully revealed the intracellular targets of LfcinB using an E. coli proteome chip approach. PMID:22164243

Simultaneous Proteomic Discovery and Targeted Monitoring using Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burnum-Johnson, Kristin E.; Nie, Song; Casey, Cameron P.

Current proteomics approaches are comprised of both broad discovery measurements as well as more quantitative targeted measurements. These two different measurement types are used to initially identify potentially important proteins (e.g., candidate biomarkers) and then enable improved quantification for a limited number of selected proteins. However, both approaches suffer from limitations, particularly the lower sensitivity, accuracy, and quantitation precision for discovery approaches compared to targeted approaches, and the limited proteome coverage provided by targeted approaches. Herein, we describe a new proteomics approach that allows both discovery and targeted monitoring (DTM) in a single analysis using liquid chromatography, ion mobility spectrometrymore » and mass spectrometry (LC-IMS-MS). In DTM, heavy labeled peptides for target ions are spiked into tryptic digests and both the labeled and unlabeled peptides are broadly detected using LC-IMS-MS instrumentation, allowing the benefits of discovery and targeted approaches. To understand the possible improvement of the DTM approach, it was compared to LC-MS broad measurements using an accurate mass and time tag database and selected reaction monitoring (SRM) targeted measurements. The DTM results yielded greater peptide/protein coverage and a significant improvement in the detection of lower abundance species compared to LC-MS discovery measurements. DTM was also observed to have similar detection limits as SRM for the targeted measurements indicating its potential for combining the discovery and targeted approaches.« less

Panorama: A Targeted Proteomics Knowledge Base

PubMed Central

2015-01-01

Panorama is a web application for storing, sharing, analyzing, and reusing targeted assays created and refined with Skyline,1 an increasingly popular Windows client software tool for targeted proteomics experiments. Panorama allows laboratories to store and organize curated results contained in Skyline documents with fine-grained permissions, which facilitates distributed collaboration and secure sharing of published and unpublished data via a web-browser interface. It is fully integrated with the Skyline workflow and supports publishing a document directly to a Panorama server from the Skyline user interface. Panorama captures the complete Skyline document information content in a relational database schema. Curated results published to Panorama can be aggregated and exported as chromatogram libraries. These libraries can be used in Skyline to pick optimal targets in new experiments and to validate peak identification of target peptides. Panorama is open-source and freely available. It is distributed as part of LabKey Server,2 an open source biomedical research data management system. Laboratories and organizations can set up Panorama locally by downloading and installing the software on their own servers. They can also request freely hosted projects on https://panoramaweb.org, a Panorama server maintained by the Department of Genome Sciences at the University of Washington. PMID:25102069

In situ Proteomic Profiling of Curcumin Targets in HCT116 Colon Cancer Cell Line.

PubMed

Wang, Jigang; Zhang, Jianbin; Zhang, Chong-Jing; Wong, Yin Kwan; Lim, Teck Kwang; Hua, Zi-Chun; Liu, Bin; Tannenbaum, Steven R; Shen, Han-Ming; Lin, Qingsong

2016-02-26

To date, the exact targets and mechanism of action of curcumin, a natural product with anti-inflammatory and anti-cancer properties, remain elusive. Here we synthesized a cell permeable curcumin probe (Cur-P) with an alkyne moiety, which can be tagged with biotin for affinity enrichment, or with a fluorescent dye for visualization of the direct-binding protein targets of curcumin in situ. iTRAQ(TM) quantitative proteomics approach was applied to distinguish the specific binding targets from the non-specific ones. In total, 197 proteins were confidently identified as curcumin binding targets from HCT116 colon cancer cell line. Gene Ontology analysis showed that the targets are broadly distributed and enriched in the nucleus, mitochondria and plasma membrane, and they are involved in various biological functions including metabolic process, regulation, response to stimulus and cellular process. Ingenuity Pathway Analysis(TM) (IPA) suggested that curcumin may exert its anticancer effects over multiple critical biological pathways including the EIF2, eIF4/p70S6K, mTOR signaling and mitochondrial dysfunction pathways. Functional validations confirmed that curcumin downregulates cellular protein synthesis, and induces autophagy, lysosomal activation and increased ROS production, thus leading to cell death.

In situ Proteomic Profiling of Curcumin Targets in HCT116 Colon Cancer Cell Line

PubMed Central

Wang, Jigang; Zhang, Jianbin; Zhang, Chong-Jing; Wong, Yin Kwan; Lim, Teck Kwang; Hua, Zi-Chun; Liu, Bin; Tannenbaum, Steven R.; Shen, Han-Ming; Lin, Qingsong

2016-01-01

To date, the exact targets and mechanism of action of curcumin, a natural product with anti-inflammatory and anti-cancer properties, remain elusive. Here we synthesized a cell permeable curcumin probe (Cur-P) with an alkyne moiety, which can be tagged with biotin for affinity enrichment, or with a fluorescent dye for visualization of the direct-binding protein targets of curcumin in situ. iTRAQTM quantitative proteomics approach was applied to distinguish the specific binding targets from the non-specific ones. In total, 197 proteins were confidently identified as curcumin binding targets from HCT116 colon cancer cell line. Gene Ontology analysis showed that the targets are broadly distributed and enriched in the nucleus, mitochondria and plasma membrane, and they are involved in various biological functions including metabolic process, regulation, response to stimulus and cellular process. Ingenuity Pathway AnalysisTM (IPA) suggested that curcumin may exert its anticancer effects over multiple critical biological pathways including the EIF2, eIF4/p70S6K, mTOR signaling and mitochondrial dysfunction pathways. Functional validations confirmed that curcumin downregulates cellular protein synthesis, and induces autophagy, lysosomal activation and increased ROS production, thus leading to cell death. PMID:26915414

Chemical proteomics for target discovery of head-to-tail cyclized mini-proteins

NASA Astrophysics Data System (ADS)

Hellinger, Roland; Thell, Kathrin; Vasileva, Mina; Muhammad, Taj; Gunasekera, Sunithi; Kümmel, Daniel; Göransson, Ulf; Becker, Christian W.; Gruber, Christian W.

2017-10-01

Target deconvolution is one of the most challenging tasks in drug discovery, but a key step in drug development. In contrast to small molecules, there is a lack of validated and robust methodologies for target elucidation of peptides. In particular, it is difficult to apply these methods to cyclic and cysteine-stabilized peptides since they exhibit reduced amenability to chemical modification and affinity capture; however, such ribosomal synthesized and post-translationally modified peptide natural products are rich sources of promising drug candidates. For example, plant-derived circular peptides called cyclotides have recently attracted much attention due to their immunosuppressive effects and oral activity in the treatment of multiple sclerosis in mice, but their molecular target has hitherto not been reported. In this study a chemical proteomics approach using photo-affinity crosslinking was developed to determine a target of the circular peptide [T20K]kalata B1. Using this prototypic nature-derived peptide enabled the identification of a possible modulation of 14-3-3 proteins. This biochemical interaction was validated via competition pull down assays as well as a cellular reporter assay indicating an effect on 14-3-3-dependent transcriptional activity. As proof of concept, the presented approach may be applicable for target elucidation of various cyclic peptides and mini-proteins, in particular cyclotides, which represent a promising class of molecules in drug discovery and development.

Data-Driven Approach To Determine Popular Proteins for Targeted Proteomics Translation of Six Organ Systems.

PubMed

Lam, Maggie P Y; Venkatraman, Vidya; Xing, Yi; Lau, Edward; Cao, Quan; Ng, Dominic C M; Su, Andrew I; Ge, Junbo; Van Eyk, Jennifer E; Ping, Peipei

2016-11-04

Amidst the proteomes of human tissues lie subsets of proteins that are closely involved in conserved pathophysiological processes. Much of biomedical research concerns interrogating disease signature proteins and defining their roles in disease mechanisms. With advances in proteomics technologies, it is now feasible to develop targeted proteomics assays that can accurately quantify protein abundance as well as their post-translational modifications; however, with rapidly accumulating number of studies implicating proteins in diseases, current resources are insufficient to target every protein without judiciously prioritizing the proteins with high significance and impact for assay development. We describe here a data science method to prioritize and expedite assay development on high-impact proteins across research fields by leveraging the biomedical literature record to rank and normalize proteins that are popularly and preferentially published by biomedical researchers. We demonstrate this method by finding priority proteins across six major physiological systems (cardiovascular, cerebral, hepatic, renal, pulmonary, and intestinal). The described method is data-driven and builds upon the collective knowledge of previous publications referenced on PubMed to lend objectivity to target selection. The method and resulting popular protein lists may also be useful for exploring biological processes associated with various physiological systems and research topics, in addition to benefiting ongoing efforts to facilitate the broad translation of proteomics technologies.

Mechanism-based Proteomic Screening Identifies Targets of Thioredoxin-like Proteins*

PubMed Central

Nakao, Lia S.; Everley, Robert A.; Marino, Stefano M.; Lo, Sze M.; de Souza, Luiz E.; Gygi, Steven P.; Gladyshev, Vadim N.

2015-01-01

Thioredoxin (Trx)-fold proteins are protagonists of numerous cellular pathways that are subject to thiol-based redox control. The best characterized regulator of thiols in proteins is Trx1 itself, which together with thioredoxin reductase 1 (TR1) and peroxiredoxins (Prxs) comprises a key redox regulatory system in mammalian cells. However, there are numerous other Trx-like proteins, whose functions and redox interactors are unknown. It is also unclear if the principles of Trx1-based redox control apply to these proteins. Here, we employed a proteomic strategy to four Trx-like proteins containing CXXC motifs, namely Trx1, Rdx12, Trx-like protein 1 (Txnl1) and nucleoredoxin 1 (Nrx1), whose cellular targets were trapped in vivo using mutant Trx-like proteins, under conditions of low endogenous expression of these proteins. Prxs were detected as key redox targets of Trx1, but this approach also supported the detection of TR1, which is the Trx1 reductant, as well as mitochondrial intermembrane proteins AIF and Mia40. In addition, glutathione peroxidase 4 was found to be a Rdx12 redox target. In contrast, no redox targets of Txnl1 and Nrx1 could be detected, suggesting that their CXXC motifs do not engage in mixed disulfides with cellular proteins. For some Trx-like proteins, the method allowed distinguishing redox and non-redox interactions. Parallel, comparative analyses of multiple thiol oxidoreductases revealed differences in the functions of their CXXC motifs, providing important insights into thiol-based redox control of cellular processes. PMID:25561728

A proteomic signature of ovarian cancer tumor fluid identified by highthroughput and verified by targeted proteomics.

PubMed

Poersch, Aline; Grassi, Mariana Lopes; Carvalho, Vinícius Pereira de; Lanfredi, Guilherme Pauperio; Palma, Camila de Souza; Greene, Lewis Joel; de Sousa, Christiani Bisinoto; Carrara, Hélio Humberto Angotti; Candido Dos Reis, Francisco José; Faça, Vitor Marcel

2016-08-11

Tumor fluid samples have emerged as a rich source for the identification of ovarian cancer in the context of proteomics studies. To uncover differences among benign and malignant ovarian samples, we performed a quantitative proteomic study consisting of albumin immunodepletion, isotope labeling with acrylamide and in-depth proteomic profiling by LC-MS/MS in a pool of 10 samples of each histological type. 1135 proteins were identified, corresponding to 505 gene products. 223 proteins presented associated quantification and the comparative analysis of histological types revealed 75 differentially abundant proteins. Based on this, we developed a panel for targeted proteomic analysis using the multiple reaction monitoring (MRM) method for validation of 51 proteins in individual samples of high-grade serous ovarian tumor fluids (malignant) and benign serous cystadenoma tumor fluids. This analysis showed concordant results in terms of average amounts of proteins, and APOE, SERPINF2, SERPING1, ADAM17, CD44 and OVGP1 were statistically significant between benign and malignant group. The results observed in the MRM for APOE were confirmed by western blotting, where APOE was more abundant in malignant samples. This molecular signature can contribute to improve tumor stratification and shall be investigated in combination with current biomarkers in larger cohorts to improve ovarian cancer diagnosis. Despite advances in cancer research, ovarian cancer has a high mortality and remains a major challenge due to a number of particularities of the disease, especially late diagnosis caused by vague clinical symptoms, the cellular and molecular heterogeneity of tumors, and the lack of effective treatment. Thus, efforts are directed to better understand this neoplasia, its origin, development and, particularly the identification and validation of biomarkers for early detection of the disease in asymptomatic stage. In the present work, we confirmed by MRM method in individual ovarian

How may targeted proteomics complement genomic data in breast cancer?

PubMed

Guerin, Mathilde; Gonçalves, Anthony; Toiron, Yves; Baudelet, Emilie; Audebert, Stéphane; Boyer, Jean-Baptiste; Borg, Jean-Paul; Camoin, Luc

2017-01-01

Breast cancer (BC) is the most common female cancer in the world and was recently deconstructed in different molecular entities. Although most of the recent assays to characterize tumors at the molecular level are genomic-based, proteins are the actual executors of cellular functions and represent the vast majority of targets for anticancer drugs. Accumulated data has demonstrated an important level of quantitative and qualitative discrepancies between genomic/transcriptomic alterations and their protein counterparts, mostly related to the large number of post-translational modifications. Areas covered: This review will present novel proteomics technologies such as Reverse Phase Protein Array (RPPA) or mass-spectrometry (MS) based approaches that have emerged and that could progressively replace old-fashioned methods (e.g. immunohistochemistry, ELISA, etc.) to validate proteins as diagnostic, prognostic or predictive biomarkers, and eventually monitor them in the routine practice. Expert commentary: These different targeted proteomic approaches, able to complement genomic data in BC and characterize tumors more precisely, will permit to go through a more personalized treatment for each patient and tumor.

Misclassification Errors in Unsupervised Classification Methods. Comparison Based on the Simulation of Targeted Proteomics Data

PubMed Central

Andreev, Victor P; Gillespie, Brenda W; Helfand, Brian T; Merion, Robert M

2016-01-01

Unsupervised classification methods are gaining acceptance in omics studies of complex common diseases, which are often vaguely defined and are likely the collections of disease subtypes. Unsupervised classification based on the molecular signatures identified in omics studies have the potential to reflect molecular mechanisms of the subtypes of the disease and to lead to more targeted and successful interventions for the identified subtypes. Multiple classification algorithms exist but none is ideal for all types of data. Importantly, there are no established methods to estimate sample size in unsupervised classification (unlike power analysis in hypothesis testing). Therefore, we developed a simulation approach allowing comparison of misclassification errors and estimating the required sample size for a given effect size, number, and correlation matrix of the differentially abundant proteins in targeted proteomics studies. All the experiments were performed in silico. The simulated data imitated the expected one from the study of the plasma of patients with lower urinary tract dysfunction with the aptamer proteomics assay Somascan (SomaLogic Inc, Boulder, CO), which targeted 1129 proteins, including 330 involved in inflammation, 180 in stress response, 80 in aging, etc. Three popular clustering methods (hierarchical, k-means, and k-medoids) were compared. K-means clustering performed much better for the simulated data than the other two methods and enabled classification with misclassification error below 5% in the simulated cohort of 100 patients based on the molecular signatures of 40 differentially abundant proteins (effect size 1.5) from among the 1129-protein panel. PMID:27524871

Improved prediction of peptide detectability for targeted proteomics using a rank-based algorithm and organism-specific data.

PubMed

Qeli, Ermir; Omasits, Ulrich; Goetze, Sandra; Stekhoven, Daniel J; Frey, Juerg E; Basler, Konrad; Wollscheid, Bernd; Brunner, Erich; Ahrens, Christian H

2014-08-28

The in silico prediction of the best-observable "proteotypic" peptides in mass spectrometry-based workflows is a challenging problem. Being able to accurately predict such peptides would enable the informed selection of proteotypic peptides for targeted quantification of previously observed and non-observed proteins for any organism, with a significant impact for clinical proteomics and systems biology studies. Current prediction algorithms rely on physicochemical parameters in combination with positive and negative training sets to identify those peptide properties that most profoundly affect their general detectability. Here we present PeptideRank, an approach that uses learning to rank algorithm for peptide detectability prediction from shotgun proteomics data, and that eliminates the need to select a negative dataset for the training step. A large number of different peptide properties are used to train ranking models in order to predict a ranking of the best-observable peptides within a protein. Empirical evaluation with rank accuracy metrics showed that PeptideRank complements existing prediction algorithms. Our results indicate that the best performance is achieved when it is trained on organism-specific shotgun proteomics data, and that PeptideRank is most accurate for short to medium-sized and abundant proteins, without any loss in prediction accuracy for the important class of membrane proteins. Targeted proteomics approaches have been gaining a lot of momentum and hold immense potential for systems biology studies and clinical proteomics. However, since only very few complete proteomes have been reported to date, for a considerable fraction of a proteome there is no experimental proteomics evidence that would allow to guide the selection of the best-suited proteotypic peptides (PTPs), i.e. peptides that are specific to a given proteoform and that are repeatedly observed in a mass spectrometer. We describe a novel, rank-based approach for the prediction

Proteome-wide prediction of targets for aspirin: new insight into the molecular mechanism of aspirin

PubMed Central

Dai, Shao-Xing; Li, Wen-Xing

2016-01-01

Besides its anti-inflammatory, analgesic and anti-pyretic properties, aspirin is used for the prevention of cardiovascular disease and various types of cancer. The multiple activities of aspirin likely involve several molecular targets and pathways rather than a single target. Therefore, systematic identification of these targets of aspirin can help us understand the underlying mechanisms of the activities. In this study, we identified 23 putative targets of aspirin in the human proteome by using binding pocket similarity detecting tool combination with molecular docking, free energy calculation and pathway analysis. These targets have diverse folds and are derived from different protein family. However, they have similar aspirin-binding pockets. The binding free energy with aspirin for newly identified targets is comparable to that for the primary targets. Pathway analysis revealed that the targets were enriched in several pathways such as vascular endothelial growth factor (VEGF) signaling, Fc epsilon RI signaling and arachidonic acid metabolism, which are strongly involved in inflammation, cardiovascular disease and cancer. Therefore, the predicted target profile of aspirin suggests a new explanation for the disease prevention ability of aspirin. Our findings provide a new insight of aspirin and its efficacy of disease prevention in a systematic and global view. PMID:26989626

Proteome-wide prediction of targets for aspirin: new insight into the molecular mechanism of aspirin.

PubMed

Dai, Shao-Xing; Li, Wen-Xing; Li, Gong-Hua; Huang, Jing-Fei

2016-01-01

Besides its anti-inflammatory, analgesic and anti-pyretic properties, aspirin is used for the prevention of cardiovascular disease and various types of cancer. The multiple activities of aspirin likely involve several molecular targets and pathways rather than a single target. Therefore, systematic identification of these targets of aspirin can help us understand the underlying mechanisms of the activities. In this study, we identified 23 putative targets of aspirin in the human proteome by using binding pocket similarity detecting tool combination with molecular docking, free energy calculation and pathway analysis. These targets have diverse folds and are derived from different protein family. However, they have similar aspirin-binding pockets. The binding free energy with aspirin for newly identified targets is comparable to that for the primary targets. Pathway analysis revealed that the targets were enriched in several pathways such as vascular endothelial growth factor (VEGF) signaling, Fc epsilon RI signaling and arachidonic acid metabolism, which are strongly involved in inflammation, cardiovascular disease and cancer. Therefore, the predicted target profile of aspirin suggests a new explanation for the disease prevention ability of aspirin. Our findings provide a new insight of aspirin and its efficacy of disease prevention in a systematic and global view.

CPTAC Team Releases Targeted Proteomic Assays for Ovarian Cancer | Office of Cancer Clinical Proteomics Research

Cancer.gov

Pacific Northwest National Laboratory (PNNL) investigators in the Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI), announces the public release of 98 targeted mass spectrometry-based assays for ovarian cancer research studies.  Chosen based on proteogenomic observations from the recently published multi-institutional collaborative project between PNNL and Johns Hopkins University that comprehensively examined the collections of proteins in the tumors of ovarian cancer patients (highlighted in a paper in

Proteomic analysis of Chlorella vulgaris: Potential targets for enhanced lipid accumulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guarnieri, Michael T.; Nag, Ambarish; Yang, Shihui

2013-11-01

Oleaginous microalgae are capable of producing large quantities of fatty acids and triacylglycerides. As such, they are promising feedstocks for the production of biofuels and bioproducts. Genetic strain-engineering strategies offer a means to accelerate the commercialization of algal biofuels by improving the rate and total accumulation of microalgal lipids. However, the industrial potential of these organisms remains to be met, largely due to the incomplete knowledgebase surrounding the mechanisms governing the induction of algal lipid biosynthesis. Such strategies require further elucidation of genes and gene products controlling algal lipid accumulation. In this study, we have set out to examine thesemore » mechanisms and identify novel strain-engineering targets in the oleaginous microalga, Chlorella vulgaris. Comparative shotgun proteomic analyses have identified a number of novel targets, including previously unidentified transcription factors and proteins involved in cell signaling and cell cycle regulation. These results lay the foundation for strain-improvement strategies and demonstrate the power of translational proteomic analysis.« less

Using PeptideAtlas, SRMAtlas and PASSEL – Comprehensive Resources for discovery and targeted proteomics

PubMed Central

Kusebauch, Ulrike; Deutsch, Eric W.; Campbell, David S.; Sun, Zhi; Farrah, Terry; Moritz, Robert L.

2014-01-01

PeptideAtlas, SRMAtlas and PASSEL are web-accessible resources to support discovery and targeted proteomics research. PeptideAtlas is a multi-species compendium of shotgun proteomic data provided by the scientific community, SRMAtlas is a resource of high-quality, complete proteome SRM assays generated in a consistent manner for the targeted identification and quantification of proteins, and PASSEL is a repository that compiles and represents selected reaction monitoring data, all in an easy to use interface. The databases are generated from native mass spectrometry data files that are analyzed in a standardized manner including statistical validation of the results. Each resource offers search functionalities and can be queried by user defined constraints; the query results are provided in tables or are graphically displayed. PeptideAtlas, SRMAtlas and PASSEL are publicly available freely via the website http://www.peptideatlas.org. In this protocol, we describe the use of these resources, we highlight how to submit, search, collate and download data. PMID:24939129

Development and application of a quantitative multiplexed small GTPase activity assay using targeted proteomics.

PubMed

Zhang, Cheng-Cheng; Li, Ru; Jiang, Honghui; Lin, Shujun; Rogalski, Jason C; Liu, Kate; Kast, Juergen

2015-02-06

Small GTPases are a family of key signaling molecules that are ubiquitously expressed in various types of cells. Their activity is often analyzed by western blot, which is limited by its multiplexing capability, the quality of isoform-specific antibodies, and the accuracy of quantification. To overcome these issues, a quantitative multiplexed small GTPase activity assay has been developed. Using four different binding domains, this assay allows the binding of up to 12 active small GTPase isoforms simultaneously in a single experiment. To accurately quantify the closely related small GTPase isoforms, a targeted proteomic approach, i.e., selected/multiple reaction monitoring, was developed, and its functionality and reproducibility were validated. This assay was successfully applied to human platelets and revealed time-resolved coactivation of multiple small GTPase isoforms in response to agonists and differential activation of these isoforms in response to inhibitor treatment. This widely applicable approach can be used for signaling pathway studies and inhibitor screening in many cellular systems.

[Application progress of proteomic in pharmacological study of Chinese medicinal formulae].

PubMed

Liu, Yu-Qian; Zhan, Shu-Yu; Ruan, Yu-Er; Zuo, Zhi-Yan; Ji, Xiao-Ming; Wang, Shuai-Jie; Ding, Bao-Yue

2017-10-01

Chinese medicinal formulae are the important means of clinical treatment in traditional Chinese medicine. It is urgent to use modern advanced scientific and technological means to reveal the complicated mechanism of Chinese medicinal formulae because they have the function characteristics of multiple components, multiple targets and integrated regulation. The systematic and comprehensive research model of proteomic is in line with the function characteristics of Chinese medicinal formulae, and proteomic has been widely used in the study of pharmacological mechanism of Chinese medicinal formulae. The recent applications of proteomic in pharmacological study of Chinese medicinal formulae in anti-cardiovascular and cerebrovascular diseases, anti-liver disease, antidiabetic, anticancer, anti-rheumatoid arthritis and other diseases were reviewed in this paper, and then the future development direction of proteomic in pharmacological study of Chinese medicinal formulae was put forward. This review is to provide the ideas and method for proteomic research on function mechanism of Chinese medicinal formulae. Copyright© by the Chinese Pharmaceutical Association.

Compositional Analysis of Asymmetric and Symmetric Dimethylated H3R2 Using Liquid Chromatography-Tandem Mass Spectrometry-Based Targeted Proteomics.

PubMed

Xu, Qingqing; Xu, Feifei; Liu, Liang; Chen, Yun

2016-09-06

Protein arginine methylation is one of the common post-translational modifications in cellular processes. To date, two isomeric forms of dimethylated arginine have been identified: asymmetric N(G),N(G)-dimethylarginine (aDMA), and symmetric N(G),N'(G)-dimethylarginine (sDMA). Evidence indicated that these isomers can coexist and have different or even opposite functions, with aDMA and sDMA forms of arginine 2 on histone H3 (i.e., H3R2me2a and H3R2me2s) being an example. Thus, specific detection and quantification of each isomeric form is important. Current methods are capable of predicting and detecting thousands of methylarginine sites in proteins, whereas differentiation and stoichiometric measurement of dimethylated protein isomers are still challenging. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)-based targeted proteomics has emerged as a promising technique for site-specific quantification of protein methylation using enzymatic peptides as surrogates of target proteins. However, it should be pointed out that a routine targeted proteomics strategy cannot easily distinguish sDMA- and aDMA-containing surrogate peptides due to their common nature. The estimated amount should be considered as the sum of both arginine dimethylated isomers. In this study, compositional analysis based on a linear algebra algorithm as an add-on to targeted proteomics was employed to quantify H3R2me2a and H3R2me2s (i.e., surrogate peptides of AR(me2a)TK(me1/2)QT and AR(me2s)TK(me1/2)QT). To achieve this simultaneous quantification, a targeted proteomics assay was developed and validated for each isomer first. With the slope and intercept of their calibration curves for each multiple reaction monitoring (MRM) transition, linear algebraic equations were derived. Using a series of mock mixtures consisting of isomers in varying concentrations, the reliability of the method was confirmed. Finally, the H3R2 dimethylation status was analyzed in normal MCF-10A cells

Screening Novel Molecular Targets of Metformin in Breast Cancer by Proteomic Approach

PubMed Central

Al-Zaidan, Lobna; El Ruz, Rasha Abu; Malki, Ahmed M.

2017-01-01

increase the understanding of breast cancer prognosis and permit future studies to examine the effect of metformin on the proteomic pathways against other types of cancers. Finally, it suggests the possibility to develop further therapeutic generations of metformin with increased anticancer effect through targeting specific proteomes. PMID:29085821

Using the CPTAC Assay Portal to identify and implement highly characterized targeted proteomics assays

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whiteaker, Jeffrey R.; Halusa, Goran; Hoofnagle, Andrew N.

2016-02-12

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI) has launched an Assay Portal (http://assays.cancer.gov) to serve as an open-source repository of well-characterized targeted proteomic assays. The portal is designed to curate and disseminate highly characterized, targeted mass spectrometry (MS)-based assays by providing detailed assay performance characterization data, standard operating procedures, and access to reagents. Assay content is accessed via the portal through queries to find assays targeting proteins associated with specific cellular pathways, protein complexes, or specific chromosomal regions. The position of the peptide analytes for which there are available assays are mapped relative tomore » other features of interest in the protein, such as sequence domains, isoforms, single nucleotide polymorphisms, and post-translational modifications. The overarching goals are to enable robust quantification of all human proteins and to standardize the quantification of targeted MS-based assays to ultimately enable harmonization of results over time and across laboratories.« less

Using the CPTAC Assay Portal to Identify and Implement Highly Characterized Targeted Proteomics Assays.

PubMed

Whiteaker, Jeffrey R; Halusa, Goran N; Hoofnagle, Andrew N; Sharma, Vagisha; MacLean, Brendan; Yan, Ping; Wrobel, John A; Kennedy, Jacob; Mani, D R; Zimmerman, Lisa J; Meyer, Matthew R; Mesri, Mehdi; Boja, Emily; Carr, Steven A; Chan, Daniel W; Chen, Xian; Chen, Jing; Davies, Sherri R; Ellis, Matthew J C; Fenyö, David; Hiltke, Tara; Ketchum, Karen A; Kinsinger, Chris; Kuhn, Eric; Liebler, Daniel C; Liu, Tao; Loss, Michael; MacCoss, Michael J; Qian, Wei-Jun; Rivers, Robert; Rodland, Karin D; Ruggles, Kelly V; Scott, Mitchell G; Smith, Richard D; Thomas, Stefani; Townsend, R Reid; Whiteley, Gordon; Wu, Chaochao; Zhang, Hui; Zhang, Zhen; Rodriguez, Henry; Paulovich, Amanda G

2016-01-01

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI) has launched an Assay Portal (http://assays.cancer.gov) to serve as an open-source repository of well-characterized targeted proteomic assays. The portal is designed to curate and disseminate highly characterized, targeted mass spectrometry (MS)-based assays by providing detailed assay performance characterization data, standard operating procedures, and access to reagents. Assay content is accessed via the portal through queries to find assays targeting proteins associated with specific cellular pathways, protein complexes, or specific chromosomal regions. The position of the peptide analytes for which there are available assays are mapped relative to other features of interest in the protein, such as sequence domains, isoforms, single nucleotide polymorphisms, and posttranslational modifications. The overarching goals are to enable robust quantification of all human proteins and to standardize the quantification of targeted MS-based assays to ultimately enable harmonization of results over time and across laboratories.

Matrix metalloproteinase proteomics: substrates, targets, and therapy.

PubMed

Morrison, Charlotte J; Butler, Georgina S; Rodríguez, David; Overall, Christopher M

2009-10-01

Proteomics encompasses powerful techniques termed 'degradomics' for unbiased high-throughput protease substrate discovery screens that have been applied to an important family of extracellular proteases, the matrix metalloproteinases (MMPs). Together with the data generated from genetic deletion and transgenic mouse models and genomic profiling, these screens can uncover the diverse range of MMP functions, reveal which MMPs and MMP-mediated pathways exacerbate pathology, and which are involved in protection and the resolution of disease. This information can be used to identify and validate candidate drug targets and antitargets, and is critical for the development of new inhibitors of MMP function. Such inhibitors may target either the MMP directly in a specific manner or pathways upstream and downstream of MMP activity that are mediating deleterious effects in disease. Since MMPs do not operate alone but are part of the 'protease web', it is necessary to use system-wide approaches to understand MMP proteolysis in vivo, to discover new biological roles and their potential for therapeutic modification.

Combining results of multiple search engines in proteomics.

PubMed

Shteynberg, David; Nesvizhskii, Alexey I; Moritz, Robert L; Deutsch, Eric W

2013-09-01

A crucial component of the analysis of shotgun proteomics datasets is the search engine, an algorithm that attempts to identify the peptide sequence from the parent molecular ion that produced each fragment ion spectrum in the dataset. There are many different search engines, both commercial and open source, each employing a somewhat different technique for spectrum identification. The set of high-scoring peptide-spectrum matches for a defined set of input spectra differs markedly among the various search engine results; individual engines each provide unique correct identifications among a core set of correlative identifications. This has led to the approach of combining the results from multiple search engines to achieve improved analysis of each dataset. Here we review the techniques and available software for combining the results of multiple search engines and briefly compare the relative performance of these techniques.

Combining Results of Multiple Search Engines in Proteomics*

PubMed Central

Shteynberg, David; Nesvizhskii, Alexey I.; Moritz, Robert L.; Deutsch, Eric W.

2013-01-01

A crucial component of the analysis of shotgun proteomics datasets is the search engine, an algorithm that attempts to identify the peptide sequence from the parent molecular ion that produced each fragment ion spectrum in the dataset. There are many different search engines, both commercial and open source, each employing a somewhat different technique for spectrum identification. The set of high-scoring peptide-spectrum matches for a defined set of input spectra differs markedly among the various search engine results; individual engines each provide unique correct identifications among a core set of correlative identifications. This has led to the approach of combining the results from multiple search engines to achieve improved analysis of each dataset. Here we review the techniques and available software for combining the results of multiple search engines and briefly compare the relative performance of these techniques. PMID:23720762

Application of targeted proteomics to metabolically engineered Escherichia coli.

PubMed

Singh, Pragya; Batth, Tanveer S; Juminaga, Darmawi; Dahl, Robert H; Keasling, Jay D; Adams, Paul D; Petzold, Christopher J

2012-04-01

As synthetic biology matures to compete with chemical transformation of commodity and high-value compounds, a wide variety of well-characterized biological parts are needed to facilitate system design. Protein quantification based on selected-reaction monitoring (SRM) mass spectrometry compliments metabolite and transcript analysis for system characterization and optimizing flux through engineered pathways. By using SRM quantification, we assayed red fluorescent protein (RFP) expressed from plasmids containing several inducible and constitutive promoters and subsequently assessed protein production from the same promoters driving expression of eight mevalonate pathway proteins in Escherichia coli. For each of the promoter systems, the protein level for the first gene in the operon followed that of RFP, however, the levels of proteins produced from genes farther from the promoter were much less consistent. Second, we used targeted proteomics to characterize tyrosine biosynthesis pathway proteins after removal of native regulation. The changes were not expected to cause significant impact on protein levels, yet significant variation in protein abundance was observed and tyrosine production for these strains spanned a range from less than 1 mg/L to greater than 250 mg/L. Overall, our results underscore the importance of targeted proteomics for determining accurate protein levels in engineered systems and fine-tuning metabolic pathways. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomics meets blood banking: identification of protein targets for the improvement of platelet quality.

PubMed

Schubert, Peter; Devine, Dana V

2010-01-03

Proteomics has brought new perspectives to the fields of hematology and transfusion medicine in the last decade. The steady improvement of proteomic technology is propelling novel discoveries of molecular mechanisms by studying protein expression, post-translational modifications and protein interactions. This review article focuses on the application of proteomics to the identification of molecular mechanisms leading to the deterioration of blood platelets during storage - a critical aspect in the provision of platelet transfusion products. Several proteomic approaches have been employed to analyse changes in the platelet protein profile during storage and the obtained data now need to be translated into platelet biochemistry in order to connect the results to platelet function. Targeted biochemical applications then allow the identification of points for intervention in signal transduction pathways. Once validated and placed in a transfusion context, these data will provide further understanding of the underlying molecular mechanisms leading to platelet storage lesion. Future aspects of proteomics in blood banking will aim to make use of protein markers identified for platelet storage lesion development to monitor proteome changes when alterations such as the use of additive solutions or pathogen reduction strategies are put in place in order to improve platelet quality for patients. (c) 2009 Elsevier B.V. All rights reserved.

Targeted Data Extraction of the MS/MS Spectra Generated by Data-independent Acquisition: A New Concept for Consistent and Accurate Proteome Analysis*

PubMed Central

Gillet, Ludovic C.; Navarro, Pedro; Tate, Stephen; Röst, Hannes; Selevsek, Nathalie; Reiter, Lukas; Bonner, Ron; Aebersold, Ruedi

2012-01-01

Most proteomic studies use liquid chromatography coupled to tandem mass spectrometry to identify and quantify the peptides generated by the proteolysis of a biological sample. However, with the current methods it remains challenging to rapidly, consistently, reproducibly, accurately, and sensitively detect and quantify large fractions of proteomes across multiple samples. Here we present a new strategy that systematically queries sample sets for the presence and quantity of essentially any protein of interest. It consists of using the information available in fragment ion spectral libraries to mine the complete fragment ion maps generated using a data-independent acquisition method. For this study, the data were acquired on a fast, high resolution quadrupole-quadrupole time-of-flight (TOF) instrument by repeatedly cycling through 32 consecutive 25-Da precursor isolation windows (swaths). This SWATH MS acquisition setup generates, in a single sample injection, time-resolved fragment ion spectra for all the analytes detectable within the 400–1200 m/z precursor range and the user-defined retention time window. We show that suitable combinations of fragment ions extracted from these data sets are sufficiently specific to confidently identify query peptides over a dynamic range of 4 orders of magnitude, even if the precursors of the queried peptides are not detectable in the survey scans. We also show that queried peptides are quantified with a consistency and accuracy comparable with that of selected reaction monitoring, the gold standard proteomic quantification method. Moreover, targeted data extraction enables ad libitum quantification refinement and dynamic extension of protein probing by iterative re-mining of the once-and-forever acquired data sets. This combination of unbiased, broad range precursor ion fragmentation and targeted data extraction alleviates most constraints of present proteomic methods and should be equally applicable to the comprehensive

PACOM: A Versatile Tool for Integrating, Filtering, Visualizing, and Comparing Multiple Large Mass Spectrometry Proteomics Data Sets.

PubMed

Martínez-Bartolomé, Salvador; Medina-Aunon, J Alberto; López-García, Miguel Ángel; González-Tejedo, Carmen; Prieto, Gorka; Navajas, Rosana; Salazar-Donate, Emilio; Fernández-Costa, Carolina; Yates, John R; Albar, Juan Pablo

2018-04-06

Mass-spectrometry-based proteomics has evolved into a high-throughput technology in which numerous large-scale data sets are generated from diverse analytical platforms. Furthermore, several scientific journals and funding agencies have emphasized the storage of proteomics data in public repositories to facilitate its evaluation, inspection, and reanalysis. (1) As a consequence, public proteomics data repositories are growing rapidly. However, tools are needed to integrate multiple proteomics data sets to compare different experimental features or to perform quality control analysis. Here, we present a new Java stand-alone tool, Proteomics Assay COMparator (PACOM), that is able to import, combine, and simultaneously compare numerous proteomics experiments to check the integrity of the proteomic data as well as verify data quality. With PACOM, the user can detect source of errors that may have been introduced in any step of a proteomics workflow and that influence the final results. Data sets can be easily compared and integrated, and data quality and reproducibility can be visually assessed through a rich set of graphical representations of proteomics data features as well as a wide variety of data filters. Its flexibility and easy-to-use interface make PACOM a unique tool for daily use in a proteomics laboratory. PACOM is available at https://github.com/smdb21/pacom .

A Miniaturized Chemical Proteomic Approach for Target Profiling of Clinical Kinase Inhibitors in Tumor Biopsies

PubMed Central

Chamrád, Ivo; Rix, Uwe; Stukalov, Alexey; Gridling, Manuela; Parapatics, Katja; Müller, André C.; Altiok, Soner; Colinge, Jacques; Superti-Furga, Giulio; Haura, Eric B.; Bennett, Keiryn L.

2014-01-01

While targeted therapy based on the idea of attenuating the activity of a preselected, therapeutically relevant protein has become one of the major trends in modern cancer therapy, no truly specific targeted drug has been developed and most clinical agents have displayed a degree of polypharmacology. Therefore, the specificity of anticancer therapeutics has emerged as a highly important but severely underestimated issue. Chemical proteomics is a powerful technique combining postgenomic drug-affinity chromatography with high-end mass spectrometry analysis and bioinformatic data processing to assemble a target profile of a desired therapeutic molecule. Due to high demands on the starting material, however, chemical proteomic studies have been mostly limited to cancer cell lines. Herein, we report a down-scaling of the technique to enable the analysis of very low abundance samples, as those obtained from needle biopsies. By a systematic investigation of several important parameters in pull-downs with the multikinase inhibitor bosutinib, the standard experimental protocol was optimized to 100 µg protein input. At this level, more than 30 well-known targets were detected per single pull-down replicate with high reproducibility. Moreover, as presented by the comprehensive target profile obtained from miniaturized pull-downs with another clinical drug, dasatinib, the optimized protocol seems to be extendable to other drugs of interest. Sixty distinct human and murine targets were finally identified for bosutinib and dasatinib in chemical proteomic experiments utilizing core needle biopsy samples from xenotransplants derived from patient tumor tissue. Altogether, the developed methodology proves robust and generic and holds many promises for the field of personalized health care. PMID:23901793

Potassium Channel KIR4.1 as an Immune Target in Multiple Sclerosis

PubMed Central

Srivastava, Rajneesh; Aslam, Muhammad; Kalluri, Sudhakar Reddy; Schirmer, Lucas; Buck, Dorothea; Tackenberg, Björn; Rothhammer, Veit; Chan, Andrew; Gold, Ralf; Berthele, Achim; Bennett, Jeffrey L.; Korn, Thomas; Hemmer, Bernhard

2016-01-01

BACKGROUND Multiple sclerosis is a chronic inflammatory demyelinating disease of the central nervous system. Many findings suggest that the disease has an autoimmune pathogenesis; the target of the immune response is not yet known. METHODS We screened serum IgG from persons with multiple sclerosis to identify antibodies that are capable of binding to brain tissue and observed specific binding of IgG to glial cells in a subgroup of patients. Using a proteomic approach focusing on membrane proteins, we identified the ATP-sensitive inward rectifying potassium channel KIR4.1 as the target of the IgG antibodies. We used a multifaceted validation strategy to confirm KIR4.1 as a target of the autoantibody response in multiple sclerosis and to show its potential pathogenicity in vivo. RESULTS Serum levels of antibodies to KIR4.1 were higher in persons with multiple sclerosis than in persons with other neurologic diseases and healthy donors (P<0.001 for both comparisons). We replicated this finding in two independent groups of persons with multiple sclerosis or other neurologic diseases (P<0.001 for both comparisons). Analysis of the combined data sets indicated the presence of serum antibodies to KIR4.1 in 186 of 397 persons with multiple sclerosis (46.9%), in 3 of 329 persons with other neurologic diseases (0.9%), and in none of the 59 healthy donors. These antibodies bound to the first extracellular loop of KIR4.1. Injection of KIR4.1 serum IgG into the cisternae magnae of mice led to a profound loss of KIR4.1 expression, altered expression of glial fibrillary acidic protein in astrocytes, and activation of the complement cascade at sites of KIR4.1 expression in the cerebellum. CONCLUSIONS KIR4.1 is a target of the autoantibody response in a subgroup of persons with multiple sclerosis. (Funded by the German Ministry for Education and Research and Deutsche Forschungsgemeinschaft.) PMID:22784115

Simultaneous quantification of protein phosphorylation sites using liquid chromatography-tandem mass spectrometry-based targeted proteomics: a linear algebra approach for isobaric phosphopeptides.

PubMed

Xu, Feifei; Yang, Ting; Sheng, Yuan; Zhong, Ting; Yang, Mi; Chen, Yun

2014-12-05

As one of the most studied post-translational modifications (PTM), protein phosphorylation plays an essential role in almost all cellular processes. Current methods are able to predict and determine thousands of phosphorylation sites, whereas stoichiometric quantification of these sites is still challenging. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)-based targeted proteomics is emerging as a promising technique for site-specific quantification of protein phosphorylation using proteolytic peptides as surrogates of proteins. However, several issues may limit its application, one of which relates to the phosphopeptides with different phosphorylation sites and the same mass (i.e., isobaric phosphopeptides). While employment of site-specific product ions allows for these isobaric phosphopeptides to be distinguished and quantified, site-specific product ions are often absent or weak in tandem mass spectra. In this study, linear algebra algorithms were employed as an add-on to targeted proteomics to retrieve information on individual phosphopeptides from their common spectra. To achieve this simultaneous quantification, a LC-MS/MS-based targeted proteomics assay was first developed and validated for each phosphopeptide. Given the slope and intercept of calibration curves of phosphopeptides in each transition, linear algebraic equations were developed. Using a series of mock mixtures prepared with varying concentrations of each phosphopeptide, the reliability of the approach to quantify isobaric phosphopeptides containing multiple phosphorylation sites (≥ 2) was discussed. Finally, we applied this approach to determine the phosphorylation stoichiometry of heat shock protein 27 (HSP27) at Ser78 and Ser82 in breast cancer cells and tissue samples.

Hypothalamus proteomics from mouse models with obesity and anorexia reveals therapeutic targets of appetite regulation

PubMed Central

Manousopoulou, A; Koutmani, Y; Karaliota, S; Woelk, C H; Manolakos, E S; Karalis, K; Garbis, S D

2016-01-01

Objective: This study examined the proteomic profile of the hypothalamus in mice exposed to a high-fat diet (HFD) or with the anorexia of acute illness. This comparison could provide insight on the effects of these two opposite states of energy balance on appetite regulation. Methods: Four to six-week-old male C56BL/6J mice were fed a normal (control 1 group; n=7) or a HFD (HFD group; n=10) for 8 weeks. The control 2 (n=7) and lipopolysaccharide (LPS) groups (n=10) were fed a normal diet for 8 weeks before receiving an injection of saline and LPS, respectively. Hypothalamic regions were analysed using a quantitative proteomics method based on a combination of techniques including iTRAQ stable isotope labeling, orthogonal two-dimensional liquid chromatography hyphenated with nanospray ionization and high-resolution mass spectrometry. Key proteins were validated with quantitative PCR. Results: Quantitative proteomics of the hypothalamous regions profiled a total of 9249 protein groups (q<0.05). Of these, 7718 protein groups were profiled with a minimum of two unique peptides for each. Hierachical clustering of the differentiated proteome revealed distinct proteomic signatures for the hypothalamus under the HFD and LPS nutritional conditions. Literature research with in silico bioinformatics interpretation of the differentiated proteome identified key biological relevant proteins and implicated pathways. Furthermore, the study identified potential pharmacologic targets. In the LPS groups, the anorexigen pro-opiomelanocortin was downregulated. In mice with obesity, nuclear factor-κB, glycine receptor subunit alpha-4 (GlyR) and neuropeptide Y levels were elevated, whereas serotonin receptor 1B levels decreased. Conclusions: High-precision quantitative proteomics revealed that under acute systemic inflammation in the hypothalamus as a response to LPS, homeostatic mechanisms mediating loss of appetite take effect. Conversely, under chronic inflammation in the

Hypothalamus proteomics from mouse models with obesity and anorexia reveals therapeutic targets of appetite regulation.

PubMed

Manousopoulou, A; Koutmani, Y; Karaliota, S; Woelk, C H; Manolakos, E S; Karalis, K; Garbis, S D

2016-04-25

This study examined the proteomic profile of the hypothalamus in mice exposed to a high-fat diet (HFD) or with the anorexia of acute illness. This comparison could provide insight on the effects of these two opposite states of energy balance on appetite regulation. Four to six-week-old male C56BL/6J mice were fed a normal (control 1 group; n=7) or a HFD (HFD group; n=10) for 8 weeks. The control 2 (n=7) and lipopolysaccharide (LPS) groups (n=10) were fed a normal diet for 8 weeks before receiving an injection of saline and LPS, respectively. Hypothalamic regions were analysed using a quantitative proteomics method based on a combination of techniques including iTRAQ stable isotope labeling, orthogonal two-dimensional liquid chromatography hyphenated with nanospray ionization and high-resolution mass spectrometry. Key proteins were validated with quantitative PCR. Quantitative proteomics of the hypothalamous regions profiled a total of 9249 protein groups (q<0.05). Of these, 7718 protein groups were profiled with a minimum of two unique peptides for each. Hierachical clustering of the differentiated proteome revealed distinct proteomic signatures for the hypothalamus under the HFD and LPS nutritional conditions. Literature research with in silico bioinformatics interpretation of the differentiated proteome identified key biological relevant proteins and implicated pathways. Furthermore, the study identified potential pharmacologic targets. In the LPS groups, the anorexigen pro-opiomelanocortin was downregulated. In mice with obesity, nuclear factor-κB, glycine receptor subunit alpha-4 (GlyR) and neuropeptide Y levels were elevated, whereas serotonin receptor 1B levels decreased. High-precision quantitative proteomics revealed that under acute systemic inflammation in the hypothalamus as a response to LPS, homeostatic mechanisms mediating loss of appetite take effect. Conversely, under chronic inflammation in the hypothalamus as a response to HFD, mechanisms

ProteinInferencer: Confident protein identification and multiple experiment comparison for large scale proteomics projects.

PubMed

Zhang, Yaoyang; Xu, Tao; Shan, Bing; Hart, Jonathan; Aslanian, Aaron; Han, Xuemei; Zong, Nobel; Li, Haomin; Choi, Howard; Wang, Dong; Acharya, Lipi; Du, Lisa; Vogt, Peter K; Ping, Peipei; Yates, John R

2015-11-03

Shotgun proteomics generates valuable information from large-scale and target protein characterizations, including protein expression, protein quantification, protein post-translational modifications (PTMs), protein localization, and protein-protein interactions. Typically, peptides derived from proteolytic digestion, rather than intact proteins, are analyzed by mass spectrometers because peptides are more readily separated, ionized and fragmented. The amino acid sequences of peptides can be interpreted by matching the observed tandem mass spectra to theoretical spectra derived from a protein sequence database. Identified peptides serve as surrogates for their proteins and are often used to establish what proteins were present in the original mixture and to quantify protein abundance. Two major issues exist for assigning peptides to their originating protein. The first issue is maintaining a desired false discovery rate (FDR) when comparing or combining multiple large datasets generated by shotgun analysis and the second issue is properly assigning peptides to proteins when homologous proteins are present in the database. Herein we demonstrate a new computational tool, ProteinInferencer, which can be used for protein inference with both small- or large-scale data sets to produce a well-controlled protein FDR. In addition, ProteinInferencer introduces confidence scoring for individual proteins, which makes protein identifications evaluable. This article is part of a Special Issue entitled: Computational Proteomics. Copyright © 2015. Published by Elsevier B.V.

Targeted Proteomics Approach for Precision Plant Breeding.

PubMed

Chawade, Aakash; Alexandersson, Erik; Bengtsson, Therese; Andreasson, Erik; Levander, Fredrik

2016-02-05

Selected reaction monitoring (SRM) is a targeted mass spectrometry technique that enables precise quantitation of hundreds of peptides in a single run. This technique provides new opportunities for multiplexed protein biomarker measurements. For precision plant breeding, DNA-based markers have been used extensively, but the potential of protein biomarkers has not been exploited. In this work, we developed an SRM marker panel with assays for 104 potato (Solanum tuberosum) peptides selected using univariate and multivariate statistics. Thereafter, using random forest classification, the prediction markers were identified for Phytopthora infestans resistance in leaves, P. infestans resistance in tubers, and plant yield in potato leaf secretome samples. The results suggest that the marker panel has the predictive potential for three traits, two of which have no commercial DNA markers so far. Furthermore, the marker panel was also tested and found to be applicable to potato clones not used during the marker development. The proposed workflow is thus a proof-of-concept for targeted proteomics as an efficient readout in accelerated breeding for complex and agronomically important traits.

Proteomic Approaches and Identification of Novel Therapeutic Targets for Alcoholism

PubMed Central

Gorini, Giorgio; Adron Harris, R; Dayne Mayfield, R

2014-01-01

Recent studies have shown that gene regulation is far more complex than previously believed and does not completely explain changes at the protein level. Therefore, the direct study of the proteome, considerably different in both complexity and dynamicity to the genome/transcriptome, has provided unique insights to an increasing number of researchers. During the past decade, extraordinary advances in proteomic techniques have changed the way we can analyze the composition, regulation, and function of protein complexes and pathways underlying altered neurobiological conditions. When combined with complementary approaches, these advances provide the contextual information for decoding large data sets into meaningful biologically adaptive processes. Neuroproteomics offers potential breakthroughs in the field of alcohol research by leading to a deeper understanding of how alcohol globally affects protein structure, function, interactions, and networks. The wealth of information gained from these advances can help pinpoint relevant biomarkers for early diagnosis and improved prognosis of alcoholism and identify future pharmacological targets for the treatment of this addiction. PMID:23900301

Multiple shell fusion targets

DOEpatents

Lindl, J.D.; Bangerter, R.O.

1975-10-31

Multiple shell fusion targets for use with electron beam and ion beam implosion systems are described. The multiple shell targets are of the low-power type and use a separate relatively low Z, low density ablator at large radius for the outer shell, which reduces the focusing and power requirements of the implosion system while maintaining reasonable aspect ratios. The targets use a high Z, high density pusher shell placed at a much smaller radius in order to obtain an aspect ratio small enough to protect against fluid instability. Velocity multiplication between these shells further lowers the power requirements. Careful tuning of the power profile and intershell density results in a low entropy implosion which allows breakeven at low powers. For example, with ion beams as a power source, breakeven at 10-20 Terrawatts with 10 MeV alpha particles for imploding a multiple shell target can be accomplished.

Skyline: an open source document editor for creating and analyzing targeted proteomics experiments.

PubMed

MacLean, Brendan; Tomazela, Daniela M; Shulman, Nicholas; Chambers, Matthew; Finney, Gregory L; Frewen, Barbara; Kern, Randall; Tabb, David L; Liebler, Daniel C; MacCoss, Michael J

2010-04-01

Skyline is a Windows client application for targeted proteomics method creation and quantitative data analysis. It is open source and freely available for academic and commercial use. The Skyline user interface simplifies the development of mass spectrometer methods and the analysis of data from targeted proteomics experiments performed using selected reaction monitoring (SRM). Skyline supports using and creating MS/MS spectral libraries from a wide variety of sources to choose SRM filters and verify results based on previously observed ion trap data. Skyline exports transition lists to and imports the native output files from Agilent, Applied Biosystems, Thermo Fisher Scientific and Waters triple quadrupole instruments, seamlessly connecting mass spectrometer output back to the experimental design document. The fast and compact Skyline file format is easily shared, even for experiments requiring many sample injections. A rich array of graphs displays results and provides powerful tools for inspecting data integrity as data are acquired, helping instrument operators to identify problems early. The Skyline dynamic report designer exports tabular data from the Skyline document model for in-depth analysis with common statistical tools. Single-click, self-updating web installation is available at http://proteome.gs.washington.edu/software/skyline. This web site also provides access to instructional videos, a support board, an issues list and a link to the source code project.

Chemical proteomics reveals HSP70 1A as a target for the anticancer diterpene oridonin in Jurkat cells.

PubMed

Dal Piaz, Fabrizio; Cotugno, Roberta; Lepore, Laura; Vassallo, Antonio; Malafronte, Nicola; Lauro, Gianluigi; Bifulco, Giuseppe; Belisario, Maria Antonietta; De Tommasi, Nunziatina

2013-04-26

Oridonin, an ent-kaurane diterpene isolated from well known Chinese medicinal plant Isodon rubescens, has been shown to have multiple biological activities. Among them, the anticancer activity has been repeatedly reported by many research groups. The chemopreventive and antitumor effects of oridonin have been related to its ability to interfere with several pathways which are involved in cell proliferation, cell cycle arrest, apoptosis and/or autophagy. Despite the number of studies performed on this diterpene, the molecular mechanism underlying its cellular activity remains to be elucidated. Hence, we tried to mine target protein(s) of oridonin by employing a mass spectrometry-based chemical proteomics approach, providing evidences that oridonin is able to directly bind the multifunctional, stress-inducible heat shock protein 70 1A (HSP70 1A). Oridonin/HSP70 complex formation was confirmed in leukemia-derived Jurkat cells. The characterization of HSP70 inhibition by oridonin was performed using chemical and biological approaches. Moreover, the binding site of oridonin on the chaperone was identified by a mass-based approach combined with Molecular Dynamics simulations. Although natural products showed high efficiency and several of these agents have now entered in clinical trials, information concerning the mechanisms of action at a molecular level of many of them is very poor or completely missed. Nevertheless, the identification of the molecular target of a drug candidate has several advantages. The most significant is the ability to set up target-based assays and to allow structure-activity relationship studies to guide medicinal chemistry efforts towards lead optimization. The knowledge of drug targets can also facilitate the identification of potential toxicities or side effects, if there is any precedent of toxicities for the identified target. Achieving this in an effective, unbiased and efficient manner subsists as a significant challenge for the new era

Corra: Computational framework and tools for LC-MS discovery and targeted mass spectrometry-based proteomics

PubMed Central

Brusniak, Mi-Youn; Bodenmiller, Bernd; Campbell, David; Cooke, Kelly; Eddes, James; Garbutt, Andrew; Lau, Hollis; Letarte, Simon; Mueller, Lukas N; Sharma, Vagisha; Vitek, Olga; Zhang, Ning; Aebersold, Ruedi; Watts, Julian D

2008-01-01

Background Quantitative proteomics holds great promise for identifying proteins that are differentially abundant between populations representing different physiological or disease states. A range of computational tools is now available for both isotopically labeled and label-free liquid chromatography mass spectrometry (LC-MS) based quantitative proteomics. However, they are generally not comparable to each other in terms of functionality, user interfaces, information input/output, and do not readily facilitate appropriate statistical data analysis. These limitations, along with the array of choices, present a daunting prospect for biologists, and other researchers not trained in bioinformatics, who wish to use LC-MS-based quantitative proteomics. Results We have developed Corra, a computational framework and tools for discovery-based LC-MS proteomics. Corra extends and adapts existing algorithms used for LC-MS-based proteomics, and statistical algorithms, originally developed for microarray data analyses, appropriate for LC-MS data analysis. Corra also adapts software engineering technologies (e.g. Google Web Toolkit, distributed processing) so that computationally intense data processing and statistical analyses can run on a remote server, while the user controls and manages the process from their own computer via a simple web interface. Corra also allows the user to output significantly differentially abundant LC-MS-detected peptide features in a form compatible with subsequent sequence identification via tandem mass spectrometry (MS/MS). We present two case studies to illustrate the application of Corra to commonly performed LC-MS-based biological workflows: a pilot biomarker discovery study of glycoproteins isolated from human plasma samples relevant to type 2 diabetes, and a study in yeast to identify in vivo targets of the protein kinase Ark1 via phosphopeptide profiling. Conclusion The Corra computational framework leverages computational innovation to

Identification of Tengfu Jiangya Tablet Target Biomarkers with Quantitative Proteomic Technique

PubMed Central

Xu, Jingwen; Zhang, Shijun; Jiang, Haiqiang; Wang, Nan; Lin, Haiqing

2017-01-01

Tengfu Jiangya Tablet (TJT) is a well accepted antihypertension drug in China and its major active components were Uncaria total alkaloids and Semen Raphani soluble alkaloid. To further explore treatment effects mechanism of TJT on essential hypertension, a serum proteomic study was performed. Potential biomarkers were quantified in serum of hypertension individuals before and after taking TJT with isobaric tags for relative and absolute quantitation (iTRAQ) coupled two-dimensional liquid chromatography followed electrospray ionization-tandem mass spectrometry (2D LC-MS/MS) proteomics technique. Among 391 identified proteins with high confidence, 70 proteins were differentially expressed (fold variation criteria, >1.2 or <0.83) between two groups (39 upregulated and 31 downregulated). Combining with Gene Ontology annotation, KEGG pathway analysis, and literature retrieval, 5 proteins were chosen as key target biomarkers during TJT therapeutic process. And the alteration profiles of these 5 proteins were verified by ELISA and Western Blot. Proteins Kininogen 1 and Keratin 1 are members of Kallikrein system, while Myeloperoxidase, Serum Amyloid protein A, and Retinol binding protein 4 had been reported closely related to vascular endothelial injury. Our study discovered 5 target biomarkers of the compound Chinese medicine TJT. Secondly, this research initially revealed the antihypertension therapeutic mechanism of this drug from a brand-new aspect. PMID:28408942

Multiplexed targeted proteomic assay to assess coagulation factor concentrations and thrombosis-associated cancer

PubMed Central

van Vlijmen, Bart J.; Yang, Juncong; Percy, Andrew J.

2017-01-01

The plasma levels of pro- and anticoagulant proteins are important markers for venous thrombosis (VT) risk and can be affected by both genetic and acquired factors, including cancer. Generally, these markers are measured using activity- or antibody-based assays. Targeted proteomics with stable-isotope–labeled internal standards has proven adept at the rapid, multiplex, and precise quantification of proteins in complex biological samples such as plasma. We used liquid chromatography coupled to multiple reaction monitoring (MRM) mass spectrometry to evaluate the concentrations of 31 coagulation- and fibrinolysis-related proteins in plasma from 25 healthy controls, 25 patients with VT, and 25 patients with VT who were also diagnosed with cancer. The concentration level of 1 to 3 proteotypic peptides per protein was determined, and all samples were previously characterized using traditional antibody- or activity-based methods. When comparing the conventional and the MRM strategies, the mean Pearson correlation for the 13 proteins (covered by 36 target peptides) shared between the 2 approaches was 0.77, indicating a good correlation. Additionally, MRM offers higher sensitivity (mean regression slope, 0.81), higher multiplicity in a single run, and good ability to leverage all measurements to discriminate groups using unsupervised clustering, which identified vitamin K antagonist users as well as patients with VT and cancer. The data collected using MRM show that the combination of coagulation factor levels yields signature information on VT and cancer, which was not obvious from a single measurement. These results encourage the further validation and investigation of MRM in profiling protein signature of disease. PMID:29296750

Refining comparative proteomics by spectral counting to account for shared peptides and multiple search engines

PubMed Central

Chen, Yao-Yi; Dasari, Surendra; Ma, Ze-Qiang; Vega-Montoto, Lorenzo J.; Li, Ming

2013-01-01

Spectral counting has become a widely used approach for measuring and comparing protein abundance in label-free shotgun proteomics. However, when analyzing complex samples, the ambiguity of matching between peptides and proteins greatly affects the assessment of peptide and protein inventories, differentiation, and quantification. Meanwhile, the configuration of database searching algorithms that assign peptides to MS/MS spectra may produce different results in comparative proteomic analysis. Here, we present three strategies to improve comparative proteomics through spectral counting. We show that comparing spectral counts for peptide groups rather than for protein groups forestalls problems introduced by shared peptides. We demonstrate the advantage and flexibility of this new method in two datasets. We present four models to combine four popular search engines that lead to significant gains in spectral counting differentiation. Among these models, we demonstrate a powerful vote counting model that scales well for multiple search engines. We also show that semi-tryptic searching outperforms tryptic searching for comparative proteomics. Overall, these techniques considerably improve protein differentiation on the basis of spectral count tables. PMID:22552787

Refining comparative proteomics by spectral counting to account for shared peptides and multiple search engines.

PubMed

Chen, Yao-Yi; Dasari, Surendra; Ma, Ze-Qiang; Vega-Montoto, Lorenzo J; Li, Ming; Tabb, David L

2012-09-01

Spectral counting has become a widely used approach for measuring and comparing protein abundance in label-free shotgun proteomics. However, when analyzing complex samples, the ambiguity of matching between peptides and proteins greatly affects the assessment of peptide and protein inventories, differentiation, and quantification. Meanwhile, the configuration of database searching algorithms that assign peptides to MS/MS spectra may produce different results in comparative proteomic analysis. Here, we present three strategies to improve comparative proteomics through spectral counting. We show that comparing spectral counts for peptide groups rather than for protein groups forestalls problems introduced by shared peptides. We demonstrate the advantage and flexibility of this new method in two datasets. We present four models to combine four popular search engines that lead to significant gains in spectral counting differentiation. Among these models, we demonstrate a powerful vote counting model that scales well for multiple search engines. We also show that semi-tryptic searching outperforms tryptic searching for comparative proteomics. Overall, these techniques considerably improve protein differentiation on the basis of spectral count tables.

Prioritization of potential drug targets against P. aeruginosa by core proteomic analysis using computational subtractive genomics and Protein-Protein interaction network.

PubMed

Uddin, Reaz; Jamil, Faiza

2018-06-01

Pseudomonas aeruginosa is an opportunistic gram-negative bacterium that has the capability to acquire resistance under hostile conditions and become a threat worldwide. It is involved in nosocomial infections. In the current study, potential novel drug targets against P. aeruginosa have been identified using core proteomic analysis and Protein-Protein Interactions (PPIs) studies. The non-redundant reference proteome of 68 strains having complete genome and latest assembly version of P. aeruginosa were downloaded from ftp NCBI RefSeq server in October 2016. The standalone CD-HIT tool was used to cluster ortholog proteins (having >=80% amino acid identity) present in all strains. The pan-proteome was clustered in 12,380 Clusters of Orthologous Proteins (COPs). By using in-house shell scripts, 3252 common COPs were extracted out and designated as clusters of core proteome. The core proteome of PAO1 strain was selected by fetching PAO1's proteome from common COPs. As a result, 1212 proteins were shortlisted that are non-homologous to the human but essential for the survival of the pathogen. Among these 1212 proteins, 321 proteins are conserved hypothetical proteins. Considering their potential as drug target, those 321 hypothetical proteins were selected and their probable functions were characterized. Based on the druggability criteria, 18 proteins were shortlisted. The interacting partners were identified by investigating the PPIs network using STRING v10 database. Subsequently, 8 proteins were shortlisted as 'hub proteins' and proposed as potential novel drug targets against P. aeruginosa. The study is interesting for the scientific community working to identify novel drug targets against MDR pathogens particularly P. aeruginosa. Copyright © 2018 Elsevier Ltd. All rights reserved.

Skyline: an open source document editor for creating and analyzing targeted proteomics experiments

PubMed Central

MacLean, Brendan; Tomazela, Daniela M.; Shulman, Nicholas; Chambers, Matthew; Finney, Gregory L.; Frewen, Barbara; Kern, Randall; Tabb, David L.; Liebler, Daniel C.; MacCoss, Michael J.

2010-01-01

Summary: Skyline is a Windows client application for targeted proteomics method creation and quantitative data analysis. It is open source and freely available for academic and commercial use. The Skyline user interface simplifies the development of mass spectrometer methods and the analysis of data from targeted proteomics experiments performed using selected reaction monitoring (SRM). Skyline supports using and creating MS/MS spectral libraries from a wide variety of sources to choose SRM filters and verify results based on previously observed ion trap data. Skyline exports transition lists to and imports the native output files from Agilent, Applied Biosystems, Thermo Fisher Scientific and Waters triple quadrupole instruments, seamlessly connecting mass spectrometer output back to the experimental design document. The fast and compact Skyline file format is easily shared, even for experiments requiring many sample injections. A rich array of graphs displays results and provides powerful tools for inspecting data integrity as data are acquired, helping instrument operators to identify problems early. The Skyline dynamic report designer exports tabular data from the Skyline document model for in-depth analysis with common statistical tools. Availability: Single-click, self-updating web installation is available at http://proteome.gs.washington.edu/software/skyline. This web site also provides access to instructional videos, a support board, an issues list and a link to the source code project. Contact: brendanx@u.washington.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20147306

Technological advances and proteomic applications in drug discovery and target deconvolution: identification of the pleiotropic effects of statins.

PubMed

Banfi, Cristina; Baetta, Roberta; Gianazza, Erica; Tremoli, Elena

2017-06-01

Proteomic-based techniques provide a powerful tool for identifying the full spectrum of protein targets of a drug, elucidating its mechanism(s) of action, and identifying biomarkers of its efficacy and safety. Herein, we outline the technological advancements in the field, and illustrate the contribution of proteomics to the definition of the pharmacological profile of statins, which represent the cornerstone of the prevention and treatment of cardiovascular diseases (CVDs). Statins act by inhibiting 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase, thus reducing cholesterol biosynthesis and consequently enhancing the clearance of low-density lipoproteins from the blood; however, HMG-CoA reductase inhibition can result in a multitude of additional effects beyond lipid lowering, known as 'pleiotropic effects'. The case of statins highlights the unique contribution of proteomics to the target profiling of a drug molecule. Copyright © 2017 Elsevier Ltd. All rights reserved.

NCI Launches Proteomics Assay Portal | Office of Cancer Clinical Proteomics Research

Cancer.gov

In a paper recently published by the journal Nature Methods, Investigators from the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (NCI-CPTAC) announced the launch of a proteomics Assay Portal for multiple reaction monitoring-mass spectrometry (MRM-MS) assays.  This community web-based repository for well-characterized quantitative proteomic assays currently consists of 456 unique peptide assays to 282 unique proteins and ser

Improved Quantitative Plant Proteomics via the Combination of Targeted and Untargeted Data Acquisition

PubMed Central

Hart-Smith, Gene; Reis, Rodrigo S.; Waterhouse, Peter M.; Wilkins, Marc R.

2017-01-01

Quantitative proteomics strategies – which are playing important roles in the expanding field of plant molecular systems biology – are traditionally designated as either hypothesis driven or non-hypothesis driven. Many of these strategies aim to select individual peptide ions for tandem mass spectrometry (MS/MS), and to do this mixed hypothesis driven and non-hypothesis driven approaches are theoretically simple to implement. In-depth investigations into the efficacies of such approaches have, however, yet to be described. In this study, using combined samples of unlabeled and metabolically 15N-labeled Arabidopsis thaliana proteins, we investigate the mixed use of targeted data acquisition (TDA) and data dependent acquisition (DDA) – referred to as TDA/DDA – to facilitate both hypothesis driven and non-hypothesis driven quantitative data collection in individual LC-MS/MS experiments. To investigate TDA/DDA for hypothesis driven data collection, 7 miRNA target proteins of differing size and abundance were targeted using inclusion lists comprised of 1558 m/z values, using 3 different TDA/DDA experimental designs. In samples in which targeted peptide ions were of particularly low abundance (i.e., predominantly only marginally above mass analyser detection limits), TDA/DDA produced statistically significant increases in the number of targeted peptides identified (230 ± 8 versus 80 ± 3 for DDA; p = 1.1 × 10-3) and quantified (35 ± 3 versus 21 ± 2 for DDA; p = 0.038) per experiment relative to the use of DDA only. These expected improvements in hypothesis driven data collection were observed alongside unexpected improvements in non-hypothesis driven data collection. Untargeted peptide ions with m/z values matching those in inclusion lists were repeatedly identified and quantified across technical replicate TDA/DDA experiments, resulting in significant increases in the percentages of proteins repeatedly quantified in TDA/DDA experiments only relative to DDA

Targeted proteomic assays for quantitation of proteins identified by proteogenomic analysis of ovarian cancer

DOE PAGES

Song, Ehwang; Gao, Yuqian; Wu, Chaochao; ...

2017-07-19

Here, mass spectrometry (MS) based targeted proteomic methods such as selected reaction monitoring (SRM) are becoming the method of choice for preclinical verification of candidate protein biomarkers. The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute has investigated the standardization and analytical validation of the SRM assays and demonstrated robust analytical performance on different instruments across different laboratories. An Assay Portal has also been established by CPTAC to provide the research community a resource consisting of large set of targeted MS-based assays, and a depository to share assays publicly, providing that assays meet the guidelines proposed bymore » CPTAC. Herein, we report 98 SRM assays covering 70 candidate protein biomarkers previously reported as associated with ovarian cancer that have been thoroughly characterized according to the CPTAC Assay Characterization Guidance Document. The experiments, methods and results for characterizing these SRM assays for their MS response, repeatability, selectivity, stability, and reproducible detection of endogenous analytes are described in detail.« less

Core Proteomic Analysis of Unique Metabolic Pathways of Salmonella enterica for the Identification of Potential Drug Targets.

PubMed

Uddin, Reaz; Sufian, Muhammad

2016-01-01

Infections caused by Salmonella enterica, a Gram-negative facultative anaerobic bacteria belonging to the family of Enterobacteriaceae, are major threats to the health of humans and animals. The recent availability of complete genome data of pathogenic strains of the S. enterica gives new avenues for the identification of drug targets and drug candidates. We have used the genomic and metabolic pathway data to identify pathways and proteins essential to the pathogen and absent from the host. We took the whole proteome sequence data of 42 strains of S. enterica and Homo sapiens along with KEGG-annotated metabolic pathway data, clustered proteins sequences using CD-HIT, identified essential genes using DEG database and discarded S. enterica homologs of human proteins in unique metabolic pathways (UMPs) and characterized hypothetical proteins with SVM-prot and InterProScan. Through this core proteomic analysis we have identified enzymes essential to the pathogen. The identification of 73 enzymes common in 42 strains of S. enterica is the real strength of the current study. We proposed all 73 unexplored enzymes as potential drug targets against the infections caused by the S. enterica. The study is comprehensive around S. enterica and simultaneously considered every possible pathogenic strain of S. enterica. This comprehensiveness turned the current study significant since, to the best of our knowledge it is the first subtractive core proteomic analysis of the unique metabolic pathways applied to any pathogen for the identification of drug targets. We applied extensive computational methods to shortlist few potential drug targets considering the druggability criteria e.g. Non-homologous to the human host, essential to the pathogen and playing significant role in essential metabolic pathways of the pathogen (i.e. S. enterica). In the current study, the subtractive proteomics through a novel approach was applied i.e. by considering only proteins of the unique metabolic

Multiple myeloma phosphotyrosine proteomic profile associated with FGFR3 expression, ligand activation, and drug inhibition

PubMed Central

St-Germain, Jonathan R.; Taylor, Paul; Tong, Jiefei; Jin, Lily L.; Nikolic, Ana; Stewart, Ian I.; Ewing, Robert M.; Dharsee, Moyez; Li, Zhihua; Trudel, Suzanne; Moran, Michael F.

2009-01-01

Signaling by growth factor receptor tyrosine kinases is manifest through networks of proteins that are substrates and/or bind to the activated receptors. FGF receptor-3 (FGFR3) is a drug target in a subset of human multiple myelomas (MM) and is mutationally activated in some cervical and colon and many bladder cancers and in certain skeletal dysplasias. To define the FGFR3 network in multiple myeloma, mass spectrometry was used to identify and quantify phosphotyrosine (pY) sites modulated by FGFR3 activation and inhibition in myeloma-derived KMS11 cells. Label-free quantification of peptide ion currents indicated the activation of FGFR3 by phosphorylation of tandem tyrosines in the kinase domain activation loop when cellular pY phosphatases were inhibited by pervanadate. Among the 175 proteins that accumulated pY in response to pervanadate was a subset of 52 including FGFR3 that contained a total of 61 pY sites that were sensitive to inhibition by the FGFR3 inhibitor PD173074. The FGFR3 isoform containing the tandem pY motif in its activation loop was targeted by PD173074. Forty of the drug-sensitive pY sites, including two located within the 35-residue cytoplasmic domain of the transmembrane growth factor binding proteoglycan (and multiple myeloma biomarker) Syndecan-1/CD138, were also stimulated in cells treated with the ligand FGF1, providing additional validation of their link to FGFR3. The identification of these overlapping sets of co-modulated tyrosine phosphorylations presents an outline of an FGFR3 network in the MM model and demonstrates the potential for pharmacodynamic monitoring by label-free quantitative phospho-proteomics. PMID:19901323

Differential proteomics of human seminal plasma: A potential target for searching male infertility marker proteins.

PubMed

Tomar, Anil Kumar; Sooch, Balwinder Singh; Singh, Sarman; Yadav, Savita

2012-04-01

The clinical fertility tests, available in the market, fail to define the exact cause of male infertility in almost half of the cases and point toward a crucial need of developing better ways of infertility investigations. The protein biomarkers may help us toward better understanding of unknown cases of male infertility that, in turn, can guide us to find better therapeutic solutions. Many clinical attempts have been made to identify biomarkers of male infertility in sperm proteome but only few studies have targeted seminal plasma. Human seminal plasma is a rich source of proteins that are essentially required for development of sperm and successful fertilization. This viewpoint article highlights the importance of human seminal plasma proteome in reproductive physiology and suggests that differential proteomics integrated with functional analysis may help us in searching potential biomarkers of male infertility. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Supramolecular Affinity Chromatography for Methylation-Targeted Proteomics.

PubMed

Garnett, Graham A E; Starke, Melissa J; Shaurya, Alok; Li, Janessa; Hof, Fraser

2016-04-05

Proteome-wide studies of post-translationally methylated species using mass spectrometry are complicated by high sample diversity, competition for ionization among peptides, and mass redundancies. Antibody-based enrichment has powered methylation proteomics until now, but the reliability, pan-specificity, polyclonal nature, and stability of the available pan-specific antibodies are problematic and do not provide a standard, reliable platform for investigators. We have invented an anionic supramolecular host that can form host-guest complexes selectively with methyllysine-containing peptides and used it to create a methylysine-affinity column. The column resolves peptides on the basis of methylation-a feat impossible with a comparable commercial cation-exchange column. A proteolyzed nuclear extract was separated on the methyl-affinity column prior to standard proteomics analysis. This experiment demonstrates that such chemical methyl-affinity columns are capable of enriching and improving the analysis of methyllysine residues from complex protein mixtures. We discuss the importance of this advance in the context of biomolecule-driven enrichment methods.

Rapid detection of proteins in transgenic crops without protein reference standards by targeted proteomic mass spectrometry.

PubMed

Schacherer, Lindsey J; Xie, Weiping; Owens, Michaela A; Alarcon, Clara; Hu, Tiger X

2016-09-01

Liquid chromatography coupled with tandem mass spectrometry is increasingly used for protein detection for transgenic crops research. Currently this is achieved with protein reference standards which may take a significant time or efforts to obtain and there is a need for rapid protein detection without protein reference standards. A sensitive and specific method was developed to detect target proteins in transgenic maize leaf crude extract at concentrations as low as ∼30 ng mg(-1) dry leaf without the need of reference standards or any sample enrichment. A hybrid Q-TRAP mass spectrometer was used to monitor all potential tryptic peptides of the target proteins in both transgenic and non-transgenic samples. The multiple reaction monitoring-initiated detection and sequencing (MIDAS) approach was used for initial peptide/protein identification via Mascot database search. Further confirmation was achieved by direct comparison between transgenic and non-transgenic samples. Definitive confirmation was provided by running the same experiments of synthetic peptides or protein standards, if available. A targeted proteomic mass spectrometry method using MIDAS approach is an ideal methodology for detection of new proteins in early stages of transgenic crop research and development when neither protein reference standards nor antibodies are available. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Proteome complexity and the forces that drive proteome imbalance.

PubMed

Harper, J Wade; Bennett, Eric J

2016-09-15

The cellular proteome is a complex microcosm of structural and regulatory networks that requires continuous surveillance and modification to meet the dynamic needs of the cell. It is therefore crucial that the protein flux of the cell remains in balance to ensure proper cell function. Genetic alterations that range from chromosome imbalance to oncogene activation can affect the speed, fidelity and capacity of protein biogenesis and degradation systems, which often results in proteome imbalance. An improved understanding of the causes and consequences of proteome imbalance is helping to reveal how these systems can be targeted to treat diseases such as cancer.

University of Victoria Genome British Columbia Proteomics Centre Partners with CPTAC | Office of Cancer Clinical Proteomics Research

Cancer.gov

University of Victoria Genome British Columbia Proteomics Centre, a leader in proteomic technology development, has partnered with the U.S. National Cancer Institute (NCI) to make targeted proteomic assays accessible to the community through NCI’s CPTAC Assay Portal (https://assays.cancer.gov).

Evolution of Clinical Proteomics and its Role in Medicine | Office of Cancer Clinical Proteomics Research

Cancer.gov

NCI's Office of Cancer Clinical Proteomics Research authored a review of the current state of clinical proteomics in the peer-reviewed Journal of Proteome Research. The review highlights outcomes from the CPTC program and also provides a thorough overview of the different technologies that have pushed the field forward. Additionally, the review provides a vision for moving the field forward through linking advances in genomic and proteomic analysis to develop new, molecularly targeted interventions.

Highly multiplexed targeted proteomics using precise control of peptide retention time.

PubMed

Gallien, Sebastien; Peterman, Scott; Kiyonami, Reiko; Souady, Jamal; Duriez, Elodie; Schoen, Alan; Domon, Bruno

2012-04-01

Large-scale proteomics applications using SRM analysis on triple quadrupole mass spectrometers present new challenges to LC-MS/MS experimental design. Despite the automation of building large-scale LC-SRM methods, the increased numbers of targeted peptides can compromise the balance between sensitivity and selectivity. To facilitate large target numbers, time-scheduled SRM transition acquisition is performed. Previously published results have demonstrated incorporation of a well-characterized set of synthetic peptides enabled chromatographic characterization of the elution profile for most endogenous peptides. We have extended this application of peptide trainer kits to not only build SRM methods but to facilitate real-time elution profile characterization that enables automated adjustment of the scheduled detection windows. Incorporation of dynamic retention time adjustments better facilitate targeted assays lasting several days without the need for constant supervision. This paper provides an overview of how the dynamic retention correction approach identifies and corrects for commonly observed LC variations. This adjustment dramatically improves robustness in targeted discovery experiments as well as routine quantification experiments. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Current advances in esophageal cancer proteomics.

PubMed

Uemura, Norihisa; Kondo, Tadashi

2015-06-01

We review the current status of proteomics for esophageal cancer (EC) from a clinician's viewpoint. The ultimate goal of cancer proteomics is the improvement of clinical outcome. The proteome as a functional translation of the genome is a straightforward representation of genomic mechanisms that trigger carcinogenesis. Cancer proteomics has identified the mechanisms of carcinogenesis and tumor progression, detected biomarker candidates for early diagnosis, and provided novel therapeutic targets for personalized treatments. Our review focuses on three major topics in EC proteomics: diagnostics, treatment, and molecular mechanisms. We discuss the major histological differences between EC types, i.e., esophageal squamous cell carcinoma and adenocarcinoma, and evaluate the clinical significance of published proteomics studies, including promising diagnostic biomarkers and novel therapeutic targets, which should be further validated prior to launching clinical trials. Multi-disciplinary collaborations between basic scientists, clinicians, and pathologists should be established for inter-institutional validation. In conclusion, EC proteomics has provided significant results, which after thorough validation, should lead to the development of novel clinical tools and improvement of the clinical outcome for esophageal cancer patients. This article is part of a Special Issue entitled: Medical Proteomics. Copyright © 2014 Elsevier B.V. All rights reserved.

Targeted Feature Detection for Data-Dependent Shotgun Proteomics.

PubMed

Weisser, Hendrik; Choudhary, Jyoti S

2017-08-04

Label-free quantification of shotgun LC-MS/MS data is the prevailing approach in quantitative proteomics but remains computationally nontrivial. The central data analysis step is the detection of peptide-specific signal patterns, called features. Peptide quantification is facilitated by associating signal intensities in features with peptide sequences derived from MS2 spectra; however, missing values due to imperfect feature detection are a common problem. A feature detection approach that directly targets identified peptides (minimizing missing values) but also offers robustness against false-positive features (by assigning meaningful confidence scores) would thus be highly desirable. We developed a new feature detection algorithm within the OpenMS software framework, leveraging ideas and algorithms from the OpenSWATH toolset for DIA/SRM data analysis. Our software, FeatureFinderIdentification ("FFId"), implements a targeted approach to feature detection based on information from identified peptides. This information is encoded in an MS1 assay library, based on which ion chromatogram extraction and detection of feature candidates are carried out. Significantly, when analyzing data from experiments comprising multiple samples, our approach distinguishes between "internal" and "external" (inferred) peptide identifications (IDs) for each sample. On the basis of internal IDs, two sets of positive (true) and negative (decoy) feature candidates are defined. A support vector machine (SVM) classifier is then trained to discriminate between the sets and is subsequently applied to the "uncertain" feature candidates from external IDs, facilitating selection and confidence scoring of the best feature candidate for each peptide. This approach also enables our algorithm to estimate the false discovery rate (FDR) of the feature selection step. We validated FFId based on a public benchmark data set, comprising a yeast cell lysate spiked with protein standards that provide a known

Dihydrolipoyl dehydrogenase as a potential UVB target in skin epidermis; using an integrated approach of label-free quantitative proteomics and targeted metabolite analysis.

PubMed

Moon, Eunjung; Park, Hye Min; Lee, Choong Hwan; Do, Seon-Gil; Park, Jong-Moon; Han, Na-Young; Do, Moon Ho; Lee, Jong Ha; Lee, Hookeun; Kim, Sun Yeou

2015-03-18

Photodamage is extrinsically induced by overexposure to ultraviolet (UV) radiation, and it increases the risk of various skin disorders. Therefore, discovery of novel biomarkers of photodamage is important. In this study, using LC-MS/MS analysis of epidermis from UVB-irradiated hairless mice, we identified 57 proteins whose levels changed after UVB exposure, and selected 7 proteins related to the tricarboxylic acid (TCA) cycle through pathway analysis. Dihydrolipoyl dehydrogenase (DLD) was the only TCA cycle-associated protein that showed a decreased expression after the UVB exposure. We also performed targeted analysis to detect intermediates and products of the TCA cycle using GC-TOF-MS. Interestingly, malic acid and fumaric acid levels significantly decreased in the UVB-treated group. Our results demonstrate that DLD and its associated metabolites, malic acid and fumaric acid, may be candidate biomarkers of UVB-induced skin photoaging. Additionally, we showed that Aloe vera, a natural skin moisturizer, regulated DLD, malic acid and fumaric acid levels in UVB-exposed epidermis. Our strategy to integrate the proteome and targeted metabolite to detect novel UVB targets will lead to a better understanding of skin photoaging and photodamage. Our study also supports that A. vera exerts significant anti-photodamage activity via regulation of DLD, a novel UVB target, in the epidermis. This study is the first example of an integration of proteomic and metabolite analysis techniques to find new biomarker candidates for the regulation of the UVB-induced skin photoaging. DLD, malic acid, and fumaric acid can be used for development of cosmeceuticals and nutraceuticals regulating the change of skin metabolism induced by the UVB overexposure. Moreover, this is also the first attempt to investigate the role of the TCA cycle in photodamaged epidermis. Our integration of the proteomic and targeted metabolite analyses will lead to a better understanding of the unidentified

Biomarker Discovery and Mechanistic Studies of Prostate Cancer Using Targeted Proteomic Approaches

DTIC Science & Technology

2012-07-01

1-0431 TITLE: Biomarker Discovery and Mechanistic Studies of Prostate Cancer Using Targeted Proteomic Approaches PRINCIPAL INVESTIGATOR...July 2012 2. REPORT TYPE Final 3. DATES COVERED (From - To) 1 July 2008 – 30 June 2012 4. TITLE AND SUBTITLE Biomarker Discovery and Mechanistic...Department of Defense Synergistic Idea Development Award W81XWH-08-1-0430 (to H.Z) and W81XWH-08-1-0431 (to N.K.), an NIH/NCRR COBRE grant 1P20RR020171 (to

Proteome complexity and the forces that drive proteome imbalance

PubMed Central

Harper, J. Wade; Bennett, Eric J.

2016-01-01

Summary The cellular proteome is a complex microcosm of structural and regulatory networks that requires continuous surveillance and modification to meet the dynamic needs of the cell. It is therefore crucial that the protein flux of the cell remains in balance to ensure proper cell function. Genetic alterations that range from chromosome imbalance to oncogene activation can affect the speed, fidelity and capacity of protein biogenesis and degradation systems, which often results in proteome imbalance. An improved understanding of the causes and consequences of proteome imbalance is helping to reveal how these systems can be targeted to treat diseases such as cancer. PMID:27629639

The Escherichia coli Peripheral Inner Membrane Proteome*

PubMed Central

Papanastasiou, Malvina; Orfanoudaki, Georgia; Koukaki, Marina; Kountourakis, Nikos; Sardis, Marios Frantzeskos; Aivaliotis, Michalis; Karamanou, Spyridoula; Economou, Anastassios

2013-01-01

Biological membranes are essential for cell viability. Their functional characteristics strongly depend on their protein content, which consists of transmembrane (integral) and peripherally associated membrane proteins. Both integral and peripheral inner membrane proteins mediate a plethora of biological processes. Whereas transmembrane proteins have characteristic hydrophobic stretches and can be predicted using bioinformatics approaches, peripheral inner membrane proteins are hydrophilic, exist in equilibria with soluble pools, and carry no discernible membrane targeting signals. We experimentally determined the cytoplasmic peripheral inner membrane proteome of the model organism Escherichia coli using a multidisciplinary approach. Initially, we extensively re-annotated the theoretical proteome regarding subcellular localization using literature searches, manual curation, and multi-combinatorial bioinformatics searches of the available databases. Next we used sequential biochemical fractionations coupled to direct identification of individual proteins and protein complexes using high resolution mass spectrometry. We determined that the proposed cytoplasmic peripheral inner membrane proteome occupies a previously unsuspected ∼19% of the basic E. coli BL21(DE3) proteome, and the detected peripheral inner membrane proteome occupies ∼25% of the estimated expressed proteome of this cell grown in LB medium to mid-log phase. This value might increase when fleeting interactions, not studied here, are taken into account. Several proteins previously regarded as exclusively cytoplasmic bind membranes avidly. Many of these proteins are organized in functional or/and structural oligomeric complexes that bind to the membrane with multiple interactions. Identified proteins cover the full spectrum of biological activities, and more than half of them are essential. Our data suggest that the cytoplasmic proteome displays remarkably dynamic and extensive communication with

Metabolomics Coupled with Proteomics Advancing Drug Discovery toward More Agile Development of Targeted Combination Therapies*

PubMed Central

Wang, Xijun; Zhang, Aihua; Wang, Ping; Sun, Hui; Wu, Gelin; Sun, Wenjun; Lv, Haitao; Jiao, Guozheng; Xu, Hongying; Yuan, Ye; Liu, Lian; Zou, Dixin; Wu, Zeming; Han, Ying; Yan, Guangli; Dong, Wei; Wu, Fangfang; Dong, Tianwei; Yu, Yang; Zhang, Shuxiang; Wu, Xiuhong; Tong, Xin; Meng, Xiangcai

2013-01-01

To enhance the therapeutic efficacy and reduce the adverse effects of traditional Chinese medicine, practitioners often prescribe combinations of plant species and/or minerals, called formulae. Unfortunately, the working mechanisms of most of these compounds are difficult to determine and thus remain unknown. In an attempt to address the benefits of formulae based on current biomedical approaches, we analyzed the components of Yinchenhao Tang, a classical formula that has been shown to be clinically effective for treating hepatic injury syndrome. The three principal components of Yinchenhao Tang are Artemisia annua L., Gardenia jasminoids Ellis, and Rheum Palmatum L., whose major active ingredients are 6,7-dimethylesculetin (D), geniposide (G), and rhein (R), respectively. To determine the mechanisms underlying the efficacy of this formula, we conducted a systematic analysis of the therapeutic effects of the DGR compound using immunohistochemistry, biochemistry, metabolomics, and proteomics. Here, we report that the DGR combination exerts a more robust therapeutic effect than any one or two of the three individual compounds by hitting multiple targets in a rat model of hepatic injury. Thus, DGR synergistically causes intensified dynamic changes in metabolic biomarkers, regulates molecular networks through target proteins, has a synergistic/additive effect, and activates both intrinsic and extrinsic pathways. PMID:23362329

Metabolomics coupled with proteomics advancing drug discovery toward more agile development of targeted combination therapies.

PubMed

Wang, Xijun; Zhang, Aihua; Wang, Ping; Sun, Hui; Wu, Gelin; Sun, Wenjun; Lv, Haitao; Jiao, Guozheng; Xu, Hongying; Yuan, Ye; Liu, Lian; Zou, Dixin; Wu, Zeming; Han, Ying; Yan, Guangli; Dong, Wei; Wu, Fangfang; Dong, Tianwei; Yu, Yang; Zhang, Shuxiang; Wu, Xiuhong; Tong, Xin; Meng, Xiangcai

2013-05-01

To enhance the therapeutic efficacy and reduce the adverse effects of traditional Chinese medicine, practitioners often prescribe combinations of plant species and/or minerals, called formulae. Unfortunately, the working mechanisms of most of these compounds are difficult to determine and thus remain unknown. In an attempt to address the benefits of formulae based on current biomedical approaches, we analyzed the components of Yinchenhao Tang, a classical formula that has been shown to be clinically effective for treating hepatic injury syndrome. The three principal components of Yinchenhao Tang are Artemisia annua L., Gardenia jasminoids Ellis, and Rheum Palmatum L., whose major active ingredients are 6,7-dimethylesculetin (D), geniposide (G), and rhein (R), respectively. To determine the mechanisms underlying the efficacy of this formula, we conducted a systematic analysis of the therapeutic effects of the DGR compound using immunohistochemistry, biochemistry, metabolomics, and proteomics. Here, we report that the DGR combination exerts a more robust therapeutic effect than any one or two of the three individual compounds by hitting multiple targets in a rat model of hepatic injury. Thus, DGR synergistically causes intensified dynamic changes in metabolic biomarkers, regulates molecular networks through target proteins, has a synergistic/additive effect, and activates both intrinsic and extrinsic pathways.

A liquid chromatography-tandem mass spectrometry-based targeted proteomics assay for monitoring P-glycoprotein levels in human breast tissue.

PubMed

Yang, Ting; Chen, Fei; Xu, Feifei; Wang, Fengliang; Xu, Qingqing; Chen, Yun

2014-09-25

P-glycoprotein (P-gp) can efflux drugs from cancer cells, and its overexpression is commonly associated with multi-drug resistance (MDR). Thus, the accurate quantification of P-gp would help predict the response to chemotherapy and for prognosis of breast cancer patients. An advanced liquid chromatography-tandem mass spectrometry (LC/MS/MS)-based targeted proteomics assay was developed and validated for monitoring P-gp levels in breast tissue. Tryptic peptide 368IIDNKPSIDSYSK380 was selected as a surrogate analyte for quantification, and immuno-depleted tissue extract was used as a surrogate matrix. Matched pairs of breast tissue samples from 60 patients who were suspected to have drug resistance were subject to analysis. The levels of P-gp were quantified. Using data from normal tissue, we suggested a P-gp reference interval. The experimental values of tumor tissue samples were compared with those obtained from Western blotting and immunohistochemistry (IHC). The result indicated that the targeted proteomics approach was comparable to IHC but provided a lower limit of quantification (LOQ) and could afford more reliable results at low concentrations than the other two methods. LC/MS/MS-based targeted proteomics may allow the quantification of P-gp in breast tissue in a more accurate manner. Copyright © 2014 Elsevier B.V. All rights reserved.

Mass spectrometry-based proteomics: from cancer biology to protein biomarkers, drug targets, and clinical applications.

PubMed

Jimenez, Connie R; Verheul, Henk M W

2014-01-01

Proteomics is optimally suited to bridge the gap between genomic information on the one hand and biologic functions and disease phenotypes at the other, since it studies the expression and/or post-translational modification (especially phosphorylation) of proteins--the major cellular players bringing about cellular functions--at a global level in biologic specimens. Mass spectrometry technology and (bio)informatic tools have matured to the extent that they can provide high-throughput, comprehensive, and quantitative protein inventories of cells, tissues, and biofluids in clinical samples at low level. In this article, we focus on next-generation proteomics employing nanoliquid chromatography coupled to high-resolution tandem mass spectrometry for in-depth (phospho)protein profiling of tumor tissues and (proximal) biofluids, with a focus on studies employing clinical material. In addition, we highlight emerging proteogenomic approaches for the identification of tumor-specific protein variants, and targeted multiplex mass spectrometry strategies for large-scale biomarker validation. Below we provide a discussion of recent progress, some research highlights, and challenges that remain for clinical translation of proteomic discoveries.

Plasma Membrane Proteomics of Human Breast Cancer Cell Lines Identifies Potential Targets for Breast Cancer Diagnosis and Treatment

PubMed Central

Ziegler, Yvonne S.; Moresco, James J.; Tu, Patricia G.; Yates, John R.; Nardulli, Ann M.

2014-01-01

The use of broad spectrum chemotherapeutic agents to treat breast cancer results in substantial and debilitating side effects, necessitating the development of targeted therapies to limit tumor proliferation and prevent metastasis. In recent years, the list of approved targeted therapies has expanded, and it includes both monoclonal antibodies and small molecule inhibitors that interfere with key proteins involved in the uncontrolled growth and migration of cancer cells. The targeting of plasma membrane proteins has been most successful to date, and this is reflected in the large representation of these proteins as targets of newer therapies. In view of these facts, experiments were designed to investigate the plasma membrane proteome of a variety of human breast cancer cell lines representing hormone-responsive, ErbB2 over-expressing and triple negative cell types, as well as a benign control. Plasma membranes were isolated by using an aqueous two-phase system, and the resulting proteins were subjected to mass spectrometry analysis. Overall, each of the cell lines expressed some unique proteins, and a number of proteins were expressed in multiple cell lines, but in patterns that did not always follow traditional clinical definitions of breast cancer type. From our data, it can be deduced that most cancer cells possess multiple strategies to promote uncontrolled growth, reflected in aberrant expression of tyrosine kinases, cellular adhesion molecules, and structural proteins. Our data set provides a very rich and complex picture of plasma membrane proteins present on breast cancer cells, and the sorting and categorizing of this data provides interesting insights into the biology, classification, and potential treatment of this prevalent and debilitating disease. PMID:25029196

Assay Portal | Office of Cancer Clinical Proteomics Research

Cancer.gov

The CPTAC Assay Portal serves as a centralized public repository of "fit-for-purpose," multiplexed quantitative mass spectrometry-based proteomic targeted assays. Targeted proteomic assays eliminate issues that are commonly observed using conventional protein detection systems.

Multiple Click-Selective tRNA Synthetases Expand Mammalian Cell-Specific Proteomics.

PubMed

Yang, Andrew C; du Bois, Haley; Olsson, Niclas; Gate, David; Lehallier, Benoit; Berdnik, Daniela; Brewer, Kyle D; Bertozzi, Carolyn R; Elias, Joshua E; Wyss-Coray, Tony

2018-06-13

Bioorthogonal tools enable cell-type-specific proteomics, a prerequisite to understanding biological processes in multicellular organisms. Here we report two engineered aminoacyl-tRNA synthetases for mammalian bioorthogonal labeling: a tyrosyl ( ScTyr Y43G ) and a phenylalanyl ( MmPhe T413G ) tRNA synthetase that incorporate azide-bearing noncanonical amino acids specifically into the nascent proteomes of host cells. Azide-labeled proteins are chemoselectively tagged via azide-alkyne cycloadditions with fluorophores for imaging or affinity resins for mass spectrometric characterization. Both mutant synthetases label human, hamster, and mouse cell line proteins and selectively activate their azido-bearing amino acids over 10-fold above the canonical. ScTyr Y43G and MmPhe T413G label overlapping but distinct proteomes in human cell lines, with broader proteome coverage upon their coexpression. In mice, ScTyr Y43G and MmPhe T413G label the melanoma tumor proteome and plasma secretome. This work furnishes new tools for mammalian residue-specific bioorthogonal chemistry, and enables more robust and comprehensive cell-type-specific proteomics in live mammals.

Requests Cancer Targets for Monoclonal Antibody Production and Characterization | Office of Cancer Clinical Proteomics Research

Cancer.gov

In an effort to provide well-characterized monoclonal antibodies to the scientific community, the National Cancer Institute (NCI) Antibody Characterization Program requests cancer-related protein targets for affinity production and distribution. The program from The Office of Cancer Clinical Proteomics Research provides reagents and other critical resources that support protein and/or peptide measurements and analysis.

Scientific Approaches | Office of Cancer Clinical Proteomics Research

Cancer.gov

CPTAC employs two complementary scientific approaches, a "Targeting Genome to Proteome" (Targeting G2P) approach and a "Mapping Proteome to Genome" (Mapping P2G) approach, in order to address biological questions from data generated on a sample.

YPED: An Integrated Bioinformatics Suite and Database for Mass Spectrometry-based Proteomics Research

PubMed Central

Colangelo, Christopher M.; Shifman, Mark; Cheung, Kei-Hoi; Stone, Kathryn L.; Carriero, Nicholas J.; Gulcicek, Erol E.; Lam, TuKiet T.; Wu, Terence; Bjornson, Robert D.; Bruce, Can; Nairn, Angus C.; Rinehart, Jesse; Miller, Perry L.; Williams, Kenneth R.

2015-01-01

We report a significantly-enhanced bioinformatics suite and database for proteomics research called Yale Protein Expression Database (YPED) that is used by investigators at more than 300 institutions worldwide. YPED meets the data management, archival, and analysis needs of a high-throughput mass spectrometry-based proteomics research ranging from a single laboratory, group of laboratories within and beyond an institution, to the entire proteomics community. The current version is a significant improvement over the first version in that it contains new modules for liquid chromatography–tandem mass spectrometry (LC–MS/MS) database search results, label and label-free quantitative proteomic analysis, and several scoring outputs for phosphopeptide site localization. In addition, we have added both peptide and protein comparative analysis tools to enable pairwise analysis of distinct peptides/proteins in each sample and of overlapping peptides/proteins between all samples in multiple datasets. We have also implemented a targeted proteomics module for automated multiple reaction monitoring (MRM)/selective reaction monitoring (SRM) assay development. We have linked YPED’s database search results and both label-based and label-free fold-change analysis to the Skyline Panorama repository for online spectra visualization. In addition, we have built enhanced functionality to curate peptide identifications into an MS/MS peptide spectral library for all of our protein database search identification results. PMID:25712262

YPED: an integrated bioinformatics suite and database for mass spectrometry-based proteomics research.

PubMed

Colangelo, Christopher M; Shifman, Mark; Cheung, Kei-Hoi; Stone, Kathryn L; Carriero, Nicholas J; Gulcicek, Erol E; Lam, TuKiet T; Wu, Terence; Bjornson, Robert D; Bruce, Can; Nairn, Angus C; Rinehart, Jesse; Miller, Perry L; Williams, Kenneth R

2015-02-01

We report a significantly-enhanced bioinformatics suite and database for proteomics research called Yale Protein Expression Database (YPED) that is used by investigators at more than 300 institutions worldwide. YPED meets the data management, archival, and analysis needs of a high-throughput mass spectrometry-based proteomics research ranging from a single laboratory, group of laboratories within and beyond an institution, to the entire proteomics community. The current version is a significant improvement over the first version in that it contains new modules for liquid chromatography-tandem mass spectrometry (LC-MS/MS) database search results, label and label-free quantitative proteomic analysis, and several scoring outputs for phosphopeptide site localization. In addition, we have added both peptide and protein comparative analysis tools to enable pairwise analysis of distinct peptides/proteins in each sample and of overlapping peptides/proteins between all samples in multiple datasets. We have also implemented a targeted proteomics module for automated multiple reaction monitoring (MRM)/selective reaction monitoring (SRM) assay development. We have linked YPED's database search results and both label-based and label-free fold-change analysis to the Skyline Panorama repository for online spectra visualization. In addition, we have built enhanced functionality to curate peptide identifications into an MS/MS peptide spectral library for all of our protein database search identification results. Copyright © 2015 The Authors. Production and hosting by Elsevier Ltd.. All rights reserved.

Comparative Proteome Analysis in Schizosaccharomyces pombe Identifies Metabolic Targets to Improve Protein Production and Secretion*

PubMed Central

Hung, Chien-Wen; Klein, Tobias; Cassidy, Liam; Linke, Dennis; Lange, Sabrina; Anders, Uwe; Bureik, Matthias; Heinzle, Elmar; Schneider, Konstantin; Tholey, Andreas

2016-01-01

Protein secretion in yeast is a complex process and its efficiency depends on a variety of parameters. We performed a comparative proteome analysis of a set of Schizosaccharomyces pombe strains producing the α-glucosidase maltase in increasing amounts to investigate the overall proteomic response of the cell to the burden of protein production along the various steps of protein production and secretion. Proteome analysis of these strains, utilizing an isobaric labeling/two dimensional LC-MALDI MS approach, revealed complex changes, from chaperones and secretory transport machinery to proteins controlling transcription and translation. We also found an unexpectedly high amount of changes in enzyme levels of the central carbon metabolism and a significant up-regulation of several amino acid biosyntheses. These amino acids were partially underrepresented in the cellular protein compared with the composition of the model protein. Additional feeding of these amino acids resulted in a 1.5-fold increase in protein secretion. Membrane fluidity was identified as a second bottleneck for high-level protein secretion and addition of fluconazole to the culture caused a significant decrease in ergosterol levels, whereas protein secretion could be further increased by a factor of 2.1. In summary, we show that high level protein secretion causes global changes of protein expression levels in the cell and that precursor availability and membrane composition limit protein secretion in this yeast. In this respect, comparative proteome analysis is a powerful tool to identify targets for an efficient increase of protein production and secretion in S. pombe. Data are available via ProteomeXchange with identifiers PXD002693 and PXD003016. PMID:27477394

Clinical veterinary proteomics: Techniques and approaches to decipher the animal plasma proteome.

PubMed

Ghodasara, P; Sadowski, P; Satake, N; Kopp, S; Mills, P C

2017-12-01

Over the last two decades, technological advancements in the field of proteomics have advanced our understanding of the complex biological systems of living organisms. Techniques based on mass spectrometry (MS) have emerged as powerful tools to contextualise existing genomic information and to create quantitative protein profiles from plasma, tissues or cell lines of various species. Proteomic approaches have been used increasingly in veterinary science to investigate biological processes responsible for growth, reproduction and pathological events. However, the adoption of proteomic approaches by veterinary investigators lags behind that of researchers in the human medical field. Furthermore, in contrast to human proteomics studies, interpretation of veterinary proteomic data is difficult due to the limited protein databases available for many animal species. This review article examines the current use of advanced proteomics techniques for evaluation of animal health and welfare and covers the current status of clinical veterinary proteomics research, including successful protein identification and data interpretation studies. It includes a description of an emerging tool, sequential window acquisition of all theoretical fragment ion mass spectra (SWATH-MS), available on selected mass spectrometry instruments. This newly developed data acquisition technique combines advantages of discovery and targeted proteomics approaches, and thus has the potential to advance the veterinary proteomics field by enhancing identification and reproducibility of proteomics data. Copyright © 2017 Elsevier Ltd. All rights reserved.

An Anti-proteome Nanobody Library Approach Yields a Specific Immunoassay for Trypanosoma congolense Diagnosis Targeting Glycosomal Aldolase.

PubMed

Odongo, Steven; Sterckx, Yann G J; Stijlemans, Benoît; Pillay, Davita; Baltz, Théo; Muyldermans, Serge; Magez, Stefan

2016-02-01

Infectious diseases pose a severe worldwide threat to human and livestock health. While early diagnosis could enable prompt preventive interventions, the majority of diseases are found in rural settings where basic laboratory facilities are scarce. Under such field conditions, point-of-care immunoassays provide an appropriate solution for rapid and reliable diagnosis. The limiting steps in the development of the assay are the identification of a suitable target antigen and the selection of appropriate high affinity capture and detection antibodies. To meet these challenges, we describe the development of a Nanobody (Nb)-based antigen detection assay generated from a Nb library directed against the soluble proteome of an infectious agent. In this study, Trypanosoma congolense was chosen as a model system. An alpaca was vaccinated with whole-parasite soluble proteome to generate a Nb library from which the most potent T. congolense specific Nb sandwich immunoassay (Nb474H-Nb474B) was selected. First, the Nb474-homologous sandwich ELISA (Nb474-ELISA) was shown to detect experimental infections with high Positive Predictive Value (98%), Sensitivity (87%) and Specificity (94%). Second, it was demonstrated under experimental conditions that the assay serves as test-of-cure after Berenil treatment. Finally, this assay allowed target antigen identification. The latter was independently purified through immuno-capturing from (i) T. congolense soluble proteome, (ii) T. congolense secretome preparation and (iii) sera of T. congolense infected mice. Subsequent mass spectrometry analysis identified the target as T. congolense glycosomal aldolase. The results show that glycosomal aldolase is a candidate biomarker for active T. congolense infections. In addition, and by proof-of-principle, the data demonstrate that the Nb strategy devised here offers a unique approach to both diagnostic development and target discovery that could be widely applied to other infectious diseases.

Reminder: NCI Requests Cancer Targets for Monoclonal Antibody Production and Characterization | Office of Cancer Clinical Proteomics Research

Cancer.gov

In an effort to improve rigor and reproducibility, the National Cancer Institute (NCI) Antibody Characterization Program requests cancer-related protein targets for monoclonal antibody production and distribution to the scientific community. The program from The Office of Cancer Clinical Proteomics Research provides well-characterized

Targeting human pathogenic bacteria by siderophores: A proteomics review.

PubMed

Ferreira, Daniela; Seca, Ana M L; C G A, Diana; Silva, Artur M S

2016-08-11

Human bacterial infections are still a major public health problem throughout the world. Therefore it is fundamental to understand how pathogenic bacteria interact with their human host and to develop more advanced drugs or vaccines in response to the increasing bacterial resistance. Since iron is essential to bacterial survival and growth inside the host tissues, these microorganisms have developed highly efficient iron-acquisition systems; the most common one involves the secretion of iron chelators into the extracellular environment, known as siderophores, and the corresponding siderophore-membrane receptors or transporters responsible for the iron uptake. In the past few decades, several biochemical methods and genetic screens have been employed to track down and identify these iron-scavenging molecules. However, compared with the previous "static" approaches, proteomic identification is revealing far more molecules through full protein mapping and becoming more rapid and selective, leading the scientific and medical community to consider standardizing proteomic tools for clinical biomarker detection of bacterial infectious diseases. In this review, we focus on human pathogenic Gram-negative bacteria and discuss the importance of siderophores in their virulence and the available proteomic strategies to identify siderophore-related proteins and their expression level under different growth conditions. The promising use of siderophore antibiotics to overcome bacterial resistance and the future of proteomics in the routine clinical care are also mentioned. Proteomic strategies to identify siderophore-related proteins and their expression level can be helpful to control and/or find a cure of infectious deseases especially if related with multidrug resistance. Siderophores are low-molecular-weight compounds produced by bacteria which can become clinical biomarkers and/or antibiotics used mainly in "Trojan horse" type strategies. Due to the above mention we think

Quantitative Proteomic Analysis of the Hfq-Regulon in Sinorhizobium meliloti 2011

PubMed Central

Sobrero, Patricio; Schlüter, Jan-Philip; Lanner, Ulrike; Schlosser, Andreas; Becker, Anke; Valverde, Claudio

2012-01-01

Riboregulation stands for RNA-based control of gene expression. In bacteria, small non-coding RNAs (sRNAs) are a major class of riboregulatory elements, most of which act at the post-transcriptional level by base-pairing target mRNA genes. The RNA chaperone Hfq facilitates antisense interactions between target mRNAs and regulatory sRNAs, thus influencing mRNA stability and/or translation rate. In the α-proteobacterium Sinorhizobium meliloti strain 2011, the identification and detection of multiple sRNAs genes and the broadly pleitropic phenotype associated to the absence of a functional Hfq protein both support the existence of riboregulatory circuits controlling gene expression to ensure the fitness of this bacterium in both free living and symbiotic conditions. In order to identify target mRNAs subject to Hfq-dependent riboregulation, we have compared the proteome of an hfq mutant and the wild type S. meliloti by quantitative proteomics following protein labelling with 15N. Among 2139 univocally identified proteins, a total of 195 proteins showed a differential abundance between the Hfq mutant and the wild type strain; 65 proteins accumulated ≥2-fold whereas 130 were downregulated (≤0.5-fold) in the absence of Hfq. This profound proteomic impact implies a major role for Hfq on regulation of diverse physiological processes in S. meliloti, from transport of small molecules to homeostasis of iron and nitrogen. Changes in the cellular levels of proteins involved in transport of nucleotides, peptides and amino acids, and in iron homeostasis, were confirmed with phenotypic assays. These results represent the first quantitative proteomic analysis in S. meliloti. The comparative analysis of the hfq mutant proteome allowed identification of novel strongly Hfq-regulated genes in S. meliloti. PMID:23119037

Quantitative proteomic analysis of the Hfq-regulon in Sinorhizobium meliloti 2011.

PubMed

Sobrero, Patricio; Schlüter, Jan-Philip; Lanner, Ulrike; Schlosser, Andreas; Becker, Anke; Valverde, Claudio

2012-01-01

Riboregulation stands for RNA-based control of gene expression. In bacteria, small non-coding RNAs (sRNAs) are a major class of riboregulatory elements, most of which act at the post-transcriptional level by base-pairing target mRNA genes. The RNA chaperone Hfq facilitates antisense interactions between target mRNAs and regulatory sRNAs, thus influencing mRNA stability and/or translation rate. In the α-proteobacterium Sinorhizobium meliloti strain 2011, the identification and detection of multiple sRNAs genes and the broadly pleitropic phenotype associated to the absence of a functional Hfq protein both support the existence of riboregulatory circuits controlling gene expression to ensure the fitness of this bacterium in both free living and symbiotic conditions. In order to identify target mRNAs subject to Hfq-dependent riboregulation, we have compared the proteome of an hfq mutant and the wild type S. meliloti by quantitative proteomics following protein labelling with (15)N. Among 2139 univocally identified proteins, a total of 195 proteins showed a differential abundance between the Hfq mutant and the wild type strain; 65 proteins accumulated ≥2-fold whereas 130 were downregulated (≤0.5-fold) in the absence of Hfq. This profound proteomic impact implies a major role for Hfq on regulation of diverse physiological processes in S. meliloti, from transport of small molecules to homeostasis of iron and nitrogen. Changes in the cellular levels of proteins involved in transport of nucleotides, peptides and amino acids, and in iron homeostasis, were confirmed with phenotypic assays. These results represent the first quantitative proteomic analysis in S. meliloti. The comparative analysis of the hfq mutant proteome allowed identification of novel strongly Hfq-regulated genes in S. meliloti.

Assessment of Sample Preparation Bias in Mass Spectrometry-Based Proteomics.

PubMed

Klont, Frank; Bras, Linda; Wolters, Justina C; Ongay, Sara; Bischoff, Rainer; Halmos, Gyorgy B; Horvatovich, Péter

2018-04-17

For mass spectrometry-based proteomics, the selected sample preparation strategy is a key determinant for information that will be obtained. However, the corresponding selection is often not based on a fit-for-purpose evaluation. Here we report a comparison of in-gel (IGD), in-solution (ISD), on-filter (OFD), and on-pellet digestion (OPD) workflows on the basis of targeted (QconCAT-multiple reaction monitoring (MRM) method for mitochondrial proteins) and discovery proteomics (data-dependent acquisition, DDA) analyses using three different human head and neck tissues (i.e., nasal polyps, parotid gland, and palatine tonsils). Our study reveals differences between the sample preparation methods, for example, with respect to protein and peptide losses, quantification variability, protocol-induced methionine oxidation, and asparagine/glutamine deamidation as well as identification of cysteine-containing peptides. However, none of the methods performed best for all types of tissues, which argues against the existence of a universal sample preparation method for proteome analysis.

Targeted Feature Detection for Data-Dependent Shotgun Proteomics

PubMed Central

2017-01-01

Label-free quantification of shotgun LC–MS/MS data is the prevailing approach in quantitative proteomics but remains computationally nontrivial. The central data analysis step is the detection of peptide-specific signal patterns, called features. Peptide quantification is facilitated by associating signal intensities in features with peptide sequences derived from MS2 spectra; however, missing values due to imperfect feature detection are a common problem. A feature detection approach that directly targets identified peptides (minimizing missing values) but also offers robustness against false-positive features (by assigning meaningful confidence scores) would thus be highly desirable. We developed a new feature detection algorithm within the OpenMS software framework, leveraging ideas and algorithms from the OpenSWATH toolset for DIA/SRM data analysis. Our software, FeatureFinderIdentification (“FFId”), implements a targeted approach to feature detection based on information from identified peptides. This information is encoded in an MS1 assay library, based on which ion chromatogram extraction and detection of feature candidates are carried out. Significantly, when analyzing data from experiments comprising multiple samples, our approach distinguishes between “internal” and “external” (inferred) peptide identifications (IDs) for each sample. On the basis of internal IDs, two sets of positive (true) and negative (decoy) feature candidates are defined. A support vector machine (SVM) classifier is then trained to discriminate between the sets and is subsequently applied to the “uncertain” feature candidates from external IDs, facilitating selection and confidence scoring of the best feature candidate for each peptide. This approach also enables our algorithm to estimate the false discovery rate (FDR) of the feature selection step. We validated FFId based on a public benchmark data set, comprising a yeast cell lysate spiked with protein standards

Integrative FourD omics approach profiles the target network of the carbon storage regulatory system

PubMed Central

Sowa, Steven W.; Gelderman, Grant; Leistra, Abigail N.; Buvanendiran, Aishwarya; Lipp, Sarah; Pitaktong, Areen; Vakulskas, Christopher A.; Romeo, Tony; Baldea, Michael

2017-01-01

Abstract Multi-target regulators represent a largely untapped area for metabolic engineering and anti-bacterial development. These regulators are complex to characterize because they often act at multiple levels, affecting proteins, transcripts and metabolites. Therefore, single omics experiments cannot profile their underlying targets and mechanisms. In this work, we used an Integrative FourD omics approach (INFO) that consists of collecting and analyzing systems data throughout multiple time points, using multiple genetic backgrounds, and multiple omics approaches (transcriptomics, proteomics and high throughput sequencing crosslinking immunoprecipitation) to evaluate simultaneous changes in gene expression after imposing an environmental stress that accentuates the regulatory features of a network. Using this approach, we profiled the targets and potential regulatory mechanisms of a global regulatory system, the well-studied carbon storage regulatory (Csr) system of Escherichia coli, which is widespread among bacteria. Using 126 sets of proteomics and transcriptomics data, we identified 136 potential direct CsrA targets, including 50 novel ones, categorized their behaviors into distinct regulatory patterns, and performed in vivo fluorescence-based follow up experiments. The results of this work validate 17 novel mRNAs as authentic direct CsrA targets and demonstrate a generalizable strategy to integrate multiple lines of omics data to identify a core pool of regulator targets. PMID:28126921

Comparative analysis of primary hepatocellular carcinoma with single and multiple lesions by iTRAQ-based quantitative proteomics.

PubMed

Xing, Xiaohua; Huang, Yao; Wang, Sen; Chi, Minhui; Zeng, Yongyi; Chen, Lihong; Li, Ling; Zeng, Jinhua; Lin, Minjie; Han, Xiao; Liu, Xiaolong; Liu, Jingfeng

2015-10-14

In clinical practices, the therapeutic outcomes and prognosis of hepatocellular carcinoma (HCC) patients with different tumor numbers after surgery are very different; however, the underlying mechanisms of the tumorigenesis and development of HCC with different tumor numbers are still not well understood. Here, we systematically compared the overall proteome profiles between the primary HCC with single and multiple lesions using iTRAQ-based quantitative proteomics approach. We identified that 107 and 330 proteins were dysregulated in HCC tissue with multiple lesions (MC group) and HCC tissue with a single lesion (SC group), compared with their non-cancerous tissue (MN and SN groups) respectively. The dysregulated proteins in MC group are concentrated in UBC signaling pathway and NFκB signaling pathway, but the dysregulated proteins in SC group are more concentrated in ERK signaling pathway and the NFκB signaling pathway. These information revealed that there might be different molecular mechanisms of the tumorigenesis and development of the HCC with single and multiple lesions. Furthermore, HSD17B13 were only down-regulated in MC group while HK2 were only up-regulated in SC group among these dysregulated proteins. Therefore, the protein HSD17B13 and HK2 might be potential biomarkers for the primary HCC with single and multiple lesions. Copyright © 2015 Elsevier B.V. All rights reserved.

Architecture of a Host-Parasite Interface: Complex Targeting Mechanisms Revealed Through Proteomics.

PubMed

Gadelha, Catarina; Zhang, Wenzhu; Chamberlain, James W; Chait, Brian T; Wickstead, Bill; Field, Mark C

2015-07-01

Surface membrane organization and composition is key to cellular function, and membrane proteins serve many essential roles in endocytosis, secretion, and cell recognition. The surface of parasitic organisms, however, is a double-edged sword; this is the primary interface between parasites and their hosts, and those crucial cellular processes must be carried out while avoiding elimination by the host immune defenses. For extracellular African trypanosomes, the surface is partitioned such that all endo- and exocytosis is directed through a specific membrane region, the flagellar pocket, in which it is thought the majority of invariant surface proteins reside. However, very few of these proteins have been identified, severely limiting functional studies, and hampering the development of potential treatments. Here we used an integrated biochemical, proteomic and bioinformatic strategy to identify surface components of the human parasite Trypanosoma brucei. This surface proteome contains previously known flagellar pocket proteins as well as multiple novel components, and is significantly enriched in proteins that are essential for parasite survival. Molecules with receptor-like properties are almost exclusively parasite-specific, whereas transporter-like proteins are conserved in model organisms. Validation shows that the majority of surface proteome constituents are bona fide surface-associated proteins and, as expected, most present at the flagellar pocket. Moreover, the largest systematic analysis of trypanosome surface molecules to date provides evidence that the cell surface is compartmentalized into three distinct domains with free diffusion of molecules in each, but selective, asymmetric traffic between. This work provides a paradigm for the compartmentalization of a cell surface and a resource for its analysis. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Proteomics Reveals Plastid- and Periplastid-Targeted Proteins in the Chlorarachniophyte Alga Bigelowiella natans

PubMed Central

Hopkins, Julia F.; Spencer, David F.; Laboissiere, Sylvie; Neilson, Jonathan A.D.; Eveleigh, Robert J.M.; Durnford, Dion G.; Gray, Michael W.; Archibald, John M.

2012-01-01

Chlorarachniophytes are unicellular marine algae with plastids (chloroplasts) of secondary endosymbiotic origin. Chlorarachniophyte cells retain the remnant nucleus (nucleomorph) and cytoplasm (periplastidial compartment, PPC) of the green algal endosymbiont from which their plastid was derived. To characterize the diversity of nucleus-encoded proteins targeted to the chlorarachniophyte plastid, nucleomorph, and PPC, we isolated plastid–nucleomorph complexes from the model chlorarachniophyte Bigelowiella natans and subjected them to high-pressure liquid chromatography-tandem mass spectrometry. Our proteomic analysis, the first of its kind for a nucleomorph-bearing alga, resulted in the identification of 324 proteins with 95% confidence. Approximately 50% of these proteins have predicted bipartite leader sequences at their amino termini. Nucleus-encoded proteins make up >90% of the proteins identified. With respect to biological function, plastid-localized light-harvesting proteins were well represented, as were proteins involved in chlorophyll biosynthesis. Phylogenetic analyses revealed that many, but by no means all, of the proteins identified in our proteomic screen are of apparent green algal ancestry, consistent with the inferred evolutionary origin of the plastid and nucleomorph in chlorarachniophytes. PMID:23221610

Quantitative analysis of oyster larval proteome provides new insights into the effects of multiple climate change stressors.

PubMed

Dineshram, Ramadoss; Chandramouli, Kondethimmanahalli; Ko, Ginger Wai Kuen; Zhang, Huoming; Qian, Pei-Yuan; Ravasi, Timothy; Thiyagarajan, Vengatesen

2016-06-01

The metamorphosis of planktonic larvae of the Pacific oyster (Crassostrea gigas) underpins their complex life-history strategy by switching on the molecular machinery required for sessile life and building calcite shells. Metamorphosis becomes a survival bottleneck, which will be pressured by different anthropogenically induced climate change-related variables. Therefore, it is important to understand how metamorphosing larvae interact with emerging climate change stressors. To predict how larvae might be affected in a future ocean, we examined changes in the proteome of metamorphosing larvae under multiple stressors: decreased pH (pH 7.4), increased temperature (30 °C), and reduced salinity (15 psu). Quantitative protein expression profiling using iTRAQ-LC-MS/MS identified more than 1300 proteins. Decreased pH had a negative effect on metamorphosis by down-regulating several proteins involved in energy production, metabolism, and protein synthesis. However, warming switched on these down-regulated pathways at pH 7.4. Under multiple stressors, cell signaling, energy production, growth, and developmental pathways were up-regulated, although metamorphosis was still reduced. Despite the lack of lethal effects, significant physiological responses to both individual and interacting climate change related stressors were observed at proteome level. The metamorphosing larvae of the C. gigas population in the Yellow Sea appear to have adequate phenotypic plasticity at the proteome level to survive in future coastal oceans, but with developmental and physiological costs. © 2016 John Wiley & Sons Ltd.

Chimeric plastid proteome in the Florida "red tide" dinoflagellate Karenia brevis.

PubMed

Nosenko, Tetyana; Lidie, Kristy L; Van Dolah, Frances M; Lindquist, Erika; Cheng, Jan-Fang; Bhattacharya, Debashish

2006-11-01

Current understanding of the plastid proteome comes almost exclusively from studies of plants and red algae. The proteome in these taxa has a relatively simple origin via integration of proteins from a single cyanobacterial primary endosymbiont and the host. However, the most successful algae in marine environments are the chlorophyll c-containing chromalveolates such as diatoms and dinoflagellates that contain a plastid of red algal origin derived via secondary or tertiary endosymbiosis. Virtually nothing is known about the plastid proteome in these taxa. We analyzed expressed sequence tag data from the toxic "Florida red tide" dinoflagellate Karenia brevis that has undergone a tertiary plastid endosymbiosis. Comparative analyses identified 30 nuclear-encoded plastid-targeted proteins in this chromalveolate that originated via endosymbiotic or horizontal gene transfer (HGT) from multiple different sources. We identify a fundamental divide between plant/red algal and chromalveolate plastid proteomes that reflects a history of mixotrophy in the latter group resulting in a highly chimeric proteome. Loss of phagocytosis in the "red" and "green" clades effectively froze their proteomes, whereas chromalveolate lineages retain the ability to engulf prey allowing them to continually recruit new, potentially adaptive genes through subsequent endosymbioses and HGT. One of these genes is an electron transfer protein (plastocyanin) of green algal origin in K. brevis that likely allows this species to thrive under conditions of iron depletion.

Targeted Proteomics-Driven Computational Modeling of Macrophage S1P Chemosensing*

PubMed Central

Manes, Nathan P.; Angermann, Bastian R.; Koppenol-Raab, Marijke; An, Eunkyung; Sjoelund, Virginie H.; Sun, Jing; Ishii, Masaru; Germain, Ronald N.; Meier-Schellersheim, Martin; Nita-Lazar, Aleksandra

2015-01-01

Osteoclasts are monocyte-derived multinuclear cells that directly attach to and resorb bone. Sphingosine-1-phosphate (S1P)1 regulates bone resorption by functioning as both a chemoattractant and chemorepellent of osteoclast precursors through two G-protein coupled receptors that antagonize each other in an S1P-concentration-dependent manner. To quantitatively explore the behavior of this chemosensing pathway, we applied targeted proteomics, transcriptomics, and rule-based pathway modeling using the Simmune toolset. RAW264.7 cells (a mouse monocyte/macrophage cell line) were used as model osteoclast precursors, RNA-seq was used to identify expressed target proteins, and selected reaction monitoring (SRM) mass spectrometry using internal peptide standards was used to perform absolute abundance measurements of pathway proteins. The resulting transcript and protein abundance values were strongly correlated. Measured protein abundance values, used as simulation input parameters, led to in silico pathway behavior matching in vitro measurements. Moreover, once model parameters were established, even simulated responses toward stimuli that were not used for parameterization were consistent with experimental findings. These findings demonstrate the feasibility and value of combining targeted mass spectrometry with pathway modeling for advancing biological insight. PMID:26199343

Targeted proteomics coming of age - SRM, PRM and DIA performance evaluated from a core facility perspective.

PubMed

Kockmann, Tobias; Trachsel, Christian; Panse, Christian; Wahlander, Asa; Selevsek, Nathalie; Grossmann, Jonas; Wolski, Witold E; Schlapbach, Ralph

2016-08-01

Quantitative mass spectrometry is a rapidly evolving methodology applied in a large number of omics-type research projects. During the past years, new designs of mass spectrometers have been developed and launched as commercial systems while in parallel new data acquisition schemes and data analysis paradigms have been introduced. Core facilities provide access to such technologies, but also actively support the researchers in finding and applying the best-suited analytical approach. In order to implement a solid fundament for this decision making process, core facilities need to constantly compare and benchmark the various approaches. In this article we compare the quantitative accuracy and precision of current state of the art targeted proteomics approaches single reaction monitoring (SRM), parallel reaction monitoring (PRM) and data independent acquisition (DIA) across multiple liquid chromatography mass spectrometry (LC-MS) platforms, using a readily available commercial standard sample. All workflows are able to reproducibly generate accurate quantitative data. However, SRM and PRM workflows show higher accuracy and precision compared to DIA approaches, especially when analyzing low concentrated analytes. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Targeted Proteomic Quantification on Quadrupole-Orbitrap Mass Spectrometer*

PubMed Central

Gallien, Sebastien; Duriez, Elodie; Crone, Catharina; Kellmann, Markus; Moehring, Thomas; Domon, Bruno

2012-01-01

There is an immediate need for improved methods to systematically and precisely quantify large sets of peptides in complex biological samples. To date protein quantification in biological samples has been routinely performed on triple quadrupole instruments operated in selected reaction monitoring mode (SRM), and two major challenges remain. Firstly, the number of peptides to be included in one survey experiment needs to be increased to routinely reach several hundreds, and secondly, the degree of selectivity should be improved so as to reliably discriminate the targeted analytes from background interferences. High resolution and accurate mass (HR/AM) analysis on the recently developed Q-Exactive mass spectrometer can potentially address these issues. This instrument presents a unique configuration: it is constituted of an orbitrap mass analyzer equipped with a quadrupole mass filter as the front-end for precursor ion mass selection. This configuration enables new quantitative methods based on HR/AM measurements, including targeted analysis in MS mode (single ion monitoring) and in MS/MS mode (parallel reaction monitoring). The ability of the quadrupole to select a restricted m/z range allows one to overcome the dynamic range limitations associated with trapping devices, and the MS/MS mode provides an additional stage of selectivity. When applied to targeted protein quantification in urine samples and benchmarked with the reference SRM technique, the quadrupole-orbitrap instrument exhibits similar or better performance in terms of selectivity, dynamic range, and sensitivity. This high performance is further enhanced by leveraging the multiplexing capability of the instrument to design novel acquisition methods and apply them to large targeted proteomic studies for the first time, as demonstrated on 770 tryptic yeast peptides analyzed in one 60-min experiment. The increased quality of quadrupole-orbitrap data has the potential to improve existing protein

CONVERGENT TRANSCRIPTOMICS AND PROTEOMICS OF ENVIRONMENTAL ENRICHMENT AND COCAINE IDENTIFIES NOVEL THERAPEUTIC STRATEGIES FOR ADDICTION

PubMed Central

ZHANG, YAFANG; CROFTON, ELIZABETH J.; FAN, XIUZHEN; LI, DINGGE; KONG, FANPING; SINHA, MALA; LUXON, BRUCE A.; SPRATT, HEIDI M.; LICHTI, CHERYL F.; GREEN, THOMAS A.

2016-01-01

Transcriptomic and proteomic approaches have separately proven effective at identifying novel mechanisms affecting addiction-related behavior; however, it is difficult to prioritize the many promising leads from each approach. A convergent secondary analysis of proteomic and transcriptomic results can glean additional information to help prioritize promising leads. The current study is a secondary analysis of the convergence of recently published separate transcriptomic and proteomic analyses of nucleus accumbens (NAc) tissue from rats subjected to environmental enrichment vs. isolation and cocaine self-administration vs. saline. Multiple bioinformatics approaches (e.g. Gene Ontology (GO) analysis, Ingenuity Pathway Analysis (IPA), and Gene Set Enrichment Analysis (GSEA)) were used to interrogate these rich data sets. Although there was little correspondence between mRNA vs. protein at the individual target level, good correspondence was found at the level of gene/protein sets, particularly for the environmental enrichment manipulation. These data identify gene sets where there is a positive relationship between changes in mRNA and protein (e.g. glycolysis, ATP synthesis, translation elongation factor activity, etc.) and gene sets where there is an inverse relationship (e.g. ribosomes, Rho GTPase signaling, protein ubiquitination, etc.). Overall environmental enrichment produced better correspondence than cocaine self-administration. The individual targets contributing to mRNA and protein effects were largely not overlapping. As a whole, these results confirm that robust transcriptomic and proteomic data sets can provide similar results at the gene/protein set level even when there is little correspondence at the individual target level and little overlap in the targets contributing to the effects. PMID:27717806

Integrative FourD omics approach profiles the target network of the carbon storage regulatory system.

PubMed

Sowa, Steven W; Gelderman, Grant; Leistra, Abigail N; Buvanendiran, Aishwarya; Lipp, Sarah; Pitaktong, Areen; Vakulskas, Christopher A; Romeo, Tony; Baldea, Michael; Contreras, Lydia M

2017-02-28

Multi-target regulators represent a largely untapped area for metabolic engineering and anti-bacterial development. These regulators are complex to characterize because they often act at multiple levels, affecting proteins, transcripts and metabolites. Therefore, single omics experiments cannot profile their underlying targets and mechanisms. In this work, we used an Integrative FourD omics approach (INFO) that consists of collecting and analyzing systems data throughout multiple time points, using multiple genetic backgrounds, and multiple omics approaches (transcriptomics, proteomics and high throughput sequencing crosslinking immunoprecipitation) to evaluate simultaneous changes in gene expression after imposing an environmental stress that accentuates the regulatory features of a network. Using this approach, we profiled the targets and potential regulatory mechanisms of a global regulatory system, the well-studied carbon storage regulatory (Csr) system of Escherichia coli, which is widespread among bacteria. Using 126 sets of proteomics and transcriptomics data, we identified 136 potential direct CsrA targets, including 50 novel ones, categorized their behaviors into distinct regulatory patterns, and performed in vivo fluorescence-based follow up experiments. The results of this work validate 17 novel mRNAs as authentic direct CsrA targets and demonstrate a generalizable strategy to integrate multiple lines of omics data to identify a core pool of regulator targets. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

The Brain Proteome of the Ubiquitin Ligase Peli1 Knock-Out Mouse during Experimental Autoimmune Encephalomyelitis.

PubMed

Lereim, Ragnhild Reehorst; Oveland, Eystein; Xiao, Yichuan; Torkildsen, Øivind; Wergeland, Stig; Myhr, Kjell-Morten; Sun, Shao-Cong; Berven, Frode S

2016-09-01

The ubiquitin ligase Peli1 has previously been suggested as a potential treatment target in multiple sclerosis. In the multiple sclerosis disease model, experimental autoimmune encephalomyelitis, Peli1 knock-out led to less activated microglia and less inflammation in the central nervous system. Despite being important in microglia, Peli1 expression has also been detected in glial and neuronal cells. In the present study the overall brain proteomes of Peli1 knock-out mice and wild-type mice were compared prior to experimental autoimmune encephalomyelitis induction, at onset of the disease and at disease peak. Brain samples from the frontal hemisphere, peripheral from the extensive inflammatory foci, were analyzed using TMT-labeling of sample pools, and the discovered proteins were verified in individual mice using label-free proteomics. The greatest proteomic differences between Peli1 knock-out and wild-type mice were observed at the disease peak. In Peli1 knock-out a higher degree of antigen presentation, increased activity of adaptive and innate immune cells and alterations to proteins involved in iron metabolism were observed during experimental autoimmune encephalomyelitis. These results unravel global effects to the brain proteome when abrogating Peli1 expression, underlining the importance of Peli1 as a regulator of the immune response also peripheral to inflammatory foci during experimental autoimmune encephalomyelitis. The proteomics data is available in PRIDE with accession PXD003710.

Discovery and Targeted Proteomics on Cutaneous Biopsies Infected by Borrelia to Investigate Lyme Disease*

PubMed Central

Schnell, Gilles; Boeuf, Amandine; Westermann, Benoît; Jaulhac, Benoît; Lipsker, Dan; Carapito, Christine; Boulanger, Nathalie; Ehret-Sabatier, Laurence

2015-01-01

Lyme disease is the most important vector-borne disease in the Northern hemisphere and represents a major public health challenge with insufficient means of reliable diagnosis. Skin is rarely investigated in proteomics but constitutes in the case of Lyme disease the key interface where the pathogens can enter, persist, and multiply. Therefore, we investigated proteomics on skin samples to detect Borrelia proteins directly in cutaneous biopsies in a robust and specific way. We first set up a discovery gel prefractionation-LC-MS/MS approach on a murine model infected by Borrelia burgdorferi sensu stricto that allowed the identification of 25 Borrelia proteins among more than 1300 mouse proteins. Then we developed a targeted gel prefractionation-LC-selected reaction monitoring (SRM) assay to detect 9/33 Borrelia proteins/peptides in mouse skin tissue samples using heavy labeled synthetic peptides. We successfully transferred this assay from the mouse model to human skin biopsies (naturally infected by Borrelia), and we were able to detect two Borrelia proteins: OspC and flagellin. Considering the extreme variability of OspC, we developed an extended SRM assay to target a large set of variants. This assay afforded the detection of nine peptides belonging to either OspC or flagellin in human skin biopsies. We further shortened the sample preparation and showed that Borrelia is detectable in mouse and human skin biopsies by directly using a liquid digestion followed by LC-SRM analysis without any prefractionation. This study thus shows that a targeted SRM approach is a promising tool for the early direct diagnosis of Lyme disease with high sensitivity (<10 fmol of OspC/mg of human skin biopsy). PMID:25713121

The quest of the human proteome and the missing proteins: digging deeper.

PubMed

Reddy, Panga Jaipal; Ray, Sandipan; Srivastava, Sanjeeva

2015-05-01

view was to study the wider tissue range with multiple digesting enzymes and follow targeted proteomics workflow in particular. On the innovation trajectory from the proteomics laboratory to novel proteomics diagnostics and therapeutics in society, we will also need new conceptual frames for translation science and innovation strategy in proteomics. These will embody both technical as well as rigorous social science and humanities considerations to understand the correlates of the proteome from cell to society.

Proteomic validation of protease drug targets: pharmacoproteomics of matrix metalloproteinase inhibitor drugs using isotope-coded affinity tag labelling and tandem mass spectrometry.

PubMed

Butler, G S; Overall, C M

2007-01-01

We illustrate the use of quantitative proteomics, namely isotope-coded affinity tag labelling and tandem mass spectrometry, to assess the targets and effects of the blockade of matrix metalloproteinases by an inhibitor drug in a breast cancer cell culture system. Treatment of MT1-MMP-transfected MDA-MB-231 cells with AG3340 (Prinomastat) directly affected the processing a multitude of matrix metalloproteinase substrates, and indirectly altered the expression of an array of other proteins with diverse functions. Therefore, broad spectrum blockade of MMPs has wide-ranging biological consequences. In this human breast cancer cell line, secreted substrates accumulated uncleaved in the conditioned medium and plasma membrane protein substrates were retained on the cell surface, due to reduced processing and shedding of these proteins (cell surface receptors, growth factors and bioactive molecules) to the medium in the presence of the matrix metalloproteinase inhibitor. Hence, proteomic investigation of drug-perturbed cellular proteomes can identify new protease substrates and at the same time provides valuable information for target validation, drug efficacy and potential side effects prior to commitment to clinical trials.

Combined expressional analysis, bioinformatics and targeted proteomics identify new potential therapeutic targets in glioblastoma stem cells.

PubMed

Stangeland, Biljana; Mughal, Awais A; Grieg, Zanina; Sandberg, Cecilie Jonsgar; Joel, Mrinal; Nygård, Ståle; Meling, Torstein; Murrell, Wayne; Vik Mo, Einar O; Langmoen, Iver A

2015-09-22

Glioblastoma (GBM) is both the most common and the most lethal primary brain tumor. It is thought that GBM stem cells (GSCs) are critically important in resistance to therapy. Therefore, there is a strong rationale to target these cells in order to develop new molecular therapies.To identify molecular targets in GSCs, we compared gene expression in GSCs to that in neural stem cells (NSCs) from the adult human brain, using microarrays. Bioinformatic filtering identified 20 genes (PBK/TOPK, CENPA, KIF15, DEPDC1, CDC6, DLG7/DLGAP5/HURP, KIF18A, EZH2, HMMR/RHAMM/CD168, NOL4, MPP6, MDM1, RAPGEF4, RHBDD1, FNDC3B, FILIP1L, MCC, ATXN7L4/ATXN7L1, P2RY5/LPAR6 and FAM118A) that were consistently expressed in GSC cultures and consistently not expressed in NSC cultures. The expression of these genes was confirmed in clinical samples (TCGA and REMBRANDT). The first nine genes were highly co-expressed in all GBM subtypes and were part of the same protein-protein interaction network. Furthermore, their combined up-regulation correlated negatively with patient survival in the mesenchymal GBM subtype. Using targeted proteomics and the COGNOSCENTE database we linked these genes to GBM signalling pathways.Nine genes: PBK, CENPA, KIF15, DEPDC1, CDC6, DLG7, KIF18A, EZH2 and HMMR should be further explored as targets for treatment of GBM.

Qualis-SIS: automated standard curve generation and quality assessment for multiplexed targeted quantitative proteomic experiments with labeled standards.

PubMed

Mohammed, Yassene; Percy, Andrew J; Chambers, Andrew G; Borchers, Christoph H

2015-02-06

Multiplexed targeted quantitative proteomics typically utilizes multiple reaction monitoring and allows the optimized quantification of a large number of proteins. One challenge, however, is the large amount of data that needs to be reviewed, analyzed, and interpreted. Different vendors provide software for their instruments, which determine the recorded responses of the heavy and endogenous peptides and perform the response-curve integration. Bringing multiplexed data together and generating standard curves is often an off-line step accomplished, for example, with spreadsheet software. This can be laborious, as it requires determining the concentration levels that meet the required accuracy and precision criteria in an iterative process. We present here a computer program, Qualis-SIS, that generates standard curves from multiplexed MRM experiments and determines analyte concentrations in biological samples. Multiple level-removal algorithms and acceptance criteria for concentration levels are implemented. When used to apply the standard curve to new samples, the software flags each measurement according to its quality. From the user's perspective, the data processing is instantaneous due to the reactivity paradigm used, and the user can download the results of the stepwise calculations for further processing, if necessary. This allows for more consistent data analysis and can dramatically accelerate the downstream data analysis.

Screening trematodes for novel intervention targets: a proteomic and immunological comparison of Schistosoma haematobium, Schistosoma bovis and Echinostoma caproni

PubMed Central

HIGÓN, MELISSA; COWAN, GRAEME; NAUSCH, NORMAN; CAVANAGH, DAVID; OLEAGA, ANA; TOLEDO, RAFAEL; STOTHARD, J. RUSSELL; ANTÚNEZ, ORETO; MARCILLA, ANTONIO; BURCHMORE, RICHARD; MUTAPI, FRANCISCA

2011-01-01

SUMMARY With the current paucity of vaccine targets for parasitic diseases, particularly those in childhood, the aim of this study was to compare protein expression and immune cross-reactivity between the trematodes Schistosoma haematobium, S. bovis and Echinostoma caproni in the hope of identifying novel intervention targets. Native adult parasite proteins were separated by 2-dimensional gel electrophoresis and identified through electrospray ionisation tandem mass spectrometry to produce a reference gel. Proteins from differential gel electrophoresis analyses of the three parasite proteomes were compared and screened against sera from hamsters infected with S. haematobium and E. caproni following 2-dimensional Western blotting. Differential protein expression between the three species was observed with circa 5% of proteins from S. haematobium showing expression up-regulation compared to the other two species. There was 91% similarity between the proteomes of the two Schistosoma species and 81% and 78·6% similarity between S. haematobium and S. bovis versus E. caproni, respectively. Although there were some common cross-species antigens, species-species targets were revealed which, despite evolutionary homology, could be due to phenotypic plasticity arising from different host-parasite relationships. Nevertheless, this approach helps to identify novel intervention targets which could be used as broad-spectrum candidates for future use in human and veterinary vaccines. PMID:21729355

Multiple target laser ablation system

DOEpatents

Mashburn, D.N.

1996-01-09

A laser ablation apparatus and method are provided in which multiple targets consisting of material to be ablated are mounted on a movable support. The material transfer rate is determined for each target material, and these rates are stored in a controller. A position detector determines which target material is in a position to be ablated, and then the controller controls the beam trigger timing and energy level to achieve a desired proportion of each constituent material in the resulting film. 3 figs.

Multiple target laser ablation system

DOEpatents

Mashburn, Douglas N.

1996-01-01

A laser ablation apparatus and method are provided in which multiple targets consisting of material to be ablated are mounted on a movable support. The material transfer rate is determined for each target material, and these rates are stored in a controller. A position detector determines which target material is in a position to be ablated, and then the controller controls the beam trigger timing and energy level to achieve a desired proportion of each constituent material in the resulting film.

Connecting genomic alterations to cancer biology with proteomics: the NCI Clinical Proteomic Tumor Analysis Consortium.

PubMed

Ellis, Matthew J; Gillette, Michael; Carr, Steven A; Paulovich, Amanda G; Smith, Richard D; Rodland, Karin K; Townsend, R Reid; Kinsinger, Christopher; Mesri, Mehdi; Rodriguez, Henry; Liebler, Daniel C

2013-10-01

The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium is applying the latest generation of proteomic technologies to genomically annotated tumors from The Cancer Genome Atlas (TCGA) program, a joint initiative of the NCI and the National Human Genome Research Institute. By providing a fully integrated accounting of DNA, RNA, and protein abnormalities in individual tumors, these datasets will illuminate the complex relationship between genomic abnormalities and cancer phenotypes, thus producing biologic insights as well as a wave of novel candidate biomarkers and therapeutic targets amenable to verification using targeted mass spectrometry methods. ©2013 AACR.

Analysis of cellular responses of macrophages to zinc ions and zinc oxide nanoparticles: a combined targeted and proteomic approach.

PubMed

Triboulet, Sarah; Aude-Garcia, Catherine; Armand, Lucie; Gerdil, Adèle; Diemer, Hélène; Proamer, Fabienne; Collin-Faure, Véronique; Habert, Aurélie; Strub, Jean-Marc; Hanau, Daniel; Herlin, Nathalie; Carrière, Marie; Van Dorsselaer, Alain; Rabilloud, Thierry

2014-06-07

Two different zinc oxide nanoparticles, as well as zinc ions, are used to study the cellular responses of the RAW 264 macrophage cell line. A proteomic screen is used to provide a wide view of the molecular effects of zinc, and the most prominent results are cross-validated by targeted studies. Furthermore, the alteration of important macrophage functions (e.g. phagocytosis) by zinc is also investigated. The intracellular dissolution/uptake of zinc is also studied to further characterize zinc toxicity. Zinc oxide nanoparticles dissolve readily in the cells, leading to high intracellular zinc concentrations, mostly as protein-bound zinc. The proteomic screen reveals a rather weak response in the oxidative stress response pathway, but a strong response both in the central metabolism and in the proteasomal protein degradation pathway. Targeted experiments confirm that carbohydrate catabolism and proteasome are critical determinants of sensitivity to zinc, which also induces DNA damage. Conversely, glutathione levels and phagocytosis appear unaffected at moderately toxic zinc concentrations.

Comparative and Quantitative Global Proteomics Approaches: An Overview

PubMed Central

Deracinois, Barbara; Flahaut, Christophe; Duban-Deweer, Sophie; Karamanos, Yannis

2013-01-01

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. PMID:28250403

Multiple Posttranslational Modifications of Leptospira biflexa Proteins as Revealed by Proteomic Analysis

PubMed Central

Carroll, James A.; Olano, L. Rennee; Sturdevant, Daniel E.; Rosa, Patricia A.

2015-01-01

The saprophyte Leptospira biflexa is an excellent model for studying the physiology of the medically important Leptospira genus, the pathogenic members of which are more recalcitrant to genetic manipulation and have significantly slower in vitro growth. However, relatively little is known regarding the proteome of L. biflexa, limiting its utility as a model for some studies. Therefore, we have generated a proteomic map of both soluble and membrane-associated proteins of L. biflexa during exponential growth and in stationary phase. Using these data, we identified abundantly produced proteins in each cellular fraction and quantified the transcript levels from a subset of these genes using quantitative reverse transcription-PCR (RT-PCR). These proteins should prove useful as cellular markers and as controls for gene expression studies. We also observed a significant number of L. biflexa membrane-associated proteins with multiple isoforms, each having unique isoelectric focusing points. L. biflexa cell lysates were examined for several posttranslational modifications suggested by the protein patterns. Methylation and acetylation of lysine residues were predominately observed in the proteins of the membrane-associated fraction, while phosphorylation was detected mainly among soluble proteins. These three posttranslational modification systems appear to be conserved between the free-living species L. biflexa and the pathogenic species Leptospira interrogans, suggesting an important physiological advantage despite the varied life cycles of the different species. PMID:26655756

Current Challenges in Detecting Food Allergens by Shotgun and Targeted Proteomic Approaches: A Case Study on Traces of Peanut Allergens in Baked Cookies

PubMed Central

Pedreschi, Romina; Nørgaard, Jørgen; Maquet, Alain

2012-01-01

There is a need for selective and sensitive methods to detect the presence of food allergens at trace levels in highly processed food products. In this work, a combination of non-targeted and targeted proteomics approaches are used to illustrate the difficulties encountered in the detection of the major peanut allergens Ara h 1, Ara h 2 and Ara h 3 from a representative processed food matrix. Shotgun proteomics was employed for selection of the proteotypic peptides for targeted approaches via selective reaction monitoring. Peanut presence through detection of the proteotypic Ara h 3/4 peptides AHVQVVDSNGNR (m/z 432.5, 3+) and SPDIYNPQAGSLK (m/z 695.4, 2+) was confirmed and the developed method was able to detect peanut presence at trace levels (≥10 μg peanut g−1 matrix) in baked cookies. PMID:22413066

Hybrid foraging search: Searching for multiple instances of multiple types of target.

PubMed

Wolfe, Jeremy M; Aizenman, Avigael M; Boettcher, Sage E P; Cain, Matthew S

2016-02-01

This paper introduces the "hybrid foraging" paradigm. In typical visual search tasks, observers search for one instance of one target among distractors. In hybrid search, observers search through visual displays for one instance of any of several types of target held in memory. In foraging search, observers collect multiple instances of a single target type from visual displays. Combining these paradigms, in hybrid foraging tasks observers search visual displays for multiple instances of any of several types of target (as might be the case in searching the kitchen for dinner ingredients or an X-ray for different pathologies). In the present experiment, observers held 8-64 target objects in memory. They viewed displays of 60-105 randomly moving photographs of objects and used the computer mouse to collect multiple targets before choosing to move to the next display. Rather than selecting at random among available targets, observers tended to collect items in runs of one target type. Reaction time (RT) data indicate searching again for the same item is more efficient than searching for any other targets, held in memory. Observers were trying to maximize collection rate. As a result, and consistent with optimal foraging theory, they tended to leave 25-33% of targets uncollected when moving to the next screen/patch. The pattern of RTs shows that while observers were collecting a target item, they had already begun searching memory and the visual display for additional targets, making the hybrid foraging task a useful way to investigate the interaction of visual and memory search. Copyright © 2015 Elsevier Ltd. All rights reserved.

Hybrid foraging search: Searching for multiple instances of multiple types of target

PubMed Central

Wolfe, Jeremy M.; Aizenman, Avigael M.; Boettcher, Sage E.P.; Cain, Matthew S.

2016-01-01

This paper introduces the “hybrid foraging” paradigm. In typical visual search tasks, observers search for one instance of one target among distractors. In hybrid search, observers search through visual displays for one instance of any of several types of target held in memory. In foraging search, observers collect multiple instances of a single target type from visual displays. Combining these paradigms, in hybrid foraging tasks observers search visual displays for multiple instances of any of several types of target (as might be the case in searching the kitchen for dinner ingredients or an X-ray for different pathologies). In the present experiment, observers held 8–64 targets objects in memory. They viewed displays of 60–105 randomly moving photographs of objects and used the computer mouse to collect multiple targets before choosing to move to the next display. Rather than selecting at random among available targets, observers tended to collect items in runs of one target type. Reaction time (RT) data indicate searching again for the same item is more efficient than searching for any other targets, held in memory. Observers were trying to maximize collection rate. As a result, and consistent with optimal foraging theory, they tended to leave 25–33% of targets uncollected when moving to the next screen/patch. The pattern of RTs shows that while observers were collecting a target item, they had already begun searching memory and the visual display for additional targets, making the hybrid foraging task a useful way to investigate the interaction of visual and memory search. PMID:26731644

Identification of novel biomarker and therapeutic target candidates for acute intracerebral hemorrhage by quantitative plasma proteomics.

PubMed

Li, Guo-Chun; Zhang, Lina; Yu, Ming; Jia, Haiyu; Tian, Ting; Wang, Junqin; Wang, Fuqiang; Zhou, Ling

2017-01-01

The systematic mechanisms of acute intracerebral hemorrhage are still unknown and unverified, although many recent researches have indicated the secondary insults. This study was aimed to disclose the pathological mechanism and identify novel biomarker and therapeutic target candidates by plasma proteome. Patients with AICH (n = 8) who demographically matched healthy controls (n = 4) were prospectively enrolled, and their plasma samples were obtained. The TMT-LC-MS/MS-based proteomics approach was used to quantify the differential proteome across plasma samples, and the results were analyzed by Ingenuity Pathway Analysis to explore canonical pathways and the relationship involved in the uploaded data. Compared with healthy controls, there were 31 differentially expressed proteins in the ICH group ( P  < 0.05), of which 21 proteins increased while 10 proteins decreased in abundance. These proteins are involved in 21 canonical pathways. One network with high confidence level was selected by the function network analysis, in which 23 proteins, P38MAPK and NFκB signaling pathways participated. Upstream regulator analysis found two regulators, IL6 and TNF, with an activation z -score. Seven biomarker candidates: APCS, FGB, LBP, MGMT, IGFBP2, LYZ, and APOA4 were found. Six candidate proteins were selected to assess the validity of the results by subsequent Western blotting analysis. Our analysis provided several intriguing pathways involved in ICH, like LXR/RXR activation, acute phase response signaling, and production of NO and ROS in macrophages pathways. The three upstream regulators: IL-6, TNF, LPS, and seven biomarker candidates: APCS, APOA4, FGB, IGFBP2, LBP, LYZ, and MGMT were uncovered. LPS, APOA4, IGFBP2, LBP, LYZ, and MGMT are novel potential biomarkers in ICH development. The identified proteins and pathways provide new perspectives to the potential pathological mechanism and therapeutic targets underlying ICH.

Effects of Hypertension and Exercise on Cardiac Proteome Remodelling

PubMed Central

Petriz, Bernardo A.; Franco, Octavio L.

2014-01-01

Left ventricle hypertrophy is a common outcome of pressure overload stimulus closely associated with hypertension. This process is triggered by adverse molecular signalling, gene expression, and proteome alteration. Proteomic research has revealed that several molecular targets are associated with pathologic cardiac hypertrophy, including angiotensin II, endothelin-1 and isoproterenol. Several metabolic, contractile, and stress-related proteins are shown to be altered in cardiac hypertrophy derived by hypertension. On the other hand, exercise is a nonpharmacologic agent used for hypertension treatment, where cardiac hypertrophy induced by exercise training is characterized by improvement in cardiac function and resistance against ischemic insult. Despite the scarcity of proteomic research performed with exercise, healthy and pathologic heart proteomes are shown to be modulated in a completely different way. Hence, the altered proteome induced by exercise is mostly associated with cardioprotective aspects such as contractile and metabolic improvement and physiologic cardiac hypertrophy. The present review, therefore, describes relevant studies involving the molecular characteristics and alterations from hypertensive-induced and exercise-induced hypertrophy, as well as the main proteomic research performed in this field. Furthermore, proteomic research into the effect of hypertension on other target-demerged organs is examined. PMID:24877123

Expediting SRM assay development for large-scale targeted proteomics experiments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Chaochao; Shi, Tujin; Brown, Joseph N.

2014-08-22

Due to their high sensitivity and specificity, targeted proteomics measurements, e.g. selected reaction monitoring (SRM), are becoming increasingly popular for biological and translational applications. Selection of optimal transitions and optimization of collision energy (CE) are important assay development steps for achieving sensitive detection and accurate quantification; however, these steps can be labor-intensive, especially for large-scale applications. Herein, we explored several options for accelerating SRM assay development evaluated in the context of a relatively large set of 215 synthetic peptide targets. We first showed that HCD fragmentation is very similar to CID in triple quadrupole (QQQ) instrumentation, and by selection ofmore » top six y fragment ions from HCD spectra, >86% of top transitions optimized from direct infusion on QQQ instrument are covered. We also demonstrated that the CE calculated by existing prediction tools was less accurate for +3 precursors, and a significant increase in intensity for transitions could be obtained using a new CE prediction equation constructed from the present experimental data. Overall, our study illustrates the feasibility of expediting the development of larger numbers of high-sensitivity SRM assays through automation of transitions selection and accurate prediction of optimal CE to improve both SRM throughput and measurement quality.« less

Multidimensional proteomics for cell biology.

PubMed

Larance, Mark; Lamond, Angus I

2015-05-01

The proteome is a dynamic system in which each protein has interconnected properties - dimensions - that together contribute to the phenotype of a cell. Measuring these properties has proved challenging owing to their diversity and dynamic nature. Advances in mass spectrometry-based proteomics now enable the measurement of multiple properties for thousands of proteins, including their abundance, isoform expression, turnover rate, subcellular localization, post-translational modifications and interactions. Complementing these experimental developments are new data analysis, integration and visualization tools as well as data-sharing resources. Together, these advances in the multidimensional analysis of the proteome are transforming our understanding of various cellular and physiological processes.

Sensor Compromise Detection in Multiple-Target Tracking Systems

PubMed Central

Doucette, Emily A.; Curtis, Jess W.

2018-01-01

Tracking multiple targets using a single estimator is a problem that is commonly approached within a trusted framework. There are many weaknesses that an adversary can exploit if it gains control over the sensors. Because the number of targets that the estimator has to track is not known with anticipation, an adversary could cause a loss of information or a degradation in the tracking precision. Other concerns include the introduction of false targets, which would result in a waste of computational and material resources, depending on the application. In this work, we study the problem of detecting compromised or faulty sensors in a multiple-target tracker, starting with the single-sensor case and then considering the multiple-sensor scenario. We propose an algorithm to detect a variety of attacks in the multiple-sensor case, via the application of finite set statistics (FISST), one-class classifiers and hypothesis testing using nonparametric techniques. PMID:29466314

Live dynamic imaging of caveolae pumping targeted antibody rapidly and specifically across endothelium in the lung.

PubMed

Oh, Phil; Borgström, Per; Witkiewicz, Halina; Li, Yan; Borgström, Bengt J; Chrastina, Adrian; Iwata, Koji; Zinn, Kurt R; Baldwin, Richard; Testa, Jacqueline E; Schnitzer, Jan E

2007-03-01

How effectively and quickly endothelial caveolae can transcytose in vivo is unknown, yet critical for understanding their function and potential clinical utility. Here we use quantitative proteomics to identify aminopeptidase P (APP) concentrated in caveolae of lung endothelium. Electron microscopy confirms this and shows that APP antibody targets nanoparticles to caveolae. Dynamic intravital fluorescence microscopy reveals that targeted caveolae operate effectively as pumps, moving antibody within seconds from blood across endothelium into lung tissue, even against a concentration gradient. This active transcytosis requires normal caveolin-1 expression. Whole body gamma-scintigraphic imaging shows rapid, specific delivery into lung well beyond that achieved by standard vascular targeting. This caveolar trafficking in vivo may underscore a key physiological mechanism for selective transvascular exchange and may provide an enhanced delivery system for imaging agents, drugs, gene-therapy vectors and nanomedicines. 'In vivo proteomic imaging' as described here integrates organellar proteomics with multiple imaging techniques to identify an accessible target space that includes the transvascular pumping space of the caveola.

Proteomics Analysis of Nucleolar SUMO-1 Target Proteins upon Proteasome Inhibition*

PubMed Central

Matafora, Vittoria; D'Amato, Alfonsina; Mori, Silvia; Blasi, Francesco; Bachi, Angela

2009-01-01

Many cellular processes are regulated by the coordination of several post-translational modifications that allow a very fine modulation of substrates. Recently it has been reported that there is a relationship between sumoylation and ubiquitination. Here we propose that the nucleolus is the key organelle in which SUMO-1 conjugates accumulate in response to proteasome inhibition. We demonstrated that, upon proteasome inhibition, the SUMO-1 nuclear dot localization is redirected to nucleolar structures. To better understand this process we investigated, by quantitative proteomics, the effect of proteasome activity on endogenous nucleolar SUMO-1 targets. 193 potential SUMO-1 substrates were identified, and interestingly in several purified SUMO-1 conjugates ubiquitin chains were found to be present, confirming the coordination of these two modifications. 23 SUMO-1 targets were confirmed by an in vitro sumoylation reaction performed on nuclear substrates. They belong to protein families such as small nuclear ribonucleoproteins, heterogeneous nuclear ribonucleoproteins, ribosomal proteins, histones, RNA-binding proteins, and transcription factor regulators. Among these, histone H1, histone H3, and p160 Myb-binding protein 1A were further characterized as novel SUMO-1 substrates. The analysis of the nature of the SUMO-1 targets identified in this study strongly indicates that sumoylation, acting in coordination with the ubiquitin-proteasome system, regulates the maintenance of nucleolar integrity. PMID:19596686

Designing multiple ligands - medicinal chemistry strategies and challenges.

PubMed

Morphy, Richard; Rankovic, Zoran

2009-01-01

It has been widely recognised over the recent years that parallel modulation of multiple biological targets can be beneficial for treatment of diseases with complex etiologies such as cancer asthma, and psychiatric disease. In this article, current strategies for the generation of ligands with a specific multi-target profile (designed multiple ligands or DMLs) are described and a number of illustrative example are given. Designing multiple ligands is frequently a challenging endeavour for medicinal chemists, with the need to appropriately balance affinity for 2 or more targets whilst obtaining physicochemical and pharmacokinetic properties that are consistent with the administration of an oral drug. Given that the properties of DMLs are influenced to a large extent by the proteomic superfamily to which the targets belong and the lead generation strategy that is pursued, an early assessment of the feasibility of any given DML project is essential.

Detection of alternative splice variants at the proteome level in Aspergillus flavus.

PubMed

Chang, Kung-Yen; Georgianna, D Ryan; Heber, Steffen; Payne, Gary A; Muddiman, David C

2010-03-05

Identification of proteins from proteolytic peptides or intact proteins plays an essential role in proteomics. Researchers use search engines to match the acquired peptide sequences to the target proteins. However, search engines depend on protein databases to provide candidates for consideration. Alternative splicing (AS), the mechanism where the exon of pre-mRNAs can be spliced and rearranged to generate distinct mRNA and therefore protein variants, enable higher eukaryotic organisms, with only a limited number of genes, to have the requisite complexity and diversity at the proteome level. Multiple alternative isoforms from one gene often share common segments of sequences. However, many protein databases only include a limited number of isoforms to keep minimal redundancy. As a result, the database search might not identify a target protein even with high quality tandem MS data and accurate intact precursor ion mass. We computationally predicted an exhaustive list of putative isoforms of Aspergillus flavus proteins from 20 371 expressed sequence tags to investigate whether an alternative splicing protein database can assign a greater proportion of mass spectrometry data. The newly constructed AS database provided 9807 new alternatively spliced variants in addition to 12 832 previously annotated proteins. The searches of the existing tandem MS spectra data set using the AS database identified 29 new proteins encoded by 26 genes. Nine fungal genes appeared to have multiple protein isoforms. In addition to the discovery of splice variants, AS database also showed potential to improve genome annotation. In summary, the introduction of an alternative splicing database helps identify more proteins and unveils more information about a proteome.

Quantitative Proteomics Reveals Temporal Proteomic Changes in Signaling Pathways during BV2 Mouse Microglial Cell Activation.

PubMed

Woo, Jongmin; Han, Dohyun; Wang, Joseph Injae; Park, Joonho; Kim, Hyunsoo; Kim, Youngsoo

2017-09-01

The development of systematic proteomic quantification techniques in systems biology research has enabled one to perform an in-depth analysis of cellular systems. We have developed a systematic proteomic approach that encompasses the spectrum from global to targeted analysis on a single platform. We have applied this technique to an activated microglia cell system to examine changes in the intracellular and extracellular proteomes. Microglia become activated when their homeostatic microenvironment is disrupted. There are varying degrees of microglial activation, and we chose to focus on the proinflammatory reactive state that is induced by exposure to such stimuli as lipopolysaccharide (LPS) and interferon-gamma (IFN-γ). Using an improved shotgun proteomics approach, we identified 5497 proteins in the whole-cell proteome and 4938 proteins in the secretome that were associated with the activation of BV2 mouse microglia by LPS or IFN-γ. Of the differentially expressed proteins in stimulated microglia, we classified pathways that were related to immune-inflammatory responses and metabolism. Our label-free parallel reaction monitoring (PRM) approach made it possible to comprehensively measure the hyper-multiplex quantitative value of each protein by high-resolution mass spectrometry. Over 450 peptides that corresponded to pathway proteins and direct or indirect interactors via the STRING database were quantified by label-free PRM in a single run. Moreover, we performed a longitudinal quantification of secreted proteins during microglial activation, in which neurotoxic molecules that mediate neuronal cell loss in the brain are released. These data suggest that latent pathways that are associated with neurodegenerative diseases can be discovered by constructing and analyzing a pathway network model of proteins. Furthermore, this systematic quantification platform has tremendous potential for applications in large-scale targeted analyses. The proteomics data for

A mathematical analysis of multiple-target SELEX.

PubMed

Seo, Yeon-Jung; Chen, Shiliang; Nilsen-Hamilton, Marit; Levine, Howard A

2010-10-01

SELEX (Systematic Evolution of Ligands by Exponential Enrichment) is a procedure by which a mixture of nucleic acids can be fractionated with the goal of identifying those with specific biochemical activities. One combines the mixture with a specific target molecule and then separates the target-NA complex from the resulting reactions. The target-NA complex is separated from the unbound NA by mechanical means (such as by filtration), the NA is eluted from the complex, amplified by PCR (polymerase chain reaction), and the process repeated. After several rounds, one should be left with the nucleic acids that best bind to the target. The problem was first formulated mathematically in Irvine et al. (J. Mol. Biol. 222:739-761, 1991). In Levine and Nilsen-Hamilton (Comput. Biol. Chem. 31:11-25, 2007), a mathematical analysis of the process was given. In Vant-Hull et al. (J. Mol. Biol. 278:579-597, 1998), multiple target SELEX was considered. It was assumed that each target has a single nucleic acid binding site that permits occupation by no more than one nucleic acid. Here, we revisit Vant-Hull et al. (J. Mol. Biol. 278:579-597, 1998) using the same assumptions. The iteration scheme is shown to be convergent and a simplified algorithm is given. Our interest here is in the behavior of the multiple target SELEX process as a discrete "time" dynamical system. Our goal is to characterize the limiting states and their dependence on the initial distribution of nucleic acid and target fraction components. (In multiple target SELEX, we vary the target component fractions, but not their concentrations, as fixed and the initial pool of nucleic acids as a variable starting condition). Given N nucleic acids and a target consisting of M subtarget component species, there is an M × N matrix of affinities, the (i,j) entry corresponding to the affinity of the jth nucleic acid for the ith subtarget. We give a structure condition on this matrix that is equivalent to the following

Tetrazine ligation for chemical proteomics.

PubMed

Kang, Kyungtae; Park, Jongmin; Kim, Eunha

2016-01-01

Determining small molecule-target protein interaction is essential for the chemical proteomics. One of the most important keys to explore biological system in chemical proteomics field is finding first-class molecular tools. Chemical probes can provide great spatiotemporal control to elucidate biological functions of proteins as well as for interrogating biological pathways. The invention of bioorthogonal chemistry has revolutionized the field of chemical biology by providing superior chemical tools and has been widely used for investigating the dynamics and function of biomolecules in live condition. Among 20 different bioorthogonal reactions, tetrazine ligation has been spotlighted as the most advanced bioorthogonal chemistry because of their extremely faster kinetics and higher specificity than others. Therefore, tetrazine ligation has a tremendous potential to enhance the proteomic research. This review highlights the current status of tetrazine ligation reaction as a molecular tool for the chemical proteomics.

Proteomic and biochemical assays of glutathione-related proteins in susceptible and multiple herbicide resistant Avena fatua L.

PubMed

Burns, Erin E; Keith, Barbara K; Refai, Mohammed Y; Bothner, Brian; Dyer, William E

2017-08-01

Extensive herbicide usage has led to the evolution of resistant weed populations that cause substantial crop yield losses and increase production costs. The multiple herbicide resistant (MHR) Avena fatua L. populations utilized in this study are resistant to members of all selective herbicide families, across five modes of action, available for A. fatua control in U.S. small grain production, and thus pose significant agronomic and economic threats. Resistance to ALS and ACCase inhibitors is not conferred by target site mutations, indicating that non-target site resistance mechanisms are involved. To investigate the potential involvement of glutathione-related enzymes in the MHR phenotype, we used a combination of proteomic, biochemical, and immunological approaches to compare their constitutive activities in herbicide susceptible (HS1 and HS2) and MHR (MHR3 and MHR4) A. fatua plants. Proteomic analysis identified three tau and one phi glutathione S-transferases (GSTs) present at higher levels in MHR compared to HS plants, while immunoassays revealed elevated levels of lambda, phi, and tau GSTs. GST specific activity towards 1-chloro-2,4-dinitrobenzene was 1.2-fold higher in MHR4 than in HS1 plants and 1.3- and 1.2-fold higher in MHR3 than in HS1 and HS2 plants, respectively. However, GST specific activities towards fenoxaprop-P-ethyl and imazamethabenz-methyl were not different between untreated MHR and HS plants. Dehydroascorbate reductase specific activity was 1.4-fold higher in MHR than HS plants. Pretreatment with the GST inhibitor NBD-Cl did not affect MHR sensitivity to fenoxaprop-P-ethyl application, while the herbicide safener and GST inducer mefenpyr reduced the efficacy of low doses of fenoxaprop-P-ethyl on MHR4 but not MHR3 plants. Mefenpyr treatment also partially reduced the efficacy of thiencarbazone-methyl or mesosulfuron-methyl on MHR3 or MHR4 plants, respectively. Overall, the GSTs described here are not directly involved in enhanced rates of

MCAM: multiple clustering analysis methodology for deriving hypotheses and insights from high-throughput proteomic datasets.

PubMed

Naegle, Kristen M; Welsch, Roy E; Yaffe, Michael B; White, Forest M; Lauffenburger, Douglas A

2011-07-01

Advances in proteomic technologies continue to substantially accelerate capability for generating experimental data on protein levels, states, and activities in biological samples. For example, studies on receptor tyrosine kinase signaling networks can now capture the phosphorylation state of hundreds to thousands of proteins across multiple conditions. However, little is known about the function of many of these protein modifications, or the enzymes responsible for modifying them. To address this challenge, we have developed an approach that enhances the power of clustering techniques to infer functional and regulatory meaning of protein states in cell signaling networks. We have created a new computational framework for applying clustering to biological data in order to overcome the typical dependence on specific a priori assumptions and expert knowledge concerning the technical aspects of clustering. Multiple clustering analysis methodology ('MCAM') employs an array of diverse data transformations, distance metrics, set sizes, and clustering algorithms, in a combinatorial fashion, to create a suite of clustering sets. These sets are then evaluated based on their ability to produce biological insights through statistical enrichment of metadata relating to knowledge concerning protein functions, kinase substrates, and sequence motifs. We applied MCAM to a set of dynamic phosphorylation measurements of the ERRB network to explore the relationships between algorithmic parameters and the biological meaning that could be inferred and report on interesting biological predictions. Further, we applied MCAM to multiple phosphoproteomic datasets for the ERBB network, which allowed us to compare independent and incomplete overlapping measurements of phosphorylation sites in the network. We report specific and global differences of the ERBB network stimulated with different ligands and with changes in HER2 expression. Overall, we offer MCAM as a broadly-applicable approach

Whole CMV Proteome Pattern Recognition Analysis after HSCT Identifies Unique Epitope Targets Associated with the CMV Status

PubMed Central

Pérez-Bercoff, Lena; Valentini, Davide; Gaseitsiwe, Simani; Mahdavifar, Shahnaz; Schutkowski, Mike; Poiret, Thomas; Pérez-Bercoff, Åsa; Ljungman, Per; Maeurer, Markus J.

2014-01-01

Cytomegalovirus (CMV) infection represents a vital complication after Hematopoietic Stem Cell Transplantation (HSCT). We screened the entire CMV proteome to visualize the humoral target epitope-focus profile in serum after HSCT. IgG profiling from four patient groups (donor and/or recipient +/− for CMV) was performed at 6, 12 and 24 months after HSCT using microarray slides containing 17174 of 15mer-peptides overlapping by 4 aa covering 214 proteins from CMV. Data were analyzed using maSigPro, PAM and the ‘exclusive recognition analysis (ERA)’ to identify unique CMV epitope responses for each patient group. The ‘exclusive recognition analysis’ of serum epitope patterns segregated best 12 months after HSCT for the D+/R+ group (versus D−/R−). Epitopes were derived from UL123 (IE1), UL99 (pp28), UL32 (pp150), this changed at 24 months to 2 strongly recognized peptides provided from UL123 and UL100. Strongly (IgG) recognized CMV targets elicited also robust cytokine production in T-cells from patients after HSCT defined by intracellular cytokine staining (IL-2, TNF, IFN and IL-17). High-content peptide microarrays allow epitope profiling of entire viral proteomes; this approach can be useful to map relevant targets for diagnostics and therapy in patients with well defined clinical endpoints. Peptide microarray analysis visualizes the breadth of B-cell immune reconstitution after HSCT and provides a useful tool to gauge immune reconstitution. PMID:24740411

Spatial-Resolution Cell Type Proteome Profiling of Cancer Tissue by Fully Integrated Proteomics Technology.

PubMed

Xu, Ruilian; Tang, Jun; Deng, Quantong; He, Wan; Sun, Xiujie; Xia, Ligang; Cheng, Zhiqiang; He, Lisheng; You, Shuyuan; Hu, Jintao; Fu, Yuxiang; Zhu, Jian; Chen, Yixin; Gao, Weina; He, An; Guo, Zhengyu; Lin, Lin; Li, Hua; Hu, Chaofeng; Tian, Ruijun

2018-05-01

Increasing attention has been focused on cell type proteome profiling for understanding the heterogeneous multicellular microenvironment in tissue samples. However, current cell type proteome profiling methods need large amounts of starting materials which preclude their application to clinical tumor specimens with limited access. Here, by seamlessly combining laser capture microdissection and integrated proteomics sample preparation technology SISPROT, specific cell types in tumor samples could be precisely dissected with single cell resolution and processed for high-sensitivity proteome profiling. Sample loss and contamination due to the multiple transfer steps are significantly reduced by the full integration and noncontact design. H&E staining dyes which are necessary for cell type investigation could be selectively removed by the unique two-stage design of the spintip device. This easy-to-use proteome profiling technology achieved high sensitivity with the identification of more than 500 proteins from only 0.1 mm 2 and 10 μm thickness colon cancer tissue section. The first cell type proteome profiling of four cell types from one colon tumor and surrounding normal tissue, including cancer cells, enterocytes, lymphocytes, and smooth muscle cells, was obtained. 5271, 4691, 4876, and 2140 protein groups were identified, respectively, from tissue section of only 5 mm 2 and 10 μm thickness. Furthermore, spatially resolved proteome distribution profiles of enterocytes, lymphocytes, and smooth muscle cells on the same tissue slices and across four consecutive sections with micrometer distance were successfully achieved. This fully integrated proteomics technology, termed LCM-SISPROT, is therefore promising for spatial-resolution cell type proteome profiling of tumor microenvironment with a minute amount of clinical starting materials.

Multiple Posttranslational Modifications of Leptospira biflexa Proteins as Revealed by Proteomic Analysis.

PubMed

Stewart, Philip E; Carroll, James A; Olano, L Rennee; Sturdevant, Daniel E; Rosa, Patricia A

2016-02-15

The saprophyte Leptospira biflexa is an excellent model for studying the physiology of the medically important Leptospira genus, the pathogenic members of which are more recalcitrant to genetic manipulation and have significantly slower in vitro growth. However, relatively little is known regarding the proteome of L. biflexa, limiting its utility as a model for some studies. Therefore, we have generated a proteomic map of both soluble and membrane-associated proteins of L. biflexa during exponential growth and in stationary phase. Using these data, we identified abundantly produced proteins in each cellular fraction and quantified the transcript levels from a subset of these genes using quantitative reverse transcription-PCR (RT-PCR). These proteins should prove useful as cellular markers and as controls for gene expression studies. We also observed a significant number of L. biflexa membrane-associated proteins with multiple isoforms, each having unique isoelectric focusing points. L. biflexa cell lysates were examined for several posttranslational modifications suggested by the protein patterns. Methylation and acetylation of lysine residues were predominately observed in the proteins of the membrane-associated fraction, while phosphorylation was detected mainly among soluble proteins. These three posttranslational modification systems appear to be conserved between the free-living species L. biflexa and the pathogenic species Leptospira interrogans, suggesting an important physiological advantage despite the varied life cycles of the different species. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Proteomic Profiling of Cranial (Superior) Cervical Ganglia Reveals Beta-Amyloid and Ubiquitin Proteasome System Perturbations in an Equine Multiple System Neuropathy.

PubMed

McGorum, Bruce C; Pirie, R Scott; Eaton, Samantha L; Keen, John A; Cumyn, Elizabeth M; Arnott, Danielle M; Chen, Wenzhang; Lamont, Douglas J; Graham, Laura C; Llavero Hurtado, Maica; Pemberton, Alan; Wishart, Thomas M

2015-11-01

Equine grass sickness (EGS) is an acute, predominantly fatal, multiple system neuropathy of grazing horses with reported incidence rates of ∼2%. An apparently identical disease occurs in multiple species, including but not limited to cats, dogs, and rabbits. Although the precise etiology remains unclear, ultrastructural findings have suggested that the primary lesion lies in the glycoprotein biosynthetic pathway of specific neuronal populations. The goal of this study was therefore to identify the molecular processes underpinning neurodegeneration in EGS. Here, we use a bottom-up approach beginning with the application of modern proteomic tools to the analysis of cranial (superior) cervical ganglion (CCG, a consistently affected tissue) from EGS-affected patients and appropriate control cases postmortem. In what appears to be the proteomic application of modern proteomic tools to equine neuronal tissues and/or to an inherent neurodegenerative disease of large animals (not a model of human disease), we identified 2,311 proteins in CCG extracts, with 320 proteins increased and 186 decreased by greater than 20% relative to controls. Further examination of selected proteomic candidates by quantitative fluorescent Western blotting (QFWB) and subcellular expression profiling by immunohistochemistry highlighted a previously unreported dysregulation in proteins commonly associated with protein misfolding/aggregation responses seen in a myriad of human neurodegenerative conditions, including but not limited to amyloid precursor protein (APP), microtubule associated protein (Tau), and multiple components of the ubiquitin proteasome system (UPS). Differentially expressed proteins eligible for in silico pathway analysis clustered predominantly into the following biofunctions: (1) diseases and disorders, including; neurological disease and skeletal and muscular disorders and (2) molecular and cellular functions, including cellular assembly and organization, cell

Building high-quality assay libraries for targeted analysis of SWATH MS data.

PubMed

Schubert, Olga T; Gillet, Ludovic C; Collins, Ben C; Navarro, Pedro; Rosenberger, George; Wolski, Witold E; Lam, Henry; Amodei, Dario; Mallick, Parag; MacLean, Brendan; Aebersold, Ruedi

2015-03-01

Targeted proteomics by selected/multiple reaction monitoring (S/MRM) or, on a larger scale, by SWATH (sequential window acquisition of all theoretical spectra) MS (mass spectrometry) typically relies on spectral reference libraries for peptide identification. Quality and coverage of these libraries are therefore of crucial importance for the performance of the methods. Here we present a detailed protocol that has been successfully used to build high-quality, extensive reference libraries supporting targeted proteomics by SWATH MS. We describe each step of the process, including data acquisition by discovery proteomics, assertion of peptide-spectrum matches (PSMs), generation of consensus spectra and compilation of MS coordinates that uniquely define each targeted peptide. Crucial steps such as false discovery rate (FDR) control, retention time normalization and handling of post-translationally modified peptides are detailed. Finally, we show how to use the library to extract SWATH data with the open-source software Skyline. The protocol takes 2-3 d to complete, depending on the extent of the library and the computational resources available.

Affordable proteomics: the two-hybrid systems.

PubMed

Gillespie, Marc

2003-06-01

Numerous proteomic methodologies exist, but most require a heavy investment in expertise and technology. This puts these approaches out of reach for many laboratories and small companies, rarely allowing proteomics to be used as a pilot approach for biomarker or target identification. Two proteomic approaches, 2D gel electrophoresis and the two-hybrid systems, are currently available to most researchers. The two-hybrid systems, though accommodating to large-scale experiments, were originally designed as practical screens, that by comparison to current proteomics tools were small-scale, affordable and technically feasible. The screens rapidly generated data, identifying protein interactions that were previously uncharacterized. The foundation for a two-hybrid proteomic investigation can be purchased as separate kits from a number of companies. The true power of the technique lies not in its affordability, but rather in its portability. The two-hybrid system puts proteomics back into laboratories where the output of the screens can be evaluated by researchers with experience in the particular fields of basic research, cancer biology, toxicology or drug development.

Application of targeted quantitative proteomics analysis in human cerebrospinal fluid using a liquid chromatography matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (LC MALDI TOF/TOF) platform.

PubMed

Pan, Sheng; Rush, John; Peskind, Elaine R; Galasko, Douglas; Chung, Kathryn; Quinn, Joseph; Jankovic, Joseph; Leverenz, James B; Zabetian, Cyrus; Pan, Catherine; Wang, Yan; Oh, Jung Hun; Gao, Jean; Zhang, Jianpeng; Montine, Thomas; Zhang, Jing

2008-02-01

Targeted quantitative proteomics by mass spectrometry aims to selectively detect one or a panel of peptides/proteins in a complex sample and is particularly appealing for novel biomarker verification/validation because it does not require specific antibodies. Here, we demonstrated the application of targeted quantitative proteomics in searching, identifying, and quantifying selected peptides in human cerebrospinal spinal fluid (CSF) using a matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (MALDI TOF/TOF)-based platform. The approach involved two major components: the use of isotopic-labeled synthetic peptides as references for targeted identification and quantification and a highly selective mass spectrometric analysis based on the unique characteristics of the MALDI instrument. The platform provides high confidence for targeted peptide detection in a complex system and can potentially be developed into a high-throughput system. Using the liquid chromatography (LC) MALDI TOF/TOF platform and the complementary identification strategy, we were able to selectively identify and quantify a panel of targeted peptides in the whole proteome of CSF without prior depletion of abundant proteins. The effectiveness and robustness of the approach associated with different sample complexity, sample preparation strategies, as well as mass spectrometric quantification were evaluated. Other issues related to chromatography separation and the feasibility for high-throughput analysis were also discussed. Finally, we applied targeted quantitative proteomics to analyze a subset of previously identified candidate markers in CSF samples of patients with Parkinson's disease (PD) at different stages and Alzheimer's disease (AD) along with normal controls.

Genomes2Drugs: Identifies Target Proteins and Lead Drugs from Proteome Data

PubMed Central

Toomey, David; Hoppe, Heinrich C.; Brennan, Marian P.; Nolan, Kevin B.; Chubb, Anthony J.

2009-01-01

Background Genome sequencing and bioinformatics have provided the full hypothetical proteome of many pathogenic organisms. Advances in microarray and mass spectrometry have also yielded large output datasets of possible target proteins/genes. However, the challenge remains to identify new targets for drug discovery from this wealth of information. Further analysis includes bioinformatics and/or molecular biology tools to validate the findings. This is time consuming and expensive, and could fail to yield novel drugs if protein purification and crystallography is impossible. To pre-empt this, a researcher may want to rapidly filter the output datasets for proteins that show good homology to proteins that have already been structurally characterised or proteins that are already targets for known drugs. Critically, those researchers developing novel antibiotics need to select out the proteins that show close homology to any human proteins, as future inhibitors are likely to cross-react with the host protein, causing off-target toxicity effects later in clinical trials. Methodology/Principal Findings To solve many of these issues, we have developed a free online resource called Genomes2Drugs which ranks sequences to identify proteins that are (i) homologous to previously crystallized proteins or (ii) targets of known drugs, but are (iii) not homologous to human proteins. When tested using the Plasmodium falciparum malarial genome the program correctly enriched the ranked list of proteins with known drug target proteins. Conclusions/Significance Genomes2Drugs rapidly identifies proteins that are likely to succeed in drug discovery pipelines. This free online resource helps in the identification of potential drug targets. Importantly, the program further highlights proteins that are likely to be inhibited by FDA-approved drugs. These drugs can then be rapidly moved into Phase IV clinical studies under ‘change-of-application’ patents. PMID:19593435

Interaction Analysis through Proteomic Phage Display

PubMed Central

2014-01-01

Phage display is a powerful technique for profiling specificities of peptide binding domains. The method is suited for the identification of high-affinity ligands with inhibitor potential when using highly diverse combinatorial peptide phage libraries. Such experiments further provide consensus motifs for genome-wide scanning of ligands of potential biological relevance. A complementary but considerably less explored approach is to display expression products of genomic DNA, cDNA, open reading frames (ORFs), or oligonucleotide libraries designed to encode defined regions of a target proteome on phage particles. One of the main applications of such proteomic libraries has been the elucidation of antibody epitopes. This review is focused on the use of proteomic phage display to uncover protein-protein interactions of potential relevance for cellular function. The method is particularly suited for the discovery of interactions between peptide binding domains and their targets. We discuss the largely unexplored potential of this method in the discovery of domain-motif interactions of potential biological relevance. PMID:25295249

eIF4E and eIF4GI have distinct and differential imprints on multiple myeloma's proteome and signaling

PubMed Central

Attar-Schneider, Oshrat; Pasmanik-Chor, Metsada; Tartakover-Matalon, Shelly

2015-01-01

Accumulating data indicate translation plays a role in cancer biology, particularly its rate limiting stage of initiation. Despite this evolving recognition, the function and importance of specific translation initiation factors is unresolved. The eukaryotic translation initiation complex eIF4F consists of eIF4E and eIF4G at a 1:1 ratio. Although it is expected that they display interdependent functions, several publications suggest independent mechanisms. This study is the first to directly assess the relative contribution of eIF4F components to the expressed cellular proteome, transcription factors, microRNAs, and phenotype in a malignancy known for extensive protein synthesis-multiple myeloma (MM). Previously, we have shown that eIF4E/eIF4GI attenuation (siRNA/Avastin) deleteriously affected MM cells' fate and reduced levels of eIF4E/eIF4GI established targets. Here, we demonstrated that eIF4E/eIF4GI indeed have individual influences on cell proteome. We used an objective, high throughput assay of mRNA microarrays to examine the significance of eIF4E/eIF4GI silencing to several cellular facets such as transcription factors, microRNAs and phenotype. We showed different imprints for eIF4E and eIF4GI in all assayed aspects. These results promote our understanding of the relative contribution and importance of eIF4E and eIF4GI to the malignant phenotype and shed light on their function in eIF4F translation initiation complex. PMID:25717031

Target-similarity search using Plasmodium falciparum proteome identifies approved drugs with anti-malarial activity and their possible targets

PubMed Central

Akala, Hoseah M.; Macharia, Rosaline W.; Juma, Dennis W.; Cheruiyot, Agnes C.; Andagalu, Ben; Brown, Mathew L.; El-Shemy, Hany A.; Nyanjom, Steven G.

2017-01-01

Malaria causes about half a million deaths annually, with Plasmodium falciparum being responsible for 90% of all the cases. Recent reports on artemisinin resistance in Southeast Asia warrant urgent discovery of novel drugs for the treatment of malaria. However, most bioactive compounds fail to progress to treatments due to safety concerns. Drug repositioning offers an alternative strategy where drugs that have already been approved as safe for other diseases could be used to treat malaria. This study screened approved drugs for antimalarial activity using an in silico chemogenomics approach prior to in vitro verification. All the P. falciparum proteins sequences available in NCBI RefSeq were mined and used to perform a similarity search against DrugBank, TTD and STITCH databases to identify similar putative drug targets. Druggability indices of the potential P. falciparum drug targets were obtained from TDR targets database. Functional amino acid residues of the drug targets were determined using ConSurf server which was used to fine tune the similarity search. This study predicted 133 approved drugs that could target 34 P. falciparum proteins. A literature search done at PubMed and Google Scholar showed 105 out of the 133 drugs to have been previously tested against malaria, with most showing activity. For further validation, drug susceptibility assays using SYBR Green I method were done on a representative group of 10 predicted drugs, eight of which did show activity against P. falciparum 3D7 clone. Seven had IC50 values ranging from 1 μM to 50 μM. This study also suggests drug-target association and hence possible mechanisms of action of drugs that did show antiplasmodial activity. The study results validate the use of proteome-wide target similarity approach in identifying approved drugs with activity against P. falciparum and could be adapted for other pathogens. PMID:29088219

Memory for found targets interferes with subsequent performance in multiple-target visual search.

PubMed

Cain, Matthew S; Mitroff, Stephen R

2013-10-01

Multiple-target visual searches--when more than 1 target can appear in a given search display--are commonplace in radiology, airport security screening, and the military. Whereas 1 target is often found accurately, additional targets are more likely to be missed in multiple-target searches. To better understand this decrement in 2nd-target detection, here we examined 2 potential forms of interference that can arise from finding a 1st target: interference from the perceptual salience of the 1st target (a now highly relevant distractor in a known location) and interference from a newly created memory representation for the 1st target. Here, we found that removing found targets from the display or making them salient and easily segregated color singletons improved subsequent search accuracy. However, replacing found targets with random distractor items did not improve subsequent search accuracy. Removing and highlighting found targets likely reduced both a target's visual salience and its memory load, whereas replacing a target removed its visual salience but not its representation in memory. Collectively, the current experiments suggest that the working memory load of a found target has a larger effect on subsequent search accuracy than does its perceptual salience. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Deep-proteome mapping of WM-266-4 human metastatic melanoma cells: From oncogenic addiction to druggable targets

PubMed Central

Litou, Zoi I.; Konstandi, Ourania A.; Giannopoulou, Aikaterini F.; Anastasiadou, Ema; Voutsinas, Gerassimos E.; Tsangaris, George Th.; Stravopodis, Dimitrios J.

2017-01-01

Cutaneous melanoma is a malignant tumor of skin melanocytes that are pigment-producing cells located in the basal layer (stratum basale) of epidermis. Accumulation of genetic mutations within their oncogenes or tumor-suppressor genes compels melanocytes to aberrant proliferation and spread to distant organs of the body, thereby resulting in severe and/or lethal malignancy. Metastatic melanoma’s heavy mutational load, molecular heterogeneity and resistance to therapy necessitate the development of novel biomarkers and drug-based protocols that target key proteins involved in perpetuation of the disease. To this direction, we have herein employed a nano liquid chromatography-tandem mass spectrometry (nLC-MS/MS) proteomics technology to profile the deep-proteome landscape of WM-266-4 human metastatic melanoma cells. Our advanced melanoma-specific catalogue proved to contain 6,681 unique proteins, which likely constitute the hitherto largest single cell-line-derived proteomic collection of the disease. Through engagement of UNIPROT, DAVID, KEGG, PANTHER, INTACT, CYTOSCAPE, dbEMT and GAD bioinformatics resources, WM-266-4 melanoma proteins were categorized according to their sub-cellular compartmentalization, function and tumorigenicity, and successfully reassembled in molecular networks and interactomes. The obtained data dictate the presence of plastically inter-converted sub-populations of non-cancer and cancer stem cells, and also indicate the oncoproteomic resemblance of melanoma to glioma and lung cancer. Intriguingly, WM-266-4 cells seem to be subjected to both epithelial-to-mesenchymal (EMT) and mesenchymal-to-epithelial (MET) programs, with 1433G and ADT3 proteins being identified in the EMT/MET molecular interface. Oncogenic addiction of WM-266-4 cells to autocrine/paracrine signaling of IL17-, DLL3-, FGF(2/13)- and OSTP-dependent sub-routines suggests their critical contribution to the metastatic melanoma chemotherapeutic refractoriness. Interestingly, the

GenomewidePDB 2.0: A Newly Upgraded Versatile Proteogenomic Database for the Chromosome-Centric Human Proteome Project.

PubMed

Jeong, Seul-Ki; Hancock, William S; Paik, Young-Ki

2015-09-04

Since the launch of the Chromosome-centric Human Proteome Project (C-HPP) in 2012, the number of "missing" proteins has fallen to 2932, down from ∼5932 since the number was first counted in 2011. We compared the characteristics of missing proteins with those of already annotated proteins with respect to transcriptional expression pattern and the time periods in which newly identified proteins were annotated. We learned that missing proteins commonly exhibit lower levels of transcriptional expression and less tissue-specific expression compared with already annotated proteins. This makes it more difficult to identify missing proteins as time goes on. One of the C-HPP goals is to identify alternative spliced product of proteins (ASPs), which are usually difficult to find by shot-gun proteomic methods due to their sequence similarities with the representative proteins. To resolve this problem, it may be necessary to use a targeted proteomics approach (e.g., selected and multiple reaction monitoring [S/MRM] assays) and an innovative bioinformatics platform that enables the selection of target peptides for rarely expressed missing proteins or ASPs. Given that the success of efforts to identify missing proteins may rely on more informative public databases, it was necessary to upgrade the available integrative databases. To this end, we attempted to improve the features and utility of GenomewidePDB by integrating transcriptomic information (e.g., alternatively spliced transcripts), annotated peptide information, and an advanced search interface that can find proteins of interest when applying a targeted proteomics strategy. This upgraded version of the database, GenomewidePDB 2.0, may not only expedite identification of the remaining missing proteins but also enhance the exchange of information among the proteome community. GenomewidePDB 2.0 is available publicly at http://genomewidepdb.proteomix.org/.

Key players in neurodegenerative disorders in focus-New insights into the proteomic profile of Alzheimer's disease, schizophrenia, ALS, and multiple sclerosis-24th HUPO BPP Workshop: September 29, 2015, Vancouver, Canada.

PubMed

Schrötter, Andreas; Park, Young Mok; Marcus, Katrin; Martins-de-Souza, Daniel; Nilsson, Peter; Magraoui, Fouzi El; Meyer, Helmut E; Grinberg, Lea T

2016-04-01

The HUPO Brain Proteome Project (HUPO BPP) held its 24th workshop in Vancouver, Canada, September 29, 2015. The focus of the autumn workshop was on new insights into the proteomic profile of Alzheimer's disease, schizophrenia, ALS and multiple sclerosis. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative proteomics in Giardia duodenalis-Achievements and challenges.

PubMed

Emery, Samantha J; Lacey, Ernest; Haynes, Paul A

2016-08-01

Giardia duodenalis (syn. G. lamblia and G. intestinalis) is a protozoan parasite of vertebrates and a major contributor to the global burden of diarrheal diseases and gastroenteritis. The publication of multiple genome sequences in the G. duodenalis species complex has provided important insights into parasite biology, and made post-genomic technologies, including proteomics, significantly more accessible. The aims of proteomics are to identify and quantify proteins present in a cell, and assign functions to them within the context of dynamic biological systems. In Giardia, proteomics in the post-genomic era has transitioned from reliance on gel-based systems to utilisation of a diverse array of techniques based on bottom-up LC-MS/MS technologies. Together, these have generated crucial foundations for subcellular proteomes, elucidated intra- and inter-assemblage isolate variation, and identified pathways and markers in differentiation, host-parasite interactions and drug resistance. However, in Giardia, proteomics remains an emerging field, with considerable shortcomings evident from the published research. These include a bias towards assemblage A, a lack of emphasis on quantitative analytical techniques, and limited information on post-translational protein modifications. Additionally, there are multiple areas of research for which proteomic data is not available to add value to published transcriptomic data. The challenge of amalgamating data in the systems biology paradigm necessitates the further generation of large, high-quality quantitative datasets to accurately model parasite biology. This review surveys the current proteomic research available for Giardia and evaluates their technical and quantitative approaches, while contextualising their biological insights into parasite pathology, isolate variation and eukaryotic evolution. Finally, we propose areas of priority for the generation of future proteomic data to explore fundamental questions in Giardia

Identification and validation nucleolin as a target of curcumol in nasopharyngeal carcinoma cells.

PubMed

Wang, Juan; Wu, Jiacai; Li, Xumei; Liu, Haowei; Qin, Jianli; Bai, Zhun; Chi, Bixia; Chen, Xu

2018-06-30

Identification of the specific protein target(s) of a drug is a critical step in unraveling its mechanisms of action (MOA) in many natural products. Curcumol, isolated from well known Chinese medicinal plant Curcuma zedoary, has been shown to possess multiple biological activities. It can inhibit nasopharyngeal carcinoma (NPC) proliferation and induce apoptosis, but its target protein(s) in NPC cells remains unclear. In this study, we employed a mass spectrometry-based chemical proteomics approach reveal the possible protein targets of curcumol in NPC cells. Cellular thermal shift assay (CETSA), molecular docking and cell-based assay was used to validate the binding interactions. Chemical proteomics capturing uncovered that NCL is a target of curcumol in NPC cells, Molecular docking showed that curcumol bound to NCL with an -7.8 kcal/mol binding free energy. Cell function analysis found that curcumol's treatment leads to a degradation of NCL in NPC cells, and it showed slight effects on NP69 cells. In conclusion, our results providing evidences that NCL is a target protein of curcumol. We revealed that the anti-cancer effects of curcumol in NPC cells are mediated, at least in part, by NCL inhibition. Many natural products showed high bioactivity, while their mechanisms of action (MOA) are very poor or completely missed. Understanding the MOA of natural drugs can thoroughly exploit their therapeutic potential and minimize their adverse side effects. Identification of the specific protein target(s) of a drug is a critical step in unraveling its MOA. Compound-centric chemical proteomics is a classic chemical proteomics approach which integrates chemical synthesis with cell biology and mass spectrometry (MS) to identify protein targets of natural products determine the drug mechanism of action, describe its toxicity, and figure out the possible cause of off-target. It is an affinity-based chemical proteomics method to identify small molecule-protein interactions

Proteomic study of acute respiratory distress syndrome: current knowledge and implications for drug development

PubMed Central

Levitt, Joseph E.; Rogers, Angela J.

2017-01-01

The acute respiratory distress syndrome (ARDS) is a common cause of acute respiratory failure, and is associated with substantial mortality and morbidity. Dozens of clinical trials targeting ARDS have failed, with no drug specifically targeting lung injury in widespread clinical use. Thus, the need for drug development in ARDS is great. Targeted proteomic studies in ARDS have identified many key pathways in the disease, including inflammation, epithelial injury, endothelial injury or activation, and disordered coagulation and repair. Recent studies reveal the potential for proteomic changes to identify novel subphenotypes of ARDS patients who may be most likely to respond to therapy and could thus be targeted for enrollment in clinical trials. Nontargeted studies of proteomics in ARDS are just beginning and have the potential to identify novel drug targets and key pathways in the disease. Proteomics will play an important role in phenotyping of patients and developing novel therapies for ARDS in the future. PMID:27031735

Chemical Proteomics Reveals Ferrochelatase as a Common Off-target of Kinase Inhibitors.

PubMed

Klaeger, Susan; Gohlke, Bjoern; Perrin, Jessica; Gupta, Vipul; Heinzlmeir, Stephanie; Helm, Dominic; Qiao, Huichao; Bergamini, Giovanna; Handa, Hiroshi; Savitski, Mikhail M; Bantscheff, Marcus; Médard, Guillaume; Preissner, Robert; Kuster, Bernhard

2016-05-20

Many protein kinases are valid drug targets in oncology because they are key components of signal transduction pathways. The number of clinical kinase inhibitors is on the rise, but these molecules often exhibit polypharmacology, potentially eliciting desired and toxic effects. Therefore, a comprehensive assessment of a compound's target space is desirable for a better understanding of its biological effects. The enzyme ferrochelatase (FECH) catalyzes the conversion of protoporphyrin IX into heme and was recently found to be an off-target of the BRAF inhibitor Vemurafenib, likely explaining the phototoxicity associated with this drug in melanoma patients. This raises the question of whether FECH binding is a more general feature of kinase inhibitors. To address this, we applied a chemical proteomics approach using kinobeads to evaluate 226 clinical kinase inhibitors for their ability to bind FECH. Surprisingly, low or submicromolar FECH binding was detected for 29 of all compounds tested and isothermal dose response measurements confirmed target engagement in cells. We also show that Vemurafenib, Linsitinib, Neratinib, and MK-2461 reduce heme levels in K562 cells, verifying that drug binding leads to a loss of FECH activity. Further biochemical and docking experiments identified the protoporphyrin pocket in FECH as one major drug binding site. Since the genetic loss of FECH activity leads to photosensitivity in humans, our data strongly suggest that FECH inhibition by kinase inhibitors is the molecular mechanism triggering photosensitivity in patients. We therefore suggest that a FECH assay should generally be part of the preclinical molecular toxicology package for the development of kinase inhibitors.

Progress on the HUPO Draft Human Proteome: 2017 Metrics of the Human Proteome Project.

PubMed

Omenn, Gilbert S; Lane, Lydie; Lundberg, Emma K; Overall, Christopher M; Deutsch, Eric W

2017-12-01

The Human Proteome Organization (HUPO) Human Proteome Project (HPP) continues to make progress on its two overall goals: (1) completing the protein parts list, with an annual update of the HUPO draft human proteome, and (2) making proteomics an integrated complement to genomics and transcriptomics throughout biomedical and life sciences research. neXtProt version 2017-01-23 has 17 008 confident protein identifications (Protein Existence [PE] level 1) that are compliant with the HPP Guidelines v2.1 ( https://hupo.org/Guidelines ), up from 13 664 in 2012-12 and 16 518 in 2016-04. Remaining to be found by mass spectrometry and other methods are 2579 "missing proteins" (PE2+3+4), down from 2949 in 2016. PeptideAtlas 2017-01 has 15 173 canonical proteins, accounting for nearly all of the 15 290 PE1 proteins based on MS data. These resources have extensive data on PTMs, single amino acid variants, and splice isoforms. The Human Protein Atlas v16 has 10 492 highly curated protein entries with tissue and subcellular spatial localization of proteins and transcript expression. Organ-specific popular protein lists have been generated for broad use in quantitative targeted proteomics using SRM-MS or DIA-SWATH-MS studies of biology and disease.

Proteomic approaches in cancer risk and response assessment.

PubMed

Petricoin, Emanuel F; Liotta, Lance A

2004-02-01

Proteomics is more than just a list-generating exercise where increases or decreases in protein expression are identified. Proteomic technologies will ultimately characterize information-flow through the protein circuitry that interconnects the extracellular microenvironment to the serum or plasma macroenvironment through intracellular signaling systems and their control of gene transcription. The nature of this information can be a cause or a consequence of disease processes and how patients respond to therapy. Analysis of human cancer as a model for how proteomics can have an impact at the bedside can take advantage of several promising new proteomic technologies. These technologies are being developed for early detection and risk assessment, therapeutic targeting and patient-tailored therapy.

The role of proteomics in studies of protein moonlighting.

PubMed

Beynon, Robert J; Hammond, Dean; Harman, Victoria; Woolerton, Yvonne

2014-12-01

The increasing acceptance that proteins may exert multiple functions in the cell brings with it new analytical challenges that will have an impact on the field of proteomics. Many proteomics workflows begin by destroying information about the interactions between different proteins, and the reduction of a complex protein mixture to constituent peptides also scrambles information about the combinatorial potential of post-translational modifications. To bring the focus of proteomics on to the domain of protein moonlighting will require novel analytical and quantitative approaches.

A Cell Wall Proteome and Targeted Cell Wall Analyses Provide Novel Information on Hemicellulose Metabolism in Flax.

PubMed

Chabi, Malika; Goulas, Estelle; Leclercq, Celine C; de Waele, Isabelle; Rihouey, Christophe; Cenci, Ugo; Day, Arnaud; Blervacq, Anne-Sophie; Neutelings, Godfrey; Duponchel, Ludovic; Lerouge, Patrice; Hausman, Jean-François; Renaut, Jenny; Hawkins, Simon

2017-09-01

Experimentally-generated (nanoLC-MS/MS) proteomic analyses of four different flax organs/tissues (inner-stem, outer-stem, leaves and roots) enriched in proteins from 3 different sub-compartments (soluble-, membrane-, and cell wall-proteins) was combined with publically available data on flax seed and whole-stem proteins to generate a flax protein database containing 2996 nonredundant total proteins. Subsequent multiple analyses (MapMan, CAZy, WallProtDB and expert curation) of this database were then used to identify a flax cell wall proteome consisting of 456 nonredundant proteins localized in the cell wall and/or associated with cell wall biosynthesis, remodeling and other cell wall related processes. Examination of the proteins present in different flax organs/tissues provided a detailed overview of cell wall metabolism and highlighted the importance of hemicellulose and pectin remodeling in stem tissues. Phylogenetic analyses of proteins in the cell wall proteome revealed an important paralogy in the class IIIA xyloglucan endo-transglycosylase/hydrolase (XTH) family associated with xyloglucan endo-hydrolase activity.Immunolocalisation, FT-IR microspectroscopy, and enzymatic fingerprinting indicated that flax fiber primary/S1 cell walls contained xyloglucans with typical substituted side chains as well as glucuronoxylans in much lower quantities. These results suggest a likely central role of xyloglucans and endotransglucosylase/hydrolase activity in flax fiber formation and cell wall remodeling processes. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Improved Detection of HER2 by a Quasi-Targeted Proteomics Approach Using Aptamer-Peptide Probe and Liquid Chromatography-Tandem Mass Spectrometry.

PubMed

Zhou, Weixian; Xu, Feifei; Li, Danni; Chen, Yun

2018-03-01

Human epidermal growth factor receptor 2 (HER2)-positive breast cancer is a particularly aggressive type of the disease. To date, much evidence has indicated that accurate HER2 status detection is crucial for prognosis and treatment strategy selection. Thus, bioanalytical techniques for early and accurate detection of HER2 have the potential to improve patient care. Currently, the widely used immunohistochemical staining normally has problems with reproducibility and lack of standardization, resulting in poor concordance between laboratories. Aptamers are a good alternative, but the extent of their use in quantitative analysis of HER2 is limited because of the lack of effective detection methods. We developed a quasi-targeted proteomics assay and converted the HER2 signal into the mass response of reporter peptide by a combination of aptamer-peptide probe and LC-MS/MS. The selected aptamer-peptide probe consisted of aptamer HB5 and the substrate peptide GDKAVLGVDPFR that contained the reporter peptide AVLGVDPFR. After characterization of this newly synthesized probe (e.g., conjugation efficiency, stability, binding affinity, specificity, and digestion efficiency), probe binding and trypsin shaving conditions were optimized. The resulting limit of quantification for HER2 was 25 pmol/L. Then, the quasi-targeted proteomics assay was applied to determine the HER2 concentrations in the HER2-positive breast cancer cells BT474 and SK-BR-3, the HER2-negative breast cancer cells MDA-MB-231 and MCF-7, and 36 pairs of human breast primary tumors and adjacent normal tissue samples. The results were highly concordant with those obtained by immunohistochemistry with reflex testing by fluorescent in situ hybridization. Quasi-targeted proteomics can be a quantitative alternative for HER2 detection. © 2017 American Association for Clinical Chemistry.

A Proteomics View of the Molecular Mechanisms and Biomarkers of Glaucomatous Neurodegeneration

PubMed Central

Tezel, Gülgün

2013-01-01

Despite improving understanding of glaucoma, key molecular players of neurodegeneration that can be targeted for treatment of glaucoma, or molecular biomarkers that can be useful for clinical testing, remain unclear. Proteomics technology offers a powerful toolbox to accomplish these important goals of the glaucoma research and is increasingly being applied to identify molecular mechanisms and biomarkers of glaucoma. Recent studies of glaucoma using proteomics analysis techniques have resulted in the lists of differentially expressed proteins in human glaucoma and animal models. The global analysis of protein expression in glaucoma has been followed by cell-specific proteome analysis of retinal ganglion cells and astrocytes. The proteomics data have also guided targeted studies to identify post-translational modifications and protein-protein interactions during glaucomatous neurodegeneration. In addition, recent applications of proteomics have provided a number of potential biomarker candidates. Proteomics technology holds great promise to move glaucoma research forward toward new treatment strategies and biomarker discovery. By reviewing the major proteomics approaches and their applications in the field of glaucoma, this article highlights the power of proteomics in translational and clinical research related to glaucoma and also provides a framework for future research to functionally test the importance of specific molecular pathways and validate candidate biomarkers. PMID:23396249

Quantitative proteomics-based analysis supports a significant role of GTG proteins in regulation of ABA response in Arabidopsis roots.

PubMed

Alvarez, Sophie; Roy Choudhury, Swarup; Hicks, Leslie M; Pandey, Sona

2013-03-01

Abscisic acid (ABA) is proposed to be perceived by multiple receptors in plants. We have previously reported on the role of two GPCR-type G-proteins (GTG proteins) as plasma membrane-localized ABA receptors in Arabidopsis thaliana. However, due to the presence of multiple transmembrane domains, detailed structural and biochemical characterization of GTG proteins remains limited. Since ABA induces substantial changes in the proteome of plants, a labeling LC-based quantitative proteomics approach was applied to elucidate the global effects and possible downstream targets of GTG1/GTG2 proteins. Quantitative differences in protein abundance between wild-type and gtg1gtg2 were analyzed for evaluation of the effect of ABA on the root proteome and its dependence on the presence of functional GTG1/GTG2 proteins. The results presented in this study reveal the most comprehensive ABA-responsive root proteome reported to date in Arabidopsis. Notably, the majority of ABA-responsive proteins required the presence of GTG proteins, supporting their key role in ABA signaling. These observations were further confirmed by additional experiments. Overall, comparison of the ABA-dependent protein abundance changes in wild-type versus gtg1gtg2 provides clues to their possible links with some of the well-established effectors of the ABA signaling pathways and their role in mediating phytohormone cross-talk.

Identification of BAG3 target proteins in anaplastic thyroid cancer cells by proteomic analysis.

PubMed

Galdiero, Francesca; Bello, Anna Maria; Spina, Anna; Capiluongo, Anna; Liuu, Sophie; De Marco, Margot; Rosati, Alessandra; Capunzo, Mario; Napolitano, Maria; Vuttariello, Emilia; Monaco, Mario; Califano, Daniela; Turco, Maria Caterina; Chiappetta, Gennaro; Vinh, Joëlle; Chiappetta, Giovanni

2018-01-30

BAG3 protein is an apoptosis inhibitor and is highly expressed in Anaplastic Thyroid Cancer. We investigated the entire set of proteins modulated by BAG3 silencing in the human anaplastic thyroid 8505C cancer cells by using the Stable-Isotope Labeling by Amino acids in Cell culture strategy combined with mass spectrometry analysis. By this approach we identified 37 up-regulated and 54 down-regulated proteins in BAG3-silenced cells. Many of these proteins are reportedly involved in tumor progression, invasiveness and resistance to therapies. We focused our attention on an oncogenic protein, CAV1, and a tumor suppressor protein, SERPINB2, that had not previously been reported to be modulated by BAG3. Their expression levels in BAG3-silenced cells were confirmed by qRT-PCR and western blot analyses, disclosing two novel targets of BAG3 pro-tumor activity. We also examined the dataset of proteins obtained by the quantitative proteomics analysis using two tools, Downstream Effect Analysis and Upstream Regulator Analysis of the Ingenuity Pathways Analysis software. Our analyses confirm the association of the proteome profile observed in BAG3-silenced cells with an increase in cell survival and a decrease in cell proliferation and invasion, and highlight the possible involvement of four tumor suppressor miRNAs and TP53/63 proteins in BAG3 activity.

Avalanche multiplication and impact ionization in amorphous selenium photoconductive target

NASA Astrophysics Data System (ADS)

Park, Wug-Dong; Tanioka, Kenkichi

2014-03-01

The avalanche multiplication factor and the hole ionization coefficient in the amorphous selenium (a-Se) high-gain avalanche rushing amorphous photoconductor (HARP) target depend on the electric field. The phenomenon of avalanche multiplication and impact ionization in the 0.4-µm-thick a-Se HARP target is investigated. The hot carrier energy in the 0.4-µm-thick a-Se HARP target increases linearly as the target voltage increases. The energy relaxation length of hot carriers in the a-Se photoconductor of the 0.4-µm-thick HARP target saturates as the electric field increases. The average energy Eav of a hot carrier and the energy relaxation length λE in the a-Se photoconductor of the 0.4-µm-thick HARP target at 1 × 108 V/m were 0.25 eV and 2.5 nm, respectively. In addition, the hole ionization coefficient β and the avalanche multiplication factor M are derived as a function of the electric field, the average energy of a hot carrier, and the impact ionization energy. The experimental hole ionization coefficient β and the avalanche multiplication factor M in the 0.4-µm-thick a-Se HARP target agree with the theoretical results.

Analysis of the liver mitochondrial proteome in response to ethanol and S-adenosylmethionine treatments: novel molecular targets of disease and hepatoprotection.

PubMed

Andringa, Kelly K; King, Adrienne L; Eccleston, Heather B; Mantena, Sudheer K; Landar, Aimee; Jhala, Nirag C; Dickinson, Dale A; Squadrito, Giuseppe L; Bailey, Shannon M

2010-05-01

S-adenosylmethionine (SAM) minimizes alcohol hepatotoxicity; however, the molecular mechanisms responsible for SAM hepatoprotection remain unknown. Herein, we use proteomics to determine whether the hepatoprotective action of SAM against early-stage alcoholic liver disease is linked to alterations in the mitochondrial proteome. For this, male rats were fed control or ethanol-containing liquid diets +/- SAM and liver mitochondria were prepared for proteomic analysis. Two-dimensional isoelectric focusing (2D IEF/SDS-PAGE) and blue native gel electrophoresis (BN-PAGE) were used to determine changes in matrix and oxidative phosphorylation (OxPhos) proteins, respectively. SAM coadministration minimized alcohol-dependent inflammation and preserved mitochondrial respiration. SAM supplementation preserved liver SAM levels in ethanol-fed rats; however, mitochondrial SAM levels were increased by ethanol and SAM treatments. With use of 2D IEF/SDS-PAGE, 30 proteins showed significant changes in abundance in response to ethanol, SAM, or both. Classes of proteins affected by ethanol and SAM treatments were chaperones, beta oxidation proteins, sulfur metabolism proteins, and dehydrogenase enzymes involved in methionine, glycine, and choline metabolism. BN-PAGE revealed novel changes in the levels of 19 OxPhos proteins in response to ethanol, SAM, or both. Ethanol- and SAM-dependent alterations in the proteome were not linked to corresponding changes in gene expression. In conclusion, ethanol and SAM treatment led to multiple changes in the liver mitochondrial proteome. The protective effects of SAM against alcohol toxicity are mediated, in part, through maintenance of proteins involved in key mitochondrial energy conserving and biosynthetic pathways. This study demonstrates that SAM may be a promising candidate for treatment of alcoholic liver disease.

Proteomics of effector-triggered immunity (ETI) in plants.

PubMed

Hurley, Brenden; Subramaniam, Rajagopal; Guttman, David S; Desveaux, Darrell

2014-01-01

Effector-triggered immunity (ETI) was originally termed gene-for-gene resistance and dates back to fundamental observations of flax resistance to rust fungi by Harold Henry Flor in the 1940s. Since then, genetic and biochemical approaches have defined our current understanding of how plant "resistance" proteins recognize microbial effectors. More recently, proteomic approaches have expanded our view of the protein landscape during ETI and contributed significant advances to our mechanistic understanding of ETI signaling. Here we provide an overview of proteomic techniques that have been used to study plant ETI including both global and targeted approaches. We discuss the challenges associated with ETI proteomics and highlight specific examples from the literature, which demonstrate how proteomics is advancing the ETI research field.

Proteomics for understanding miRNA biology

PubMed Central

Huang, Tai-Chung; Pinto, Sneha M.; Pandey, Akhilesh

2013-01-01

MicroRNAs (miRNAs) are small noncoding RNAs that play important roles in posttranscriptional regulation of gene expression. Mature miRNAs associate with the RNA interference silencing complex to repress mRNA translation and/or degrade mRNA transcripts. Mass spectrometry-based proteomics has enabled identification of several core components of the canonical miRNA processing pathway and their posttranslational modifications which are pivotal in miRNA regulatory mechanisms. The use of quantitative proteomic strategies has also emerged as a key technique for experimental identification of miRNA targets by allowing direct determination of proteins whose levels are altered because of translational suppression. This review focuses on the role of proteomics and labeling strategies to understand miRNA biology. PMID:23125164

Metabolome and proteome profiling of complex I deficiency induced by rotenone.

PubMed

Gielisch, Ina; Meierhofer, David

2015-01-02

Complex I (CI; NADH dehydrogenase) deficiency causes mitochondrial diseases, including Leigh syndrome. A variety of clinical symptoms of CI deficiency are known, including neurodegeneration. Here, we report an integrative study combining liquid chromatography-mass spectrometry (LC-MS)-based metabolome and proteome profiling in CI deficient HeLa cells. We report a rapid LC-MS-based method for the relative quantification of targeted metabolome profiling with an additional layer of confidence by applying multiple reaction monitoring (MRM) ion ratios for further identity confirmation and robustness. The proteome was analyzed by label-free quantification (LFQ). More than 6000 protein groups were identified. Pathway and network analyses revealed that the respiratory chain was highly deregulated, with metabolites such as FMN, FAD, NAD(+), and ADP, direct players of the OXPHOS system, and metabolites of the TCA cycle decreased up to 100-fold. Synthesis of functional iron-sulfur clusters, which are of central importance for the electron transfer chain, and degradation products like bilirubin were also significantly reduced. Glutathione metabolism on the pathway level, as well as individual metabolite components such as NADPH, glutathione (GSH), and oxidized glutathione (GSSG), was downregulated. Overall, metabolome and proteome profiles in CI deficient cells correlated well, supporting our integrated approach.

Integration of gel-based and gel-free proteomic data for functional analysis of proteins through Soybean Proteome Database.

PubMed

Komatsu, Setsuko; Wang, Xin; Yin, Xiaojian; Nanjo, Yohei; Ohyanagi, Hajime; Sakata, Katsumi

2017-06-23

The Soybean Proteome Database (SPD) stores data on soybean proteins obtained with gel-based and gel-free proteomic techniques. The database was constructed to provide information on proteins for functional analyses. The majority of the data is focused on soybean (Glycine max 'Enrei'). The growth and yield of soybean are strongly affected by environmental stresses such as flooding. The database was originally constructed using data on soybean proteins separated by two-dimensional polyacrylamide gel electrophoresis, which is a gel-based proteomic technique. Since 2015, the database has been expanded to incorporate data obtained by label-free mass spectrometry-based quantitative proteomics, which is a gel-free proteomic technique. Here, the portions of the database consisting of gel-free proteomic data are described. The gel-free proteomic database contains 39,212 proteins identified in 63 sample sets, such as temporal and organ-specific samples of soybean plants grown under flooding stress or non-stressed conditions. In addition, data on organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored. Furthermore, the database integrates multiple omics data such as genomics, transcriptomics, metabolomics, and proteomics. The SPD database is accessible at http://proteome.dc.affrc.go.jp/Soybean/. The Soybean Proteome Database stores data obtained from both gel-based and gel-free proteomic techniques. The gel-free proteomic database comprises 39,212 proteins identified in 63 sample sets, such as different organs of soybean plants grown under flooding stress or non-stressed conditions in a time-dependent manner. In addition, organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored in the gel-free proteomics database. A total of 44,704 proteins, including 5490 proteins identified using a gel-based proteomic technique, are stored in the SPD. It accounts for approximately 80% of all predicted proteins from

Elucidation of cross-species proteomic effects in human and hominin bone proteome identification through a bioinformatics experiment.

PubMed

Welker, F

2018-02-20

The study of ancient protein sequences is increasingly focused on the analysis of older samples, including those of ancient hominins. The analysis of such ancient proteomes thereby potentially suffers from "cross-species proteomic effects": the loss of peptide and protein identifications at increased evolutionary distances due to a larger number of protein sequence differences between the database sequence and the analyzed organism. Error-tolerant proteomic search algorithms should theoretically overcome this problem at both the peptide and protein level; however, this has not been demonstrated. If error-tolerant searches do not overcome the cross-species proteomic issue then there might be inherent biases in the identified proteomes. Here, a bioinformatics experiment is performed to test this using a set of modern human bone proteomes and three independent searches against sequence databases at increasing evolutionary distances: the human (0 Ma), chimpanzee (6-8 Ma) and orangutan (16-17 Ma) reference proteomes, respectively. Incorrectly suggested amino acid substitutions are absent when employing adequate filtering criteria for mutable Peptide Spectrum Matches (PSMs), but roughly half of the mutable PSMs were not recovered. As a result, peptide and protein identification rates are higher in error-tolerant mode compared to non-error-tolerant searches but did not recover protein identifications completely. Data indicates that peptide length and the number of mutations between the target and database sequences are the main factors influencing mutable PSM identification. The error-tolerant results suggest that the cross-species proteomics problem is not overcome at increasing evolutionary distances, even at the protein level. Peptide and protein loss has the potential to significantly impact divergence dating and proteome comparisons when using ancient samples as there is a bias towards the identification of conserved sequences and proteins. Effects are minimized

Mitochondrial proteome disruption in the diabetic heart through targeted epigenetic regulation at the mitochondrial heat shock protein 70 (mtHsp70) nuclear locus.

PubMed

Shepherd, Danielle L; Hathaway, Quincy A; Nichols, Cody E; Durr, Andrya J; Pinti, Mark V; Hughes, Kristen M; Kunovac, Amina; Stine, Seth M; Hollander, John M

2018-06-01

>99% of the mitochondrial proteome is nuclear-encoded. The mitochondrion relies on a coordinated multi-complex process for nuclear genome-encoded mitochondrial protein import. Mitochondrial heat shock protein 70 (mtHsp70) is a key component of this process and a central constituent of the protein import motor. Type 2 diabetes mellitus (T2DM) disrupts mitochondrial proteomic signature which is associated with decreased protein import efficiency. The goal of this study was to manipulate the mitochondrial protein import process through targeted restoration of mtHsp70, in an effort to restore proteomic signature and mitochondrial function in the T2DM heart. A novel line of cardiac-specific mtHsp70 transgenic mice on the db/db background were generated and cardiac mitochondrial subpopulations were isolated with proteomic evaluation and mitochondrial function assessed. MicroRNA and epigenetic regulation of the mtHsp70 gene during T2DM were also evaluated. MtHsp70 overexpression restored cardiac function and nuclear-encoded mitochondrial protein import, contributing to a beneficial impact on proteome signature and enhanced mitochondrial function during T2DM. Further, transcriptional repression at the mtHsp70 genomic locus through increased localization of H3K27me3 during T2DM insult was observed. Our results suggest that restoration of a key protein import constituent, mtHsp70, provides therapeutic benefit through attenuation of mitochondrial and contractile dysfunction in T2DM. Copyright © 2018 Elsevier Ltd. All rights reserved.

Comparative proteomics of cerebrospinal fluid reveals a predictive model for differential diagnosis of pneumococcal, meningococcal, and enteroviral meningitis, and novel putative therapeutic targets

PubMed Central

2015-01-01

Background Meningitis is the inflammation of the meninges in response to infection or chemical agents. While aseptic meningitis, most frequently caused by enteroviruses, is usually benign with a self-limiting course, bacterial meningitis remains associated with high morbidity and mortality rates, despite advances in antimicrobial therapy and intensive care. Fast and accurate differential diagnosis is crucial for assertive choice of the appropriate therapeutic approach for each form of meningitis. Methods We used 2D-PAGE and mass spectrometry to identify the cerebrospinal fluid proteome specifically related to the host response to pneumococcal, meningococcal, and enteroviral meningitis. The disease-specific proteome signatures were inspected by pathway analysis. Results Unique cerebrospinal fluid proteome signatures were found to the three aetiological forms of meningitis investigated, and a qualitative predictive model with four protein markers was developed for the differential diagnosis of these diseases. Nevertheless, pathway analysis of the disease-specific proteomes unveiled that Kallikrein-kinin system may play a crucial role in the pathophysiological mechanisms leading to brain damage in bacterial meningitis. Proteins taking part in this cellular process are proposed as putative targets to novel adjunctive therapies. Conclusions Comparative proteomics of cerebrospinal fluid disclosed candidate biomarkers, which were combined in a qualitative and sequential predictive model with potential to improve the differential diagnosis of pneumococcal, meningococcal and enteroviral meningitis. Moreover, we present the first evidence of the possible implication of Kallikrein-kinin system in the pathophysiology of bacterial meningitis. PMID:26040285

Comparative proteomics of cerebrospinal fluid reveals a predictive model for differential diagnosis of pneumococcal, meningococcal, and enteroviral meningitis, and novel putative therapeutic targets.

PubMed

Cordeiro, Ana Paula; Silva Pereira, Rosiane Aparecida; Chapeaurouge, Alex; Coimbra, Clarice Semião; Perales, Jonas; Oliveira, Guilherme; Sanchez Candiani, Talitah Michel; Coimbra, Roney Santos

2015-01-01

Meningitis is the inflammation of the meninges in response to infection or chemical agents. While aseptic meningitis, most frequently caused by enteroviruses, is usually benign with a self-limiting course, bacterial meningitis remains associated with high morbidity and mortality rates, despite advances in antimicrobial therapy and intensive care. Fast and accurate differential diagnosis is crucial for assertive choice of the appropriate therapeutic approach for each form of meningitis. We used 2D-PAGE and mass spectrometry to identify the cerebrospinal fluid proteome specifically related to the host response to pneumococcal, meningococcal, and enteroviral meningitis. The disease-specific proteome signatures were inspected by pathway analysis. Unique cerebrospinal fluid proteome signatures were found to the three aetiological forms of meningitis investigated, and a qualitative predictive model with four protein markers was developed for the differential diagnosis of these diseases. Nevertheless, pathway analysis of the disease-specific proteomes unveiled that Kallikrein-kinin system may play a crucial role in the pathophysiological mechanisms leading to brain damage in bacterial meningitis. Proteins taking part in this cellular process are proposed as putative targets to novel adjunctive therapies. Comparative proteomics of cerebrospinal fluid disclosed candidate biomarkers, which were combined in a qualitative and sequential predictive model with potential to improve the differential diagnosis of pneumococcal, meningococcal and enteroviral meningitis. Moreover, we present the first evidence of the possible implication of Kallikrein-kinin system in the pathophysiology of bacterial meningitis.

Examining perceptual and conceptual set biases in multiple-target visual search.

PubMed

Biggs, Adam T; Adamo, Stephen H; Dowd, Emma Wu; Mitroff, Stephen R

2015-04-01

Visual search is a common practice conducted countless times every day, and one important aspect of visual search is that multiple targets can appear in a single search array. For example, an X-ray image of airport luggage could contain both a water bottle and a gun. Searchers are more likely to miss additional targets after locating a first target in multiple-target searches, which presents a potential problem: If airport security officers were to find a water bottle, would they then be more likely to miss a gun? One hypothetical cause of multiple-target search errors is that searchers become biased to detect additional targets that are similar to a found target, and therefore become less likely to find additional targets that are dissimilar to the first target. This particular hypothesis has received theoretical, but little empirical, support. In the present study, we tested the bounds of this idea by utilizing "big data" obtained from the mobile application Airport Scanner. Multiple-target search errors were substantially reduced when the two targets were identical, suggesting that the first-found target did indeed create biases during subsequent search. Further analyses delineated the nature of the biases, revealing both a perceptual set bias (i.e., a bias to find additional targets with features similar to those of the first-found target) and a conceptual set bias (i.e., a bias to find additional targets with a conceptual relationship to the first-found target). These biases are discussed in terms of the implications for visual-search theories and applications for professional visual searchers.

A targeted proteomic strategy for the measurement of oral cancer candidate biomarkers in human saliva

PubMed Central

Kawahara, Rebeca; Bollinger, James G.; Rivera, César; Ribeiro, Ana Carolina P.; Brandão, Thaís Bianca; Paes Leme, Adriana F.; MacCoss, Michael J.

2015-01-01

Head and neck cancers, including oral squamous cell carcinoma (OSCC), are the sixth most common malignancy in the world and are characterized by poor prognosis and a low survival rate. Saliva is oral fluid with intimate contact with OSCC. Besides non-invasive, simple, and rapid to collect, saliva is a potential source of biomarkers. In this study, we build an SRM assay that targets fourteen OSCC candidate biomarker proteins, which were evaluated in a set of clinically-derived saliva samples. Using Skyline software package, we demonstrated a statistically significant higher abundance of the C1R, LCN2, SLPI, FAM49B, TAGLN2, CFB, C3, C4B, LRG1, SERPINA1 candidate biomarkers in the saliva of OSCC patients. Furthermore, our study also demonstrated that CFB, C3, C4B, SERPINA1 and LRG1 are associated with the risk of developing OSCC. Overall, this study successfully used targeted proteomics to measure in saliva a panel of biomarker candidates for OSCC. PMID:26552850

Molecular stratification and precision medicine in systemic sclerosis from genomic and proteomic data.

PubMed

Martyanov, Viktor; Whitfield, Michael L

2016-01-01

The goal of this review is to summarize recent advances into the pathogenesis and treatment of systemic sclerosis (SSc) from genomic and proteomic studies. Intrinsic gene expression-driven molecular subtypes of SSc are reproducible across three independent datasets. These subsets are a consistent feature of SSc and are found in multiple end-target tissues, such as skin and esophagus. Intrinsic subsets as well as baseline levels of molecular target pathways are potentially predictive of clinical response to specific therapeutics, based on three recent clinical trials. A gene expression-based biomarker of modified Rodnan skin score, a measure of SSc skin severity, can be used as a surrogate outcome metric and has been validated in a recent trial. Proteome analyses have identified novel biomarkers of SSc that correlate with SSc clinical phenotypes. Integrating intrinsic gene expression subset data, baseline molecular pathway information, and serum biomarkers along with surrogate measures of modified Rodnan skin score provides molecular context in SSc clinical trials. With validation, these approaches could be used to match patients with the therapies from which they are most likely to benefit and thus increase the likelihood of clinical improvement.

NCI Blog Post: CPTAC, the Complementary Sibling of TCGA (An Interview with Dr. Henry Rodriguez about NCI’s Proteomics Program) | Office of Cancer Clinical Proteomics Research

Cancer.gov

What is proteomics? Proteomics is a highly automated and rapid method for measuring all the proteins in a biological sample. Proteins are the molecules that actually do most of the work inside a cell. When researchers develop cancer drugs, those drugs typically target proteins, so scientists and clinicians really have to understand what the proteins are doing. Proteomics researchers are now able to measure up to 10,000 proteins per tumor sample.

Challenges for proteomics core facilities.

PubMed

Lilley, Kathryn S; Deery, Michael J; Gatto, Laurent

2011-03-01

Many analytical techniques have been executed by core facilities established within academic, pharmaceutical and other industrial institutions. The centralization of such facilities ensures a level of expertise and hardware which often cannot be supported by individual laboratories. The establishment of a core facility thus makes the technology available for multiple researchers in the same institution. Often, the services within the core facility are also opened out to researchers from other institutions, frequently with a fee being levied for the service provided. In the 1990s, with the onset of the age of genomics, there was an abundance of DNA analysis facilities, many of which have since disappeared from institutions and are now available through commercial sources. Ten years on, as proteomics was beginning to be utilized by many researchers, this technology found itself an ideal candidate for being placed within a core facility. We discuss what in our view are the daily challenges of proteomics core facilities. We also examine the potential unmet needs of the proteomics core facility that may also be applicable to proteomics laboratories which do not function as core facilities. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Affinity Proteomics in the mountains: Alpbach 2015.

PubMed

Taussig, Michael J

2016-09-25

The 2015 Alpbach Workshop on Affinity Proteomics, organised by the EU AFFINOMICS consortium, was the 7th workshop in this series. As in previous years, the focus of the event was the current state of affinity methods for proteome analysis, including complementarity with mass spectrometry, progress in recombinant binder production methods, alternatives to classical antibodies as affinity reagents, analysis of proteome targets, industry focus on biomarkers, and diagnostic and clinical applications. The combination of excellent science with Austrian mountain scenery and winter sports engender an atmosphere that makes this series of workshops exceptional. The articles in this Special Issue represent a cross-section of the presentations at the 2015 meeting. Copyright © 2016 Elsevier B.V. All rights reserved.

iTRAQ-based quantitative proteomic analysis reveals proteomic changes in three fenoxaprop-P-ethyl-resistant Beckmannia syzigachne biotypes with differing ACCase mutations.

PubMed

Pan, Lang; Zhang, Jian; Wang, Junzhi; Yu, Qin; Bai, Lianyang; Dong, Liyao

2017-05-08

American sloughgrass (Beckmannia syzigachne Steud.) is a weed widely distributed in wheat fields of China. In recent years, the evolution of herbicide (fenoxaprop-P-ethyl)-resistant populations has decreased the susceptibility of B. syzigachne. This study compared 4 B. syzigachne populations (3 resistant and 1 susceptible) using iTRAQ to characterize fenoxaprop-P-ethyl resistance in B. syzigachne at the proteomic level. Through searching the UniProt database, 3104 protein species were identified from 13,335 unique peptides. Approximately 2834 protein species were assigned to 23 functional classifications provided by the COG database. Among these, 2299 protein species were assigned to 125 predicted pathways. The resistant biotype contained 8 protein species that changed in abundance relative to the susceptible biotype; they were involved in photosynthesis, oxidative phosphorylation, and fatty acid biosynthesis pathways. In contrast to previous studies comparing only 1 resistant and 1 susceptible population, our use of 3 fenoxaprop-resistant B. syzigachne populations with different genetic backgrounds minimized irrelevant differential expression and eliminated false positives. Therefore, we could more confidently link the differentially expressed proteins to herbicide resistance. Proteomic analysis demonstrated that fenoxaprop-P-ethyl resistance is associated with photosynthetic capacity, a connection that might be related to the target-site mutations in resistant B. syzigachne. This is the first large-scale proteomics study examining herbicide stress responses in different B. syzigachne biotypes. This study has biological relevance because it is the first to employ proteomic analysis for understanding the mechanisms underlying Beckmannia syzigachne herbicide resistance. The plant is a major weed in China and negatively affects crop yield, but has developed considerable resistance to the most common herbicide, fenoxaprop-P-ethyl. Through comparisons of resistant and

Proteomics: a new approach to the study of disease.

PubMed

Chambers, G; Lawrie, L; Cash, P; Murray, G I

2000-11-01

The global analysis of cellular proteins has recently been termed proteomics and is a key area of research that is developing in the post-genome era. Proteomics uses a combination of sophisticated techniques including two-dimensional (2D) gel electrophoresis, image analysis, mass spectrometry, amino acid sequencing, and bio-informatics to resolve comprehensively, to quantify, and to characterize proteins. The application of proteomics provides major opportunities to elucidate disease mechanisms and to identify new diagnostic markers and therapeutic targets. This review aims to explain briefly the background to proteomics and then to outline proteomic techniques. Applications to the study of human disease conditions ranging from cancer to infectious diseases are reviewed. Finally, possible future advances are briefly considered, especially those which may lead to faster sample throughput and increased sensitivity for the detection of individual proteins. Copyright 2000 John Wiley & Sons, Ltd.

Proteomic Identification of Non-Gal Antibody Targets After Pig-to-Primate Cardiac Xenotransplantation

PubMed Central

Byrne, Guerard W.; Stalboerger, Paul G.; Davila, Eduardo; Heppelmann, Carrie J.; Gazi, Mozammel H.; McGregor, Hugh C. J.; LaBreche, Peter T.; Davies, William R.; Rao, Vinay P.; Oi, Keiji; Tazelaar, Henry D.; Logan, John S.; McGregor, Christopher G. A.

2008-01-01

Background Experience with non-antigenic galactose α1,3 galactose (αGal) polymers and development of αGal deficient pigs has reduced or eliminated the significance of this antigen in xenograft rejection. Despite these advances, delayed xenograft rejection (DXR) continues to occur most likely due to antibody responses to non-Gal endothelial cell (EC) antigens. Methods To gauge the diversity of the non-Gal antibody response we used antibody derived from CD46 transgenic heterotopic cardiac xenografts performed without T-cell immunosuppression, Group A (n = 4) and Gal knockout (GT-KO) heart transplants under tacrolimus and sirolimus immunosuppression, Group B (n = 8). Non-Gal antibody was measured by flow cytometry and by Western blots using GT-KO EC membrane antigens. A nanoLC/MS/MS analysis of proteins recovered from 2D gels was used to identify target antigens. Results Group A recipients exhibited a mixed cellular and humoral rejection. Group B recipients mainly exhibited classical DXR. Western blot analysis showed a non-Gal antibody response induced by GT+ and GT-KO hearts to an overlapping set of pig aortic EC membrane antigens. Proteomic analysis identified 14 potential target antigens but failed to define several immunodominant targets. Conclusions These experiments indicate that the non-Gal antibody response is directed to a number of stress response and inflammation related pig EC antigens and a few undefined targets. Further analysis of these antibody specificities using alternative methods is required to more fully define the repertoire of non-Gal antibody responses. PMID:18957049

A proteomic landscape of diffuse-type gastric cancer.

PubMed

Ge, Sai; Xia, Xia; Ding, Chen; Zhen, Bei; Zhou, Quan; Feng, Jinwen; Yuan, Jiajia; Chen, Rui; Li, Yumei; Ge, Zhongqi; Ji, Jiafu; Zhang, Lianhai; Wang, Jiayuan; Li, Zhongwu; Lai, Yumei; Hu, Ying; Li, Yanyan; Li, Yilin; Gao, Jing; Chen, Lin; Xu, Jianming; Zhang, Chunchao; Jung, Sung Yun; Choi, Jong Min; Jain, Antrix; Liu, Mingwei; Song, Lei; Liu, Wanlin; Guo, Gaigai; Gong, Tongqing; Huang, Yin; Qiu, Yang; Huang, Wenwen; Shi, Tieliu; Zhu, Weimin; Wang, Yi; He, Fuchu; Shen, Lin; Qin, Jun

2018-03-08

The diffuse-type gastric cancer (DGC) is a subtype of gastric cancer with the worst prognosis and few treatment options. Here we present a dataset from 84 DGC patients, composed of a proteome of 11,340 gene products and mutation information of 274 cancer driver genes covering paired tumor and nearby tissue. DGC can be classified into three subtypes (PX1-3) based on the altered proteome alone. PX1 and PX2 exhibit dysregulation in the cell cycle and PX2 features an additional EMT process; PX3 is enriched in immune response proteins, has the worst survival, and is insensitive to chemotherapy. Data analysis revealed four major vulnerabilities in DGC that may be targeted for treatment, and allowed the nomination of potential immunotherapy targets for DGC patients, particularly for those in PX3. This dataset provides a rich resource for information and knowledge mining toward altered signaling pathways in DGC and demonstrates the benefit of proteomic analysis in cancer molecular subtyping.

Comparison of the Membrane Proteome of Virulent Mycobacterium tuberculosis and the Attenuated Mycobacterium bovis BCG Vaccine Strain by Label-free Quantitative Proteomics

PubMed Central

Gunawardena, Harsha P.; Feltcher, Meghan E.; Wrobel, John A.; Gu, Sheng; Braunstein, Miriam; Chen, Xian

2015-01-01

The Mycobacterium tuberculosis (MTB) membrane is rich in antigens that are potential targets for diagnostics and the development of new vaccines. To better understand the mechanisms underlying MTB virulence and identify new targets for therapeutic intervention we investigated the differential composition of membrane proteomes between virulent M. tuberculosis H37Rv (MTB) and the Mycobacterium bovis BCG vaccine strain. To compare the membrane proteomes, we used LC-MS/MS analysis in combination with label-free quantitative (LFQ) proteomics, utilizing the area-under-curve (AUC) of the extracted ion chromatograms (XIC) of peptides obtained from m/z and retention time alignment of MS1 features. With this approach, we obtained relative abundance ratios for 2,203 identified membrane-associated proteins in high confidence. Of these proteins, 294 showed statistically significant differences of at least 2 fold, in relative abundance between MTB and BCG membrane fractions. Our comparative analysis detected several proteins associated with known genomic regions of difference between MTB and BCG as being absent, which validated the accuracy of our approach. In further support of our label-free quantitative data, we verified select protein differences by immunoblotting. To our knowledge we have generated the first comprehensive and high coverage profile of comparative membrane proteome changes between virulent MTB and its attenuated relative BCG, which helps elucidate the proteomic basis of the intrinsic virulence of the MTB pathogen. PMID:24093440

Proteomics for understanding miRNA biology.

PubMed

Huang, Tai-Chung; Pinto, Sneha M; Pandey, Akhilesh

2013-02-01

MicroRNAs (miRNAs) are small noncoding RNAs that play important roles in posttranscriptional regulation of gene expression. Mature miRNAs associate with the RNA interference silencing complex to repress mRNA translation and/or degrade mRNA transcripts. Mass spectrometry-based proteomics has enabled identification of several core components of the canonical miRNA processing pathway and their posttranslational modifications which are pivotal in miRNA regulatory mechanisms. The use of quantitative proteomic strategies has also emerged as a key technique for experimental identification of miRNA targets by allowing direct determination of proteins whose levels are altered because of translational suppression. This review focuses on the role of proteomics and labeling strategies to understand miRNA biology. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomic-based identification of Apg-2 as a therapeutic target for chronic myeloid leukemia.

PubMed

Li, Yajuan; Chen, Xi; Shi, Meng; Wang, Haixia; Cao, Weixi; Wang, Xiaozhong; Li, Chunli; Feng, Wenli

2013-12-01

The oncogenic BCR/ABL tyrosine kinase induces constitutive enhanced "spontaneous" DNA damage and unfaithful repair in Philadelphia chromosome positive leukemia cells. Here, we investigated the changes of protein profile in H2O2-induced DNA damage/repair in BaF3-MIGR1 and BaF3-BCR/ABL cells through a proteomic strategy consisting of two-dimensional gel electrophoresis (2-DE) coupled with MALDI-TOF mass spectrometry. In total, 41 spots were differentially expressed and 13 proteins were identified with further MS analysis. Two essential proteins, Proto-oncogene tyrosine-protein kinase ABL1 (c-ABL) and Heat shock 70kDa protein 4 (Apg-2), were confirmed by Western blot and showed consistent changes with proteomic results. Moreover, functional analysis demonstrated that inhibition of Apg-2 not only decreased cell proliferation, but also induced cell apoptosis in BCR/ABL positive cells (BaF3-BCR/ABL, BaF3-BCR/ABL(T315I)). We also proved that Apg-2 inhibition aggravated H2O2 induced damage in BCR/ABL positive cells, and enhanced the sensitivity of BaF3-BCR/ABL(T315I) to STI571. Taken together, the findings in this work provide us with some clues to a better understanding of the molecular mechanisms underlying BCR/ABL in the DNA damage/repair processes and demonstrated that Apg-2 would be a valid target for anti-leukemia drug development. © 2013.

Generation of accurate peptide retention data for targeted and data independent quantitative LC-MS analysis: Chromatographic lessons in proteomics.

PubMed

Krokhin, Oleg V; Spicer, Vic

2016-12-01

The emergence of data-independent quantitative LC-MS/MS analysis protocols further highlights the importance of high-quality reproducible chromatographic procedures. Knowing, controlling and being able to predict the effect of multiple factors that alter peptide RP-HPLC separation selectivity is critical for successful data collection for the construction of ion libraries. Proteomic researchers have often regarded RP-HPLC as a "black box", while vast amount of research on peptide separation is readily available. In addition to obvious parameters, such as the type of ion-pairing modifier, stationary phase and column temperature, we describe the "mysterious" effects of gradient slope, column size and flow rate on peptide separation selectivity. Retention time variations due to these parameters are governed by the linear solvent strength (LSS) theory on a peptide level by the value of its slope S in the basic LSS equation-a parameter that can be accurately predicted. Thus, the application of shallower gradients, higher flow rates, or smaller columns will each increases the relative retention of peptides with higher S-values (long species with multiple positively charged groups). Simultaneous changes to these parameters that each drive shifts in separation selectivity in the same direction should be avoided. The unification of terminology represents another pressing issue in this field of applied proteomics that should be addressed to facilitate further progress. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Selective Targeting of the Cysteine Proteome by Thioredoxin and Glutathione Redox Systems

PubMed Central

Go, Young-Mi; Roede, James R.; Walker, Douglas I.; Duong, Duc M.; Seyfried, Nicholas T.; Orr, Michael; Liang, Yongliang; Pennell, Kurt D.; Jones, Dean P.

2013-01-01

Thioredoxin (Trx) and GSH are the major thiol antioxidants protecting cells from oxidative stress-induced cytotoxicity. Redox states of Trx and GSH have been used as indicators of oxidative stress. Accumulating studies suggest that Trx and GSH redox systems regulate cell signaling and metabolic pathways differently and independently during diverse stressful conditions. In the current study, we used a mass spectrometry-based redox proteomics approach to test responses of the cysteine (Cys) proteome to selective disruption of the Trx- and GSH-dependent systems. Auranofin (ARF) was used to inhibit Trx reductase without detectable oxidation of the GSH/GSSG couple, and buthionine sulfoximine (BSO) was used to deplete GSH without detectable oxidation of Trx1. Results for 606 Cys-containing peptides (peptidyl Cys) showed that 36% were oxidized more than 1.3-fold by ARF, whereas BSO-induced oxidation of peptidyl Cys was only 10%. Mean fold oxidation of these peptides was also higher by ARF than BSO treatment. Analysis of potential functional pathways showed that ARF oxidized peptides associated with glycolysis, cytoskeleton remodeling, translation and cell adhesion. Of 60 peptidyl Cys oxidized due to depletion of GSH, 41 were also oxidized by ARF and included proteins of translation and cell adhesion but not glycolysis or cytoskeletal remodeling. Studies to test functional correlates showed that pyruvate kinase activity and lactate levels were decreased with ARF but not BSO, confirming the effects on glycolysis-associated proteins are sensitive to oxidation by ARF. These data show that the Trx system regulates a broader range of proteins than the GSH system, support distinct function of Trx and GSH in cellular redox control, and show for the first time in mammalian cells selective targeting peptidyl Cys and biological pathways due to deficient function of the Trx system. PMID:23946468

A comparative proteomics method for multiple samples based on a 18O-reference strategy and a quantitation and identification-decoupled strategy.

PubMed

Wang, Hongbin; Zhang, Yongqian; Gui, Shuqi; Zhang, Yong; Lu, Fuping; Deng, Yulin

2017-08-15

Comparisons across large numbers of samples are frequently necessary in quantitative proteomics. Many quantitative methods used in proteomics are based on stable isotope labeling, but most of these are only useful for comparing two samples. For up to eight samples, the iTRAQ labeling technique can be used. For greater numbers of samples, the label-free method has been used, but this method was criticized for low reproducibility and accuracy. An ingenious strategy has been introduced, comparing each sample against a 18 O-labeled reference sample that was created by pooling equal amounts of all samples. However, it is necessary to use proportion-known protein mixtures to investigate and evaluate this new strategy. Another problem for comparative proteomics of multiple samples is the poor coincidence and reproducibility in protein identification results across samples. In present study, a method combining 18 O-reference strategy and a quantitation and identification-decoupled strategy was investigated with proportion-known protein mixtures. The results obviously demonstrated that the 18 O-reference strategy had greater accuracy and reliability than other previously used comparison methods based on transferring comparison or label-free strategies. By the decoupling strategy, the quantification data acquired by LC-MS and the identification data acquired by LC-MS/MS are matched and correlated to identify differential expressed proteins, according to retention time and accurate mass. This strategy made protein identification possible for all samples using a single pooled sample, and therefore gave a good reproducibility in protein identification across multiple samples, and allowed for optimizing peptide identification separately so as to identify more proteins. Copyright © 2017 Elsevier B.V. All rights reserved.

Human Spermatozoa Contain Multiple Targets for Protein S-Nitrosylation: An Alternative Mechanism of the Modulation of Sperm Function by Nitric Oxide?

PubMed Central

Lefièvre, Linda; Chen, Yongjian; Conner, Sarah J; Scott, Joanna L; Publicover, Steve J; Ford, W Christopher L; Barratt, Christopher LR

2009-01-01

Nitric oxide (NO) enhances human sperm motility and capacitation associated with increased protein phosphorylation. NO activates soluble guanylyl cyclase, but can also modify protein function covalently via S-nitrosylation of cysteine. Remarkably, this mechanism remains unexplored in sperm although they depend on post-translational protein modification to achieve changes in function required for fertilisation. Our objective was to identify targets for S-nitrosylation in human sperm. Spermatozoa were incubated with NO donors and S-nitrosylated proteins were identified using the biotin switch assay and a proteomic approach using tandem mass spectrometry. 240 S-nitrosylated proteins were detected in sperm incubated with S-nitrosoglutathione. Minimal levels were observed in glutathione or untreated samples. Proteins identified consistently based on multiple peptides included established targets for S-nitrosylation in other cells e.g. tubulin,, glutathione-S-transferase and heat shock proteins but also novel targets including A-kinase anchoring protein (AKAP) types 3 and 4, voltage-dependent anion-selective channel protein 3 and semenogelin 1 and 2. In situ localisation revealed S-nitrosylated targets on the post-acrosomal region of the head and throughout the flagellum. Potential targets for S-nitrosylation in human sperm include physiologically significant proteins not previously reported in other cells. Their identification will provide novel insight into the mechanism of action of NO in spermatozoa. PMID:17683036

Proteomics in bone research

PubMed Central

Zhang, Hengwei; Recker, Robert; Lee, Wai-Nang Paul; Xiao, Gary Guishan

2010-01-01

Osteoporosis is prevalent among the elderly and is a major cause of bone fracture in this population. Bone integrity is maintained by the dynamic processes of bone resorption and bone formation (bone remodeling). Osteoporosis results when there is an imbalance of the two counteracting processes. Bone mineral density, measured by dual-energy x-ray absorptiometry has been the primary method to assess fracture risk for decades. Recent studies demonstrated that measurement of bone turnover markers allows for a dynamic assessment of bone remodeling, while imaging techniques, such as dual-energy x-ray absorptiometry, do not. The application of proteomics has permitted discoveries of new, sensitive, bone turnover markers, which provide unique information for clinical diagnosis and treatment of patients with bone diseases. This review summarizes the recent findings of proteomic studies on bone diseases, properties of mesenchymal stem cells with high expansion rates and osteoblast and osteoclast differentiation, with emphasis on the role of quantitative proteomics in the study of signaling dynamics, biomarkers and discovery of therapeutic targets. PMID:20121480

Proteomic profiling of human plasma for cancer biomarker discovery.

PubMed

Huang, Zhao; Ma, Linguang; Huang, Canhua; Li, Qifu; Nice, Edouard C

2017-03-01

Over the past decades, substantial advances have been made in both the early diagnosis and accurate prognosis of many cancers because of the impressive development of novel proteomic strategies. However, it remains difficult to standardize proteomic approaches. In addition, the heterogeneity of proteins in distinct tissues results in incomplete population of the whole proteome, which inevitably limits its clinical practice. As one of the most complex proteomes in the human body, the plasma proteome contains secreted proteins originating from multiple organs and tissues, making it a favorable matrix for comprehensive biomarker discovery. Here, we will discuss the roles of plasma proteome profiling in cancer biomarker discovery and validation, and highlight both the inherent advantages and disadvantages. Although several hurdles lay ahead, further advances in this technology will greatly increase our understanding of cancer biology, reveal new biomarkers and biomarker panels, and open a new avenue for more efficient early diagnosis and surveillance of cancer, leading toward personalized medicine. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomes and Phosphoproteomes of Anther and Pollen: Availability and Progress.

PubMed

Zhang, Zaibao; Hu, Menghui; Feng, Xiaobing; Gong, Andong; Cheng, Lin; Yuan, Hongyu

2017-10-01

In flowering plants, anther development plays crucial role in sexual reproduction. Within the anther, microspore mother cells meiosis produces microspores, which further develop into pollen grains that play decisive role in plant reproduction. Previous studies on anther biology mainly focused on single gene functions relying on genetic and molecular methods. Recently, anther development has been expanded from multiple OMICS approaches like transcriptomics, proteomics/phosphoproteomics, and metabolomics. The development of proteomics techniques allowing increased proteome coverage and quantitative measurements of proteins which can characterize proteomes and their modulation during normal development, biotic and abiotic stresses in anther development. In this review, we summarize the achievements of proteomics and phosphoproteomics with anther and pollen organs from model plant and crop species (i.e. Arabidopsis, rice, tobacco). The increased proteomic information facilitated translation of information from the models to crops and thus aid in agricultural improvement. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mass spectrometry based proteomics: existing capabilities and future directions

PubMed Central

Angel, Thomas E.; Aryal, Uma K.; Hengel, Shawna M.; Baker, Erin S.; Kelly, Ryan T.; Robinson, Errol W.; Smith, Richard D.

2012-01-01

Mass spectrometry (MS)-based proteomics is emerging as a broadly effective means for identification, characterization, and quantification of proteins that are integral components of the processes essential for life. Characterization of proteins at the proteome and sub-proteome (e.g., the phosphoproteome, proteoglycome, or degradome/peptidome) levels provides a foundation for understanding fundamental aspects of biology. Emerging technologies such as ion mobility separations coupled with MS and microchip-based-proteome measurements combined with MS instrumentation and chromatographic separation techniques, such as nanoscale reversed phase liquid chromatography and capillary electrophoresis, show great promise for both broad undirected and targeted highly sensitive measurements. MS-based proteomics is increasingly contribute to our understanding of the dynamics, interactions, and roles that proteins and peptides play, advancing our understanding of biology on a systems wide level for a wide range of applications including investigations of microbial communities, bioremediation, and human health. PMID:22498958

Top-Down Targeted Proteomics Reveals Decrease in Myosin Regulatory Light-Chain Phosphorylation That Contributes to Sarcopenic Muscle Dysfunction.

PubMed

Gregorich, Zachery R; Peng, Ying; Cai, Wenxuan; Jin, Yutong; Wei, Liming; Chen, Albert J; McKiernan, Susan H; Aiken, Judd M; Moss, Richard L; Diffee, Gary M; Ge, Ying

2016-08-05

Sarcopenia, the loss of skeletal muscle mass and function with advancing age, is a significant cause of disability and loss of independence in the elderly and thus, represents a formidable challenge for the aging population. Nevertheless, the molecular mechanism(s) underlying sarcopenia-associated muscle dysfunction remain poorly understood. In this study, we employed an integrated approach combining top-down targeted proteomics with mechanical measurements to dissect the molecular mechanism(s) in age-related muscle dysfunction. Top-down targeted proteomic analysis uncovered a progressive age-related decline in the phosphorylation of myosin regulatory light chain (RLC), a critical protein involved in the modulation of muscle contractility, in the skeletal muscle of aging rats. Top-down tandem mass spectrometry analysis identified a previously unreported bis-phosphorylated proteoform of fast skeletal RLC and localized the sites of decreasing phosphorylation to Ser14/15. Of these sites, Ser14 phosphorylation represents a previously unidentified site of phosphorylation in RLC from fast-twitch skeletal muscle. Subsequent mechanical analysis of single fast-twitch fibers isolated from the muscles of rats of different ages revealed that the observed decline in RLC phosphorylation can account for age-related decreases in the contractile properties of sarcopenic fast-twitch muscles. These results strongly support a role for decreasing RLC phosphorylation in sarcopenia-associated muscle dysfunction and suggest that therapeutic modulation of RLC phosphorylation may represent a new avenue for the treatment of sarcopenia.

Integration analysis of quantitative proteomics and transcriptomics data identifies potential targets of frizzled-8 protein-related antiproliferative factor in vivo.

PubMed

Yang, Wei; Kim, Yongsoo; Kim, Taek-Kyun; Keay, Susan K; Kim, Kwang Pyo; Steen, Hanno; Freeman, Michael R; Hwang, Daehee; Kim, Jayoung

2012-12-01

What's known on the subject? and What does the study add? Interstitial cystitis (IC) is a prevalent and debilitating pelvic disorder generally accompanied by chronic pain combined with chronic urinating problems. Over one million Americans are affected, especially middle-aged women. However, its aetiology or mechanism remains unclear. No efficient drug has been provided to patients. Several urinary biomarker candidates have been identified for IC; among the most promising is antiproliferative factor (APF), whose biological activity is detectable in urine specimens from >94% of patients with both ulcerative and non-ulcerative IC. The present study identified several important mediators of the effect of APF on bladder cell physiology, suggesting several candidate drug targets against IC. In an attempt to identify potential proteins and genes regulated by APF in vivo, and to possibly expand the APF-regulated network identified by stable isotope labelling by amino acids in cell culture (SILAC), we performed an integration analysis of our own SILAC data and the microarray data of Gamper et al. (2009) BMC Genomics 10: 199. Notably, two of the proteins (i.e. MAPKSP1 and GSPT1) that are down-regulated by APF are involved in the activation of mTORC1, suggesting that the mammalian target of rapamycin (mTOR) pathway is potentially a critical pathway regulated by APF in vivo. Several components of the mTOR pathway are currently being studied as potential therapeutic targets in other diseases. Our analysis suggests that this pathway might also be relevant in the design of diagnostic tools and medications targeting IC. • To enhance our understanding of the interstitial cystitis urine biomarker antiproliferative factor (APF), as well as interstitial cystitis biology more generally at the systems level, we reanalyzed recently published large-scale quantitative proteomics and in vivo transcriptomics data sets using an integration analysis tool that we have developed. • To

What computational non-targeted mass spectrometry-based metabolomics can gain from shotgun proteomics.

PubMed

Hamzeiy, Hamid; Cox, Jürgen

2017-02-01

Computational workflows for mass spectrometry-based shotgun proteomics and untargeted metabolomics share many steps. Despite the similarities, untargeted metabolomics is lagging behind in terms of reliable fully automated quantitative data analysis. We argue that metabolomics will strongly benefit from the adaptation of successful automated proteomics workflows to metabolomics. MaxQuant is a popular platform for proteomics data analysis and is widely considered to be superior in achieving high precursor mass accuracies through advanced nonlinear recalibration, usually leading to five to ten-fold better accuracy in complex LC-MS/MS runs. This translates to a sharp decrease in the number of peptide candidates per measured feature, thereby strongly improving the coverage of identified peptides. We argue that similar strategies can be applied to untargeted metabolomics, leading to equivalent improvements in metabolite identification. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Platelet proteomics: from discovery to diagnosis.

PubMed

Looße, Christina; Swieringa, Frauke; Heemskerk, Johan W M; Sickmann, Albert; Lorenz, Christin

2018-05-22

Platelets are the smallest cells within the circulating blood with key roles in physiological haemostasis and pathological thrombosis regulated by the onset of activating/inhibiting processes via receptor responses and signalling cascades. Areas covered: Proteomics as well as genomic approaches have been fundamental in identifying and quantifying potential targets for future diagnostic strategies in the prevention of bleeding and thrombosis, and uncovering the complexity of platelet functions in health and disease. In this article, we provide a critical overview on current functional tests used in diagnostics and the future perspectives for platelet proteomics in clinical applications. Expert commentary: Proteomics represents a valuable tool for the identification of patients with diverse platelet associated defects. In-depth validation of identified biomarkers, e.g. receptors, signalling proteins, post-translational modifications, in large cohorts is decisive for translation into routine clinical diagnostics.

Specter: linear deconvolution for targeted analysis of data-independent acquisition mass spectrometry proteomics.

PubMed

Peckner, Ryan; Myers, Samuel A; Jacome, Alvaro Sebastian Vaca; Egertson, Jarrett D; Abelin, Jennifer G; MacCoss, Michael J; Carr, Steven A; Jaffe, Jacob D

2018-05-01

Mass spectrometry with data-independent acquisition (DIA) is a promising method to improve the comprehensiveness and reproducibility of targeted and discovery proteomics, in theory by systematically measuring all peptide precursors in a biological sample. However, the analytical challenges involved in discriminating between peptides with similar sequences in convoluted spectra have limited its applicability in important cases, such as the detection of single-nucleotide polymorphisms (SNPs) and alternative site localizations in phosphoproteomics data. We report Specter (https://github.com/rpeckner-broad/Specter), an open-source software tool that uses linear algebra to deconvolute DIA mixture spectra directly through comparison to a spectral library, thus circumventing the problems associated with typical fragment-correlation-based approaches. We validate the sensitivity of Specter and its performance relative to that of other methods, and show that Specter is able to successfully analyze cases involving highly similar peptides that are typically challenging for DIA analysis methods.

Proteomic profile of Mycobacterium tuberculosis after eupomatenoid-5 induction reveals potential drug targets.

PubMed

Ghiraldi-Lopes, Luciana D; Campanerut-Sá, Paula Az; Meneguello, Jean E; Seixas, Flávio Av; Lopes-Ortiz, Mariana A; Scodro, Regiane Bl; Pires, Claudia Ta; da Silva, Rosi Z; Siqueira, Vera Ld; Nakamura, Celso V; Cardoso, Rosilene F

2017-08-01

We investigated a proteome profile, protein-protein interaction and morphological changes of Mycobacterium tuberculosis after different times of eupomatenoid-5 (EUP-5) induction to evaluate the cellular response to the drug-induced damages. The bacillus was induced to sub-minimal inhibitory concentration of EUP-5 at 12 h, 24 h and 48 h. The proteins were separated by 2D gel electrophoresis, identified by LC/MS-MS. Scanning electron microscopy and Search Tool for the Retrieval of Interacting Genes/Proteins analyses were performed. EUP-5 impacts mainly in M. tuberculosis proteins of intermediary metabolism and interactome suggests a multisite disturbance that contributes to bacilli death. Scanning electron microscopy revealed the loss of bacillary form. Some of the differentially expressed proteins have the potential to be drug targets such as citrate synthase (Rv0896), phosphoglycerate kinase (Rv1437), ketol-acid reductoisomerase (Rv3001c) and ATP synthase alpha chain (Rv1308).

Knowledge Translation: Moving Proteomics Science to Innovation in Society.

PubMed

Holmes, Christina; McDonald, Fiona; Jones, Mavis; Graham, Janice

2016-06-01

Proteomics is one of the pivotal next-generation biotechnologies in the current "postgenomics" era. Little is known about the ways in which innovative proteomics science is navigating the complex socio-political space between laboratory and society. It cannot be assumed that the trajectory between proteomics laboratory and society is linear and unidirectional. Concerned about public accountability and hopes for knowledge-based innovations, funding agencies and citizens increasingly expect that emerging science and technologies, such as proteomics, are effectively translated and disseminated as innovation in society. Here, we describe translation strategies promoted in the knowledge translation (KT) and science communication literatures and examine the use of these strategies within the field of proteomics. Drawing on data generated from qualitative interviews with proteomics scientists and ethnographic observation of international proteomics conferences over a 5-year period, we found that proteomics science incorporates a variety of KT strategies to reach knowledge users outside the field. To attain the full benefit of KT, however, proteomics scientists must challenge their own normative assumptions and approaches to innovation dissemination-beyond the current paradigm relying primarily on publication for one's scientific peers within one's field-and embrace the value of broader (interdisciplinary) KT strategies in promoting the uptake of their research. Notably, the Human Proteome Organization (HUPO) is paying increasing attention to a broader range of KT strategies, including targeted dissemination, integrated KT, and public outreach. We suggest that increasing the variety of KT strategies employed by proteomics scientists is timely and would serve well the omics system sciences community.

Computer applications making rapid advances in high throughput microbial proteomics (HTMP).

PubMed

Anandkumar, Balakrishna; Haga, Steve W; Wu, Hui-Fen

2014-02-01

The last few decades have seen the rise of widely-available proteomics tools. From new data acquisition devices, such as MALDI-MS and 2DE to new database searching softwares, these new products have paved the way for high throughput microbial proteomics (HTMP). These tools are enabling researchers to gain new insights into microbial metabolism, and are opening up new areas of study, such as protein-protein interactions (interactomics) discovery. Computer software is a key part of these emerging fields. This current review considers: 1) software tools for identifying the proteome, such as MASCOT or PDQuest, 2) online databases of proteomes, such as SWISS-PROT, Proteome Web, or the Proteomics Facility of the Pathogen Functional Genomics Resource Center, and 3) software tools for applying proteomic data, such as PSI-BLAST or VESPA. These tools allow for research in network biology, protein identification, functional annotation, target identification/validation, protein expression, protein structural analysis, metabolic pathway engineering and drug discovery.

Mining the nucleus accumbens proteome for novel targets of alcohol self-administration in male C57BL/6J mice.

PubMed

Faccidomo, Sara; Swaim, Katarina S; Saunders, Briana L; Santanam, Taruni S; Taylor, Seth M; Kim, Michelle; Reid, Grant T; Eastman, Vallari R; Hodge, Clyde W

2018-06-01

There is a clear need for discovery of effective medications to treat behavioral pathologies associated with alcohol addiction, such as chronic drinking. The goal of this preclinical study was to assess effects of chronic alcohol drinking on the nucleus accumbens (NAcb) proteome to identify and validate novel targets for medications development. Two-dimensional difference in-gel electrophoresis (2D-DIGE) with matrix-assisted laser desorption ionization tandem time-of-flight (MALDI-TOF/TOF) was used to assess effects of chronic voluntary home-cage (24-h access) alcohol drinking on the NAcb proteome of C57BL/6J mice. To extend these findings to a model of alcohol self-administration and reinforcement, we investigated potential regulation of the positive reinforcing effects of alcohol by the target protein glutathione S-transferase Pi 1 (GSTP1) using a pharmacological inhibition strategy in mice trained to self-administer alcohol or sucrose. Expression of 52 unique proteins in the NAcb was changed by chronic alcohol drinking relative to water control (23 upregulated, 29 downregulated). Ingenuity Pathway Analysis showed that alcohol drinking altered an array of protein networks associated with neurological and psychological disorders, molecular and cellular functions, and physiological systems and development. DAVID functional annotation analysis identified 9 proteins (SNCA, GSTP1, PRDX3, PPP3R1, EIF5A, PHB, PEBP1/RKIP, GAPDH, AND SOD1) that were significantly overrepresented in a functional cluster that included the Gene Ontology categories "response to alcohol" and "aging." Immunoblots confirmed changes in Pebp1 (RKIP) and GSTP1 in NAcb with no change in amygdala or frontal cortex, suggesting anatomical specificity. Systemic inhibition of GSTP1 with Ezatiostat (0-30 mg/kg, i.p.) dose-dependently reduced the reinforcing effects of alcohol as measured by operant self-administration, in the absence of motor effects. Sucrose self-administration was also reduced but in a

Organized proteomic heterogeneity in colorectal cancer liver metastases and implications for therapies.

PubMed

Turtoi, Andrei; Blomme, Arnaud; Debois, Delphine; Somja, Joan; Delvaux, David; Patsos, Georgios; Di Valentin, Emmanuel; Peulen, Olivier; Mutijima, Eugène Nzaramba; De Pauw, Edwin; Delvenne, Philippe; Detry, Olivier; Castronovo, Vincent

2014-03-01

Tumor heterogeneity is a major obstacle for developing effective anticancer treatments. Recent studies have pointed to large stochastic genetic heterogeneity within cancer lesions, where no pattern seems to exist that would enable a more structured targeted therapy approach. Because to date no similar information is available at the protein (phenotype) level, we employed matrix assisted laser desorption ionization (MALDI) image-guided proteomics and explored the heterogeneity of extracellular and membrane subproteome in a unique collection of eight fresh human colorectal carcinoma (CRC) liver metastases. Monitoring the spatial distribution of over 1,000 proteins, we found unexpectedly that all liver metastasis lesions displayed a reproducible, zonally delineated pattern of functional and therapeutic biomarker heterogeneity. The peritumoral region featured elevated lipid metabolism and protein synthesis, the rim of the metastasis displayed increased cellular growth, movement, and drug metabolism, whereas the center of the lesion was characterized by elevated carbohydrate metabolism and DNA-repair activity. From the aspect of therapeutic targeting, zonal expression of known and novel biomarkers was evident, reinforcing the need to select several targets in order to achieve optimal coverage of the lesion. Finally, we highlight two novel antigens, LTBP2 and TGFBI, whose expression is a consistent feature of CRC liver metastasis. We demonstrate their in vivo antibody-based targeting and highlight their potential usefulness for clinical applications. The proteome heterogeneity of human CRC liver metastases has a distinct, organized pattern. This particular hallmark can now be used as part of the strategy for developing rational therapies based on multiple sets of targetable antigens. © 2014 by the American Association for the Study of Liver Diseases.

Retrodiction for Bayesian multiple-hypothesis/multiple-target tracking in densely cluttered environment

NASA Astrophysics Data System (ADS)

Koch, Wolfgang

1996-05-01

Sensor data processing in a dense target/dense clutter environment is inevitably confronted with data association conflicts which correspond with the multiple hypothesis character of many modern approaches (MHT: multiple hypothesis tracking). In this paper we analyze the efficiency of retrodictive techniques that generalize standard fixed interval smoothing to MHT applications. 'Delayed estimation' based on retrodiction provides uniquely interpretable and accurate trajectories from ambiguous MHT output if a certain time delay is tolerated. In a Bayesian framework the theoretical background of retrodiction and its intimate relation to Bayesian MHT is sketched. By a simulated example with two closely-spaced targets, relatively low detection probabilities, and rather high false return densities, we demonstrate the benefits of retrodiction and quantitatively discuss the achievable track accuracies and the time delays involved for typical radar parameters.

A Human Proteome Array Approach to Identifying Key Host Proteins Targeted by Toxoplasma Kinase ROP18*

PubMed Central

Yang, Zhaoshou; Hou, Yongheng; Hao, Taofang; Rho, Hee-Sool; Wan, Jun; Luan, Yizhao; Gao, Xin; Yao, Jianping; Pan, Aihua; Xie, Zhi; Qian, Jiang; Liao, Wanqin; Zhu, Heng; Zhou, Xingwang

2017-01-01

Toxoplasma kinase ROP18 is a key molecule responsible for the virulence of Toxoplasma gondii; however, the mechanisms by which ROP18 exerts parasite virulence via interaction with host proteins remain limited to a small number of identified substrates. To identify a broader array of ROP18 substrates, we successfully purified bioactive mature ROP18 and used it to probe a human proteome array. Sixty eight new putative host targets were identified. Functional annotation analysis suggested that these proteins have a variety of functions, including metabolic process, kinase activity and phosphorylation, cell growth, apoptosis and cell death, and immunity, indicating a pleiotropic role of ROP18 kinase. Among these proteins, four candidates, p53, p38, UBE2N, and Smad1, were further validated. We demonstrated that ROP18 targets p53, p38, UBE2N, and Smad1 for degradation. Importantly, we demonstrated that ROP18 phosphorylates Smad1 Ser-187 to trigger its proteasome-dependent degradation. Further functional characterization of the substrates of ROP18 may enhance understanding of the pathogenesis of Toxoplasma infection and provide new therapeutic targets. Similar strategies could be used to identify novel host targets for other microbial kinases functioning at the pathogen-host interface. PMID:28087594

A proteomic approach to obesity and type 2 diabetes

PubMed Central

López-Villar, Elena; Martos-Moreno, Gabriel Á; Chowen, Julie A; Okada, Shigeru; Kopchick, John J; Argente, Jesús

2015-01-01

The incidence of obesity and type diabetes 2 has increased dramatically resulting in an increased interest in its biomedical relevance. However, the mechanisms that trigger the development of diabetes type 2 in obese patients remain largely unknown. Scientific, clinical and pharmaceutical communities are dedicating vast resources to unravel this issue by applying different omics tools. During the last decade, the advances in proteomic approaches and the Human Proteome Organization have opened and are opening a new door that may be helpful in the identification of patients at risk and to improve current therapies. Here, we briefly review some of the advances in our understanding of type 2 diabetes that have occurred through the application of proteomics. We also review, in detail, the current improvements in proteomic methodologies and new strategies that could be employed to further advance our understanding of this pathology. By applying these new proteomic advances, novel therapeutic and/or diagnostic protein targets will be discovered in the obesity/Type 2 diabetes area. PMID:25960181

Head and neck cancer: proteomic advances and biomarker achievements.

PubMed

Rezende, Taia Maria Berto; de Souza Freire, Mirna; Franco, Octávio Luiz

2010-11-01

Tumors of the head and neck comprise an important neoplasia group, the incidence of which is increasing in many parts of the world. Recent advances in diagnostic and therapeutic techniques for these lesions have yielded novel molecular targets, uncovered signal pathway dominance, and advanced early cancer detection. Proteomics is a powerful tool for investigating the distribution of proteins and small molecules within biological systems through the analysis of different types of samples. The proteomic profiles of different types of cancer have been studied, and this has provided remarkable advances in cancer understanding. This review covers recent advances for head and neck cancer; it encompasses the risk factors, pathogenesis, proteomic tools that can help in understanding cancer, and new proteomic findings in this type of cancer. Copyright © 2010 American Cancer Society.

Analysis of Intrinsic Peptide Detectability via Integrated Label-Free and SRM-Based Absolute Quantitative Proteomics.

PubMed

Jarnuczak, Andrew F; Lee, Dave C H; Lawless, Craig; Holman, Stephen W; Eyers, Claire E; Hubbard, Simon J

2016-09-02

Quantitative mass spectrometry-based proteomics of complex biological samples remains challenging in part due to the variability and charge competition arising during electrospray ionization (ESI) of peptides and the subsequent transfer and detection of ions. These issues preclude direct quantification from signal intensity alone in the absence of a standard. A deeper understanding of the governing principles of peptide ionization and exploitation of the inherent ionization and detection parameters of individual peptides is thus of great value. Here, using the yeast proteome as a model system, we establish the concept of peptide F-factor as a measure of detectability, closely related to ionization efficiency. F-factor is calculated by normalizing peptide precursor ion intensity by absolute abundance of the parent protein. We investigated F-factor characteristics in different shotgun proteomics experiments, including across multiple ESI-based LC-MS platforms. We show that F-factors mirror previously observed physicochemical predictors as peptide detectability but demonstrate a nonlinear relationship between hydrophobicity and peptide detectability. Similarly, we use F-factors to show how peptide ion coelution adversely affects detectability and ionization. We suggest that F-factors have great utility for understanding peptide detectability and gas-phase ion chemistry in complex peptide mixtures, selection of surrogate peptides in targeted MS studies, and for calibration of peptide ion signal in label-free workflows. Data are available via ProteomeXchange with identifier PXD003472.

Novel targets of sulforaphane in primary cardiomyocytes identified by proteomic analysis.

PubMed

Angeloni, Cristina; Turroni, Silvia; Bianchi, Laura; Fabbri, Daniele; Motori, Elisa; Malaguti, Marco; Leoncini, Emanuela; Maraldi, Tullia; Bini, Luca; Brigidi, Patrizia; Hrelia, Silvana

2013-01-01

Cardiovascular diseases represent the main cause of mortality in the industrialized world and the identification of effective preventive strategies is of fundamental importance. Sulforaphane, an isothiocyanate from cruciferous vegetables, has been shown to up-regulate phase II enzymes in cardiomyocytes and counteract oxidative stress-induced apoptosis. Aim of the present study was the identification and characterization of novel sulforaphane targets in cardiomyocytes applying a proteomic approach. Two-dimensional gel electrophoresis and mass spectrometry were used to generate protein profiles of primary neonatal rat cardiomyocytes treated and untreated with 5 µM sulforaphane for 1-48 h. According to image analysis, 64 protein spots were found as differentially expressed and their functional correlations were investigated using the MetaCore program. We mainly focused on 3 proteins: macrophage migration inhibitory factor (MIF), CLP36 or Elfin, and glyoxalase 1, due to their possible involvement in cardioprotection. Validation of the time-dependent differential expression of these proteins was performed by western blotting. In particular, to gain insight into the cardioprotective role of the modulation of glyoxalase 1 by sulforaphane, further experiments were performed using methylglyoxal to mimic glycative stress. Sulforaphane was able to counteract methylglyoxal-induced apoptosis, ROS production, and glycative stress, likely through glyoxalase 1 up-regulation. In this study, we reported for the first time new molecular targets of sulforaphane, such as MIF, CLP36 and glyoxalase 1. In particular, we gave new insights into the anti-glycative role of sulforaphane in cardiomyocytes, confirming its pleiotropic behavior in counteracting cardiovascular diseases.

Quantitative Proteomics Analysis Identifies Mitochondria as Therapeutic Targets of Multidrug-Resistance in Ovarian Cancer

PubMed Central

Chen, Xiulan; Wei, Shasha; Ma, Ying; Lu, Jie; Niu, Gang; Xue, Yanhong; Chen, Xiaoyuan; Yang, Fuquan

2014-01-01

Doxorubicin is a widely used chemotherapeutic agent for the treatment of a variety of solid tumors. However, resistance to this anticancer drug is a major obstacle to the effective treatment of tumors. As mitochondria play important roles in cell life and death, we anticipate that mitochondria may be related to drug resistance. Here, stable isotope labeling by amino acids in cell culture (SILAC)-based quantitative proteomic strategy was applied to compare mitochondrial protein expression in doxorubicin sensitive OVCAR8 cells and its doxorubicin-resistant variant NCI_ADR/RES cells. A total of 2085 proteins were quantified, of which 122 proteins displayed significant changes in the NCI_ADR/RES cells. These proteins participated in a variety of cell processes including cell apoptosis, substance metabolism, transport, detoxification and drug metabolism. Then qRT-PCR and western blot were applied to validate the differentially expressed proteins quantified by SILAC. Further functional studies with RNAi demonstrated TOP1MT, a mitochondrial protein participated in DNA repair, was involved in doxorubicin resistance in NCI_ADR/RES cells. Besides the proteomic study, electron microscopy and fluorescence analysis also observed that mitochondrial morphology and localization were greatly altered in NCI_ADR/RES cells. Mitochondrial membrane potential was also decreased in NCI_ADR/RES cells. All these results indicate that mitochondrial function is impaired in doxorubicin-resistant cells and mitochondria play an important role in doxorubicin resistance. This research provides some new information about doxorubicin resistance, indicating that mitochondria could be therapeutic targets of doxorubicin resistance in ovarian cancer cells. PMID:25285166

The Multinational Arabidopsis Steering Subcommittee for Proteomics Assembles the Largest Proteome Database Resource for Plant Systems Biology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weckwerth, Wolfram; Baginsky, Sacha; Van Wijk, Klass

2009-12-01

online resources, and raw data have been deposited in PRIDE and PRIDE BioMart. Included in this database is an Arabidopsis proteome map that provides evidence for the expression of {approx}50% of all predicted gene models, including several alternative gene models that are not represented in The Arabidopsis Information Resource (TAIR) protein database. A set of organ-specific biomarkers is provided, as well as organ-specific proteotypic peptides for 4105 proteins that can be used to facilitate targeted quantitative proteomic surveys. In the future, the AtProteome database will be linked to additional existing resources developed by MASCP members, such as PPDB, ProMEX, and SUBA. The most comprehensive study on the Arabidopsis chloroplast proteome, which includes information on chloroplast sorting signals, posttranslational modifications (PTMs), and protein abundances (analyzed by high-accuracy MS [Orbitrap]), was recently published by the van Wijk lab.2 These and previous data are available via the plant proteome database (PPDB; http://ppdb.tc.cornell.edu) for A. thaliana and maize. PPDB provides genome-wide experimental and functional characterization of the A. thaliana and maize proteomes, including PTMs and subcellular localization information, with an emphasis on leaf and plastid proteins. Maize and Arabidopsis proteome entries are directly linked via internal BLAST alignments within PPDB. Direct links for each protein to TAIR, SUBA, ProMEX, and other resources are also provided.« less

Targeted therapy of multiple myeloma.

PubMed

Dolloff, Nathan G; Talamo, Giampaolo

2013-01-01

Multiple myeloma (MM) is a plasma cell malignancy and the second most common hematologic cancer. MM is characterized by the accumulation of malignant plasma cells within the bone marrow, and presents clinically with a broad range of symptoms, including hypercalcemia, renal insufficiency, anemia, and lytic bone lesions. MM is a heterogeneous disease associated with genomic instability, where patients may express multiple genetic abnormalities that affect several oncogenic pathways. Commonly detected genetic aberrations are translocations involving immunoglobulin heavy chain (IgH) switch regions (chromosome 14q32) and oncogenes such as c-maf [t(14:16)], cyclin D1 [t(11:14)], and FGFR3/MMSET [t(4:14)]. Advances in the basic understanding of MM and the development of novel agents, such as the immunomodulatory drugs (IMiDs) thalidomide and lenalidomide and the proteasome inhibitor bortezomib, have increased therapeutic response rates and prolonged patient survival. Despite these advances MM remains incurable in the majority of patients, and it is therefore critical to identify additional therapeutic strategies and targets for its treatment. In this chapter, we review the underlying genetic components of MM and discuss the results of recent clinical trials that demonstrate the effectiveness of targeted agents in the management of MM. In addition, we discuss experimental therapies that are currently in clinical development along with their molecular rationale in the treatment of MM.

CPTAC researchers report first large-scale integrated proteomic and genomic analysis of a human cancer | Office of Cancer Clinical Proteomics Research

Cancer.gov

Investigators from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) who comprehensively analyzed 95 human colorectal tumor samples, have determined how gene alterations identified in previous analyses of the same samples are expressed at the protein level. The integration of proteomic and genomic data, or proteogenomics, provides a more comprehensive view of the biological features that drive cancer than genomic analysis alone and may help identify the most important targets for cancer detection and intervention.

Advances in Proteomics of Mycobacterium leprae.

PubMed

Parkash, O; Singh, B P

2012-04-01

Although Mycobacterium leprae was the first bacterial pathogen identified causing human disease, it remains one of the few that is non-cultivable. Understanding the biology of M. leprae is one of the primary challenges in current leprosy research. Genomics has been extremely valuable, nonetheless, functional proteins are ultimately responsible for controlling most aspects of cellular functions, which in turn could facilitate parasitizing the host. Furthermore, bacterial proteins provide targets for most of the vaccines and immunodiagnostic tools. Better understanding of the proteomics of M. leprae could also help in developing new drugs against M. leprae. During the past nearly 15 years, there have been several developments towards the identification of M. leprae proteins employing contemporary proteomics tools. In this review, we discuss the knowledge gained on the biology and pathogenesis of M. leprae from current proteomic studies. © 2012 The Authors. Scandinavian Journal of Immunology © 2012 Blackwell Publishing Ltd.

Biomechanical and proteomic analysis of INF- β-treated astrocytes

NASA Astrophysics Data System (ADS)

Vergara, Daniele; Martignago, Roberta; Leporatti, Stefano; Bonsegna, Stefania; Maruccio, Giuseppe; De Nuccio, Franco; Santino, Angelo; Cingolani, Roberto; Nicolardi, Giuseppe; Maffia, Michele; Rinaldi, Ross

2009-11-01

Astrocytes have a key role in the pathogenesis of several diseases including multiple sclerosis and were proposed as the designed target for immunotherapy. In this study we used atomic force microscopy (AFM) and proteomics methods to analyse and correlate the modifications induced in the viscoleastic properties of astrocytes to the changes induced in protein expression after interferon- β (IFN-β) treatment. Our results indicated that IFN-β treatment resulted in a significant decrease in the Young's modulus, a measure of cell elasticity, in comparison with control cells. The molecular mechanisms that trigger these changes were investigated by 2DE (two-dimensional electrophoresis) and confocal analyses and confirmed by western blotting. Altered proteins were found to be involved in cytoskeleton organization and other important physiological processes.

Systemic hyperfibrinolysis after trauma: a pilot study of targeted proteomic analysis of superposed mechanisms in patient plasma.

PubMed

Banerjee, Anirban; Silliman, Christopher C; Moore, Ernest E; Dzieciatkowska, Monika; Kelher, Marguerite; Sauaia, Angela; Jones, Kenneth; Chapman, Michael P; Gonzalez, Eduardo; Moore, Hunter B; D'Alessandro, Angelo; Peltz, Erik; Huebner, Benjamin E; Einerson, Peter; Chandler, James; Ghasabayan, Arsen; Hansen, Kirk

2018-06-01

Viscoelastic measurements of hemostasis indicate that 20% of seriously injured patients exhibit systemic hyperfibrinolysis, with increased early mortality. These patients have normal clot formation with rapid clot lysis. Targeted proteomics was applied to quantify plasma proteins from hyperfibrinolytic (HF) patients to elucidate potential pathophysiology. Blood samples were collected in the field or at emergency department arrival and thrombelastography (TEG) was used to characterize in vitro clot formation under native and tissue plasminogen activator (tPA)-stimulated conditions. Ten samples were taken from injured patients exhibiting normal lysis time at 30 min (Ly30), "eufibrinolytic" (EF), 10 from HF patients, defined as tPA-stimulated TEG Ly30 >50%, and 10 from healthy controls. Trauma patient samples were analyzed by targeted proteomics and ELISA assays for specific coagulation proteins. HF patients exhibited increased plasminogen activation. Thirty-three proteins from the HF patients were significantly decreased compared with healthy controls and EF patients; 17 were coagulation proteins with anti-protease consumption (p < 0.005). The other 16 decreased proteins indicate activation of the alternate complement pathway, depletion of carrier proteins, and four glycoproteins. CXC7 was elevated in all injured patients versus healthy controls (p < 0.005), and 35 proteins were unchanged across all groups (p > 0.1 and fold change of concentrations of 0.75-1.3). HF patients had significant decreases in specific proteins and support mechanisms known in trauma-induced hyperfibrinolysis and also unexpected decreases in coagulation factors, factors II, X, and XIII, without changes in clot formation (SP, R times, or angle). Decreased clot stability in HF patients was corroborated with tPA-stimulated TEGs. Prognostic, level III.

Proteome | Office of Cancer Clinical Proteomics Research

Cancer.gov

A proteome is the entire complement of proteins, including modifications made to a particular set of proteins, produced by an organism or a cellular system. This will vary with time and distinct requirements such as growth conditions and stresses, and thus is highly dynamic and spatial. Proteomics is the study of the proteome.

Multiclassifier combinatorial proteomics of organelle shadows at the example of mitochondria in chromatin data.

PubMed

Kustatscher, Georg; Grabowski, Piotr; Rappsilber, Juri

2016-02-01

Subcellular localization is an important aspect of protein function, but the protein composition of many intracellular compartments is poorly characterized. For example, many nuclear bodies are challenging to isolate biochemically and thus remain inaccessible to proteomics. Here, we explore covariation in proteomics data as an alternative route to subcellular proteomes. Rather than targeting a structure of interest biochemically, we target it by machine learning. This becomes possible by taking data obtained for one organelle and searching it for traces of another organelle. As an extreme example and proof-of-concept we predict mitochondrial proteins based on their covariation in published interphase chromatin data. We detect about ⅓ of the known mitochondrial proteins in our chromatin data, presumably most as contaminants. However, these proteins are not present at random. We show covariation of mitochondrial proteins in chromatin proteomics data. We then exploit this covariation by multiclassifier combinatorial proteomics to define a list of mitochondrial proteins. This list agrees well with different databases on mitochondrial composition. This benchmark test raises the possibility that, in principle, covariation proteomics may also be applicable to structures for which no biochemical isolation procedures are available. © 2015 The Authors. Proteomics Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Confetti: A Multiprotease Map of the HeLa Proteome for Comprehensive Proteomics*

PubMed Central

Guo, Xiaofeng; Trudgian, David C.; Lemoff, Andrew; Yadavalli, Sivaramakrishna; Mirzaei, Hamid

2014-01-01

Bottom-up proteomics largely relies on tryptic peptides for protein identification and quantification. Tryptic digestion often provides limited coverage of protein sequence because of issues such as peptide length, ionization efficiency, and post-translational modification colocalization. Unfortunately, a region of interest in a protein, for example, because of proximity to an active site or the presence of important post-translational modifications, may not be covered by tryptic peptides. Detection limits, quantification accuracy, and isoform differentiation can also be improved with greater sequence coverage. Selected reaction monitoring (SRM) would also greatly benefit from being able to identify additional targetable sequences. In an attempt to improve protein sequence coverage and to target regions of proteins that do not generate useful tryptic peptides, we deployed a multiprotease strategy on the HeLa proteome. First, we used seven commercially available enzymes in single, double, and triple enzyme combinations. A total of 48 digests were performed. 5223 proteins were detected by analyzing the unfractionated cell lysate digest directly; with 42% mean sequence coverage. Additional strong-anion exchange fractionation of the most complementary digests permitted identification of over 3000 more proteins, with improved mean sequence coverage. We then constructed a web application (https://proteomics.swmed.edu/confetti) that allows the community to examine a target protein or protein isoform in order to discover the enzyme or combination of enzymes that would yield peptides spanning a certain region of interest in the sequence. Finally, we examined the use of nontryptic digests for SRM. From our strong-anion exchange fractionation data, we were able to identify three or more proteotypic SRM candidates within a single digest for 6056 genes. Surprisingly, in 25% of these cases the digest producing the most observable proteotypic peptides was neither trypsin nor Lys

Activity-based proteome profiling of potential cellular targets of Orlistat--an FDA-approved drug with anti-tumor activities.

PubMed

Yang, Peng-Yu; Liu, Kai; Ngai, Mun Hong; Lear, Martin J; Wenk, Markus R; Yao, Shao Q

2010-01-20

Orlistat, or tetrahydrolipstatin (THL), is an FDA-approved antiobesity drug with potential antitumor activities. Cellular off-targets and potential side effects of Orlistat in cancer therapies, however, have not been extensively explored thus far. In this study, we report the total of synthesis of THL-like protein-reactive probes, in which extremely conservative modifications (i.e., an alkyne handle) were introduced in the parental THL structure to maintain the native biological properties of Orlistat, while providing the necessary functionality for target identification via the bio-orthogonal click chemistry. With these natural productlike, cell-permeable probes, we were able to demonstrate, for the first time, this chemical proteomic approach is suitable for the identification of previously unknown cellular targets of Orlistat. In addition to the expected fatty acid synthase (FAS), we identified a total of eight new targets, some of which were further validated by experiments including Western blotting, recombinant protein expression, and site-directed mutagenesis. Our findings have important implications in the consideration of Orlistat as a potential anticancer drug at its early stages of development for cancer therapy. Our strategy should be broadly useful for off-target identification against quite a number of existing drugs and/or candidates, which are also covalent modifiers of their biological targets.

Prestroke Proteomic Changes in Cerebral Microvessels in Stroke-Prone, Transgenic[hCETP]-Hyperlipidemic, Dahl Salt-Sensitive Hypertensive Rats

PubMed Central

Bergerat, Agnes; Decano, Julius; Wu, Chang-Jiun; Choi, Hyungwon; Nesvizhskii, Alexey I; Moran, Ann Marie; Ruiz-Opazo, Nelson; Steffen, Martin; Herrera, Victoria LM

2011-01-01

Stroke is the third leading cause of death in the United States with high rates of morbidity among survivors. The search to fill the unequivocal need for new therapeutic approaches would benefit from unbiased proteomic analyses of animal models of spontaneous stroke in the prestroke stage. Since brain microvessels play key roles in neurovascular coupling, we investigated prestroke microvascular proteome changes. Proteomic analysis of cerebral cortical microvessels (cMVs) was done by tandem mass spectrometry comparing two prestroke time points. Metaprotein-pathway analyses of proteomic spectral count data were done to identify risk factor–induced changes, followed by QSPEC-analyses of individual protein changes associated with increased stroke susceptibility. We report 26 cMV proteome profiles from male and female stroke-prone and non–stroke-prone rats at 2 months and 4.5 months of age prior to overt stroke events. We identified 1,934 proteins by two or more peptides. Metaprotein pathway analysis detected age-associated changes in energy metabolism and cell-to-microenvironment interactions, as well as sex-specific changes in energy metabolism and endothelial leukocyte transmigration pathways. Stroke susceptibility was associated independently with multiple protein changes associated with ischemia, angiogenesis or involved in blood brain barrier (BBB) integrity. Immunohistochemical analysis confirmed aquaporin-4 and laminin-α1 induction in cMVs, representative of proteomic changes with >65 Bayes factor (BF), associated with stroke susceptibility. Altogether, proteomic analysis demonstrates significant molecular changes in ischemic cerebral microvasculature in the prestroke stage, which could contribute to the observed model phenotype of microhemorrhages and postischemic hemorrhagic transformation. These pathways comprise putative targets for translational research of much needed novel diagnostic and therapeutic approaches for stroke. PMID:21519634

Pre-fractionation strategies to resolve pea (Pisum sativum) sub-proteomes

PubMed Central

Meisrimler, Claudia-Nicole; Menckhoff, Ljiljana; Kukavica, Biljana M.; Lüthje, Sabine

2015-01-01

Legumes are important crop plants and pea (Pisum sativum L.) has been investigated as a model with respect to several physiological aspects. The sequencing of the pea genome has not been completed. Therefore, proteomic approaches are currently limited. Nevertheless, the increasing numbers of available EST-databases as well as the high homology of the pea and medicago genome (Medicago truncatula Gaertner) allow the successful identification of proteins. Due to the un-sequenced pea genome, pre-fractionation approaches have been used in pea proteomic surveys in the past. Aside from a number of selective proteome studies on crude extracts and the chloroplast, few studies have targeted other components such as the pea secretome, an important sub-proteome of interest due to its role in abiotic and biotic stress processes. The secretome itself can be further divided into different sub-proteomes (plasma membrane, apoplast, cell wall proteins). Cell fractionation in combination with different gel-electrophoresis, chromatography methods and protein identification by mass spectrometry are important partners to gain insight into pea sub-proteomes, post-translational modifications and protein functions. Overall, pea proteomics needs to link numerous existing physiological and biochemical data to gain further insight into adaptation processes, which play important roles in field applications. Future developments and directions in pea proteomics are discussed. PMID:26539198

Highly abundant defense proteins in human sweat as revealed by targeted proteomics and label-free quantification mass spectrometry.

PubMed

Csősz, É; Emri, G; Kalló, G; Tsaprailis, G; Tőzsér, J

2015-10-01

The healthy human skin with its effective antimicrobial defense system forms an efficient barrier against invading pathogens. There is evidence suggesting that the composition of this chemical barrier varies between diseases, making the easily collected sweat an ideal candidate for biomarker discoveries. Our aim was to provide information about the normal composition of the sweat, and to study the chemical barrier found at the surface of skin. Sweat samples from healthy individuals were collected during sauna bathing, and the global protein panel was analysed by label-free mass spectrometry. SRM-based targeted proteomic methods were designed and stable isotope labelled reference peptides were used for method validation. Ninety-five sweat proteins were identified, 20 of them were novel proteins. It was shown that dermcidin is the most abundant sweat protein, and along with apolipoprotein D, clusterin, prolactin-inducible protein and serum albumin, they make up 91% of secreted sweat proteins. The roles of these highly abundant proteins were reviewed; all of which have protective functions, highlighting the importance of sweat glands in composing the first line of innate immune defense system, and maintaining the epidermal barrier integrity. Our findings with regard to the proteins forming the chemical barrier of the skin as determined by label-free quantification and targeted proteomics methods are in accordance with previous studies, and can be further used as a starting point for non-invasive sweat biomarker research. © 2015 European Academy of Dermatology and Venereology.

Mapping Proteome-Wide Interactions of Reactive Chemicals Using Chemoproteomic Platforms

PubMed Central

Counihan, Jessica L.; Ford, Breanna; Nomura, Daniel K.

2015-01-01

A large number of pharmaceuticals, endogenous metabolites, and environmental chemicals act through covalent mechanisms with protein targets. Yet, their specific interactions with the proteome still remain poorly defined for most of these reactive chemicals. Deciphering direct protein targets of reactive small-molecules is critical in understanding their biological action, off-target effects, potential toxicological liabilities, and development of safer and more selective agents. Chemoproteomic technologies have arisen as a powerful strategy that enable the assessment of proteome-wide interactions of these irreversible agents directly in complex biological systems. We review here several chemoproteomic strategies that have facilitated our understanding of specific protein interactions of irreversibly-acting pharmaceuticals, endogenous metabolites, and environmental electrophiles to reveal novel pharmacological, biological, and toxicological mechanisms. PMID:26647369

Study of the Plasma Membrane Proteome Dynamics Reveals Novel Targets of the Nitrogen Regulation in Yeast.

PubMed

Villers, Jennifer; Savocco, Jérôme; Szopinska, Aleksandra; Degand, Hervé; Nootens, Sylvain; Morsomme, Pierre

2017-09-01

Yeast cells, to be able to grow on a wide variety of nitrogen sources, regulate the set of nitrogen transporters present at their plasma membrane. Such regulation relies on both transcriptional and post-translational events. Although microarray studies have identified most nitrogen-sensitive genes, nitrogen-induced post-translational regulation has only been studied for very few proteins among which the general amino acid permease Gap1. Adding a preferred nitrogen source to proline-grown cells triggers Gap1 endocytosis and vacuolar degradation in an Rsp5-Bul1/2-dependent manner. Here, we used a proteomic approach to follow the dynamics of the plasma membrane proteome after addition of a preferred nitrogen source. We identified new targets of the nitrogen regulation and four transporters of poor nitrogen sources-Put4, Opt2, Dal5, and Ptr2-that rapidly decrease in abundance. Although the kinetics is different for each transporter, we found that three of them-Put4, Dal5, and Ptr2-are endocytosed, like Gap1, in an Rsp5-dependent manner and degraded in the vacuole. Finally, we showed that Gap1 stabilization at the plasma membrane, through deletion of Bul proteins, regulates the abundance of Put4, Dal5 and Ptr2. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Multiple-Targeted Graphene-based Nanocarrier for Intracellular Imaging of mRNAs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Ying; Li, Zhaohui; Liu, Misha

Simultaneous detection and imaging of multiple intracellular messenger RNA (mRNAs) hold great significant for early cancer diagnostics and preventive medicine development. Herein, we propose a multiple-targeted graphene oxide (GO) nanocarrier that can simultaneously detect and image different type mRNAs in living cells. First of all, in vitro detection of multiple targets have been realized successfully based on the multiple-targeted GO nanocarrier with linear relationship ranging from 3 nM to 200 nM, as well as sensitive detection limit of 1.84 nM for manganese superoxide dismutase (Mn-SOD) mRNA and 2.45 nM for β-actin mRNA. Additionally, this nanosensing platform composed of fluorescent labeledmore » single strand DNA probes and GO nanocarrier can identify Mn-SOD mRNA and endogenous mRNA of β-actin in living cancer cells, showing rapid response, high specificity, nuclease stability, and good biocompatibility during the cell imaging. Thirdly, changes of the expression levels of mRNA in living cells before or after the drug treatment can be monitored successfully. By using multiple ssDNA as probes and GO nanocarrier as the cellular delivery cargo, the proposed simultaneous multiple-targeted sensing platform will be of great potential as a powerful tool for intracellular trafficking process from basic research to clinical diagnosis.« less

Statistical characterization of multiple-reaction monitoring mass spectrometry (MRM-MS) assays for quantitative proteomics

PubMed Central

2012-01-01

Multiple reaction monitoring mass spectrometry (MRM-MS) with stable isotope dilution (SID) is increasingly becoming a widely accepted assay for the quantification of proteins and peptides. These assays have shown great promise in relatively high throughput verification of candidate biomarkers. While the use of MRM-MS assays is well established in the small molecule realm, their introduction and use in proteomics is relatively recent. As such, statistical and computational methods for the analysis of MRM-MS data from proteins and peptides are still being developed. Based on our extensive experience with analyzing a wide range of SID-MRM-MS data, we set forth a methodology for analysis that encompasses significant aspects ranging from data quality assessment, assay characterization including calibration curves, limits of detection (LOD) and quantification (LOQ), and measurement of intra- and interlaboratory precision. We draw upon publicly available seminal datasets to illustrate our methods and algorithms. PMID:23176545

Statistical characterization of multiple-reaction monitoring mass spectrometry (MRM-MS) assays for quantitative proteomics.

PubMed

Mani, D R; Abbatiello, Susan E; Carr, Steven A

2012-01-01

Multiple reaction monitoring mass spectrometry (MRM-MS) with stable isotope dilution (SID) is increasingly becoming a widely accepted assay for the quantification of proteins and peptides. These assays have shown great promise in relatively high throughput verification of candidate biomarkers. While the use of MRM-MS assays is well established in the small molecule realm, their introduction and use in proteomics is relatively recent. As such, statistical and computational methods for the analysis of MRM-MS data from proteins and peptides are still being developed. Based on our extensive experience with analyzing a wide range of SID-MRM-MS data, we set forth a methodology for analysis that encompasses significant aspects ranging from data quality assessment, assay characterization including calibration curves, limits of detection (LOD) and quantification (LOQ), and measurement of intra- and interlaboratory precision. We draw upon publicly available seminal datasets to illustrate our methods and algorithms.

Sys-BodyFluid: a systematical database for human body fluid proteome research

PubMed Central

Li, Su-Jun; Peng, Mao; Li, Hong; Liu, Bo-Shu; Wang, Chuan; Wu, Jia-Rui; Li, Yi-Xue; Zeng, Rong

2009-01-01

Recently, body fluids have widely become an important target for proteomic research and proteomic study has produced more and more body fluid related protein data. A database is needed to collect and analyze these proteome data. Thus, we developed this web-based body fluid proteome database Sys-BodyFluid. It contains eleven kinds of body fluid proteomes, including plasma/serum, urine, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, synovial fluid, nipple aspirate fluid, tear fluid, seminal fluid, human milk and amniotic fluid. Over 10 000 proteins are presented in the Sys-BodyFluid. Sys-BodyFluid provides the detailed protein annotations, including protein description, Gene Ontology, domain information, protein sequence and involved pathways. These proteome data can be retrieved by using protein name, protein accession number and sequence similarity. In addition, users can query between these different body fluids to get the different proteins identification information. Sys-BodyFluid database can facilitate the body fluid proteomics and disease proteomics research as a reference database. It is available at http://www.biosino.org/bodyfluid/. PMID:18978022

Sys-BodyFluid: a systematical database for human body fluid proteome research.

PubMed

Li, Su-Jun; Peng, Mao; Li, Hong; Liu, Bo-Shu; Wang, Chuan; Wu, Jia-Rui; Li, Yi-Xue; Zeng, Rong

2009-01-01

Recently, body fluids have widely become an important target for proteomic research and proteomic study has produced more and more body fluid related protein data. A database is needed to collect and analyze these proteome data. Thus, we developed this web-based body fluid proteome database Sys-BodyFluid. It contains eleven kinds of body fluid proteomes, including plasma/serum, urine, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, synovial fluid, nipple aspirate fluid, tear fluid, seminal fluid, human milk and amniotic fluid. Over 10,000 proteins are presented in the Sys-BodyFluid. Sys-BodyFluid provides the detailed protein annotations, including protein description, Gene Ontology, domain information, protein sequence and involved pathways. These proteome data can be retrieved by using protein name, protein accession number and sequence similarity. In addition, users can query between these different body fluids to get the different proteins identification information. Sys-BodyFluid database can facilitate the body fluid proteomics and disease proteomics research as a reference database. It is available at http://www.biosino.org/bodyfluid/.

Investigation of the therapy targets of Yi-Qi-Yang-Yin-Hua-Tan-Qu-Yu recipe on type 2 diabetes by serum proteome labeled with iTRAQ.

PubMed

Zhao, Jing; Xie, Ming; Liu, Jin-Na; Wang, Bang-Zhong

2018-04-11

Ethnopharmacology relevance Based on basic theories of Chinese medicine, Yi-Qi-Yang-Yin-Hua-Tan-Qu-Yu (YQYYHTQY) recipe was constituted by eleven kinds of Chinese herbs and effective in treatment of type 2 diabetes (T2DM). But the therapy target was unclear. In this study, we used the serum proteome labeled by iTRAQ to find therapy target of YQYYHTQY recipe on T2DM. The rat model was induced by high-fat diet (HFD) and streptozotocin (STZ, 30mg/kg). Drugs were administered to rats once daily for 14 days. Related laboratory parameters were observed. Serum proteome were compared between T2DM and YQYYHTQY group using the iTRAQ labeling quantitative proteomics technique. Functional differential proteins were analysis by STRING software. Target proteins were confirmed by ELISA kits. Hyperglycemia, hyperinsulinemia, insulin resistance, decrease of glucose transporter, depilation, less activity, flock together, depression, ecchymosis of tongue and tail appearance, the typical diabetic patients "a little more than three" symptoms, as well as the decrease of grip strength, serum cyclic adenosine monophosphate (cAMP)/ cyclic guanosine monophosphate (cGMP) ratio, serum high density lipoprotein-cholesterol (HDL-C) and the increase of serum triglyceride (TG), total cholesterol (TC), low density lipoprotein-cholesterol (LDL-C), thromboxane B 2 (TXB 2 )/ 6-keto prostaglandin F1α (6-keto PGF1α) ratio, endothelin-1 (ET-1) levels were found in T2DM group. After drugs treatment, all the above indexes almost were improved in different degrees and effect of YQYYHTQY recipe was superior to pioglitazone hydrochloride. In addition, there were 23 differential proteins, 5 up-regulated and 18 down-regulated proteins. Of them, there were 4 proteins related with diabetes, blood and behavior. Cell division control protein 42 homolog (CDC42) and Ras homolog gene family member A (RhoA) were the therapy targets of YQYYHTQY recipe on T2DM. YQYYHTQY recipe showed therapy effect on T2DM. CDC42 and

A Method for Label-Free, Differential Top-Down Proteomics.

PubMed

Ntai, Ioanna; Toby, Timothy K; LeDuc, Richard D; Kelleher, Neil L

2016-01-01

Biomarker discovery in the translational research has heavily relied on labeled and label-free quantitative bottom-up proteomics. Here, we describe a new approach to biomarker studies that utilizes high-throughput top-down proteomics and is the first to offer whole protein characterization and relative quantitation within the same experiment. Using yeast as a model, we report procedures for a label-free approach to quantify the relative abundance of intact proteins ranging from 0 to 30 kDa in two different states. In this chapter, we describe the integrated methodology for the large-scale profiling and quantitation of the intact proteome by liquid chromatography-mass spectrometry (LC-MS) without the need for metabolic or chemical labeling. This recent advance for quantitative top-down proteomics is best implemented with a robust and highly controlled sample preparation workflow before data acquisition on a high-resolution mass spectrometer, and the application of a hierarchical linear statistical model to account for the multiple levels of variance contained in quantitative proteomic comparisons of samples for basic and clinical research.

Sorafenib: targeting multiple tyrosine kinases in cancer.

PubMed

Hasskarl, Jens

2014-01-01

Sorafenib (BAY 43-9006, Nexavar®) is an oral multiple tyrosine kinase inhibitor. Main targets are receptor tyrosine kinase pathways frequently deregulated in cancer such as the Raf-Ras pathway, vascular endothelial growth factor (VEGF) pathway, and FMS-like tyrosine kinase 3 (FLT3). Sorafenib was approved by the FDA in fast track for advanced renal cell cancer and hepatocellular cancer and shows good clinical activity in thyroid cancer. Multiple clinical trials are undertaken to further investigate the role of sorafenib alone or in combination for the treatment of various tumor entities.

A study protocol for quantitative targeted absolute proteomics (QTAP) by LC-MS/MS: application for inter-strain differences in protein expression levels of transporters, receptors, claudin-5, and marker proteins at the blood–brain barrier in ddY, FVB, and C57BL/6J mice

PubMed Central

2013-01-01

Proteomics has opened a new horizon in biological sciences. Global proteomic analysis is a promising technology for the discovery of thousands of proteins, post-translational modifications, polymorphisms, and molecular interactions in a variety of biological systems. The activities and roles of the identified proteins must also be elucidated, but this is complicated by the inability of conventional proteomic methods to yield quantitative information for protein expression. Thus, a variety of biological systems remain “black boxes”. Quantitative targeted absolute proteomics (QTAP) enables the determination of absolute expression levels (mol) of any target protein, including low-abundance functional proteins, such as transporters and receptors. Therefore, QTAP will be useful for understanding the activities and roles of individual proteins and their differences, including normal/disease, human/animal, or in vitro/in vivo. Here, we describe the study protocols and precautions for QTAP experiments including in silico target peptide selection, determination of peptide concentration by amino acid analysis, setup of selected/multiple reaction monitoring (SRM/MRM) analysis in liquid chromatography–tandem mass spectrometry, preparation of protein samples (brain capillaries and plasma membrane fractions) followed by the preparation of peptide samples, simultaneous absolute quantification of target proteins by SRM/MRM analysis, data analysis, and troubleshooting. An application of QTAP in biological sciences was introduced that utilizes data from inter-strain differences in the protein expression levels of transporters, receptors, tight junction proteins and marker proteins at the blood–brain barrier in ddY, FVB, and C57BL/6J mice. Among 18 molecules, 13 (abcb1a/mdr1a/P-gp, abcc4/mrp4, abcg2/bcrp, slc2a1/glut1, slc7a5/lat1, slc16a1/mct1, slc22a8/oat3, insr, lrp1, tfr1, claudin-5, Na+/K+-ATPase, and γ-gtp) were detected in the isolated brain capillaries, and their

Large-scale inference of protein tissue origin in gram-positive sepsis plasma using quantitative targeted proteomics

PubMed Central

Malmström, Erik; Kilsgård, Ola; Hauri, Simon; Smeds, Emanuel; Herwald, Heiko; Malmström, Lars; Malmström, Johan

2016-01-01

The plasma proteome is highly dynamic and variable, composed of proteins derived from surrounding tissues and cells. To investigate the complex processes that control the composition of the plasma proteome, we developed a mass spectrometry-based proteomics strategy to infer the origin of proteins detected in murine plasma. The strategy relies on the construction of a comprehensive protein tissue atlas from cells and highly vascularized organs using shotgun mass spectrometry. The protein tissue atlas was transformed to a spectral library for highly reproducible quantification of tissue-specific proteins directly in plasma using SWATH-like data-independent mass spectrometry analysis. We show that the method can determine drastic changes of tissue-specific protein profiles in blood plasma from mouse animal models with sepsis. The strategy can be extended to several other species advancing our understanding of the complex processes that contribute to the plasma proteome dynamics. PMID:26732734

The Use of Proteomics in Assisted Reproduction.

PubMed

Kosteria, Ioanna; Anagnostopoulos, Athanasios K; Kanaka-Gantenbein, Christina; Chrousos, George P; Tsangaris, George T

2017-01-01

Despite the explosive increase in the use of Assisted Reproductive Technologies (ART) over the last 30 years, their success rates remain suboptimal. Proteomics is a rapidly-evolving technology-driven science that has already been widely applied in the exploration of human reproduction and fertility, providing useful insights into its physiology and leading to the identification of numerous proteins that may be potential biomarkers and/or treatment targets of a successful ART pregnancy. Here we present a brief overview of the techniques used in proteomic analyses and attempt a comprehensive presentation of recent data from mass spectrometry-based proteomic studies in humans, regarding all components of ARTs, including the male and female gamete, the derived zygote and embryo, the endometrium and, finally, the ART offspring both pre- and postnatally. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Quantification of mutant SPOP proteins in prostate cancer using mass spectrometry-based targeted proteomics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Hui; Barbieri, Christopher E.; He, Jintang

Speckle-type POZ protein (SPOP) is an E3 ubiquitin ligase adaptor protein that functions as a potential tumor suppressor, and SPOP mutations have been identified in ~10% of human prostate cancers. However, it remains unclear if mutant SPOP proteins can be utilized as biomarkers for early detection, diagnosis, prognosis or targeted therapy of prostate cancer. Moreover, the SPOP mutation sites are distributed in a relatively short region where multiple lysine residues, posing significant challenges for bottom-up proteomics analysis of the SPOP mutations. To address this issue, PRISM (high-pressure, high-resolution separations coupled with intelligent selection and multiplexing)-SRM (selected reaction monitoring) mass spectrometrymore » assays have been developed for quantifying wild-type SPOP protein and 11 prostate cancer-derived SPOP mutations. Despite inherent limitations due to amino acid sequence constraints, all the PRISM-SRM assays developed using Arg-C digestion showed a linear dynamic range of at least two orders of magnitude, with limits of quantification range from 0.1 to 1 fmol/μg of total protein in the cell lysate. Applying these SRM assays to analyze HEK293T cells with and without expression of the three most frequent SPOP mutations in prostate cancer (Y87N, F102C or F133V) led to confident detection of all three SPOP mutations in corresponding positive cell lines but not in the negative cell lines. Expression of the F133V mutation and wild-type SPOP was at much lower levels compared to that of F102C and Y87N mutations; however, at present it is unknown if this also affects the activity of the SPOP protein. In summary, PRISM-SRM enables multiplexed, isoform-specific detection of mutant SPOP proteins in cell lysates, which holds great potential in biomarker development for prostate cancer.« less

Application of proteomics in research on traditional Chinese medicine.

PubMed

Suo, Tongchuan; Wang, Haixia; Li, Zheng

2016-09-01

Traditional Chinese medicine (TCM) is a widely used complementary alternative medicine approach. Although many aspects of its effectiveness have been approved clinically, rigorous scientific techniques are highly required to translate the promises from TCM into powerful modern therapies. In this respect, proteomics is useful because of its ability to unveil the underlying target proteins and/or protein biomarkers. In this review, we summarize the recent interplay between proteomics and research on TCM, ranging from exploration of the medicinal materials to the biological basis of TCM concepts, and from pathological studies to pharmacological investigations. We show that proteomic analyses provide preliminary biological evidence of the promises in TCM, and the integration of proteomics with other omics and bioinformatics offers a comprehensive methodology to address the complications of TCM. Expert commentary: Currently, only limited information can be obtained regarding TCM issues and thus more work is required to resolve the ambiguity. As such, more collaborations between proteomics and other techniques (other omics, network pharmacology, etc.) are essential for deciphering the underlying biological basis in TCM topics.

Phosphorylation of ubiquitin at Ser65 affects its polymerization, targets, and proteome-wide turnover

PubMed Central

Swaney, Danielle L; Rodríguez-Mias, Ricard A; Villén, Judit

2015-01-01

Ubiquitylation is an essential post-translational modification that regulates numerous cellular processes, most notably protein degradation. Ubiquitin can itself be phosphorylated at nearly every serine, threonine, and tyrosine residue. However, the effect of this modification on ubiquitin function is largely unknown. Here, we characterized the effects of phosphorylation of yeast ubiquitin at serine 65 in vivo and in vitro. We find this post-translational modification to be regulated under oxidative stress, occurring concomitantly with the restructuring of the ubiquitin landscape into a highly polymeric state. Phosphomimetic mutation of S65 recapitulates the oxidative stress phenotype, causing a dramatic accumulation of ubiquitylated proteins and a proteome-wide reduction of protein turnover rates. Importantly, this mutation impacts ubiquitin chain disassembly, chain linkage distribution, ubiquitin interactions, and substrate targeting. These results demonstrate that phosphorylation is an additional mode of ubiquitin regulation with broad implications in cellular physiology. PMID:26142280

Combined miRNA profiling and proteomics demonstrates that different miRNAs target a common set of proteins to promote colorectal cancer metastasis.

PubMed

Torres, Sofía; Garcia-Palmero, Irene; Bartolomé, Rubén A; Fernandez-Aceñero, María Jesús; Molina, Elena; Calviño, Eva; Segura, Miguel F; Casal, J Ignacio

2017-05-01

The process of liver colonization in colorectal cancer remains poorly characterized. Here, we addressed the role of microRNA (miRNA) dysregulation in metastasis. We first compared miRNA expression profiles between colorectal cancer cell lines with different metastatic properties and then identified target proteins of the dysregulated miRNAs to establish their functions and prognostic value. We found that 38 miRNAs were differentially expressed between highly metastatic (KM12SM/SW620) and poorly metastatic (KM12C/SW480) cancer cell lines. After initial validation, we determined that three miRNAs (miR-424-3p, -503, and -1292) were overexpressed in metastatic colorectal cancer cell lines and human samples. Stable transduction of non-metastatic cells with each of the three miRNAs promoted metastatic properties in culture and increased liver colonization in vivo. Moreover, miR-424-3p and miR-1292 were associated with poor prognosis in human patients. A quantitative proteomic analysis of colorectal cancer cells transfected with miR-424-3p, miR-503, or miR-1292 identified alterations in 149, 129, or 121 proteins, respectively, with an extensive overlap of the target proteins of the three miRNAs. Importantly, down-regulation of two of these shared target proteins, CKB and UBA2, increased cell adhesion and proliferation in colorectal cancer cells. The capacity of distinct miRNAs to regulate the same mRNAs boosts the capacity of miRNAs to regulate cancer metastasis and underscores the necessity of targeting multiple miRNAs for effective cancer therapy. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Proteomics of industrial fungi: trends and insights for biotechnology.

PubMed

de Oliveira, José Miguel P Ferreira; de Graaff, Leo H

2011-01-01

Filamentous fungi are widely known for their industrial applications, namely, the production of food-processing enzymes and metabolites such as antibiotics and organic acids. In the past decade, the full genome sequencing of filamentous fungi increased the potential to predict encoded proteins enormously, namely, hydrolytic enzymes or proteins involved in the biosynthesis of metabolites of interest. The integration of genome sequence information with possible phenotypes requires, however, the knowledge of all the proteins in the cell in a system-wise manner, given by proteomics. This review summarises the progress of proteomics and its importance for the study of biotechnological processes in filamentous fungi. A major step forward in proteomics was to couple protein separation with high-resolution mass spectrometry, allowing accurate protein quantification. Despite the fact that most fungal proteomic studies have been focused on proteins from mycelial extracts, many proteins are related to processes which are compartmentalised in the fungal cell, e.g. β-lactam antibiotic production in the microbody. For the study of such processes, a targeted approach is required, e.g. by organelle proteomics. Typical workflows for sample preparation in fungal organelle proteomics are discussed, including homogenisation and sub-cellular fractionation. Finally, examples are presented of fungal organelle proteomic studies, which have enlarged the knowledge on areas of interest to biotechnology, such as protein secretion, energy production or antibiotic biosynthesis.

Proteomics of industrial fungi: trends and insights for biotechnology

PubMed Central

de Oliveira, José Miguel P. Ferreira

2010-01-01

Filamentous fungi are widely known for their industrial applications, namely, the production of food-processing enzymes and metabolites such as antibiotics and organic acids. In the past decade, the full genome sequencing of filamentous fungi increased the potential to predict encoded proteins enormously, namely, hydrolytic enzymes or proteins involved in the biosynthesis of metabolites of interest. The integration of genome sequence information with possible phenotypes requires, however, the knowledge of all the proteins in the cell in a system-wise manner, given by proteomics. This review summarises the progress of proteomics and its importance for the study of biotechnological processes in filamentous fungi. A major step forward in proteomics was to couple protein separation with high-resolution mass spectrometry, allowing accurate protein quantification. Despite the fact that most fungal proteomic studies have been focused on proteins from mycelial extracts, many proteins are related to processes which are compartmentalised in the fungal cell, e.g. β-lactam antibiotic production in the microbody. For the study of such processes, a targeted approach is required, e.g. by organelle proteomics. Typical workflows for sample preparation in fungal organelle proteomics are discussed, including homogenisation and sub-cellular fractionation. Finally, examples are presented of fungal organelle proteomic studies, which have enlarged the knowledge on areas of interest to biotechnology, such as protein secretion, energy production or antibiotic biosynthesis. PMID:20922379

Quantification of Flavin-containing Monooxygenases 1, 3, and 5 in Human Liver Microsomes by UPLC-MRM-Based Targeted Quantitative Proteomics and Its Application to the Study of Ontogeny.

PubMed

Chen, Yao; Zane, Nicole R; Thakker, Dhiren R; Wang, Michael Zhuo

2016-07-01

Flavin-containing monooxygenases (FMOs) have a significant role in the metabolism of small molecule pharmaceuticals. Among the five human FMOs, FMO1, FMO3, and FMO5 are the most relevant to hepatic drug metabolism. Although age-dependent hepatic protein expression, based on immunoquantification, has been reported previously for FMO1 and FMO3, there is very little information on hepatic FMO5 protein expression. To overcome the limitations of immunoquantification, an ultra-performance liquid chromatography (UPLC)-multiple reaction monitoring (MRM)-based targeted quantitative proteomic method was developed and optimized for the quantification of FMO1, FMO3, and FMO5 in human liver microsomes (HLM). A post-in silico product ion screening process was incorporated to verify LC-MRM detection of potential signature peptides before their synthesis. The developed method was validated by correlating marker substrate activity and protein expression in a panel of adult individual donor HLM (age 39-67 years). The mean (range) protein expression of FMO3 and FMO5 was 46 (26-65) pmol/mg HLM protein and 27 (11.5-49) pmol/mg HLM protein, respectively. To demonstrate quantification of FMO1, a panel of fetal individual donor HLM (gestational age 14-20 weeks) was analyzed. The mean (range) FMO1 protein expression was 7.0 (4.9-9.7) pmol/mg HLM protein. Furthermore, the ontogenetic protein expression of FMO5 was evaluated in fetal, pediatric, and adult HLM. The quantification of FMO proteins also was compared using two different calibration standards, recombinant proteins versus synthetic signature peptides, to assess the ratio between holoprotein versus total protein. In conclusion, a UPLC-MRM-based targeted quantitative proteomic method has been developed for the quantification of FMO enzymes in HLM. Copyright © 2016 by The American Society for Pharmacology and Experimental Therapeutics.

Quantification of Flavin-containing Monooxygenases 1, 3, and 5 in Human Liver Microsomes by UPLC-MRM-Based Targeted Quantitative Proteomics and Its Application to the Study of Ontogeny

PubMed Central

Chen, Yao; Zane, Nicole R.; Thakker, Dhiren R.

2016-01-01

Flavin-containing monooxygenases (FMOs) have a significant role in the metabolism of small molecule pharmaceuticals. Among the five human FMOs, FMO1, FMO3, and FMO5 are the most relevant to hepatic drug metabolism. Although age-dependent hepatic protein expression, based on immunoquantification, has been reported previously for FMO1 and FMO3, there is very little information on hepatic FMO5 protein expression. To overcome the limitations of immunoquantification, an ultra-performance liquid chromatography (UPLC)-multiple reaction monitoring (MRM)-based targeted quantitative proteomic method was developed and optimized for the quantification of FMO1, FMO3, and FMO5 in human liver microsomes (HLM). A post-in silico product ion screening process was incorporated to verify LC-MRM detection of potential signature peptides before their synthesis. The developed method was validated by correlating marker substrate activity and protein expression in a panel of adult individual donor HLM (age 39–67 years). The mean (range) protein expression of FMO3 and FMO5 was 46 (26–65) pmol/mg HLM protein and 27 (11.5–49) pmol/mg HLM protein, respectively. To demonstrate quantification of FMO1, a panel of fetal individual donor HLM (gestational age 14–20 weeks) was analyzed. The mean (range) FMO1 protein expression was 7.0 (4.9–9.7) pmol/mg HLM protein. Furthermore, the ontogenetic protein expression of FMO5 was evaluated in fetal, pediatric, and adult HLM. The quantification of FMO proteins also was compared using two different calibration standards, recombinant proteins versus synthetic signature peptides, to assess the ratio between holoprotein versus total protein. In conclusion, a UPLC-MRM-based targeted quantitative proteomic method has been developed for the quantification of FMO enzymes in HLM. PMID:26839369

Using Data Independent Acquisition (DIA) to Model High-responding Peptides for Targeted Proteomics Experiments*

PubMed Central

Searle, Brian C.; Egertson, Jarrett D.; Bollinger, James G.; Stergachis, Andrew B.; MacCoss, Michael J.

2015-01-01

Targeted mass spectrometry is an essential tool for detecting quantitative changes in low abundant proteins throughout the proteome. Although selected reaction monitoring (SRM) is the preferred method for quantifying peptides in complex samples, the process of designing SRM assays is laborious. Peptides have widely varying signal responses dictated by sequence-specific physiochemical properties; one major challenge is in selecting representative peptides to target as a proxy for protein abundance. Here we present PREGO, a software tool that predicts high-responding peptides for SRM experiments. PREGO predicts peptide responses with an artificial neural network trained using 11 minimally redundant, maximally relevant properties. Crucial to its success, PREGO is trained using fragment ion intensities of equimolar synthetic peptides extracted from data independent acquisition experiments. Because of similarities in instrumentation and the nature of data collection, relative peptide responses from data independent acquisition experiments are a suitable substitute for SRM experiments because they both make quantitative measurements from integrated fragment ion chromatograms. Using an SRM experiment containing 12,973 peptides from 724 synthetic proteins, PREGO exhibits a 40–85% improvement over previously published approaches at selecting high-responding peptides. These results also represent a dramatic improvement over the rules-based peptide selection approaches commonly used in the literature. PMID:26100116

A compound chimeric antigen receptor strategy for targeting multiple myeloma.

PubMed

Chen, K H; Wada, M; Pinz, K G; Liu, H; Shuai, X; Chen, X; Yan, L E; Petrov, J C; Salman, H; Senzel, L; Leung, E L H; Jiang, X; Ma, Y

2018-02-01

Current clinical outcomes using chimeric-antigen receptors (CARs) against multiple myeloma show promise in the eradication of bulk disease. However, these anti-BCMA (CD269) CARs observe relapse as a common phenomenon after treatment due to the reemergence of either antigen-positive or -negative cells. Hence, the development of improvements in CAR design to target antigen loss and increase effector cell persistency represents a critical need. Here, we report on the anti-tumor activity of a CAR T-cell possessing two complete and independent CAR receptors against the multiple myeloma antigens BCMA and CS1. We determined that the resulting compound CAR (cCAR) T-cell possesses consistent, potent and directed cytotoxicity against each target antigen population. Using multiple mouse models of myeloma and mixed cell populations, we are further able to show superior in vivo survival by directed cytotoxicity against multiple populations compared to a single-expressing CAR T-cell. These findings indicate that compound targeting of BCMA and CS1 on myeloma cells can potentially be an effective strategy for augmenting the response against myeloma bulk disease and for initiation of broader coverage CAR therapy.

SPS' Digest: the Swiss Proteomics Society selection of proteomics articles.

PubMed

Hoogland, Christine; Lion, Niels; Palagi, Patricia M; Sanchez, Jean-Charles; Tissot, Jean-Daniel

2005-08-01

Despite the consolidation of the specialized proteomics literature around a few established journals, such as Proteomics, Molecular and Cellular Proteomics, and the Journal of Proteome Research, a lot of information is still spread in many different publications from different fields, such as analytical sciences, MS, bioinformatics, etc. The purpose of SPS' Digest is to gather a selection of proteomics articles, to categorize them, and to make the list available on a periodic basis through a web page and email alerts.

Parasites, proteomes and systems: has Descartes' clock run out of time?

PubMed

Wastling, J M; Armstrong, S D; Krishna, R; Xia, D

2012-08-01

Systems biology aims to integrate multiple biological data types such as genomics, transcriptomics and proteomics across different levels of structure and scale; it represents an emerging paradigm in the scientific process which challenges the reductionism that has dominated biomedical research for hundreds of years. Systems biology will nevertheless only be successful if the technologies on which it is based are able to deliver the required type and quality of data. In this review we discuss how well positioned is proteomics to deliver the data necessary to support meaningful systems modelling in parasite biology. We summarise the current state of identification proteomics in parasites, but argue that a new generation of quantitative proteomics data is now needed to underpin effective systems modelling. We discuss the challenges faced to acquire more complete knowledge of protein post-translational modifications, protein turnover and protein-protein interactions in parasites. Finally we highlight the central role of proteome-informatics in ensuring that proteomics data is readily accessible to the user-community and can be translated and integrated with other relevant data types.

Parasites, proteomes and systems: has Descartes’ clock run out of time?

PubMed Central

WASTLING, J. M.; ARMSTRONG, S. D.; KRISHNA, R.; XIA, D.

2012-01-01

SUMMARY Systems biology aims to integrate multiple biological data types such as genomics, transcriptomics and proteomics across different levels of structure and scale; it represents an emerging paradigm in the scientific process which challenges the reductionism that has dominated biomedical research for hundreds of years. Systems biology will nevertheless only be successful if the technologies on which it is based are able to deliver the required type and quality of data. In this review we discuss how well positioned is proteomics to deliver the data necessary to support meaningful systems modelling in parasite biology. We summarise the current state of identification proteomics in parasites, but argue that a new generation of quantitative proteomics data is now needed to underpin effective systems modelling. We discuss the challenges faced to acquire more complete knowledge of protein post-translational modifications, protein turnover and protein-protein interactions in parasites. Finally we highlight the central role of proteome-informatics in ensuring that proteomics data is readily accessible to the user-community and can be translated and integrated with other relevant data types. PMID:22828391

Directed shotgun proteomics guided by saturated RNA-seq identifies a complete expressed prokaryotic proteome

PubMed Central

Omasits, Ulrich; Quebatte, Maxime; Stekhoven, Daniel J.; Fortes, Claudia; Roschitzki, Bernd; Robinson, Mark D.; Dehio, Christoph; Ahrens, Christian H.

2013-01-01

Prokaryotes, due to their moderate complexity, are particularly amenable to the comprehensive identification of the protein repertoire expressed under different conditions. We applied a generic strategy to identify a complete expressed prokaryotic proteome, which is based on the analysis of RNA and proteins extracted from matched samples. Saturated transcriptome profiling by RNA-seq provided an endpoint estimate of the protein-coding genes expressed under two conditions which mimic the interaction of Bartonella henselae with its mammalian host. Directed shotgun proteomics experiments were carried out on four subcellular fractions. By specifically targeting proteins which are short, basic, low abundant, and membrane localized, we could eliminate their initial underrepresentation compared to the estimated endpoint. A total of 1250 proteins were identified with an estimated false discovery rate below 1%. This represents 85% of all distinct annotated proteins and ∼90% of the expressed protein-coding genes. Genes that were detected at the transcript but not protein level, were found to be highly enriched in several genomic islands. Furthermore, genes that lacked an ortholog and a functional annotation were not detected at the protein level; these may represent examples of overprediction in genome annotations. A dramatic membrane proteome reorganization was observed, including differential regulation of autotransporters, adhesins, and hemin binding proteins. Particularly noteworthy was the complete membrane proteome coverage, which included expression of all members of the VirB/D4 type IV secretion system, a key virulence factor. PMID:23878158

Directed Shotgun Proteomics Guided by Saturated RNA-seq Identifies a Complete Expressed Prokaryotic Proteome

DOE Office of Scientific and Technical Information (OSTI.GOV)

Omasits, U.; Quebatte, Maxime; Stekhoven, Daniel J.

2013-11-01

Prokaryotes, due to their moderate complexity, are particularly amenable to the comprehensive identification of the protein repertoire expressed under different conditions. We applied a generic strategy to identify a complete expressed prokaryotic proteome, which is based on the analysis of RNA and proteins extracted from matched samples. Saturated transcriptome profiling by RNA-seq provided an endpoint estimate of the protein-coding genes expressed under two conditions which mimic the interaction of Bartonella henselae with its mammalian host. Directed shotgun proteomics experiments were carried out on four subcellular fractions. By specifically targeting proteins which are short, basic, low abundant, and membrane localized, wemore » could eliminate their initial underrepresentation compared to the estimated endpoint. A total of 1250 proteins were identified with an estimated false discovery rate below 1%. This represents 85% of all distinct annotated proteins and ~90% of the expressed protein-coding genes. Genes that were detected at the transcript but not protein level, were found to be highly enriched in several genomic islands. Furthermore, genes that lacked an ortholog and a functional annotation were not detected at the protein level; these may represent examples of overprediction in genome annotations. A dramatic membrane proteome reorganization was observed, including differential regulation of autotransporters, adhesins, and hemin binding proteins. Particularly noteworthy was the complete membrane proteome coverage, which included expression of all members of the VirB/D4 type IV secretion system, a key virulence factor.« less

Quantitative proteomics to study carbapenem resistance in Acinetobacter baumannii

PubMed Central

Tiwari, Vishvanath; Tiwari, Monalisa

2014-01-01

Acinetobacter baumannii is an opportunistic pathogen causing pneumonia, respiratory infections and urinary tract infections. The prevalence of this lethal pathogen increases gradually in the clinical setup where it can grow on artificial surfaces, utilize ethanol as a carbon source. Moreover it resists desiccation. Carbapenems, a β-lactam, are the most commonly prescribed drugs against A. baumannii. Resistance against carbapenem has emerged in Acinetobacter baumannii which can create significant health problems and is responsible for high morbidity and mortality. With the development of quantitative proteomics, a considerable progress has been made in the study of carbapenem resistance of Acinetobacter baumannii. Recent updates showed that quantitative proteomics has now emerged as an important tool to understand the carbapenem resistance mechanism in Acinetobacter baumannii. Present review also highlights the complementary nature of different quantitative proteomic methods used to study carbapenem resistance and suggests to combine multiple proteomic methods for understanding the response to antibiotics by Acinetobacter baumannii. PMID:25309531

Plasticity in the proteome of Emiliania huxleyi CCMP 1516 to extremes of light is highly targeted.

PubMed

McKew, Boyd A; Lefebvre, Stephane C; Achterberg, Eric P; Metodieva, Gergana; Raines, Christine A; Metodiev, Metodi V; Geider, Richard J

2013-10-01

Optimality principles are often applied in theoretical studies of microalgal ecophysiology to predict changes in allocation of resources to different metabolic pathways, and optimal acclimation is likely to involve changes in the proteome, which typically accounts for > 50% of cellular nitrogen (N). We tested the hypothesis that acclimation of the microalga Emiliania huxleyi CCMP 1516 to suboptimal vs supraoptimal light involves large changes in the proteome as cells rebalance the capacities to absorb light, fix CO2 , perform biosynthesis and resist photooxidative stress. Emiliania huxleyi was grown in nutrient-replete continuous culture at 30 (LL) and 1000 μmol photons m(-2) s(-1) (HL), and changes in the proteome were assessed by LC-MS/MS shotgun proteomics. Changes were most evident in proteins involved in the light reactions of photosynthesis; the relative abundance of photosystem I (PSI) and PSII proteins was 70% greater in LL, light-harvesting fucoxanthin-chlorophyll proteins (Lhcfs) were up to 500% greater in LL and photoprotective LI818 proteins were 300% greater in HL. The marked changes in the abundances of Lhcfs and LI818s, together with the limited plasticity in the bulk of the E. huxleyi proteome, probably reflect evolutionary pressures to provide energy to maintain metabolic capabilities in stochastic light environments encountered by this species in nature. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

Metformin targets multiple signaling pathways in cancer.

PubMed

Lei, Yong; Yi, Yanhua; Liu, Yang; Liu, Xia; Keller, Evan T; Qian, Chao-Nan; Zhang, Jian; Lu, Yi

2017-01-26

Metformin, an inexpensive and well-tolerated oral agent commonly used in the first-line treatment of type 2 diabetes, has become the focus of intense research as a candidate anticancer agent. Here, we discuss the potential of metformin in cancer therapeutics, particularly its functions in multiple signaling pathways, including AMP-activated protein kinase, mammalian target of rapamycin, insulin-like growth factor, c-Jun N-terminal kinase/mitogen-activated protein kinase (p38 MAPK), human epidermal growth factor receptor-2, and nuclear factor kappaB pathways. In addition, cutting-edge targeting of cancer stem cells by metformin is summarized.

Tracking Multiple Video Targets with an Improved GM-PHD Tracker

PubMed Central

Zhou, Xiaolong; Yu, Hui; Liu, Honghai; Li, Youfu

2015-01-01

Tracking multiple moving targets from a video plays an important role in many vision-based robotic applications. In this paper, we propose an improved Gaussian mixture probability hypothesis density (GM-PHD) tracker with weight penalization to effectively and accurately track multiple moving targets from a video. First, an entropy-based birth intensity estimation method is incorporated to eliminate the false positives caused by noisy video data. Then, a weight-penalized method with multi-feature fusion is proposed to accurately track the targets in close movement. For targets without occlusion, a weight matrix that contains all updated weights between the predicted target states and the measurements is constructed, and a simple, but effective method based on total weight and predicted target state is proposed to search the ambiguous weights in the weight matrix. The ambiguous weights are then penalized according to the fused target features that include spatial-colour appearance, histogram of oriented gradient and target area and further re-normalized to form a new weight matrix. With this new weight matrix, the tracker can correctly track the targets in close movement without occlusion. For targets with occlusion, a robust game-theoretical method is used. Finally, the experiments conducted on various video scenarios validate the effectiveness of the proposed penalization method and show the superior performance of our tracker over the state of the art. PMID:26633422

Serum proteome profiling in canine idiopathic dilated cardiomyopathy using TMT-based quantitative proteomics approach.

PubMed

Bilić, Petra; Guillemin, Nicolas; Kovačević, Alan; Beer Ljubić, Blanka; Jović, Ines; Galan, Asier; Eckersall, Peter David; Burchmore, Richard; Mrljak, Vladimir

2018-05-15

Idiopathic dilated cardiomyopathy (iDCM) is a primary myocardial disorder with an unknown aetiology, characterized by reduced contractility and ventricular dilation of the left or both ventricles. Naturally occurring canine iDCM was used herein to identify serum proteomic signature of the disease compared to the healthy state, providing an insight into underlying mechanisms and revealing proteins with biomarker potential. To achieve this, we used high-throughput label-based quantitative LC-MS/MS proteomics approach and bioinformatics analysis of the in silico inferred interactome protein network created from the initial list of differential proteins. To complement the proteomic analysis, serum biochemical parameters and levels of know biomarkers of cardiac function were measured. Several proteins with biomarker potential were identified, such as inter-alpha-trypsin inhibitor heavy chain H4, microfibril-associated glycoprotein 4 and apolipoprotein A-IV, which were validated using an independent method (Western blotting) and showed high specificity and sensitivity according to the receiver operating characteristic curve analysis. Bioinformatics analysis revealed involvement of different pathways in iDCM, such as complement cascade activation, lipoprotein particles dynamics, elastic fibre formation, GPCR signalling and respiratory electron transport chain. Idiopathic dilated cardiomyopathy is a severe primary myocardial disease of unknown cause, affecting both humans and dogs. This study is a contribution to the canine heart disease research by means of proteomic and bioinformatic state of the art analyses, following similar approach in human iDCM research. Importantly, we used serum as non-invasive and easily accessible biological source of information and contributed to the scarce data on biofluid proteome research on this topic. Bioinformatics analysis revealed biological pathways modulated in canine iDCM with potential of further targeted research. Also, several

Proteomics in Heart Failure: Top-down or Bottom-up?

PubMed Central

Gregorich, Zachery R.; Chang, Ying-Hua; Ge, Ying

2014-01-01

Summary The pathophysiology of heart failure (HF) is diverse, owing to multiple etiologies and aberrations in a number of cellular processes. Therefore, it is essential to understand how defects in the molecular pathways that mediate cellular responses to internal and external stressors function as a system to drive the HF phenotype. Mass spectrometry (MS)-based proteomics strategies have great potential for advancing our understanding of disease mechanisms at the systems level because proteins are the effector molecules for all cell functions and, thus, are directly responsible for determining cell phenotype. Two MS-based proteomics strategies exist: peptide-based bottom-up and protein-based top-down proteomics—each with its own unique strengths and weaknesses for interrogating the proteome. In this review, we will discuss the advantages and disadvantages of bottom-up and top-down MS for protein identification, quantification, and the analysis of post-translational modifications, as well as highlight how both of these strategies have contributed to our understanding of the molecular and cellular mechanisms underlying HF. Additionally, the challenges associated with both proteomics approaches will be discussed and insights will be offered regarding the future of MS-based proteomics in HF research. PMID:24619480

Preprocessing and Analysis of LC-MS-Based Proteomic Data

PubMed Central

Tsai, Tsung-Heng; Wang, Minkun; Ressom, Habtom W.

2016-01-01

Liquid chromatography coupled with mass spectrometry (LC-MS) has been widely used for profiling protein expression levels. This chapter is focused on LC-MS data preprocessing, which is a crucial step in the analysis of LC-MS based proteomics. We provide a high-level overview, highlight associated challenges, and present a step-by-step example for analysis of data from LC-MS based untargeted proteomic study. Furthermore, key procedures and relevant issues with the subsequent analysis by multiple reaction monitoring (MRM) are discussed. PMID:26519169

Integrative proteomics, genomics, and translational immunology approaches reveal mutated forms of Proteolipid Protein 1 (PLP1) and mutant-specific immune response in multiple sclerosis.

PubMed

Qendro, Veneta; Bugos, Grace A; Lundgren, Debbie H; Glynn, John; Han, May H; Han, David K

2017-03-01

In order to gain mechanistic insights into multiple sclerosis (MS) pathogenesis, we utilized a multi-dimensional approach to test the hypothesis that mutations in myelin proteins lead to immune activation and central nervous system autoimmunity in MS. Mass spectrometry-based proteomic analysis of human MS brain lesions revealed seven unique mutations of PLP1; a key myelin protein that is known to be destroyed in MS. Surprisingly, in-depth genomic analysis of two MS patients at the genomic DNA and mRNA confirmed mutated PLP1 in RNA, but not in the genomic DNA. Quantification of wild type and mutant PLP RNA levels by qPCR further validated the presence of mutant PLP RNA in the MS patients. To seek evidence linking mutations in abundant myelin proteins and immune-mediated destruction of myelin, specific immune response against mutant PLP1 in MS patients was examined. Thus, we have designed paired, wild type and mutant peptide microarrays, and examined antibody response to multiple mutated PLP1 in sera from MS patients. Consistent with the idea of different patients exhibiting unique mutation profiles, we found that 13 out of 20 MS patients showed antibody responses against specific but not against all the mutant-PLP1 peptides. Interestingly, we found mutant PLP-directed antibody response against specific mutant peptides in the sera of pre-MS controls. The results from integrative proteomic, genomic, and immune analyses reveal a possible mechanism of mutation-driven pathogenesis in human MS. The study also highlights the need for integrative genomic and proteomic analyses for uncovering pathogenic mechanisms of human diseases. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimized approaches for quantification of drug transporters in tissues and cells by MRM proteomics.

PubMed

Prasad, Bhagwat; Unadkat, Jashvant D

2014-07-01

Drug transporter expression in tissues (in vivo) usually differs from that in cell lines used to measure transporter activity (in vitro). Therefore, quantification of transporter expression in tissues and cell lines is important to develop scaling factor for in vitro to in vivo extrapolation (IVIVE) of transporter-mediated drug disposition. Since traditional immunoquantification methods are semiquantitative, targeted proteomics is now emerging as a superior method to quantify proteins, including membrane transporters. This superiority is derived from the selectivity, precision, accuracy, and speed of analysis by liquid chromatography tandem mass spectrometry (LC-MS/MS) in multiple reaction monitoring (MRM) mode. Moreover, LC-MS/MS proteomics has broader applicability because it does not require selective antibodies for individual proteins. There are a number of recent research and review papers that discuss the use of LC-MS/MS for transporter quantification. Here, we have compiled from the literature various elements of MRM proteomics to provide a comprehensive systematic strategy to quantify drug transporters. This review emphasizes practical aspects and challenges in surrogate peptide selection, peptide qualification, peptide synthesis and characterization, membrane protein isolation, protein digestion, sample preparation, LC-MS/MS parameter optimization, method validation, and sample analysis. In particular, bioinformatic tools used in method development and sample analysis are discussed in detail. Various pre-analytical and analytical sources of variability that should be considered during transporter quantification are highlighted. All these steps are illustrated using P-glycoprotein (P-gp) as a case example. Greater use of quantitative transporter proteomics will lead to a better understanding of the role of drug transporters in drug disposition.

Mitochondrial-targeted catalase is good for the old mouse proteome, but not for the young: 'reverse' antagonistic pleiotropy?

PubMed

Basisty, Nathan; Dai, Dao-Fu; Gagnidze, Arni; Gitari, Lemuel; Fredrickson, Jeanne; Maina, Yvonne; Beyer, Richard P; Emond, Mary J; Hsieh, Edward J; MacCoss, Michael J; Martin, George M; Rabinovitch, Peter S

2016-08-01

Reactive oxygen species (ROS) are highly reactive oxygen-containing molecules associated with aging and a broad spectrum of pathologies. We have previously shown that transgenic expression of the antioxidant enzyme catalase targeted to the mitochondria (mCAT) in mice reduces ROS, attenuates age-related disease, and increases lifespan. However, it has been increasingly recognized that ROS also has beneficial roles in signaling, hormesis, stress response, and immunity. We therefore hypothesized that mCAT might be beneficial only when ROS approaches pathological levels in older age and might not be advantageous at a younger age when basal ROS is low. We analyzed abundance and turnover of the global proteome in hearts and livers of young (4 month) and old (20 month) mCAT and wild-type (WT) mice. In old hearts and livers of WT mice, protein half-lives were reduced compared to young, while in mCAT mice the reverse was observed; the longest half-lives were seen in old mCAT mice and the shortest in young mCAT. Protein abundance of old mCAT hearts recapitulated a more youthful proteomic expression profile (P-value < 0.01). However, young mCAT mice partially phenocopied the older wild-type proteome (P-value < 0.01). Age strongly interacts with mCAT, consistent with antagonistic pleiotropy in the reverse of the typical direction. These findings underscore the contrasting roles of ROS in young vs. old mice and indicate the need for better understanding of the interaction between dose and age in assessing the efficacy of therapeutic interventions in aging, including mitochondrial antioxidants. © 2016 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.

18O-labeled proteome reference as global internal standards for targeted quantification by selected reaction monitoring-mass spectrometry.

PubMed

Kim, Jong-Seo; Fillmore, Thomas L; Liu, Tao; Robinson, Errol; Hossain, Mahmud; Champion, Boyd L; Moore, Ronald J; Camp, David G; Smith, Richard D; Qian, Wei-Jun

2011-12-01

Selected reaction monitoring (SRM)-MS is an emerging technology for high throughput targeted protein quantification and verification in biomarker discovery studies; however, the cost associated with the application of stable isotope-labeled synthetic peptides as internal standards can be prohibitive for screening a large number of candidate proteins as often required in the preverification phase of discovery studies. Herein we present a proof of concept study using an (18)O-labeled proteome reference as global internal standards (GIS) for SRM-based relative quantification. The (18)O-labeled proteome reference (or GIS) can be readily prepared and contains a heavy isotope ((18)O)-labeled internal standard for every possible tryptic peptide. Our results showed that the percentage of heavy isotope ((18)O) incorporation applying an improved protocol was >99.5% for most peptides investigated. The accuracy, reproducibility, and linear dynamic range of quantification were further assessed based on known ratios of standard proteins spiked into the labeled mouse plasma reference. Reliable quantification was observed with high reproducibility (i.e. coefficient of variance <10%) for analyte concentrations that were set at 100-fold higher or lower than those of the GIS based on the light ((16)O)/heavy ((18)O) peak area ratios. The utility of (18)O-labeled GIS was further illustrated by accurate relative quantification of 45 major human plasma proteins. Moreover, quantification of the concentrations of C-reactive protein and prostate-specific antigen was illustrated by coupling the GIS with standard additions of purified protein standards. Collectively, our results demonstrated that the use of (18)O-labeled proteome reference as GIS provides a convenient, low cost, and effective strategy for relative quantification of a large number of candidate proteins in biological or clinical samples using SRM.

Incorporating multiple secondary targets into learning trials for individuals with autism spectrum disorder.

PubMed

Nottingham, Casey L; Vladescu, Jason C; Kodak, Tiffany; Kisamore, April N

2017-07-01

The current study examined the outcome of presenting multiple secondary targets in learning trials for individuals with autism spectrum disorder. We compared conditions in which (a) a secondary target was presented in the antecedent and consequence of trials, (b) two secondary targets were presented in the consequence of trials, (c) one secondary target was presented in the consequence of each trial, and (d) no additional targets were presented trials. The participants acquired the majority of secondary targets. Presenting one or multiple secondary targets per trial, regardless of the location of these secondary targets, increased the efficiency of instruction in comparison to a condition with no secondary target. © 2017 Society for the Experimental Analysis of Behavior.

Optoelectronic System Measures Distances to Multiple Targets

NASA Technical Reports Server (NTRS)

Liebe, Carl Christian; Abramovici, Alexander; Bartman, Randall; Chapsky, Jacob; Schmalz, John; Coste, Keith; Litty, Edward; Lam, Raymond; Jerebets, Sergei

2007-01-01

An optoelectronic metrology apparatus now at the laboratory-prototype stage of development is intended to repeatedly determine distances of as much as several hundred meters, at submillimeter accuracy, to multiple targets in rapid succession. The underlying concept of optoelectronic apparatuses that can measure distances to targets is not new; such apparatuses are commonly used in general surveying and machining. However, until now such apparatuses have been, variously, constrained to (1) a single target or (2) multiple targets with a low update rate and a requirement for some a priori knowledge of target geometry. When fully developed, the present apparatus would enable measurement of distances to more than 50 targets at an update rate greater than 10 Hz, without a requirement for a priori knowledge of target geometry. The apparatus (see figure) includes a laser ranging unit (LRU) that includes an electronic camera (photo receiver), the field of view of which contains all relevant targets. Each target, mounted at a fiducial position on an object of interest, consists of a small lens at the output end of an optical fiber that extends from the object of interest back to the LRU. For each target and its optical fiber, there is a dedicated laser that is used to illuminate the target via the optical fiber. The targets are illuminated, one at a time, with laser light that is modulated at a frequency of 10.01 MHz. The modulated laser light is emitted by the target, from where it returns to the camera (photodetector), where it is detected. Both the outgoing and incoming 10.01-MHz laser signals are mixed with a 10-MHz local-oscillator to obtain beat notes at 10 kHz, and the difference between the phases of the beat notes is measured by a phase meter. This phase difference serves as a measure of the total length of the path traveled by light going out through the optical fiber and returning to the camera (photodetector) through free space. Because the portion of the path

Improved False Discovery Rate Estimation Procedure for Shotgun Proteomics.

PubMed

Keich, Uri; Kertesz-Farkas, Attila; Noble, William Stafford

2015-08-07

Interpreting the potentially vast number of hypotheses generated by a shotgun proteomics experiment requires a valid and accurate procedure for assigning statistical confidence estimates to identified tandem mass spectra. Despite the crucial role such procedures play in most high-throughput proteomics experiments, the scientific literature has not reached a consensus about the best confidence estimation methodology. In this work, we evaluate, using theoretical and empirical analysis, four previously proposed protocols for estimating the false discovery rate (FDR) associated with a set of identified tandem mass spectra: two variants of the target-decoy competition protocol (TDC) of Elias and Gygi and two variants of the separate target-decoy search protocol of Käll et al. Our analysis reveals significant biases in the two separate target-decoy search protocols. Moreover, the one TDC protocol that provides an unbiased FDR estimate among the target PSMs does so at the cost of forfeiting a random subset of high-scoring spectrum identifications. We therefore propose the mix-max procedure to provide unbiased, accurate FDR estimates in the presence of well-calibrated scores. The method avoids biases associated with the two separate target-decoy search protocols and also avoids the propensity for target-decoy competition to discard a random subset of high-scoring target identifications.

Improved False Discovery Rate Estimation Procedure for Shotgun Proteomics

PubMed Central

2016-01-01

Interpreting the potentially vast number of hypotheses generated by a shotgun proteomics experiment requires a valid and accurate procedure for assigning statistical confidence estimates to identified tandem mass spectra. Despite the crucial role such procedures play in most high-throughput proteomics experiments, the scientific literature has not reached a consensus about the best confidence estimation methodology. In this work, we evaluate, using theoretical and empirical analysis, four previously proposed protocols for estimating the false discovery rate (FDR) associated with a set of identified tandem mass spectra: two variants of the target-decoy competition protocol (TDC) of Elias and Gygi and two variants of the separate target-decoy search protocol of Käll et al. Our analysis reveals significant biases in the two separate target-decoy search protocols. Moreover, the one TDC protocol that provides an unbiased FDR estimate among the target PSMs does so at the cost of forfeiting a random subset of high-scoring spectrum identifications. We therefore propose the mix-max procedure to provide unbiased, accurate FDR estimates in the presence of well-calibrated scores. The method avoids biases associated with the two separate target-decoy search protocols and also avoids the propensity for target-decoy competition to discard a random subset of high-scoring target identifications. PMID:26152888

Redox proteomics and drug development.

PubMed

D'Alessandro, Angelo; Rinalducci, Sara; Zolla, Lello

2011-11-18

As alterations of the redox homeostasis lie at the root of many pathophysiological processes in human health, redox proteomics holds the promise to shed further light on fundamental biological processes. In this review, the mechanisms of reactive oxygen species (ROS) and reactive nitrogen species (RNS) production are reviewed, mainly addressing those chemical phenomena which have already been associated with pathological conditions (of the central nervous system, cardiovascular system, or simply related to aging and altered-cell cycle regulation). From Alzheimer's to Parkinson's and Hungtinton's disease, from ageing to cancer, oxidative stress (OS) appears to represent a common trait in so many relevant biological aspects of human health, that further investments in the field of redox proteomics ought to be mandatory. For the foreseeable future, redox proteomics will likely play a pivotal role in the quest for new therapeutical targets and their validation, in the process of determining OS-triggered cellular alteration upon drug treatments and thus in the very heart of the design and testing of new drugs and their metabolites against those pathologies relying on altered redox homeostasis. Copyright © 2011 Elsevier B.V. All rights reserved.

A proteomic approach to obesity and type 2 diabetes.

PubMed

López-Villar, Elena; Martos-Moreno, Gabriel Á; Chowen, Julie A; Okada, Shigeru; Kopchick, John J; Argente, Jesús

2015-07-01

The incidence of obesity and type diabetes 2 has increased dramatically resulting in an increased interest in its biomedical relevance. However, the mechanisms that trigger the development of diabetes type 2 in obese patients remain largely unknown. Scientific, clinical and pharmaceutical communities are dedicating vast resources to unravel this issue by applying different omics tools. During the last decade, the advances in proteomic approaches and the Human Proteome Organization have opened and are opening a new door that may be helpful in the identification of patients at risk and to improve current therapies. Here, we briefly review some of the advances in our understanding of type 2 diabetes that have occurred through the application of proteomics. We also review, in detail, the current improvements in proteomic methodologies and new strategies that could be employed to further advance our understanding of this pathology. By applying these new proteomic advances, novel therapeutic and/or diagnostic protein targets will be discovered in the obesity/Type 2 diabetes area. © 2015 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

Global profiling of lysine reactivity and ligandability in the human proteome

NASA Astrophysics Data System (ADS)

Hacker, Stephan M.; Backus, Keriann M.; Lazear, Michael R.; Forli, Stefano; Correia, Bruno E.; Cravatt, Benjamin F.

2017-12-01

Nucleophilic amino acids make important contributions to protein function, including performing key roles in catalysis and serving as sites for post-translational modification. Electrophilic groups that target amino-acid nucleophiles have been used to create covalent ligands and drugs, but have, so far, been mainly limited to cysteine and serine. Here, we report a chemical proteomic platform for the global and quantitative analysis of lysine residues in native biological systems. We have quantified, in total, more than 9,000 lysines in human cell proteomes and have identified several hundred residues with heightened reactivity that are enriched at protein functional sites and can frequently be targeted by electrophilic small molecules. We have also discovered lysine-reactive fragment electrophiles that inhibit enzymes by active site and allosteric mechanisms, as well as disrupt protein-protein interactions in transcriptional regulatory complexes, emphasizing the broad potential and diverse functional consequences of liganding lysine residues throughout the human proteome.

Global profiling of lysine reactivity and ligandability in the human proteome.

PubMed

Hacker, Stephan M; Backus, Keriann M; Lazear, Michael R; Forli, Stefano; Correia, Bruno E; Cravatt, Benjamin F

2017-12-01

Nucleophilic amino acids make important contributions to protein function, including performing key roles in catalysis and serving as sites for post-translational modification. Electrophilic groups that target amino-acid nucleophiles have been used to create covalent ligands and drugs, but have, so far, been mainly limited to cysteine and serine. Here, we report a chemical proteomic platform for the global and quantitative analysis of lysine residues in native biological systems. We have quantified, in total, more than 9,000 lysines in human cell proteomes and have identified several hundred residues with heightened reactivity that are enriched at protein functional sites and can frequently be targeted by electrophilic small molecules. We have also discovered lysine-reactive fragment electrophiles that inhibit enzymes by active site and allosteric mechanisms, as well as disrupt protein-protein interactions in transcriptional regulatory complexes, emphasizing the broad potential and diverse functional consequences of liganding lysine residues throughout the human proteome.

Data Pre-Processing for Label-Free Multiple Reaction Monitoring (MRM) Experiments

PubMed Central

Chung, Lisa M.; Colangelo, Christopher M.; Zhao, Hongyu

2014-01-01

Multiple Reaction Monitoring (MRM) conducted on a triple quadrupole mass spectrometer allows researchers to quantify the expression levels of a set of target proteins. Each protein is often characterized by several unique peptides that can be detected by monitoring predetermined fragment ions, called transitions, for each peptide. Concatenating large numbers of MRM transitions into a single assay enables simultaneous quantification of hundreds of peptides and proteins. In recognition of the important role that MRM can play in hypothesis-driven research and its increasing impact on clinical proteomics, targeted proteomics such as MRM was recently selected as the Nature Method of the Year. However, there are many challenges in MRM applications, especially data pre‑processing where many steps still rely on manual inspection of each observation in practice. In this paper, we discuss an analysis pipeline to automate MRM data pre‑processing. This pipeline includes data quality assessment across replicated samples, outlier detection, identification of inaccurate transitions, and data normalization. We demonstrate the utility of our pipeline through its applications to several real MRM data sets. PMID:24905083

Data Pre-Processing for Label-Free Multiple Reaction Monitoring (MRM) Experiments.

PubMed

Chung, Lisa M; Colangelo, Christopher M; Zhao, Hongyu

2014-06-05

Multiple Reaction Monitoring (MRM) conducted on a triple quadrupole mass spectrometer allows researchers to quantify the expression levels of a set of target proteins. Each protein is often characterized by several unique peptides that can be detected by monitoring predetermined fragment ions, called transitions, for each peptide. Concatenating large numbers of MRM transitions into a single assay enables simultaneous quantification of hundreds of peptides and proteins. In recognition of the important role that MRM can play in hypothesis-driven research and its increasing impact on clinical proteomics, targeted proteomics such as MRM was recently selected as the Nature Method of the Year. However, there are many challenges in MRM applications, especially data pre‑processing where many steps still rely on manual inspection of each observation in practice. In this paper, we discuss an analysis pipeline to automate MRM data pre‑processing. This pipeline includes data quality assessment across replicated samples, outlier detection, identification of inaccurate transitions, and data normalization. We demonstrate the utility of our pipeline through its applications to several real MRM data sets.

A covariant multiple scattering series for elastic projectile-target scattering

NASA Technical Reports Server (NTRS)

Gross, Franz; Maung-Maung, Khin

1989-01-01

A covariant formulation of the multiple scattering series for the optical potential is presented. The case of a scalar nucleon interacting with a spin zero isospin zero A-body target through meson exchange, is considered. It is shown that a covariant equation for the projectile-target t-matrix can be obtained which sums the ladder and crossed ladder diagrams efficiently. From this equation, a multiple scattering series for the optical potential is derived, and it is shown that in the impulse approximation, the two-body t-matrix associated with the first order optical potential is the one in which one particle is kept on mass-shell. The meaning of various terms in the multiple scattering series is given. The construction of the first-order optical potential for elastic scattering calculations is described.

Quantum partial search for uneven distribution of multiple target items

NASA Astrophysics Data System (ADS)

Zhang, Kun; Korepin, Vladimir

2018-06-01

Quantum partial search algorithm is an approximate search. It aims to find a target block (which has the target items). It runs a little faster than full Grover search. In this paper, we consider quantum partial search algorithm for multiple target items unevenly distributed in a database (target blocks have different number of target items). The algorithm we describe can locate one of the target blocks. Efficiency of the algorithm is measured by number of queries to the oracle. We optimize the algorithm in order to improve efficiency. By perturbation method, we find that the algorithm runs the fastest when target items are evenly distributed in database.

Quantitative Proteomics via High Resolution MS Quantification: Capabilities and Limitations

PubMed Central

Higgs, Richard E.; Butler, Jon P.; Han, Bomie; Knierman, Michael D.

2013-01-01

Recent improvements in the mass accuracy and resolution of mass spectrometers have led to renewed interest in label-free quantification using data from the primary mass spectrum (MS1) acquired from data-dependent proteomics experiments. The capacity for higher specificity quantification of peptides from samples enriched for proteins of biological interest offers distinct advantages for hypothesis generating experiments relative to immunoassay detection methods or prespecified peptide ions measured by multiple reaction monitoring (MRM) approaches. Here we describe an evaluation of different methods to post-process peptide level quantification information to support protein level inference. We characterize the methods by examining their ability to recover a known dilution of a standard protein in background matrices of varying complexity. Additionally, the MS1 quantification results are compared to a standard, targeted, MRM approach on the same samples under equivalent instrument conditions. We show the existence of multiple peptides with MS1 quantification sensitivity similar to the best MRM peptides for each of the background matrices studied. Based on these results we provide recommendations on preferred approaches to leveraging quantitative measurements of multiple peptides to improve protein level inference. PMID:23710359

Extending the Limits of Quantitative Proteome Profiling with Data-Independent Acquisition and Application to Acetaminophen-Treated Three-Dimensional Liver Microtissues*

PubMed Central

Bruderer, Roland; Bernhardt, Oliver M.; Gandhi, Tejas; Miladinović, Saša M.; Cheng, Lin-Yang; Messner, Simon; Ehrenberger, Tobias; Zanotelli, Vito; Butscheid, Yulia; Escher, Claudia; Vitek, Olga; Rinner, Oliver; Reiter, Lukas

2015-01-01

The data-independent acquisition (DIA) approach has recently been introduced as a novel mass spectrometric method that promises to combine the high content aspect of shotgun proteomics with the reproducibility and precision of selected reaction monitoring. Here, we evaluate, whether SWATH-MS type DIA effectively translates into a better protein profiling as compared with the established shotgun proteomics. We implemented a novel DIA method on the widely used Orbitrap platform and used retention-time-normalized (iRT) spectral libraries for targeted data extraction using Spectronaut. We call this combination hyper reaction monitoring (HRM). Using a controlled sample set, we show that HRM outperformed shotgun proteomics both in the number of consistently identified peptides across multiple measurements and quantification of differentially abundant proteins. The reproducibility of HRM in peptide detection was above 98%, resulting in quasi complete data sets compared with 49% of shotgun proteomics. Utilizing HRM, we profiled acetaminophen (APAP)1-treated three-dimensional human liver microtissues. An early onset of relevant proteome changes was revealed at subtoxic doses of APAP. Further, we detected and quantified for the first time human NAPQI-protein adducts that might be relevant for the toxicity of APAP. The adducts were identified on four mitochondrial oxidative stress related proteins (GATM, PARK7, PRDX6, and VDAC2) and two other proteins (ANXA2 and FTCD). Our findings imply that DIA should be the preferred method for quantitative protein profiling. PMID:25724911

Global proteomics profiling improves drug sensitivity prediction: results from a multi-omics, pan-cancer modeling approach.

PubMed

Ali, Mehreen; Khan, Suleiman A; Wennerberg, Krister; Aittokallio, Tero

2018-04-15

Proteomics profiling is increasingly being used for molecular stratification of cancer patients and cell-line panels. However, systematic assessment of the predictive power of large-scale proteomic technologies across various drug classes and cancer types is currently lacking. To that end, we carried out the first pan-cancer, multi-omics comparative analysis of the relative performance of two proteomic technologies, targeted reverse phase protein array (RPPA) and global mass spectrometry (MS), in terms of their accuracy for predicting the sensitivity of cancer cells to both cytotoxic chemotherapeutics and molecularly targeted anticancer compounds. Our results in two cell-line panels demonstrate how MS profiling improves drug response predictions beyond that of the RPPA or the other omics profiles when used alone. However, frequent missing MS data values complicate its use in predictive modeling and required additional filtering, such as focusing on completely measured or known oncoproteins, to obtain maximal predictive performance. Rather strikingly, the two proteomics profiles provided complementary predictive signal both for the cytotoxic and targeted compounds. Further, information about the cellular-abundance of primary target proteins was found critical for predicting the response of targeted compounds, although the non-target features also contributed significantly to the predictive power. The clinical relevance of the selected protein markers was confirmed in cancer patient data. These results provide novel insights into the relative performance and optimal use of the widely applied proteomic technologies, MS and RPPA, which should prove useful in translational applications, such as defining the best combination of omics technologies and marker panels for understanding and predicting drug sensitivities in cancer patients. Processed datasets, R as well as Matlab implementations of the methods are available at https://github.com/mehr-een/bemkl-rbps. mehreen

Defining the wheat gluten peptide fingerprint via a discovery and targeted proteomics approach.

PubMed

Martínez-Esteso, María José; Nørgaard, Jørgen; Brohée, Marcel; Haraszi, Reka; Maquet, Alain; O'Connor, Gavin

2016-09-16

Accurate, reliable and sensitive detection methods for gluten are required to support current EU regulations. The enforcement of legislative levels requires that measurement results are comparable over time and between methods. This is not a trivial task for gluten which comprises a large number of protein targets. This paper describes a strategy for defining a set of specific analytical targets for wheat gluten. A comprehensive proteomic approach was applied by fractionating wheat gluten using RP-HPLC (reversed phase high performance liquid chromatography) followed by a multi-enzymatic digestion (LysC, trypsin and chymotrypsin) with subsequent mass spectrometric analysis. This approach identified 434 peptide sequences from gluten. Peptides were grouped based on two criteria: unique to a single gluten protein sequence; contained known immunogenic and toxic sequences in the context of coeliac disease. An LC-MS/MS method based on selected reaction monitoring (SRM) was developed on a triple quadrupole mass spectrometer for the specific detection of the target peptides. The SRM based screening approach was applied to gluten containing cereals (wheat, rye, barley and oats) and non-gluten containing flours (corn, soy and rice). A unique set of wheat gluten marker peptides were identified and are proposed as wheat specific markers. The measurement of gluten in processed food products in support of regulatory limits is performed routinely. Mass spectrometry is emerging as a viable alternative to ELISA based methods. Here we outline a set of peptide markers that are representative of gluten and consider the end user's needs in protecting those with coeliac disease. The approach taken has been applied to wheat but can be easily extended to include other species potentially enabling the MS quantification of different gluten containing species from the identified markers. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Overview of proteomics studies in obstructive sleep apnea

PubMed Central

Feliciano, Amélia; Torres, Vukosava Milic; Vaz, Fátima; Carvalho, Ana Sofia; Matthiesen, Rune; Pinto, Paula; Malhotra, Atul; Bárbara, Cristina; Penque, Deborah

2015-01-01

Obstructive sleep apnea (OSA) is an underdiagnosed common public health concern causing deleterious effects on metabolic and cardiovascular health. Although much has been learned regarding the pathophysiology and consequences of OSA in the past decades, the molecular mechanisms associated with such processes remain poorly defined. The advanced high-throughput proteomics-based technologies have become a fundamental approach for identifying novel disease mediators as potential diagnostic and therapeutic targets for many diseases, including OSA. Here, we briefly review OSA pathophysiology and the technological advances in proteomics and the first results of its application to address critical issues in the OSA field. PMID:25770042

Targeted Proteomics Predicts a Sustained Complete-Response after Transarterial Chemoembolization and Clinical Outcomes in Patients with Hepatocellular Carcinoma: A Prospective Cohort Study.

PubMed

Yu, Su Jong; Kim, Hyunsoo; Min, Hophil; Sohn, Areum; Cho, Young Youn; Yoo, Jeong-Ju; Lee, Dong Hyeon; Cho, Eun Ju; Lee, Jeong-Hoon; Gim, Jungsoo; Park, Taesung; Kim, Yoon Jun; Kim, Chung Yong; Yoon, Jung-Hwan; Kim, Youngsoo

2017-03-03

This study was aimed to identify blood-based biomarkers to predict a sustained complete response (CR) after transarterial chemoembolization (TACE) using targeted proteomics. Consecutive patients with HCC who had undergone TACE were prospectively enrolled (training (n = 100) and validation set (n = 80)). Serum samples were obtained before and 6 months after TACE. Treatment responses were evaluated using the modified Response Evaluation Criteria in Solid Tumors (mRECIST). In the training set, the MRM-MS assay identified five marker candidate proteins (LRG1, APCS, BCHE, C7, and FCN3). When this five-marker panel was combined with the best-performing clinical variables (tumor number, baseline PIVKA, and baseline AFP), the resulting ensemble model had the highest area under the receiver operating curve (AUROC) value in predicting a sustained CR after TACE in the training and validation sets (0.881 and 0.813, respectively). Furthermore, the ensemble model was an independent predictor of rapid progression (hazard ratio (HR), 2.889; 95% confidence interval (CI), 1.612-5.178; P value < 0.001) and overall an unfavorable survival rate (HR, 1.985; 95% CI, 1.024-3.848; P value = 0.042) in the entire population by multivariate analysis. Targeted proteomics-based ensemble model can predict clinical outcomes after TACE. Therefore, this model can aid in determining the best candidates for TACE and the need for adjuvant therapy.

Proteomics Analysis of the Nucleolus in Adenovirus-infected Cells

PubMed Central

Lam, Yun W.; Evans, Vanessa C.; Heesom, Kate J.; Lamond, Angus I.; Matthews, David A.

2010-01-01

Adenoviruses replicate primarily in the host cell nucleus, and it is well established that adenovirus infection affects the structure and function of host cell nucleoli in addition to coding for a number of nucleolar targeted viral proteins. Here we used unbiased proteomics methods, including high throughput mass spectrometry coupled with stable isotope labeling by amino acids in cell culture (SILAC) and traditional two-dimensional gel electrophoresis, to identify quantitative changes in the protein composition of the nucleolus during adenovirus infection. Two-dimensional gel analysis revealed changes in six proteins. By contrast, SILAC-based approaches identified 351 proteins with 24 proteins showing at least a 2-fold change after infection. Of those, four were previously reported to have aberrant localization and/or functional relevance during adenovirus infection. In total, 15 proteins identified as changing in amount by proteomics methods were examined in infected cells using confocal microscopy. Eleven of these proteins showed altered patterns of localization in adenovirus-infected cells. Comparing our data with the effects of actinomycin D on the nucleolar proteome revealed that adenovirus infection apparently specifically targets a relatively small subset of nucleolar antigens at the time point examined. PMID:19812395

Proteomics analysis of the nucleolus in adenovirus-infected cells.

PubMed

Lam, Yun W; Evans, Vanessa C; Heesom, Kate J; Lamond, Angus I; Matthews, David A

2010-01-01

Adenoviruses replicate primarily in the host cell nucleus, and it is well established that adenovirus infection affects the structure and function of host cell nucleoli in addition to coding for a number of nucleolar targeted viral proteins. Here we used unbiased proteomics methods, including high throughput mass spectrometry coupled with stable isotope labeling by amino acids in cell culture (SILAC) and traditional two-dimensional gel electrophoresis, to identify quantitative changes in the protein composition of the nucleolus during adenovirus infection. Two-dimensional gel analysis revealed changes in six proteins. By contrast, SILAC-based approaches identified 351 proteins with 24 proteins showing at least a 2-fold change after infection. Of those, four were previously reported to have aberrant localization and/or functional relevance during adenovirus infection. In total, 15 proteins identified as changing in amount by proteomics methods were examined in infected cells using confocal microscopy. Eleven of these proteins showed altered patterns of localization in adenovirus-infected cells. Comparing our data with the effects of actinomycin D on the nucleolar proteome revealed that adenovirus infection apparently specifically targets a relatively small subset of nucleolar antigens at the time point examined.

Announcing the Launch of CPTAC’s Proteogenomics DREAM Challenge | Office of Cancer Clinical Proteomics Research

Cancer.gov

This week, we are excited to announce the launch of the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) Proteogenomics Computational DREAM Challenge.  The aim of this Challenge is to encourage the generation of computational methods for extracting information from the cancer proteome and for linking those data to genomic and transcriptomic information.  The specific goals are to predict proteomic and phosphoproteomic data from other multiple data types including transcriptomics and genetics.

Top-down Proteomics: Technology Advancements and Applications to Heart Diseases

PubMed Central

Cai, Wenxuan; Tucholski, Trisha M.; Gregorich, Zachery R.; Ge, Ying

2016-01-01

Introduction Diseases of the heart are a leading cause of morbidity and mortality for both men and women worldwide, and impose significant economic burdens on the healthcare systems. Despite substantial effort over the last several decades, the molecular mechanisms underlying diseases of the heart remain poorly understood. Areas covered Altered protein post-translational modifications (PTMs) and protein isoform switching are increasingly recognized as important disease mechanisms. Top-down high-resolution mass spectrometry (MS)-based proteomics has emerged as the most powerful method for the comprehensive analysis of PTMs and protein isoforms. Here, we will review recent technology developments in the field of top-down proteomics, as well as highlight recent studies utilizing top-down proteomics to decipher the cardiac proteome for the understanding of the molecular mechanisms underlying diseases of the heart. Expert commentary Top-down proteomics is a premier method for the global and comprehensive study of protein isoforms and their PTMs, enabling the identification of novel protein isoforms and PTMs, characterization of sequence variations, and quantification of disease-associated alterations. Despite significant challenges, continuous development of top-down proteomics technology will greatly aid the dissection of the molecular mechanisms underlying diseases of the hearts for the identification of novel biomarkers and therapeutic targets. PMID:27448560

Building ProteomeTools based on a complete synthetic human proteome

PubMed Central

Zolg, Daniel P.; Wilhelm, Mathias; Schnatbaum, Karsten; Zerweck, Johannes; Knaute, Tobias; Delanghe, Bernard; Bailey, Derek J.; Gessulat, Siegfried; Ehrlich, Hans-Christian; Weininger, Maximilian; Yu, Peng; Schlegl, Judith; Kramer, Karl; Schmidt, Tobias; Kusebauch, Ulrike; Deutsch, Eric W.; Aebersold, Ruedi; Moritz, Robert L.; Wenschuh, Holger; Moehring, Thomas; Aiche, Stephan; Huhmer, Andreas; Reimer, Ulf; Kuster, Bernhard

2018-01-01

The ProteomeTools project builds molecular and digital tools from the human proteome to facilitate biomedical and life science research. Here, we report the generation and multimodal LC-MS/MS analysis of >330,000 synthetic tryptic peptides representing essentially all canonical human gene products and exemplify the utility of this data. The resource will be extended to >1 million peptides and all data will be shared with the community via ProteomicsDB and proteomeXchange. PMID:28135259

Hyperspectral target detection using manifold learning and multiple target spectra

DOE PAGES

Ziemann, Amanda K.; Theiler, James; Messinger, David W.

2016-03-31

Imagery collected from satellites and airborne platforms provides an important tool for remotely analyzing the content of a scene. In particular, the ability to remotely detect a specific material within a scene is of critical importance in nonproliferation and other applications. The sensor systems that process hyperspectral images collect the high-dimensional spectral information necessary to perform these detection analyses. For a d-dimensional hyperspectral image, however, where d is the number of spectral bands, it is common for the data to inherently occupy an m-dimensional space with m << d. In the remote sensing community, this has led to recent interestmore » in the use of manifold learning, which seeks to characterize the embedded lower-dimensional, nonlinear manifold that the data discretely approximate. The research presented in this paper focuses on a graph theory and manifold learning approach to target detection, using an adaptive version of locally linear embedding that is biased to separate target pixels from background pixels. Finally, this approach incorporates multiple target signatures for a particular material, accounting for the spectral variability that is often present within a solid material of interest.« less

Proteomic identification of E6AP as a molecular target of tamoxifen in MCF7 cells.

PubMed

Lochab, Savita; Pal, Pooja; Kanaujiya, Jitendra K; Tripathi, Shashi B; Kapoor, Isha; Bhatt, Madan L B; Sanyal, Sabyasachi; Behre, Gerhard; Trivedi, Arun K

2012-05-01

Tamoxifen (Tam) is most widely used selective estrogen receptor modulator (SERM) for treatment of hormone-responsive breast cancer. Despite being regularly used in clinical therapy for breast cancer since 1971, the mechanism of Tam action remains largely unclear. In order to gain insights into Tam-mediated antibreast cancer actions, we applied 2DE and MS based proteomics approach to identify target proteins of Tam. We identified E6-associated protein, i.e. E6AP (UBE3A) among others to be regulated by Tam that otherwise is upregulated in breast tumors. We confirmed our 2DE finding by immunoblotting and further show that Tam leads to inhibition of E6AP expression presumably by promoting its autoubiquitination, which is coupled with nuclear export and subsequent proteasome-mediated degradation. Furthermore, we show that Tam- and siE6AP-mediated inhibition of E6AP leads to enhanced G0-G1 growth arrest and apoptosis, which is also evident from significant upregulation of cytochrome-c, Bax, p21, and PARP cleavage. Taken together, our data suggest that, Tam-targeted E6AP inhibition is in fact required for Tam-mediated antibreast cancer actions. Thus, E6AP may be a therapeutic target in breast cancer. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantification of pancreatic cancer proteome and phosphorylome: indicates molecular events likely contributing to cancer and activity of drug targets.

PubMed

Britton, David; Zen, Yoh; Quaglia, Alberto; Selzer, Stefan; Mitra, Vikram; Löβner, Christopher; Jung, Stephan; Böhm, Gitte; Schmid, Peter; Prefot, Petra; Hoehle, Claudia; Koncarevic, Sasa; Gee, Julia; Nicholson, Robert; Ward, Malcolm; Castellano, Leandro; Stebbing, Justin; Zucht, Hans Dieter; Sarker, Debashis; Heaton, Nigel; Pike, Ian

2014-01-01

LC-MS/MS phospho-proteomics is an essential technology to help unravel the complex molecular events that lead to and propagate cancer. We have developed a global phospho-proteomic workflow to determine activity of signaling pathways and drug targets in pancreatic cancer tissue for clinical application. Peptides resulting from tryptic digestion of proteins extracted from frozen tissue of pancreatic ductal adenocarcinoma and background pancreas (n = 12), were labelled with tandem mass tags (TMT 8-plex), separated by strong cation exchange chromatography, then were analysed by LC-MS/MS directly or first enriched for phosphopeptides using IMAC and TiO2, prior to analysis. In-house, commercial and freeware bioinformatic platforms were used to identify relevant biological events from the complex dataset. Of 2,101 proteins identified, 152 demonstrated significant difference in abundance between tumor and non-tumor tissue. They included proteins that are known to be up-regulated in pancreatic cancer (e.g. Mucin-1), but the majority were new candidate markers such as HIPK1 & MLCK. Of the 6,543 unique phosphopeptides identified (6,284 unique phosphorylation sites), 635 showed significant regulation, particularly those from proteins involved in cell migration (Rho guanine nucleotide exchange factors & MRCKα) and formation of focal adhesions. Activator phosphorylation sites on FYN, AKT1, ERK2, HDAC1 and other drug targets were found to be highly modulated (≥2 fold) in different cases highlighting their predictive power. Here we provided critical information enabling us to identify the common and unique molecular events likely contributing to cancer in each case. Such information may be used to help predict more bespoke therapy suitable for an individual case.

Analysis of the outer membrane proteome and secretome of Bacteroides fragilis reveals a multiplicity of secretion mechanisms.

PubMed

Wilson, Marlena M; Anderson, D Eric; Bernstein, Harris D

2015-01-01

Bacteroides fragilis is a widely distributed member of the human gut microbiome and an opportunistic pathogen. Cell surface molecules produced by this organism likely play important roles in colonization, communication with other microbes, and pathogenicity, but the protein composition of the outer membrane (OM) and the mechanisms used to transport polypeptides into the extracellular space are poorly characterized. Here we used LC-MS/MS to analyze the OM proteome and secretome of B. fragilis NCTC 9343 grown under laboratory conditions. Of the 229 OM proteins that we identified, 108 are predicted to be lipoproteins, and 61 are predicted to be TonB-dependent transporters. Based on their proximity to genes encoding TonB-dependent transporters, many of the lipoprotein genes likely encode proteins involved in nutrient or small molecule uptake. Interestingly, protease accessibility and biotinylation experiments indicated that an unusually large fraction of the lipoproteins are cell-surface exposed. We also identified three proteins that are members of a novel family of autotransporters, multiple potential type I protein secretion systems, and proteins that appear to be components of a type VI secretion apparatus. The secretome consisted of lipoproteins and other proteins that might be substrates of the putative type I or type VI secretion systems. Our proteomic studies show that B. fragilis differs considerably from well-studied Gram-negative bacteria such as Escherichia coli in both the spectrum of OM proteins that it produces and the range of secretion strategies that it utilizes.

Method and platform standardization in MRM-based quantitative plasma proteomics.

PubMed

Percy, Andrew J; Chambers, Andrew G; Yang, Juncong; Jackson, Angela M; Domanski, Dominik; Burkhart, Julia; Sickmann, Albert; Borchers, Christoph H

2013-12-16

There exists a growing demand in the proteomics community to standardize experimental methods and liquid chromatography-mass spectrometry (LC/MS) platforms in order to enable the acquisition of more precise and accurate quantitative data. This necessity is heightened by the evolving trend of verifying and validating candidate disease biomarkers in complex biofluids, such as blood plasma, through targeted multiple reaction monitoring (MRM)-based approaches with stable isotope-labeled standards (SIS). Considering the lack of performance standards for quantitative plasma proteomics, we previously developed two reference kits to evaluate the MRM with SIS peptide approach using undepleted and non-enriched human plasma. The first kit tests the effectiveness of the LC/MRM-MS platform (kit #1), while the second evaluates the performance of an entire analytical workflow (kit #2). Here, these kits have been refined for practical use and then evaluated through intra- and inter-laboratory testing on 6 common LC/MS platforms. For an identical panel of 22 plasma proteins, similar concentrations were determined, regardless of the kit, instrument platform, and laboratory of analysis. These results demonstrate the value of the kit and reinforce the utility of standardized methods and protocols. The proteomics community needs standardized experimental protocols and quality control methods in order to improve the reproducibility of MS-based quantitative data. This need is heightened by the evolving trend for MRM-based validation of proposed disease biomarkers in complex biofluids such as blood plasma. We have developed two kits to assist in the inter- and intra-laboratory quality control of MRM experiments: the first kit tests the effectiveness of the LC/MRM-MS platform (kit #1), while the second evaluates the performance of an entire analytical workflow (kit #2). In this paper, we report the use of these kits in intra- and inter-laboratory testing on 6 common LC/MS platforms. This

A proteomics performance standard to support measurement quality in proteomics.

PubMed

Beasley-Green, Ashley; Bunk, David; Rudnick, Paul; Kilpatrick, Lisa; Phinney, Karen

2012-04-01

The emergence of MS-based proteomic platforms as a prominent technology utilized in biochemical and biomedical research has increased the need for high-quality MS measurements. To address this need, National Institute of Standards and Technology (NIST) reference material (RM) 8323 yeast protein extract is introduced as a proteomics quality control material for benchmarking the preanalytical and analytical performance of proteomics-based experimental workflows. RM 8323 yeast protein extract is based upon the well-characterized eukaryote Saccharomyces cerevisiae and can be utilized in the design and optimization of proteomics-based methodologies from sample preparation to data analysis. To demonstrate its utility as a proteomics quality control material, we coupled LC-MS/MS measurements of RM 8323 with the NIST MS Quality Control (MSQC) performance metrics to quantitatively assess the LC-MS/MS instrumentation parameters that influence measurement accuracy, repeatability, and reproducibility. Due to the complexity of the yeast proteome, we also demonstrate how NIST RM 8323, along with the NIST MSQC performance metrics, can be used in the evaluation and optimization of proteomics-based sample preparation methods. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomic and Bioinformatic Studies for the Characterization of Response to Pemetrexed in Platinum Drug Resistant Ovarian Cancer.

PubMed

Severi, Leda; Losi, Lorena; Fonda, Sergio; Taddia, Laura; Gozzi, Gaia; Marverti, Gaetano; Magni, Fulvio; Chinello, Clizia; Stella, Martina; Sheouli, Jalid; Braicu, Elena I; Genovese, Filippo; Lauriola, Angela; Marraccini, Chiara; Gualandi, Alessandra; D'Arca, Domenico; Ferrari, Stefania; Costi, Maria P

2018-01-01

Proteomics and bioinformatics are a useful combined technology for the characterization of protein expression level and modulation associated with the response to a drug and with its mechanism of action. The folate pathway represents an important target in the anticancer drugs therapy. In the present study, a discovery proteomics approach was applied to tissue samples collected from ovarian cancer patients who relapsed after the first-line carboplatin-based chemotherapy and were treated with pemetrexed (PMX), a known folate pathway targeting drug. The aim of the work is to identify the proteomic profile that can be associated to the response to the PMX treatment in pre-treatement tissue. Statistical metrics of the experimental Mass Spectrometry (MS) data were combined with a knowledge-based approach that included bioinformatics and a literature review through ProteinQuest™ tool, to design a protein set of reference (PSR). The PSR provides feedback for the consistency of MS proteomic data because it includes known validated proteins. A panel of 24 proteins with levels that were significantly different in pre-treatment samples of patients who responded to the therapy vs. the non-responder ones, was identified. The differences of the identified proteins were explained for the patients with different outcomes and the known PMX targets were further validated. The protein panel herein identified is ready for further validation in retrospective clinical trials using a targeted proteomic approach. This study may have a general relevant impact on biomarker application for cancer patients therapy selection.

Proteomics of ovarian cancer: functional insights and clinical applications

DOE PAGES

Elzek, Mohamed A.; Rodland, Karin D.

2015-03-04

In the past decade, there has been an increasing interest in applying proteomics to assist in understanding the pathogenesis of ovarian cancer, elucidating the mechanism of drug resistance, and in the development of biomarkers for early detection of ovarian cancer. Although ovarian cancer is a spectrum of different diseases, the strategies for diagnosis and treatment with surgery and adjuvant therapy are similar across ovarian cancer types, increasing the general applicability of discoveries made through proteomics research. While proteomic experiments face many difficulties which slow the pace of clinical applications, recent advances in proteomic technology contribute significantly to the identification ofmore » aberrant proteins and networks which can serve as targets for biomarker development and individualized therapies. This review provides a summary of the literature on proteomics’ contributions to ovarian cancer research and highlights the current issues, future directions, and challenges. In conclusion, we propose that protein-level characterization of primary lesion in ovarian cancer can decipher the mystery of this disease, improve diagnostic tools, and lead to more effective screening programs.« less

Microchip-Based Single-Cell Functional Proteomics for Biomedical Applications

PubMed Central

Lu, Yao; Yang, Liu; Wei, Wei; Shi, Qihui

2017-01-01

Cellular heterogeneity has been widely recognized but only recently have single cell tools become available that allow characterizing heterogeneity at the genomic and proteomic levels. We review the technological advances in microchip-based toolkits for single-cell functional proteomics. Each of these tools has distinct advantages and limitations, and a few have advanced toward being applied to address biological or clinical problems that fail to be addressed by traditional population-based methods. High-throughput single-cell proteomic assays generate high-dimensional data sets that contain new information and thus require developing new analytical framework to extract new biology. In this review article, we highlight a few biological and clinical applications in which the microchip-based single-cell proteomic tools provide unique advantages. The examples include resolving functional heterogeneity and dynamics of immune cells, dissecting cell-cell interaction by creating well-contolled on-chip microenvironment, capturing high-resolution snapshots of immune system functions in patients for better immunotherapy and elucidating phosphoprotein signaling networks in cancer cells for guiding effective molecularly targeted therapies. PMID:28280819

Targeted proteome analysis of single-gene deletion strains of Saccharomyces cerevisiae lacking enzymes in the central carbon metabolism.

PubMed

Matsuda, Fumio; Kinoshita, Syohei; Nishino, Shunsuke; Tomita, Atsumi; Shimizu, Hiroshi

2017-01-01

Central carbon metabolism is controlled by modulating the protein abundance profiles of enzymes that maintain the essential systems in living organisms. In this study, metabolic adaptation mechanisms in the model organism Saccharomyces cerevisiae were investigated by direct determination of enzyme abundance levels in 30 wild type and mutant strains. We performed a targeted proteome analysis using S. cerevisiae strains that lack genes encoding the enzymes responsible for central carbon metabolism. Our analysis revealed that at least 30% of the observed variations in enzyme abundance levels could be explained by global regulatory mechanisms. A enzyme-enzyme co-abundance analysis revealed that the abundances of enzyme proteins involved in the trehalose metabolism and glycolysis changed in a coordinated manner under the control of the transcription factors for global regulation. The remaining variations were derived from local mechanisms such as a mutant-specific increase in the abundances of remote enzymes. The proteome data also suggested that, although the functional compensation of the deficient enzyme was attained by using more resources for protein biosynthesis, available resources for the biosynthesis of the enzymes responsible for central metabolism were not abundant in S. cerevisiae cells. These results showed that global and local regulation of enzyme abundance levels shape central carbon metabolism in S. cerevisiae by using a limited resource for protein biosynthesis.

The emergence of top-down proteomics in clinical research

PubMed Central

2013-01-01

Proteomic technology has advanced steadily since the development of 'soft-ionization' techniques for mass-spectrometry-based molecular identification more than two decades ago. Now, the large-scale analysis of proteins (proteomics) is a mainstay of biological research and clinical translation, with researchers seeking molecular diagnostics, as well as protein-based markers for personalized medicine. Proteomic strategies using the protease trypsin (known as bottom-up proteomics) were the first to be developed and optimized and form the dominant approach at present. However, researchers are now beginning to understand the limitations of bottom-up techniques, namely the inability to characterize and quantify intact protein molecules from a complex mixture of digested peptides. To overcome these limitations, several laboratories are taking a whole-protein-based approach, in which intact protein molecules are the analytical targets for characterization and quantification. We discuss these top-down techniques and how they have been applied to clinical research and are likely to be applied in the near future. Given the recent improvements in mass-spectrometry-based proteomics and stronger cooperation between researchers, clinicians and statisticians, both peptide-based (bottom-up) strategies and whole-protein-based (top-down) strategies are set to complement each other and help researchers and clinicians better understand and detect complex disease phenotypes. PMID:23806018

Proteomic profile of dormant Trichophyton Rubrum conidia

PubMed Central

Leng, Wenchuan; Liu, Tao; Li, Rui; Yang, Jian; Wei, Candong; Zhang, Wenliang; Jin, Qi

2008-01-01

Background Trichophyton rubrum is the most common dermatophyte causing fungal skin infections in humans. Asexual sporulation is an important means of propagation for T. rubrum, and conidia produced by this way are thought to be the primary cause of human infections. Despite their importance in pathogenesis, the conidia of T. rubrum remain understudied. We intend to intensively investigate the proteome of dormant T. rubrum conidia to characterize its molecular and cellular features and to enhance the development of novel therapeutic strategies. Results The proteome of T. rubrum conidia was analyzed by combining shotgun proteomics with sample prefractionation and multiple enzyme digestion. In total, 1026 proteins were identified. All identified proteins were compared to those in the NCBI non-redundant protein database, the eukaryotic orthologous groups database, and the gene ontology database to obtain functional annotation information. Functional classification revealed that the identified proteins covered nearly all major biological processes. Some proteins were spore specific and related to the survival and dispersal of T. rubrum conidia, and many proteins were important to conidial germination and response to environmental conditions. Conclusion Our results suggest that the proteome of T. rubrum conidia is considerably complex, and that the maintenance of conidial dormancy is an intricate and elaborate process. This data set provides the first global framework for the dormant T. rubrum conidia proteome and is a stepping stone on the way to further study of the molecular mechanisms of T. rubrum conidial germination and the maintenance of conidial dormancy. PMID:18578874

Architecture Mapping of the Inner Mitochondrial Membrane Proteome by Chemical Tools in Live Cells.

PubMed

Lee, Song-Yi; Kang, Myeong-Gyun; Shin, Sanghee; Kwak, Chulhwan; Kwon, Taejoon; Seo, Jeong Kon; Kim, Jong-Seo; Rhee, Hyun-Woo

2017-03-15

The inner mitochondrial membrane (IMM) proteome plays a central role in maintaining mitochondrial physiology and cellular metabolism. Various important biochemical reactions such as oxidative phosphorylation, metabolite production, and mitochondrial biogenesis are conducted by the IMM proteome, and mitochondria-targeted therapeutics have been developed for IMM proteins, which is deeply related for various human metabolic diseases including cancer and neurodegenerative diseases. However, the membrane topology of the IMM proteome remains largely unclear because of the lack of methods to evaluate it in live cells in a high-throughput manner. In this article, we reveal the in vivo topological direction of 135 IMM proteins, using an in situ-generated radical probe with genetically targeted peroxidase (APEX). Owing to the short lifetime of phenoxyl radicals generated in situ by submitochondrial targeted APEX and the impermeability of the IMM to small molecules, the solvent-exposed tyrosine residues of both the matrix and intermembrane space (IMS) sides of IMM proteins were exclusively labeled with the radical probe in live cells by Matrix-APEX and IMS-APEX, respectively and identified by mass spectrometry. From this analysis, we confirmed 58 IMM protein topologies and we could determine the topological direction of 77 IMM proteins whose topology at the IMM has not been fully characterized. We also found several IMM proteins (e.g., LETM1 and OXA1) whose topological information should be revised on the basis of our results. Overall, our identification of structural information on the mitochondrial inner-membrane proteome can provide valuable insights for the architecture and connectome of the IMM proteome in live cells.

Automated selected reaction monitoring data analysis workflow for large-scale targeted proteomic studies.

PubMed

Surinova, Silvia; Hüttenhain, Ruth; Chang, Ching-Yun; Espona, Lucia; Vitek, Olga; Aebersold, Ruedi

2013-08-01

Targeted proteomics based on selected reaction monitoring (SRM) mass spectrometry is commonly used for accurate and reproducible quantification of protein analytes in complex biological mixtures. Strictly hypothesis-driven, SRM assays quantify each targeted protein by collecting measurements on its peptide fragment ions, called transitions. To achieve sensitive and accurate quantitative results, experimental design and data analysis must consistently account for the variability of the quantified transitions. This consistency is especially important in large experiments, which increasingly require profiling up to hundreds of proteins over hundreds of samples. Here we describe a robust and automated workflow for the analysis of large quantitative SRM data sets that integrates data processing, statistical protein identification and quantification, and dissemination of the results. The integrated workflow combines three software tools: mProphet for peptide identification via probabilistic scoring; SRMstats for protein significance analysis with linear mixed-effect models; and PASSEL, a public repository for storage, retrieval and query of SRM data. The input requirements for the protocol are files with SRM traces in mzXML format, and a file with a list of transitions in a text tab-separated format. The protocol is especially suited for data with heavy isotope-labeled peptide internal standards. We demonstrate the protocol on a clinical data set in which the abundances of 35 biomarker candidates were profiled in 83 blood plasma samples of subjects with ovarian cancer or benign ovarian tumors. The time frame to realize the protocol is 1-2 weeks, depending on the number of replicates used in the experiment.

Isolation and proteomic analysis of Chlamydomonas centrioles.

PubMed

Keller, Lani C; Marshall, Wallace F

2008-01-01

Centrioles are barrel-shaped cytoskeletal organelles composed of nine triplet microtubules blades arranged in a pinwheel-shaped array. Centrioles are required for recruitment of pericentriolar material (PCM) during centrosome formation, and they act as basal bodies, which are necessary for the outgrowth of cilia and flagella. Despite being described over a hundred years ago, centrioles are still among the most enigmatic organelles in all of cell biology. To gain molecular insights into the function and assembly of centrioles, we sought to determine the composition of the centriole proteome. Here, we describe a method that allows for the isolation of virtually "naked" centrioles, with little to no obscuring PCM, from the green alga, Chlamydomonas. Proteomic analysis of this material provided evidence that multiple human disease gene products encode protein components of the centriole, including genes involved in Meckel syndrome and Oral-Facial-Digital syndrome. Isolated centrioles can be used in combination with a wide variety of biochemical assays in addition to being utilized as a source for proteomic analysis.

A Scalable Approach for Protein False Discovery Rate Estimation in Large Proteomic Data Sets.

PubMed

Savitski, Mikhail M; Wilhelm, Mathias; Hahne, Hannes; Kuster, Bernhard; Bantscheff, Marcus

2015-09-01

Calculating the number of confidently identified proteins and estimating false discovery rate (FDR) is a challenge when analyzing very large proteomic data sets such as entire human proteomes. Biological and technical heterogeneity in proteomic experiments further add to the challenge and there are strong differences in opinion regarding the conceptual validity of a protein FDR and no consensus regarding the methodology for protein FDR determination. There are also limitations inherent to the widely used classic target-decoy strategy that particularly show when analyzing very large data sets and that lead to a strong over-representation of decoy identifications. In this study, we investigated the merits of the classic, as well as a novel target-decoy-based protein FDR estimation approach, taking advantage of a heterogeneous data collection comprised of ∼19,000 LC-MS/MS runs deposited in ProteomicsDB (https://www.proteomicsdb.org). The "picked" protein FDR approach treats target and decoy sequences of the same protein as a pair rather than as individual entities and chooses either the target or the decoy sequence depending on which receives the highest score. We investigated the performance of this approach in combination with q-value based peptide scoring to normalize sample-, instrument-, and search engine-specific differences. The "picked" target-decoy strategy performed best when protein scoring was based on the best peptide q-value for each protein yielding a stable number of true positive protein identifications over a wide range of q-value thresholds. We show that this simple and unbiased strategy eliminates a conceptual issue in the commonly used "classic" protein FDR approach that causes overprediction of false-positive protein identification in large data sets. The approach scales from small to very large data sets without losing performance, consistently increases the number of true-positive protein identifications and is readily implemented in

Use of proteomic methods in the analysis of human body fluids in Alzheimer research.

PubMed

Zürbig, Petra; Jahn, Holger

2012-12-01

Proteomics is the study of the entire population of proteins and peptides in an organism or a part of it, such as a cell, tissue, or fluids like cerebrospinal fluid, plasma, serum, urine, or saliva. It is widely assumed that changes in the composition of the proteome may reflect disease states and provide clues to its origin, eventually leading to targets for new treatments. The ability to perform large-scale proteomic studies now is based jointly on recent advances in our analytical methods. Separation techniques like CE and 2DE have developed and matured. Detection methods like MS have also improved greatly in the last 5 years. These developments have also driven the fields of bioinformatics, needed to deal with the increased data production and systems biology. All these developing methods offer specific advantages but also come with certain limitations. This review describes the different proteomic methods used in the field, their limitations, and their possible pitfalls. Based on a literature search in PubMed, we identified 112 studies that applied proteomic techniques to identify biomarkers for Alzheimer disease. This review describes the results of these studies on proteome changes in human body fluids of Alzheimer patients reviewing the most important studies. We extracted a list of 366 proteins and peptides that were identified by these studies as potential targets in Alzheimer research. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteome analysis of ofloxacin and moxifloxacin induced mycobacterium tuberculosis isolates by proteomic approach.

PubMed

Lata, Manju; Sharma, Divakar; Kumar, Bhavnesh; Deo, Nirmala; Tiwari, Pramod Kumar; Bisht, Deepa; Venkatesan, Krishnamurthy

2015-01-01

Ofloxacin (OFX) and moxifloxacin (MOX) are the most promising second line drugs for tuberculosis treatment. Although the primary mechanism of action of OFX and MOX is gyrase inhibition, other possible mechanisms cannot be ruled out. Being the functional moiety of cell, the proteins act as primary targets for developing drugs, diagnostics and therapeutics. In this study we have investigated the proteomic changes of Mycobacterium tuberculosis isolates induced by OFX and MOX by applying comparative proteomic approaches based on two-dinensional gel electrophoresis (2DE) along with matrix assisted laser desorption ionisation time of flight mass spectrometry (MALDI TOF/TOF-MS) and bioinformatic tools. The findings are likely to provide new understanding of OFX and MOX mechanisms that might be helpful in exploring new diagnostics and drug targets. Our study explored eleven proteins (Rv2889c, Rv2623, Rv0952, Rv1827, Rv1932, Rv0054, Rv1080c, Rv3418c, Rv3914, Rv1636 and Rv0009) that were overexpressed in the presence of drugs. Among them, Rv2623, Rv1827 and Rv1636 were identified as proteins with unknown function. InterProScan and molecular docking revealed that the conserved domain of hypothetical proteins interact with OFX and MOX which indicate a probable inhibition/modulation of the functioning of these proteins by both drugs, which might be overexpressed to overcome this effect.

A Review: Proteomics in Retinal Artery Occlusion, Retinal Vein Occlusion, Diabetic Retinopathy and Acquired Macular Disorders.

PubMed

Cehofski, Lasse Jørgensen; Honoré, Bent; Vorum, Henrik

2017-04-28

Retinal artery occlusion (RAO), retinal vein occlusion (RVO), diabetic retinopathy (DR) and age-related macular degeneration (AMD) are frequent ocular diseases with potentially sight-threatening outcomes. In the present review we discuss major findings of proteomic studies of RAO, RVO, DR and AMD, including an overview of ocular proteome changes associated with anti-vascular endothelial growth factor (VEGF) treatments. Despite the severe outcomes of RAO, the proteome of the disease remains largely unstudied. There is also limited knowledge about the proteome of RVO, but proteomic studies suggest that RVO is associated with remodeling of the extracellular matrix and adhesion processes. Proteomic studies of DR have resulted in the identification of potential therapeutic targets such as carbonic anhydrase-I. Proliferative diabetic retinopathy is the most intensively studied stage of DR. Proteomic studies have established VEGF, pigment epithelium-derived factor (PEDF) and complement components as key factors associated with AMD. The aim of this review is to highlight the major milestones in proteomics in RAO, RVO, DR and AMD. Through large-scale protein analyses, proteomics is bringing new important insights into these complex pathological conditions.

A unique role of endogenous visual-spatial attention in rapid processing of multiple targets

PubMed Central

Guzman, Emmanuel; Grabowecky, Marcia; Palafox, German; Suzuki, Satoru

2012-01-01

Visual spatial attention can be exogenously captured by a salient stimulus or can be endogenously allocated by voluntary effort. Whether these two attention modes serve distinctive functions is debated, but for processing of single targets the literature suggests superiority of exogenous attention (it is faster acting and serves more functions). We report that endogenous attention uniquely contributes to processing of multiple targets. For speeded visual discrimination, response times are faster for multiple redundant targets than for single targets due to probability summation and/or signal integration. This redundancy gain was unaffected when attention was exogenously diverted from the targets, but was completely eliminated when attention was endogenously diverted. This was not due to weaker manipulation of exogenous attention because our exogenous and endogenous cues similarly affected overall response times. Thus, whereas exogenous attention is superior for processing single targets, endogenous attention plays a unique role in allocating resources crucial for rapid concurrent processing of multiple targets. PMID:21517209

Characterization, design, and function of the mitochondrial proteome: from organs to organisms.

PubMed

Lotz, Christopher; Lin, Amanda J; Black, Caitlin M; Zhang, Jun; Lau, Edward; Deng, Ning; Wang, Yueju; Zong, Nobel C; Choi, Jeong H; Xu, Tao; Liem, David A; Korge, Paavo; Weiss, James N; Hermjakob, Henning; Yates, John R; Apweiler, Rolf; Ping, Peipei

2014-02-07

Mitochondria are a common energy source for organs and organisms; their diverse functions are specialized according to the unique phenotypes of their hosting environment. Perturbation of mitochondrial homeostasis accompanies significant pathological phenotypes. However, the connections between mitochondrial proteome properties and function remain to be experimentally established on a systematic level. This uncertainty impedes the contextualization and translation of proteomic data to the molecular derivations of mitochondrial diseases. We present a collection of mitochondrial features and functions from four model systems, including two cardiac mitochondrial proteomes from distinct genomes (human and mouse), two unique organ mitochondrial proteomes from identical genetic codons (mouse heart and mouse liver), as well as a relevant metazoan out-group (drosophila). The data, composed of mitochondrial protein abundance and their biochemical activities, capture the core functionalities of these mitochondria. This investigation allowed us to redefine the core mitochondrial proteome from organs and organisms, as well as the relevant contributions from genetic information and hosting milieu. Our study has identified significant enrichment of disease-associated genes and their products. Furthermore, correlational analyses suggest that mitochondrial proteome design is primarily driven by cellular environment. Taken together, these results connect proteome feature with mitochondrial function, providing a prospective resource for mitochondrial pathophysiology and developing novel therapeutic targets in medicine.

Multiple operating system rotation environment moving target defense

DOE Office of Scientific and Technical Information (OSTI.GOV)

Evans, Nathaniel; Thompson, Michael

Systems and methods for providing a multiple operating system rotation environment ("MORE") moving target defense ("MTD") computing system are described. The MORE-MTD system provides enhanced computer system security through a rotation of multiple operating systems. The MORE-MTD system increases attacker uncertainty, increases the cost of attacking the system, reduces the likelihood of an attacker locating a vulnerability, and reduces the exposure time of any located vulnerability. The MORE-MTD environment is effectuated by rotation of the operating systems at a given interval. The rotating operating systems create a consistently changing attack surface for remote attackers.

Metrics for the Human Proteome Project 2016: Progress on Identifying and Characterizing the Human Proteome, Including Post-Translational Modifications.

PubMed

Omenn, Gilbert S; Lane, Lydie; Lundberg, Emma K; Beavis, Ronald C; Overall, Christopher M; Deutsch, Eric W

2016-11-04

variants (SAAVSs), and splice isoforms. Meanwhile, the Biology- and Disease-driven (B/D)-HPP has created comprehensive SRM resources, generated popular protein lists to guide targeted proteomics assays for specific diseases, and launched an Early Career Researchers initiative.

The unique peptidome: Taxon-specific tryptic peptides as biomarkers for targeted metaproteomics.

PubMed

Mesuere, Bart; Van der Jeugt, Felix; Devreese, Bart; Vandamme, Peter; Dawyndt, Peter

2016-09-01

The Unique Peptide Finder (http://unipept.ugent.be/peptidefinder) is an interactive web application to quickly hunt for tryptic peptides that are unique to a particular species, genus, or any other taxon. Biodiversity within the target taxon is represented by a set of proteomes selected from a monthly updated list of complete and nonredundant UniProt proteomes, supplemented with proprietary proteomes loaded into persistent local browser storage. The software computes and visualizes pan and core peptidomes as unions and intersections of tryptic peptides occurring in the selected proteomes. In addition, it also computes and displays unique peptidomes as the set of all tryptic peptides that occur in all selected proteomes but not in any UniProt record not assigned to the target taxon. As a result, the unique peptides can serve as robust biomarkers for the target taxon, for example, in targeted metaproteomics studies. Computations are extremely fast since they are underpinned by the Unipept database, the lowest common ancestor algorithm implemented in Unipept and modern web technologies that facilitate in-browser data storage and parallel processing. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Implementation of statistical process control for proteomic experiments via LC MS/MS.

PubMed

Bereman, Michael S; Johnson, Richard; Bollinger, James; Boss, Yuval; Shulman, Nick; MacLean, Brendan; Hoofnagle, Andrew N; MacCoss, Michael J

2014-04-01

Statistical process control (SPC) is a robust set of tools that aids in the visualization, detection, and identification of assignable causes of variation in any process that creates products, services, or information. A tool has been developed termed Statistical Process Control in Proteomics (SProCoP) which implements aspects of SPC (e.g., control charts and Pareto analysis) into the Skyline proteomics software. It monitors five quality control metrics in a shotgun or targeted proteomic workflow. None of these metrics require peptide identification. The source code, written in the R statistical language, runs directly from the Skyline interface, which supports the use of raw data files from several of the mass spectrometry vendors. It provides real time evaluation of the chromatographic performance (e.g., retention time reproducibility, peak asymmetry, and resolution), and mass spectrometric performance (targeted peptide ion intensity and mass measurement accuracy for high resolving power instruments) via control charts. Thresholds are experiment- and instrument-specific and are determined empirically from user-defined quality control standards that enable the separation of random noise and systematic error. Finally, Pareto analysis provides a summary of performance metrics and guides the user to metrics with high variance. The utility of these charts to evaluate proteomic experiments is illustrated in two case studies.

The proteomic landscape of triple-negative breast cancer.

PubMed

Lawrence, Robert T; Perez, Elizabeth M; Hernández, Daniel; Miller, Chris P; Haas, Kelsey M; Irie, Hanna Y; Lee, Su-In; Blau, C Anthony; Villén, Judit

2015-04-28

Triple-negative breast cancer is a heterogeneous disease characterized by poor clinical outcomes and a shortage of targeted treatment options. To discover molecular features of triple-negative breast cancer, we performed quantitative proteomics analysis of twenty human-derived breast cell lines and four primary breast tumors to a depth of more than 12,000 distinct proteins. We used this data to identify breast cancer subtypes at the protein level and demonstrate the precise quantification of biomarkers, signaling proteins, and biological pathways by mass spectrometry. We integrated proteomics data with exome sequence resources to identify genomic aberrations that affect protein expression. We performed a high-throughput drug screen to identify protein markers of drug sensitivity and understand the mechanisms of drug resistance. The genome and proteome provide complementary information that, when combined, yield a powerful engine for therapeutic discovery. This resource is available to the cancer research community to catalyze further analysis and investigation. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Probing the Proteome on Earth and Beyond

NASA Astrophysics Data System (ADS)

Ostrom, P.

2008-12-01

Less than a decade ago, protein sequencing was the bane of paleobiology. Since that time researchers have completely sequenced proteins in >50 Ka fossils, been dazzled by reports of collagen peptides in dinosaur bones, and witnessed the development of phylogenetic trees from ancient protein sequences. Enlisting proteomics as biosignature is now in our grasp. In this talk the pitfalls and challenges of mass spectrometric approaches to protein sequencing will be illustrated and phylogenetic applications will be discussed. Work on extinct organisms at Michigan State University, University of Michigan and York University will provide a vantage point to assess methodologies, explore diagenetic alterations, evaluate mass spectra and illustrate issues associated with data base searching. Challenges encountered in the study of paleoproteomics, such as the absence of sequences for extinct organisms in commercially available databases, protein diagenesis and low concentrations of target are parallel to those that will be encountered when protein sequencing is extended to extreme and extraterrestrial environments. Thus, lessons learned from interrogating the ancient proteome are important and necessary step in developing proteomics as a biosignature tools.

Magnetoresistive biosensors for quantitative proteomics

NASA Astrophysics Data System (ADS)

Zhou, Xiahan; Huang, Chih-Cheng; Hall, Drew A.

2017-08-01

Quantitative proteomics, as a developing method for study of proteins and identification of diseases, reveals more comprehensive and accurate information of an organism than traditional genomics. A variety of platforms, such as mass spectrometry, optical sensors, electrochemical sensors, magnetic sensors, etc., have been developed for detecting proteins quantitatively. The sandwich immunoassay is widely used as a labeled detection method due to its high specificity and flexibility allowing multiple different types of labels. While optical sensors use enzyme and fluorophore labels to detect proteins with high sensitivity, they often suffer from high background signal and challenges in miniaturization. Magnetic biosensors, including nuclear magnetic resonance sensors, oscillator-based sensors, Hall-effect sensors, and magnetoresistive sensors, use the specific binding events between magnetic nanoparticles (MNPs) and target proteins to measure the analyte concentration. Compared with other biosensing techniques, magnetic sensors take advantage of the intrinsic lack of magnetic signatures in biological samples to achieve high sensitivity and high specificity, and are compatible with semiconductor-based fabrication process to have low-cost and small-size for point-of-care (POC) applications. Although still in the development stage, magnetic biosensing is a promising technique for in-home testing and portable disease monitoring.

Comprehensive Analysis of Temporal Alterations in Cellular Proteome of Bacillus subtilis under Curcumin Treatment

PubMed Central

Reddy, Panga Jaipal; Sinha, Sneha; Ray, Sandipan; Sathe, Gajanan J.; Chatterjee, Aditi; Prasad, T. S. Keshava; Dhali, Snigdha; Srikanth, Rapole; Panda, Dulal; Srivastava, Sanjeeva

2015-01-01

Curcumin is a natural dietary compound with antimicrobial activity against various gram positive and negative bacteria. This study aims to investigate the proteome level alterations in Bacillus subtilis due to curcumin treatment and identification of its molecular/cellular targets to understand the mechanism of action. We have performed a comprehensive proteomic analysis of B. subtilis AH75 strain at different time intervals of curcumin treatment (20, 60 and 120 min after the drug exposure, three replicates) to compare the protein expression profiles using two complementary quantitative proteomic techniques, 2D-DIGE and iTRAQ. To the best of our knowledge, this is the first comprehensive longitudinal investigation describing the effect of curcumin treatment on B. subtilis proteome. The proteomics analysis revealed several interesting targets such UDP-N-acetylglucosamine 1-carboxyvinyltransferase 1, putative septation protein SpoVG and ATP-dependent Clp protease proteolytic subunit. Further, in silico pathway analysis using DAVID and KOBAS has revealed modulation of pathways related to the fatty acid metabolism and cell wall synthesis, which are crucial for cell viability. Our findings revealed that curcumin treatment lead to inhibition of the cell wall and fatty acid synthesis in addition to differential expression of many crucial proteins involved in modulation of bacterial metabolism. Findings obtained from proteomics analysis were further validated using 5-cyano-2,3-ditolyl tetrazolium chloride (CTC) assay for respiratory activity, resazurin assay for metabolic activity and membrane integrity assay by potassium and inorganic phosphate leakage measurement. The gene expression analysis of selected cell wall biosynthesis enzymes has strengthened the proteomics findings and indicated the major effect of curcumin on cell division. PMID:25874956

Comprehensive analysis of temporal alterations in cellular proteome of Bacillus subtilis under curcumin treatment.

PubMed

Reddy, Panga Jaipal; Sinha, Sneha; Ray, Sandipan; Sathe, Gajanan J; Chatterjee, Aditi; Prasad, T S Keshava; Dhali, Snigdha; Srikanth, Rapole; Panda, Dulal; Srivastava, Sanjeeva

2015-01-01

Curcumin is a natural dietary compound with antimicrobial activity against various gram positive and negative bacteria. This study aims to investigate the proteome level alterations in Bacillus subtilis due to curcumin treatment and identification of its molecular/cellular targets to understand the mechanism of action. We have performed a comprehensive proteomic analysis of B. subtilis AH75 strain at different time intervals of curcumin treatment (20, 60 and 120 min after the drug exposure, three replicates) to compare the protein expression profiles using two complementary quantitative proteomic techniques, 2D-DIGE and iTRAQ. To the best of our knowledge, this is the first comprehensive longitudinal investigation describing the effect of curcumin treatment on B. subtilis proteome. The proteomics analysis revealed several interesting targets such UDP-N-acetylglucosamine 1-carboxyvinyltransferase 1, putative septation protein SpoVG and ATP-dependent Clp protease proteolytic subunit. Further, in silico pathway analysis using DAVID and KOBAS has revealed modulation of pathways related to the fatty acid metabolism and cell wall synthesis, which are crucial for cell viability. Our findings revealed that curcumin treatment lead to inhibition of the cell wall and fatty acid synthesis in addition to differential expression of many crucial proteins involved in modulation of bacterial metabolism. Findings obtained from proteomics analysis were further validated using 5-cyano-2,3-ditolyl tetrazolium chloride (CTC) assay for respiratory activity, resazurin assay for metabolic activity and membrane integrity assay by potassium and inorganic phosphate leakage measurement. The gene expression analysis of selected cell wall biosynthesis enzymes has strengthened the proteomics findings and indicated the major effect of curcumin on cell division.

Redox Proteomics: A Key Tool for New Insights into Protein Modification with Relevance to Disease.

PubMed

Butterfield, D Allan; Perluigi, Marzia

2017-03-01

Oxidatively modified proteins are characterized by elevations in protein-resident carbonyls or 3-nitrotyrosine, measures of protein oxidation, or protein bound reactive alkenals such as 4-hydroxy-2-nonenal, a measure of lipid peroxidation. Oxidatively modified proteins nearly always have altered structure and function. Redox proteomics is that branch of proteomics used to identify oxidized proteins and determine the extent and location of oxidative modifications in the proteomes of interest. This technique nearly always employs mass spectrometry as the major platform to achieve the goals of identifying the target proteins. Once identified, oxidatively modified proteins can be placed in specific molecular pathways to provide insights into protein oxidation and human disease. Both original research and review articles are included in this Forum on Redox Proteomics. The topics related to redox proteomics range from basic chemistry of sulfur radical-induced redox modifications in proteins, to the thiol secretome and inflammatory network, to reversible thiol oxidation in proteomes, to the role of glutamine synthetase in peripheral and central environments on inflammation and insulin resistance, to bioanalytical aspects of tyrosine nitrated proteins, to protein oxidation in human smokers and models thereof, and to Alzheimer disease, including articles on the brain ubiquitinylome and the "triangle of death" composed of oxidatively modified proteins involved in energy metabolism, mammalian target of rampamycin activation, and the proteostasis network. This Forum on Redox Proteomics is both timely and a critically important resource to highlight one of the key tools needed to better understand protein structure and function in oxidative environments in health and disease. Antioxid. Redox Signal. 26, 277-279.

Proteomics of Skeletal Muscle: Focus on Insulin Resistance and Exercise Biology

PubMed Central

Deshmukh, Atul S.

2016-01-01

Skeletal muscle is the largest tissue in the human body and plays an important role in locomotion and whole body metabolism. It accounts for ~80% of insulin stimulated glucose disposal. Skeletal muscle insulin resistance, a primary feature of Type 2 diabetes, is caused by a decreased ability of muscle to respond to circulating insulin. Physical exercise improves insulin sensitivity and whole body metabolism and remains one of the most promising interventions for the prevention of Type 2 diabetes. Insulin resistance and exercise adaptations in skeletal muscle might be a cause, or consequence, of altered protein expressions profiles and/or their posttranslational modifications (PTMs). Mass spectrometry (MS)-based proteomics offer enormous promise for investigating the molecular mechanisms underlying skeletal muscle insulin resistance and exercise-induced adaptation; however, skeletal muscle proteomics are challenging. This review describes the technical limitations of skeletal muscle proteomics as well as emerging developments in proteomics workflow with respect to samples preparation, liquid chromatography (LC), MS and computational analysis. These technologies have not yet been fully exploited in the field of skeletal muscle proteomics. Future studies that involve state-of-the-art proteomics technology will broaden our understanding of exercise-induced adaptations as well as molecular pathogenesis of insulin resistance. This could lead to the identification of new therapeutic targets. PMID:28248217

Multi-target detection and positioning in crowds using multiple camera surveillance

NASA Astrophysics Data System (ADS)

Huang, Jiahu; Zhu, Qiuyu; Xing, Yufeng

2018-04-01

In this study, we propose a pixel correspondence algorithm for positioning in crowds based on constraints on the distance between lines of sight, grayscale differences, and height in a world coordinates system. First, a Gaussian mixture model is used to obtain the background and foreground from multi-camera videos. Second, the hair and skin regions are extracted as regions of interest. Finally, the correspondences between each pixel in the region of interest are found under multiple constraints and the targets are positioned by pixel clustering. The algorithm can provide appropriate redundancy information for each target, which decreases the risk of losing targets due to a large viewing angle and wide baseline. To address the correspondence problem for multiple pixels, we construct a pixel-based correspondence model based on a similar permutation matrix, which converts the correspondence problem into a linear programming problem where a similar permutation matrix is found by minimizing an objective function. The correct pixel correspondences can be obtained by determining the optimal solution of this linear programming problem and the three-dimensional position of the targets can also be obtained by pixel clustering. Finally, we verified the algorithm with multiple cameras in experiments, which showed that the algorithm has high accuracy and robustness.

Hair-bundle proteomes of avian and mammalian inner-ear utricles

PubMed Central

Wilmarth, Phillip A.; Krey, Jocelyn F.; Shin, Jung-Bum; Choi, Dongseok; David, Larry L.; Barr-Gillespie, Peter G.

2015-01-01

Examination of multiple proteomics datasets within or between species increases the reliability of protein identification. We report here proteomes of inner-ear hair bundles from three species (chick, mouse, and rat), which were collected on LTQ or LTQ Velos ion-trap mass spectrometers; the constituent proteins were quantified using MS2 intensities, which are the summed intensities of all peptide fragmentation spectra matched to a protein. The data are available via ProteomeXchange with identifiers PXD002410 (chick LTQ), PXD002414 (chick Velos), PXD002415 (mouse Velos), and PXD002416 (rat LTQ). The two chick bundle datasets compared favourably to a third, already-described chick bundle dataset, which was quantified using MS1 peak intensities, the summed intensities of peptides identified by high-resolution mass spectrometry (PXD000104; updated analysis in PXD002445). The mouse bundle dataset described here was comparable to a different mouse bundle dataset quantified using MS1 intensities (PXD002167). These six datasets will be useful for identifying the core proteome of vestibular hair bundles. PMID:26645194

Quantitative proteomic analysis reveals novel mitochondrial targets of estrogen deficiency in the aged female rat heart.

PubMed

Lancaster, T S; Jefferson, S J; Hunter, J Craig; Lopez, Veronica; Van Eyk, J E; Lakatta, E G; Korzick, D H

2012-10-17

The incidence of myocardial infarction rises sharply at menopause, implicating a potential role for estrogen (E(2)) loss in age-related increases in ischemic injury. We aimed to identify quantitative changes to the cardiac mitochondrial proteome of aging females, based on the hypothesis that E(2) deficiency exacerbates age-dependent disruptions in mitochondrial proteins. Mitochondria isolated from left ventricles of adult (6 mo) and aged (24 mo) F344 ovary-intact or ovariectomized (OVX) rats were labeled with 8plex isobaric tags for relative and absolute quantification (iTRAQ; n = 5-6/group). Groups studied were adult, adult OVX, aged, and aged OVX. In vivo coronary artery ligation and in vitro mitochondrial respiration studies were also performed in a subset of rats. We identified 965 proteins across groups and significant directional changes in 67 proteins of aged and/or aged OVX; 32 proteins were unique to aged OVX. Notably, only six proteins were similarly altered in adult OVX (voltage-dependent ion channel 1, adenine nucleotide translocator 1, cytochrome c oxidase subunits VIIc and VIc, catalase, and myosin binding protein C). Proteins affected by aging were primarily related to cellular metabolism, oxidative stress, and cell death. The largest change occurred in monoamine oxidase-A (MAO-A), a source of oxidative stress. While acute MAO-A inhibition induced mild uncoupling in aged mitochondria, reductions in infarct size were not observed. Age-dependent alterations in mitochondrial signaling indicate a highly selective myocardial response to E(2) deficiency. The combined proteomic and functional approaches described here offer possibility of new protein targets for experimentation and therapeutic intervention in the aged female population.

Laser Capture Microdissection in the Genomic and Proteomic Era: Targeting the Genetic Basis of Cancer

PubMed Central

Domazet, Barbara; MacLennan, Gregory T.; Lopez-Beltran, Antonio; Montironi, Rodolfo; Cheng, Liang

2008-01-01

The advent of new technologies has enabled deeper insight into processes atsubcellular levels, which will ultimately improve diagnostic procedures and patient outcome. Thanks to cell enrichment methods, it is now possible to study cells in their native environment. This has greatly contributed to a rapid growth in several areas, such as gene expression analysis, proteomics, and metabolonomics. Laser capture microdissection (LCM) as a method of procuring subpopulations of cells under direct visual inspection is playing an important role in these areas. This review provides an overview of existing LCM technology and its downstream applications in genomics, proteomics, diagnostics and therapy. PMID:18787684

Laser capture microdissection in the genomic and proteomic era: targeting the genetic basis of cancer.

PubMed

Domazet, Barbara; Maclennan, Gregory T; Lopez-Beltran, Antonio; Montironi, Rodolfo; Cheng, Liang

2008-03-15

The advent of new technologies has enabled deeper insight into processes at subcellular levels, which will ultimately improve diagnostic procedures and patient outcome. Thanks to cell enrichment methods, it is now possible to study cells in their native environment. This has greatly contributed to a rapid growth in several areas, such as gene expression analysis, proteomics, and metabolonomics. Laser capture microdissection (LCM) as a method of procuring subpopulations of cells under direct visual inspection is playing an important role in these areas. This review provides an overview of existing LCM technology and its downstream applications in genomics, proteomics, diagnostics and therapy.

Multiple targets detection method in detection of UWB through-wall radar

NASA Astrophysics Data System (ADS)

Yang, Xiuwei; Yang, Chuanfa; Zhao, Xingwen; Tian, Xianzhong

2017-11-01

In this paper, the problems and difficulties encountered in the detection of multiple moving targets by UWB radar are analyzed. The experimental environment and the penetrating radar system are established. An adaptive threshold method based on local area is proposed to effectively filter out clutter interference The objective of the moving target is analyzed, and the false target is further filtered out by extracting the target feature. Based on the correlation between the targets, the target matching algorithm is proposed to improve the detection accuracy. Finally, the effectiveness of the above method is verified by practical experiment.

Proteomics research in India: an update.

PubMed

Reddy, Panga Jaipal; Atak, Apurva; Ghantasala, Saicharan; Kumar, Saurabh; Gupta, Shabarni; Prasad, T S Keshava; Zingde, Surekha M; Srivastava, Sanjeeva

2015-09-08

After a successful completion of the Human Genome Project, deciphering the mystery surrounding the human proteome posed a major challenge. Despite not being largely involved in the Human Genome Project, the Indian scientific community contributed towards proteomic research along with the global community. Currently, more than 76 research/academic institutes and nearly 145 research labs are involved in core proteomic research across India. The Indian researchers have been major contributors in drafting the "human proteome map" along with international efforts. In addition to this, virtual proteomics labs, proteomics courses and remote triggered proteomics labs have helped to overcome the limitations of proteomics education posed due to expensive lab infrastructure. The establishment of Proteomics Society, India (PSI) has created a platform for the Indian proteomic researchers to share ideas, research collaborations and conduct annual conferences and workshops. Indian proteomic research is really moving forward with the global proteomics community in a quest to solve the mysteries of proteomics. A draft map of the human proteome enhances the enthusiasm among intellectuals to promote proteomic research in India to the world.This article is part of a Special Issue entitled: Proteomics in India. Copyright © 2015 Elsevier B.V. All rights reserved.

Proteomic Analysis of Cerebrospinal Fluid in a Fulminant Case of Multiple Sclerosis

PubMed Central

Füvesi, Judit; Hanrieder, Jörg; Bencsik, Krisztina; Rajda, Cecilia; Kovács, S. Krisztián; Kaizer, László; Beniczky, Sándor; Vécsei, László; Bergquist, Jonas

2012-01-01

Multiple Sclerosis (MS) is a chronic disease, but in rare fulminant cases rapid progression may lead to death shortly after diagnosis. Currently there is no diagnostic test to predict disease course. The aim of this study was to identify potential biomarkers/proteins related to rapid progression. We present the case history of a 15-year-old male MS patient. Cerebrospinal fluid (CSF) was taken at diagnosis and at the time of rapid progression leading to the patient’s death. Using isobaric tag labeling and nanoflow liquid chromatography in conjunction with matrix assisted laser desorption/ionization time of flight tandem mass spectrometry we quantitatively analyzed the protein content of two CSF samples from the patient with fulminant MS as well as one relapsing-remitting (RR) MS patient and one control headache patient, whose CSF analysis was normal. Seventy-eight proteins were identified and seven proteins were found to be more abundant in both fulminant MS samples but not in the RR MS sample compared to the control. These proteins are involved in the immune response, blood coagulation, cell proliferation and cell adhesion. In conclusion, in this pilot study we were able to show differences in the CSF proteome of a rapidly progressing MS patient compared to a more typical clinical form of MS and a control subject. PMID:22837721

Proteomic analyses of host and pathogen responses during bovine mastitis.

PubMed

Boehmer, Jamie L

2011-12-01

The pursuit of biomarkers for use as clinical screening tools, measures for early detection, disease monitoring, and as a means for assessing therapeutic responses has steadily evolved in human and veterinary medicine over the past two decades. Concurrently, advances in mass spectrometry have markedly expanded proteomic capabilities for biomarker discovery. While initial mass spectrometric biomarker discovery endeavors focused primarily on the detection of modulated proteins in human tissues and fluids, recent efforts have shifted to include proteomic analyses of biological samples from food animal species. Mastitis continues to garner attention in veterinary research due mainly to affiliated financial losses and food safety concerns over antimicrobial use, but also because there are only a limited number of efficacious mastitis treatment options. Accordingly, comparative proteomic analyses of bovine milk have emerged in recent years. Efforts to prevent agricultural-related food-borne illness have likewise fueled an interest in the proteomic evaluation of several prominent strains of bacteria, including common mastitis pathogens. The interest in establishing biomarkers of the host and pathogen responses during bovine mastitis stems largely from the need to better characterize mechanisms of the disease, to identify reliable biomarkers for use as measures of early detection and drug efficacy, and to uncover potentially novel targets for the development of alternative therapeutics. The following review focuses primarily on comparative proteomic analyses conducted on healthy versus mastitic bovine milk. However, a comparison of the host defense proteome of human and bovine milk and the proteomic analysis of common veterinary pathogens are likewise introduced.

UNiquant, a program for quantitative proteomics analysis using stable isotope labeling.

PubMed

Huang, Xin; Tolmachev, Aleksey V; Shen, Yulei; Liu, Miao; Huang, Lin; Zhang, Zhixin; Anderson, Gordon A; Smith, Richard D; Chan, Wing C; Hinrichs, Steven H; Fu, Kai; Ding, Shi-Jian

2011-03-04

Stable isotope labeling (SIL) methods coupled with nanoscale liquid chromatography and high resolution tandem mass spectrometry are increasingly useful for elucidation of the proteome-wide differences between multiple biological samples. Development of more effective programs for the sensitive identification of peptide pairs and accurate measurement of the relative peptide/protein abundance are essential for quantitative proteomic analysis. We developed and evaluated the performance of a new program, termed UNiquant, for analyzing quantitative proteomics data using stable isotope labeling. UNiquant was compared with two other programs, MaxQuant and Mascot Distiller, using SILAC-labeled complex proteome mixtures having either known or unknown heavy/light ratios. For the SILAC-labeled Jeko-1 cell proteome digests with known heavy/light ratios (H/L = 1:1, 1:5, and 1:10), UNiquant quantified a similar number of peptide pairs as MaxQuant for the H/L = 1:1 and 1:5 mixtures. In addition, UNiquant quantified significantly more peptides than MaxQuant and Mascot Distiller in the H/L = 1:10 mixtures. UNiquant accurately measured relative peptide/protein abundance without the need for postmeasurement normalization of peptide ratios, which is required by the other programs.

UNiquant, a Program for Quantitative Proteomics Analysis Using Stable Isotope Labeling

PubMed Central

Huang, Xin; Tolmachev, Aleksey V.; Shen, Yulei; Liu, Miao; Huang, Lin; Zhang, Zhixin; Anderson, Gordon A.; Smith, Richard D.; Chan, Wing C.; Hinrichs, Steven H.; Fu, Kai; Ding, Shi-Jian

2011-01-01

Stable isotope labeling (SIL) methods coupled with nanoscale liquid chromatography and high resolution tandem mass spectrometry are increasingly useful for elucidation of the proteome-wide differences between multiple biological samples. Development of more effective programs for the sensitive identification of peptide pairs and accurate measurement of the relative peptide/protein abundance are essential for quantitative proteomic analysis. We developed and evaluated the performance of a new program, termed UNiquant, for analyzing quantitative proteomics data using stable isotope labeling. UNiquant was compared with two other programs, MaxQuant and Mascot Distiller, using SILAC-labeled complex proteome mixtures having either known or unknown heavy/light ratios. For the SILAC-labeled Jeko-1 cell proteome digests with known heavy/light ratios (H/L = 1:1, 1:5, and 1:10), UNiquant quantified a similar number of peptide pairs as MaxQuant for the H/L = 1:1 and 1:5 mixtures. In addition, UNiquant quantified significantly more peptides than MaxQuant and Mascot Distiller in the H/L = 1:10 mixtures. UNiquant accurately measured relative peptide/protein abundance without the need for post-measurement normalization of peptide ratios, which is required by the other programs. PMID:21158445

Waveform Optimization for Target Estimation by Cognitive Radar with Multiple Antennas.

PubMed

Yao, Yu; Zhao, Junhui; Wu, Lenan

2018-05-29

A new scheme based on Kalman filtering to optimize the waveforms of an adaptive multi-antenna radar system for target impulse response (TIR) estimation is presented. This work aims to improve the performance of TIR estimation by making use of the temporal correlation between successive received signals, and minimize the mean square error (MSE) of TIR estimation. The waveform design approach is based upon constant learning from the target feature at the receiver. Under the multiple antennas scenario, a dynamic feedback loop control system is established to real-time monitor the change in the target features extracted form received signals. The transmitter adapts its transmitted waveform to suit the time-invariant environment. Finally, the simulation results show that, as compared with the waveform design method based on the MAP criterion, the proposed waveform design algorithm is able to improve the performance of TIR estimation for extended targets with multiple iterations, and has a relatively lower level of complexity.

Elucidating structural and molecular mechanisms of β-arrestin-biased agonism at GPCRs via MS-based proteomics.

PubMed

Xiao, Kunhong; Sun, Jinpeng

2018-01-01

The discovery of β-arrestin-dependent GPCR signaling has led to an exciting new field in GPCR pharmacology: to develop "biased agonists" that can selectively target a specific downstream signaling pathway that elicits beneficial therapeutic effects without activating other pathways that elicit negative side effects. This new trend in GPCR drug discovery requires us to understand the structural and molecular mechanisms of β-arrestin-biased agonism, which largely remain unclear. We have used cutting-edge mass spectrometry (MS)-based proteomics, combined with systems, chemical and structural biology to study protein function, macromolecular interaction, protein expression and posttranslational modifications in the β-arrestin-dependent GPCR signaling. These high-throughput proteomic studies have provided a systems view of β-arrestin-biased agonism from several perspectives: distinct receptor phosphorylation barcode, multiple receptor conformations, distinct β-arrestin conformations, and ligand-specific signaling. The information obtained from these studies offers new insights into the molecular basis of GPCR regulation by β-arrestin and provides a potential platform for developing novel therapeutic interventions through GPCRs. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparative analysis of methicillin-sensitive and resistant Staphylococcus aureus exposed to emodin based on proteomic profiling.

PubMed

Ji, Xiaoyu; Liu, Xiaoqiang; Peng, Yuanxia; Zhan, Ruoting; Xu, Hui; Ge, Xijin

2017-12-09

Emodin has a strong antibacterial activity, including methicillin-resistant Staphylococcus aureus (MRSA). However, the mechanism by which emodin induces growth inhibition against MRSA remains unclear. In this study, the isobaric tags for relative and absolute quantitation (iTRAQ) proteomics approach was used to investigate the modes of action of emodin on a MRSA isolate and methicillin-sensitive S. aureus ATCC29213(MSSA). Proteomic analysis showed that expression levels of 145 and 122 proteins were changed significantly in MRSA and MSSA, respectively, after emodin treatment. Comparative analysis of the functions of differentially expressed proteins between the two strains was performed via bioinformatics tools blast2go and STRING database. Proteins related to pyruvate pathway imbalance induction, protein synthesis inhibition, and DNA synthesis suppression were found in both methicillin-sensitive and resistant strains. Moreover, Interference proteins related to membrane damage mechanism were also observed in MRSA. Our findings indicate that emodin is a potential antibacterial agent targeting MRSA via multiple mechanisms. Copyright © 2017 Elsevier Inc. All rights reserved.

Quantitative iTRAQ LC-MS/MS proteomics reveals metabolic responses to biofuel ethanol in cyanobacterial Synechocystis sp. PCC 6803.

PubMed

Qiao, Jianjun; Wang, Jiangxin; Chen, Lei; Tian, Xiaoxu; Huang, Siqiang; Ren, Xiaoyue; Zhang, Weiwen

2012-11-02

Recent progress in metabolic engineering has led to autotrophic production of ethanol in various cyanobacterial hosts. However, cyanobacteria are known to be sensitive to ethanol, which restricts further efforts to increase ethanol production levels in these renewable host systems. To understand the mechanisms of ethanol tolerance so that engineering more robust cyanobacterial hosts can be possible, in this study, the responses of model cyanobacterial Synechocystis sp. PCC 6803 to ethanol were determined using a quantitative proteomics approach with iTRAQ LC-MS/MS technologies. The resulting high-quality proteomic data set consisted of 24,887 unique peptides corresponding to 1509 identified proteins, a coverage of approximately 42% of the predicted proteins in the Synechocystis genome. Using a cutoff of 1.5-fold change and a p-value less than 0.05, 135 and 293 unique proteins with differential abundance levels were identified between control and ethanol-treated samples at 24 and 48 h, respectively. Functional analysis showed that the Synechocystis cells employed a combination of induced common stress response, modifications of cell membrane and envelope, and induction of multiple transporters and cell mobility-related proteins as protection mechanisms against ethanol toxicity. Interestingly, our proteomic analysis revealed that proteins related to multiple aspects of photosynthesis were up-regulated in the ethanol-treated Synechocystis cells, consistent with increased chlorophyll a concentration in the cells upon ethanol exposure. The study provided the first comprehensive view of the complicated molecular mechanisms against ethanol stress and also provided a list of potential gene targets for further engineering ethanol tolerance in Synechocystis PCC 6803.

Chimeric origins of ochrophytes and haptophytes revealed through an ancient plastid proteome

PubMed Central

Dorrell, Richard G; Gile, Gillian; McCallum, Giselle; Méheust, Raphaël; Bapteste, Eric P; Klinger, Christen M; Brillet-Guéguen, Loraine; Freeman, Katalina D; Richter, Daniel J; Bowler, Chris

2017-01-01

Plastids are supported by a wide range of proteins encoded within the nucleus and imported from the cytoplasm. These plastid-targeted proteins may originate from the endosymbiont, the host, or other sources entirely. Here, we identify and characterise 770 plastid-targeted proteins that are conserved across the ochrophytes, a major group of algae including diatoms, pelagophytes and kelps, that possess plastids derived from red algae. We show that the ancestral ochrophyte plastid proteome was an evolutionary chimera, with 25% of its phylogenetically tractable nucleus-encoded proteins deriving from green algae. We additionally show that functional mixing of host and plastid proteomes, such as through dual-targeting, is an ancestral feature of plastid evolution. Finally, we detect a clear phylogenetic signal from one ochrophyte subgroup, the lineage containing pelagophytes and dictyochophytes, in plastid-targeted proteins from another major algal lineage, the haptophytes. This may represent a possible serial endosymbiosis event deep in eukaryotic evolutionary history. DOI: http://dx.doi.org/10.7554/eLife.23717.001 PMID:28498102

Targeted Proteomics to Assess the Response to Anti-Angiogenic Treatment in Human Glioblastoma (GBM).

PubMed

Demeure, Kevin; Fack, Fred; Duriez, Elodie; Tiemann, Katja; Bernard, Amandine; Golebiewska, Anna; Bougnaud, Sébastien; Bjerkvig, Rolf; Domon, Bruno; Niclou, Simone P

2016-02-01

Glioblastoma (GBM) is a highly aggressive primary brain tumor with dismal outcome for affected patients. Because of the significant neo-angiogenesis exhibited by GBMs, anti-angiogenic therapies have been intensively evaluated during the past years. Recent clinical studies were however disappointing, although a subpopulation of patients may benefit from such treatment. We have previously shown that anti-angiogenic targeting in GBM increases hypoxia and leads to a metabolic adaptation toward glycolysis, suggesting that combination treatments also targeting the glycolytic phenotype may be effective in GBM patients. The aim of this study was to identify marker proteins that are altered by treatment and may serve as a short term readout of anti-angiogenic therapy. Ultimately such proteins could be tested as markers of efficacy able to identify patient subpopulations responsive to the treatment. We applied a proteomics approach based on selected reaction monitoring (SRM) to precisely quantify targeted protein candidates, selected from pathways related to metabolism, apoptosis and angiogenesis. The workflow was developed in the context of patient-derived intracranial GBM xenografts developed in rodents and ensured the specific identification of human tumor versus rodent stroma-derived proteins. Quality control experiments were applied to assess sample heterogeneity and reproducibility of SRM assays at different levels. The data demonstrate that tumor specific proteins can be precisely quantified within complex biological samples, reliably identifying small concentration differences induced by the treatment. In line with previous work, we identified decreased levels of TCA cycle enzymes, including isocitrate dehydrogenase, whereas malectin, calnexin, and lactate dehydrogenase A were augmented after treatment. We propose the most responsive proteins of our subset as potential novel biomarkers to assess treatment response after anti-angiogenic therapy that warrant future

Targeted Proteomics to Assess the Response to Anti-Angiogenic Treatment in Human Glioblastoma (GBM)*

PubMed Central

Demeure, Kevin; Fack, Fred; Duriez, Elodie; Tiemann, Katja; Bernard, Amandine; Golebiewska, Anna; Bougnaud, Sébastien; Bjerkvig, Rolf; Domon, Bruno; Niclou, Simone P.

2016-01-01

Glioblastoma (GBM) is a highly aggressive primary brain tumor with dismal outcome for affected patients. Because of the significant neo-angiogenesis exhibited by GBMs, anti-angiogenic therapies have been intensively evaluated during the past years. Recent clinical studies were however disappointing, although a subpopulation of patients may benefit from such treatment. We have previously shown that anti-angiogenic targeting in GBM increases hypoxia and leads to a metabolic adaptation toward glycolysis, suggesting that combination treatments also targeting the glycolytic phenotype may be effective in GBM patients. The aim of this study was to identify marker proteins that are altered by treatment and may serve as a short term readout of anti-angiogenic therapy. Ultimately such proteins could be tested as markers of efficacy able to identify patient subpopulations responsive to the treatment. We applied a proteomics approach based on selected reaction monitoring (SRM) to precisely quantify targeted protein candidates, selected from pathways related to metabolism, apoptosis and angiogenesis. The workflow was developed in the context of patient-derived intracranial GBM xenografts developed in rodents and ensured the specific identification of human tumor versus rodent stroma-derived proteins. Quality control experiments were applied to assess sample heterogeneity and reproducibility of SRM assays at different levels. The data demonstrate that tumor specific proteins can be precisely quantified within complex biological samples, reliably identifying small concentration differences induced by the treatment. In line with previous work, we identified decreased levels of TCA cycle enzymes, including isocitrate dehydrogenase, whereas malectin, calnexin, and lactate dehydrogenase A were augmented after treatment. We propose the most responsive proteins of our subset as potential novel biomarkers to assess treatment response after anti-angiogenic therapy that warrant future

Comparative proteomic assessment of matrisome enrichment methodologies.

PubMed

Krasny, Lukas; Paul, Angela; Wai, Patty; Howard, Beatrice A; Natrajan, Rachael C; Huang, Paul H

2016-11-01

The matrisome is a complex and heterogeneous collection of extracellular matrix (ECM) and ECM-associated proteins that play important roles in tissue development and homeostasis. While several strategies for matrisome enrichment have been developed, it is currently unknown how the performance of these different methodologies compares in the proteomic identification of matrisome components across multiple tissue types. In the present study, we perform a comparative proteomic assessment of two widely used decellularisation protocols and two extraction methods to characterise the matrisome in four murine organs (heart, mammary gland, lung and liver). We undertook a systematic evaluation of the performance of the individual methods on protein yield, matrisome enrichment capability and the ability to isolate core matrisome and matrisome-associated components. Our data find that sodium dodecyl sulphate (SDS) decellularisation leads to the highest matrisome enrichment efficiency, while the extraction protocol that comprises chemical and trypsin digestion of the ECM fraction consistently identifies the highest number of matrisomal proteins across all types of tissue examined. Matrisome enrichment had a clear benefit over non-enriched tissue for the comprehensive identification of matrisomal components in murine liver and heart. Strikingly, we find that all four matrisome enrichment methods led to significant losses in the soluble matrisome-associated proteins across all organs. Our findings highlight the multiple factors (including tissue type, matrisome class of interest and desired enrichment purity) that influence the choice of enrichment methodology, and we anticipate that these data will serve as a useful guide for the design of future proteomic studies of the matrisome. © 2016 The Author(s).

Comparative proteomic assessment of matrisome enrichment methodologies

PubMed Central

Krasny, Lukas; Paul, Angela; Wai, Patty; Howard, Beatrice A.; Natrajan, Rachael C.; Huang, Paul H.

2016-01-01

The matrisome is a complex and heterogeneous collection of extracellular matrix (ECM) and ECM-associated proteins that play important roles in tissue development and homeostasis. While several strategies for matrisome enrichment have been developed, it is currently unknown how the performance of these different methodologies compares in the proteomic identification of matrisome components across multiple tissue types. In the present study, we perform a comparative proteomic assessment of two widely used decellularisation protocols and two extraction methods to characterise the matrisome in four murine organs (heart, mammary gland, lung and liver). We undertook a systematic evaluation of the performance of the individual methods on protein yield, matrisome enrichment capability and the ability to isolate core matrisome and matrisome-associated components. Our data find that sodium dodecyl sulphate (SDS) decellularisation leads to the highest matrisome enrichment efficiency, while the extraction protocol that comprises chemical and trypsin digestion of the ECM fraction consistently identifies the highest number of matrisomal proteins across all types of tissue examined. Matrisome enrichment had a clear benefit over non-enriched tissue for the comprehensive identification of matrisomal components in murine liver and heart. Strikingly, we find that all four matrisome enrichment methods led to significant losses in the soluble matrisome-associated proteins across all organs. Our findings highlight the multiple factors (including tissue type, matrisome class of interest and desired enrichment purity) that influence the choice of enrichment methodology, and we anticipate that these data will serve as a useful guide for the design of future proteomic studies of the matrisome. PMID:27589945

Molecular Approach to Targeted Therapy for Multiple Sclerosis.

PubMed

Sherbet, Gajanan V

2016-01-01

The development and evolution of targeted therapy to any disease require the identification of targets amenable to treatment of patients. Here the pathogenetic signalling systems involved in multiple sclerosis are scrutinised to locate nodes of deregulation and dysfunction in order to devise strategies of drug development for targeted intervention. Oliogoclonal bands (OCB) are isoelectric focusing profiles of immunoglobulins synthesised in the central nervous system. OCBs enable the diagnosis of multiple sclerosis with high sensitivity and specificity and are related to the course of the disease and progression. The OCB patterns can be linked with the expression of angiogenic molecular species. Angiogenic signalling which has also been implicated in demyelination provides the option of using angiogenesis inhibitors in disease control. The PI3K (phosphoinositide 3-kinase)/Akt axis has emerged with a key role in myelination with its demonstrable links with mTOR mediated transcription of downstream target genes. Inflammatory signals and innate and acquired immunity from the activation of NF-κB (nuclear factor κB) responsive genes are considered. NF-κB signalling could be implicated in myelination. The transcription factor STAT (signal transducers and activators of transcription) and the EBV (Epstein- Barr virus) transcription factor BZLF1 contributing significantly to the disease process are a major environmental factor linked to MS. EBV can activate TGF (transforming growth factor) and VEGF (vascular endothelial growth factor) signalling. EBV microRNAs are reviewed as signalling mediators of pathogenesis. Stem cell transplantation therapy has lately gained much credence, so the current status of mesenchymal and hematopoietic stem cell therapy is reviewed with emphasis on the differential expression immune-related genes and operation of signalling systems.

Technical advances in proteomics: new developments in data-independent acquisition.

PubMed

Hu, Alex; Noble, William S; Wolf-Yadlin, Alejandro

2016-01-01

The ultimate aim of proteomics is to fully identify and quantify the entire complement of proteins and post-translational modifications in biological samples of interest. For the last 15 years, liquid chromatography-tandem mass spectrometry (LC-MS/MS) in data-dependent acquisition (DDA) mode has been the standard for proteomics when sampling breadth and discovery were the main objectives; multiple reaction monitoring (MRM) LC-MS/MS has been the standard for targeted proteomics when precise quantification, reproducibility, and validation were the main objectives. Recently, improvements in mass spectrometer design and bioinformatics algorithms have resulted in the rediscovery and development of another sampling method: data-independent acquisition (DIA). DIA comprehensively and repeatedly samples every peptide in a protein digest, producing a complex set of mass spectra that is difficult to interpret without external spectral libraries. Currently, DIA approaches the identification breadth of DDA while achieving the reproducible quantification characteristic of MRM or its newest version, parallel reaction monitoring (PRM). In comparative de novo identification and quantification studies in human cell lysates, DIA identified up to 89% of the proteins detected in a comparable DDA experiment while providing reproducible quantification of over 85% of them. DIA analysis aided by spectral libraries derived from prior DIA experiments or auxiliary DDA data produces identification and quantification as reproducible and precise as that achieved by MRM/PRM, except on low‑abundance peptides that are obscured by stronger signals. DIA is still a work in progress toward the goal of sensitive, reproducible, and precise quantification without external spectral libraries. New software tools applied to DIA analysis have to deal with deconvolution of complex spectra as well as proper filtering of false positives and false negatives. However, the future outlook is positive, and various

Proteomic Approach for Extracting Cytoplasmic Proteins from Streptococcus sanguinis using Mass Spectrometry

PubMed Central

El-Rami, Fadi; Nelson, Kristina; Xu, Ping

2017-01-01

Streptococcus sanguinis is a commensal and early colonizer of oral cavity as well as an opportunistic pathogen of infectious endocarditis. Extracting the soluble proteome of this bacterium provides deep insights about the physiological dynamic changes under different growth and stress conditions, thus defining “proteomic signatures” as targets for therapeutic intervention. In this protocol, we describe an experimentally verified approach to extract maximal cytoplasmic proteins from Streptococcus sanguinis SK36 strain. A combination of procedures was adopted that broke the thick cell wall barrier and minimized denaturation of the intracellular proteome, using optimized buffers and a sonication step. Extracted proteome was quantitated using Pierce BCA Protein Quantitation assay and protein bands were macroscopically assessed by Coomassie Blue staining. Finally, a high resolution detection of the extracted proteins was conducted through Synapt G2Si mass spectrometer, followed by label-free relative quantification via Progenesis QI. In conclusion, this pipeline for proteomic extraction and analysis of soluble proteins provides a fundamental tool in deciphering the biological complexity of Streptococcus sanguinis. PMID:29152022

Bioinformatics for spermatogenesis: annotation of male reproduction based on proteomics

PubMed Central

Zhou, Tao; Zhou, Zuo-Min; Guo, Xue-Jiang

2013-01-01

Proteomics strategies have been widely used in the field of male reproduction, both in basic and clinical research. Bioinformatics methods are indispensable in proteomics-based studies and are used for data presentation, database construction and functional annotation. In the present review, we focus on the functional annotation of gene lists obtained through qualitative or quantitative methods, summarizing the common and male reproduction specialized proteomics databases. We introduce several integrated tools used to find the hidden biological significance from the data obtained. We further describe in detail the information on male reproduction derived from Gene Ontology analyses, pathway analyses and biomedical analyses. We provide an overview of bioinformatics annotations in spermatogenesis, from gene function to biological function and from biological function to clinical application. On the basis of recently published proteomics studies and associated data, we show that bioinformatics methods help us to discover drug targets for sperm motility and to scan for cancer-testis genes. In addition, we summarize the online resources relevant to male reproduction research for the exploration of the regulation of spermatogenesis. PMID:23852026

Comparative shotgun proteomics using spectral count data and quasi-likelihood modeling.

PubMed

Li, Ming; Gray, William; Zhang, Haixia; Chung, Christine H; Billheimer, Dean; Yarbrough, Wendell G; Liebler, Daniel C; Shyr, Yu; Slebos, Robbert J C

2010-08-06

Shotgun proteomics provides the most powerful analytical platform for global inventory of complex proteomes using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and allows a global analysis of protein changes. Nevertheless, sampling of complex proteomes by current shotgun proteomics platforms is incomplete, and this contributes to variability in assessment of peptide and protein inventories by spectral counting approaches. Thus, shotgun proteomics data pose challenges in comparing proteomes from different biological states. We developed an analysis strategy using quasi-likelihood Generalized Linear Modeling (GLM), included in a graphical interface software package (QuasiTel) that reads standard output from protein assemblies created by IDPicker, an HTML-based user interface to query shotgun proteomic data sets. This approach was compared to four other statistical analysis strategies: Student t test, Wilcoxon rank test, Fisher's Exact test, and Poisson-based GLM. We analyzed the performance of these tests to identify differences in protein levels based on spectral counts in a shotgun data set in which equimolar amounts of 48 human proteins were spiked at different levels into whole yeast lysates. Both GLM approaches and the Fisher Exact test performed adequately, each with their unique limitations. We subsequently compared the proteomes of normal tonsil epithelium and HNSCC using this approach and identified 86 proteins with differential spectral counts between normal tonsil epithelium and HNSCC. We selected 18 proteins from this comparison for verification of protein levels between the individual normal and tumor tissues using liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM-MS). This analysis confirmed the magnitude and direction of the protein expression differences in all 6 proteins for which reliable data could be obtained. Our analysis demonstrates that shotgun proteomic data sets from different tissue phenotypes are

Comparative Shotgun Proteomics Using Spectral Count Data and Quasi-Likelihood Modeling

PubMed Central

2010-01-01

Shotgun proteomics provides the most powerful analytical platform for global inventory of complex proteomes using liquid chromatography−tandem mass spectrometry (LC−MS/MS) and allows a global analysis of protein changes. Nevertheless, sampling of complex proteomes by current shotgun proteomics platforms is incomplete, and this contributes to variability in assessment of peptide and protein inventories by spectral counting approaches. Thus, shotgun proteomics data pose challenges in comparing proteomes from different biological states. We developed an analysis strategy using quasi-likelihood Generalized Linear Modeling (GLM), included in a graphical interface software package (QuasiTel) that reads standard output from protein assemblies created by IDPicker, an HTML-based user interface to query shotgun proteomic data sets. This approach was compared to four other statistical analysis strategies: Student t test, Wilcoxon rank test, Fisher’s Exact test, and Poisson-based GLM. We analyzed the performance of these tests to identify differences in protein levels based on spectral counts in a shotgun data set in which equimolar amounts of 48 human proteins were spiked at different levels into whole yeast lysates. Both GLM approaches and the Fisher Exact test performed adequately, each with their unique limitations. We subsequently compared the proteomes of normal tonsil epithelium and HNSCC using this approach and identified 86 proteins with differential spectral counts between normal tonsil epithelium and HNSCC. We selected 18 proteins from this comparison for verification of protein levels between the individual normal and tumor tissues using liquid chromatography−multiple reaction monitoring mass spectrometry (LC−MRM-MS). This analysis confirmed the magnitude and direction of the protein expression differences in all 6 proteins for which reliable data could be obtained. Our analysis demonstrates that shotgun proteomic data sets from different tissue

Proteomics and Systems Biology: Current and Future Applications in the Nutritional Sciences1

PubMed Central

Moore, J. Bernadette; Weeks, Mark E.

2011-01-01

In the last decade, advances in genomics, proteomics, and metabolomics have yielded large-scale datasets that have driven an interest in global analyses, with the objective of understanding biological systems as a whole. Systems biology integrates computational modeling and experimental biology to predict and characterize the dynamic properties of biological systems, which are viewed as complex signaling networks. Whereas the systems analysis of disease-perturbed networks holds promise for identification of drug targets for therapy, equally the identified critical network nodes may be targeted through nutritional intervention in either a preventative or therapeutic fashion. As such, in the context of the nutritional sciences, it is envisioned that systems analysis of normal and nutrient-perturbed signaling networks in combination with knowledge of underlying genetic polymorphisms will lead to a future in which the health of individuals will be improved through predictive and preventative nutrition. Although high-throughput transcriptomic microarray data were initially most readily available and amenable to systems analysis, recent technological and methodological advances in MS have contributed to a linear increase in proteomic investigations. It is now commonplace for combined proteomic technologies to generate complex, multi-faceted datasets, and these will be the keystone of future systems biology research. This review will define systems biology, outline current proteomic methodologies, highlight successful applications of proteomics in nutrition research, and discuss the challenges for future applications of systems biology approaches in the nutritional sciences. PMID:22332076

PeroxisomeDB: a database for the peroxisomal proteome, functional genomics and disease

PubMed Central

Schlüter, Agatha; Fourcade, Stéphane; Domènech-Estévez, Enric; Gabaldón, Toni; Huerta-Cepas, Jaime; Berthommier, Guillaume; Ripp, Raymond; Wanders, Ronald J. A.; Poch, Olivier; Pujol, Aurora

2007-01-01

Peroxisomes are essential organelles of eukaryotic origin, ubiquitously distributed in cells and organisms, playing key roles in lipid and antioxidant metabolism. Loss or malfunction of peroxisomes causes more than 20 fatal inherited conditions. We have created a peroxisomal database () that includes the complete peroxisomal proteome of Homo sapiens and Saccharomyces cerevisiae, by gathering, updating and integrating the available genetic and functional information on peroxisomal genes. PeroxisomeDB is structured in interrelated sections ‘Genes’, ‘Functions’, ‘Metabolic pathways’ and ‘Diseases’, that include hyperlinks to selected features of NCBI, ENSEMBL and UCSC databases. We have designed graphical depictions of the main peroxisomal metabolic routes and have included updated flow charts for diagnosis. Precomputed BLAST, PSI-BLAST, multiple sequence alignment (MUSCLE) and phylogenetic trees are provided to assist in direct multispecies comparison to study evolutionary conserved functions and pathways. Highlights of the PeroxisomeDB include new tools developed for facilitating (i) identification of novel peroxisomal proteins, by means of identifying proteins carrying peroxisome targeting signal (PTS) motifs, (ii) detection of peroxisomes in silico, particularly useful for screening the deluge of newly sequenced genomes. PeroxisomeDB should contribute to the systematic characterization of the peroxisomal proteome and facilitate system biology approaches on the organelle. PMID:17135190

Development of proteome-wide binding reagents for research and diagnostics.

PubMed

Taussig, Michael J; Schmidt, Ronny; Cook, Elizabeth A; Stoevesandt, Oda

2013-12-01

Alongside MS, antibodies and other specific protein-binding molecules have a special place in proteomics as affinity reagents in a toolbox of applications for determining protein location, quantitative distribution and function (affinity proteomics). The realisation that the range of research antibodies available, while apparently vast is nevertheless still very incomplete and frequently of uncertain quality, has stimulated projects with an objective of raising comprehensive, proteome-wide sets of protein binders. With progress in automation and throughput, a remarkable number of recent publications refer to the practical possibility of selecting binders to every protein encoded in the genome. Here we review the requirements of a pipeline of production of protein binders for the human proteome, including target prioritisation, antigen design, 'next generation' methods, databases and the approaches taken by ongoing projects in Europe and the USA. While the task of generating affinity reagents for all human proteins is complex and demanding, the benefits of well-characterised and quality-controlled pan-proteome binder resources for biomedical research, industry and life sciences in general would be enormous and justify the effort. Given the technical, personnel and financial resources needed to fulfil this aim, expansion of current efforts may best be addressed through large-scale international collaboration. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Review: Proteomics in Retinal Artery Occlusion, Retinal Vein Occlusion, Diabetic Retinopathy and Acquired Macular Disorders

PubMed Central

Cehofski, Lasse Jørgensen; Honoré, Bent; Vorum, Henrik

2017-01-01

Retinal artery occlusion (RAO), retinal vein occlusion (RVO), diabetic retinopathy (DR) and age-related macular degeneration (AMD) are frequent ocular diseases with potentially sight-threatening outcomes. In the present review we discuss major findings of proteomic studies of RAO, RVO, DR and AMD, including an overview of ocular proteome changes associated with anti-vascular endothelial growth factor (VEGF) treatments. Despite the severe outcomes of RAO, the proteome of the disease remains largely unstudied. There is also limited knowledge about the proteome of RVO, but proteomic studies suggest that RVO is associated with remodeling of the extracellular matrix and adhesion processes. Proteomic studies of DR have resulted in the identification of potential therapeutic targets such as carbonic anhydrase-I. Proliferative diabetic retinopathy is the most intensively studied stage of DR. Proteomic studies have established VEGF, pigment epithelium-derived factor (PEDF) and complement components as key factors associated with AMD. The aim of this review is to highlight the major milestones in proteomics in RAO, RVO, DR and AMD. Through large-scale protein analyses, proteomics is bringing new important insights into these complex pathological conditions. PMID:28452939

MASPECTRAS: a platform for management and analysis of proteomics LC-MS/MS data

PubMed Central

Hartler, Jürgen; Thallinger, Gerhard G; Stocker, Gernot; Sturn, Alexander; Burkard, Thomas R; Körner, Erik; Rader, Robert; Schmidt, Andreas; Mechtler, Karl; Trajanoski, Zlatko

2007-01-01

Background The advancements of proteomics technologies have led to a rapid increase in the number, size and rate at which datasets are generated. Managing and extracting valuable information from such datasets requires the use of data management platforms and computational approaches. Results We have developed the MAss SPECTRometry Analysis System (MASPECTRAS), a platform for management and analysis of proteomics LC-MS/MS data. MASPECTRAS is based on the Proteome Experimental Data Repository (PEDRo) relational database schema and follows the guidelines of the Proteomics Standards Initiative (PSI). Analysis modules include: 1) import and parsing of the results from the search engines SEQUEST, Mascot, Spectrum Mill, X! Tandem, and OMSSA; 2) peptide validation, 3) clustering of proteins based on Markov Clustering and multiple alignments; and 4) quantification using the Automated Statistical Analysis of Protein Abundance Ratios algorithm (ASAPRatio). The system provides customizable data retrieval and visualization tools, as well as export to PRoteomics IDEntifications public repository (PRIDE). MASPECTRAS is freely available at Conclusion Given the unique features and the flexibility due to the use of standard software technology, our platform represents significant advance and could be of great interest to the proteomics community. PMID:17567892

Wheat proteomics: proteome modulation and abiotic stress acclimation

PubMed Central

Komatsu, Setsuko; Kamal, Abu H. M.; Hossain, Zahed

2014-01-01

Cellular mechanisms of stress sensing and signaling represent the initial plant responses to adverse conditions. The development of high-throughput “Omics” techniques has initiated a new era of the study of plant molecular strategies for adapting to environmental changes. However, the elucidation of stress adaptation mechanisms in plants requires the accurate isolation and characterization of stress-responsive proteins. Because the functional part of the genome, namely the proteins and their post-translational modifications, are critical for plant stress responses, proteomic studies provide comprehensive information about the fine-tuning of cellular pathways that primarily involved in stress mitigation. This review summarizes the major proteomic findings related to alterations in the wheat proteomic profile in response to abiotic stresses. Moreover, the strengths and weaknesses of different sample preparation techniques, including subcellular protein extraction protocols, are discussed in detail. The continued development of proteomic approaches in combination with rapidly evolving bioinformatics tools and interactive databases will facilitate understanding of the plant mechanisms underlying stress tolerance. PMID:25538718

Fuzzy Neural Network-Based Interacting Multiple Model for Multi-Node Target Tracking Algorithm

PubMed Central

Sun, Baoliang; Jiang, Chunlan; Li, Ming

2016-01-01

An interacting multiple model for multi-node target tracking algorithm was proposed based on a fuzzy neural network (FNN) to solve the multi-node target tracking problem of wireless sensor networks (WSNs). Measured error variance was adaptively adjusted during the multiple model interacting output stage using the difference between the theoretical and estimated values of the measured error covariance matrix. The FNN fusion system was established during multi-node fusion to integrate with the target state estimated data from different nodes and consequently obtain network target state estimation. The feasibility of the algorithm was verified based on a network of nine detection nodes. Experimental results indicated that the proposed algorithm could trace the maneuvering target effectively under sensor failure and unknown system measurement errors. The proposed algorithm exhibited great practicability in the multi-node target tracking of WSNs. PMID:27809271

Integrated Proteomic Pipeline Using Multiple Search Engines for a Proteogenomic Study with a Controlled Protein False Discovery Rate.

PubMed

Park, Gun Wook; Hwang, Heeyoun; Kim, Kwang Hoe; Lee, Ju Yeon; Lee, Hyun Kyoung; Park, Ji Yeong; Ji, Eun Sun; Park, Sung-Kyu Robin; Yates, John R; Kwon, Kyung-Hoon; Park, Young Mok; Lee, Hyoung-Joo; Paik, Young-Ki; Kim, Jin Young; Yoo, Jong Shin

2016-11-04

In the Chromosome-Centric Human Proteome Project (C-HPP), false-positive identification by peptide spectrum matches (PSMs) after database searches is a major issue for proteogenomic studies using liquid-chromatography and mass-spectrometry-based large proteomic profiling. Here we developed a simple strategy for protein identification, with a controlled false discovery rate (FDR) at the protein level, using an integrated proteomic pipeline (IPP) that consists of four engrailed steps as follows. First, using three different search engines, SEQUEST, MASCOT, and MS-GF+, individual proteomic searches were performed against the neXtProt database. Second, the search results from the PSMs were combined using statistical evaluation tools including DTASelect and Percolator. Third, the peptide search scores were converted into E-scores normalized using an in-house program. Last, ProteinInferencer was used to filter the proteins containing two or more peptides with a controlled FDR of 1.0% at the protein level. Finally, we compared the performance of the IPP to a conventional proteomic pipeline (CPP) for protein identification using a controlled FDR of <1% at the protein level. Using the IPP, a total of 5756 proteins (vs 4453 using the CPP) including 477 alternative splicing variants (vs 182 using the CPP) were identified from human hippocampal tissue. In addition, a total of 10 missing proteins (vs 7 using the CPP) were identified with two or more unique peptides, and their tryptic peptides were validated using MS/MS spectral pattern from a repository database or their corresponding synthetic peptides. This study shows that the IPP effectively improved the identification of proteins, including alternative splicing variants and missing proteins, in human hippocampal tissues for the C-HPP. All RAW files used in this study were deposited in ProteomeXchange (PXD000395).

Proteomics of contrasting rice genotypes: Identification of potential targets for raising crops for saline environment.

PubMed

Lakra, Nita; Kaur, Charanpreet; Anwar, Khalid; Singla-Pareek, Sneh Lata; Pareek, Ashwani

2018-05-01

High salinity is one of the major problems in crop productivity, affecting seed germination as well as yield. In order to enhance tolerance of crops towards salinity, it is essential to understand the underlying physiological and molecular mechanisms. In this endeavor, study of contrasting genotypes of the same species differing in their response towards salinity stress can be very useful. In the present study, we have investigated temporal differences in morphological, physiological and proteome profiles of two contrasting genotypes of rice to understand the basis of salt tolerance. When compared to IR64 rice, Pokkali, the salt-tolerant wild genotype, has enhanced capacity to cope with stress, better growth rate and possesses efficient antioxidant system, as well as better photosynthetic machinery. Our proteome studies revealed a higher and an early abundance of proteins involved in stress tolerance and photosynthesis in Pokkali in comparison with IR64, which, in contrast, showed greater changes in metabolic machinery even during early duration of stress. Our findings suggest important differences in physicochemical and proteome profiles of the two genotypes, which may be the basis of observed stress tolerance in the salt-tolerant Pokkali. © 2017 John Wiley & Sons Ltd.

The International Proteomics Tutorial Programme (IPTP): a teaching tool box for the proteomics community.

PubMed

James, Peter

2011-09-01

The most critical functions of the various proteomics organisations are the training of young scientists and the dissemination of information to the general scientific community. The education committees of the Human Proteome Organisation (HUPO) and the European Proteomics Association (EuPA) together with their national counterparts are therefore launching the International Proteomics Tutorial Programme to meet these needs. The programme is being led by Peter James (Sweden), Thierry Rabilloud (France) and Kazuyuki Nakamura (Japan). It involves collaboration between the leading proteomics journals: Journal of Proteome Research, Journal of Proteomics, Molecular and Cellular Proteomics, and Proteomics. The overall level is aimed at Masters/PhD level students who are starting out their research and who would benefit from a solid grounding in the techniques used in modern protein-based research. The tutorial program will cover core techniques and basics as an introduction to scientists new to the field. At a later stage the programme may be expanded with a series of more advanced topics focussing on the application of proteomics techniques to biological problem solving. The entire series of articles and slides will be made freely available for teaching use at the Journals and Organisations homepages and at a special website, www.proteomicstutorials.org. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Plasmodium vivax trophozoite-stage proteomes

PubMed Central

Anderson, D.C.; Lapp, Stacey A.; Akinyi, Sheila; Meyer, Esmeralda V.S.; Barnwell, John W.; Korir-Morrison, Cindy; Galinski, Mary R.

2015-01-01

membranes. Studies of stage-specific P. vivax expressed proteomes have been limited in scope and focused mainly on pathogen proteins, thus limiting understanding of the biology of this pathogen and its host interactions. Here three P. vivax proteomes are reported from biological replicates based on purified trophozoite-infected reticulocytes from different Saimiri boliviensis infections (the main non-human primate experimental model for P. vivax biology and pathogenesis). An in-depth analysis of two of the proteomes using 2D LC/MS/MS and multiple search engines identified 1375 pathogen proteins and 3209 host proteins. Numerous functional categories of both host and pathogen proteins were identified, including several known P. vivax protein family members (e.g., PHIST, eTRAMP and VIR), and 33% of protein identifications were classified as hypothetical. Ribosome subunit proteins were noted for both P. vivax and S. boliviensis, consistent with this parasite species’ known reticulocyte host–cell specificity. In two biological replicates analyzed for post-translational modifications, hemoglobin was extensively oxidized, and various other proteins were also oxidized or nitrated in one of the two replicates. The cause of such protein modification remains to be determined but could include oxidized heme and oxygen radicals released from the infected red blood cell’s parasite-induced acidic digestive vacuoles. In any case, the data suggests the presence of distinct infection-specific conditions whereby both the pathogen and host infected red blood cell proteins may be subject to significant oxidative stress. PMID:25545414

Thermosensitivity of growth is determined by chaperone-mediated proteome reallocation

PubMed Central

Chen, Ke; Gao, Ye; Mih, Nathan; O’Brien, Edward J.; Yang, Laurence; Palsson, Bernhard O.

2017-01-01

Maintenance of a properly folded proteome is critical for bacterial survival at notably different growth temperatures. Understanding the molecular basis of thermoadaptation has progressed in two main directions, the sequence and structural basis of protein thermostability and the mechanistic principles of protein quality control assisted by chaperones. Yet we do not fully understand how structural integrity of the entire proteome is maintained under stress and how it affects cellular fitness. To address this challenge, we reconstruct a genome-scale protein-folding network for Escherichia coli and formulate a computational model, FoldME, that provides statistical descriptions of multiscale cellular response consistent with many datasets. FoldME simulations show (i) that the chaperones act as a system when they respond to unfolding stress rather than achieving efficient folding of any single component of the proteome, (ii) how the proteome is globally balanced between chaperones for folding and the complex machinery synthesizing the proteins in response to perturbation, (iii) how this balancing determines growth rate dependence on temperature and is achieved through nonspecific regulation, and (iv) how thermal instability of the individual protein affects the overall functional state of the proteome. Overall, these results expand our view of cellular regulation, from targeted specific control mechanisms to global regulation through a web of nonspecific competing interactions that modulate the optimal reallocation of cellular resources. The methodology developed in this study enables genome-scale integration of environment-dependent protein properties and a proteome-wide study of cellular stress responses. PMID:29073085

Proteomic analysis of Medulloblastoma reveals functional biology with translational potential.

PubMed

Rivero-Hinojosa, Samuel; Lau, Ling San; Stampar, Mojca; Staal, Jerome; Zhang, Huizhen; Gordish-Dressman, Heather; Northcott, Paul A; Pfister, Stefan M; Taylor, Michael D; Brown, Kristy J; Rood, Brian R

2018-06-07

Genomic characterization has begun to redefine diagnostic classifications of cancers. However, it remains a challenge to infer disease phenotypes from genomic alterations alone. To help realize the promise of genomics, we have performed a quantitative proteomics investigation using Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) and 41 tissue samples spanning the 4 genomically based subgroups of medulloblastoma and control cerebellum. We have identified and quantitated thousands of proteins across these groups and find that we are able to recapitulate the genomic subgroups based upon subgroup restricted and differentially abundant proteins while also identifying subgroup specific protein isoforms. Integrating our proteomic measurements with genomic data, we calculate a poor correlation between mRNA and protein abundance. Using EPIC 850 k methylation array data on the same tissues, we also investigate the influence of copy number alterations and DNA methylation on the proteome in an attempt to characterize the impact of these genetic features on the proteome. Reciprocally, we are able to use the proteome to identify which genomic alterations result in altered protein abundance and thus are most likely to impact biology. Finally, we are able to assemble protein-based pathways yielding potential avenues for clinical intervention. From these, we validate the EIF4F cap-dependent translation pathway as a novel druggable pathway in medulloblastoma. Thus, quantitative proteomics complements genomic platforms to yield a more complete understanding of functional tumor biology and identify novel therapeutic targets for medulloblastoma.

Investigating RAS Signaling in Cancer | Office of Cancer Clinical Proteomics Research

Cancer.gov

CPTAC expertise has been charged to develop RAS specific targeted proteomic assays to study the important pathways of human cancer. The oncogene RAS is linked to 30 percent of human cancers, but the search for a targeted therapy for RAS has remained elusive. To advance our understanding of this oncogene and to develop improved targeted therapies against RAS pathway, the National Cancer Institute (NCI) has launched a RAS Initiative.

Assay Characterization Guidance Documents | Office of Cancer Clinical Proteomics Research

Cancer.gov

CPTAC characterized assays are defined as those that meet the criteria described in the Assay Characterization Guidance Document. This guidance document aligns with recommendations by the research community as “fit-for-purpose” validation requirements of targeted proteomics assays.

Allowable carbon emissions lowered by multiple climate targets.

PubMed

Steinacher, Marco; Joos, Fortunat; Stocker, Thomas F

2013-07-11

Climate targets are designed to inform policies that would limit the magnitude and impacts of climate change caused by anthropogenic emissions of greenhouse gases and other substances. The target that is currently recognized by most world governments places a limit of two degrees Celsius on the global mean warming since preindustrial times. This would require large sustained reductions in carbon dioxide emissions during the twenty-first century and beyond. Such a global temperature target, however, is not sufficient to control many other quantities, such as transient sea level rise, ocean acidification and net primary production on land. Here, using an Earth system model of intermediate complexity (EMIC) in an observation-informed Bayesian approach, we show that allowable carbon emissions are substantially reduced when multiple climate targets are set. We take into account uncertainties in physical and carbon cycle model parameters, radiative efficiencies, climate sensitivity and carbon cycle feedbacks along with a large set of observational constraints. Within this framework, we explore a broad range of economically feasible greenhouse gas scenarios from the integrated assessment community to determine the likelihood of meeting a combination of specific global and regional targets under various assumptions. For any given likelihood of meeting a set of such targets, the allowable cumulative emissions are greatly reduced from those inferred from the temperature target alone. Therefore, temperature targets alone are unable to comprehensively limit the risks from anthropogenic emissions.

Yeast Interspecies Comparative Proteomics Reveals Divergence in Expression Profiles and Provides Insights into Proteome Resource Allocation and Evolutionary Roles of Gene Duplication*

PubMed Central

Kito, Keiji; Ito, Haruka; Nohara, Takehiro; Ohnishi, Mihoko; Ishibashi, Yuko; Takeda, Daisuke

2016-01-01

Omics analysis is a versatile approach for understanding the conservation and diversity of molecular systems across multiple taxa. In this study, we compared the proteome expression profiles of four yeast species (Saccharomyces cerevisiae, Saccharomyces mikatae, Kluyveromyces waltii, and Kluyveromyces lactis) grown on glucose- or glycerol-containing media. Conserved expression changes across all species were observed only for a small proportion of all proteins differentially expressed between the two growth conditions. Two Kluyveromyces species, both of which exhibited a high growth rate on glycerol, a nonfermentative carbon source, showed distinct species-specific expression profiles. In K. waltii grown on glycerol, proteins involved in the glyoxylate cycle and gluconeogenesis were expressed in high abundance. In K. lactis grown on glycerol, the expression of glycolytic and ethanol metabolic enzymes was unexpectedly low, whereas proteins involved in cytoplasmic translation, including ribosomal proteins and elongation factors, were highly expressed. These marked differences in the types of predominantly expressed proteins suggest that K. lactis optimizes the balance of proteome resource allocation between metabolism and protein synthesis giving priority to cellular growth. In S. cerevisiae, about 450 duplicate gene pairs were retained after whole-genome duplication. Intriguingly, we found that in the case of duplicates with conserved sequences, the total abundance of proteins encoded by a duplicate pair in S. cerevisiae was similar to that of protein encoded by nonduplicated ortholog in Kluyveromyces yeast. Given the frequency of haploinsufficiency, this observation suggests that conserved duplicate genes, even though minor cases of retained duplicates, do not exhibit a dosage effect in yeast, except for ribosomal proteins. Thus, comparative proteomic analyses across multiple species may reveal not only species-specific characteristics of metabolic processes under

False-positive rate determination of protein target discovery using a covalent modification- and mass spectrometry-based proteomics platform.

PubMed

Strickland, Erin C; Geer, M Ariel; Hong, Jiyong; Fitzgerald, Michael C

2014-01-01

Detection and quantitation of protein-ligand binding interactions is important in many areas of biological research. Stability of proteins from rates of oxidation (SPROX) is an energetics-based technique for identifying the proteins targets of ligands in complex biological mixtures. Knowing the false-positive rate of protein target discovery in proteome-wide SPROX experiments is important for the correct interpretation of results. Reported here are the results of a control SPROX experiment in which chemical denaturation data is obtained on the proteins in two samples that originated from the same yeast lysate, as would be done in a typical SPROX experiment except that one sample would be spiked with the test ligand. False-positive rates of 1.2-2.2% and <0.8% are calculated for SPROX experiments using Q-TOF and Orbitrap mass spectrometer systems, respectively. Our results indicate that the false-positive rate is largely determined by random errors associated with the mass spectral analysis of the isobaric mass tag (e.g., iTRAQ®) reporter ions used for peptide quantitation. Our results also suggest that technical replicates can be used to effectively eliminate such false positives that result from this random error, as is demonstrated in a SPROX experiment to identify yeast protein targets of the drug, manassantin A. The impact of ion purity in the tandem mass spectral analyses and of background oxidation on the false-positive rate of protein target discovery using SPROX is also discussed.

Multiple-target tracking implementation in the ebCMOS camera system: the LUSIPHER prototype

NASA Astrophysics Data System (ADS)

Doan, Quang Tuyen; Barbier, Remi; Dominjon, Agnes; Cajgfinger, Thomas; Guerin, Cyrille

2012-06-01

The domain of the low light imaging systems progresses very fast, thanks to detection and electronic multiplication technology evolution, such as the emCCD (electron multiplying CCD) or the ebCMOS (electron bombarded CMOS). We present an ebCMOS camera system that is able to track every 2 ms more than 2000 targets with a mean number of photons per target lower than two. The point light sources (targets) are spots generated by a microlens array (Shack-Hartmann) used in adaptive optics. The Multiple-Target-Tracking designed and implemented on a rugged workstation is described. The results and the performances of the system on the identification and tracking are presented and discussed.

Combining Search Engines for Comparative Proteomics

PubMed Central

Tabb, David

2012-01-01

Many proteomics laboratories have found spectral counting to be an ideal way to recognize biomarkers that differentiate cohorts of samples. This approach assumes that proteins that differ in quantity between samples will generate different numbers of identifiable tandem mass spectra. Increasingly, researchers are employing multiple search engines to maximize the identifications generated from data collections. This talk evaluates four strategies to combine information from multiple search engines in comparative proteomics. The “Count Sum” model pools the spectra across search engines. The “Vote Counting” model combines the judgments from each search engine by protein. Two other models employ parametric and non-parametric analyses of protein-specific p-values from different search engines. We evaluated the four strategies in two different data sets. The ABRF iPRG 2009 study generated five LC-MS/MS analyses of “red” E. coli and five analyses of “yellow” E. coli. NCI CPTAC Study 6 generated five concentrations of Sigma UPS1 spiked into a yeast background. All data were identified with X!Tandem, Sequest, MyriMatch, and TagRecon. For both sample types, “Vote Counting” appeared to manage the diverse identification sets most effectively, yielding heightened discrimination as more search engines were added.

Abundance of Drug Transporters in the Human Kidney Cortex as Quantified by Quantitative Targeted Proteomics

PubMed Central

Prasad, Bhagwat; Johnson, Katherine; Billington, Sarah; Lee, Caroline; Chung, Git W.; Brown, Colin D.A.; Kelly, Edward J.; Himmelfarb, Jonathan

2016-01-01

Protein expression of renal uptake and efflux transporters was quantified by quantitative targeted proteomics using the surrogate peptide approach. Renal uptake transporters assessed in this study included organic anion transporters (OAT1–OAT4), organic cation transporter 2 (OCT2), organic/carnitine cation transporters (OCTN1 and OCTN2), and sodium-glucose transporter 2 (SGLT2); efflux transporters included P-glycoprotein, breast cancer resistance protein, multidrug resistance proteins (MRP2 and MRP4), and multidrug and toxin extrusion proteins (MATE1 and MATE2-K). Total membrane was isolated from the cortex of human kidneys (N = 41). The isolated membranes were digested by trypsin and the digest was subjected to liquid chromatography–tandem mass spectrometry analysis. The mean expression of surrogate peptides was as follows (given with the standard deviation, in picomoles per milligram of total membrane protein): OAT1 (5.3 ± 1.9), OAT2 (0.9 ± 0.3), OAT3 (3.5 ± 1.6), OAT4 (0.5 ± 0.2), OCT2 (7.4 ± 2.8), OCTN1 (1.3 ± 0.6), OCTN2 (0.6 ± 0.2), P-glycoprotein (2.1 ± 0.8), MRP2 (1.4 ± 0.6), MRP4 (0.9 ± 0.6), MATE1 (5.1 ± 2.3), and SGLT2 (3.7 ± 1.8). Breast cancer resistance protein (BCRP) and MATE2-K proteins were detectable but were below the lower limit of quantification. Interestingly, the protein expression of OAT1 and OAT3 was significantly correlated (r > 0.8). A significant correlation was also observed between expression of multiple other drug transporters, such as OATs/OCT2 or OCTN1/OCTN2, and SGLT2/OCTNs, OCT, OATs, and MRP2. These renal transporter data should be useful in deriving in vitro to in vivo scaling factors to accurately predict renal clearance and kidney epithelial cell exposure to drugs or their metabolites. PMID:27621205

Diversification of the muscle proteome through alternative splicing.

PubMed

Nakka, Kiran; Ghigna, Claudia; Gabellini, Davide; Dilworth, F Jeffrey

2018-03-06

Skeletal muscles express a highly specialized proteome that allows the metabolism of energy sources to mediate myofiber contraction. This muscle-specific proteome is partially derived through the muscle-specific transcription of a subset of genes. Surprisingly, RNA sequencing technologies have also revealed a significant role for muscle-specific alternative splicing in generating protein isoforms that give specialized function to the muscle proteome. In this review, we discuss the current knowledge with respect to the mechanisms that allow pre-mRNA transcripts to undergo muscle-specific alternative splicing while identifying some of the key trans-acting splicing factors essential to the process. The importance of specific splicing events to specialized muscle function is presented along with examples in which dysregulated splicing contributes to myopathies. Though there is now an appreciation that alternative splicing is a major contributor to proteome diversification, the emergence of improved "targeted" proteomic methodologies for detection of specific protein isoforms will soon allow us to better appreciate the extent to which alternative splicing modifies the activity of proteins (and their ability to interact with other proteins) in the skeletal muscle. In addition, we highlight a continued need to better explore the signaling pathways that contribute to the temporal control of trans-acting splicing factor activity to ensure specific protein isoforms are expressed in the proper cellular context. An understanding of the signal-dependent and signal-independent events driving muscle-specific alternative splicing has the potential to provide us with novel therapeutic strategies to treat different myopathies.

PeptideDepot: flexible relational database for visual analysis of quantitative proteomic data and integration of existing protein information.

PubMed

Yu, Kebing; Salomon, Arthur R

2009-12-01

Recently, dramatic progress has been achieved in expanding the sensitivity, resolution, mass accuracy, and scan rate of mass spectrometers able to fragment and identify peptides through MS/MS. Unfortunately, this enhanced ability to acquire proteomic data has not been accompanied by a concomitant increase in the availability of flexible tools allowing users to rapidly assimilate, explore, and analyze this data and adapt to various experimental workflows with minimal user intervention. Here we fill this critical gap by providing a flexible relational database called PeptideDepot for organization of expansive proteomic data sets, collation of proteomic data with available protein information resources, and visual comparison of multiple quantitative proteomic experiments. Our software design, built upon the synergistic combination of a MySQL database for safe warehousing of proteomic data with a FileMaker-driven graphical user interface for flexible adaptation to diverse workflows, enables proteomic end-users to directly tailor the presentation of proteomic data to the unique analysis requirements of the individual proteomics lab. PeptideDepot may be deployed as an independent software tool or integrated directly with our high throughput autonomous proteomic pipeline used in the automated acquisition and post-acquisition analysis of proteomic data.

Pressurized Pepsin Digestion in Proteomics

PubMed Central

López-Ferrer, Daniel; Petritis, Konstantinos; Robinson, Errol W.; Hixson, Kim K.; Tian, Zhixin; Lee, Jung Hwa; Lee, Sang-Won; Tolić, Nikola; Weitz, Karl K.; Belov, Mikhail E.; Smith, Richard D.; Paša-Tolić, Ljiljana

2011-01-01

Integrated top-down bottom-up proteomics combined with on-line digestion has great potential to improve the characterization of protein isoforms in biological systems and is amendable to high throughput proteomics experiments. Bottom-up proteomics ultimately provides the peptide sequences derived from the tandem MS analyses of peptides after the proteome has been digested. Top-down proteomics conversely entails the MS analyses of intact proteins for more effective characterization of genetic variations and/or post-translational modifications. Herein, we describe recent efforts toward efficient integration of bottom-up and top-down LC-MS-based proteomics strategies. Since most proteomics separations utilize acidic conditions, we exploited the compatibility of pepsin (where the optimal digestion conditions are at low pH) for integration into bottom-up and top-down proteomics work flows. Pressure-enhanced pepsin digestions were successfully performed and characterized with several standard proteins in either an off-line mode using a Barocycler or an on-line mode using a modified high pressure LC system referred to as a fast on-line digestion system (FOLDS). FOLDS was tested using pepsin and a whole microbial proteome, and the results were compared against traditional trypsin digestions on the same platform. Additionally, FOLDS was integrated with a RePlay configuration to demonstrate an ultrarapid integrated bottom-up top-down proteomics strategy using a standard mixture of proteins and a monkey pox virus proteome. PMID:20627868

Proteomic characterization of Withaferin A-targeted protein networks for the treatment of monoclonal myeloma gammopathies.

PubMed

Dom, Martin; Offner, Fritz; Vanden Berghe, Wim; Van Ostade, Xaveer

2018-05-15

Withaferin A (WA), a natural steroid lactone from the plant Withania somnifera, is often studied because of its antitumor properties. Although many in vitro and in vivo studies have been performed, the identification of Withaferin A protein targets and its mechanism of antitumor action remain incomplete. We used quantitative chemoproteomics and differential protein expression analysis to characterize the WA antitumor effects on a multiple myeloma cell model. Identified relevant targets were further validated by Ingenuity Pathway Analysis and Western blot and indicate that WA targets protein networks that are specific for monoclonal gammopathy of undetermined significance (MGUS) and other closely related disorders, such as multiple myeloma (MM) and Waldenström macroglobulinemia (WM). By blocking the PSMB10 proteasome subunit, downregulation of ANXA4, potential association with HDAC6 and upregulation of HMOX1, WA puts a massive blockage on both proteotoxic and oxidative stress responses pathways, leaving cancer cells defenseless against WA induced stresses. These results indicate that WA mediated apoptosis is preceded by simultaneous targeting of cellular stress response pathways like proteasome degradation, autophagy and unfolded protein stress response and thus suggests that WA can be used as an effective treatment for MGUS and other closely related disorders. Multifunctional antitumor compounds are of great potential since they reduce the risk of multidrug resistance in chemotherapy. Unfortunately, characterization of all protein targets of a multifunctional compound is lacking. Therefore, we optimized an SILAC quantitative chemoproteomics workflow to identify the potential protein targets of Withaferin A (WA), a natural multifunctional compound with promising antitumor properties. To further understand the antitumor mechanisms of WA, we performed a differential protein expression analysis and combined the altered expression data with chemoproteome WA target data

Targeting of a Nuclease to Murine Leukemia Virus Capsids Inhibits Viral Multiplication

NASA Astrophysics Data System (ADS)

Natsoulis, Georges; Seshaiah, Partha; Federspiel, Mark J.; Rein, Alan; Hughes, Stephen H.; Boeke, Jef D.

1995-01-01

Capsid-targeted viral inactivation is an antiviral strategy in which toxic fusion proteins are targeted to virions, where they inhibit viral multiplication by destroying viral components. These fusion proteins consist of a virion structural protein moiety and an enzymatic moiety such as a nuclease. Such fusion proteins can severely inhibit transposition of yeast retrotransposon Ty1, an element whose transposition mechanistically resembles retroviral multiplication. We demonstrate that expression of a murine retrovirus capsid-staphylococcal nuclease fusion protein inhibits multiplication of the corresponding murine leukemia virus by 30- to 100-fold. Staphylococcal nuclease is apparently inactive intracellularly and hence nontoxic to the host cell, but it is active extracellularly because of its requirement for high concentrations of Ca2+ ions. Virions assembled in and shed from cells expressing the fusion protein contain very small amounts of intact viral RNA, as would be predicted for nuclease-mediated inhibition of viral multiplication.

The HUPO proteomics standards initiative--overcoming the fragmentation of proteomics data.

PubMed

Hermjakob, Henning

2006-09-01

Proteomics is a key field of modern biomolecular research, with many small and large scale efforts producing a wealth of proteomics data. However, the vast majority of this data is never exploited to its full potential. Even in publicly funded projects, often the raw data generated in a specific context is analysed, conclusions are drawn and published, but little attention is paid to systematic documentation, archiving, and public access to the data supporting the scientific results. It is often difficult to validate the results stated in a particular publication, and even simple global questions like "In which cellular contexts has my protein of interest been observed?" can currently not be answered with realistic effort, due to a lack of standardised reporting and collection of proteomics data. The Proteomics Standards Initiative (PSI), a work group of the Human Proteome Organisation (HUPO), defines community standards for data representation in proteomics to facilitate systematic data capture, comparison, exchange and verification. In this article we provide an overview of PSI organisational structure, activities, and current results, as well as ways to get involved in the broad-based, open PSI process.

Altered proteomic polymorphisms in the caterpillar body and stroma of natural Cordyceps sinensis during maturation.

PubMed

Dong, Yun-Zi; Zhang, Li-Juan; Wu, Zi-Mei; Gao, Ling; Yao, Yi-Sang; Tan, Ning-Zhi; Wu, Jian-Yong; Ni, Luqun; Zhu, Jia-Shi

2014-01-01

To examine the maturational changes in proteomic polymorphisms resulting from differential expression by multiple intrinsic fungi in the caterpillar body and stroma of natural Cordyceps sinensis (Cs), an integrated micro-ecosystem. The surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) biochip technique was used to profile the altered protein compositions in the caterpillar body and stroma of Cs during its maturation. The MS chromatograms were analyzed using density-weighted algorithms to examine the similarities and cluster relationships among the proteomic polymorphisms of the Cs compartments and the mycelial products Hirsutella sinensis (Hs) and Paecilomyces hepiali (Ph). SELDI-TOF MS chromatograms displayed dynamic proteomic polymorphism alterations among samples from the different Cs compartments during maturation. More than 1,900 protein bands were analyzed using density-weighted ZUNIX similarity equations and clustering methods, revealing integral polymorphism similarities of 57.4% between the premature and mature stromata and 42.8% between the premature and mature caterpillar bodies. The across-compartment similarity was low, ranging from 10.0% to 18.4%. Consequently, each Cs compartment (i.e., the stroma and caterpillar body) formed a clustering clade, and the 2 clades formed a Cs cluster. The polymorphic similarities ranged from 0.51% to 1.04% between Hs and the Cs compartments and were 2.8- to 4.8-fold higher (1.92%-4.34%) between Ph and the Cs compartments. The Hs and Ph mycelial samples formed isolated clades outside of the Cs cluster. Proteomic polymorphisms in the caterpillar body and stroma of Cs change dynamically during maturation. The proteomic polymorphisms in Hs and Ph differ from those in Cs, suggesting the presence of multiple Cs-associated fungi and multiple Ophiocordyceps sinensis genotypes with altered differential protein expression in the Cs compartments during maturation. In conjunction with

Altered Proteomic Polymorphisms in the Caterpillar Body and Stroma of Natural Cordyceps sinensis during Maturation

PubMed Central

Wu, Zi-Mei; Gao, Ling; Yao, Yi-Sang; Tan, Ning-Zhi; Wu, Jian-Yong; Ni, Luqun; Zhu, Jia-Shi

2014-01-01

Objective To examine the maturational changes in proteomic polymorphisms resulting from differential expression by multiple intrinsic fungi in the caterpillar body and stroma of natural Cordyceps sinensis (Cs), an integrated micro-ecosystem. Methods The surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) biochip technique was used to profile the altered protein compositions in the caterpillar body and stroma of Cs during its maturation. The MS chromatograms were analyzed using density-weighted algorithms to examine the similarities and cluster relationships among the proteomic polymorphisms of the Cs compartments and the mycelial products Hirsutella sinensis (Hs) and Paecilomyces hepiali (Ph). Results: SELDI-TOF MS chromatograms displayed dynamic proteomic polymorphism alterations among samples from the different Cs compartments during maturation. More than 1,900 protein bands were analyzed using density-weighted ZUNIX similarity equations and clustering methods, revealing integral polymorphism similarities of 57.4% between the premature and mature stromata and 42.8% between the premature and mature caterpillar bodies. The across-compartment similarity was low, ranging from 10.0% to 18.4%. Consequently, each Cs compartment (i.e., the stroma and caterpillar body) formed a clustering clade, and the 2 clades formed a Cs cluster. The polymorphic similarities ranged from 0.51% to 1.04% between Hs and the Cs compartments and were 2.8- to 4.8-fold higher (1.92%–4.34%) between Ph and the Cs compartments. The Hs and Ph mycelial samples formed isolated clades outside of the Cs cluster. Conclusion Proteomic polymorphisms in the caterpillar body and stroma of Cs change dynamically during maturation. The proteomic polymorphisms in Hs and Ph differ from those in Cs, suggesting the presence of multiple Cs-associated fungi and multiple Ophiocordyceps sinensis genotypes with altered differential protein expression in the Cs compartments

Targeted proteomics reveals strain-specific changes in the mouse insulin and central metabolic pathways after a sustained high-fat diet.

PubMed

Sabidó, Eduard; Wu, Yibo; Bautista, Lucia; Porstmann, Thomas; Chang, Ching-Yun; Vitek, Olga; Stoffel, Markus; Aebersold, Ruedi

2013-07-16

The metabolic syndrome is a collection of risk factors including obesity, insulin resistance and hepatic steatosis, which occur together and increase the risk of diseases such as diabetes, cardiovascular disease and cancer. In spite of intense research, the complex etiology of insulin resistance and its association with the accumulation of triacylglycerides in the liver and with hepatic steatosis remains not completely understood. Here, we performed quantitative measurements of 144 proteins involved in the insulin-signaling pathway and central metabolism in liver homogenates of two genetically well-defined mouse strains C57BL/6J and 129Sv that were subjected to a sustained high-fat diet. We used targeted mass spectrometry by selected reaction monitoring (SRM) to generate accurate and reproducible quantitation of the targeted proteins across 36 different samples (12 conditions and 3 biological replicates), generating one of the largest quantitative targeted proteomics data sets in mammalian tissues. Our results revealed rapid response to high-fat diet that diverged early in the feeding regimen, and evidenced a response to high-fat diet dominated by the activation of peroxisomal β-oxidation in C57BL/6J and by lipogenesis in 129Sv mice.

Quantitative body fluid proteomics in medicine - A focus on minimal invasiveness.

PubMed

Csősz, Éva; Kalló, Gergő; Márkus, Bernadett; Deák, Eszter; Csutak, Adrienne; Tőzsér, József

2017-02-05

Identification of new biomarkers specific for various pathological conditions is an important field in medical sciences. Body fluids have emerging potential in biomarker studies especially those which are continuously available and can be collected by non-invasive means. Changes in the protein composition of body fluids such as tears, saliva, sweat, etc. may provide information on both local and systemic conditions of medical relevance. In this review, our aim is to discuss the quantitative proteomics techniques used in biomarker studies, and to present advances in quantitative body fluid proteomics of non-invasively collectable body fluids with relevance to biomarker identification. The advantages and limitations of the widely used quantitative proteomics techniques are also presented. Based on the reviewed literature, we suggest an ideal pipeline for body fluid analyses aiming at biomarkers discoveries: starting from identification of biomarker candidates by shotgun quantitative proteomics or protein arrays, through verification of potential biomarkers by targeted mass spectrometry, to the antibody-based validation of biomarkers. The importance of body fluids as a rich source of biomarkers is discussed. Quantitative proteomics is a challenging part of proteomics applications. The body fluids collected by non-invasive means have high relevance in medicine; they are good sources for biomarkers used in establishing the diagnosis, follow up of disease progression and predicting high risk groups. The review presents the most widely used quantitative proteomics techniques in body fluid analysis and lists the potential biomarkers identified in tears, saliva, sweat, nasal mucus and urine for local and systemic diseases. Copyright © 2016 Elsevier B.V. All rights reserved.

The proteomic profile of hair damage.

PubMed

Sinclair, R; Flagler, M J; Jones, L; Rufaut, N; Davis, M G

2012-06-01

Monilethrix is a congenital hair shaft disorder with associated fragility. Many of the changes seen in monilethrix hair on light microscopy and scanning electron microscopy are also seen in hair weathering and cosmetic damage to hair. We used monilethrix as a model to investigate the relationship between hair protein structure and hair strength and resistance to cosmetic insult. We applied proteomic techniques to identify novel peptide damage markers for chemical oxidative damage to hair. The findings suggest that specific sites in the protein structure of hair are targeted during oxidative damage from bleaching, a unique insight into how chemical damage compromises the structural integrity of the hair shaft at the molecular level. Applying proteomics to the study of congenital and acquired hair shaft disorders can deliver new insights into hair damage and novel strategies to strengthen hair. © 2012 The Authors. BJD © 2012 British Association of Dermatologists.

Making proteomics data accessible and reusable: current state of proteomics databases and repositories.

PubMed

Perez-Riverol, Yasset; Alpi, Emanuele; Wang, Rui; Hermjakob, Henning; Vizcaíno, Juan Antonio

2015-03-01

Compared to other data-intensive disciplines such as genomics, public deposition and storage of MS-based proteomics, data are still less developed due to, among other reasons, the inherent complexity of the data and the variety of data types and experimental workflows. In order to address this need, several public repositories for MS proteomics experiments have been developed, each with different purposes in mind. The most established resources are the Global Proteome Machine Database (GPMDB), PeptideAtlas, and the PRIDE database. Additionally, there are other useful (in many cases recently developed) resources such as ProteomicsDB, Mass Spectrometry Interactive Virtual Environment (MassIVE), Chorus, MaxQB, PeptideAtlas SRM Experiment Library (PASSEL), Model Organism Protein Expression Database (MOPED), and the Human Proteinpedia. In addition, the ProteomeXchange consortium has been recently developed to enable better integration of public repositories and the coordinated sharing of proteomics information, maximizing its benefit to the scientific community. Here, we will review each of the major proteomics resources independently and some tools that enable the integration, mining and reuse of the data. We will also discuss some of the major challenges and current pitfalls in the integration and sharing of the data. © 2014 The Authors. PROTEOMICS published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Advances in Quantitative Proteomics of Microbes and Microbial Communities

NASA Astrophysics Data System (ADS)

Waldbauer, J.; Zhang, L.; Rizzo, A. I.

2015-12-01

Quantitative measurements of gene expression are key to developing a mechanistic, predictive understanding of how microbial metabolism drives many biogeochemical fluxes and responds to environmental change. High-throughput RNA-sequencing can afford a wealth of information about transcript-level expression patterns, but it is becoming clear that expression dynamics are often very different at the protein level where biochemistry actually occurs. These divergent dynamics between levels of biological organization necessitate quantitative proteomic measurements to address many biogeochemical questions. The protein-level expression changes that underlie shifts in the magnitude, or even the direction, of metabolic and biogeochemical fluxes can be quite subtle and test the limits of current quantitative proteomics techniques. Here we describe methodologies for high-precision, whole-proteome quantification that are applicable to both model organisms of biogeochemical interest that may not be genetically tractable, and to complex community samples from natural environments. Employing chemical derivatization of peptides with multiple isotopically-coded tags, this strategy is rapid and inexpensive, can be implemented on a wide range of mass spectrometric instrumentation, and is relatively insensitive to chromatographic variability. We demonstrate the utility of this quantitative proteomics approach in application to both isolates and natural communities of sulfur-metabolizing and photosynthetic microbes.

Redefining the Breast Cancer Exosome Proteome by Tandem Mass Tag Quantitative Proteomics and Multivariate Cluster Analysis.

PubMed

Clark, David J; Fondrie, William E; Liao, Zhongping; Hanson, Phyllis I; Fulton, Amy; Mao, Li; Yang, Austin J

2015-10-20

Exosomes are microvesicles of endocytic origin constitutively released by multiple cell types into the extracellular environment. With evidence that exosomes can be detected in the blood of patients with various malignancies, the development of a platform that uses exosomes as a diagnostic tool has been proposed. However, it has been difficult to truly define the exosome proteome due to the challenge of discerning contaminant proteins that may be identified via mass spectrometry using various exosome enrichment strategies. To better define the exosome proteome in breast cancer, we incorporated a combination of Tandem-Mass-Tag (TMT) quantitative proteomics approach and Support Vector Machine (SVM) cluster analysis of three conditioned media derived fractions corresponding to a 10 000g cellular debris pellet, a 100 000g crude exosome pellet, and an Optiprep enriched exosome pellet. The quantitative analysis identified 2 179 proteins in all three fractions, with known exosomal cargo proteins displaying at least a 2-fold enrichment in the exosome fraction based on the TMT protein ratios. Employing SVM cluster analysis allowed for the classification 251 proteins as "true" exosomal cargo proteins. This study provides a robust and vigorous framework for the future development of using exosomes as a potential multiprotein marker phenotyping tool that could be useful in breast cancer diagnosis and monitoring disease progression.

Systems biology approaches and tools for analysis of interactomes and multi-target drugs.

PubMed

Schrattenholz, André; Groebe, Karlfried; Soskic, Vukic

2010-01-01

diseases" remains a most pressing medical need. Currently, a change of paradigm can be observed with regard to a new interest in agents that modulate multiple targets simultaneously, essentially "dirty drugs." Targeting cellular function as a system rather than on the level of the single target, significantly increases the size of the drugable proteome and is expected to introduce novel classes of multi-target drugs with fewer adverse effects and toxicity. Multiple target approaches have recently been used to design medications against atherosclerosis, cancer, depression, psychosis and neurodegenerative diseases. A focussed approach towards "systemic" drugs will certainly require the development of novel computational and mathematical concepts for appropriate modelling of complex data. But the key is the extraction of relevant molecular information from biological systems by implementing rigid statistical procedures to differential proteomic analytics.

QCloud: A cloud-based quality control system for mass spectrometry-based proteomics laboratories

PubMed Central

Chiva, Cristina; Olivella, Roger; Borràs, Eva; Espadas, Guadalupe; Pastor, Olga; Solé, Amanda

2018-01-01

The increasing number of biomedical and translational applications in mass spectrometry-based proteomics poses new analytical challenges and raises the need for automated quality control systems. Despite previous efforts to set standard file formats, data processing workflows and key evaluation parameters for quality control, automated quality control systems are not yet widespread among proteomics laboratories, which limits the acquisition of high-quality results, inter-laboratory comparisons and the assessment of variability of instrumental platforms. Here we present QCloud, a cloud-based system to support proteomics laboratories in daily quality assessment using a user-friendly interface, easy setup, automated data processing and archiving, and unbiased instrument evaluation. QCloud supports the most common targeted and untargeted proteomics workflows, it accepts data formats from different vendors and it enables the annotation of acquired data and reporting incidences. A complete version of the QCloud system has successfully been developed and it is now open to the proteomics community (http://qcloud.crg.eu). QCloud system is an open source project, publicly available under a Creative Commons License Attribution-ShareAlike 4.0. PMID:29324744

Proteomics in investigation of cancer metastasis: functional and clinical consequences and methodological challenges.

PubMed

Maryáš, Josef; Faktor, Jakub; Dvořáková, Monika; Struhárová, Iva; Grell, Peter; Bouchal, Pavel

2014-03-01

Metastases are responsible for most of the cases of death in patients with solid tumors. There is thus an urgent clinical need of better understanding the exact molecular mechanisms and finding novel therapeutics targets and biomarkers of metastatic disease of various tumors. Metastases are formed in a complicated biological process called metastatic cascade. Up to now, proteomics has enabled the identification of number of metastasis-associated proteins and potential biomarkers in cancer tissues, microdissected cells, model systems, and secretomes. Expression profiles and biological role of key proteins were confirmed in verification and functional experiments. This communication reviews these observations and analyses the methodological aspects of the proteomics approaches used. Moreover, it reviews contribution of current proteomics in the field of functional characterization and interactome analysis of proteins involved in various events in metastatic cascade. It is evident that ongoing technical progress will further increase proteome coverage and sample capacity of proteomics technologies, giving complex answers to clinical and functional questions asked. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Feature-aided multiple target tracking in the image plane

NASA Astrophysics Data System (ADS)

Brown, Andrew P.; Sullivan, Kevin J.; Miller, David J.

2006-05-01

Vast quantities of EO and IR data are collected on airborne platforms (manned and unmanned) and terrestrial platforms (including fixed installations, e.g., at street intersections), and can be exploited to aid in the global war on terrorism. However, intelligent preprocessing is required to enable operator efficiency and to provide commanders with actionable target information. To this end, we have developed an image plane tracker which automatically detects and tracks multiple targets in image sequences using both motion and feature information. The effects of platform and camera motion are compensated via image registration, and a novel change detection algorithm is applied for accurate moving target detection. The contiguous pixel blob on each moving target is segmented for use in target feature extraction and model learning. Feature-based target location measurements are used for tracking through move-stop-move maneuvers, close target spacing, and occlusion. Effective clutter suppression is achieved using joint probabilistic data association (JPDA), and confirmed target tracks are indicated for further processing or operator review. In this paper we describe the algorithms implemented in the image plane tracker and present performance results obtained with video clips from the DARPA VIVID program data collection and from a miniature unmanned aerial vehicle (UAV) flight.

Personalized medicine beyond genomics: alternative futures in big data-proteomics, environtome and the social proteome.

PubMed

Özdemir, Vural; Dove, Edward S; Gürsoy, Ulvi K; Şardaş, Semra; Yıldırım, Arif; Yılmaz, Şenay Görücü; Ömer Barlas, I; Güngör, Kıvanç; Mete, Alper; Srivastava, Sanjeeva

2017-01-01

No field in science and medicine today remains untouched by Big Data, and psychiatry is no exception. Proteomics is a Big Data technology and a next generation biomarker, supporting novel system diagnostics and therapeutics in psychiatry. Proteomics technology is, in fact, much older than genomics and dates to the 1970s, well before the launch of the international Human Genome Project. While the genome has long been framed as the master or "elite" executive molecule in cell biology, the proteome by contrast is humble. Yet the proteome is critical for life-it ensures the daily functioning of cells and whole organisms. In short, proteins are the blue-collar workers of biology, the down-to-earth molecules that we cannot live without. Since 2010, proteomics has found renewed meaning and international attention with the launch of the Human Proteome Project and the growing interest in Big Data technologies such as proteomics. This article presents an interdisciplinary technology foresight analysis and conceptualizes the terms "environtome" and "social proteome". We define "environtome" as the entire complement of elements external to the human host, from microbiome, ambient temperature and weather conditions to government innovation policies, stock market dynamics, human values, political power and social norms that collectively shape the human host spatially and temporally. The "social proteome" is the subset of the environtome that influences the transition of proteomics technology to innovative applications in society. The social proteome encompasses, for example, new reimbursement schemes and business innovation models for proteomics diagnostics that depart from the "once-a-life-time" genotypic tests and the anticipated hype attendant to context and time sensitive proteomics tests. Building on the "nesting principle" for governance of complex systems as discussed by Elinor Ostrom, we propose here a 3-tiered organizational architecture for Big Data science such as

Enterotoxigenic Escherichia coli Elicits Immune Responses to Multiple Surface Proteins▿ †

PubMed Central

Roy, Koushik; Bartels, Scott; Qadri, Firdausi; Fleckenstein, James M.

2010-01-01

Enterotoxigenic Escherichia coli (ETEC) causes considerable morbidity and mortality due to diarrheal illness in developing countries, particularly in young children. Despite the global importance of these heterogeneous pathogens, a broadly protective vaccine is not yet available. While much is known regarding the immunology of well-characterized virulence proteins, in particular the heat-labile toxin (LT) and colonization factors (CFs), to date, evaluation of the immune response to other antigens has been limited. However, the availability of genomic DNA sequences for ETEC strains coupled with proteomics technology affords opportunities to examine novel uncharacterized antigens that might also serve as targets for vaccine development. Analysis of whole or fractionated bacterial proteomes with convalescent-phase sera can potentially accelerate identification of secreted or surface-expressed targets that are recognized during the course of infection. Here we report results of an immunoproteomics approach to antigen discovery with ETEC strain H10407. Immunoblotting of proteins separated by two-dimensional electrophoresis (2DE) with sera from mice infected with strain H10407 or with convalescent human sera obtained following natural ETEC infections demonstrated multiple immunoreactive molecules in culture supernatant, outer membrane, and outer membrane vesicle preparations, suggesting that many antigens are recognized during the course of infection. Proteins identified by this approach included established virulence determinants, more recently identified putative virulence factors, as well as novel secreted and outer membrane proteins. Together, these studies suggest that existing and emerging proteomics technologies can provide a useful complement to ongoing approaches to ETEC vaccine development. PMID:20457787

Standardized protocols for quality control of MRM-based plasma proteomic workflows.

PubMed

Percy, Andrew J; Chambers, Andrew G; Smith, Derek S; Borchers, Christoph H

2013-01-04

Mass spectrometry (MS)-based proteomics is rapidly emerging as a viable technology for the identification and quantitation of biological samples, such as human plasma--the most complex yet commonly employed biofluid in clinical analyses. The transition from a qualitative to quantitative science is required if proteomics is going to successfully make the transition to a clinically useful technique. MS, however, has been criticized for a lack of reproducibility and interlaboratory transferability. Currently, the MS and plasma proteomics communities lack standardized protocols and reagents to ensure that high-quality quantitative data can be accurately and precisely reproduced by laboratories across the world using different MS technologies. Toward addressing this issue, we have developed standard protocols for multiple reaction monitoring (MRM)-based assays with customized isotopically labeled internal standards for quality control of the sample preparation workflow and the MS platform in quantitative plasma proteomic analyses. The development of reference standards and their application to a single MS platform is discussed herein, along with the results from intralaboratory tests. The tests highlighted the importance of the reference standards in assessing the efficiency and reproducibility of the entire bottom-up proteomic workflow and revealed errors related to the sample preparation and performance quality and deficits of the MS and LC systems. Such evaluations are necessary if MRM-based quantitative plasma proteomics is to be used in verifying and validating putative disease biomarkers across different research laboratories and eventually in clinical laboratories.

Recent advances in proteomic applications for schistosomiasis research: potential clinical impact.

PubMed

Sotillo, Javier; Doolan, Denise; Loukas, Alex

2017-02-01

Schistosomiasis is a neglected tropical disease affecting hundreds of millions of people worldwide. Recent advances in the field of proteomics and the development of new and highly sensitive mass spectrometers and quantitative techniques have provided new tools for advancing the molecular biology, cell biology, diagnosis and vaccine development for public health threats such as schistosomiasis. Areas covered: In this review we describe the latest advances in research that utilizes proteomics-based tools to address some of the key challenges to developing effective interventions against schistosomiasis. We also provide information about the potential of extracellular vesicles to advance the fight against this devastating disease. Expert commentary: Different proteins are already being tested as vaccines against schistosomiasis with promising results. The re-analysis of the Schistosoma spp. proteomes using new and more sensitive mass spectrometers as well as better separation approaches will help identify more vaccine targets in a rational and informed manner. In addition, the recent development of new proteome microarrays will facilitate characterisation of novel markers of infection as well as new vaccine and diagnostic candidate antigens.

Efficient search of multiple types of targets

NASA Astrophysics Data System (ADS)

Wosniack, M. E.; Raposo, E. P.; Viswanathan, G. M.; da Luz, M. G. E.

2015-12-01

Random searches often take place in fragmented landscapes. Also, in many instances like animal foraging, significant benefits to the searcher arise from visits to a large diversity of patches with a well-balanced distribution of targets found. Up to date, such aspects have been widely ignored in the usual single-objective analysis of search efficiency, in which one seeks to maximize just the number of targets found per distance traversed. Here we address the problem of determining the best strategies for the random search when these multiple-objective factors play a key role in the process. We consider a figure of merit (efficiency function), which properly "scores" the mentioned tasks. By considering random walk searchers with a power-law asymptotic Lévy distribution of step lengths, p (ℓ ) ˜ℓ-μ , with 1 <μ ≤3 , we show that the standard optimal strategy with μopt≈2 no longer holds universally. Instead, optimal searches with enhanced superdiffusivity emerge, including values as low as μopt≈1.3 (i.e., tending to the ballistic limit). For the general theory of random search optimization, our findings emphasize the necessity to correctly characterize the multitude of aims in any concrete metric to compare among possible candidates to efficient strategies. In the context of animal foraging, our results might explain some empirical data pointing to stronger superdiffusion (μ <2 ) in the search behavior of different animal species, conceivably associated to multiple goals to be achieved in fragmented landscapes.

CPTAC Releases Cancer Proteome Confirmatory Colon Study Data | Office of Cancer Clinical Proteomics Research

Cancer.gov

The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) announces the release of the cancer proteome confirmatory colon study data. The goal of the study is to analyze the proteomes of approximately 100 confirmatory colon tumor patients, which includes tumor and adjacent normal samples, with liquid chromatography-tandem mass spectrometry (LC-MS/MS) global proteomic and phosphoproteomic profiling.

Proteomics in medical microbiology.

PubMed

Cash, P

2000-04-01

The techniques of proteomics (high resolution two-dimensional electrophoresis and protein characterisation) are widely used for microbiological research to analyse global protein synthesis as an indicator of gene expression. The rapid progress in microbial proteomics has been achieved through the wide availability of whole genome sequences for a number of bacterial groups. Beyond providing a basic understanding of microbial gene expression, proteomics has also played a role in medical areas of microbiology. Progress has been made in the use of the techniques for investigating the epidemiology and taxonomy of human microbial pathogens, the identification of novel pathogenic mechanisms and the analysis of drug resistance. In each of these areas, proteomics has provided new insights that complement genomic-based investigations. This review describes the current progress in these research fields and highlights some of the technical challenges existing for the application of proteomics in medical microbiology. The latter concern the analysis of genetically heterogeneous bacterial populations and the integration of the proteomic and genomic data for these bacteria. The characterisation of the proteomes of bacterial pathogens growing in their natural hosts remains a future challenge.