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

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.

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

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.

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.

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 through affinity chromatography approach coupled with mass spectrometry, has been conventionally used to identify target proteins and has yielded good results. Curcumol, has shown effective inhibition on Nasopharyngeal Carcinoma (NPC) Cells, interacted with NCL and then initiated the anti-tumor biological effect. This research demonstrated the effectiveness of chemical proteomics approaches in natural drugs molecular target identification, revealing and understanding of the novel mechanism of actions of curcumol is crucial for cancer prevention and treatment in nasopharynx cancer. Copyright © 2018 Elsevier B.V. All rights reserved.

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/.

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.

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.

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.

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.

Development of a Targeted Urine Proteome Assay for kidney diseases.

PubMed

Cantley, Lloyd G; Colangelo, Christopher M; Stone, Kathryn L; Chung, Lisa; Belcher, Justin; Abbott, Thomas; Cantley, Jennifer L; Williams, Kenneth R; Parikh, Chirag R

2016-01-01

Since human urine is the most readily available biofluid whose proteome changes in response to disease, it is a logical sample for identifying protein biomarkers for kidney diseases. Potential biomarkers were identified by using a multiproteomics workflow to compare urine proteomes of kidney transplant patients with immediate and delayed graft function. Differentially expressed proteins were identified, and corresponding stable isotope labeled internal peptide standards were synthesized for scheduled MRM. The Targeted Urine Proteome Assay (TUPA) was then developed by identifying those peptides for which there were at least two transitions for which interference in a urine matrix across 156 MRM runs was <30%. This resulted in an assay that monitors 224 peptides from 167 quantifiable proteins. TUPA opens the way for using a robust mass spectrometric technology, MRM, for quantifying and validating biomarkers from among 167 urinary proteins. This approach, while developed using differentially expressed urinary proteins from patients with delayed versus immediate graft function after kidney transplant, can be expanded to include differentially expressed urinary proteins in multiple kidney diseases. Thus, TUPA could provide a single assay to help diagnose, prognose, and manage many kidney diseases. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

TRIC: an automated alignment strategy for reproducible protein quantification in targeted proteomics

PubMed Central

Röst, Hannes L.; Liu, Yansheng; D’Agostino, Giuseppe; Zanella, Matteo; Navarro, Pedro; Rosenberger, George; Collins, Ben C.; Gillet, Ludovic; Testa, Giuseppe; Malmström, Lars; Aebersold, Ruedi

2016-01-01

Large scale, quantitative proteomic studies have become essential for the analysis of clinical cohorts, large perturbation experiments and systems biology studies. While next-generation mass spectrometric techniques such as SWATH-MS have substantially increased throughput and reproducibility, ensuring consistent quantification of thousands of peptide analytes across multiple LC-MS/MS runs remains a challenging and laborious manual process. To produce highly consistent and quantitatively accurate proteomics data matrices in an automated fashion, we have developed the TRIC software which utilizes fragment ion data to perform cross-run alignment, consistent peak-picking and quantification for high throughput targeted proteomics. TRIC uses a graph-based alignment strategy based on non-linear retention time correction to integrate peak elution information from all LC-MS/MS runs acquired in a study. When compared to state-of-the-art SWATH-MS data analysis, the algorithm was able to reduce the identification error by more than 3-fold at constant recall, while correcting for highly non-linear chromatographic effects. On a pulsed-SILAC experiment performed on human induced pluripotent stem (iPS) cells, TRIC was able to automatically align and quantify thousands of light and heavy isotopic peak groups and substantially increased the quantitative completeness and biological information in the data, providing insights into protein dynamics of iPS cells. Overall, this study demonstrates the importance of consistent quantification in highly challenging experimental setups, and proposes an algorithm to automate this task, constituting the last missing piece in a pipeline for automated analysis of massively parallel targeted proteomics datasets. PMID:27479329

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-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.

Targeted brain proteomics uncover multiple pathways to Alzheimer's dementia.

PubMed

Yu, Lei; Petyuk, Vladislav A; Gaiteri, Chris; Mostafavi, Sara; Young-Pearse, Tracy; Shah, Raj C; Buchman, Aron S; Schneider, Julie A; Piehowski, Paul D; Sontag, Ryan L; Fillmore, Thomas L; Shi, Tujin; Smith, Richard D; De Jager, Philip L; Bennett, David A

2018-06-16

Previous gene expression analysis identified a network of co-expressed genes that is associated with β-amyloid neuropathology and cognitive decline in older adults. The current work targeted influential genes in this network with quantitative proteomics to identify potential novel therapeutic targets. Data came from 834 community-based older persons who were followed annually, died and underwent brain autopsy. Uniform structured postmortem evaluations assessed the burden of β-amyloid and other common age-related neuropathologies. Selected reaction monitoring quantified cortical protein abundance of 12 genes prioritized from a molecular network of aging human brain that is implicated in Alzheimer's dementia. Regression and linear mixed models examined the protein associations with β-amyloid load and other neuropathologic indices as well as cognitive decline over multiple years prior to death. The average age at death was 88.6 years. 349 participants (41.9%) had Alzheimer's dementia at death. A higher level of PLXNB1 abundance was associated with more β-amyloid load (p=1.0 × 10 -7 ) and higher PHFtau tangle density (p=2.3 × 10 -7 ), and the association of PLXNB1 with cognitive decline is mediated by these known Alzheimer's disease pathologies. On the other hand, higher IGFBP5, HSPB2, AK4 and lower ITPK1 levels were associated with faster cognitive decline and, unlike PLXNB1, these associations were not fully explained by common neuropathologic indices, suggesting novel mechanisms leading to cognitive decline. Using targeted proteomics, this work identified cortical proteins involved in Alzheimer's dementia and begins to dissect two different molecular pathways: one affecting β-amyloid deposition and another affecting resilience without a known pathologic footprint. This article is protected by copyright. All rights reserved. © 2018 American Neurological Association.

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.

Quantitative proteomics in cardiovascular research: global and targeted strategies

PubMed Central

Shen, Xiaomeng; Young, Rebeccah; Canty, John M.; Qu, Jun

2014-01-01

Extensive technical advances in the past decade have substantially expanded quantitative proteomics in cardiovascular research. This has great promise for elucidating the mechanisms of cardiovascular diseases (CVD) and the discovery of cardiac biomarkers used for diagnosis and treatment evaluation. Global and targeted proteomics are the two major avenues of quantitative proteomics. While global approaches enable unbiased discovery of altered proteins via relative quantification at the proteome level, targeted techniques provide higher sensitivity and accuracy, and are capable of multiplexed absolute quantification in numerous clinical/biological samples. While promising, technical challenges need to be overcome to enable full utilization of these techniques in cardiovascular medicine. Here we discuss recent advances in quantitative proteomics and summarize applications in cardiovascular research with an emphasis on biomarker discovery and elucidating molecular mechanisms of disease. We propose the integration of global and targeted strategies as a high-throughput pipeline for cardiovascular proteomics. Targeted approaches enable rapid, extensive validation of biomarker candidates discovered by global proteomics. These approaches provide a promising alternative to immunoassays and other low-throughput means currently used for limited validation. PMID:24920501

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.

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 leap brought in periodontal diagnostics by this study lies in the introduction of the well established discovery-through-verification pipeline for periodontal biomarker discovery and validation in further periodontal patient cohorts. Published under license by The American Society for Biochemistry and Molecular Biology, Inc.

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

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.

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 analysis of other classes of analytes, beyond proteomics. PMID:22261725

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.

Simultaneous generation of aptamers to multiple gamma-carboxyglutamic acid proteins from a focused aptamer library using DeSELEX and convergent selection.

PubMed

Layzer, Juliana M; Sullenger, Bruce A

2007-01-01

By using the in vitro selection method SELEX against the complex mixture of GLA proteins and utilizing methods to deconvolute the resulting ligands, we were able to successfully generate 2'-ribo purine, 2'-fluoro pyrimidine aptamers to various individual targets in the GLA protein proteome that ranged in concentration from 10 nM to 1.4 microM in plasma. Perhaps not unexpectedly, the majority of the aptamers isolated following SELEX bind the most abundant protein in the mixture, prothrombin (FII), with high affinity. We show that by deselecting the dominant prothrombin aptamer the selection can be redirected. By using this DeSELEX approach, we were able to shift the selection toward other sequences and to less abundant protein targets and obtained an aptamer to Factor IX (FIX). We also demonstrate that by using an RNA library that is focused around a proteome, purified protein targets can then be used to rapidly generate aptamers to the protein targets that are rare in the initial mixture such as Factor VII (FVII) and Factor X (FX). Moreover, for all four proteins targeted (FII, FVII, FIX, and FX), aptamers were identified that could inhibit the individual protein's activitity in coagulation assays. Thus, by applying the concepts of DeSELEX and focused library selection, aptamers specific for any protein in a particular proteome can theoretically be generated, even when the proteins in the mixture are present at very different concentrations.

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).

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

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

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.

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.

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.

An extensive library of surrogate peptides for all human proteins.

PubMed

Mohammed, Yassene; Borchers, Christoph H

2015-11-03

Selecting the most appropriate surrogate peptides to represent a target protein is a major component of experimental design in Multiple Reaction Monitoring (MRM). Our software PeptidePicker with its v-score remains distinctive in its approach of integrating information about the proteins, their tryptic peptides, and the suitability of these peptides for MRM that is available online in UniProtKB, NCBI's dbSNP, ExPASy, PeptideAtlas, PRIDE, and GPMDB. The scoring algorithm reflects our "best knowledge" for selecting candidate peptides for MRM, based on the uniqueness of the peptide in the targeted proteome, its physiochemical properties, and whether it has previously been observed. Here we present an updated approach where we have already compiled a list of all possible surrogate peptides of the human proteome. Using our stringent selection criteria, the list includes 165k suitable MRM peptides covering 17k proteins of the human reviewed proteins in UniProtKB. Compared to average of 2-4min per protein for retrieving and integrating the information, the precompiled list includes all peptides available instantly. This allows a more cohesive and faster design of a multiplexed MRM experiment and provides insights into evidence for a protein's existence. We will keep this list up-to-date as proteomics data repositories continue to grow. This article is part of a Special Issue entitled: Computational Proteomics. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

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, parental drug-sensitive MCF-7/WT cancer cells, and drug-resistant MCF-7/ADR cancer cells. Dimethylated H3R2 was also monitored in MCF-7/WT cells with the treatment of doxorubicin (DOX) for confirmation.

PROCAL: A Set of 40 Peptide Standards for Retention Time Indexing, Column Performance Monitoring, and Collision Energy Calibration.

PubMed

Zolg, Daniel Paul; Wilhelm, Mathias; Yu, Peng; Knaute, Tobias; Zerweck, Johannes; Wenschuh, Holger; Reimer, Ulf; Schnatbaum, Karsten; Kuster, Bernhard

2017-11-01

Beyond specific applications, such as the relative or absolute quantification of peptides in targeted proteomic experiments, synthetic spike-in peptides are not yet systematically used as internal standards in bottom-up proteomics. A number of retention time standards have been reported that enable chromatographic aligning of multiple LC-MS/MS experiments. However, only few peptides are typically included in such sets limiting the analytical parameters that can be monitored. Here, we describe PROCAL (ProteomeTools Calibration Standard), a set of 40 synthetic peptides that span the entire hydrophobicity range of tryptic digests, enabling not only accurate determination of retention time indices but also monitoring of chromatographic separation performance over time. The fragmentation characteristics of the peptides can also be used to calibrate and compare collision energies between mass spectrometers. The sequences of all selected peptides do not occur in any natural protein, thus eliminating the need for stable isotope labeling. We anticipate that this set of peptides will be useful for multiple purposes in individual laboratories but also aiding the transfer of data acquisition and analysis methods between laboratories, notably the use of spectral libraries. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

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.

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 and proteins provided reliable design and validation of quantitative approaches using SRM on targeted proteins proposed involved in strawberry fruit. Our data revealed the identifying candidate proteins and their quantitative changes in relation to fruit ripening and flavonoids and anthocyanin biosynthesis and regulation. More importantly, this quantitative proteomic data is also compared with chemical analysis to reveal possible control levels of this important quality trait. Although, MRM approach is not new in plant biology research, the application has been very rare. This is the first systematic multi-targeted interrogation of the possible regulation of entire pathway of flavonoids and anthocyanin biosynthesis in strawberry fruit at different ripening stages using quantitative MRM technique on mass spectrometry. Our results demonstrate the power of targeted quantitative mass spectrometry data for analysis of proteins in biological regulation. These results indicate that distinct and diverse control of flavonoids and anthocyanin biosynthesis mechanisms at metabolism and proteins levels. This important and complementary knowledge will be useful for systematically characterizing the flavonoids and anthocyanin biosynthesis pathway of any fruit/plant species. Copyright © 2015. Published by Elsevier B.V.

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

Novel biomarkers for cardiovascular risk assessment: current status and future directions.

PubMed

MacNamara, James; Eapen, Danny J; Quyyumi, Arshed; Sperling, Laurence

2015-09-01

Cardiovascular disease (CVD) is the leading cause of mortality in the modern world. Traditional risk algorithms may miss up to 20% of CVD events. Therefore, there is a need for new cardiac biomarkers. Many fields of research are dedicated to improving cardiac risk prediction, including genomics, transcriptomics and proteomics. To date, even the most promising biomarkers have only demonstrated modest associations and predictive ability. Few have undergone randomized control trials. A number of biomarkers are targets to new therapies aimed to reduce cardiovascular risk. Currently, some of the most promising risk prediction has been demonstrated with panels of multiple biomarkers. This article reviews the current state and future of proteomic biomarkers and aggregate biomarker panels.

Quantitative Proteomic Profiling the Molecular Signatures of Annexin A5 in Lung Squamous Carcinoma Cells.

PubMed

Sun, Bing; Bai, Yuxin; Zhang, Liyuan; Gong, Linlin; Qi, Xiaoyu; Li, Huizhen; Wang, Faming; Chi, Xinming; Jiang, Yulin; Shao, Shujuan

Lung cancer remains the leading cancer killer around the world. It's crucial to identify newer mechanism-based targets to effectively manage lung cancer. Annexin A5 (ANXA5) is a protein kinase C inhibitory protein and calcium dependent phospholipid-binding protein, which may act as an endogenous regulator of various pathophysiological processes. However, its molecular mechanism in lung cancer remains poorly understood. This study was designed to determine the mechanism of ANXA5 in lung cancer with a hope to obtain useful information to provide a new therapeutic target. We used a stable isotope dimethyl labeling based quantitative proteomic method to identify differentially expressed proteins in NSCLC cell lines after ANXA5 transfection. Out of 314 proteins, we identified 26 and 44 proteins that were down- and up-regulated upon ANXA5 modulation, respectively. The IPA analysis revealed that glycolysis and gluconeogenesis were the predominant pathways modulated by ANXA5. Multiple central nodes, namely HSPA5, FN1, PDIA6, ENO1, ALDOA, JUP and KRT6A appeared to occupy regulatory nodes in the protein-protein networks upon ANXA5 modulation. Taken together, ANXA5 appears to have pleotropic effects, as it modulates multiple key signaling pathways, supporting the potential usefulness of ANXA5 as a potential target in lung cancer. This study might provide a new insight into the mechanism of ANXA5 in lung cancer.

Improving transcriptome de novo assembly by using a reference genome of a related species: Translational genomics from oil palm to coconut.

PubMed

Armero, Alix; Baudouin, Luc; Bocs, Stéphanie; This, Dominique

2017-01-01

The palms are a family of tropical origin and one of the main constituents of the ecosystems of these regions around the world. The two main species of palm represent different challenges: coconut (Cocos nucifera L.) is a source of multiple goods and services in tropical communities, while oil palm (Elaeis guineensis Jacq) is the main protagonist of the oil market. In this study, we present a workflow that exploits the comparative genomics between a target species (coconut) and a reference species (oil palm) to improve the transcriptomic data, providing a proteome useful to answer functional or evolutionary questions. This workflow reduces redundancy and fragmentation, two inherent problems of transcriptomic data, while preserving the functional representation of the target species. Our approach was validated in Arabidopsis thaliana using Arabidopsis lyrata and Capsella rubella as references species. This analysis showed the high sensitivity and specificity of our strategy, relatively independent of the reference proteome. The workflow increased the length of proteins products in A. thaliana by 13%, allowing, often, to recover 100% of the protein sequence length. In addition redundancy was reduced by a factor greater than 3. In coconut, the approach generated 29,366 proteins, 1,246 of these proteins deriving from new contigs obtained with the BRANCH software. The coconut proteome presented a functional profile similar to that observed in rice and an important number of metabolic pathways related to secondary metabolism. The new sequences found with BRANCH software were enriched in functions related to biotic stress. Our strategy can be used as a complementary step to de novo transcriptome assembly to get a representative proteome of a target species. The results of the current analysis are available on the website PalmComparomics (http://palm-comparomics.southgreen.fr/).

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

Efficient visualization of high-throughput targeted proteomics experiments: TAPIR.

PubMed

Röst, Hannes L; Rosenberger, George; Aebersold, Ruedi; Malmström, Lars

2015-07-15

Targeted mass spectrometry comprises a set of powerful methods to obtain accurate and consistent protein quantification in complex samples. To fully exploit these techniques, a cross-platform and open-source software stack based on standardized data exchange formats is required. We present TAPIR, a fast and efficient Python visualization software for chromatograms and peaks identified in targeted proteomics experiments. The input formats are open, community-driven standardized data formats (mzML for raw data storage and TraML encoding the hierarchical relationships between transitions, peptides and proteins). TAPIR is scalable to proteome-wide targeted proteomics studies (as enabled by SWATH-MS), allowing researchers to visualize high-throughput datasets. The framework integrates well with existing automated analysis pipelines and can be extended beyond targeted proteomics to other types of analyses. TAPIR is available for all computing platforms under the 3-clause BSD license at https://github.com/msproteomicstools/msproteomicstools. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

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

PubMed

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

2015-05-01

Given the diverse range of transcriptional and post-transcriptional mechanisms of gene regulation, the estimates of the human proteome is likely subject to scientific surprises as the field of proteomics has gained momentum worldwide. In this regard, the establishment of the "Human Proteome Draft" using high-resolution mass spectrometry (MS), tissue microarrays, and immunohistochemistry by three independent research groups (laboratories of Pandey, Kuster, and Uhlen) accelerated the pace of proteomics research. The Chromosome Centric Human Proteome Project (C-HPP) has taken initiative towards the completion of the Human Proteome Project (HPP) so as to understand the proteomics correlates of common complex human diseases and biological diversity, not to mention person-to-person and population differences in response to drugs, nutrition, vaccines, and other health interventions and host-environment interactions. Although high-resolution MS-based and antibody microarray approaches have shown enormous promises, we are still unable to map the whole human proteome due to the presence of numerous "missing proteins." In December 2014, at the Indian Institute of Technology Bombay, Mumbai the 6(th) Annual Meeting of the Proteomics Society, India (PSI) and the International Proteomics Conference was held. As part of this interdisciplinary summit, a panel discussion session on "The Quest of the Human Proteome and Missing Proteins" was organized. Eminent scientists in the field of proteomics and systems biology, including Akhilesh Pandey, Gilbert S. Omenn, Mark S. Baker, and Robert L. Mortiz, shed light on different aspects of the human proteome drafts and missing proteins. Importantly, the possible reasons for the "missing proteins" in shotgun MS workflow were identified and debated by experts as low tissue expression, lack of enzymatic digestion site, or protein lost during extraction, among other contributing factors. To capture the missing proteins, the experts' collective 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.

Characterization and quantification of proteins secreted by single human embryos prior to implantation.

PubMed

Poli, Maurizio; Ori, Alessandro; Child, Tim; Jaroudi, Souraya; Spath, Katharina; Beck, Martin; Wells, Dagan

2015-11-01

The use of in vitro fertilization (IVF) has revolutionized the treatment of infertility and is now responsible for 1-5% of all births in industrialized countries. During IVF, it is typical for patients to generate multiple embryos. However, only a small proportion of them possess the genetic and metabolic requirements needed in order to produce a healthy pregnancy. The identification of the embryo with the greatest developmental capacity represents a major challenge for fertility clinics. Current methods for the assessment of embryo competence are proven inefficient, and the inadvertent transfer of non-viable embryos is the principal reason why most IVF treatments (approximately two-thirds) end in failure. In this study, we investigate how the application of proteomic measurements could improve success rates in clinical embryology. We describe a procedure that allows the identification and quantification of proteins of embryonic origin, present in attomole concentrations in the blastocoel, the enclosed fluid-filled cavity that forms within 5-day-old human embryos. By using targeted proteomics, we demonstrate the feasibility of quantifying multiple proteins in samples derived from single blastocoels and that such measurements correlate with aspects of embryo viability, such as chromosomal (ploidy) status. This study illustrates the potential of high-sensitivity proteomics to measure clinically relevant biomarkers in minute samples and, more specifically, suggests that key aspects of embryo competence could be measured using a proteomic-based strategy, with negligible risk of harm to the living embryo. Our work paves the way for the development of "next-generation" embryo competence assessment strategies, based on functional proteomics. © 2015 The Authors. Published under the terms of the CC BY 4.0 license.

Targeted proteomics identifies liquid-biopsy signatures for extracapsular prostate cancer

PubMed Central

Kim, Yunee; Jeon, Jouhyun; Mejia, Salvador; Yao, Cindy Q; Ignatchenko, Vladimir; Nyalwidhe, Julius O; Gramolini, Anthony O; Lance, Raymond S; Troyer, Dean A; Drake, Richard R; Boutros, Paul C; Semmes, O. John; Kislinger, Thomas

2016-01-01

Biomarkers are rapidly gaining importance in personalized medicine. Although numerous molecular signatures have been developed over the past decade, there is a lack of overlap and many biomarkers fail to validate in independent patient cohorts and hence are not useful for clinical application. For these reasons, identification of novel and robust biomarkers remains a formidable challenge. We combine targeted proteomics with computational biology to discover robust proteomic signatures for prostate cancer. Quantitative proteomics conducted in expressed prostatic secretions from men with extraprostatic and organ-confined prostate cancers identified 133 differentially expressed proteins. Using synthetic peptides, we evaluate them by targeted proteomics in a 74-patient cohort of expressed prostatic secretions in urine. We quantify a panel of 34 candidates in an independent 207-patient cohort. We apply machine-learning approaches to develop clinical predictive models for prostate cancer diagnosis and prognosis. Our results demonstrate that computationally guided proteomics can discover highly accurate non-invasive biomarkers. PMID:27350604

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

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

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

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.

Automated Validation of Results and Removal of Fragment Ion Interferences in Targeted Analysis of Data-independent Acquisition Mass Spectrometry (MS) using SWATHProphet*

PubMed Central

Keller, Andrew; Bader, Samuel L.; Shteynberg, David; Hood, Leroy; Moritz, Robert L.

2015-01-01

Proteomics by mass spectrometry technology is widely used for identifying and quantifying peptides and proteins. The breadth and sensitivity of peptide detection have been advanced by the advent of data-independent acquisition mass spectrometry. Analysis of such data, however, is challenging due to the complexity of fragment ion spectra that have contributions from multiple co-eluting precursor ions. We present SWATHProphet software that identifies and quantifies peptide fragment ion traces in data-independent acquisition data, provides accurate probabilities to ensure results are correct, and automatically detects and removes contributions to quantitation originating from interfering precursor ions. Integration in the widely used open source Trans-Proteomic Pipeline facilitates subsequent analyses such as combining results of multiple data sets together for improved discrimination using iProphet and inferring sample proteins using ProteinProphet. This novel development should greatly help make data-independent acquisition mass spectrometry accessible to large numbers of users. PMID:25713123

The role of targeted chemical proteomics in pharmacology

PubMed Central

Sutton, Chris W

2012-01-01

Traditionally, proteomics is the high-throughput characterization of the global complement of proteins in a biological system using cutting-edge technologies (robotics and mass spectrometry) and bioinformatics tools (Internet-based search engines and databases). As the field of proteomics has matured, a diverse range of strategies have evolved to answer specific problems. Chemical proteomics is one such direction that provides the means to enrich and detect less abundant proteins (the ‘hidden’ proteome) from complex mixtures of wide dynamic range (the ‘deep’ proteome). In pharmacology, chemical proteomics has been utilized to determine the specificity of drugs and their analogues, for anticipated known targets, only to discover other proteins that bind and could account for side effects observed in preclinical and clinical trials. As a consequence, chemical proteomics provides a valuable accessory in refinement of second- and third-generation drug design for treatment of many diseases. However, determining definitive affinity capture of proteins by a drug immobilized on soft gel chromatography matrices has highlighted some of the challenges that remain to be addressed. Examples of the different strategies that have emerged using well-established drugs against pharmaceutically important enzymes, such as protein kinases, metalloproteases, PDEs, cytochrome P450s, etc., indicate the potential opportunity to employ chemical proteomics as an early-stage screening approach in the identification of new targets. PMID:22074351

Halobacterium salinarum NRC-1 PeptideAtlas: toward strategies for targeted proteomics and improved proteome coverage.

PubMed

Van, Phu T; Schmid, Amy K; King, Nichole L; Kaur, Amardeep; Pan, Min; Whitehead, Kenia; Koide, Tie; Facciotti, Marc T; Goo, Young Ah; Deutsch, Eric W; Reiss, David J; Mallick, Parag; Baliga, Nitin S

2008-09-01

The relatively small numbers of proteins and fewer possible post-translational modifications in microbes provide a unique opportunity to comprehensively characterize their dynamic proteomes. We have constructed a PeptideAtlas (PA) covering 62.7% of the predicted proteome of the extremely halophilic archaeon Halobacterium salinarum NRC-1 by compiling approximately 636 000 tandem mass spectra from 497 mass spectrometry runs in 88 experiments. Analysis of the PA with respect to biophysical properties of constituent peptides, functional properties of parent proteins of detected peptides, and performance of different mass spectrometry approaches has highlighted plausible strategies for improving proteome coverage and selecting signature peptides for targeted proteomics. Notably, discovery of a significant correlation between absolute abundances of mRNAs and proteins has helped identify low abundance of proteins as the major limitation in peptide detection. Furthermore, we have discovered that iTRAQ labeling for quantitative proteomic analysis introduces a significant bias in peptide detection by mass spectrometry. Therefore, despite identifying at least one proteotypic peptide for almost all proteins in the PA, a context-dependent selection of proteotypic peptides appears to be the most effective approach for targeted proteomics.

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

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 biological membrane surfaces that we are only beginning to decipher. PMID:23230279

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

Halobacterium salinarum NRC-1 PeptideAtlas: strategies for targeted proteomics

PubMed Central

Van, Phu T.; Schmid, Amy K.; King, Nichole L.; Kaur, Amardeep; Pan, Min; Whitehead, Kenia; Koide, Tie; Facciotti, Marc T.; Goo, Young-Ah; Deutsch, Eric W.; Reiss, David J.; Mallick, Parag; Baliga, Nitin S.

2009-01-01

The relatively small numbers of proteins and fewer possible posttranslational modifications in microbes provides a unique opportunity to comprehensively characterize their dynamic proteomes. We have constructed a Peptide Atlas (PA) for 62.7% of the predicted proteome of the extremely halophilic archaeon Halobacterium salinarum NRC-1 by compiling approximately 636,000 tandem mass spectra from 497 mass spectrometry runs in 88 experiments. Analysis of the PA with respect to biophysical properties of constituent peptides, functional properties of parent proteins of detected peptides, and performance of different mass spectrometry approaches has helped highlight plausible strategies for improving proteome coverage and selecting signature peptides for targeted proteomics. Notably, discovery of a significant correlation between absolute abundances of mRNAs and proteins has helped identify low abundance of proteins as the major limitation in peptide detection. Furthermore we have discovered that iTRAQ labeling for quantitative proteomic analysis introduces a significant bias in peptide detection by mass spectrometry. Therefore, despite identifying at least one proteotypic peptide for almost all proteins in the PA, a context-dependent selection of proteotypic peptides appears to be the most effective approach for targeted proteomics. PMID:18652504

[Techniques for rapid production of monoclonal antibodies for use with antibody technology].

PubMed

Kamada, Haruhiko

2012-01-01

A monoclonal antibody (Mab), due to its specific binding ability to a target protein, can potentially be one of the most useful tools for the functional analysis of proteins in recent proteomics-based research. However, the production of Mab is a very time-consuming and laborious process (i.e., preparation of recombinant antigens, immunization of animals, preparation of hybridomas), making it the rate-limiting step in using Mabs in high-throughput proteomics research, which heavily relies on comprehensive and rapid methods. Therefore, there is a great demand for new methods to efficiently generate Mabs against a group of proteins identified by proteome analysis. Here, we describe a useful method called "Antibody proteomic technique" for the rapid generations of Mabs to pharmaceutical target, which were identified by proteomic analyses of disease samples (ex. tumor tissue, etc.). We also introduce another method to find profitable targets on vasculature, which is called "Vascular proteomic technique". Our results suggest that this method for the rapid generation of Mabs to proteins may be very useful in proteomics-based research as well as in clinical applications.

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.

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.

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

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.

Systems biology approaches and tools for analysis of interactomes and multi-target drugs.

PubMed

Schrattenholz, André; Groebe, Karlfried; Soskic, Vukic

2010-01-01

Systems biology is essentially a proteomic and epigenetic exercise because the relatively condensed information of genomes unfolds on the level of proteins. The flexibility of cellular architectures is not only mediated by a dazzling number of proteinaceous species but moreover by the kinetics of their molecular changes: The time scales of posttranslational modifications range from milliseconds to years. The genetic framework of an organism only provides the blue print of protein embodiments which are constantly shaped by external input. Indeed, posttranslational modifications of proteins represent the scope and velocity of these inputs and fulfil the requirements of integration of external spatiotemporal signal transduction inside an organism. The optimization of biochemical networks for this type of information processing and storage results in chemically extremely fine tuned molecular entities. The huge dynamic range of concentrations, the chemical diversity and the necessity of synchronisation of complex protein expression patterns pose the major challenge of systemic analysis of biological models. One further message is that many of the key reactions in living systems are essentially based on interactions of moderate affinities and moderate selectivities. This principle is responsible for the enormous flexibility and redundancy of cellular circuitries. In complex disorders such as cancer or neurodegenerative diseases, which initially appear to be rooted in relatively subtle dysfunctions of multimodal physiologic pathways, drug discovery programs based on the concept of high affinity/high specificity compounds ("one-target, one-disease"), which has been dominating the pharmaceutical industry for a long time, increasingly turn out to be unsuccessful. Despite improvements in rational drug design and high throughput screening methods, the number of novel, single-target drugs fell much behind expectations during the past decade, and the treatment of "complex 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.

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).

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 protein expression levels were within a range of 0.637-101 fmol/μg protein. The largest difference in the levels between the three strains was 2.2-fold for 13 molecules, although bcrp and mct1 displayed statistically significant differences between C57BL/6J and the other strain(s). Highly sensitive simultaneous absolute quantification achieved by QTAP will increase the usefulness of proteomics in biological sciences and is expected to advance the new research field of pharmacoproteomics (PPx). PMID:23758935

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.

Recommendations for the generation, quantification, storage and handling of peptides used for mass spectrometry-based assays

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

Hoofnagle, Andrew N.; Whiteaker, Jeffrey R.; Carr, Steven A.

2015-12-30

The Clinical Proteomic Tumor Analysis Consortium (1) (CPTAC) of the National Cancer Institute (NCI) is a comprehensive and coordinated effort to accelerate the understanding of the molecular basis of cancer through the application of robust technologies and workflows for the quantitative measurements of proteins. The Assay Development Working Group of the CPTAC Program aims to foster broad uptake of targeted mass spectrometry-based assays employing isotopically labeled peptides for confident assignment and quantification, including multiple reaction monitoring (MRM; also referred to as Selected Reaction Monitoring), parallel reaction monitoring (PRM), and other targeted methods.

Scout-MRM: Multiplexed Targeted Mass Spectrometry-Based Assay without Retention Time Scheduling Exemplified by Dickeya dadantii Proteomic Analysis during Plant Infection.

PubMed

Rougemont, Blandine; Bontemps Gallo, Sébastien; Ayciriex, Sophie; Carrière, Romain; Hondermarck, Hubert; Lacroix, Jean Marie; Le Blanc, J C Yves; Lemoine, Jérôme

2017-02-07

Targeted mass spectrometry of a surrogate peptide panel is a powerful method to study the dynamics of protein networks, but chromatographic time scheduling remains a major limitation for dissemination and implementation of robust and large multiplexed assays. We unveil a Multiple Reaction Monitoring method (Scout-MRM) where the use of spiked scout peptides triggers complex transition lists, regardless of the retention time of targeted surrogate peptides. The interest of Scout-MRM method regarding the retention time independency, multiplexing capability, reproducibility, and putative interest in facilitating method transfer was illustrated by a 782-peptide-plex relative assay targeting 445 proteins of the phytopathogen Dickeya dadantii during plant infection.

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.

Targeted Peptide Measurements in Biology and Medicine: Best Practices for Mass Spectrometry-based Assay Development Using a Fit-for-Purpose Approach

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

Carr, Steven A.; Abbateillo, Susan E.; Ackermann, Bradley L.

2014-01-14

Adoption of targeted mass spectrometry (MS) approaches such as multiple reaction monitoring (MRM) to study biological and biomedical questions is well underway in the proteomics community. Successful application depends on the ability to generate reliable assays that uniquely and confidently identify target peptides in a sample. Unfortunately, there is a wide range of criteria being applied to say that an assay has been successfully developed. There is no consensus on what criteria are acceptable and little understanding of the impact of variable criteria on the quality of the results generated. Publications describing targeted MS assays for peptides frequently do notmore » contain sufficient information for readers to establish confidence that the tests work as intended or to be able to apply the tests described in their own labs. Guidance must be developed so that targeted MS assays with established performance can be made widely distributed and applied by many labs worldwide. To begin to address the problems and their solutions, a workshop was held at the National Institutes of Health with representatives from the multiple communities developing and employing targeted MS assays. Participants discussed the analytical goals of their experiments and the experimental evidence needed to establish that the assays they develop work as intended and are achieving the required levels of performance. Using this “fit-for-purpose” approach, the group defined three tiers of assays distinguished by their performance and extent of analytical characterization. Computational and statistical tools useful for the analysis of targeted MS results were described. Participants also detailed the information that authors need to provide in their manuscripts to enable reviewers and readers to clearly understand what procedures were performed and to evaluate the reliability of the peptide or protein quantification measurements reported. This paper presents a summary of the meeting and recommendations. Molecular & Cellular Proteomics 13: 10.1074/mcp.M113.036095, 907–917, 2014.« less

Biochemical Fractionation and Stable Isotope Dilution Liquid Chromatography-mass Spectrometry for Targeted and Microdomain-specific Protein Quantification in Human Postmortem Brain Tissue*

PubMed Central

MacDonald, Matthew L.; Ciccimaro, Eugene; Prakash, Amol; Banerjee, Anamika; Seeholzer, Steven H.; Blair, Ian A.; Hahn, Chang-Gyu

2012-01-01

Synaptic architecture and its adaptive changes require numerous molecular events that are both highly ordered and complex. A majority of neuropsychiatric illnesses are complex trait disorders, in which multiple etiologic factors converge at the synapse via many signaling pathways. Investigating the protein composition of synaptic microdomains from human patient brain tissues will yield valuable insights into the interactions of risk genes in many disorders. These types of studies in postmortem tissues have been limited by the lack of proper study paradigms. Thus, it is necessary not only to develop strategies to quantify protein and post-translational modifications at the synapse, but also to rigorously validate them for use in postmortem human brain tissues. In this study we describe the development of a liquid chromatography-selected reaction monitoring method, using a stable isotope-labeled neuronal proteome standard prepared from the brain tissue of a stable isotope-labeled mouse, for the multiplexed quantification of target synaptic proteins in mammalian samples. Additionally, we report the use of this method to validate a biochemical approach for the preparation of synaptic microdomain enrichments from human postmortem prefrontal cortex. Our data demonstrate that a targeted mass spectrometry approach with a true neuronal proteome standard facilitates accurate and precise quantification of over 100 synaptic proteins in mammalian samples, with the potential to quantify over 1000 proteins. Using this method, we found that protein enrichments in subcellular fractions prepared from human postmortem brain tissue were strikingly similar to those prepared from fresh mouse brain tissue. These findings demonstrate that biochemical fractionation methods paired with targeted proteomic strategies can be used in human brain tissues, with important implications for the study of neuropsychiatric disease. PMID:22942359

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

Integrated Molecular Characterization of Uterine Carcinosarcoma.

PubMed

Cherniack, Andrew D; Shen, Hui; Walter, Vonn; Stewart, Chip; Murray, Bradley A; Bowlby, Reanne; Hu, Xin; Ling, Shiyun; Soslow, Robert A; Broaddus, Russell R; Zuna, Rosemary E; Robertson, Gordon; Laird, Peter W; Kucherlapati, Raju; Mills, Gordon B; Weinstein, John N; Zhang, Jiashan; Akbani, Rehan; Levine, Douglas A

2017-03-13

We performed genomic, epigenomic, transcriptomic, and proteomic characterizations of uterine carcinosarcomas (UCSs). Cohort samples had extensive copy-number alterations and highly recurrent somatic mutations. Frequent mutations were found in TP53, PTEN, PIK3CA, PPP2R1A, FBXW7, and KRAS, similar to endometrioid and serous uterine carcinomas. Transcriptome sequencing identified a strong epithelial-to-mesenchymal transition (EMT) gene signature in a subset of cases that was attributable to epigenetic alterations at microRNA promoters. The range of EMT scores in UCS was the largest among all tumor types studied via The Cancer Genome Atlas. UCSs shared proteomic features with gynecologic carcinomas and sarcomas with intermediate EMT features. Multiple somatic mutations and copy-number alterations in genes that are therapeutic targets were identified. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

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.

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 .

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.

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

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.

Improving transcriptome de novo assembly by using a reference genome of a related species: Translational genomics from oil palm to coconut

PubMed Central

Armero, Alix; Bocs, Stéphanie; This, Dominique

2017-01-01

The palms are a family of tropical origin and one of the main constituents of the ecosystems of these regions around the world. The two main species of palm represent different challenges: coconut (Cocos nucifera L.) is a source of multiple goods and services in tropical communities, while oil palm (Elaeis guineensis Jacq) is the main protagonist of the oil market. In this study, we present a workflow that exploits the comparative genomics between a target species (coconut) and a reference species (oil palm) to improve the transcriptomic data, providing a proteome useful to answer functional or evolutionary questions. This workflow reduces redundancy and fragmentation, two inherent problems of transcriptomic data, while preserving the functional representation of the target species. Our approach was validated in Arabidopsis thaliana using Arabidopsis lyrata and Capsella rubella as references species. This analysis showed the high sensitivity and specificity of our strategy, relatively independent of the reference proteome. The workflow increased the length of proteins products in A. thaliana by 13%, allowing, often, to recover 100% of the protein sequence length. In addition redundancy was reduced by a factor greater than 3. In coconut, the approach generated 29,366 proteins, 1,246 of these proteins deriving from new contigs obtained with the BRANCH software. The coconut proteome presented a functional profile similar to that observed in rice and an important number of metabolic pathways related to secondary metabolism. The new sequences found with BRANCH software were enriched in functions related to biotic stress. Our strategy can be used as a complementary step to de novo transcriptome assembly to get a representative proteome of a target species. The results of the current analysis are available on the website PalmComparomics (http://palm-comparomics.southgreen.fr/). PMID:28334050

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.

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.

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.

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.

A new dimethyl labeling-based SID-MRM-MS method and its application to three proteases involved in insulin maturation.

PubMed

Cheng, Dongwan; Zheng, Li; Hou, Junjie; Wang, Jifeng; Xue, Peng; Yang, Fuquan; Xu, Tao

2015-01-01

The absolute quantification of target proteins in proteomics involves stable isotope dilution coupled with multiple reactions monitoring mass spectrometry (SID-MRM-MS). The successful preparation of stable isotope-labeled internal standard peptides is an important prerequisite for the SID-MRM absolute quantification methods. Dimethyl labeling has been widely used in relative quantitative proteomics and it is fast, simple, reliable, cost-effective, and applicable to any protein sample, making it an ideal candidate method for the preparation of stable isotope-labeled internal standards. MRM mass spectrometry is of high sensitivity, specificity, and throughput characteristics and can quantify multiple proteins simultaneously, including low-abundance proteins in precious samples such as pancreatic islets. In this study, a new method for the absolute quantification of three proteases involved in insulin maturation, namely PC1/3, PC2 and CPE, was developed by coupling a stable isotope dimethyl labeling strategy for internal standard peptide preparation with SID-MRM-MS quantitative technology. This method offers a new and effective approach for deep understanding of the functional status of pancreatic β cells and pathogenesis in diabetes.

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

Plasmodium immunomics.

PubMed

Doolan, Denise L

2011-01-01

The Plasmodium parasite, the causative agent of malaria, is an excellent model for immunomic-based approaches to vaccine development. The Plasmodium parasite has a complex life cycle with multiple stages and stage-specific expression of ∼5300 putative proteins. No malaria vaccine has yet been licensed. Many believe that an effective vaccine will need to target several antigens and multiple stages, and will require the generation of both antibody and cellular immune responses. Vaccine efforts to date have been stage-specific and based on only a very limited number of proteins representing <0.5% of the genome. The recent availability of comprehensive genomic, proteomic and transcriptomic datasets from human and selected non-human primate and rodent malarias provide a foundation to exploit for vaccine development. This information can be mined to identify promising vaccine candidate antigens, by proteome-wide screening of antibody and T cell reactivity using specimens from individuals exposed to malaria and technology platforms such as protein arrays, high throughput protein production and epitope prediction algorithms. Such antigens could be incorporated into a rational vaccine development process that targets specific stages of the Plasmodium parasite life cycle with immune responses implicated in parasite elimination and control. Immunomic approaches which enable the selection of the best possible targets by prioritising antigens according to clinically relevant criteria may overcome the problem of poorly immunogenic, poorly protective vaccines that has plagued malaria vaccine developers for the past 25 years. Herein, current progress and perspectives regarding Plasmodium immunomics are reviewed. Copyright © 2010 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

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.

MaRiMba: a software application for spectral library-based MRM transition list assembly.

PubMed

Sherwood, Carly A; Eastham, Ashley; Lee, Lik Wee; Peterson, Amelia; Eng, Jimmy K; Shteynberg, David; Mendoza, Luis; Deutsch, Eric W; Risler, Jenni; Tasman, Natalie; Aebersold, Ruedi; Lam, Henry; Martin, Daniel B

2009-10-01

Multiple reaction monitoring mass spectrometry (MRM-MS) is a targeted analysis method that has been increasingly viewed as an avenue to explore proteomes with unprecedented sensitivity and throughput. We have developed a software tool, called MaRiMba, to automate the creation of explicitly defined MRM transition lists required to program triple quadrupole mass spectrometers in such analyses. MaRiMba creates MRM transition lists from downloaded or custom-built spectral libraries, restricts output to specified proteins or peptides, and filters based on precursor peptide and product ion properties. MaRiMba can also create MRM lists containing corresponding transitions for isotopically heavy peptides, for which the precursor and product ions are adjusted according to user specifications. This open-source application is operated through a graphical user interface incorporated into the Trans-Proteomic Pipeline, and it outputs the final MRM list to a text file for upload to MS instruments. To illustrate the use of MaRiMba, we used the tool to design and execute an MRM-MS experiment in which we targeted the proteins of a well-defined and previously published standard mixture.

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.

Multiplexed evaluation of capture agent binding kinetics using arrays of silicon photonic microring resonators.

PubMed

Byeon, Ji-Yeon; Bailey, Ryan C

2011-09-07

High affinity capture agents recognizing biomolecular targets are essential in the performance of many proteomic detection methods. Herein, we report the application of a label-free silicon photonic biomolecular analysis platform for simultaneously determining kinetic association and dissociation constants for two representative protein capture agents: a thrombin-binding DNA aptamer and an anti-thrombin monoclonal antibody. The scalability and inherent multiplexing capability of the technology make it an attractive platform for simultaneously evaluating the binding characteristics of multiple capture agents recognizing the same target antigen, and thus a tool complementary to emerging high-throughput capture agent generation strategies.

Assessment of SRM, MRM(3) , and DIA for the targeted analysis of phosphorylation dynamics in non-small cell lung cancer.

PubMed

Schmidlin, Thierry; Garrigues, Luc; Lane, Catherine S; Mulder, T Celine; van Doorn, Sander; Post, Harm; de Graaf, Erik L; Lemeer, Simone; Heck, Albert J R; Altelaar, A F Maarten

2016-08-01

Hypothesis-driven MS-based targeted proteomics has gained great popularity in a relatively short timespan. Next to the widely established selected reaction monitoring (SRM) workflow, data-independent acquisition (DIA), also referred to as sequential window acquisition of all theoretical spectra (SWATH) was introduced as a high-throughput targeted proteomics method. DIA facilitates increased proteome coverage, however, does not yet reach the sensitivity obtained with SRM. Therefore, a well-informed method selection is crucial for designing a successful targeted proteomics experiment. This is especially the case when targeting less conventional peptides such as those that contain PTMs, as these peptides do not always adhere to the optimal fragmentation considerations for targeted assays. Here, we provide insight into the performance of DIA, SRM, and MRM cubed (MRM(3) ) in the analysis of phosphorylation dynamics throughout the phosphoinositide 3-kinase mechanistic target of rapamycin (PI3K-mTOR) and mitogen-activated protein kinase (MAPK) signaling network. We observe indeed that DIA is less sensitive when compared to SRM, however demonstrates increased flexibility, by postanalysis selection of alternative phosphopeptide precursors. Additionally, we demonstrate the added benefit of MRM(3) , allowing the quantification of two poorly accessible phosphosites. In total, targeted proteomics enabled the quantification of 42 PI3K-mTOR and MAPK phosphosites, gaining a so far unachieved in-depth view mTOR signaling events linked to tyrosine kinase inhibitor resistance in non-small cell lung cancer. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

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

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 in drug discovery and optimization. In the present study, we used a chemical proteomic approach aimed to define the possible protein target of the ent-kaurane diterpene oridonin. This natural compound has drawn a rising attention for cancer biologists due to its remarkable anti-tumor activities: accumulating evidence has suggested that oridonin is able to hamper the progression of tumor, mitigate tumor burden and alleviate cancer syndrome, which may improve greatly the survival rates of cancer patients; however molecular mechanisms by which this compound exerts its anti-tumor activities still remained to be discovered. We identified the molecular chaperone HSP70 1A as an oridonin target in Jurkat cells, thus suggesting a mechanism of action for the diterpene consistent with the multiple biological activities described for it. HSP70 inhibition by oridonin might indeed simultaneously result in the impairment of some of client proteins, thus in turn affecting several molecular pathways. Shedding light on the molecular basis of the biological activity of oridonin, our findings may be relevant for possible therapeutic applications of oridonin, such as its use in combination and the design of new therapeutic approaches. In addition, this research demonstrates the effectiveness of chemical proteomic approaches in drug discovery studies and in orphan drug molecular target identification. Copyright © 2013 Elsevier B.V. All rights reserved.

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.

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

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.

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 of the best-suited PTPs for targeted proteomics applications. By building on methods developed in the field of information retrieval (e.g. web search engines like Google's PageRank), we circumvent the delicate step of selecting positive and negative training sets and at the same time also more closely reflect the experimentalist´s need for selecting e.g. the 5 most promising peptides for targeting a protein of interest. This approach allows to predict PTPs for not yet observed proteins or for organisms without prior experimental proteomics data such as many non-model organisms. Copyright © 2014 Elsevier B.V. All rights reserved.

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

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 plastid biology, preferentially based on model systems is deficient. New plant genomes are expected to enable the identification of potentially new plastid-targeted proteins that will aid in studying novel roles of plastids. PMID:25393533

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.

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.

A VCP inhibitor substrate trapping approach (VISTA) enables proteomic profiling of endogenous ERAD substrates.

PubMed

Huang, Edmond Y; To, Milton; Tran, Erica; Dionisio, Lorraine T Ador; Cho, Hyejin J; Baney, Katherine L M; Pataki, Camille I; Olzmann, James A

2018-05-01

Endoplasmic reticulum (ER)-associated degradation (ERAD) mediates the proteasomal clearance of proteins from the early secretory pathway. In this process, ubiquitinated substrates are extracted from membrane-embedded dislocation complexes by the AAA ATPase VCP and targeted to the cytosolic 26S proteasome. In addition to its well-established role in the degradation of misfolded proteins, ERAD also regulates the abundance of key proteins such as enzymes involved in cholesterol synthesis. However, due to the lack of generalizable methods, our understanding of the scope of proteins targeted by ERAD remains limited. To overcome this obstacle, we developed a VCP inhibitor substrate trapping approach (VISTA) to identify endogenous ERAD substrates. VISTA exploits the small-molecule VCP inhibitor CB5083 to trap ERAD substrates in a membrane-associated, ubiquitinated form. This strategy, coupled with quantitative ubiquitin proteomics, identified previously validated (e.g., ApoB100, Insig2, and DHCR7) and novel (e.g., SCD1 and RNF5) ERAD substrates in cultured human hepatocellular carcinoma cells. Moreover, our results indicate that RNF5 autoubiquitination on multiple lysine residues targets it for ubiquitin and VCP--dependent clearance. Thus, VISTA provides a generalizable discovery method that expands the available toolbox of strategies to elucidate the ERAD substrate landscape.

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

Elucidation of the Ebola virus VP24 cellular interactome and disruption of virus biology through targeted inhibition of host-cell protein function.

PubMed

García-Dorival, Isabel; Wu, Weining; Dowall, Stuart; Armstrong, Stuart; Touzelet, Olivier; Wastling, Jonathan; Barr, John N; Matthews, David; Carroll, Miles; Hewson, Roger; Hiscox, Julian A

2014-11-07

Viral pathogenesis in the infected cell is a balance between antiviral responses and subversion of host-cell processes. Many viral proteins specifically interact with host-cell proteins to promote virus biology. Understanding these interactions can lead to knowledge gains about infection and provide potential targets for antiviral therapy. One such virus is Ebola, which has profound consequences for human health and causes viral hemorrhagic fever where case fatality rates can approach 90%. The Ebola virus VP24 protein plays a critical role in the evasion of the host immune response and is likely to interact with multiple cellular proteins. To map these interactions and better understand the potential functions of VP24, label-free quantitative proteomics was used to identify cellular proteins that had a high probability of forming the VP24 cellular interactome. Several known interactions were confirmed, thus placing confidence in the technique, but new interactions were also discovered including one with ATP1A1, which is involved in osmoregulation and cell signaling. Disrupting the activity of ATP1A1 in Ebola-virus-infected cells with a small molecule inhibitor resulted in a decrease in progeny virus, thus illustrating how quantitative proteomics can be used to identify potential therapeutic targets.

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.

Targeting Metabolic Plasticity in Breast Cancer Cells via Mitochondrial Complex I Modulation

PubMed Central

Xu, Qijin; Biener-Ramanujan, Eva; Yang, Wei; Ramanujan, V Krishnan

2016-01-01

Purpose Heterogeneity commonly observed in clinical tumors stems both from the genetic diversity as well as from the differential metabolic adaptation of multiple cancer types during their struggle to maintain uncontrolled proliferation and invasion in vivo. This study aims to identify a potential metabolic window of such adaptation in aggressive human breast cancer cell lines. Methods With a multidisciplinary approach using high resolution imaging, cell metabolism assays, proteomic profiling and animal models of human tumor xenografts and via clinically-relevant, pharmacological approach for modulating mitochondrial complex I function in human breast cancer cell lines, we report a novel route to target metabolic plasticity in human breast cancer cells. Results By a systematic modulation of mitochondrial function and by mitigating metabolic switch phenotype in aggressive human breast cancer cells, we demonstrate that the resulting metabolic adaptation signatures can predictably decrease tumorigenic potential in vivo. Proteomic profiling of the metabolic adaptation in these cells further revealed novel protein-pathway interactograms highlighting the importance of antioxidant machinery in the observed metabolic adaptation. Conclusions Improved metabolic adaptation potential in aggressive human breast cancer cells contribute to improving mitochondrial function and reducing metabolic switch phenotype –which may be vital for targeting primary tumor growth in vivo. PMID:25677747

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

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

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

Needles in the blue sea: sub-species specificity in targeted protein biomarker analyses within the vast oceanic microbial metaproteome.

PubMed

Saito, Mak A; Dorsk, Alexander; Post, Anton F; McIlvin, Matthew R; Rappé, Michael S; DiTullio, Giacomo R; Moran, Dawn M

2015-10-01

Proteomics has great potential for studies of marine microbial biogeochemistry, yet high microbial diversity in many locales presents us with unique challenges. We addressed this challenge with a targeted metaproteomics workflow for NtcA and P-II, two nitrogen regulatory proteins, and demonstrated its application for cyanobacterial taxa within microbial samples from the Central Pacific Ocean. Using METATRYP, an open-source Python toolkit, we examined the number of shared (redundant) tryptic peptides in representative marine microbes, with the number of tryptic peptides shared between different species typically being 1% or less. The related cyanobacteria Prochlorococcus and Synechococcus shared an average of 4.8 ± 1.9% of their tryptic peptides, while shared intraspecies peptides were higher, 13 ± 15% shared peptides between 12 Prochlorococcus genomes. An NtcA peptide was found to target multiple cyanobacteria species, whereas a P-II peptide showed specificity to the high-light Prochlorococcus ecotype. Distributions of NtcA and P-II in the Central Pacific Ocean were similar except at the Equator likely due to differential nitrogen stress responses between Prochlorococcus and Synechococcus. The number of unique tryptic peptides coded for within three combined oceanic microbial metagenomes was estimated to be ∼4 × 10(7) , 1000-fold larger than an individual microbial proteome and 27-fold larger than the human proteome, yet still 20 orders of magnitude lower than the peptide diversity possible in all protein space, implying that peptide mapping algorithms should be able to withstand the added level of complexity in metaproteomic samples. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Large-scale label-free comparative proteomics analysis of polo-like kinase 1 inhibition via the small-molecule inhibitor BI 6727 (Volasertib) in BRAF(V600E) mutant melanoma cells.

PubMed

Cholewa, Brian D; Pellitteri-Hahn, Molly C; Scarlett, Cameron O; Ahmad, Nihal

2014-11-07

Polo-like kinase 1 (Plk1) is a serine/threonine kinase that plays a key role during the cell cycle by regulating mitotic entry, progression, and exit. Plk1 is overexpressed in a variety of human cancers and is essential to sustained oncogenic proliferation, thus making Plk1 an attractive therapeutic target. However, the clinical efficacy of Plk1 inhibition has not emulated the preclinical success, stressing an urgent need for a better understanding of Plk1 signaling. This study addresses that need by utilizing a quantitative proteomics strategy to compare the proteome of BRAF(V600E) mutant melanoma cells following treatment with the Plk1-specific inhibitor BI 6727. Employing label-free nano-LC-MS/MS technology on a Q-exactive followed by SIEVE processing, we identified more than 20 proteins of interest, many of which have not been previously associated with Plk1 signaling. Here we report the down-regulation of multiple metabolic proteins with an associated decrease in cellular metabolism, as assessed by lactate and NAD levels. Furthermore, we have also identified the down-regulation of multiple proteasomal subunits, resulting in a significant decrease in 20S proteasome activity. Additionally, we have identified a novel association between Plk1 and p53 through heterogeneous ribonucleoprotein C1/C2 (hnRNPC), thus providing valuable insight into Plk1's role in cancer cell survival.

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.

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.

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.

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.

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.

Proteome Analysis of Peroxisomes from Etiolated Arabidopsis Seedlings Identifies a Peroxisomal Protease Involved in β-Oxidation and Development1[C][W][OPEN

PubMed Central

Quan, Sheng; Yang, Pingfang; Cassin-Ross, Gaëlle; Kaur, Navneet; Switzenberg, Robert; Aung, Kyaw; Li, Jiying; Hu, Jianping

2013-01-01

Plant peroxisomes are highly dynamic organelles that mediate a suite of metabolic processes crucial to development. Peroxisomes in seeds/dark-grown seedlings and in photosynthetic tissues constitute two major subtypes of plant peroxisomes, which had been postulated to contain distinct primary biochemical properties. Multiple in-depth proteomic analyses had been performed on leaf peroxisomes, yet the major makeup of peroxisomes in seeds or dark-grown seedlings remained unclear. To compare the metabolic pathways of the two dominant plant peroxisomal subtypes and discover new peroxisomal proteins that function specifically during seed germination, we performed proteomic analysis of peroxisomes from etiolated Arabidopsis (Arabidopsis thaliana) seedlings. The detection of 77 peroxisomal proteins allowed us to perform comparative analysis with the peroxisomal proteome of green leaves, which revealed a large overlap between these two primary peroxisomal variants. Subcellular targeting analysis by fluorescence microscopy validated around 10 new peroxisomal proteins in Arabidopsis. Mutant analysis suggested the role of the cysteine protease RESPONSE TO DROUGHT21A-LIKE1 in β-oxidation, seed germination, and growth. This work provides a much-needed road map of a major type of plant peroxisome and has established a basis for future investigations of peroxisomal proteolytic processes to understand their roles in development and in plant interaction with the environment. PMID:24130194

The Cytotoxicity Mechanism of 6-Shogaol-Treated HeLa Human Cervical Cancer Cells Revealed by Label-Free Shotgun Proteomics and Bioinformatics Analysis.

PubMed

Liu, Qun; Peng, Yong-Bo; Qi, Lian-Wen; Cheng, Xiao-Lan; Xu, Xiao-Jun; Liu, Le-Le; Liu, E-Hu; Li, Ping

2012-01-01

Cervical cancer is one of the most common cancers among women in the world. 6-Shogaol is a natural compound isolated from the rhizome of ginger (Zingiber officinale). In this paper, we demonstrated that 6-shogaol induced apoptosis and G2/M phase arrest in human cervical cancer HeLa cells. Endoplasmic reticulum stress and mitochondrial pathway were involved in 6-shogaol-mediated apoptosis. Proteomic analysis based on label-free strategy by liquid chromatography chip quadrupole time-of-flight mass spectrometry was subsequently proposed to identify, in a non-target-biased manner, the molecular changes in cellular proteins in response to 6-shogaol treatment. A total of 287 proteins were differentially expressed in response to 24 h treatment with 15 μM 6-shogaol in HeLa cells. Significantly changed proteins were subjected to functional pathway analysis by multiple analyzing software. Ingenuity pathway analysis (IPA) suggested that 14-3-3 signaling is a predominant canonical pathway involved in networks which may be significantly associated with the process of apoptosis and G2/M cell cycle arrest induced by 6-shogaol. In conclusion, this work developed an unbiased protein analysis strategy by shotgun proteomics and bioinformatics analysis. Data observed provide a comprehensive analysis of the 6-shogaol-treated HeLa cell proteome and reveal protein alterations that are associated with its anticancer mechanism.

The Cytotoxicity Mechanism of 6-Shogaol-Treated HeLa Human Cervical Cancer Cells Revealed by Label-Free Shotgun Proteomics and Bioinformatics Analysis

PubMed Central

Liu, Qun; Peng, Yong-Bo; Qi, Lian-Wen; Cheng, Xiao-Lan; Xu, Xiao-Jun; Liu, Le-Le; Liu, E-Hu; Li, Ping

2012-01-01

Cervical cancer is one of the most common cancers among women in the world. 6-Shogaol is a natural compound isolated from the rhizome of ginger (Zingiber officinale). In this paper, we demonstrated that 6-shogaol induced apoptosis and G2/M phase arrest in human cervical cancer HeLa cells. Endoplasmic reticulum stress and mitochondrial pathway were involved in 6-shogaol-mediated apoptosis. Proteomic analysis based on label-free strategy by liquid chromatography chip quadrupole time-of-flight mass spectrometry was subsequently proposed to identify, in a non-target-biased manner, the molecular changes in cellular proteins in response to 6-shogaol treatment. A total of 287 proteins were differentially expressed in response to 24 h treatment with 15 μM 6-shogaol in HeLa cells. Significantly changed proteins were subjected to functional pathway analysis by multiple analyzing software. Ingenuity pathway analysis (IPA) suggested that 14-3-3 signaling is a predominant canonical pathway involved in networks which may be significantly associated with the process of apoptosis and G2/M cell cycle arrest induced by 6-shogaol. In conclusion, this work developed an unbiased protein analysis strategy by shotgun proteomics and bioinformatics analysis. Data observed provide a comprehensive analysis of the 6-shogaol-treated HeLa cell proteome and reveal protein alterations that are associated with its anticancer mechanism. PMID:23243437

Targeted Quantification of Isoforms of a Thylakoid-Bound Protein: MRM Method Development.

PubMed

Bru-Martínez, Roque; Martínez-Márquez, Ascensión; Morante-Carriel, Jaime; Sellés-Marchart, Susana; Martínez-Esteso, María José; Pineda-Lucas, José Luis; Luque, Ignacio

2018-01-01

Targeted mass spectrometric methods such as selected/multiple reaction monitoring (SRM/MRM) have found intense application in protein detection and quantification which competes with classical immunoaffinity techniques. It provides a universal procedure to develop a fast, highly specific, sensitive, accurate, and cheap methodology for targeted detection and quantification of proteins based on the direct analysis of their surrogate peptides typically generated by tryptic digestion. This methodology can be advantageously applied in the field of plant proteomics and particularly for non-model species since immunoreagents are scarcely available. Here, we describe the issues to take into consideration in order to develop a MRM method to detect and quantify isoforms of the thylakoid-bound protein polyphenol oxidase from the non-model and database underrepresented species Eriobotrya japonica Lindl.

Mass spectrometry for biomarker development

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

Wu, Chaochao; Liu, Tao; Baker, Erin Shammel

2015-06-19

Biomarkers potentially play a crucial role in early disease diagnosis, prognosis and targeted therapy. In the past decade, mass spectrometry based proteomics has become increasingly important in biomarker development due to large advances in technology and associated methods. This chapter mainly focuses on the application of broad (e.g. shotgun) proteomics in biomarker discovery and the utility of targeted proteomics in biomarker verification and validation. A range of mass spectrometry methodologies are discussed emphasizing their efficacy in the different stages in biomarker development, with a particular emphasis on blood biomarker development.

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.

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

Mining Missing Membrane Proteins by High-pH Reverse Phase StageTip Fractionation and Multiple Reaction Monitoring Mass Spectrometry

PubMed Central

Kitata, Reta Birhanu; Dimayacyac-Esleta, Baby Rorielyn T.; Choong, Wai-Kok; Tsai, Chia-Feng; Lin, Tai-Du; Tsou, Chih-Chiang; Weng, Shao-Hsing; Chen, Yi-Ju; Yang, Pan-Chyr; Arco, Susan D.; Nesvizhskii, Alexey I.; Sung, Ting-Yi; Chen, Yu-Ju

2016-01-01

Despite significant efforts in the past decade towards complete mapping of the human proteome, 3564 proteins (neXtProt, 09-2014) are still “missing proteins”. Over one-third of these missing proteins are annotated as membrane proteins, owing to their relatively challenging accessibility with standard shotgun proteomics. Using non-small cell lung cancer (NSCLC) as a model study, we aim to mine missing proteins from disease-associated membrane proteome, which may be still largely under-represented. To increase identification coverage, we employed Hp-RP StageTip pre-fractionation of membrane-enriched samples from 11 NSCLC cell lines. Analysis of membrane samples from 20 pairs of tumor and adjacent normal lung tissue were incorporated to include physiologically expressed membrane proteins. Using multiple search engines (X!Tandem, Comet and Mascot) and stringent evaluation of FDR (MAYU and PeptideShaker), we identified 7702 proteins (66% membrane proteins) and 178 missing proteins (74 membrane proteins) with PSM-, peptide-, and protein-level FDR of 1%. Through multiple reaction monitoring (MRM) using synthetic peptides, we provided additional evidences for 8 missing proteins including 7 with transmembrane helix domains (TMH). This study demonstrates that mining missing proteins focused on cancer membrane sub-proteome can greatly contribute to map the whole human proteome. All data were deposited into ProteomeXchange with the identifier PXD002224. PMID:26202522

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.

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.ali@helsinki.fi or tero.aittokallio@fimm.fi. Supplementary data are available at Bioinformatics online.

Differential proteome analysis of serum proteins associated with the development of type 2 diabetes mellitus in the KK-A(y) mouse model using the iTRAQ technique.

PubMed

Takahashi, Eri; Okumura, Akinori; Unoki-Kubota, Hiroyuki; Hirano, Hisashi; Kasuga, Masato; Kaburagi, Yasushi

2013-06-12

To identify candidate serum molecules associated with the progression of type 2 diabetes mellitus (T2DM), we carried out differential proteomic analysis using the KK-A(y) mouse, an animal model of T2DM with obesity. We employed an iTRAQ-based quantitative proteomic approach to analyze the proteomic changes in the sera collected from a pair of 4-week-old KK-A(y) versus C57BL/6 mice. Among the 227 proteins identified, a total of 45 proteins were differentially expressed in KK-A(y) versus C57BL/6 mice. We comparatively analyzed a series of the sera collected at 4 and 12weeks of age from KK-A(y) and C57BL/6 mice for the target protein using multiple reaction monitoring analysis, and identified 8 differentially expressed proteins between the sera of these mice at both time points. Among them, serine (or cysteine) peptidase inhibitor, clade A, member 3K (SERPINA3K) levels were elevated significantly in the sera of KK-A(y) mice compared to C57BL/6 mice. An in vitro assay revealed that the human homologue SERPINA3 increased the transendothelial permeability of retinal microvascular endothelial cells, which may be involved in the pathogenesis of diabetes and/or diabetic retinopathy. With the identified proteins, our proteomics study could provide valuable clues for a better understanding of the underlying mechanisms associated with T2DM. In this paper, we investigated the serum proteome of KK-A(y) mice in a pre-diabetic state compared to that of wild type controls in an attempt to uncover early diagnostic markers of diabetes that are maintained through a diabetic phenotype. We used iTRAQ-based two-dimensional LC-MS/MS serum profiling, and identified several differentially expressed proteins at the pre-diabetic stage. The differential expression was confirmed by multiple reaction monitoring assay, which is fast gaining ground as a sensitive, specific, and cost-effective methodology for relative quantification of the candidate proteins. Using these techniques, we have identified eight candidate proteins of interest including SERPINA3K, which may be important in the pathology of T2DM and/or diabetic retinopathy. Copyright © 2013 Elsevier B.V. All rights reserved.

Multiple marker abundance profiling: combining selected reaction monitoring and data-dependent acquisition for rapid estimation of organelle abundance in subcellular samples

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

Hooper, Cornelia M.; Stevens, Tim J.; Saukkonen, Anna

Measuring changes in protein or organelle abundance in the cell is an essential, but challenging aspect of cell biology. Frequently-used methods for determining organelle abundance typically rely on detection of a very few marker proteins, so are unsatisfactory. In silico estimates of protein abundances from publicly available protein spectra can provide useful standard abundance values but contain only data from tissue proteomes, and are not coupled to organelle localization data. A new protein abundance score, the normalized protein abundance scale (NPAS), expands on the number of scored proteins and the scoring accuracy of lower-abundance proteins in Arabidopsis. NPAS was combinedmore » with subcellular protein localization data, facilitating quantitative estimations of organelle abundance during routine experimental procedures. A suite of targeted proteomics markers for subcellular compartment markers was developed, enabling independent verification of in silico estimates for relative organelle abundance. Estimation of relative organelle abundance was found to be reproducible and consistent over a range of tissues and growth conditions. In silico abundance estimations and localization data have been combined into an online tool, multiple marker abundance profiling, available in the SUBA4 toolbox (http://suba.live).« less

Multiple marker abundance profiling: combining selected reaction monitoring and data-dependent acquisition for rapid estimation of organelle abundance in subcellular samples

DOE PAGES

Hooper, Cornelia M.; Stevens, Tim J.; Saukkonen, Anna; ...

2017-10-12

Measuring changes in protein or organelle abundance in the cell is an essential, but challenging aspect of cell biology. Frequently-used methods for determining organelle abundance typically rely on detection of a very few marker proteins, so are unsatisfactory. In silico estimates of protein abundances from publicly available protein spectra can provide useful standard abundance values but contain only data from tissue proteomes, and are not coupled to organelle localization data. A new protein abundance score, the normalized protein abundance scale (NPAS), expands on the number of scored proteins and the scoring accuracy of lower-abundance proteins in Arabidopsis. NPAS was combinedmore » with subcellular protein localization data, facilitating quantitative estimations of organelle abundance during routine experimental procedures. A suite of targeted proteomics markers for subcellular compartment markers was developed, enabling independent verification of in silico estimates for relative organelle abundance. Estimation of relative organelle abundance was found to be reproducible and consistent over a range of tissues and growth conditions. In silico abundance estimations and localization data have been combined into an online tool, multiple marker abundance profiling, available in the SUBA4 toolbox (http://suba.live).« less

MaRiMba: A Software Application for Spectral Library-Based MRM Transition List Assembly

PubMed Central

Sherwood, Carly A.; Eastham, Ashley; Lee, Lik Wee; Peterson, Amelia; Eng, Jimmy K.; Shteynberg, David; Mendoza, Luis; Deutsch, Eric W.; Risler, Jenni; Tasman, Natalie; Aebersold, Ruedi; Lam, Henry; Martin, Daniel B.

2009-01-01

Multiple reaction monitoring mass spectrometry (MRM-MS) is a targeted analysis method that has been increasingly viewed as an avenue to explore proteomes with unprecedented sensitivity and throughput. We have developed a software tool, called MaRiMba, to automate the creation of explicitly defined MRM transition lists required to program triple quadrupole mass spectrometers in such analyses. MaRiMba creates MRM transition lists from downloaded or custom-built spectral libraries, restricts output to specified proteins or peptides, and filters based on precursor peptide and product ion properties. MaRiMba can also create MRM lists containing corresponding transitions for isotopically heavy peptides, for which the precursor and product ions are adjusted according to user specifications. This open-source application is operated through a graphical user interface incorporated into the Trans-Proteomic Pipeline, and it outputs the final MRM list to a text file for upload to MS instruments. To illustrate the use of MaRiMba, we used the tool to design and execute an MRM-MS experiment in which we targeted the proteins of a well-defined and previously published standard mixture. PMID:19603829

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.

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

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.

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

Fluorescent Protein-Based Quantification of Alternative Splicing of a Target Cassette Exon in Mammalian Cells.

PubMed

Gurskaya, N G; Staroverov, D B; Lukyanov, K A

2016-01-01

Alternative splicing is an important mechanism of regulation of gene expression and expansion of proteome complexity. Recently we developed a new fluorescence reporter for quantitative analysis of alternative splicing of a target cassette exon in live cells (Gurskaya et al., 2012). It consists of a specially designed minigene encoding red and green fluorescent proteins (Katushka and TagGFP2) and a fragment of the target gene between them. Skipping or inclusion of the alternative exon induces a frameshift; ie, alternative exon length must not be a multiple of 3. Finally, red and green fluorescence intensities of cells expressing this reporter are used to estimate the percentage of alternative (exon-skipped) and normal (exon-retained) transcripts. Here, we provide a detailed description of design and application of the fluorescence reporter of a target alternative exon splicing in mammalian cell lines. © 2016 Elsevier Inc. All rights reserved.

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

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

Roel Verhaak, Ph.D., Presents the Somatic Genomic Landscape of Glioblastoma - TCGA

Cancer.gov

Diffuse lower grade gliomas (LGGs) are infiltrative neoplasms of the central nervous system that include astrocytoma, oligodendroglioma and oligo-astrocytoma histologies of grades II and III. Roel G.W. Verhaak, Ph.D., presents a comprehensive analysis of 293 LGGs using multiple advanced genomic, transcriptomic and proteomic platforms from The Cancer Genome Atlas to provide a deeper understanding of the molecular features of this group of neoplasms, to classify them in a clinically-relevant manner, and to provide a public resource that identifies potential targets for emerging therapies.

Artemisinin activity-based probes identify multiple molecular targets within the asexual stage of the malaria parasites Plasmodium falciparum 3D7

PubMed Central

Ismail, Hanafy M.; Barton, Victoria; Phanchana, Matthew; Charoensutthivarakul, Sitthivut; Wong, Michael H. L.; Hemingway, Janet; Biagini, Giancarlo A.; O’Neill, Paul M.; Ward, Stephen A.

2016-01-01

The artemisinin (ART)-based antimalarials have contributed significantly to reducing global malaria deaths over the past decade, but we still do not know how they kill parasites. To gain greater insight into the potential mechanisms of ART drug action, we developed a suite of ART activity-based protein profiling probes to identify parasite protein drug targets in situ. Probes were designed to retain biological activity and alkylate the molecular target(s) of Plasmodium falciparum 3D7 parasites in situ. Proteins tagged with the ART probe can then be isolated using click chemistry before identification by liquid chromatography–MS/MS. Using these probes, we define an ART proteome that shows alkylated targets in the glycolytic, hemoglobin degradation, antioxidant defense, and protein synthesis pathways, processes essential for parasite survival. This work reveals the pleiotropic nature of the biological functions targeted by this important class of antimalarial drugs. PMID:26858419

Alkylation Damage by Lipid Electrophiles Targets Functional Protein Systems*

PubMed Central

Codreanu, Simona G.; Ullery, Jody C.; Zhu, Jing; Tallman, Keri A.; Beavers, William N.; Porter, Ned A.; Marnett, Lawrence J.; Zhang, Bing; Liebler, Daniel C.

2014-01-01

Protein alkylation by reactive electrophiles contributes to chemical toxicities and oxidative stress, but the functional impact of alkylation damage across proteomes is poorly understood. We used Click chemistry and shotgun proteomics to profile the accumulation of proteome damage in human cells treated with lipid electrophile probes. Protein target profiles revealed three damage susceptibility classes, as well as proteins that were highly resistant to alkylation. Damage occurred selectively across functional protein interaction networks, with the most highly alkylation-susceptible proteins mapping to networks involved in cytoskeletal regulation. Proteins with lower damage susceptibility mapped to networks involved in protein synthesis and turnover and were alkylated only at electrophile concentrations that caused significant toxicity. Hierarchical susceptibility of proteome systems to alkylation may allow cells to survive sublethal damage while protecting critical cell functions. PMID:24429493

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

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

Mining Missing Membrane Proteins by High-pH Reverse-Phase StageTip Fractionation and Multiple Reaction Monitoring Mass Spectrometry.

PubMed

Kitata, Reta Birhanu; Dimayacyac-Esleta, Baby Rorielyn T; Choong, Wai-Kok; Tsai, Chia-Feng; Lin, Tai-Du; Tsou, Chih-Chiang; Weng, Shao-Hsing; Chen, Yi-Ju; Yang, Pan-Chyr; Arco, Susan D; Nesvizhskii, Alexey I; Sung, Ting-Yi; Chen, Yu-Ju

2015-09-04

Despite significant efforts in the past decade toward complete mapping of the human proteome, 3564 proteins (neXtProt, 09-2014) are still "missing proteins". Over one-third of these missing proteins are annotated as membrane proteins, owing to their relatively challenging accessibility with standard shotgun proteomics. Using nonsmall cell lung cancer (NSCLC) as a model study, we aim to mine missing proteins from disease-associated membrane proteome, which may be still largely under-represented. To increase identification coverage, we employed Hp-RP StageTip prefractionation of membrane-enriched samples from 11 NSCLC cell lines. Analysis of membrane samples from 20 pairs of tumor and adjacent normal lung tissue was incorporated to include physiologically expressed membrane proteins. Using multiple search engines (X!Tandem, Comet, and Mascot) and stringent evaluation of FDR (MAYU and PeptideShaker), we identified 7702 proteins (66% membrane proteins) and 178 missing proteins (74 membrane proteins) with PSM-, peptide-, and protein-level FDR of 1%. Through multiple reaction monitoring using synthetic peptides, we provided additional evidence of eight missing proteins including seven with transmembrane helix domains. This study demonstrates that mining missing proteins focused on cancer membrane subproteome can greatly contribute to map the whole human proteome. All data were deposited into ProteomeXchange with the identifier PXD002224.

Proteomic investigating the cooperative lethal effect of EGFR and MDM2 inhibitors on ovarian carcinoma.

PubMed

Chang, Shing-Jyh; Liao, En-Chi; Yeo, Hsin-Yueh; Kuo, Wen-Hung; Chen, Hsin-Yi; Tsai, Yi-Ting; Wei, Yu-Shan; Chen, Ying-Jen; Wang, Yi-Shiuan; Li, Ji-Min; Shih, Chuan-Chi; Chan, Chia-Hao; Lai, Zih-Yin; Chou, Hsiu-Chuan; Chuang, Yung-Jen; Chan, Hong-Lin

2018-06-01

With the concept of precision medicine, combining multiple molecular-targeting therapies has brought new approaches to current cancer treatments. Malfunction of the tumor suppressor protein, p53 is a universal hallmark in human cancers. Under normal conditions, p53 is degraded through an ubiquitin-proteosome pathway regulated by its negative regulator, MDM2. In contrast, cellular stress such as DNA damage will activate p53 to carry out DNA repair, cell cycle arrest, and apoptosis. In this study, we focused on ovarian carcinoma with high EGFR and MDM2 overexpression rate. We assessed the effects of combined inhibition by MDM2 (JNJ-26854165) and EGFR (gefitinib) inhibitors on various ovarian cell lines to determine the importance of these two molecular targets on cell proliferation. We then used a proteomic strategy to investigate the relationship between MDM2 and EGFR inhibition to explore the underlying mechanisms of how their combined signaling blockades work together to exert cooperative inhibition. Our results demonstrated that all four cell lines were sensitive to both individual and combined, MDM2 and EGFR inhibition. The proteomic analysis also showed that gefitinib/JNJ-treated CAOV3 cells exhibited downregulation of proteins involved in nucleotide biosynthesis such as nucleoside diphosphate kinase B (NME2). In conclusion, our study showed that the combined treatment with JNJ and gefitinib exerted synergistic inhibition on cell proliferation, thereby suggesting the potential application of combining MDM2 inhibitors with EGFR inhibitors for enhancing efficacy in ovarian cancer treatment. Copyright © 2018 Elsevier Inc. All rights reserved.

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.

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.

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.

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.

What does systems biology mean for drug development?

PubMed

Schrattenholz, André; Soskić, Vukić

2008-01-01

The complexity and flexibility of cellular architectures is increasingly recognized by impressive progress on the side of molecular analytics, i.e. proteomics, genomics and metabolomics. One of the messages from systems biology is that the number of molecular species in cellular networks is orders of magnitude bigger than anticipated by genomic analysis, in particular by fast posttranslational modifications of proteins. The requirements to manage external signals, integrate spatiotemporal signal transduction inside an organism and at the same time optimizing networks of biochemical and chemical reactions result in chemically extremely fine tuned molecular entities. Chemical side reactions of enzymatic activity, like e.g. random oxidative damage of proteins by free radicals during aging constantly introduce epigenetic alterations of protein targets. These events gradually and on an individual stochastic scale, keep modifying activities of these targets, and their affinities and selectivities towards biological and pharmacological ligands. One further message is that many of the key reactions in living systems are essentially based on interactions of low affinities and even low selectivities. This principle is responsible for the enormous flexibility and redundancy of cellular circuitries. So, in complex disorders like cancer or neurodegenerative diseases, which are rooted in relatively subtle and multimodal dysfunction of important physiologic pathways, drug discovery programs based on the concept of high affinity/high specificity compounds ("one-target, one-disease"), which still dominate the pharmaceutical industry increasingly turn out to be unsuccessful. Despite improvements in rational drug design and high throughput screening methods, the number of novel, single-target drugs fell much behind expectations during the past decade and the treatment of "complex diseases" remains a most pressing medical need. Currently a change of paradigm can be observed with regard to a new focus on agents that modulate multiple targets simultaneously. Targeting cellular function as a system rather than on the level of the single protein molecule 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 and extraction of "screenable" information from biological systems essentially ruled by deterministic chaotic processes on a background of individual stochasticity.

To What Extent is FAIMS Beneficial in the Analysis of Proteins?

NASA Astrophysics Data System (ADS)

Cooper, Helen J.

2016-04-01

High field asymmetric waveform ion mobility spectrometry (FAIMS), also known as differential ion mobility spectrometry, is emerging as a tool for biomolecular analysis. In this article, the benefits and limitations of FAIMS for protein analysis are discussed. The principles and mechanisms of FAIMS separation of ions are described, and the differences between FAIMS and conventional ion mobility spectrometry are detailed. Protein analysis is considered from both the top-down (intact proteins) and the bottom-up (proteolytic peptides) perspective. The roles of FAIMS in the analysis of complex mixtures of multiple intact proteins and in the analysis of multiple conformers of a single protein are assessed. Similarly, the application of FAIMS in proteomics and targeted analysis of peptides are considered.

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.

Comparison of protein expression between human livers and the hepatic cell lines HepG2, Hep3B, and Huh7 using SWATH and MRM-HR proteomics: Focusing on drug-metabolizing enzymes.

PubMed

Shi, Jian; Wang, Xinwen; Lyu, Lingyun; Jiang, Hui; Zhu, Hao-Jie

2018-04-01

Human hepatic cell lines are widely used as an in vitro model for the study of drug metabolism and liver toxicity. However, the validity of this model is still a subject of debate because the expressions of various proteins in the cell lines, including drug-metabolizing enzymes (DMEs), can differ significantly from those in human livers. In the present study, we first conducted an untargeted proteomics analysis of the microsomes of the cell lines HepG2, Hep3B, and Huh7, and compared them to human livers using a sequential window acquisition of all theoretical mass spectra (SWATH) method. Furthermore, high-resolution multiple reaction monitoring (MRM-HR), a targeted proteomic approach, was utilized to compare the expressions of pre-selected DMEs between human livers and the cell lines. In general, the SWATH quantifications were in good agreement with the MRM-HR analysis. Over 3000 protein groups were quantified in the cells and human livers, and the proteome profiles of human livers significantly differed from the cell lines. Among the 101 DMEs quantified with MRM-HR, most were expressed at substantially lower levels in the cell lines. Thus, appropriate caution must be exercised when using these cell lines for the study of hepatic drug metabolism and toxicity. Copyright © 2018 The Japanese Society for the Study of Xenobiotics. Published by Elsevier Ltd. All rights reserved.

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.

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 proteomics analysis software. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

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.

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.

Network-Based Approaches in Drug Discovery and Early Development

PubMed Central

Harrold, JM; Ramanathan, M; Mager, DE

2015-01-01

Identification of novel targets is a critical first step in the drug discovery and development process. Most diseases such as cancer, metabolic disorders, and neurological disorders are complex, and their pathogenesis involves multiple genetic and environmental factors. Finding a viable drug target–drug combination with high potential for yielding clinical success within the efficacy–toxicity spectrum is extremely challenging. Many examples are now available in which network-based approaches show potential for the identification of novel targets and for the repositioning of established targets. The objective of this article is to highlight network approaches for identifying novel targets with greater chances of gaining approved drugs with maximal efficacy and minimal side effects. Further enhancement of these approaches may emerge from effectively integrating computational systems biology with pharmacodynamic systems analysis. Coupling genomics, proteomics, and metabolomics databases with systems pharmacology modeling may aid in the development of disease-specific networks that can be further used to build confidence in target identification. PMID:24025802

The Human Plasma Proteome Draft of 2017: Building on the Human Plasma PeptideAtlas from Mass Spectrometry and Complementary Assays.

PubMed

Schwenk, Jochen M; Omenn, Gilbert S; Sun, Zhi; Campbell, David S; Baker, Mark S; Overall, Christopher M; Aebersold, Ruedi; Moritz, Robert L; Deutsch, Eric W

2017-12-01

Human blood plasma provides a highly accessible window to the proteome of any individual in health and disease. Since its inception in 2002, the Human Proteome Organization's Human Plasma Proteome Project (HPPP) has been promoting advances in the study and understanding of the full protein complement of human plasma and on determining the abundance and modifications of its components. In 2017, we review the history of the HPPP and the advances of human plasma proteomics in general, including several recent achievements. We then present the latest 2017-04 build of Human Plasma PeptideAtlas, which yields ∼43 million peptide-spectrum matches and 122,730 distinct peptide sequences from 178 individual experiments at a 1% protein-level FDR globally across all experiments. Applying the latest Human Proteome Project Data Interpretation Guidelines, we catalog 3509 proteins that have at least two non-nested uniquely mapping peptides of nine amino acids or more and >1300 additional proteins with ambiguous evidence. We apply the same two-peptide guideline to historical PeptideAtlas builds going back to 2006 and examine the progress made in the past ten years in plasma proteome coverage. We also compare the distribution of proteins in historical PeptideAtlas builds in various RNA abundance and cellular localization categories. We then discuss advances in plasma proteomics based on targeted mass spectrometry as well as affinity assays, which during early 2017 target ∼2000 proteins. Finally, we describe considerations about sample handling and study design, concluding with an outlook for future advances in deciphering the human plasma proteome.

C-STrap Sample Preparation Method--In-Situ Cysteinyl Peptide Capture for Bottom-Up Proteomics Analysis in the STrap Format.

PubMed

Zougman, Alexandre; Banks, Rosamonde E

2015-01-01

Recently we introduced the concept of Suspension Trapping (STrap) for bottom-up proteomics sample processing that is based upon SDS-mediated protein extraction, swift detergent removal and rapid reactor-type protein digestion in a quartz depth filter trap. As the depth filter surface is made of silica, it is readily modifiable with various functional groups using the silane coupling chemistries. Thus, during the digest, peptides possessing specific features could be targeted for enrichment by the functionalized depth filter material while non-targeted peptides could be collected as an unbound distinct fraction after the digest. In the example presented here the quartz depth filter surface is functionalized with the pyridyldithiol group therefore enabling reversible in-situ capture of the cysteine-containing peptides generated during the STrap-based digest. The described C-STrap method retains all advantages of the original STrap methodology and provides robust foundation for the conception of the targeted in-situ peptide fractionation in the STrap format for bottom-up proteomics. The presented data support the method's use in qualitative and semi-quantitative proteomics experiments.

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.

Regulation of Lipid Metabolism by Dicer Revealed through SILAC Mice

PubMed Central

Huang, Tai-Chung; Saharabuddhe, Nandini A.; Kim, Min-Sik; Getnet, Derese; Yang, Yi; Peterson, Jonathan M.; Ghosh, Bidyut; Chaerkady, Raghothama; Leach, Steven D.; Marchionni, Luigi; Wong, G. William; Pandey, Akhilesh

2012-01-01

Dicer is a ribonuclease whose major role is to generate mature microRNAs although additional functions have been proposed. Deletion of Dicer leads to embryonic lethality in mice. To study the role of Dicer in adults, we generated mice in which administration of tamoxifen induces deletion of Dicer. Surprisingly, disruption of Dicer in adult mice induced lipid accumulation in the small intestine. To dissect the underlying mechanisms, we carried out miRNA, mRNA and proteomic profiling of small intestine. The proteomic analysis was done using mice metabolically labeled with heavy lysine (SILAC mice) for an in vivo readout. We identified 646 proteins of which 80 were upregulated >2-fold and 75 were downregulated. Consistent with the accumulation of lipids, Dicer disruption caused a marked decrease of microsomal triglyceride transfer protein, long-chain fatty acyl-CoA ligase 5, fatty acid binding protein, and very-long-chain fatty acyl-CoA dehydrogenase, among others. We validated these results using multiple reaction monitoring (MRM) experiments by targeting proteotypic peptides. Our data reveal a previously unappreciated role of Dicer in lipid metabolism. These studies demonstrate a systems biology approach by integrating mouse models, metabolic labeling, gene expression profiling and quantitative proteomics can be a powerful tool for understanding complex biological systems. PMID:22313051

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

Comparative proteomic investigation of metastatic and non-metastatic osteosarcoma cells of human and canine origin

PubMed Central

Roy, Jahnabi; Wycislo, Kathryn L.; Pondenis, Holly; Fan, Timothy M.

2017-01-01

Osteosarcoma is the most common bone cancer in dogs and people. In order to improve clinical outcomes, it is necessary to identify proteins that are differentially expressed by metastatic cells. Membrane bound proteins are responsible for multiple pro-metastatic functions. Therefore characterizing the differential expression of membranous proteins between metastatic and non-metastatic clonal variants will allow the discovery of druggable targets and consequently improve treatment methodology. The objective of this investigation was to systemically identify the membrane-associated proteomics of metastatic and non-metastatic variants of human and canine origin. Two clonal variants of divergent in vivo metastatic potential from human and canine origins were used. The plasma membranes were isolated and peptide fingerprinting was used to identify differentially expressed proteins. Selected proteins were further validated using western blotting, flow cytometry, confocal microscopy and immunohistochemistry. Over 500 proteins were identified for each cell line with nearly 40% of the proteins differentially regulated. Conserved between both species, metastatic variants demonstrated significant differences in expression of membrane proteins that are responsible for pro-metastatic functions. Additionally, CD147, CD44 and vimentin were validated using various biochemical techniques. Taken together, through a comparative proteomic approach we have identified several differentially expressed cell membrane proteins that will help in the development of future therapeutics. PMID:28910304

Comparative proteomic investigation of metastatic and non-metastatic osteosarcoma cells of human and canine origin.

PubMed

Roy, Jahnabi; Wycislo, Kathryn L; Pondenis, Holly; Fan, Timothy M; Das, Aditi

2017-01-01

Osteosarcoma is the most common bone cancer in dogs and people. In order to improve clinical outcomes, it is necessary to identify proteins that are differentially expressed by metastatic cells. Membrane bound proteins are responsible for multiple pro-metastatic functions. Therefore characterizing the differential expression of membranous proteins between metastatic and non-metastatic clonal variants will allow the discovery of druggable targets and consequently improve treatment methodology. The objective of this investigation was to systemically identify the membrane-associated proteomics of metastatic and non-metastatic variants of human and canine origin. Two clonal variants of divergent in vivo metastatic potential from human and canine origins were used. The plasma membranes were isolated and peptide fingerprinting was used to identify differentially expressed proteins. Selected proteins were further validated using western blotting, flow cytometry, confocal microscopy and immunohistochemistry. Over 500 proteins were identified for each cell line with nearly 40% of the proteins differentially regulated. Conserved between both species, metastatic variants demonstrated significant differences in expression of membrane proteins that are responsible for pro-metastatic functions. Additionally, CD147, CD44 and vimentin were validated using various biochemical techniques. Taken together, through a comparative proteomic approach we have identified several differentially expressed cell membrane proteins that will help in the development of future therapeutics.

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

Mammalian plasma membrane proteins as potential biomarkers and drug targets.

PubMed

Rucevic, Marijana; Hixson, Douglas; Josic, Djuro

2011-06-01

Defining the plasma membrane proteome is crucial to understand the role of plasma membrane in fundamental biological processes. Change in membrane proteins is one of the first events that take place under pathological conditions, making plasma membrane proteins a likely source of potential disease biomarkers with prognostic or diagnostic potential. Membrane proteins are also potential targets for monoclonal antibodies and other drugs that block receptors or inhibit enzymes essential to the disease progress. Despite several advanced methods recently developed for the analysis of hydrophobic proteins and proteins with posttranslational modifications, integral membrane proteins are still under-represented in plasma membrane proteome. Recent advances in proteomic investigation of plasma membrane proteins, defining their roles as diagnostic and prognostic disease biomarkers and as target molecules in disease treatment, are presented. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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 sensitive biotypes, our study identified multiple proteins (involved in photosynthesis, oxidative phosphorylation, and fatty acid biosynthesis) that are putatively linked to B. syzigachne herbicide response. This large-scale proteomics study, sorely lacking in weed science, contributes valuable data that can be applied to more fine-tuned analyses on the functions of specific proteins in herbicide resistance. Copyright © 2017 Elsevier B.V. All rights reserved.

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

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

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

The selected reaction monitoring/multiple reaction monitoring-based mass spectrometry approach for the accurate quantitation of proteins: clinical applications in the cardiovascular diseases.

PubMed

Gianazza, Erica; Tremoli, Elena; Banfi, Cristina

2014-12-01

Selected reaction monitoring, also known as multiple reaction monitoring, is a powerful targeted mass spectrometry approach for a confident quantitation of proteins/peptides in complex biological samples. In recent years, its optimization and application have become pivotal and of great interest in clinical research to derive useful outcomes for patient care. Thus, selected reaction monitoring/multiple reaction monitoring is now used as a highly sensitive and selective method for the evaluation of protein abundances and biomarker verification with potential applications in medical screening. This review describes technical aspects for the development of a robust multiplex assay and discussing its recent applications in cardiovascular proteomics: verification of promising disease candidates to select only the highest quality peptides/proteins for a preclinical validation, as well as quantitation of protein isoforms and post-translational modifications.

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.

NOVEL METHODS FOR TARGET PROTEIN IDENTIFICATION USING IMMUNOPRECIPITATION - LC/MS/MS

EPA Science Inventory

Proteomics provides a powerful approach to screen and analyze responses to environmental exposures which induce alterations in protein expression, phosphorylation. ubiquitinylation, oxidation. and modulation of general proteome function. Post-translational modifications (PTM) of ...

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.

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.

Development of a Multiplexed Liquid Chromatography Multiple-Reaction-Monitoring Mass Spectrometry (LC-MRM/MS) Method for Evaluation of Salivary Proteins as Oral Cancer Biomarkers*

PubMed Central

Chen, Hsiao-Wei; Wu, Chun-Feng; Chu, Lichieh Julie; Chiang, Wei-Fang; Wu, Chih-Ching; Yu, Jau-Song; Tsai, Cheng-Han; Liang, Kung-Hao; Chang, Yu-Sun; Wu, Maureen; Ou Yang, Wei-Ting

2017-01-01

Multiple (selected) reaction monitoring (MRM/SRM) of peptides is a growing technology for target protein quantification because it is more robust, precise, accurate, high-throughput, and multiplex-capable than antibody-based techniques. The technique has been applied clinically to the large-scale quantification of multiple target proteins in different types of fluids. However, previous MRM-based studies have placed less focus on sample-preparation workflow and analytical performance in the precise quantification of proteins in saliva, a noninvasively sampled body fluid. In this study, we evaluated the analytical performance of a simple and robust multiple reaction monitoring (MRM)-based targeted proteomics approach incorporating liquid chromatography with mass spectrometry detection (LC-MRM/MS). This platform was used to quantitatively assess the biomarker potential of a group of 56 salivary proteins that have previously been associated with human cancers. To further enhance the development of this technology for assay of salivary samples, we optimized the workflow for salivary protein digestion and evaluated quantification performance, robustness and technical limitations in analyzing clinical samples. Using a clinically well-characterized cohort of two independent clinical sample sets (total n = 119), we quantitatively characterized these protein biomarker candidates in saliva specimens from controls and oral squamous cell carcinoma (OSCC) patients. The results clearly showed a significant elevation of most targeted proteins in saliva samples from OSCC patients compared with controls. Overall, this platform was capable of assaying the most highly multiplexed panel of salivary protein biomarkers, highlighting the clinical utility of MRM in oral cancer biomarker research. PMID:28235782

Chemical-agnostic hazard prediction: statistical inference of in ...

EPA Pesticide Factsheets

Toxicity pathways have been defined as normal cellular pathways that, when sufficiently perturbed as a consequence of chemical exposure, lead to an adverse outcome. If an exposure alters one or more normal biological pathways to an extent that leads to an adverse toxicity outcome, a significant correlation must exist between the exposure, the extent of pathway alteration, and the degree of adverse outcome. Biological pathways are regulated at multiple levels, including transcriptional, post-transcriptional, post-translational, and targeted degradation, each of which can affect the levels and extents of modification of proteins involved in the pathways. Significant alterations of toxicity pathways resulting from changes in regulation at any of these levels therefore are likely to be detectable as alterations in the proteome. We hypothesize that significant correlations between exposures, adverse outcomes, and changes in the proteome have the potential to identify putative toxicity pathways, facilitating selection of candidate targets for high throughput screening, even in the absence of a priori knowledge of either the specific pathways involved or the specific agents inducing the pathway alterations. We explored this hypothesis in vitro in BEAS-2B human airway epithelial cells exposed to different concentrations of Ni2+, Cd2+, and Cr6+, alone and in defined mixtures. Levels and phosphorylation status of a variety of signaling pathway proteins and cytokines were

Effect of collision energy optimization on the measurement of peptides by selected reaction monitoring (SRM) mass spectrometry.

PubMed

Maclean, Brendan; Tomazela, Daniela M; Abbatiello, Susan E; Zhang, Shucha; Whiteaker, Jeffrey R; Paulovich, Amanda G; Carr, Steven A; Maccoss, Michael J

2010-12-15

Proteomics experiments based on Selected Reaction Monitoring (SRM, also referred to as Multiple Reaction Monitoring or MRM) are being used to target large numbers of protein candidates in complex mixtures. At present, instrument parameters are often optimized for each peptide, a time and resource intensive process. Large SRM experiments are greatly facilitated by having the ability to predict MS instrument parameters that work well with the broad diversity of peptides they target. For this reason, we investigated the impact of using simple linear equations to predict the collision energy (CE) on peptide signal intensity and compared it with the empirical optimization of the CE for each peptide and transition individually. Using optimized linear equations, the difference between predicted and empirically derived CE values was found to be an average gain of only 7.8% of total peak area. We also found that existing commonly used linear equations fall short of their potential, and should be recalculated for each charge state and when introducing new instrument platforms. We provide a fully automated pipeline for calculating these equations and individually optimizing CE of each transition on SRM instruments from Agilent, Applied Biosystems, Thermo-Scientific and Waters in the open source Skyline software tool ( http://proteome.gs.washington.edu/software/skyline ).

Synthetic Peptide Arrays for Pathway-Level Protein Monitoring by Liquid Chromatography-Tandem Mass Spectrometry*

PubMed Central

Hewel, Johannes A.; Liu, Jian; Onishi, Kento; Fong, Vincent; Chandran, Shamanta; Olsen, Jonathan B.; Pogoutse, Oxana; Schutkowski, Mike; Wenschuh, Holger; Winkler, Dirk F. H.; Eckler, Larry; Zandstra, Peter W.; Emili, Andrew

2010-01-01

Effective methods to detect and quantify functionally linked regulatory proteins in complex biological samples are essential for investigating mammalian signaling pathways. Traditional immunoassays depend on proprietary reagents that are difficult to generate and multiplex, whereas global proteomic profiling can be tedious and can miss low abundance proteins. Here, we report a target-driven liquid chromatography-tandem mass spectrometry (LC-MS/MS) strategy for selectively examining the levels of multiple low abundance components of signaling pathways which are refractory to standard shotgun screening procedures and hence appear limited in current MS/MS repositories. Our stepwise approach consists of: (i) synthesizing microscale peptide arrays, including heavy isotope-labeled internal standards, for use as high quality references to (ii) build empirically validated high density LC-MS/MS detection assays with a retention time scheduling system that can be used to (iii) identify and quantify endogenous low abundance protein targets in complex biological mixtures with high accuracy by correlation to a spectral database using new software tools. The method offers a flexible, rapid, and cost-effective means for routine proteomic exploration of biological systems including “label-free” quantification, while minimizing spurious interferences. As proof-of-concept, we have examined the abundance of transcription factors and protein kinases mediating pluripotency and self-renewal in embryonic stem cell populations. PMID:20467045

Comparative systems analysis of the secretome of the opportunistic pathogen Aspergillus fumigatus and other Aspergillus species.

PubMed

Vivek-Ananth, R P; Mohanraj, Karthikeyan; Vandanashree, Muralidharan; Jhingran, Anupam; Craig, James P; Samal, Areejit

2018-04-26

Aspergillus fumigatus and multiple other Aspergillus species cause a wide range of lung infections, collectively termed aspergillosis. Aspergilli are ubiquitous in environment with healthy immune systems routinely eliminating inhaled conidia, however, Aspergilli can become an opportunistic pathogen in immune-compromised patients. The aspergillosis mortality rate and emergence of drug-resistance reveals an urgent need to identify novel targets. Secreted and cell membrane proteins play a critical role in fungal-host interactions and pathogenesis. Using a computational pipeline integrating data from high-throughput experiments and bioinformatic predictions, we have identified secreted and cell membrane proteins in ten Aspergillus species known to cause aspergillosis. Small secreted and effector-like proteins similar to agents of fungal-plant pathogenesis were also identified within each secretome. A comparison with humans revealed that at least 70% of Aspergillus secretomes have no sequence similarity with the human proteome. An analysis of antigenic qualities of Aspergillus proteins revealed that the secretome is significantly more antigenic than cell membrane proteins or the complete proteome. Finally, overlaying an expression dataset, four A. fumigatus proteins upregulated during infection and with available structures, were found to be structurally similar to known drug target proteins in other organisms, and were able to dock in silico with the respective drug.

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

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.

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.

Integrating Transcriptomic and Proteomic Data Using Predictive Regulatory Network Models of Host Response to Pathogens

PubMed Central

Chasman, Deborah; Walters, Kevin B.; Lopes, Tiago J. S.; Eisfeld, Amie J.; Kawaoka, Yoshihiro; Roy, Sushmita

2016-01-01

Mammalian host response to pathogenic infections is controlled by a complex regulatory network connecting regulatory proteins such as transcription factors and signaling proteins to target genes. An important challenge in infectious disease research is to understand molecular similarities and differences in mammalian host response to diverse sets of pathogens. Recently, systems biology studies have produced rich collections of omic profiles measuring host response to infectious agents such as influenza viruses at multiple levels. To gain a comprehensive understanding of the regulatory network driving host response to multiple infectious agents, we integrated host transcriptomes and proteomes using a network-based approach. Our approach combines expression-based regulatory network inference, structured-sparsity based regression, and network information flow to infer putative physical regulatory programs for expression modules. We applied our approach to identify regulatory networks, modules and subnetworks that drive host response to multiple influenza infections. The inferred regulatory network and modules are significantly enriched for known pathways of immune response and implicate apoptosis, splicing, and interferon signaling processes in the differential response of viral infections of different pathogenicities. We used the learned network to prioritize regulators and study virus and time-point specific networks. RNAi-based knockdown of predicted regulators had significant impact on viral replication and include several previously unknown regulators. Taken together, our integrated analysis identified novel module level patterns that capture strain and pathogenicity-specific patterns of expression and helped identify important regulators of host response to influenza infection. PMID:27403523

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.

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

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.

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.

A Computational Tool to Detect and Avoid Redundancy in Selected Reaction Monitoring

PubMed Central

Röst, Hannes; Malmström, Lars; Aebersold, Ruedi

2012-01-01

Selected reaction monitoring (SRM), also called multiple reaction monitoring, has become an invaluable tool for targeted quantitative proteomic analyses, but its application can be compromised by nonoptimal selection of transitions. In particular, complex backgrounds may cause ambiguities in SRM measurement results because peptides with interfering transitions similar to those of the target peptide may be present in the sample. Here, we developed a computer program, the SRMCollider, that calculates nonredundant theoretical SRM assays, also known as unique ion signatures (UIS), for a given proteomic background. We show theoretically that UIS of three transitions suffice to conclusively identify 90% of all yeast peptides and 85% of all human peptides. Using predicted retention times, the SRMCollider also simulates time-scheduled SRM acquisition, which reduces the number of interferences to consider and leads to fewer transitions necessary to construct an assay. By integrating experimental fragment ion intensities from large scale proteome synthesis efforts (SRMAtlas) with the information content-based UIS, we combine two orthogonal approaches to create high quality SRM assays ready to be deployed. We provide a user friendly, open source implementation of an algorithm to calculate UIS of any order that can be accessed online at http://www.srmcollider.org to find interfering transitions. Finally, our tool can also simulate the specificity of novel data-independent MS acquisition methods in Q1–Q3 space. This allows us to predict parameters for these methods that deliver a specificity comparable with that of SRM. Using SRM interference information in addition to other sources of information can increase the confidence in an SRM measurement. We expect that the consideration of information content will become a standard step in SRM assay design and analysis, facilitated by the SRMCollider. PMID:22535207

Display technologies: application for the discovery of drug and gene delivery agents

PubMed Central

Sergeeva, Anna; Kolonin, Mikhail G.; Molldrem, Jeffrey J.; Pasqualini, Renata; Arap, Wadih

2007-01-01

Recognition of molecular diversity of cell surface proteomes in disease is essential for the development of targeted therapies. Progress in targeted therapeutics requires establishing effective approaches for high-throughput identification of agents specific for clinically relevant cell surface markers. Over the past decade, a number of platform strategies have been developed to screen polypeptide libraries for ligands targeting receptors selectively expressed in the context of various cell surface proteomes. Streamlined procedures for identification of ligand-receptor pairs that could serve as targets in disease diagnosis, profiling, imaging and therapy have relied on the display technologies, in which polypeptides with desired binding profiles can be serially selected, in a process called biopanning, based on their physical linkage with the encoding nucleic acid. These technologies include virus/phage display, cell display, ribosomal display, mRNA display and covalent DNA display (CDT), with phage display being by far the most utilized. The scope of this review is the recent advancements in the display technologies with a particular emphasis on molecular mapping of cell surface proteomes with peptide phage display. Prospective applications of targeted compounds derived from display libraries in the discovery of targeted drugs and gene therapy vectors are discussed. PMID:17123658

Activation of antioxidant pathways in ras-mediated oncogenic transformation of human surface ovarian epithelial cells revealed by functional proteomics and mass spectrometry.

PubMed

Young, Travis W; Mei, Fang C; Yang, Gong; Thompson-Lanza, Jennifer A; Liu, Jinsong; Cheng, Xiaodong

2004-07-01

Cellular transformation is a complex process involving genetic alterations associated with multiple signaling pathways. Development of a transformation model using defined genetic elements has provided an opportunity to elucidate the role of oncogenes and tumor suppressor genes in the initiation and development of ovarian cancer. To study the cellular and molecular mechanisms of Ras-mediated oncogenic transformation of ovarian epithelial cells, we used a proteomic approach involving two-dimensional electrophoresis and mass spectrometry to profile two ovarian epithelial cell lines, one immortalized with SV40 T/t antigens and the human catalytic subunit of telomerase and the other transformed with an additional oncogenic ras(V12) allele. Of approximately 2200 observed protein spots, we have identified >30 protein targets that showed significant changes between the immortalized and transformed cell lines using peptide mass fingerprinting. Among these identified targets, one most notable group of proteins altered significantly consists of enzymes involved in cellular redox balance. Detailed analysis of these protein targets suggests that activation of Ras-signaling pathways increases the threshold of reactive oxidative species (ROS) tolerance by up-regulating the overall antioxidant capacity of cells, especially in mitochondria. This enhanced antioxidant capacity protects the transformed cells from high levels of ROS associated with the uncontrolled growth potential of tumor cells. It is conceivable that an enhanced antioxidation capability may constitute a common mechanism for tumor cells to evade apoptosis induced by oxidative stresses at high ROS levels.

Biocidal Inactivation of Lactococcus lactis Bacteriophages: Efficacy and Targets of Commonly Used Sanitizers

PubMed Central

Hayes, Stephen; Murphy, James; Mahony, Jennifer; Lugli, Gabriele A.; Ventura, Marco; Noben, Jean-Paul; Franz, Charles M. A. P.; Neve, Horst; Nauta, Arjen; Van Sinderen, Douwe

2017-01-01

Lactococcus lactis strains, being intensely used in the dairy industry, are particularly vulnerable to members of the so-called 936 group of phages. Sanitization and disinfection using purpose-made biocidal solutions is a critical step in controlling phage contamination in such dairy processing plants. The susceptibility of 36 936 group phages to biocidal treatments was examined using 14 biocides and commercially available sanitizers. The targets of a number of these biocides were investigated by means of electron microscopic and proteomic analyses. The results from this study highlight significant variations in phage resistance to biocides among 936 phages. Furthermore, rather than possessing resistance to specific biocides or biocide types, biocide-resistant phages tend to possess a broad tolerance to multiple classes of antimicrobial compounds. PMID:28210242

Spatially Directed Proteomics of the Human Lens Outer Cortex Reveals an Intermediate Filament Switch Associated With the Remodeling Zone

PubMed Central

Wenke, Jamie L.; McDonald, W. Hayes; Schey, Kevin L.

2016-01-01

Purpose To quantify protein changes in the morphologically distinct remodeling zone (RZ) and adjacent regions of the human lens outer cortex using spatially directed quantitative proteomics. Methods Lightly fixed human lens sections were deparaffinized and membranes labeled with fluorescent wheat germ agglutinin (WGA-TRITC). Morphology directed laser capture microdissection (LCM) was used to isolate tissue from four distinct regions of human lens outer cortex: differentiating zone (DF), RZ, transition zone (TZ), and inner cortex (IC). Liquid chromatography-tandem mass spectrometry (LC-MS/MS) of the plasma membrane fraction from three lenses (21-, 22-, and 27-year) revealed changes in major cytoskeletal proteins including vimentin, filensin, and phakinin. Peptides from proteins of interest were quantified using multiple reaction monitoring (MRM) mass spectrometry and isotopically-labeled internal peptide standards. Results Results revealed an intermediate filament switch from vimentin to beaded filament proteins filensin and phakinin that occurred at the RZ. Several other cytoskeletal proteins showed significant changes between regions, while most crystallins remained unchanged. Targeted proteomics provided accurate, absolute quantification of these proteins and confirmed vimentin, periplakin, and periaxin decrease from the DF to the IC, while filensin, phakinin, and brain acid soluble protein 1 (BASP1) increase significantly at the RZ. Conclusions Mass spectrometry-compatible fixation and morphology directed laser capture enabled proteomic analysis of narrow regions in the human lens outer cortex. Results reveal dramatic cytoskeletal protein changes associated with the RZ, suggesting that one role of these proteins is in membrane deformation and/or the establishment of ball and socket joints in the human RZ. PMID:27537260

Network Understanding of Herb Medicine via Rapid Identification of Ingredient-Target Interactions

NASA Astrophysics Data System (ADS)

Zhang, Hai-Ping; Pan, Jian-Bo; Zhang, Chi; Ji, Nan; Wang, Hao; Ji, Zhi-Liang

2014-01-01

Today, herb medicines have become the major source for discovery of novel agents in countermining diseases. However, many of them are largely under-explored in pharmacology due to the limitation of current experimental approaches. Therefore, we proposed a computational framework in this study for network understanding of herb pharmacology via rapid identification of putative ingredient-target interactions in human structural proteome level. A marketing anti-cancer herb medicine in China, Yadanzi (Brucea javanica), was chosen for mechanistic study. Total 7,119 ingredient-target interactions were identified for thirteen Yadanzi active ingredients. Among them, about 29.5% were estimated to have better binding affinity than their corresponding marketing drug-target interactions. Further Bioinformatics analyses suggest that simultaneous manipulation of multiple proteins in the MAPK signaling pathway and the phosphorylation process of anti-apoptosis may largely answer for Yadanzi against non-small cell lung cancers. In summary, our strategy provides an efficient however economic solution for systematic understanding of herbs' power.

Network understanding of herb medicine via rapid identification of ingredient-target interactions.

PubMed

Zhang, Hai-Ping; Pan, Jian-Bo; Zhang, Chi; Ji, Nan; Wang, Hao; Ji, Zhi-Liang

2014-01-16

Today, herb medicines have become the major source for discovery of novel agents in countermining diseases. However, many of them are largely under-explored in pharmacology due to the limitation of current experimental approaches. Therefore, we proposed a computational framework in this study for network understanding of herb pharmacology via rapid identification of putative ingredient-target interactions in human structural proteome level. A marketing anti-cancer herb medicine in China, Yadanzi (Brucea javanica), was chosen for mechanistic study. Total 7,119 ingredient-target interactions were identified for thirteen Yadanzi active ingredients. Among them, about 29.5% were estimated to have better binding affinity than their corresponding marketing drug-target interactions. Further Bioinformatics analyses suggest that simultaneous manipulation of multiple proteins in the MAPK signaling pathway and the phosphorylation process of anti-apoptosis may largely answer for Yadanzi against non-small cell lung cancers. In summary, our strategy provides an efficient however economic solution for systematic understanding of herbs' power.

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.

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.

iProphet: Multi-level Integrative Analysis of Shotgun Proteomic Data Improves Peptide and Protein Identification Rates and Error Estimates*

PubMed Central

Shteynberg, David; Deutsch, Eric W.; Lam, Henry; Eng, Jimmy K.; Sun, Zhi; Tasman, Natalie; Mendoza, Luis; Moritz, Robert L.; Aebersold, Ruedi; Nesvizhskii, Alexey I.

2011-01-01

The combination of tandem mass spectrometry and sequence database searching is the method of choice for the identification of peptides and the mapping of proteomes. Over the last several years, the volume of data generated in proteomic studies has increased dramatically, which challenges the computational approaches previously developed for these data. Furthermore, a multitude of search engines have been developed that identify different, overlapping subsets of the sample peptides from a particular set of tandem mass spectrometry spectra. We present iProphet, the new addition to the widely used open-source suite of proteomic data analysis tools Trans-Proteomics Pipeline. Applied in tandem with PeptideProphet, it provides more accurate representation of the multilevel nature of shotgun proteomic data. iProphet combines the evidence from multiple identifications of the same peptide sequences across different spectra, experiments, precursor ion charge states, and modified states. It also allows accurate and effective integration of the results from multiple database search engines applied to the same data. The use of iProphet in the Trans-Proteomics Pipeline increases the number of correctly identified peptides at a constant false discovery rate as compared with both PeptideProphet and another state-of-the-art tool Percolator. As the main outcome, iProphet permits the calculation of accurate posterior probabilities and false discovery rate estimates at the level of sequence identical peptide identifications, which in turn leads to more accurate probability estimates at the protein level. Fully integrated with the Trans-Proteomics Pipeline, it supports all commonly used MS instruments, search engines, and computer platforms. The performance of iProphet is demonstrated on two publicly available data sets: data from a human whole cell lysate proteome profiling experiment representative of typical proteomic data sets, and from a set of Streptococcus pyogenes experiments more representative of organism-specific composite data sets. PMID:21876204

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.

Epsilon-Q: An Automated Analyzer Interface for Mass Spectral Library Search and Label-Free Protein Quantification.

PubMed

Cho, Jin-Young; Lee, Hyoung-Joo; Jeong, Seul-Ki; Paik, Young-Ki

2017-12-01

Mass spectrometry (MS) is a widely used proteome analysis tool for biomedical science. In an MS-based bottom-up proteomic approach to protein identification, sequence database (DB) searching has been routinely used because of its simplicity and convenience. However, searching a sequence DB with multiple variable modification options can increase processing time, false-positive errors in large and complicated MS data sets. Spectral library searching is an alternative solution, avoiding the limitations of sequence DB searching and allowing the detection of more peptides with high sensitivity. Unfortunately, this technique has less proteome coverage, resulting in limitations in the detection of novel and whole peptide sequences in biological samples. To solve these problems, we previously developed the "Combo-Spec Search" method, which uses manually multiple references and simulated spectral library searching to analyze whole proteomes in a biological sample. In this study, we have developed a new analytical interface tool called "Epsilon-Q" to enhance the functions of both the Combo-Spec Search method and label-free protein quantification. Epsilon-Q performs automatically multiple spectral library searching, class-specific false-discovery rate control, and result integration. It has a user-friendly graphical interface and demonstrates good performance in identifying and quantifying proteins by supporting standard MS data formats and spectrum-to-spectrum matching powered by SpectraST. Furthermore, when the Epsilon-Q interface is combined with the Combo-Spec search method, called the Epsilon-Q system, it shows a synergistic function by outperforming other sequence DB search engines for identifying and quantifying low-abundance proteins in biological samples. The Epsilon-Q system can be a versatile tool for comparative proteome analysis based on multiple spectral libraries and label-free quantification.

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.

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 prior mycological and molecular observations, the findings from this proteomic study support the integrated micro-ecosystem hypothesis for natural Cs.

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 during maturation. In conjunction with prior mycological and molecular observations, the findings from this proteomic study support the integrated micro-ecosystem hypothesis for natural Cs. PMID:25310818

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

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.

Label-free protein quantification using LC-coupled ion trap or FT mass spectrometry: Reproducibility, linearity, and application with complex proteomes.

PubMed

Wang, Guanghui; Wu, Wells W; Zeng, Weihua; Chou, Chung-Lin; Shen, Rong-Fong

2006-05-01

A critical step in protein biomarker discovery is the ability to contrast proteomes, a process referred generally as quantitative proteomics. While stable-isotope labeling (e.g., ICAT, 18O- or 15N-labeling, or AQUA) remains the core technology used in mass spectrometry-based proteomic quantification, increasing efforts have been directed to the label-free approach that relies on direct comparison of peptide peak areas between LC-MS runs. This latter approach is attractive to investigators for its simplicity as well as cost effectiveness. In the present study, the reproducibility and linearity of using a label-free approach to highly complex proteomes were evaluated. Various amounts of proteins from different proteomes were subjected to repeated LC-MS analyses using an ion trap or Fourier transform mass spectrometer. Highly reproducible data were obtained between replicated runs, as evidenced by nearly ideal Pearson's correlation coefficients (for ion's peak areas or retention time) and average peak area ratios. In general, more than 50% and nearly 90% of the peptide ion ratios deviated less than 10% and 20%, respectively, from the average in duplicate runs. In addition, the multiplicity ratios of the amounts of proteins used correlated nicely with the observed averaged ratios of peak areas calculated from detected peptides. Furthermore, the removal of abundant proteins from the samples led to an improvement in reproducibility and linearity. A computer program has been written to automate the processing of data sets from experiments with groups of multiple samples for statistical analysis. Algorithms for outlier-resistant mean estimation and for adjusting statistical significance threshold in multiplicity of testing were incorporated to minimize the rate of false positives. The program was applied to quantify changes in proteomes of parental and p53-deficient HCT-116 human cells and found to yield reproducible results. Overall, this study demonstrates an alternative approach that allows global quantification of differentially expressed proteins in complex proteomes. The utility of this method to biomarker discovery is likely to synergize with future improvements in the detecting sensitivity of mass spectrometers.

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.

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

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/.

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

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.

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.

PeptideDepot: Flexible Relational Database for Visual Analysis of Quantitative Proteomic Data and Integration of Existing Protein Information

PubMed Central

Yu, Kebing; Salomon, Arthur R.

2010-01-01

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 tandem mass spectrometry (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 a variety of 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 (HTAPP) used in the automated acquisition and post-acquisition analysis of proteomic data. PMID:19834895

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.

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 as a response to HFD, mechanisms mediating a sustained ‘perpetual cycle' of appetite enhancement were observed. The GlyR protein may constitute a novel treatment target for the reduction of central orexigenic signals in obesity. PMID:27110685

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 mediating a sustained 'perpetual cycle' of appetite enhancement were observed. The GlyR protein may constitute a novel treatment target for the reduction of central orexigenic signals in obesity.

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

A brain proteomic investigation of rapamycin effects in the Tsc1+/- mouse model.

PubMed

Wesseling, Hendrik; Elgersma, Ype; Bahn, Sabine

2017-01-01

Tuberous sclerosis complex (TSC) is a rare monogenic disorder characterized by benign tumors in multiple organs as well as a high prevalence of epilepsy, intellectual disability and autism. TSC is caused by inactivating mutations in the TSC1 or TSC2 genes. Heterozygocity induces hyperactivation of mTOR which can be inhibited by mTOR inhibitors, such as rapamycin, which have proven efficacy in the treatment of TSC-associated symptoms. The aim of the present study was (1) to identify molecular changes associated with social and cognitive deficits in the brain tissue of Tsc1 +/- mice and (2) to investigate the molecular effects of rapamycin treatment, which has been shown to ameliorate genotype-related behavioural deficits. Molecular alterations in the frontal cortex and hippocampus of Tsc1 +/- and control mice, with or without rapamycin treatment, were investigated. A quantitative mass spectrometry-based shotgun proteomic approach (LC-MS E ) was employed as an unbiased method to detect changes in protein levels. Changes identified in the initial profiling stage were validated using selected reaction monitoring (SRM). Protein Set Enrichment Analysis was employed to identify dysregulated pathways. LC-MS E analysis of Tsc1 +/- mice and controls ( n  = 30) identified 51 proteins changed in frontal cortex and 108 in the hippocampus. Bioinformatic analysis combined with targeted proteomic validation revealed several dysregulated molecular pathways. Using targeted assays, proteomic alterations in the hippocampus validated the pathways "myelination", "dendrite," and "oxidative stress", an upregulation of ribosomal proteins and the mTOR kinase. LC-MS E analysis was also employed on Tsc1 +/- and wildtype mice ( n  = 34) treated with rapamycin or vehicle. Rapamycin treatment exerted a stronger proteomic effect in Tsc1 +/- mice with significant changes (mainly decreased expression) in 231 and 106 proteins, respectively. The cellular pathways "oxidative stress" and "apoptosis" were found to be affected in Tsc1 +/- mice and the cellular compartments "myelin sheet" and "neurofilaments" were affected by rapamycin treatment. Thirty-three proteins which were altered in Tsc1 +/- mice were normalized following rapamycin treatment, amongst them oxidative stress related proteins, myelin-specific and ribosomal proteins. Molecular changes in the Tsc1 +/- mouse brain were more prominent in the hippocampus compared to the frontal cortex. Pathways linked to myelination and oxidative stress response were prominently affected and, at least in part, normalized following rapamycin treatment. The results could aid in the identification of novel drug targets for the treatment of cognitive, social and psychiatric symptoms in autism spectrum disorders. Similar pathways have also been implicated in other psychiatric and neurodegenerative disorders and could imply similar disease processes. Thus, the potential efficacy of mTOR inhibitors warrants further investigation not only for autism spectrum disorders but also for other neuropsychiatric and neurodegenerative diseases.

The Role of Central Metabolism in Prostate Cancer Progression

DTIC Science & Technology

2013-09-01

prostate tissue for differences in tumor growth, proteomes and intermediates in polyunsaturated fatty acid (PUFA) metabolism . The use of the... MRM -based targeted proteomics. She has also learned a great deal of techniques in molecular and cell biology. As her initial study, she transfected

Disulfide proteome yields a detailed understanding of redox regulations: a model study of thioredoxin-linked reactions in seed germination.

PubMed

Yano, Hiroyuki; Kuroda, Masaharu

2006-01-01

Accumulating evidence suggests that redox regulations play important roles in a broad spectrum of biological processes. Recently, Yano et al. developed a disulfide proteome technique that comprehensively visualizes redox change in proteins. In this paper, using the disulfide proteome, we examined rice bran and identified fragments of embryo-specific protein and dienelactone hydrolase as putative targets of thioredoxin. Also, monitoring of the endogenous and recombinant effects of thioredoxin on rice bran proteins and supporting in vivo observations propose a mechanism of redox regulation in seed germination, in which thioredoxin activates cysteine protease with a concurrent unfolding of its substrate, the embryo-specific protein. Our findings suggest that thioredoxin controls the lifetime of specific proteins effectively by regulating the redox reactions coordinately. The model study demonstrates that the disulfide proteome technique is useful not only for identifying targets of thioredoxin, but also for clarify the detailed mechanism of redox regulation.

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

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.

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.

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.

Comparative salivary proteomics analysis of children with and without dental caries using the iTRAQ/MRM approach.

PubMed

Wang, Kun; Wang, Yufei; Wang, Xiuqing; Ren, Qian; Han, Sili; Ding, Longjiang; Li, Zhongcheng; Zhou, Xuedong; Li, Wei; Zhang, Linglin

2018-01-19

Dental caries is a major worldwide oral disease afflicting a large proportion of children. As an important host factor of caries susceptibility, saliva plays a significant role in the occurrence and development of caries. The aim of the present study was to characterize the healthy and cariogenic salivary proteome and determine the changes in salivary protein expression of children with varying degrees of active caries, also to establish salivary proteome profiles with a potential therapeutic use against dental caries. In this study, unstimulated saliva samples were collected from 30 children (age 10-12 years) with no dental caries (NDC, n = 10), low dental caries (LDC, n = 10), and high dental caries (HDC, n = 10). Salivary proteins were extracted, reduced, alkylated, trypsin digested and labeled with isobaric tags for relative and absolute quantitation, and then they were analyzed with GO annotation, biological pathway analysis, hierarchical clustering analysis, and protein-protein interaction analysis. Targeted verifications were then performed using multiple reaction monitoring mass spectrometry. A total of 244 differentially expressed proteins annotated with GO annotation in biological processes, cellular component and molecular function were identified in comparisons among children with varying degrees of active caries. A number of caries-related proteins as well as pathways were identified in this study. As compared with caries-free children, the most significantly enriched pathways involved by the up-regulated proteins in LDC and HDC were the ubiquitin mediated proteolysis pathway and African trypanosomiasis pathway, respectively. Subsequently, we selected 53 target proteins with differential expression in different comparisons, including mucin 7, mucin 5B, histatin 1, cystatin S and cystatin SN, basic salivary proline rich protein 2, for further verification using MRM assays. Protein-protein interaction analysis of these proteins revealed complex protein interaction networks, indicating synergistic action of salivary proteins in caries resistance or cariogenicity. Overall, our results afford new insight into the salivary proteome of children with dental caries. These findings might have bright prospect in future in developing novel biomimetic peptides with preventive and therapeutic benefits for childhood caries.

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.

Development of a Multiplexed Liquid Chromatography Multiple-Reaction-Monitoring Mass Spectrometry (LC-MRM/MS) Method for Evaluation of Salivary Proteins as Oral Cancer Biomarkers.

PubMed

Chen, Yi-Ting; Chen, Hsiao-Wei; Wu, Chun-Feng; Chu, Lichieh Julie; Chiang, Wei-Fang; Wu, Chih-Ching; Yu, Jau-Song; Tsai, Cheng-Han; Liang, Kung-Hao; Chang, Yu-Sun; Wu, Maureen; Ou Yang, Wei-Ting

2017-05-01

Multiple (selected) reaction monitoring (MRM/SRM) of peptides is a growing technology for target protein quantification because it is more robust, precise, accurate, high-throughput, and multiplex-capable than antibody-based techniques. The technique has been applied clinically to the large-scale quantification of multiple target proteins in different types of fluids. However, previous MRM-based studies have placed less focus on sample-preparation workflow and analytical performance in the precise quantification of proteins in saliva, a noninvasively sampled body fluid. In this study, we evaluated the analytical performance of a simple and robust multiple reaction monitoring (MRM)-based targeted proteomics approach incorporating liquid chromatography with mass spectrometry detection (LC-MRM/MS). This platform was used to quantitatively assess the biomarker potential of a group of 56 salivary proteins that have previously been associated with human cancers. To further enhance the development of this technology for assay of salivary samples, we optimized the workflow for salivary protein digestion and evaluated quantification performance, robustness and technical limitations in analyzing clinical samples. Using a clinically well-characterized cohort of two independent clinical sample sets (total n = 119), we quantitatively characterized these protein biomarker candidates in saliva specimens from controls and oral squamous cell carcinoma (OSCC) patients. The results clearly showed a significant elevation of most targeted proteins in saliva samples from OSCC patients compared with controls. Overall, this platform was capable of assaying the most highly multiplexed panel of salivary protein biomarkers, highlighting the clinical utility of MRM in oral cancer biomarker research. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

MRM as a discovery tool?

PubMed

Rudnick, Paul A

2015-04-01

Multiple-reaction monitoring (MRM) of peptides has been recognized as a promising technology because it is sensitive and robust. Borrowed from stable-isotope dilution (SID) methodologies in the field of small molecules, MRM is now routinely used in proteomics laboratories. While its usefulness validating candidate targets is widely accepted, it has not been established as a discovery tool. Traditional thinking has been that MRM workflows cannot be multiplexed high enough to efficiently profile. This is due to slower instrument scan rates and the complexities of developing increasingly large scheduling methods. In this issue, Colangelo et al. (Proteomics 2015, 15, 1202-1214) describe a pipeline (xMRM) for discovery-style MRM using label-free methods (i.e. relative quantitation). Label-free comes with cost benefits as does MRM, where data are easier to analyze than full-scan. Their paper offers numerous improvements in method design and data analysis. The robustness of their pipeline was tested on rodent postsynaptic density fractions. There, they were able to accurately quantify 112 proteins at a CV% of 11.4, with only 2.5% of the 1697 transitions requiring user intervention. Colangelo et al. aim to extend the reach of MRM deeper into the realm of discovery proteomics, an area that is currently dominated by data-dependent and data-independent workflows. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Myoferlin is a novel exosomal protein and functional regulator of cancer-derived exosomes.

PubMed

Blomme, Arnaud; Fahmy, Karim; Peulen, Olivier; Costanza, Brunella; Fontaine, Marie; Struman, Ingrid; Baiwir, Dominique; de Pauw, Edwin; Thiry, Marc; Bellahcène, Akeila; Castronovo, Vincent; Turtoi, Andrei

2016-12-13

Exosomes are communication mediators participating in the intercellular exchange of proteins, metabolites and nucleic acids. Recent studies have demonstrated that exosomes are characterized by a unique proteomic composition that is distinct from the cellular one. The mechanisms responsible for determining the proteome content of the exosomes remain however obscure. In the current study we employ ultrastructural approach to validate a novel exosomal protein myoferlin. This is a multiple C2-domain containing protein, known for its conserved physiological function in endocytosis and vesicle fusion biology. Emerging studies demonstrate that myoferlin is frequently overexpressed in cancer, where it promotes cancer cell migration and invasion. Our data expand these findings by showing that myoferlin is a general component of cancer cell derived exosomes from different breast and pancreatic cancer cell lines. Using proteomic analysis, we demonstrate for the first time that myoferlin depletion in cancer cells leads to a significantly modulated exosomal protein load. Such myoferlin-depleted exosomes were also functionally deficient as shown by their reduced capacity to transfer nucleic acids to human endothelial cells (HUVEC). Beyond this, myoferlin-depleted cancer exosomes also had a significantly reduced ability to induce migration and proliferation of HUVEC. The present study highlights myoferlin as a new functional player in exosome biology, calling for novel strategies to target this emerging oncogene in human cancer.

Analysis of disease-associated protein expression using quantitative proteomics—fibulin-5 is expressed in association with hepatic fibrosis.

PubMed

Bracht, Thilo; Schweinsberg, Vincent; Trippler, Martin; Kohl, Michael; Ahrens, Maike; Padden, Juliet; Naboulsi, Wael; Barkovits, Katalin; Megger, Dominik A; Eisenacher, Martin; Borchers, Christoph H; Schlaak, Jörg F; Hoffmann, Andreas-Claudius; Weber, Frank; Baba, Hideo A; Meyer, Helmut E; Sitek, Barbara

2015-05-01

Hepatic fibrosis and cirrhosis are major health problems worldwide. Until now, highly invasive biopsy remains the diagnostic gold standard despite many disadvantages. To develop noninvasive diagnostic assays for the assessment of liver fibrosis, it is urgently necessary to identify molecules that are robustly expressed in association with the disease. We analyzed biopsied tissue samples from 95 patients with HBV/HCV-associated hepatic fibrosis using three different quantification methods. We performed a label-free proteomics discovery study to identify novel disease-associated proteins using a subset of the cohort (n = 27). Subsequently, gene expression data from all available clinical samples were analyzed (n = 77). Finally, we performed a targeted proteomics approach, multiple reaction monitoring (MRM), to verify the disease-associated expression in samples independent from the discovery approach (n = 68). We identified fibulin-5 (FBLN5) as a novel protein expressed in relation to hepatic fibrosis. Furthermore, we confirmed the altered expression of microfibril-associated glycoprotein 4 (MFAP4), lumican (LUM), and collagen alpha-1(XIV) chain (COL14A1) in association to hepatic fibrosis. To our knowledge, no tissue-based quantitative proteomics study for hepatic fibrosis has been performed using a cohort of comparable size. By this means, we add substantial evidence for the disease-related expression of the proteins examined in this study.

Combination of a proteomics approach and reengineering of meso scale network models for prediction of mode-of-action for tyrosine kinase inhibitors.

PubMed

Balabanov, Stefan; Wilhelm, Thomas; Venz, Simone; Keller, Gunhild; Scharf, Christian; Pospisil, Heike; Braig, Melanie; Barett, Christine; Bokemeyer, Carsten; Walther, Reinhard; Brümmendorf, Tim H; Schuppert, Andreas

2013-01-01

In drug discovery, the characterisation of the precise modes of action (MoA) and of unwanted off-target effects of novel molecularly targeted compounds is of highest relevance. Recent approaches for identification of MoA have employed various techniques for modeling of well defined signaling pathways including structural information, changes in phenotypic behavior of cells and gene expression patterns after drug treatment. However, efficient approaches focusing on proteome wide data for the identification of MoA including interference with mutations are underrepresented. As mutations are key drivers of drug resistance in molecularly targeted tumor therapies, efficient analysis and modeling of downstream effects of mutations on drug MoA is a key to efficient development of improved targeted anti-cancer drugs. Here we present a combination of a global proteome analysis, reengineering of network models and integration of apoptosis data used to infer the mode-of-action of various tyrosine kinase inhibitors (TKIs) in chronic myeloid leukemia (CML) cell lines expressing wild type as well as TKI resistance conferring mutants of BCR-ABL. The inferred network models provide a tool to predict the main MoA of drugs as well as to grouping of drugs with known similar kinase inhibitory activity patterns in comparison to drugs with an additional MoA. We believe that our direct network reconstruction approach, demonstrated on proteomics data, can provide a complementary method to the established network reconstruction approaches for the preclinical modeling of the MoA of various types of targeted drugs in cancer treatment. Hence it may contribute to the more precise prediction of clinically relevant on- and off-target effects of TKIs.

Combination of a Proteomics Approach and Reengineering of Meso Scale Network Models for Prediction of Mode-of-Action for Tyrosine Kinase Inhibitors

PubMed Central

Balabanov, Stefan; Wilhelm, Thomas; Venz, Simone; Keller, Gunhild; Scharf, Christian; Pospisil, Heike; Braig, Melanie; Barett, Christine; Bokemeyer, Carsten; Walther, Reinhard

2013-01-01

In drug discovery, the characterisation of the precise modes of action (MoA) and of unwanted off-target effects of novel molecularly targeted compounds is of highest relevance. Recent approaches for identification of MoA have employed various techniques for modeling of well defined signaling pathways including structural information, changes in phenotypic behavior of cells and gene expression patterns after drug treatment. However, efficient approaches focusing on proteome wide data for the identification of MoA including interference with mutations are underrepresented. As mutations are key drivers of drug resistance in molecularly targeted tumor therapies, efficient analysis and modeling of downstream effects of mutations on drug MoA is a key to efficient development of improved targeted anti-cancer drugs. Here we present a combination of a global proteome analysis, reengineering of network models and integration of apoptosis data used to infer the mode-of-action of various tyrosine kinase inhibitors (TKIs) in chronic myeloid leukemia (CML) cell lines expressing wild type as well as TKI resistance conferring mutants of BCR-ABL. The inferred network models provide a tool to predict the main MoA of drugs as well as to grouping of drugs with known similar kinase inhibitory activity patterns in comparison to drugs with an additional MoA. We believe that our direct network reconstruction approach, demonstrated on proteomics data, can provide a complementary method to the established network reconstruction approaches for the preclinical modeling of the MoA of various types of targeted drugs in cancer treatment. Hence it may contribute to the more precise prediction of clinically relevant on- and off-target effects of TKIs. PMID:23326482

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

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, including the analysis of post-translational modifications, and the design of MS-based assays for validation of differentially expressed proteins in large datasets. Copyright © 2016 Elsevier B.V. All rights reserved.

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

Metformin is a commonly prescribed antihyperglycemic drug, and has been investigated in vivo and in vitro for its effect to improve the comorbidity of diabetes and various types of cancers. Several studies investigated the therapeutic mechanisms of metformin on cancer cells, but the exact mechanism of metformin’s effect on the proteomic pathways of cancer cells is yet to be further investigated. The main objective of our research line is to discover safe and alternative therapeutic options for breast cancer, we aimed in this study to design a novel “bottom up proteomics workflow” in which proteins were first broken into peptides to reveal their identity, then the proteomes were precisely evaluated using spectrometry analysis. In our study, metformin suppressed cell proliferation and induced apoptosis in human breast carcinoma cell line MCF-7 with minimal toxicity to normal breast epithelial cells MCF-10. Metformin induced apoptosis by arresting cells in G1 phase as evaluated by flow cytometric analysis. Moreover, The G1 phase arrest for the MCF-7 has been confirmed by increased expression levels of p21 and reduction in cyclin D1 level. Additionally, metformin increased the expression levels of p53, Bax, Bad while it reduced expression levels of Akt, Bcl-2, and Mdm2. The study employed a serviceable strategy that investigates metformin-dependent changes in the proteome using a literature-derived network. The protein extracts of the treated and untreated cell lines were analyzed employing proteomic approaches; the findings conveyed a proposed mechanism of the effectual tactics of metformin on breast cancer cells. Metformin proposed an antibreast cancer effect through the examination of the proteomic pathways upon the MCF-7 and MCF-10A exposure to the drug. Our findings proposed prolific proteomic changes that revealed the therapeutic mechanisms of metformin on breast cancer cells upon their exposure. In conclusion, the reported proteomic pathways lead to 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

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

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 article is part of a Special Issue entitled: Standardization and Quality Control in Proteomics. © 2013.

Recent progress in the genetics of spontaneously hypertensive rats.

PubMed

Pravenec, M; Křen, V; Landa, V; Mlejnek, P; Musilová, A; Šilhavý, J; Šimáková, M; Zídek, V

2014-01-01

The spontaneously hypertensive rat (SHR) is the most widely used animal model of essential hypertension and accompanying metabolic disturbances. Recent advances in sequencing of genomes of BN-Lx and SHR progenitors of the BXH/HXB recombinant inbred (RI) strains as well as accumulation of multiple data sets of intermediary phenotypes in the RI strains, including mRNA and microRNA abundance, quantitative metabolomics, proteomics, methylomics or histone modifications, will make it possible to systematically search for genetic variants involved in regulation of gene expression and in the etiology of complex pathophysiological traits. New advances in manipulation of the rat genome, including efficient transgenesis and gene targeting, will enable in vivo functional analyses of selected candidate genes to identify QTL at the molecular level or to provide insight into mechanisms whereby targeted genes affect pathophysiological traits in the SHR.

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.

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.

Intensive herbicide use has selected for constitutively elevated levels of stress-responsive mRNAs and proteins in multiple herbicide-resistant Avena fatua L.

PubMed

Keith, Barbara K; Burns, Erin E; Bothner, Brian; Carey, Charles C; Mazurie, Aurélien J; Hilmer, Jonathan K; Biyiklioglu, Sezgi; Budak, Hikmet; Dyer, William E

2017-11-01

Intensive use of herbicides has led to the evolution of two multiple herbicide-resistant (MHR) Avena fatua (wild oat) populations in Montana that are resistant to members of all selective herbicide families available for A. fatua control in US small grain crops. We used transcriptome and proteome surveys to compare constitutive changes in MHR and herbicide-susceptible (HS) plants associated with non-target site resistance. Compared to HS plants, MHR plants contained constitutively elevated levels of differentially expressed genes (DEGs) with functions in xenobiotic catabolism, stress response, redox maintenance and transcriptional regulation that are similar to abiotic stress-tolerant phenotypes. Proteome comparisons identified similarly elevated proteins including biosynthetic and multifunctional enzymes in MHR plants. Of 25 DEGs validated by RT-qPCR assay, differential regulation of 21 co-segregated with flucarbazone-sodium herbicide resistance in F 3 families, and a subset of 10 of these were induced or repressed in herbicide-treated HS plants. Although the individual and collective contributions of these DEGs and proteins to MHR remain to be determined, our results support the idea that intensive herbicide use has selected for MHR populations with altered, constitutively regulated patterns of gene expression that are similar to those in abiotic stress-tolerant plants. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Screening of multiple myeloma by polyclonal rabbit anti-human plasmacytoma cell immunoglobulin.

PubMed

Mu, Bo; Zhang, Huan; Cai, Xiaoming; Yang, Junbao; Shen, Yuewu; Chen, Baofeng; Liang, Suhua

2013-01-01

Antibody-based immunotherapy has been effectively used for tumor treatment. However, to date, only a few tumor-associated antigens (TAAs) or therapeutic targets have been identified. Identification of more immunogenic antigens is essential for improvements in multiple myeloma (MM) diagnosis and therapy. In this study, we synthesized a polyclonal antibody (PAb) by immunizing rabbits with whole human plasmacytoma ARH-77 cells and identified MM-associated antigens, including enlonase, adipophilin, and HSP90s, among others, via proteomic technologies. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay showed that 200 µg/mL PAb inhibits the proliferation of ARH-77 cells by over 50% within 48 h. Flow cytometric assay indicated that PAb treatment significantly increases the number of apoptotic cells compared with other treatments (52.1% vs. NS, 7.3% or control rabbit IgG, 9.9%). In vivo, PAb delayed tumor growth and prolonged the lifespan of mice. Terminal deoxynucleotidyl transferase dUTP nick end labeling assay showed that PAb also induces statistically significant changes in apoptosis compared with other treatments (P<0.05). We therefore conclude that PAb could be used for the effective screening and identification of TAA. PAb may have certain anti-tumor functions in vitro and in vivo. As such, its combination with proteomic technologies could be a promising approach for sieving TAA for the diagnosis and therapy of MM.

Ubiquitin-dependent and independent roles of SUMO in proteostasis.

PubMed

Liebelt, Frauke; Vertegaal, Alfred C O

2016-08-01

Cellular proteomes are continuously undergoing alterations as a result of new production of proteins, protein folding, and degradation of proteins. The proper equilibrium of these processes is known as proteostasis, implying that proteomes are in homeostasis. Stress conditions can affect proteostasis due to the accumulation of misfolded proteins as a result of overloading the degradation machinery. Proteostasis is affected in neurodegenerative diseases like Alzheimer's disease, Parkinson's disease, and multiple polyglutamine disorders including Huntington's disease. Owing to a lack of proteostasis, neuronal cells build up toxic protein aggregates in these diseases. Here, we review the role of the ubiquitin-like posttranslational modification SUMO in proteostasis. SUMO alone contributes to protein homeostasis by influencing protein signaling or solubility. However, the main contribution of SUMO to proteostasis is the ability to cooperate with, complement, and balance the ubiquitin-proteasome system at multiple levels. We discuss the identification of enzymes involved in the interplay between SUMO and ubiquitin, exploring the complexity of this crosstalk which regulates proteostasis. These enzymes include SUMO-targeted ubiquitin ligases and ubiquitin proteases counteracting these ligases. Additionally, we review the role of SUMO in brain-related diseases, where SUMO is primarily investigated because of its role during formation of aggregates, either independently or in cooperation with ubiquitin. Detailed understanding of the role of SUMO in these diseases could lead to novel treatment options. Copyright © 2016 the American Physiological Society.

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

Applications of mass spectrometry for quantitative protein analysis in formalin-fixed paraffin-embedded tissues

PubMed Central

Steiner, Carine; Ducret, Axel; Tille, Jean-Christophe; Thomas, Marlene; McKee, Thomas A; Rubbia-Brandt, Laura A; Scherl, Alexander; Lescuyer, Pierre; Cutler, Paul

2014-01-01

Proteomic analysis of tissues has advanced in recent years as instruments and methodologies have evolved. The ability to retrieve peptides from formalin-fixed paraffin-embedded tissues followed by shotgun or targeted proteomic analysis is offering new opportunities in biomedical research. In particular, access to large collections of clinically annotated samples should enable the detailed analysis of pathologically relevant tissues in a manner previously considered unfeasible. In this paper, we review the current status of proteomic analysis of formalin-fixed paraffin-embedded tissues with a particular focus on targeted approaches and the potential for this technique to be used in clinical research and clinical diagnosis. We also discuss the limitations and perspectives of the technique, particularly with regard to application in clinical diagnosis and drug discovery. PMID:24339433

A global comparability approach for biosimilar monoclonal antibodies using LC-tandem MS based proteomics.

PubMed

Chen, Shun-Li; Wu, Shiaw-Lin; Huang, Li-Juan; Huang, Jia-Bao; Chen, Shu-Hui

2013-06-01

Liquid chromatography-tandem mass spectrometry-based proteomics for peptide mapping and sequencing was used to characterize the marketed monoclonal antibody trastuzumab and compare it with two biosimilar products, mAb A containing D359E and L361M variations at the Fc site and mAb B without variants. Complete sequence coverage (100%) including disulfide linkages, glycosylations and other commonly occurring modifications (i.e., deamidation, oxidation, dehydration and K-clipping) were identified using maps generated from multi-enzyme digestions. In addition to the targeted comparison for the relative populations of targeted modification forms, a non-targeted approach was used to globally compare ion intensities in tryptic maps. The non-targeted comparison provided an extra-dimensional view to examine any possible differences related to variants or modifications. A peptide containing the two variants in mAb A, D359E and L361M, was revealed using the non-targeted comparison of the tryptic maps. In contrast, no significant differences were observed when trastuzumab was self-compared or compared with mAb B. These results were consistent with the data derived from peptide sequencing via collision induced dissociation/electron transfer dissociation. Thus, combined targeted and non-targeted approaches using powerful mass spectrometry-based proteomic tools hold great promise for the structural characterization of biosimilar products. Copyright © 2013 Elsevier B.V. All rights reserved.

Systems and Trans-System Level Analysis Identifies Conserved Iron Deficiency Responses in the Plant Lineage[W][OA

PubMed Central

Urzica, Eugen I.; Casero, David; Yamasaki, Hiroaki; Hsieh, Scott I.; Adler, Lital N.; Karpowicz, Steven J.; Blaby-Haas, Crysten E.; Clarke, Steven G.; Loo, Joseph A.; Pellegrini, Matteo; Merchant, Sabeeha S.

2012-01-01

We surveyed the iron nutrition-responsive transcriptome of Chlamydomonas reinhardtii using RNA-Seq methodology. Presumed primary targets were identified in comparisons between visually asymptomatic iron-deficient versus iron-replete cells. This includes the known components of high-affinity iron uptake as well as candidates for distributive iron transport in C. reinhardtii. Comparison of growth-inhibited iron-limited versus iron-replete cells revealed changes in the expression of genes in chloroplastic oxidative stress response pathways, among hundreds of other genes. The output from the transcriptome was validated at multiple levels: by quantitative RT-PCR for assessing the data analysis pipeline, by quantitative proteomics for assessing the impact of changes in RNA abundance on the proteome, and by cross-species comparison for identifying conserved or universal response pathways. In addition, we assessed the functional importance of three target genes, VITAMIN C 2 (VTC2), MONODEHYDROASCORBATE REDUCTASE 1 (MDAR1), and CONSERVED IN THE GREEN LINEAGE AND DIATOMS 27 (CGLD27), by biochemistry or reverse genetics. VTC2 and MDAR1, which are key enzymes in de novo ascorbate synthesis and ascorbate recycling, respectively, are likely responsible for the 10-fold increase in ascorbate content of iron-limited cells. CGLD27/At5g67370 is a highly conserved, presumed chloroplast-localized pioneer protein and is important for growth of Arabidopsis thaliana in low iron. PMID:23043051

A strategy for absolute proteome quantification with mass spectrometry by hierarchical use of peptide-concatenated standards.

PubMed

Kito, Keiji; Okada, Mitsuhiro; Ishibashi, Yuko; Okada, Satoshi; Ito, Takashi

2016-05-01

The accurate and precise absolute abundance of proteins can be determined using mass spectrometry by spiking the sample with stable isotope-labeled standards. In this study, we developed a strategy of hierarchical use of peptide-concatenated standards (PCSs) to quantify more proteins over a wider dynamic range. Multiple primary PCSs were used for quantification of many target proteins. Unique "ID-tag peptides" were introduced into individual primary PCSs, allowing us to monitor the exact amounts of individual PCSs using a "secondary PCS" in which all "ID-tag peptides" were concatenated. Furthermore, we varied the copy number of the "ID-tag peptide" in each PCS according to a range of expression levels of target proteins. This strategy accomplished absolute quantification over a wider range than that of the measured ratios. The quantified abundance of budding yeast proteins showed a high reproducibility for replicate analyses and similar copy numbers per cell for ribosomal proteins, demonstrating the accuracy and precision of this strategy. A comparison with the absolute abundance of transcripts clearly indicated different post-transcriptional regulation of expression for specific functional groups. Thus, the approach presented here is a faithful method for the absolute quantification of proteomes and provides insights into biological mechanisms, including the regulation of expressed protein abundance. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

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.

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

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.

The current status of clinical proteomics and the use of MRM and MRM(3) for biomarker validation.

PubMed

Lemoine, Jérôme; Fortin, Tanguy; Salvador, Arnaud; Jaffuel, Aurore; Charrier, Jean-Philippe; Choquet-Kastylevsky, Geneviève

2012-05-01

The transfer of biomarkers from the discovery field to clinical use is still, despite progress, on a road filled with pitfalls. Since the emergence of proteomics, thousands of putative biomarkers have been published, often with overlapping diagnostic capacities. The strengthening of the robustness of discovery technologies, particularly in mass spectrometry, has been followed by intense discussions on establishing well-defined evaluation procedures for the identified targets to ultimately allow the clinical validation and then the clinical use of some of these biomarkers. Some of the obstacles to the evaluation process have been the lack of the availability of quick and easy-to-develop, easy-to-use, robust, specific and sensitive alternative quantitative methods when immunoaffinity-based tests are unavailable. Multiple reaction monitoring (MRM; also called selected reaction monitoring) is currently proving its capabilities as a complementary or alternative technique to ELISA for large biomarker panel evaluation. Here, we present how MRM(3) can overcome the lack of specificity and sensitivity often encountered by MRM when tracking minor proteins diluted by complex biological matrices.

A Novel Immunogenic Spore Coat-Associated Protein in Bacillus Anthracis: Characterization via Proteomics Approaches and a Vector-Based Vaccine System

PubMed Central

Liu, Yu-Tsueng; Lin, Shwu-Bin; Huang, Cheng-Po; Huang, Chun-Ming

2007-01-01

New generation anthrax vaccines have been actively explored with the aim of enhancing efficacies and decreasing undesirable side effects that could be caused by licensed vaccines. Targeting novel antigens and/or eliminating the requirements for multiple needle injections and adjuvants are major objectives in the development of new anthrax vaccines. Using proteomics approaches, we identified a spore coat-associated protein (SCAP) in Bacillus anthracis. An E. coli vector-based vaccine system was used to determine the immunogenicity of SCAP. Mice generated detectable SCAP antibodies three weeks after intranasal immunization with an intact particle of ultraviolet (UV)-irradiated E. coli vector overproducing SCAP. The production of SCAP antibodies was detected via western blotting and SCAP-spotted antigen-arrays. The adjuvant effect of a UV-irradiated E. coli vector eliminates the necessity of boosting and the use of other immunomodulators which will foster the screening and manufacturing of new generation anthrax vaccines. More importantly, the immunogenic SCAP may potentially be a new candidate for the development of anthrax vaccines. PMID:18029197

Interactome disassembly during apoptosis occurs independent of caspase cleavage.

PubMed

Scott, Nichollas E; Rogers, Lindsay D; Prudova, Anna; Brown, Nat F; Fortelny, Nikolaus; Overall, Christopher M; Foster, Leonard J

2017-01-12

Protein-protein interaction networks (interactomes) define the functionality of all biological systems. In apoptosis, proteolysis by caspases is thought to initiate disassembly of protein complexes and cell death. Here we used a quantitative proteomics approach, protein correlation profiling (PCP), to explore changes in cytoplasmic and mitochondrial interactomes in response to apoptosis initiation as a function of caspase activity. We measured the response to initiation of Fas-mediated apoptosis in 17,991 interactions among 2,779 proteins, comprising the largest dynamic interactome to date. The majority of interactions were unaffected early in apoptosis, but multiple complexes containing known caspase targets were disassembled. Nonetheless, proteome-wide analysis of proteolytic processing by terminal amine isotopic labeling of substrates (TAILS) revealed little correlation between proteolytic and interactome changes. Our findings show that, in apoptosis, significant interactome alterations occur before and independently of caspase activity. Thus, apoptosis initiation includes a tight program of interactome rearrangement, leading to disassembly of relatively few, select complexes. These early interactome alterations occur independently of cleavage of these protein by caspases. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

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 discovery and label-free PRM analysis have been deposited to the ProteomeXchange Consortium with identifiers and , respectively.

A genome-wide structure-based survey of nucleotide binding proteins in M. tuberculosis

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

Bhagavat, Raghu; Kim, Heung -Bok; Kim, Chang -Yub

Nucleoside tri-phosphates (NTP) form an important class of small molecule ligands that participate in, and are essential to a large number of biological processes. Here, we seek to identify the NTP binding proteome (NTPome) in M. tuberculosis (M.tb), a deadly pathogen. Identifying the NTPome is useful not only for gaining functional insights of the individual proteins but also for identifying useful drug targets. From an earlier study, we had structural models of M.tb at a proteome scale from which a set of 13,858 small molecule binding pockets were identified. We use a set of NTP binding sub-structural motifs derived frommore » a previous study and scan the M.tb pocketome, and find that 1,768 proteins or 43% of the proteome can theoretically bind NTP ligands. Using an experimental proteomics approach involving dye-ligand affinity chromatography, we confirm NTP binding to 47 different proteins, of which 4 are hypothetical proteins. Our analysis also provides the precise list of binding site residues in each case, and the probable ligand binding pose. In conclusion, as the list includes a number of known and potential drug targets, the identification of NTP binding can directly facilitate structure-based drug design of these targets.« less

GSTM3 and GSTP1: novel players driving tumor progression in cervical cancer.

PubMed

Checa-Rojas, Alberto; Delgadillo-Silva, Luis Fernando; Velasco-Herrera, Martín Del Castillo; Andrade-Domínguez, Andrés; Gil, Jeovanis; Santillán, Orlando; Lozano, Luis; Toledo-Leyva, Alfredo; Ramírez-Torres, Alberto; Talamas-Rohana, Patricia; Encarnación-Guevara, Sergio

2018-04-24

The molecular processes and proteomic markers leading to tumor progression (TP) in cervical cancer (CC) are either unknown or only partially understood. TP affects metabolic and regulatory mechanisms that can be identified as proteomic changes. To identify which proteins are differentially expressed and to understand the mechanisms of cancer progression, we analyzed the dynamics of the tumor proteome in CC cell lines. This analysis revealed two proteins that are up-regulated during TP, GSTM3 and GSTP1. These proteins are involved in cell maintenance, cell survival and the cellular stress response via the NF-κB and MAP kinase pathways during TP. Furthermore, GSTM3 and GSTP1 knockdown showed that evasion of apoptosis was affected, and tumor proliferation was significantly reduced. Our data indicate the critical role of GST proteins in the regulation and progression of cervical cancer cells. Hence, we suggest GSTM3 and GSTP1 as novel biomarkers and potential therapeutic targets for treating cervical cancer. CC is particularly hazardous in the advanced stages, and there are few therapeutic strategies specifically targeting these stages. We performed analyses on CC tumor proteome dynamics and identified GSTM3 and GSTP1 as novel potential therapeutic targets. Knockdown of these proteins showed that they are involved in cell survival, cell proliferation and cellular evasion of apoptosis.

A genome-wide structure-based survey of nucleotide binding proteins in M. tuberculosis

DOE PAGES

Bhagavat, Raghu; Kim, Heung -Bok; Kim, Chang -Yub; ...

2017-10-02

Nucleoside tri-phosphates (NTP) form an important class of small molecule ligands that participate in, and are essential to a large number of biological processes. Here, we seek to identify the NTP binding proteome (NTPome) in M. tuberculosis (M.tb), a deadly pathogen. Identifying the NTPome is useful not only for gaining functional insights of the individual proteins but also for identifying useful drug targets. From an earlier study, we had structural models of M.tb at a proteome scale from which a set of 13,858 small molecule binding pockets were identified. We use a set of NTP binding sub-structural motifs derived frommore » a previous study and scan the M.tb pocketome, and find that 1,768 proteins or 43% of the proteome can theoretically bind NTP ligands. Using an experimental proteomics approach involving dye-ligand affinity chromatography, we confirm NTP binding to 47 different proteins, of which 4 are hypothetical proteins. Our analysis also provides the precise list of binding site residues in each case, and the probable ligand binding pose. In conclusion, as the list includes a number of known and potential drug targets, the identification of NTP binding can directly facilitate structure-based drug design of these targets.« less

Microbial Protein-Antigenome Determination (MAD) Technology: A Proteomics-Based Strategy for Rapid Identification of Microbial Targets of Host Humoral Immune Responses

USDA-ARS?s Scientific Manuscript database

Immunogenic, pathogen-specific proteins have excellent potential for development of novel management modalities. Here, we describe an innovative application of proteomics called Microbial protein-Antigenome Determination (MAD) Technology for rapid identification of native microbial proteins that el...

Microbial Protein-Antigenome Determination (MAD) Technology: A Proteomics-Based Strategy for Rapid Identification of Microbial Targets of Host Humoral Immune Responses

USDA-ARS?s Scientific Manuscript database

Immunogenic, pathogen-specific proteins have excellent potential for development of novel management modalities. Here, we describe an innovative application of proteomics called Microbial protein-Antigenome Determination (MAD) Technology for rapid identification of native microbial proteins that eli...

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.

Time-resolved cellular effects induced by TcdA from Clostridium difficile.

PubMed

Jochim, Nelli; Gerhard, Ralf; Just, Ingo; Pich, Andreas

2014-05-30

The anaerobe Clostridium difficile is a common pathogen that causes infection of the colon leading to diarrhea or pseudomembranous colitis. Its major virulence factors are toxin A (TcdA) and toxin B (TcdB), which specifically inactivate small GTPases by glucosylation leading to reorganization of the cytoskeleton and finally to cell death. In the present work a quantitative proteome analysis using the isotope-coded protein label (ICPL) approach was conducted to investigate proteome changes in the colon cell line Caco-2 after treatment with recombinant wild-type TcdA (rTcdA-wt) or a glucosyltransferase-deficient mutant TcdA (rTcdA-mut). Proteins from crude cell lysates or cellular subfractions were identified by liquid chromatography/electrospray ionization mass spectrometry (LC/ESI-MS). Two time points (5 h, 24 h) of toxin treatment were analyzed and about 4000 proteins were identified in each case. After 5 h treatment with rTcdA-wt, 150 proteins had a significantly altered abundance; rTcdA-mut caused regulation of 50 proteins at this time point. After 24 h treatment with rTcdA-wt changes in abundance of 61 proteins were observed, but no changes in protein abundance were detected after 24 h if cells were treated with rTcdA-mut. TcdA affected several proteins involved in signaling events, cytoskeleton and cell-cell contact organization, translation, and metabolic processes. The ICPL-dependent quantification was verified by label-free targeted MS techniques based on multiple reaction monitoring (MRM) and triple quadrupole mass spectrometry. LC/MS-based proteome analyses and the ICPL approach revealed comprehensive and reproducible proteome date and provided new insights into the cellular effects of clostridial glucosylating toxins (CGT). Copyright © 2014 John Wiley & Sons, Ltd.

Integrated redox proteomics and metabolomics of mitochondria to identify mechanisms of cd toxicity.

PubMed

Go, Young-Mi; Roede, James R; Orr, Michael; Liang, Yongliang; Jones, Dean P

2014-05-01

Cadmium (Cd) exposure contributes to human diseases affecting liver, kidney, lung, and other organ systems, but mechanisms underlying the pleotropic nature of these toxicities are poorly understood. Cd accumulates in humans from dietary, environmental (including cigarette smoke), and occupational sources, and has a twenty-year biologic half-life. Our previous mouse and cell studies showed that environmental low-dose Cd exposure altered protein redox states resulting in stimulation of inflammatory signaling and disruption of the actin cytoskeleton system, suggesting that Cd could impact multiple mechanisms of disease. In the current study, we investigated the effects of acute Cd exposure on the redox proteome and metabolome of mouse liver mitochondria to gain insight into associated toxicological mechanisms and functions. We analyzed redox states of liver mitochondrial proteins by redox proteomics using isotope coded affinity tag (ICAT) combined mass spectrometry. Redox ICAT identified 2687 cysteine-containing peptides (peptidyl Cys) of which 1667 peptidyl Cys (657 proteins) were detected in both control and Cd-exposed samples. Of these, 46% (1247 peptidyl Cys, 547 proteins) were oxidized by Cd more than 1.5-fold relative to controls. Bioinformatics analysis using MetaCore software showed that Cd affected 86 pathways, including 24 Cys in proteins functioning in branched chain amino acid (BCAA) and 14 Cys in proteins functioning in fatty acid (acylcarnitine/carnitine) metabolism. Consistently, high-resolution metabolomics data showed that Cd treatment altered levels of BCAA and carnitine metabolites. Together, these results show that mitochondrial protein redox and metabolites are targets in Cd-induced hepatotoxicity. The results further indicate that redox proteomics and metabolomics can be used in an integrated systems approach to investigate complex disease mechanisms.

Proteome profiling reveals regional protein alteration in cerebrum of common marmoset (Callithrix jacchus) exposed to methylmercury.

PubMed

Shao, Yueting; Yamamoto, Megumi; Figeys, Daniel; Ning, Zhibin; Chan, Hing Man

2016-03-10

Methylmercury (MeHg) is known to selectively damage the calcarine and precentral cortices along deep sulci and fissures in adult cases, but the detailed mechanism is still unclear. This study aims to identify and analyze the differential proteome expression in two regions of the cerebrum (the frontal lobe and the occipital lobe including the calcarine sulcus) of the common marmoset exposed to MeHg using a shot-gun proteomic approach. A total of 1045 and 1062 proteins were identified in the frontal lobe (FL) and occipital lobe (OL), of which, 62 and 89 proteins were found significantly changed with MeHg exposure. Functional enrichment/depletion analysis showed that the lipid metabolic process and proteolysis were affected in both two lobes. Functional changes in FL were characterized in cell cycle and cell division, sulfur compound metabolic process, microtubule-based process and glycerolipid metabolic process. In comparison, proteins were enriched in the functions of transport, carbohydrate metabolic process, chemical caused homeostasis and regulation of body fluid levels in OL. Pathway analysis predicted that vasopressin-regulated water reabsorption was disturbed in MeHg-treated FL. Our results showed that MeHg induced regional specific protein changes in FL and OL but with similar endpoint effects such as energy diminish and disruption of water transport. APOE and GPX1 were shown to be possible key proteins targeted by MeHg leading to multiple functional changes in OL. This is the first report of the whole proteome changes of primate cerebrum for MeHg neurotoxicity, and the results will contribute to the understanding of molecular basis of MeHg intoxication in humans. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

VIDEO: Dr. Henry Rodriguez - Proteogenomics in Cancer Medicine | Office of Cancer Clinical Proteomics Research

Cancer.gov

Dr. Henry Rodriguez, director of the Office of Cancer Clinical Proteomics Research (OCCPR) at NCI, speaks with ecancer television at WIN 2017 about the translation of the proteins expressed in a patient's tumor into a map for druggable targets. By combining genomic and proteomic information (proteogenomics), leading scientists are gaining new insights into ways to detect and treat cancer due to a more complete and unified understanding of complex biological processes.

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.

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 tumor fluid samples the regulation of 27 proteins out of 33 identified in a highthroughput study. We speculate that the presence and/or differential abundance observed in tumor fluid is a cooperation primarily of high rates of secretion of such tumor proteins to extra tumor environment that will at the end accumulate in plasma, and also the accumulation of acute-phase proteins throughout the entire body. On top of that, consideration of physiological influences in the interpretation of expression observed, including age, menopause status, route-of-elimination kinetics and metabolism of the tumor marker, coexisting disease, hormonal imbalances, life-style influences (smoking, alcoholism, obesity), among others, are mandatory to enable the selection of good protein tumor marker candidates for extensive validation. Copyright © 2016 Elsevier B.V. All rights reserved.

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 pathways of the pathogens and mining the proteomic data of all completely sequenced strains of the pathogen, thus improving the quality and application of the results. We believe that the sharing of the knowledge from this study would eventually lead to bring about novel and unique therapeutic regimens against the infections caused by the S. enterica.

Network Analysis of Rodent Transcriptomes in Spaceflight

NASA Technical Reports Server (NTRS)

Ramachandran, Maya; Fogle, Homer; Costes, Sylvain

2017-01-01

Network analysis methods leverage prior knowledge of cellular systems and the statistical and conceptual relationships between analyte measurements to determine gene connectivity. Correlation and conditional metrics are used to infer a network topology and provide a systems-level context for cellular responses. Integration across multiple experimental conditions and omics domains can reveal the regulatory mechanisms that underlie gene expression. GeneLab has assembled rich multi-omic (transcriptomics, proteomics, epigenomics, and epitranscriptomics) datasets for multiple murine tissues from the Rodent Research 1 (RR-1) experiment. RR-1 assesses the impact of 37 days of spaceflight on gene expression across a variety of tissue types, such as adrenal glands, quadriceps, gastrocnemius, tibalius anterior, extensor digitorum longus, soleus, eye, and kidney. Network analysis is particularly useful for RR-1 -omics datasets because it reinforces subtle relationships that may be overlooked in isolated analyses and subdues confounding factors. Our objective is to use network analysis to determine potential target nodes for therapeutic intervention and identify similarities with existing disease models. Multiple network algorithms are used for a higher confidence consensus.

Drug synergy screen and network modeling in dedifferentiated liposarcoma identifies CDK4 and IGF1R as synergistic drug targets.

PubMed

Miller, Martin L; Molinelli, Evan J; Nair, Jayasree S; Sheikh, Tahir; Samy, Rita; Jing, Xiaohong; He, Qin; Korkut, Anil; Crago, Aimee M; Singer, Samuel; Schwartz, Gary K; Sander, Chris

2013-09-24

Dedifferentiated liposarcoma (DDLS) is a rare but aggressive cancer with high recurrence and low response rates to targeted therapies. Increasing treatment efficacy may require combinations of targeted agents that counteract the effects of multiple abnormalities. To identify a possible multicomponent therapy, we performed a combinatorial drug screen in a DDLS-derived cell line and identified cyclin-dependent kinase 4 (CDK4) and insulin-like growth factor 1 receptor (IGF1R) as synergistic drug targets. We measured the phosphorylation of multiple proteins and cell viability in response to systematic drug combinations and derived computational models of the signaling network. These models predict that the observed synergy in reducing cell viability with CDK4 and IGF1R inhibitors depends on the activity of the AKT pathway. Experiments confirmed that combined inhibition of CDK4 and IGF1R cooperatively suppresses the activation of proteins within the AKT pathway. Consistent with these findings, synergistic reductions in cell viability were also found when combining CDK4 inhibition with inhibition of either AKT or epidermal growth factor receptor (EGFR), another receptor similar to IGF1R that activates AKT. Thus, network models derived from context-specific proteomic measurements of systematically perturbed cancer cells may reveal cancer-specific signaling mechanisms and aid in the design of effective combination therapies.

Drug Synergy Screen and Network Modeling in Dedifferentiated Liposarcoma Identifies CDK4 and IGF1R as Synergistic Drug Targets

PubMed Central

Miller, Martin L.; Molinelli, Evan J.; Nair, Jayasree S.; Sheikh, Tahir; Samy, Rita; Jing, Xiaohong; He, Qin; Korkut, Anil; Crago, Aimee M.; Singer, Samuel; Schwartz, Gary K.; Sander, Chris

2014-01-01

Dedifferentiated liposarcoma (DDLS) is a rare but aggressive cancer with high recurrence and low response rates to targeted therapies. Increasing treatment efficacy may require combinations of targeted agents that counteract the effects of multiple abnormalities. To identify a possible multicomponent therapy, we performed a combinatorial drug screen in a DDLS-derived cell line and identified cyclin-dependent kinase 4 (CDK4) and insulin-like growth factor 1 receptor (IGF1R) as synergistic drug targets. We measured the phosphorylation of multiple proteins and cell viability in response to systematic drug combinations and derived computational models of the signaling network. These models predict that the observed synergy in reducing cell viability with CDK4 and IGF1R inhibitors depend on activity of the AKT pathway. Experiments confirmed that combined inhibition of CDK4 and IGF1R cooperatively suppresses the activation of proteins within the AKT pathway. Consistent with these findings, synergistic reductions in cell viability were also found when combining CDK4 inhibition with inhibition of either AKT or epidermal growth factor receptor (EGFR), another receptor similar to IGF1R that activates AKT. Thus, network models derived from context-specific proteomic measurements of systematically perturbed cancer cells may reveal cancer-specific signaling mechanisms and aid in the design of effective combination therapies. PMID:24065146

Advancing the sensitivity of selected reaction monitoring-based targeted quantitative proteomics

PubMed Central

Shi, Tujin; Su, Dian; Liu, Tao; Tang, Keqi; Camp, David G.; Qian, Wei-Jun; Smith, Richard D.

2012-01-01

Selected reaction monitoring (SRM)—also known as multiple reaction monitoring (MRM)—has emerged as a promising high-throughput targeted protein quantification technology for candidate biomarker verification and systems biology applications. A major bottleneck for current SRM technology, however, is insufficient sensitivity for e.g., detecting low-abundance biomarkers likely present at the low ng/mL to pg/mL range in human blood plasma or serum, or extremely low-abundance signaling proteins in cells or tissues. Herein we review recent advances in methods and technologies, including front-end immunoaffinity depletion, fractionation, selective enrichment of target proteins/peptides including posttranslational modifications (PTMs), as well as advances in MS instrumentation which have significantly enhanced the overall sensitivity of SRM assays and enabled the detection of low-abundance proteins at low to sub- ng/mL level in human blood plasma or serum. General perspectives on the potential of achieving sufficient sensitivity for detection of pg/mL level proteins in plasma are also discussed. PMID:22577010

Advancing the sensitivity of selected reaction monitoring-based targeted quantitative proteomics

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

Shi, Tujin; Su, Dian; Liu, Tao

2012-04-01

Selected reaction monitoring (SRM)—also known as multiple reaction monitoring (MRM)—has emerged as a promising high-throughput targeted protein quantification technology for candidate biomarker verification and systems biology applications. A major bottleneck for current SRM technology, however, is insufficient sensitivity for e.g., detecting low-abundance biomarkers likely present at the pg/mL to low ng/mL range in human blood plasma or serum, or extremely low-abundance signaling proteins in the cells or tissues. Herein we review recent advances in methods and technologies, including front-end immunoaffinity depletion, fractionation, selective enrichment of target proteins/peptides or their posttranslational modifications (PTMs), as well as advances in MS instrumentation, whichmore » have significantly enhanced the overall sensitivity of SRM assays and enabled the detection of low-abundance proteins at low to sub- ng/mL level in human blood plasma or serum. General perspectives on the potential of achieving sufficient sensitivity for detection of pg/mL level proteins in plasma are also discussed.« less

From proteomics to systems biology: MAPA, MASS WESTERN, PROMEX, and COVAIN as a user-oriented platform.

PubMed

Weckwerth, Wolfram; Wienkoop, Stefanie; Hoehenwarter, Wolfgang; Egelhofer, Volker; Sun, Xiaoliang

2014-01-01

Genome sequencing and systems biology are revolutionizing life sciences. Proteomics emerged as a fundamental technique of this novel research area as it is the basis for gene function analysis and modeling of dynamic protein networks. Here a complete proteomics platform suited for functional genomics and systems biology is presented. The strategy includes MAPA (mass accuracy precursor alignment; http://www.univie.ac.at/mosys/software.html ) as a rapid exploratory analysis step; MASS WESTERN for targeted proteomics; COVAIN ( http://www.univie.ac.at/mosys/software.html ) for multivariate statistical analysis, data integration, and data mining; and PROMEX ( http://www.univie.ac.at/mosys/databases.html ) as a database module for proteogenomics and proteotypic peptides for targeted analysis. Moreover, the presented platform can also be utilized to integrate metabolomics and transcriptomics data for the analysis of metabolite-protein-transcript correlations and time course analysis using COVAIN. Examples for the integration of MAPA and MASS WESTERN data, proteogenomic and metabolic modeling approaches for functional genomics, phosphoproteomics by integration of MOAC (metal-oxide affinity chromatography) with MAPA, and the integration of metabolomics, transcriptomics, proteomics, and physiological data using this platform are presented. All software and step-by-step tutorials for data processing and data mining can be downloaded from http://www.univie.ac.at/mosys/software.html.

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.

Translational Research on the Way to Effective Therapy for Alzheimer Disease

PubMed Central

Rosenberg, Roger N.

2006-01-01

Context Alzheimer disease (AD) is a major public health issue with a prediction of 12 million Americans being affected by 2025 from the present 4 million. Molecular and genetic findings have provided significant insights into the roles that amyloid, tau, and apolipoprotein E isoforms have in the causation of AD. A central issue in AD pathogenesis is the amyloid cascade hypothesis. It states that abnormal amyloid processing and accumulation is the primary causative factor of AD and other associated neuropathologic abnormalities are of secondary consequence. It is presented to provide the rationale for novel drug and vaccination therapeutic strategies. Future research directed at prediction and prevention of AD through a genomic and proteomic analysis with identification of multiple polymorphic genes that interact, resulting in increased risk for late-onset AD, are the realistic and ultimate goals. A new approach for drug development is required, one that will emphasize a genomic and proteomic analysis to identify at-risk gene sets whose genetic expression is sufficient to cause late onset, sporadic AD. Prediction and prevention of disease prior to clinical signs and symptoms are the goals. Objective A review and analysis from electronic literature databases and subsequent reference searches of the molecular genetic data including pertinent genetic mutations and abnormal biochemical findings causal of AD, are cited. The amyloid cascade hypothesis, the contributions of apolipoprotein E, and hyperphosphorylated tau are discussed as to their roles in pathogenesis. Molecular targets for potential drug and vaccination therapies are cited from a critical assessment of the molecular and biomedical data. These data form the basis for rational, target-specific drug and vaccination therapies currently employed and planned for the near future. Phase 2 and 3 clinical trial results of drug and vaccination therapies are cited. Conclusions A new approach is needed as current pharmacologic therapy directed at symptomatic relief has proved to be marginally effective. The genomic and proteomic basis of AD will be defined in the near future, and corresponding molecular therapeutic targets will be identified. Genomic neurology has arrived and its application to resolving AD is our best hope. PMID:16275806

Translational research on the way to effective therapy for Alzheimer disease.

PubMed

Rosenberg, Roger N

2005-11-01

Alzheimer disease (AD) is a major public health issue with a prediction of 12 million Americans being affected by 2025 from the present 4 million. Molecular and genetic findings have provided significant insights into the roles that amyloid, tau, and apolipoprotein E isoforms have in the causation of AD. A central issue in AD pathogenesis is the amyloid cascade hypothesis. It states that abnormal amyloid processing and accumulation is the primary causative factor of AD and other associated neuropathologic abnormalities are of secondary consequence. It is presented to provide the rationale for novel drug and vaccination therapeutic strategies. Future research directed at prediction and prevention of AD through a genomic and proteomic analysis with identification of multiple polymorphic genes that interact, resulting in increased risk for late-onset AD, are the realistic and ultimate goals. A new approach for drug development is required, one that will emphasize a genomic and proteomic analysis to identify at-risk gene sets whose genetic expression is sufficient to cause late onset, sporadic AD. Prediction and prevention of disease prior to clinical signs and symptoms are the goals. A review and analysis from electronic literature databases and subsequent reference searches of the molecular genetic data. including pertinent genetic mutations and abnormal biochemical findings causal of AD, are cited. The amyloid cascade hypothesis, the contributions of apolipoprotein E, and hyperphosphorylated tau are discussed as to their roles in pathogenesis. Molecular targets for potential drug and vaccination therapies are cited from a critical assessment of the molecular and biomedical data. These data form the basis for rational, target-specific drug and vaccination therapies currently employed and planned for the near future. Phase 2 and 3 clinical trial results of drug and vaccination therapies are cited. A new approach is needed as current pharmacologic therapy directed at symptomatic relief has proved to be marginally effective. The genomic and proteomic basis of AD will be defined in the near future, and corresponding molecular therapeutic targets will be identified. Genomic neurology has arrived and its application to resolving AD is our best hope.

Comprehensive prediction of drug-protein interactions and side effects for the human proteome

PubMed Central

Zhou, Hongyi; Gao, Mu; Skolnick, Jeffrey

2015-01-01

Identifying unexpected drug-protein interactions is crucial for drug repurposing. We develop a comprehensive proteome scale approach that predicts human protein targets and side effects of drugs. For drug-protein interaction prediction, FINDSITEcomb, whose average precision is ~30% and recall ~27%, is employed. For side effect prediction, a new method is developed with a precision of ~57% and a recall of ~24%. Our predictions show that drugs are quite promiscuous, with the average (median) number of human targets per drug of 329 (38), while a given protein interacts with 57 drugs. The result implies that drug side effects are inevitable and existing drugs may be useful for repurposing, with only ~1,000 human proteins likely causing serious side effects. A killing index derived from serious side effects has a strong correlation with FDA approved drugs being withdrawn. Therefore, it provides a pre-filter for new drug development. The methodology is free to the academic community on the DR. PRODIS (DRugome, PROteome, and DISeasome) webserver at http://cssb.biology.gatech.edu/dr.prodis/. DR. PRODIS provides protein targets of drugs, drugs for a given protein target, associated diseases and side effects of drugs, as well as an interface for the virtual target screening of new compounds. PMID:26057345

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.

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

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.

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

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.

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 fenoxaprop-P-ethyl or imazamethabenz-methyl metabolism in MHR A. fatua. Instead, we propose that the constitutively elevated GST proteins and related enzymes in MHR plants are representative of a larger, more global suite of abiotic stress-related changes. Published by Elsevier Inc.

Reproducibility of combinatorial peptide ligand libraries for proteome capture evaluated by selected reaction monitoring.

PubMed

Di Girolamo, Francesco; Righetti, Pier Giorgio; Soste, Martin; Feng, Yuehan; Picotti, Paola

2013-08-26

Systems biology studies require the capability to quantify with high precision proteins spanning a broad range of abundances across multiple samples. However, the broad range of protein expression in cells often precludes the detection of low-abundance proteins. Different sample processing techniques can be applied to increase proteome coverage. Among these, combinatorial (hexa)peptide ligand libraries (CPLLs) bound to solid matrices have been used to specifically capture and detect low-abundance proteins in complex samples. To assess whether CPLL capture can be applied in systems biology studies involving the precise quantitation of proteins across a multitude of samples, we evaluated its performance across the whole range of protein abundances in Saccharomyces cerevisiae. We used selected reaction monitoring assays for a set of target proteins covering a broad abundance range to quantitatively evaluate the precision of the approach and its capability to detect low-abundance proteins. Replicated CPLL-isolates showed an average variability of ~10% in the amount of the isolated proteins. The high reproducibility of the technique was not dependent on the abundance of the protein or the amount of beads used for the capture. However, the protein-to-bead ratio affected the enrichment of specific proteins. We did not observe a normalization effect of CPLL beads on protein abundances. However, CPLLs enriched for and depleted specific sets of proteins and thus changed the abundances of proteins from a whole proteome extract. This allowed the identification of ~400 proteins otherwise undetected in an untreated sample, under the experimental conditions used. CPLL capture is thus a useful tool to increase protein identifications in proteomic experiments, but it should be coupled to the analysis of untreated samples, to maximize proteome coverage. Our data also confirms that CPLL capture is reproducible and can be confidently used in quantitative proteomic experiments. Combinatorial hexapeptide ligand libraries (CPLLs) bound to solid matrices have been proposed to specifically capture and detect low-abundance proteins in complex samples. To assess whether the CPLL capture can be confidently applied in systems biology studies involving the precise quantitation of proteins across a broad range of abundances and a multitude of samples, we evaluated its reproducibility and performance features. Using selected reaction monitoring assays for proteins covering the whole range of abundances we show that the technique is reproducible and compatible with quantitative proteomic studies. However, the protein-to-bead ratio affects the enrichment of specific proteins and CPLLs depleted specific sets of proteins from a whole proteome extract. Our results suggest that CPLL-based analyses should be coupled to the analysis of untreated samples, to maximize proteome coverage. Overall, our data confirms the applicability of CPLLs in systems biology research and guides the correct use of this technique. Copyright © 2013 Elsevier B.V. All rights reserved.

Long-Gradient Separations Coupled with Selected Reaction Monitoring for Highly Sensitive, Large Scale Targeted Protein Quantification in a Single Analysis

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

Shi, Tujin; Fillmore, Thomas L.; Gao, Yuqian

2013-10-01

Long-gradient separations coupled to tandem MS were recently demonstrated to provide a deep proteome coverage for global proteomics; however, such long-gradient separations have not been explored for targeted proteomics. Herein, we investigate the potential performance of the long-gradient separations coupled with selected reaction monitoring (LG-SRM) for targeted protein quantification. Direct comparison of LG-SRM (5 h gradient) and conventional LC-SRM (45 min gradient) showed that the long-gradient separations significantly reduced background interference levels and provided an 8- to 100-fold improvement in LOQ for target proteins in human female serum. Based on at least one surrogate peptide per protein, an LOQ ofmore » 10 ng/mL was achieved for the two spiked proteins in non-depleted human serum. The LG-SRM detection of seven out of eight endogenous plasma proteins expressed at ng/mL or sub-ng/mL levels in clinical patient sera was also demonstrated. A correlation coefficient of >0.99 was observed for the results of LG-SRM and ELISA measurements for prostate-specific antigen (PSA) in selected patient sera. Further enhancement of LG-SRM sensitivity was achieved by applying front-end IgY14 immunoaffinity depletion. Besides improved sensitivity, LG-SRM offers at least 3 times higher multiplexing capacity than conventional LC-SRM due to ~3-fold increase in average peak widths for a 300-min gradient compared to a 45-min gradient. Therefore, LG-SRM holds great potential for bridging the gap between global and targeted proteomics due to its advantages in both sensitivity and multiplexing capacity.« less

Early Targets of miR-34a in Neuroblastoma*

PubMed Central

De Antonellis, Pasqualino; Carotenuto, Marianeve; Vandenbussche, Jonathan; De Vita, Gennaro; Ferrucci, Veronica; Medaglia, Chiara; Boffa, Iolanda; Galiero, Alessandra; Di Somma, Sarah; Magliulo, Daniela; Aiese, Nadia; Alonzi, Alessandro; Spano, Daniela; Liguori, Lucia; Chiarolla, Cristina; Verrico, Antonio; Schulte, Johannes H.; Mestdagh, Pieter; Vandesompele, Jo; Gevaert, Kris; Zollo, Massimo

2014-01-01

Several genes encoding for proteins involved in proliferation, invasion, and apoptosis are known to be direct miR-34a targets. Here, we used proteomics to screen for targets of miR-34a in neuroblastoma (NBL), a childhood cancer that originates from precursor cells of the sympathetic nervous system. We examined the effect of miR-34a overexpression using a tetracycline inducible system in two NBL cell lines (SHEP and SH-SY5Y) at early time points of expression (6, 12, and 24 h). Proteome analysis using post-metabolic labeling led to the identification of 2,082 proteins, and among these 186 were regulated (112 proteins down-regulated and 74 up-regulated). Prediction of miR-34a targets via bioinformatics showed that 32 transcripts held miR-34a seed sequences in their 3′-UTR. By combining the proteomics data with Kaplan Meier gene-expression studies, we identified seven new gene products (ALG13, TIMM13, TGM2, ABCF2, CTCF, Ki67, and LYAR) that were correlated with worse clinical outcomes. These were further validated in vitro by 3′-UTR seed sequence regulation. In addition, Michigan Molecular Interactions searches indicated that together these proteins affect signaling pathways that regulate cell cycle and proliferation, focal adhesions, and other cellular properties that overall enhance tumor progression (including signaling pathways such as TGF-β, WNT, MAPK, and FAK). In conclusion, proteome analysis has here identified early targets of miR-34a with relevance to NBL tumorigenesis. Along with the results of previous studies, our data strongly suggest miR-34a as a useful tool for improving the chance of therapeutic success with NBL. PMID:24912852

Targeting tumor-initiating cells: Eliminating anabolic cancer stem cells with inhibitors of protein synthesis or by mimicking caloric restriction

PubMed Central

Lamb, Rebecca; Harrison, Hannah; Smith, Duncan L.; Townsend, Paul A.; Jackson, Thomas; Ozsvari, Bela; Martinez-Outschoorn, Ubaldo E.; Pestell, Richard G.; Howell, Anthony; Lisanti, Michael P.; Sotgia, Federica

2015-01-01

We have used an unbiased proteomic profiling strategy to identify new potential therapeutic targets in tumor-initiating cells (TICs), a.k.a., cancer stem cells (CSCs). Towards this end, the proteomes of mammospheres from two breast cancer cell lines were directly compared to attached monolayer cells. This allowed us to identify proteins that were highly over-expressed in CSCs and/or progenitor cells. We focused on ribosomal proteins and protein folding chaperones, since they were markedly over-expressed in mammospheres. Overall, we identified >80 molecules specifically associated with protein synthesis that were commonly upregulated in mammospheres. Most of these proteins were also transcriptionally upregulated in human breast cancer cells in vivo, providing evidence for their potential clinical relevance. As such, increased mRNA translation could provide a novel mechanism for enhancing the proliferative clonal expansion of TICs. The proteomic findings were functionally validated using known inhibitors of protein synthesis, via three independent approaches. For example, puromycin (which mimics the structure of tRNAs and competitively inhibits protein synthesis) preferentially targeted CSCs in both mammospheres and monolayer cultures, and was ~10-fold more potent for eradicating TICs, than “bulk” cancer cells. In addition, rapamycin, which inhibits mTOR and hence protein synthesis, was very effective at reducing mammosphere formation, at nanomolar concentrations. Finally, mammosphere formation was also markedly inhibited by methionine restriction, which mimics the positive effects of caloric restriction in cultured cells. Remarkably, mammosphere formation was >18-fold more sensitive to methionine restriction and replacement, as directly compared to monolayer cell proliferation. Methionine is absolutely required for protein synthesis, since every protein sequence starts with a methionine residue. Thus, the proliferation and survival of CSCs is very sensitive to the inhibition of protein synthesis, using multiple independent approaches. Our findings have important clinical implications, since they may also explain the positive therapeutic effects of PI3-kinase inhibitors and AKT inhibitors, as they ultimately converge on mTOR signaling and would block protein synthesis. We conclude that inhibition of mRNA translation by pharmacological or protein/methionine restriction may be effective strategies for eliminating TICs. Our data also indicate a novel mechanism by which caloric/protein restriction may reduce tumor growth, by targeting protein synthesis in anabolic tumor-initiating cancer cells. PMID:25671304

Quantitative Proteomics Identifies Activation of Hallmark Pathways of Cancer in Patient Melanoma.

PubMed

Byrum, Stephanie D; Larson, Signe K; Avaritt, Nathan L; Moreland, Linley E; Mackintosh, Samuel G; Cheung, Wang L; Tackett, Alan J

2013-03-01

Molecular pathways regulating melanoma initiation and progression are potential targets of therapeutic development for this aggressive cancer. Identification and molecular analysis of these pathways in patients has been primarily restricted to targeted studies on individual proteins. Here, we report the most comprehensive analysis of formalin-fixed paraffin-embedded human melanoma tissues using quantitative proteomics. From 61 patient samples, we identified 171 proteins varying in abundance among benign nevi, primary melanoma, and metastatic melanoma. Seventy-three percent of these proteins were validated by immunohistochemistry staining of malignant melanoma tissues from the Human Protein Atlas database. Our results reveal that molecular pathways involved with tumor cell proliferation, motility, and apoptosis are mis-regulated in melanoma. These data provide the most comprehensive proteome resource on patient melanoma and reveal insight into the molecular mechanisms driving melanoma progression.

Understanding Cullin-RING E3 Biology through Proteomics-based Substrate Identification*

PubMed Central

Harper, J. Wade; Tan, Meng-Kwang Marcus

2012-01-01

Protein turnover through the ubiquitin-proteasome pathway controls numerous developmental decisions and biochemical processes in eukaryotes. Central to protein ubiquitylation are ubiquitin ligases, which provide specificity in targeted ubiquitylation. With more than 600 ubiquitin ligases encoded by the human genome, many of which remain to be studied, considerable effort is being placed on the development of methods for identifying substrates of specific ubiquitin ligases. In this review, we describe proteomic technologies for the identification of ubiquitin ligase targets, with a particular focus on members of the cullin-RING E3 class of ubiquitin ligases, which use F-box proteins as substrate specific adaptor proteins. Various proteomic methods are described and are compared with genetic approaches that are available. The continued development of such methods is likely to have a substantial impact on the ubiquitin-proteasome field. PMID:22962057

Understanding cullin-RING E3 biology through proteomics-based substrate identification.

PubMed

Harper, J Wade; Tan, Meng-Kwang Marcus

2012-12-01

Protein turnover through the ubiquitin-proteasome pathway controls numerous developmental decisions and biochemical processes in eukaryotes. Central to protein ubiquitylation are ubiquitin ligases, which provide specificity in targeted ubiquitylation. With more than 600 ubiquitin ligases encoded by the human genome, many of which remain to be studied, considerable effort is being placed on the development of methods for identifying substrates of specific ubiquitin ligases. In this review, we describe proteomic technologies for the identification of ubiquitin ligase targets, with a particular focus on members of the cullin-RING E3 class of ubiquitin ligases, which use F-box proteins as substrate specific adaptor proteins. Various proteomic methods are described and are compared with genetic approaches that are available. The continued development of such methods is likely to have a substantial impact on the ubiquitin-proteasome field.

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.

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 enable biologists or other researchers to process, analyze and visualize LC-MS data with what would otherwise be a complex and not user-friendly suite of tools. Corra enables appropriate statistical analyses, with controlled false-discovery rates, ultimately to inform subsequent targeted identification of differentially abundant peptides by MS/MS. For the user not trained in bioinformatics, Corra represents a complete, customizable, free and open source computational platform enabling LC-MS-based proteomic workflows, and as such, addresses an unmet need in the LC-MS proteomics field. PMID:19087345

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

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.

A novel antibody-drug conjugate targeting SAIL for the treatment of hematologic malignancies.

PubMed

Kim, S Y; Theunissen, J-W; Balibalos, J; Liao-Chan, S; Babcock, M C; Wong, T; Cairns, B; Gonzalez, D; van der Horst, E H; Perez, M; Levashova, Z; Chinn, L; D'Alessio, J A; Flory, M; Bermudez, A; Jackson, D Y; Ha, E; Monteon, J; Bruhns, M F; Chen, G; Migone, T-S

2015-05-29

Although several new therapeutic approaches have improved outcomes in the treatment of hematologic malignancies, unmet need persists in acute myeloid leukemia (AML), multiple myeloma (MM) and non-Hodgkin's lymphoma. Here we describe the proteomic identification of a novel cancer target, SAIL (Surface Antigen In Leukemia), whose expression is observed in AML, MM, chronic lymphocytic leukemia (CLL), diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL). While SAIL is widely expressed in CLL, AML, MM, DLBCL and FL patient samples, expression in cancer cell lines is mostly limited to cells of AML origin. We evaluated the antitumor activity of anti-SAIL monoclonal antibodies, 7-1C and 67-7A, conjugated to monomethyl auristatin F. Following internalization, anti-SAIL antibody-drug conjugates (ADCs) exhibited subnanomolar IC50 values against AML cell lines in vitro. In pharmacology studies employing AML cell line xenografts, anti-SAIL ADCs resulted in significant tumor growth inhibition. The restricted expression profile of this target in normal tissues, the high prevalence in different types of hematologic cancers and the observed preclinical activity support the clinical development of SAIL-targeted ADCs.

A novel antibody–drug conjugate targeting SAIL for the treatment of hematologic malignancies

PubMed Central

Kim, S Y; Theunissen, J-W; Balibalos, J; Liao-Chan, S; Babcock, M C; Wong, T; Cairns, B; Gonzalez, D; van der Horst, E H; Perez, M; Levashova, Z; Chinn, L; D‘Alessio, J A; Flory, M; Bermudez, A; Jackson, D Y; Ha, E; Monteon, J; Bruhns, M F; Chen, G; Migone, T-S

2015-01-01

Although several new therapeutic approaches have improved outcomes in the treatment of hematologic malignancies, unmet need persists in acute myeloid leukemia (AML), multiple myeloma (MM) and non-Hodgkin's lymphoma. Here we describe the proteomic identification of a novel cancer target, SAIL (Surface Antigen In Leukemia), whose expression is observed in AML, MM, chronic lymphocytic leukemia (CLL), diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL). While SAIL is widely expressed in CLL, AML, MM, DLBCL and FL patient samples, expression in cancer cell lines is mostly limited to cells of AML origin. We evaluated the antitumor activity of anti-SAIL monoclonal antibodies, 7-1C and 67-7A, conjugated to monomethyl auristatin F. Following internalization, anti-SAIL antibody–drug conjugates (ADCs) exhibited subnanomolar IC50 values against AML cell lines in vitro. In pharmacology studies employing AML cell line xenografts, anti-SAIL ADCs resulted in significant tumor growth inhibition. The restricted expression profile of this target in normal tissues, the high prevalence in different types of hematologic cancers and the observed preclinical activity support the clinical development of SAIL-targeted ADCs. PMID:26024286

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.

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.

Isolation and Proteomic Characterization of the Arabidopsis Golgi Defines Functional and Novel Components Involved in Plant Cell Wall Biosynthesis1[W][OA

PubMed Central

Parsons, Harriet T.; Christiansen, Katy; Knierim, Bernhard; Carroll, Andrew; Ito, Jun; Batth, Tanveer S.; Smith-Moritz, Andreia M.; Morrison, Stephanie; McInerney, Peter; Hadi, Masood Z.; Auer, Manfred; Mukhopadhyay, Aindrila; Petzold, Christopher J.; Scheller, Henrik V.; Loqué, Dominique; Heazlewood, Joshua L.

2012-01-01

The plant Golgi plays a pivotal role in the biosynthesis of cell wall matrix polysaccharides, protein glycosylation, and vesicle trafficking. Golgi-localized proteins have become prospective targets for reengineering cell wall biosynthetic pathways for the efficient production of biofuels from plant cell walls. However, proteomic characterization of the Golgi has so far been limited, owing to the technical challenges inherent in Golgi purification. In this study, a combination of density centrifugation and surface charge separation techniques have allowed the reproducible isolation of Golgi membranes from Arabidopsis (Arabidopsis thaliana) at sufficiently high purity levels for in-depth proteomic analysis. Quantitative proteomic analysis, immunoblotting, enzyme activity assays, and electron microscopy all confirm high purity levels. A composition analysis indicated that approximately 19% of proteins were likely derived from contaminating compartments and ribosomes. The localization of 13 newly assigned proteins to the Golgi using transient fluorescent markers further validated the proteome. A collection of 371 proteins consistently identified in all replicates has been proposed to represent the Golgi proteome, marking an appreciable advancement in numbers of Golgi-localized proteins. A significant proportion of proteins likely involved in matrix polysaccharide biosynthesis were identified. The potential within this proteome for advances in understanding Golgi processes has been demonstrated by the identification and functional characterization of the first plant Golgi-resident nucleoside diphosphatase, using a yeast complementation assay. Overall, these data show key proteins involved in primary cell wall synthesis and include a mixture of well-characterized and unknown proteins whose biological roles and importance as targets for future research can now be realized. PMID:22430844

Exploring the Therapeutic Mechanism of Desmodium styracifolium on Oxalate Crystal-Induced Kidney Injuries Using Comprehensive Approaches Based on Proteomics and Network Pharmacology.

PubMed

Hou, Jiebin; Chen, Wei; Lu, Hongtao; Zhao, Hongxia; Gao, Songyan; Liu, Wenrui; Dong, Xin; Guo, Zhiyong

2018-01-01

Purpose: As a Chinese medicinal herb, Desmodium styracifolium (Osb.) Merr (DS) has been applied clinically to alleviate crystal-induced kidney injuries, but its effective components and their specific mechanisms still need further exploration. This research first combined the methods of network pharmacology and proteomics to explore the therapeutic protein targets of DS on oxalate crystal-induced kidney injuries to provide a reference for relevant clinical use. Methods: Oxalate-induced kidney injury mouse, rat, and HK-2 cell models were established. Proteins differentially expressed between the oxalate and control groups were respectively screened using iTRAQ combined with MALDI-TOF-MS. The common differential proteins of the three models were further analyzed by molecular docking with DS compounds to acquire differential targets. The inverse docking targets of DS were predicted through the platform of PharmMapper. The protein-protein interaction (PPI) relationship between the inverse docking targets and the differential proteins was established by STRING. Potential targets were further validated by western blot based on a mouse model with DS treatment. The effects of constituent compounds, including luteolin, apigenin, and genistein, were investigated based on an oxalate-stimulated HK-2 cell model. Results: Thirty-six common differentially expressed proteins were identified by proteomic analysis. According to previous research, the 3D structures of 15 major constituents of DS were acquired. Nineteen differential targets, including cathepsin D (CTSD), were found using molecular docking, and the component-differential target network was established. Inverse-docking targets including p38 MAPK and CDK-2 were found, and the network of component-reverse docking target was established. Through PPI analysis, 17 inverse-docking targets were linked to differential proteins. The combined network of component-inverse docking target-differential proteins was then constructed. The expressions of CTSD, p-p38 MAPK, and p-CDK-2 were shown to be increased in the oxalate group and decreased in kidney tissue by the DS treatment. Luteolin, apigenin, and genistein could protect oxalate-stimulated tubular cells as active components of DS. Conclusion: The potential targets including the CTSD, p38 MAPK, and CDK2 of DS in oxalate-induced kidney injuries and the active components (luteolin, apigenin, and genistein) of DS were successfully identified in this study by combining proteomics analysis, network pharmacology prediction, and experimental validation.

Applicability of a high-throughput shotgun plasma protein screening approach in understanding maternal biological pathways relevant to infant birth weight outcome.

PubMed

Kumarathasan, P; Vincent, R; Das, D; Mohottalage, S; Blais, E; Blank, K; Karthikeyan, S; Vuong, N Q; Arbuckle, T E; Fraser, W D

2014-04-04

There are reports linking maternal nutritional status, smoking and environmental chemical exposures to adverse pregnancy outcomes. However, biological bases for association between some of these factors and birth outcomes are yet to be established. The objective of this preliminary work is to test the capability of a new high-throughput shotgun plasma proteomic screening in identifying maternal changes relevant to pregnancy outcome. A subset of third trimester plasma samples (N=12) associated with normal and low-birth weight infants were fractionated, tryptic-digested and analyzed for global proteomic changes using a MALDI-TOF-TOF-MS methodology. Mass spectral data were mined for candidate biomarkers using bioinformatic and statistical tools. Maternal plasma profiles of cytokines (e.g. IL8, TNF-α), chemokines (e.g. MCP-1) and cardiovascular endpoints (e.g. ET-1, MMP-9) were analyzed by a targeted approach using multiplex protein array and HPLC-Fluorescence methods. Target and global plasma proteomic markers were used to identify protein interaction networks and maternal biological pathways relevant to low infant birth weight. Our results exhibited the potential to discriminate specific maternal physiologies relevant to risk of adverse birth outcomes. This proteomic approach can be valuable in understanding the impacts of maternal factors such as environmental contaminant exposures and nutrition on birth outcomes in future work. We demonstrate here the fitness of mass spectrometry-based shot-gun proteomics for surveillance of biological changes in mothers, and for adverse pathway analysis in combination with target biomarker information. This approach has potential for enabling early detection of mothers at risk for low infant birth weight and preterm birth, and thus early intervention for mitigation and prevention of adverse pregnancy outcomes. This article is part of a Special Issue entitled: Can Proteomics Fill the Gap Between Genomics and Phenotypes? Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

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

Using Proteomics to Identify Viral microRNA-Regulated Genes | Center for Cancer Research

Cancer.gov

Kaposi sarcoma is a soft tissue malignancy that affects the skin, the mucous membranes, the lymph nodes and other organs of individuals with compromised immune systems. It is caused by infection with human herpesvirus-8 also known as Kaposi sarcoma-associated herpesvirus or KSHV. The herpesvirus family is unique in that it is the only viral family currently known to express multiple microRNAs (miRNAs); KSHV produces 12 pre-miRNAs, which are processed into at least 25 mature miRNAs. While their functions are not well understood, these miRNAs may be a way for the virus to alter the host immune response without producing proteins that could be recognized and targeted by the immune system. Joseph Ziegelbauer, Ph.D., in CCR’s HIV and AIDS Malignancy Branch, and his colleagues set out to identify human targets of KSHV miRNAs and to understand their functional importance.

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

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.

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

GSTM3 and GSTP1: novel players driving tumor progression in cervical cancer

PubMed Central

Checa-Rojas, Alberto; Delgadillo-Silva, Luis Fernando; Velasco-Herrera, Martín del Castillo; Andrade-Domínguez, Andrés; Gil, Jeovanis; Santillán, Orlando; Lozano, Luis; Toledo-Leyva, Alfredo; Ramírez-Torres, Alberto; Talamas-Rohana, Patricia; Encarnación-Guevara, Sergio

2018-01-01

The molecular processes and proteomic markers leading to tumor progression (TP) in cervical cancer (CC) are either unknown or only partially understood. TP affects metabolic and regulatory mechanisms that can be identified as proteomic changes. To identify which proteins are differentially expressed and to understand the mechanisms of cancer progression, we analyzed the dynamics of the tumor proteome in CC cell lines. This analysis revealed two proteins that are up-regulated during TP, GSTM3 and GSTP1. These proteins are involved in cell maintenance, cell survival and the cellular stress response via the NF-κB and MAP kinase pathways during TP. Furthermore, GSTM3 and GSTP1 knockdown showed that evasion of apoptosis was affected, and tumor proliferation was significantly reduced. Our data indicate the critical role of GST proteins in the regulation and progression of cervical cancer cells. Hence, we suggest GSTM3 and GSTP1 as novel biomarkers and potential therapeutic targets for treating cervical cancer. Significance CC is particularly hazardous in the advanced stages, and there are few therapeutic strategies specifically targeting these stages. We performed analyses on CC tumor proteome dynamics and identified GSTM3 and GSTP1 as novel potential therapeutic targets. Knockdown of these proteins showed that they are involved in cell survival, cell proliferation and cellular evasion of apoptosis. PMID:29774096

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.

Heat-Treatment-Responsive Proteins in Different Developmental Stages of Tomato Pollen Detected by Targeted Mass Accuracy Precursor Alignment (tMAPA).

PubMed

Chaturvedi, Palak; Doerfler, Hannes; Jegadeesan, Sridharan; Ghatak, Arindam; Pressman, Etan; Castillejo, Maria Angeles; Wienkoop, Stefanie; Egelhofer, Volker; Firon, Nurit; Weckwerth, Wolfram

2015-11-06

Recently, we have developed a quantitative shotgun proteomics strategy called mass accuracy precursor alignment (MAPA). The MAPA algorithm uses high mass accuracy to bin mass-to-charge (m/z) ratios of precursor ions from LC-MS analyses, determines their intensities, and extracts a quantitative sample versus m/z ratio data alignment matrix from a multitude of samples. Here, we introduce a novel feature of this algorithm that allows the extraction and alignment of proteotypic peptide precursor ions or any other target peptide from complex shotgun proteomics data for accurate quantification of unique proteins. This strategy circumvents the problem of confusing the quantification of proteins due to indistinguishable protein isoforms by a typical shotgun proteomics approach. We applied this strategy to a comparison of control and heat-treated tomato pollen grains at two developmental stages, post-meiotic and mature. Pollen is a temperature-sensitive tissue involved in the reproductive cycle of plants and plays a major role in fruit setting and yield. By LC-MS-based shotgun proteomics, we identified more than 2000 proteins in total for all different tissues. By applying the targeted MAPA data-processing strategy, 51 unique proteins were identified as heat-treatment-responsive protein candidates. The potential function of the identified candidates in a specific developmental stage is discussed.

Open reading frames associated with cancer in the dark matter of the human genome.

PubMed

Delgado, Ana Paula; Brandao, Pamela; Chapado, Maria Julia; Hamid, Sheilin; Narayanan, Ramaswamy

2014-01-01

The uncharacterized proteins (open reading frames, ORFs) in the human genome offer an opportunity to discover novel targets for cancer. A systematic analysis of the dark matter of the human proteome for druggability and biomarker discovery is crucial to mining the genome. Numerous data mining tools are available to mine these ORFs to develop a comprehensive knowledge base for future target discovery and validation. Using the Genetic Association Database, the ORFs of the human dark matter proteome were screened for evidence of association with neoplasms. The Phenome-Genome Integrator tool was used to establish phenotypic association with disease traits including cancer. Batch analysis of the tools for protein expression analysis, gene ontology and motifs and domains was used to characterize the ORFs. Sixty-two ORFs were identified for neoplasm association. The expression Quantitative Trait Loci (eQTL) analysis identified thirteen ORFs related to cancer traits. Protein expression, motifs and domain analysis and genome-wide association studies verified the relevance of these OncoORFs in diverse tumors. The OncoORFs are also associated with a wide variety of human diseases and disorders. Our results link the OncoORFs to diverse diseases and disorders. This suggests a complex landscape of the uncharacterized proteome in human diseases. These results open the dark matter of the proteome to novel cancer target research. Copyright© 2014, International Institute of Anticancer Research (Dr. John G. Delinasios), All rights reserved.

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.

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

Extreme Evolutionary Conservation of Functionally Important Regions in H1N1 Influenza Proteome

PubMed Central

Warren, Samantha; Wan, Xiu-Feng; Conant, Gavin; Korkin, Dmitry

2013-01-01

The H1N1 subtype of influenza A virus has caused two of the four documented pandemics and is responsible for seasonal epidemic outbreaks, presenting a continuous threat to public health. Co-circulating antigenically divergent influenza strains significantly complicates vaccine development and use. Here, by combining evolutionary, structural, functional, and population information about the H1N1 proteome, we seek to answer two questions: (1) do residues on the protein surfaces evolve faster than the protein core residues consistently across all proteins that constitute the influenza proteome? and (2) in spite of the rapid evolution of surface residues in influenza proteins, are there any protein regions on the protein surface that do not evolve? To answer these questions, we first built phylogenetically-aware models of the patterns of surface and interior substitutions. Employing these models, we found a single coherent pattern of faster evolution on the protein surfaces that characterizes all influenza proteins. The pattern is consistent with the events of inter-species reassortment, the worldwide introduction of the flu vaccine in the early 80’s, as well as the differences caused by the geographic origins of the virus. Next, we developed an automated computational pipeline to comprehensively detect regions of the protein surface residues that were 100% conserved over multiple years and in multiple host species. We identified conserved regions on the surface of 10 influenza proteins spread across all avian, swine, and human strains; with the exception of a small group of isolated strains that affected the conservation of three proteins. Surprisingly, these regions were also unaffected by genetic variation in the pandemic 2009 H1N1 viral population data obtained from deep sequencing experiments. Finally, the conserved regions were intrinsically related to the intra-viral macromolecular interaction interfaces. Our study may provide further insights towards the identification of novel protein targets for influenza antivirals. PMID:24282564

The proteome and phosphoproteome of maize pollen uncovers fertility candidate proteins.

PubMed

Chao, Qing; Gao, Zhi-Fang; Wang, Yue-Feng; Li, Zhe; Huang, Xia-He; Wang, Ying-Chun; Mei, Ying-Chang; Zhao, Biligen-Gaowa; Li, Liang; Jiang, Yu-Bo; Wang, Bai-Chen

2016-06-01

Maize is unique since it is both monoecious and diclinous (separate male and female flowers on the same plant). We investigated the proteome and phosphoproteome of maize pollen containing modified proteins and here we provide a comprehensive pollen proteome and phosphoproteome which contain 100,990 peptides from 6750 proteins and 5292 phosphorylated sites corresponding to 2257 maize phosphoproteins, respectively. Interestingly, among the total 27 overrepresented phosphosite motifs we identified here, 11 were novel motifs, which suggested different modification mechanisms in plants compared to those of animals. Enrichment analysis of pollen phosphoproteins showed that pathways including DNA synthesis/chromatin structure, regulation of RNA transcription, protein modification, cell organization, signal transduction, cell cycle, vesicle transport, transport of ions and metabolisms, which were involved in pollen development, the following germination and pollen tube growth, were regulated by phosphorylation. In this study, we also found 430 kinases and 105 phosphatases in the maize pollen phosphoproteome, among which calcium dependent protein kinases (CDPKs), leucine rich repeat kinase, SNF1 related protein kinases and MAPK family proteins were heavily enriched and further analyzed. From our research, we also uncovered hundreds of male sterility-associated proteins and phosphoproteins that might influence maize productivity and serve as targets for hybrid maize seed production. At last, a putative complex signaling pathway involving CDPKs, MAPKs, ubiquitin ligases and multiple fertility proteins was constructed. Overall, our data provides new insight for further investigation of protein phosphorylation status in mature maize pollen and construction of maize male sterile mutants in the future.

Proteomics of gliomas: Initial biomarker discovery and evolution of technology

PubMed Central

Kalinina, Juliya; Peng, Junmin; Ritchie, James C.; Van Meir, Erwin G.

2011-01-01

Gliomas are a group of aggressive brain tumors that diffusely infiltrate adjacent brain tissues, rendering them largely incurable, even with multiple treatment modalities and agents. Mostly asymptomatic at early stages, they present in several subtypes with astrocytic or oligodendrocytic features and invariably progress to malignant forms. Gliomas are difficult to classify precisely because of interobserver variability during histopathologic grading. Identifying biological signatures of each glioma subtype through protein biomarker profiling of tumor or tumor-proximal fluids is therefore of high priority. Such profiling not only may provide clues regarding tumor classification but may identify clinical biomarkers and pathologic targets for the development of personalized treatments. In the past decade, differential proteomic profiling techniques have utilized tumor, cerebrospinal fluid, and plasma from glioma patients to identify the first candidate diagnostic, prognostic, predictive, and therapeutic response markers, highlighting the potential for glioma biomarker discovery. The number of markers identified, however, has been limited, their reproducibility between studies is unclear, and none have been validated for clinical use. Recent technological advancements in methodologies for high-throughput profiling, which provide easy access, rapid screening, low sample consumption, and accurate protein identification, are anticipated to accelerate brain tumor biomarker discovery. Reliable tools for biomarker verification forecast translation of the biomarkers into clinical diagnostics in the foreseeable future. Herein we update the reader on the recent trends and directions in glioma proteomics, including key findings and established and emerging technologies for analysis, together with challenges we are still facing in identifying and verifying potential glioma biomarkers. PMID:21852429

Parallel comparative proteomics and phosphoproteomics reveal that cattle myostatin regulates phosphorylation of key enzymes in glycogen metabolism and glycolysis pathway

PubMed Central

Yang, Shuping; Li, Xin; Liu, Xinfeng; Ding, Xiangbin; Xin, Xiangbo; Jin, Congfei; Zhang, Sheng; Li, Guangpeng; Guo, Hong

2018-01-01

MSTN-encoded myostatin is a negative regulator of skeletal muscle development. Here, we utilized the gluteus tissues from MSTN gene editing and wild type Luxi beef cattle which are native breed of cattle in China, performed tandem mass tag (TMT) -based comparative proteomics and phosphoproteomics analyses to investigate the regulatory mechanism of MSTN related to cellular metabolism and signaling pathway in muscle development. Out of 1,315 proteins, 69 differentially expressed proteins (DEPs) were found in global proteomics analysis. Meanwhile, 149 differentially changed phosphopeptides corresponding to 76 unique phosphorylated proteins (DEPPs) were detected from 2,600 identified phosphopeptides in 702 phosphorylated proteins. Bioinformatics analyses suggested that majority of DEPs and DEPPs were closely related to glycolysis, glycogenolysis, and muscle contractile fibre processes. The global discovery results were validated by Multiple Reaction Monitoring (MRM)-based targeted peptide quantitation analysis, western blotting, and muscle glycogen content measurement. Our data revealed that increase in abundance of key enzymes and phosphorylation on their regulatory sites appears responsible for the enhanced glycogenolysis and glycolysis in MSTN−/−. The elevated glycogenolysis was assocaited with an enhanced phosphorylation of Ser1018 in PHKA1, and Ser641/Ser645 in GYS1, which were regulated by upstream phosphorylated AKT-GSK3β pathway and highly consistent with the lower glycogen content in gluteus of MSTN−/−. Collectively, this study provides new insights into the regulatory mechanisms of MSTN involved in energy metabolism and muscle growth. PMID:29541418

Proteomic analysis of the molecular response of Raji cells to maslinic acid treatment.

PubMed

Yap, W H; Khoo, K S; Lim, S H; Yeo, C C; Lim, Y M

2012-01-15

Maslinic acid, a natural pentacyclic triterpene has been shown to inhibit growth and induce apoptosis in some tumour cell lines. We studied the molecular response of Raji cells towards maslinic acid treatment. A proteomics approach was employed to identify the target proteins. Seventeen differentially expressed proteins including those involved in DNA replication, microtubule filament assembly, nucleo-cytoplasmic trafficking, cell signaling, energy metabolism and cytoskeletal organization were identified by MALDI TOF-TOF MS. The down-regulation of stathmin, Ran GTPase activating protein-1 (RanBP1), and microtubule associated protein RP/EB family member 1 (EB1) were confirmed by Western blotting. The study of the effect of maslinic acid on Raji cell cycle regulation showed that it induced a G1 cell cycle arrest. The differential proteomic changes in maslinic acid-treated Raji cells demonstrated that it also inhibited expression of dUTPase and stathmin which are known to induce early S and G2 cell cycle arrests. The mechanism of maslinic acid-induced cell cycle arrest may be mediated by inhibiting cyclin D1 expression and enhancing the levels of cell cycle-dependent kinase (CDK) inhibitor p21 protein. Maslinic acid suppressed nuclear factor-kappa B (NF-κB) activity which is known to stimulate expression of anti-apoptotic and cell cycle regulatory gene products. These results suggest that maslinic acid affects multiple signaling molecules and inhibits fundamental pathways regulating cell growth and survival in Raji cells. Copyright © 2011 Elsevier GmbH. All rights reserved.

Physiological and proteomic analyses of Fe(III)-reducing co-cultures of Desulfotomaculum reducens MI-1 and Geobacter sulfurreducens PCA.

PubMed

Otwell, Anne E; Callister, Stephen J; Sherwood, Robert W; Zhang, Sheng; Goldman, Abby R; Smith, Richard D; Richardson, Ruth E

2018-06-15

We established Fe(III)-reducing co-cultures of two species of metal-reducing bacteria, the Gram-positive Desulfotomaculum reducens MI-1 and the Gram-negative Geobacter sulfurreducens PCA. Co-cultures were given pyruvate, a substrate that D. reducens can ferment and use as electron donor for Fe(III) reduction. G. sulfurreducens relied upon products of pyruvate oxidation by D. reducens (acetate, hydrogen) for use as electron donor in the co-culture. Co-cultures reduced Fe(III) to Fe(II) robustly, and Fe(II) was consistently detected earlier in co-cultures than pure cultures. Notably, faster cell growth, and correspondingly faster pyruvate oxidation, was observed by D. reducens in co-cultures. Global comparative proteomic analysis was performed to observe differential protein abundance during co-culture vs. pure culture growth. Proteins previously associated with Fe(III) reduction in G. sulfurreducens, namely c-type cytochromes and type IV pili proteins, were significantly increased in abundance in co-cultures relative to pure cultures. D. reducens ribosomal proteins were significantly increased in co-cultures, likely a reflection of faster growth rates observed for D. reducens cells while in co-culture. Furthermore, we developed multiple reaction monitoring (MRM) assays to quantitate specific biomarker peptides. The assays were validated in pure and co-cultures, and protein abundance ratios from targeted MRM and global proteomic analysis correlate significantly. © 2018 John Wiley & Sons Ltd.

The NEDD8 inhibitor MLN4924 increases the size of the nucleolus and activates p53 through the ribosomal-Mdm2 pathway.

PubMed

Bailly, A; Perrin, A; Bou Malhab, L J; Pion, E; Larance, M; Nagala, M; Smith, P; O'Donohue, M-F; Gleizes, P-E; Zomerdijk, J; Lamond, A I; Xirodimas, D P

2016-01-28

The ubiquitin-like molecule NEDD8 is essential for viability, growth and development, and is a potential target for therapeutic intervention. We found that the small molecule inhibitor of NEDDylation, MLN4924, alters the morphology and increases the surface size of the nucleolus in human and germline cells of Caenorhabditis elegans in the absence of nucleolar fragmentation. SILAC proteomics and monitoring of rRNA production, processing and ribosome profiling shows that MLN4924 changes the composition of the nucleolar proteome but does not inhibit RNA Pol I transcription. Further analysis demonstrates that MLN4924 activates the p53 tumour suppressor through the RPL11/RPL5-Mdm2 pathway, with characteristics of nucleolar stress. The study identifies the nucleolus as a target of inhibitors of NEDDylation and provides a mechanism for p53 activation upon NEDD8 inhibition. It also indicates that targeting the nucleolar proteome without affecting nucleolar transcription initiates the required signalling events for the control of cell cycle regulators.

A potential target for organophosphate insecticides leading to spermatotoxicity.

PubMed

Suzuki, Himiko; Tomizawa, Motohiro; Ito, Yuki; Abe, Keisuke; Noro, Yuki; Kamijima, Michihiro

2013-10-16

Organophosphate (OP) insecticides as an anticholinesterase also act on the diverse serine hydrolase targets, thereby revealing secondary or unexpected toxic effects including male reproductive toxicity. The present investigation detects a possible target molecule(s) for OP-induced spermatotoxicity (sperm deformity, underdevelopment, and reduced motility) from a chemical standpoint. The activity-based protein profiling (ABPP) approach with a phosphonofluoridate fluorescent probe pinpointed the molecular target for fenitrothion (FNT, a major OP insecticide) oxon (bioactive metabolite of FNT) in the mouse testicular membrane proteome, i.e., FNT oxon phosphorylates the fatty acid amide hydrolase (FAAH), which plays pivotal roles in spermatogenesis and sperm motility acquirement. Subsequently, mice were treated orally with vehicle or FNT for 10 days, and FAAH activity in testis or epididymis cauda was markedly reduced by the subacute exposure. ABPP analysis revealed that FAAH was selectively inhibited among the FNT-treated testicular membrane proteome. Accordingly, FAAH is a potential target for OP-elicited spermatotoxicity.

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-to-cell signaling and interaction (including epinephrine, dopamine, and adrenergic signaling and receptor function), and small molecule biochemistry. Interestingly, while the biofunctions identified in this study may represent pathways underpinning EGS-induced neurodegeneration, this is also the first demonstration of potential molecular conservation (including previously unreported dysregulation of the UPS and APP) spanning the degenerative cascades from an apparently unrelated condition of large animals, to small animal models with altered neuronal vulnerability, and human neurological conditions. Importantly, this study highlights the feasibility and benefits of applying modern proteomic techniques to veterinary investigations of neurodegenerative processes in diseases of large animals. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

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

We Are Not Alone: The iMOP Initiative and Its Roles in a Biology- and Disease-Driven Human Proteome Project.

PubMed

Tholey, Andreas; Taylor, Nicolas L; Heazlewood, Joshua L; Bendixen, Emøke

2017-12-01

Mapping of the human proteome has advanced significantly in recent years and will provide a knowledge base to accelerate our understanding of how proteins and protein networks can affect human health and disease. However, providing solutions to human health challenges will likely fail if insights are exclusively based on studies of human samples and human proteomes. In recent years, it has become evident that human health depends on an integrated understanding of the many species that make human life possible. These include the commensal microorganisms that are essential to human life, pathogens, and food species as well as the classic model organisms that enable studies of biological mechanisms. The Human Proteome Organization (HUPO) initiative on multiorganism proteomes (iMOP) works to support proteome research undertaken on nonhuman species that remain widely under-studied compared with the progress in human proteome research. This perspective argues the need for further research on multiple species that impact human life. We also present an update on recent progress in model organisms, microbiota, and food species, address the emerging problem of antibiotics resistance, and outline how iMOP activities could lead to a more inclusive approach for the human proteome project (HPP) to better support proteome research aimed at improving human health and furthering knowledge on human biology.

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.

Identification of an Effective Early Signaling Signature during Neo-Vasculogenesis In Vivo by Ex Vivo Proteomic Profiling

PubMed Central

Rohban, Rokhsareh; Reinisch, Andreas; Etchart, Nathalie; Schallmoser, Katharina; Hofmann, Nicole A.; Szoke, Krisztina; Brinchmann, Jan E.; Rad, Ehsan Bonyadi; Rohde, Eva; Strunk, Dirk

2013-01-01

Therapeutic neo-vasculogenesis in vivo can be achieved by the co-transplantation of human endothelial colony-forming progenitor cells (ECFCs) with mesenchymal stem/progenitor cells (MSPCs). The underlying mechanism is not completely understood thus hampering the development of novel stem cell therapies. We hypothesized that proteomic profiling could be used to retrieve the in vivo signaling signature during the initial phase of human neo-vasculogenesis. ECFCs and MSPCs were therefore either transplanted alone or co-transplanted subcutaneously into immune deficient mice. Early cell signaling, occurring within the first 24 hours in vivo, was analyzed using antibody microarray proteomic profiling. Vessel formation and persistence were verified in parallel transplants for up to 24 weeks. Proteomic analysis revealed significant alteration of regulatory components including caspases, calcium/calmodulin-dependent protein kinase, DNA protein kinase, human ErbB2 receptor-tyrosine kinase as well as mitogen-activated protein kinases. Caspase-4 was selected from array results as one therapeutic candidate for targeting vascular network formation in vitro as well as modulating therapeutic vasculogenesis in vivo. As a proof-of-principle, caspase-4 and general caspase-blocking led to diminished endothelial network formation in vitro and significantly decreased vasculogenesis in vivo. Proteomic profiling ex vivo thus unraveled a signaling signature which can be used for target selection to modulate neo-vasculogenesis in vivo. PMID:23826172

Activity-based proteomics of enzyme superfamilies: serine hydrolases as a case study.

PubMed

Simon, Gabriel M; Cravatt, Benjamin F

2010-04-09

Genome sequencing projects have uncovered thousands of uncharacterized enzymes in eukaryotic and prokaryotic organisms. Deciphering the physiological functions of enzymes requires tools to profile and perturb their activities in native biological systems. Activity-based protein profiling has emerged as a powerful chemoproteomic strategy to achieve these objectives through the use of chemical probes that target large swaths of enzymes that share active-site features. Here, we review activity-based protein profiling and its implementation to annotate the enzymatic proteome, with particular attention given to probes that target serine hydrolases, a diverse superfamily of enzymes replete with many uncharacterized members.

Thioredoxin targets fundamental processes in a methane-producing archaeon, Methanocaldococcus jannaschii

PubMed Central

Susanti, Dwi; Wong, Joshua H.; Vensel, William H.; Loganathan, Usha; DeSantis, Rebecca; Schmitz, Ruth A.; Balsera, Monica; Buchanan, Bob B.; Mukhopadhyay, Biswarup

2014-01-01

Thioredoxin (Trx), a small redox protein, controls multiple processes in eukaryotes and bacteria by changing the thiol redox status of selected proteins. The function of Trx in archaea is, however, unexplored. To help fill this gap, we have investigated this aspect in methanarchaea—strict anaerobes that produce methane, a fuel and greenhouse gas. Bioinformatic analyses suggested that Trx is nearly universal in methanogens. Ancient methanogens that produce methane almost exclusively from H2 plus CO2 carried approximately two Trx homologs, whereas nutritionally versatile members possessed four to eight. Due to its simplicity, we studied the Trx system of Methanocaldococcus jannaschii—a deeply rooted hyperthermophilic methanogen growing only on H2 plus CO2. The organism carried two Trx homologs, canonical Trx1 that reduced insulin and accepted electrons from Escherichia coli thioredoxin reductase and atypical Trx2. Proteomic analyses with air-oxidized extracts treated with reduced Trx1 revealed 152 potential targets representing a range of processes—including methanogenesis, biosynthesis, transcription, translation, and oxidative response. In enzyme assays, Trx1 activated two selected targets following partial deactivation by O2, validating proteomics observations: methylenetetrahydromethanopterin dehydrogenase, a methanogenesis enzyme, and sulfite reductase, a detoxification enzyme. The results suggest that Trx assists methanogens in combating oxidative stress and synchronizing metabolic activities with availability of reductant, making it a critical factor in the global carbon cycle and methane emission. Because methanogenesis developed before the oxygenation of Earth, it seems possible that Trx functioned originally in metabolic regulation independently of O2, thus raising the question whether a complex biological system of this type evolved at least 2.5 billion years ago. PMID:24505058

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

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

Identification and characterization of potential druggable targets among hypothetical proteins of extensively drug resistant Mycobacterium tuberculosis (XDR KZN 605) through subtractive genomics approach.

PubMed

Uddin, Reaz; Siddiqui, Quratulain Nehal; Azam, Syed Sikander; Saima, Bibi; Wadood, Abdul

2018-03-01

Among the resistant isolates of tuberculosis (TB), the multidrug resistance tuberculosis (MDR-TB) and extensively drug resistant tuberculosis (XDR-TB) are the areas of growing concern for which the front-line antibiotics are no more effective. As a result, the search of new therapeutic targets against TB is an imperative need of time. On the other hand, the target identification is an a priori step in drug discovery based research. Furthermore, the availability of the complete proteomic data of extensively drug resistant Mycobacterium tuberculosis (XDR-MTB) made it possible to carry out in silico analysis for the discovery of new drug targets. In the current study, we aimed to prioritize the potential drug targets among the hypothetical proteins of XDR-TB via subtractive genomics approach. In the subtractive genomics, we stepwise reduced the complete proteome of XDR-MTB to only two hypothetical proteins and evidently proposed them as new therapeutic targets. The 3D structure of one of the two target proteins was predicted via homology modeling and later on, validated by various analysis tools. Our study suggested that the domains identified and the motif hits found in the sequences of the shortlisted drug targets are crucial for the survival of the XDR-MTB. To the best of our knowledge, the current study is the first attempt in which the complete proteomic data of XDR-MTB was subjected to the computational subtractive genomics approach and therefore, would provide an opportunity to identify the unique therapeutic targets against deadly XDR-MTB. Copyright © 2017 Elsevier B.V. All rights reserved.

Molecular targets of alcohol action: translational research for pharmacotherapy development and screening

PubMed Central

Gorini, Giorgio; Bell, Richard L.; Mayfield, R. Dayne

2016-01-01

Summary Alcohol abuse and dependence are multifaceted disorders with neurobiological, psychological, and environmental components. Research on other complex neuropsychiatric diseases suggests that genetically influenced intermediate characteristics affect the risk for heavy alcohol consumption and its consequences. Diverse therapeutic interventions can be developed through identification of reliable biomarkers for this disorder and new pharmacological targets for its treatment. Advances in the fields of genomics and proteomics offer a number of possible targets for the development of new therapeutic approaches. This brain-focused review highlights studies identifying neurobiological systems associated with these targets and possible pharmacotherapies, summarizing evidence from clinically relevant animal and human studies, as well as sketching improvements and challenges facing the fields of proteomics and genomics. Concluding thoughts on using results from these profiling technologies for medication development are also presented. PMID:21199775

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.

Genomic identification of potential targets unique to Candida albicans for the discovery of antifungal agents.

PubMed

Tripathi, Himanshu; Luqman, Suaib; Meena, Abha; Khan, Feroz

2014-01-01

Despite of modern antifungal therapy, the mortality rates of invasive infection with human fungal pathogen Candida albicans are up to 40%. Studies suggest that drug resistance in the three most common species of human fungal pathogens viz., C. albicans, Aspergillus fumigatus (causing mortality rate up to 90%) and Cryptococcus neoformans (causing mortality rate up to 70%) is due to mutations in the target enzymes or high expression of drug transporter genes. Drug resistance in human fungal pathogens has led to an imperative need for the identification of new targets unique to fungal pathogens. In the present study, we have used a comparative genomics approach to find out potential target proteins unique to C. albicans, an opportunistic fungus responsible for severe infection in immune-compromised human. Interestingly, many target proteins of existing antifungal agents showed orthologs in human cells. To identify unique proteins, we have compared proteome of C. albicans [SC5314] i.e., 14,633 total proteins retrieved from the RefSeq database of NCBI, USA with proteome of human and non-pathogenic yeast Saccharomyces cerevisiae. Results showed that 4,568 proteins were identified unique to C. albicans as compared to those of human and later when these unique proteins were compared with S. cerevisiae proteome, finally 2,161 proteins were identified as unique proteins and after removing repeats total 1,618 unique proteins (42 functionally known, 1,566 hypothetical and 10 unknown) were selected as potential antifungal drug targets unique to C. albicans.

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.

Updated biological roles for matrix metalloproteinases and new "intracellular" substrates revealed by degradomics.

PubMed

Butler, Georgina S; Overall, Christopher M

2009-11-24

Shotgun proteomics techniques are conceptually unbiased, but data interpretation and follow-up experiments are often constrained by dogma, established beliefs that are accepted without question, that can dilute the power of proteomics and hinder scientific progress. Proteomics and degradomics, the characterization of all proteases, inhibitors, and protease substrates by genomic and proteomic techniques, have exponentially expanded the known substrate repertoire of the matrix metalloproteinases (MMPs), even to include intracellular proteins with newly recognized extracellular functions. Thus, the dogma that MMPs are dowdy degraders of extracellular matrix has been resolutely overturned, and the metamorphosis of MMPs into modulators of multiple signaling pathways has been facilitated. Here we review progress made in the field of degradomics and present a current view of the MMP degradome.

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.

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

Review of Software Tools for Design and Analysis of Large scale MRM Proteomic Datasets

PubMed Central

Colangelo, Christopher M.; Chung, Lisa; Bruce, Can; Cheung, Kei-Hoi

2013-01-01

Selective or Multiple Reaction monitoring (SRM/MRM) is a liquid-chromatography (LC)/tandem-mass spectrometry (MS/MS) method that enables the quantitation of specific proteins in a sample by analyzing precursor ions and the fragment ions of their selected tryptic peptides. Instrumentation software has advanced to the point that thousands of transitions (pairs of primary and secondary m/z values) can be measured in a triple quadrupole instrument coupled to an LC, by a well-designed scheduling and selection of m/z windows. The design of a good MRM assay relies on the availability of peptide spectra from previous discovery-phase LC-MS/MS studies. The tedious aspect of manually developing and processing MRM assays involving thousands of transitions has spurred to development of software tools to automate this process. Software packages have been developed for project management, assay development, assay validation, data export, peak integration, quality assessment, and biostatistical analysis. No single tool provides a complete end-to-end solution, thus this article reviews the current state and discusses future directions of these software tools in order to enable researchers to combine these tools for a comprehensive targeted proteomics workflow. PMID:23702368

Analyzing Arabidopsis thaliana root proteome provides insights into the molecular bases of enantioselective imazethapyr toxicity

PubMed Central

Qian, Haifeng; Lu, Haiping; Ding, Haiyan; Lavoie, Michel; Li, Yali; Liu, Weiping; Fu, Zhengwei

2015-01-01

Imazethapyr (IM) is a widely used chiral herbicide that inhibits the synthesis of branched-chain amino acids (BCAAs). IM is thought to exert its toxic effects on amino acid synthesis mainly through inhibition of acetolactate synthase activity, but little is known about the potential effects of IM on other key biochemical pathways. Here, we exposed the model plant Arabidospsis thaliana to trace S- and R-IM enantiomer concentrations and examined IM toxicity effects on the root proteome using iTRAQ. Conventional analyses of root carbohydrates, organic acids, and enzyme activities were also performed. We discovered several previously unknown key biochemical pathways targeted by IM in Arabidospsis. 1,322 and 987 proteins were differentially expressed in response to R- and S-IM treatments, respectively. Bioinformatics and physiological analyses suggested that IM reduced the BCAA tissue content not only by strongly suppressing BCAA synthesis but also by increasing BCAA catabolism. IM also affected sugar and starch metabolism, changed the composition of root cell walls, increased citrate production and exudation, and affected the microbial community structure of the rhizosphere. The present study shed new light on the multiple toxicity mechanisms of a selective herbicide on a model plant. PMID:26153126

Analyzing Arabidopsis thaliana root proteome provides insights into the molecular bases of enantioselective imazethapyr toxicity

NASA Astrophysics Data System (ADS)

Qian, Haifeng; Lu, Haiping; Ding, Haiyan; Lavoie, Michel; Li, Yali; Liu, Weiping; Fu, Zhengwei

2015-07-01

Imazethapyr (IM) is a widely used chiral herbicide that inhibits the synthesis of branched-chain amino acids (BCAAs). IM is thought to exert its toxic effects on amino acid synthesis mainly through inhibition of acetolactate synthase activity, but little is known about the potential effects of IM on other key biochemical pathways. Here, we exposed the model plant Arabidospsis thaliana to trace S- and R-IM enantiomer concentrations and examined IM toxicity effects on the root proteome using iTRAQ. Conventional analyses of root carbohydrates, organic acids, and enzyme activities were also performed. We discovered several previously unknown key biochemical pathways targeted by IM in Arabidospsis. 1,322 and 987 proteins were differentially expressed in response to R- and S-IM treatments, respectively. Bioinformatics and physiological analyses suggested that IM reduced the BCAA tissue content not only by strongly suppressing BCAA synthesis but also by increasing BCAA catabolism. IM also affected sugar and starch metabolism, changed the composition of root cell walls, increased citrate production and exudation, and affected the microbial community structure of the rhizosphere. The present study shed new light on the multiple toxicity mechanisms of a selective herbicide on a model plant.

Integrative Identification of Arabidopsis Mitochondrial Proteome and Its Function Exploitation through Protein Interaction Network

PubMed Central

Cui, Jian; Liu, Jinghua; Li, Yuhua; Shi, Tieliu

2011-01-01

Mitochondria are major players on the production of energy, and host several key reactions involved in basic metabolism and biosynthesis of essential molecules. Currently, the majority of nucleus-encoded mitochondrial proteins are unknown even for model plant Arabidopsis. We reported a computational framework for predicting Arabidopsis mitochondrial proteins based on a probabilistic model, called Naive Bayesian Network, which integrates disparate genomic data generated from eight bioinformatics tools, multiple orthologous mappings, protein domain properties and co-expression patterns using 1,027 microarray profiles. Through this approach, we predicted 2,311 candidate mitochondrial proteins with 84.67% accuracy and 2.53% FPR performances. Together with those experimental confirmed proteins, 2,585 mitochondria proteins (named CoreMitoP) were identified, we explored those proteins with unknown functions based on protein-protein interaction network (PIN) and annotated novel functions for 26.65% CoreMitoP proteins. Moreover, we found newly predicted mitochondrial proteins embedded in particular subnetworks of the PIN, mainly functioning in response to diverse environmental stresses, like salt, draught, cold, and wound etc. Candidate mitochondrial proteins involved in those physiological acitivites provide useful targets for further investigation. Assigned functions also provide comprehensive information for Arabidopsis mitochondrial proteome. PMID:21297957

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.

In-Depth, Reproducible Analysis of Human Plasma Using IgY 14 and SuperMix Immunodepletion.

PubMed

Beer, Lynn A; Ky, Bonnie; Barnhart, Kurt T; Speicher, David W

2017-01-01

Identification of cancer and other disease biomarkers in human plasma has been exceptionally challenging due to the complex nature of plasma and the presence of a moderate number of high- and medium-abundance proteins which mask low-abundance proteins of interest. As a result, immunoaffinity depletion formats combining multiple antibodies to target the most abundant plasma proteins have become the first stage in most plasma proteome discovery schemes. This protocol describes the use of tandem IgY 14 and SuperMix immunoaffinity depletion to reproducibly remove >99% of total plasma protein. This greatly increases the depth of analysis of human plasma proteomes. Depleted plasma samples can then be analyzed in a single high-resolution LC-MS/MS run on a Q Exactive Plus mass spectrometer, followed by label-free quantitation. If greater depth of analysis is desired, the depleted plasma can be further fractionated by separating the sample for a short distance on a 1D SDS gel and cutting the gel into uniform slices prior to trypsin digestion. Alternatively, the depleted plasma can be reduced, alkylated, and digested with trypsin followed by high-pH reversed-phase HPLC separation.

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 photobiological results from UVB-irradiated models and can elicit new diagnostic and treatment strategies based on altered metabolism. Copyright © 2015. Published by Elsevier B.V.

Feasibility of investigating differential proteomic expression in depression: implications for biomarker development in mood disorders

PubMed Central

Frye, M A; Nassan, M; Jenkins, G D; Kung, S; Veldic, M; Palmer, B A; Feeder, S E; Tye, S J; Choi, D S; Biernacka, J M

2015-01-01

The objective of this study was to determine whether proteomic profiling in serum samples can be utilized in identifying and differentiating mood disorders. A consecutive sample of patients with a confirmed diagnosis of unipolar (UP n=52) or bipolar depression (BP-I n=46, BP-II n=49) and controls (n=141) were recruited. A 7.5-ml blood sample was drawn for proteomic multiplex profiling of 320 proteins utilizing the Myriad RBM Discovery Multi-Analyte Profiling platform. After correcting for multiple testing and adjusting for covariates, growth differentiation factor 15 (GDF-15), hemopexin (HPX), hepsin (HPN), matrix metalloproteinase-7 (MMP-7), retinol-binding protein 4 (RBP-4) and transthyretin (TTR) all showed statistically significant differences among groups. In a series of three post hoc analyses correcting for multiple testing, MMP-7 was significantly different in mood disorder (BP-I+BP-II+UP) vs controls, MMP-7, GDF-15, HPN were significantly different in bipolar cases (BP-I+BP-II) vs controls, and GDF-15, HPX, HPN, RBP-4 and TTR proteins were all significantly different in BP-I vs controls. Good diagnostic accuracy (ROC-AUC⩾0.8) was obtained most notably for GDF-15, RBP-4 and TTR when comparing BP-I vs controls. While based on a small sample not adjusted for medication state, this discovery sample with a conservative method of correction suggests feasibility in using proteomic panels to assist in identifying and distinguishing mood disorders, in particular bipolar I disorder. Replication studies for confirmation, consideration of state vs trait serial assays to delineate proteomic expression of bipolar depression vs previous mania, and utility studies to assess proteomic expression profiling as an advanced decision making tool or companion diagnostic are encouraged. PMID:26645624

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.

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

Diagnosis of major depressive disorder by combining multimodal information from heart rate dynamics and serum proteomics using machine-learning algorithm.

PubMed

Kim, Eun Young; Lee, Min Young; Kim, Se Hyun; Ha, Kyooseob; Kim, Kwang Pyo; Ahn, Yong Min

2017-06-02

Major depressive disorder (MDD) is a systemic and multifactorial disorder that involves abnormalities in multiple biochemical pathways and the autonomic nervous system. This study applied a machine-learning method to classify MDD and control groups by incorporating data from serum proteomic analysis and heart rate variability (HRV) analysis for the identification of novel peripheral biomarkers. The study subjects consisted of 25 drug-free female MDD patients and 25 age- and sex-matched healthy controls. First, quantitative serum proteome profiles were analyzed by liquid chromatography-tandem mass spectrometry using pooled serum samples from 10 patients and 10 controls. Next, candidate proteins were quantified with multiple reaction monitoring (MRM) in 50 subjects. We also analyzed 22 linear and nonlinear HRV parameters in 50 subjects. Finally, we identified a combined biomarker panel consisting of proteins and HRV indexes using a support vector machine with recursive feature elimination. A separation between MDD and control groups was achieved using five parameters (apolipoprotein B, group-specific component, ceruloplasmin, RMSSD, and SampEn) at 80.1% classification accuracy. A combination of HRV and proteomic data achieved better classification accuracy. A high classification accuracy can be achieved by combining multimodal information from heart rate dynamics and serum proteomics in MDD. Our approach can be helpful for accurate clinical diagnosis of MDD. Further studies using larger, independent cohorts are needed to verify the role of these candidate biomarkers for MDD diagnosis. Copyright © 2017 Elsevier Inc. All rights reserved.

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

Elucidation of salt stress defense and tolerance mechanisms of crop plants using proteomics--current achievements and perspectives.

PubMed

Barkla, Bronwyn J; Castellanos-Cervantes, Thelma; de León, José L Diaz; Matros, Andrea; Mock, Hans-Peter; Perez-Alfocea, Francisco; Salekdeh, Ghasem H; Witzel, Katja; Zörb, Christian

2013-06-01

Salinity is a major threat limiting the productivity of crop plants. A clear demand for improving the salinity tolerance of the major crop plants is imposed by the rapidly growing world population. This review summarizes the achievements of proteomic studies to elucidate the response mechanisms of selected model and crop plants to cope with salinity stress. We also aim at identifying research areas, which deserve increased attention in future proteome studies, as a prerequisite to identify novel targets for breeding strategies. Such areas include the impact of plant-microbial communities on the salinity tolerance of crops under field conditions, the importance of hormone signaling in abiotic stress tolerance, and the significance of control mechanisms underlying the observed changes in the proteome patterns. We briefly highlight the impact of novel tools for future proteome studies and argue for the use of integrated approaches. The evaluation of genetic resources by means of novel automated phenotyping facilities will have a large impact on the application of proteomics especially in combination with metabolomics or transcriptomics. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

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.

Enhancing Bottom-up and Top-down Proteomic Measurements with Ion Mobility Separations

DOE PAGES

Baker, Erin Shammel; Burnum-Johnson, Kristin E.; Ibrahim, Yehia M.; ...

2015-07-03

Proteomic measurements with greater throughput, sensitivity and additional structural information enhance the in-depth characterization of complex mixtures and targeted studies with additional information and higher confidence. While liquid chromatography separation coupled with mass spectrometry (LC-MS) measurements have provided information on thousands of proteins in different sample types, the additional of another rapid separation stage providing structural information has many benefits for analyses. Technical advances in ion funnels and multiplexing have enabled ion mobility separations to be easily and effectively coupled with LC-MS proteomics to enhance the information content of measurements. Finally, herein, we report on applications illustrating increased sensitivity, throughput,more » and structural information by utilizing IMS-MS and LC-IMS-MS measurements for both bottom-up and top-down proteomics measurements.« less

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.

Genomic and Epigenomic Alterations in Cancer.

PubMed

Chakravarthi, Balabhadrapatruni V S K; Nepal, Saroj; Varambally, Sooryanarayana

2016-07-01

Multiple genetic and epigenetic events characterize tumor progression and define the identity of the tumors. Advances in high-throughput technologies, like gene expression profiling, next-generation sequencing, proteomics, and metabolomics, have enabled detailed molecular characterization of various tumors. The integration and analyses of these high-throughput data have unraveled many novel molecular aberrations and network alterations in tumors. These molecular alterations include multiple cancer-driving mutations, gene fusions, amplification, deletion, and post-translational modifications, among others. Many of these genomic events are being used in cancer diagnosis, whereas others are therapeutically targeted with small-molecule inhibitors. Multiple genes/enzymes that play a role in DNA and histone modifications are also altered in various cancers, changing the epigenomic landscape during cancer initiation and progression. Apart from protein-coding genes, studies are uncovering the critical regulatory roles played by noncoding RNAs and noncoding regions of the genome during cancer progression. Many of these genomic and epigenetic events function in tandem to drive tumor development and metastasis. Concurrent advances in genome-modulating technologies, like gene silencing and genome editing, are providing ability to understand in detail the process of cancer initiation, progression, and signaling as well as opening up avenues for therapeutic targeting. In this review, we discuss some of the recent advances in cancer genomic and epigenomic research. Copyright © 2016 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Mass Spectrometry Data Collection in Parallel at Multiple Core Facilities Operating TripleTOF 5600 and Orbitrap Elite/Velos Pro/Q Exactive Mass Spectrometers

PubMed Central

Jones, K.; Kim, K.; Patel, B.; Kelsen, S.; Braverman, A.; Swinton, D.; Gafken, P.; Jones, L.; Lane, W.; Neveu, J.; Leung, H.; Shaffer, S.; Leszyk, J.; Stanley, B.; Fox, T.; Stanley, A.; Yeung, Anthony

2013-01-01

Proteomic research can benefit from simultaneous access to multiple cutting-edge mass spectrometers. 18 core facilities responded to our investigators seeking service through the ABRF Discussion Forum. Five of the facilities selected completed four plasma proteomics experiments as routine fee-for-service. Each biological experiment entailed an iTRAQ 4-plex proteome comparison of immunodepleted plasma provided as 30 labeled-peptide fractions. Identical samples were analyzed by two AB SCIEX TripleTOF 5600 and three Thermo Orbitrap (Elite/Velos Pro/Q Exactive) instruments. 480 LC-MS/MS runs delivered >250 GB of data over two months. We compare herein routine service analyses of three peptide fractions of different peptide abundance. Data files from each instrument were studied to develop optimal analysis parameters to compare with default parameters in Mascot Distiller 2.4, ProteinPilot 4.5 beta, AB Sciex MS Data Converter 1.3 beta, and Proteome Discover 1.3. Peak-picking for TripleTOFs was best by ProteinPilot 4.5 beta while Mascot Distiller and Proteome Discoverer were comparable for the Orbitraps. We compared protein identification and quantitation in SwissProt 2012_07 database by Mascot Server 2.4.01 versus ProteinPilot. By all search methods, more proteins, up to two fold, were identified using the Q Exactive than others. Q Exactive excelled also at the number of unique significant peptide ion sequences. However, software-dependent impact on subsequent interpretation, due to peptide modifications, can be critical. These findings may have special implications for iTRAQ plasma proteomics. For the low abundance peptide ions, the slope of the dynamic range drop-off in the plasma proteome is uniquely sharp compared with cell lysates. Our study provides data for testable improvements in the operation of these mass spectrometers. More importantly, we have demonstrated a new affordable expedient workflow for investigators to perform proteomic experiments through the ABRF infrastructure. (We acknowledge John Cottrell for optimizing the peak-picking parameters for Mascot Distiller).

Carfilzomib resistance due to ABCB1/MDR1 overexpression is overcome by nelfinavir and lopinavir in multiple myeloma

PubMed Central

Besse, A; Stolze, S C; Rasche, L; Weinhold, N; Morgan, G J; Kraus, M; Bader, J; Overkleeft, H S; Besse, L; Driessen, C

2018-01-01

Proteasome inhibitor (PI) carfilzomib (CFZ) has activity superior to bortezomib (BTZ) and is increasingly incorporated in multiple myeloma (MM) frontline therapy and relapsed settings. Most MM patients ultimately experience PI-refractory disease, an unmet medical need with poorly understood biology and dismal outcome. Pharmacologic targeting of ABCB1 improved patient outcomes, including MM, but suffered from adverse drug effects and insufficient plasma concentrations. Proteomics analysis identified ABCB1 overexpression as the most significant change in CFZ-resistant MM cells. We addressed the functional role of ABCB1 overexpression in MM and observed significantly upregulated ABCB1 in peripheral blood malignant plasma cells (PCs) vs untreated patients’ bone marrow PC. ABCB1 overexpression reduces the proteasome-inhibiting activity of CFZ due to drug efflux, in contrast to BTZ. Likewise, the cytotoxicity of established anti-MM drugs was significantly reduced in ABCB1-expressing MM cells. In search for potential drugs targeting ABCB1 in clinical trials, we identified the HIV protease inhibitors nelfinavir (NFV) and lopinavir (LPV) as potent functional modulators of ABCB1-mediated drug export, most likely via modulation of mitochondria permeability transition pore. NFV and LPV restored CFZ activity at therapeutically relevant drug levels and thus represent ready-to-use drugs to be tested in clinical trials to target ABCB1 and to re-sensitize PC to established myeloma drugs, in particular CFZ. PMID:28676669

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.

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

Hepatic Proteomic Analysis Revealed Altered Metabolic Pathways in Insulin Resistant Akt1+/-/Akt2-/-Mice

PubMed Central

Pedersen, Brian A; Wang, Weiwen; Taylor, Jared F; Khattab, Omar S; Chen, Yu-Han; Edwards, Robert A; Yazdi, Puya G; Wang, Ping H

2015-01-01

Objective The aim of this study was to identify liver proteome changes in a mouse model of severe insulin resistance and markedly decreased leptin levels. Methods Two-dimensional differential gel electrophoresis was utilized to identify liver proteome changes in AKT1+/-/AKT2-/- mice. Proteins with altered levels were identified with tandem mass spectrometry. Ingenuity Pathway analysis was performed for the interpretation of the biological significance of the observed proteomic changes. Results 11 proteins were identified from 2 biological replicates to be differentially expressed by a ratio of at least 1.3 between age-matched insulin resistant (Akt1+/-/Akt2-/-) and wild type mice. Albumin and mitochondrial ornithine aminotransferase were detected from multiple spots, which suggest post-translational modifications. Enzymes of the urea cycle were common members of top regulated pathways. Conclusion Our results help to unveil the regulation of the liver proteome underlying altered metabolism in an animal model of severe insulin resistance. PMID:26455965

Proteomic analysis of formalin-fixed paraffin embedded tissue by MALDI imaging mass spectrometry

PubMed Central

Casadonte, Rita; Caprioli, Richard M

2012-01-01

Archived formalin-fixed paraffin-embedded (FFPE) tissue collections represent a valuable informational resource for proteomic studies. Multiple FFPE core biopsies can be assembled in a single block to form tissue microarrays (TMAs). We describe a protocol for analyzing protein in FFPE -TMAs using matrix-assisted laser desorption/ionization (MAL DI) imaging mass spectrometry (IMS). The workflow incorporates an antigen retrieval step following deparaffinization, in situ trypsin digestion, matrix application and then mass spectrometry signal acquisition. The direct analysis of FFPE -TMA tissue using IMS allows direct analysis of multiple tissue samples in a single experiment without extraction and purification of proteins. The advantages of high speed and throughput, easy sample handling and excellent reproducibility make this technology a favorable approach for the proteomic analysis of clinical research cohorts with large sample numbers. For example, TMA analysis of 300 FFPE cores would typically require 6 h of total time through data acquisition, not including data analysis. PMID:22011652

Multiplexed and scalable super-resolution imaging of three-dimensional protein localization in size-adjustable tissues.

PubMed

Ku, Taeyun; Swaney, Justin; Park, Jeong-Yoon; Albanese, Alexandre; Murray, Evan; Cho, Jae Hun; Park, Young-Gyun; Mangena, Vamsi; Chen, Jiapei; Chung, Kwanghun

2016-09-01

The biology of multicellular organisms is coordinated across multiple size scales, from the subnanoscale of molecules to the macroscale, tissue-wide interconnectivity of cell populations. Here we introduce a method for super-resolution imaging of the multiscale organization of intact tissues. The method, called magnified analysis of the proteome (MAP), linearly expands entire organs fourfold while preserving their overall architecture and three-dimensional proteome organization. MAP is based on the observation that preventing crosslinking within and between endogenous proteins during hydrogel-tissue hybridization allows for natural expansion upon protein denaturation and dissociation. The expanded tissue preserves its protein content, its fine subcellular details, and its organ-scale intercellular connectivity. We use off-the-shelf antibodies for multiple rounds of immunolabeling and imaging of a tissue's magnified proteome, and our experiments demonstrate a success rate of 82% (100/122 antibodies tested). We show that specimen size can be reversibly modulated to image both inter-regional connections and fine synaptic architectures in the mouse brain.

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.

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

Cell- and Tissue-based Proteome Profiling and Bioimaging with the Probes Derived from a Potent AXL Kinase Inhibitor.

PubMed

Li, Zhengqiu; Zheng, Binbin; Guo, Haijun; Xu, Jiaqian; Ma, Nan; Ni, Yun; Li, Lin; Hao, Piliang; Ding, Ke

2018-06-25

AXL has been defined as a novel target for cancer therapeutics. However, only a few potent and selective inhibitors targeting AXL are available to date. Our group has developed a lead compound, 9im, capable of excellent inhibition against AXL. With the aim of understanding its cellular and tissue mechanism of actions and direct subsequent structure optimization, a study on competitive affinity-based proteome profiling and bioimaging was carried out. A series of unknown cellular and tissue targets, including RYK, PCK, ATP1A3, EIF4A, Ptprn and Cox5b were discovered. In addition, trans-cyclooctene (TCO) and acedan-containing probes were developed to image the binding between 9im and its target proteins inside live cells and tumor tissues. These probes would be useful tools in the detection of expression and activity of AXL. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Covalent inhibitors: an opportunity for rational target selectivity.

PubMed

Lagoutte, Roman; Patouret, Remi; Winssinger, Nicolas

2017-08-01

There is a resurging interest in compounds that engage their target through covalent interactions. Cysteine's thiol is endowed with enhanced reactivity, making it the nucleophile of choice for covalent engagement with a ligand aligning an electrophilic trap with a cysteine residue in a target of interest. The paucity of cysteine in the proteome coupled to the fact that closely related proteins do not necessarily share a given cysteine residue enable a level of unprecedented rational target selectivity. The recent demonstration that a lysine's amine can also be engaged covalently with a mild electrophile extends the potential of covalent inhibitors. The growing database of protein structures facilitates the discovery of covalent inhibitors while the advent of proteomic technologies enables a finer resolution in the selectivity of covalently engaged proteins. Here, we discuss recent examples of discovery and design of covalent inhibitors. Copyright © 2017 Elsevier Ltd. All rights reserved.

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 in the highly curated Ingenuity Pathway database. We provide a first global overview on how WA kills multiple myeloma cancer cells and serve as a starting point for further in depth experiments. Furthermore, the combined approach can be used for other types of cancer and/or other promising multifunctional compounds, thereby increasing the potential development of new antitumor therapies. Copyright © 2018 Elsevier B.V. All rights reserved.

A compound-based proteomic approach discloses 15-ketoatractyligenin methyl ester as a new PPARγ partial agonist with anti-proliferative ability

NASA Astrophysics Data System (ADS)

Vasaturo, Michele; Fiengo, Lorenzo; de Tommasi, Nunziatina; Sabatino, Lina; Ziccardi, Pamela; Colantuoni, Vittorio; Bruno, Maurizio; Cerchia, Carmen; Novellino, Ettore; Lupo, Angelo; Lavecchia, Antonio; Piaz, Fabrizio Dal

2017-01-01

Proteomics based approaches are emerging as useful tools to identify the targets of bioactive compounds and elucidate their molecular mechanisms of action. Here, we applied a chemical proteomic strategy to identify the peroxisome proliferator-activated receptor γ (PPARγ) as a molecular target of the pro-apoptotic agent 15-ketoatractyligenin methyl ester (compound 1). We demonstrated that compound 1 interacts with PPARγ, forms a covalent bond with the thiol group of C285 and occupies the sub-pocket between helix H3 and the β-sheet of the ligand-binding domain (LBD) of the receptor by Surface Plasmon Resonance (SPR), mass spectrometry-based studies and docking experiments. 1 displayed partial agonism of PPARγ in cell-based transactivation assays and was found to inhibit the AKT pathway, as well as its downstream targets. Consistently, a selective PPARγ antagonist (GW9662) greatly reduced the anti-proliferative and pro-apoptotic effects of 1, providing the molecular basis of its action. Collectively, we identified 1 as a novel PPARγ partial agonist and elucidated its mode of action, paving the way for therapeutic strategies aimed at tailoring novel PPARγ ligands with reduced undesired harmful side effects.

A compound-based proteomic approach discloses 15-ketoatractyligenin methyl ester as a new PPARγ partial agonist with anti-proliferative ability

PubMed Central

Vasaturo, Michele; Fiengo, Lorenzo; De Tommasi, Nunziatina; Sabatino, Lina; Ziccardi, Pamela; Colantuoni, Vittorio; Bruno, Maurizio; Cerchia, Carmen; Novellino, Ettore; Lupo, Angelo; Lavecchia, Antonio; Piaz, Fabrizio Dal

2017-01-01

Proteomics based approaches are emerging as useful tools to identify the targets of bioactive compounds and elucidate their molecular mechanisms of action. Here, we applied a chemical proteomic strategy to identify the peroxisome proliferator-activated receptor γ (PPARγ) as a molecular target of the pro-apoptotic agent 15-ketoatractyligenin methyl ester (compound 1). We demonstrated that compound 1 interacts with PPARγ, forms a covalent bond with the thiol group of C285 and occupies the sub-pocket between helix H3 and the β-sheet of the ligand-binding domain (LBD) of the receptor by Surface Plasmon Resonance (SPR), mass spectrometry-based studies and docking experiments. 1 displayed partial agonism of PPARγ in cell-based transactivation assays and was found to inhibit the AKT pathway, as well as its downstream targets. Consistently, a selective PPARγ antagonist (GW9662) greatly reduced the anti-proliferative and pro-apoptotic effects of 1, providing the molecular basis of its action. Collectively, we identified 1 as a novel PPARγ partial agonist and elucidated its mode of action, paving the way for therapeutic strategies aimed at tailoring novel PPARγ ligands with reduced undesired harmful side effects. PMID:28117438

A compound-based proteomic approach discloses 15-ketoatractyligenin methyl ester as a new PPARγ partial agonist with anti-proliferative ability.

PubMed

Vasaturo, Michele; Fiengo, Lorenzo; De Tommasi, Nunziatina; Sabatino, Lina; Ziccardi, Pamela; Colantuoni, Vittorio; Bruno, Maurizio; Cerchia, Carmen; Novellino, Ettore; Lupo, Angelo; Lavecchia, Antonio; Piaz, Fabrizio Dal

2017-01-24

Proteomics based approaches are emerging as useful tools to identify the targets of bioactive compounds and elucidate their molecular mechanisms of action. Here, we applied a chemical proteomic strategy to identify the peroxisome proliferator-activated receptor γ (PPARγ) as a molecular target of the pro-apoptotic agent 15-ketoatractyligenin methyl ester (compound 1). We demonstrated that compound 1 interacts with PPARγ, forms a covalent bond with the thiol group of C285 and occupies the sub-pocket between helix H3 and the β-sheet of the ligand-binding domain (LBD) of the receptor by Surface Plasmon Resonance (SPR), mass spectrometry-based studies and docking experiments. 1 displayed partial agonism of PPARγ in cell-based transactivation assays and was found to inhibit the AKT pathway, as well as its downstream targets. Consistently, a selective PPARγ antagonist (GW9662) greatly reduced the anti-proliferative and pro-apoptotic effects of 1, providing the molecular basis of its action. Collectively, we identified 1 as a novel PPARγ partial agonist and elucidated its mode of action, paving the way for therapeutic strategies aimed at tailoring novel PPARγ ligands with reduced undesired harmful side effects.

Changes in the striatal proteome of YAC128Q mice exhibit gene-environment interactions between mutant huntingtin and manganese.

PubMed

Wegrzynowicz, Michal; Holt, Hunter K; Friedman, David B; Bowman, Aaron B

2012-02-03

Huntington's disease (HD) is a neurodegenerative disorder caused by expansion of a CAG repeat within the Huntingtin (HTT) gene, though the clinical presentation of disease and age-of-onset are strongly influenced by ill-defined environmental factors. We recently reported a gene-environment interaction wherein expression of mutant HTT is associated with neuroprotection against manganese (Mn) toxicity. Here, we are testing the hypothesis that this interaction may be manifested by altered protein expression patterns in striatum, a primary target of both neurodegeneration in HD and neurotoxicity of Mn. To this end, we compared striatal proteomes of wild-type and HD (YAC128Q) mice exposed to vehicle or Mn. Principal component analysis of proteomic data revealed that Mn exposure disrupted a segregation of WT versus mutant proteomes by the major principal component observed in vehicle-exposed mice. Identification of altered proteins revealed novel markers of Mn toxicity, particularly proteins involved in glycolysis, excitotoxicity, and cytoskeletal dynamics. In addition, YAC128Q-dependent changes suggest that axonal pathology may be an early feature in HD pathogenesis. Finally, for several proteins, genotype-specific responses to Mn were observed. These differences include increased sensitivity to exposure in YAC128Q mice (UBQLN1) and amelioration of some mutant HTT-induced alterations (SAE1, ENO1). We conclude that the interaction of Mn and mutant HTT may suppress proteomic phenotypes of YAC128Q mice, which could reveal potential targets in novel treatment strategies for HD.

A Routine 'Top-Down' Approach to Analysis of the Human Serum Proteome.

PubMed

D'Silva, Arlene M; Hyett, Jon A; Coorssen, Jens R

2017-06-06

Serum provides a rich source of potential biomarker proteoforms. One of the major obstacles in analysing serum proteomes is detecting lower abundance proteins owing to the presence of hyper-abundant species (e.g., serum albumin and immunoglobulins). Although depletion methods have been used to address this, these can lead to the concomitant removal of non-targeted protein species, and thus raise issues of specificity, reproducibility, and the capacity for meaningful quantitative analyses. Altering the native stoichiometry of the proteome components may thus yield a more complex series of issues than dealing directly with the inherent complexity of the sample. Hence, here we targeted method refinements so as to ensure optimum resolution of serum proteomes via a top down two-dimensional gel electrophoresis (2DE) approach that enables the routine assessment of proteoforms and is fully compatible with subsequent mass spectrometric analyses. Testing included various fractionation and non-fractionation approaches. The data show that resolving 500 µg protein on 17 cm 3-10 non-linear immobilised pH gradient strips in the first dimension followed by second dimension resolution on 7-20% gradient gels with a combination of lithium dodecyl sulfate (LDS) and sodium dodecyl sulfate (SDS) detergents markedly improves the resolution and detection of proteoforms in serum. In addition, well established third dimension electrophoretic separations in combination with deep imaging further contributed to the best available resolution, detection, and thus quantitative top-down analysis of serum proteomes.

Proteomic identification of fat-browning markers in cultured white adipocytes treated with curcumin.

PubMed

Kim, Sang Woo; Choi, Jae Heon; Mukherjee, Rajib; Hwang, Ki-Chul; Yun, Jong Won

2016-04-01

We previously reported that curcumin induces browning of primary white adipocytes via enhanced expression of brown adipocyte-specific genes. In this study, we attempted to identify target proteins responsible for this fat-browning effect by analyzing proteomic changes in cultured white adipocytes in response to curcumin treatment. To elucidate the role of curcumin in fat-browning, we conducted comparative proteomic analysis of primary adipocytes between control and curcumin-treated cells using two-dimensional electrophoresis combined with MALDI-TOF-MS. We also investigated fatty acid metabolic targets, mitochondrial biogenesis, and fat-browning-associated proteins using combined proteomic and network analyses. Proteomic analysis revealed that 58 protein spots from a total of 325 matched spots showed differential expression between control and curcumin-treated adipocytes. Using network analysis, most of the identified proteins were proven to be involved in various metabolic and cellular processes based on the PANTHER classification system. One of the most striking findings is that hormone-sensitive lipase (HSL) was highly correlated with main browning markers based on the STRING database. HSL and two browning markers (UCP1, PGC-1α) were co-immunoprecipitated with these markers, suggesting that HSL possibly plays a role in fat-browning of white adipocytes. Our results suggest that curcumin increased HSL levels and other browning-specific markers, suggesting its possible role in augmentation of lipolysis and suppression of lipogenesis by trans-differentiation from white adipocytes into brown adipocytes (beige).

A complete mass spectrometric map for the analysis of the yeast proteome and its application to quantitative trait analysis

PubMed Central

Picotti, Paola; Clement-Ziza, Mathieu; Lam, Henry; Campbell, David S.; Schmidt, Alexander; Deutsch, Eric W.; Röst, Hannes; Sun, Zhi; Rinner, Oliver; Reiter, Lukas; Shen, Qin; Michaelson, Jacob J.; Frei, Andreas; Alberti, Simon; Kusebauch, Ulrike; Wollscheid, Bernd; Moritz, Robert; Beyer, Andreas; Aebersold, Ruedi

2013-01-01

Complete reference maps or datasets, like the genomic map of an organism, are highly beneficial tools for biological and biomedical research. Attempts to generate such reference datasets for a proteome so far failed to reach complete proteome coverage, with saturation apparent at approximately two thirds of the proteomes tested, even for the most thoroughly characterized proteomes. Here, we used a strategy based on high-throughput peptide synthesis and mass spectrometry to generate a close to complete reference map (97% of the genome-predicted proteins) of the S. cerevisiae proteome. We generated two versions of this mass spectrometric map one supporting discovery- (shotgun) and the other hypothesis-driven (targeted) proteomic measurements. The two versions of the map, therefore, constitute a complete set of proteomic assays to support most studies performed with contemporary proteomic technologies. The reference libraries can be browsed via a web-based repository and associated navigation tools. To demonstrate the utility of the reference libraries we applied them to a protein quantitative trait locus (pQTL) analysis, which requires measurement of the same peptides over a large number of samples with high precision. Protein measurements over a set of 78 S. cerevisiae strains revealed a complex relationship between independent genetic loci, impacting on the levels of related proteins. Our results suggest that selective pressure favors the acquisition of sets of polymorphisms that maintain the stoichiometry of protein complexes and pathways. PMID:23334424

A Global Protein Kinase and Phosphatase Interaction Network in Yeast

PubMed Central

Breitkreutz, Ashton; Choi, Hyungwon; Sharom, Jeffrey R.; Boucher, Lorrie; Neduva, Victor; Larsen, Brett; Lin, Zhen-Yuan; Breitkreutz, Bobby-Joe; Stark, Chris; Liu, Guomin; Ahn, Jessica; Dewar-Darch, Danielle; Reguly, Teresa; Tang, Xiaojing; Almeida, Ricardo; Qin, Zhaohui Steve; Pawson, Tony; Gingras, Anne-Claude; Nesvizhskii, Alexey I.; Tyers, Mike

2011-01-01

The interactions of protein kinases and phosphatases with their regulatory subunits and substrates underpin cellular regulation. We identified a kinase and phosphatase interaction (KPI) network of 1844 interactions in budding yeast by mass spectrometric analysis of protein complexes. The KPI network contained many dense local regions of interactions that suggested new functions. Notably, the cell cycle phosphatase Cdc14 associated with multiple kinases that revealed roles for Cdc14 in mitogen-activated protein kinase signaling, the DNA damage response, and metabolism, whereas interactions of the target of rapamycin complex 1 (TORC1) uncovered new effector kinases in nitrogen and carbon metabolism. An extensive backbone of kinase-kinase interactions cross-connects the proteome and may serve to coordinate diverse cellular responses. PMID:20489023

Neurobiological Signatures of Alcohol Dependence Revealed by Protein Profiling

PubMed Central

Gorini, Giorgio; Roberts, Amanda J.; Mayfield, R. Dayne

2013-01-01

Alcohol abuse causes dramatic neuroadaptations in the brain, which contribute to tolerance, dependence, and behavioral modifications. Previous proteomic studies in human alcoholics and animal models have identified candidate alcoholism-related proteins. However, recent evidences suggest that alcohol dependence is caused by changes in co-regulation that are invisible to single protein-based analysis. Here, we analyze global proteomics data to integrate differential expression, co-expression networks, and gene annotations to unveil key neurobiological rearrangements associated with the transition to alcohol dependence modeled by a Chronic Intermittent Ethanol (CIE), two-bottle choice (2BC) paradigm. We analyzed cerebral cortices (CTX) and midbrains (MB) from male C57BL/6J mice subjected to a CIE, 2BC paradigm, which induces heavy drinking and represents one of the best available animal models for alcohol dependence and relapse drinking. CIE induced significant changes in protein levels in dependent mice compared with their non-dependent controls. Multiple protein isoforms showed region-specific differential regulation as a result of post-translational modifications. Our integrative analysis identified modules of co-expressed proteins that were highly correlated with CIE treatment. We found that modules most related to the effects of CIE treatment coordinate molecular imbalances in endocytic- and energy-related pathways, with specific proteins involved, such as dynamin-1. The qRT-PCR experiments validated both differential and co-expression analyses, and the correspondence among our data and previous genomic and proteomic studies in humans and rodents substantiates our findings. The changes identified above may play a key role in the escalation of ethanol consumption associated with dependence. Our approach to alcohol addiction will advance knowledge of brain remodeling mechanisms and adaptive changes in response to drug abuse, contribute to understanding of organizational principles of CTX and MB proteomes, and define potential new molecular targets for treating alcohol addiction. The integrative analysis employed here highlight the advantages of systems approaches in studying the neurobiology of alcohol addiction. PMID:24358215

Differential Proteomic Analysis of Noncardia Gastric Cancer from Individuals of Northern Brazil

PubMed Central

Leal, Mariana Ferreira; Chung, Janete; Calcagno, Danielle Queiroz; Assumpção, Paulo Pimentel; Demachki, Samia; da Silva, Ismael Dale Cotrim Guerreiro; Chammas, Roger; Burbano, Rommel Rodríguez; de Arruda Cardoso Smith, Marília

2012-01-01

Gastric cancer is the second leading cause of cancer-related death worldwide. The identification of new cancer biomarkers is necessary to reduce the mortality rates through the development of new screening assays and early diagnosis, as well as new target therapies. In this study, we performed a proteomic analysis of noncardia gastric neoplasias of individuals from Northern Brazil. The proteins were analyzed by two-dimensional electrophoresis and mass spectrometry. For the identification of differentially expressed proteins, we used statistical tests with bootstrapping resampling to control the type I error in the multiple comparison analyses. We identified 111 proteins involved in gastric carcinogenesis. The computational analysis revealed several proteins involved in the energy production processes and reinforced the Warburg effect in gastric cancer. ENO1 and HSPB1 expression were further evaluated. ENO1 was selected due to its role in aerobic glycolysis that may contribute to the Warburg effect. Although we observed two up-regulated spots of ENO1 in the proteomic analysis, the mean expression of ENO1 was reduced in gastric tumors by western blot. However, mean ENO1 expression seems to increase in more invasive tumors. This lack of correlation between proteomic and western blot analyses may be due to the presence of other ENO1 spots that present a slightly reduced expression, but with a high impact in the mean protein expression. In neoplasias, HSPB1 is induced by cellular stress to protect cells against apoptosis. In the present study, HSPB1 presented an elevated protein and mRNA expression in a subset of gastric cancer samples. However, no association was observed between HSPB1 expression and clinicopathological characteristics. Here, we identified several possible biomarkers of gastric cancer in individuals from Northern Brazil. These biomarkers may be useful for the assessment of prognosis and stratification for therapy if validated in larger clinical study sets. PMID:22860099

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 researchers are working on novel bioinformatics techniques to address these issues and increase the reproducibility, fidelity, and identification breadth of DIA.

An Informatics-assisted Label-free Approach for Personalized Tissue Membrane Proteomics: Case Study on Colorectal Cancer*

PubMed Central

Han, Chia-Li; Chen, Jinn-Shiun; Chan, Err-Cheng; Wu, Chien-Peng; Yu, Kun-Hsing; Chen, Kuei-Tien; Tsou, Chih-Chiang; Tsai, Chia-Feng; Chien, Chih-Wei; Kuo, Yung-Bin; Lin, Pei-Yi; Yu, Jau-Song; Hsueh, Chuen; Chen, Min-Chi; Chan, Chung-Chuan; Chang, Yu-Sun; Chen, Yu-Ju

2011-01-01

We developed a multiplexed label-free quantification strategy, which integrates an efficient gel-assisted digestion protocol, high-performance liquid chromatography tandem MS analysis, and a bioinformatics alignment method to determine personalized proteomic profiles for membrane proteins in human tissues. This strategy provided accurate (6% error) and reproducible (34% relative S.D.) quantification of three independently purified membrane fractions from the same human colorectal cancer (CRC) tissue. Using CRC as a model, we constructed the personalized membrane protein atlas of paired tumor and adjacent normal tissues from 28 patients with different stages of CRC. Without fractionation, this strategy confidently quantified 856 proteins (≥2 unique peptides) across different patients, including the first and robust detection (Mascot score: 22,074) of the well-documented CRC marker, carcinoembryonic antigen 5 by a discovery-type proteomics approach. Further validation of a panel of proteins, annexin A4, neutrophils defensin A1, and claudin 3, confirmed differential expression levels and high occurrences (48–70%) in 60 CRC patients. The most significant discovery is the overexpression of stomatin-like 2 (STOML2) for early diagnostic and prognostic potential. Increased expression of STOML2 was associated with decreased CRC-related survival; the mean survival period was 34.77 ± 2.03 months in patients with high STOML2 expression, whereas 53.67 ± 3.46 months was obtained for patients with low STOML2 expression. Further analysis by ELISA verified that plasma concentrations of STOML2 in early-stage CRC patients were elevated as compared with those of healthy individuals (p < 0.001), suggesting that STOML2 may be a noninvasive serological biomarker for early CRC diagnosis. The overall sensitivity of STOML2 for CRC detection was 71%, which increased to 87% when combined with CEA measurements. This study demonstrated a sensitive, label-free strategy for differential analysis of tissue membrane proteome, which may provide a roadmap for the subsequent identification of molecular target candidates of multiple cancer types. PMID:21209152

Proteomic Analysis of ABCA1-Null Macrophages Reveals a Role for Stomatin-Like Protein-2 in Raft Composition and Toll-Like Receptor Signaling.

PubMed

Chowdhury, Saiful M; Zhu, Xuewei; Aloor, Jim J; Azzam, Kathleen M; Gabor, Kristin A; Ge, William; Addo, Kezia A; Tomer, Kenneth B; Parks, John S; Fessler, Michael B

2015-07-01

Lipid raft membrane microdomains organize signaling by many prototypical receptors, including the Toll-like receptors (TLRs) of the innate immune system. Raft-localization of proteins is widely thought to be regulated by raft cholesterol levels, but this is largely on the basis of studies that have manipulated cell cholesterol using crude and poorly specific chemical tools, such as β-cyclodextrins. To date, there has been no proteome-scale investigation of whether endogenous regulators of intracellular cholesterol trafficking, such as the ATP binding cassette (ABC)A1 lipid efflux transporter, regulate targeting of proteins to rafts. Abca1(-/-) macrophages have cholesterol-laden rafts that have been reported to contain increased levels of select proteins, including TLR4, the lipopolysaccharide receptor. Here, using quantitative proteomic profiling, we identified 383 proteins in raft isolates from Abca1(+/+) and Abca1(-/-) macrophages. ABCA1 deletion induced wide-ranging changes to the raft proteome. Remarkably, many of these changes were similar to those seen in Abca1(+/+) macrophages after lipopolysaccharide exposure. Stomatin-like protein (SLP)-2, a member of the stomatin-prohibitin-flotillin-HflK/C family of membrane scaffolding proteins, was robustly and specifically increased in Abca1(-/-) rafts. Pursuing SLP-2 function, we found that rafts of SLP-2-silenced macrophages had markedly abnormal composition. SLP-2 silencing did not compromise ABCA1-dependent cholesterol efflux but reduced macrophage responsiveness to multiple TLR ligands. This was associated with reduced raft levels of the TLR co-receptor, CD14, and defective lipopolysaccharide-induced recruitment of the common TLR adaptor, MyD88, to rafts. Taken together, we show that the lipid transporter ABCA1 regulates the protein repertoire of rafts and identify SLP-2 as an ABCA1-dependent regulator of raft composition and of the innate immune response. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Proteomic Analysis of ABCA1-Null Macrophages Reveals a Role for Stomatin-Like Protein-2 in Raft Composition and Toll-Like Receptor Signaling*

PubMed Central

Chowdhury, Saiful M.; Zhu, Xuewei; Aloor, Jim J.; Azzam, Kathleen M.; Gabor, Kristin A.; Ge, William; Addo, Kezia A.; Tomer, Kenneth B.; Parks, John S.; Fessler, Michael B.

2015-01-01

Lipid raft membrane microdomains organize signaling by many prototypical receptors, including the Toll-like receptors (TLRs) of the innate immune system. Raft-localization of proteins is widely thought to be regulated by raft cholesterol levels, but this is largely on the basis of studies that have manipulated cell cholesterol using crude and poorly specific chemical tools, such as β-cyclodextrins. To date, there has been no proteome-scale investigation of whether endogenous regulators of intracellular cholesterol trafficking, such as the ATP binding cassette (ABC)A1 lipid efflux transporter, regulate targeting of proteins to rafts. Abca1−/− macrophages have cholesterol-laden rafts that have been reported to contain increased levels of select proteins, including TLR4, the lipopolysaccharide receptor. Here, using quantitative proteomic profiling, we identified 383 proteins in raft isolates from Abca1+/+ and Abca1−/− macrophages. ABCA1 deletion induced wide-ranging changes to the raft proteome. Remarkably, many of these changes were similar to those seen in Abca1+/+ macrophages after lipopolysaccharide exposure. Stomatin-like protein (SLP)-2, a member of the stomatin-prohibitin-flotillin-HflK/C family of membrane scaffolding proteins, was robustly and specifically increased in Abca1−/− rafts. Pursuing SLP-2 function, we found that rafts of SLP-2-silenced macrophages had markedly abnormal composition. SLP-2 silencing did not compromise ABCA1-dependent cholesterol efflux but reduced macrophage responsiveness to multiple TLR ligands. This was associated with reduced raft levels of the TLR co-receptor, CD14, and defective lipopolysaccharide-induced recruitment of the common TLR adaptor, MyD88, to rafts. Taken together, we show that the lipid transporter ABCA1 regulates the protein repertoire of rafts and identify SLP-2 as an ABCA1-dependent regulator of raft composition and of the innate immune response. PMID:25910759

FINDSITE-metal: Integrating evolutionary information and machine learning for structure-based metal binding site prediction at the proteome level

PubMed Central

Brylinski, Michal; Skolnick, Jeffrey

2010-01-01

The rapid accumulation of gene sequences, many of which are hypothetical proteins with unknown function, has stimulated the development of accurate computational tools for protein function prediction with evolution/structure-based approaches showing considerable promise. In this paper, we present FINDSITE-metal, a new threading-based method designed specifically to detect metal binding sites in modeled protein structures. Comprehensive benchmarks using different quality protein structures show that weakly homologous protein models provide sufficient structural information for quite accurate annotation by FINDSITE-metal. Combining structure/evolutionary information with machine learning results in highly accurate metal binding annotations; for protein models constructed by TASSER, whose average Cα RMSD from the native structure is 8.9 Å, 59.5% (71.9%) of the best of top five predicted metal locations are within 4 Å (8 Å) from a bound metal in the crystal structure. For most of the targets, multiple metal binding sites are detected with the best predicted binding site at rank 1 and within the top 2 ranks in 65.6% and 83.1% of the cases, respectively. Furthermore, for iron, copper, zinc, calcium and magnesium ions, the binding metal can be predicted with high, typically 70-90%, accuracy. FINDSITE-metal also provides a set of confidence indexes that help assess the reliability of predictions. Finally, we describe the proteome-wide application of FINDSITE-metal that quantifies the metal binding complement of the human proteome. FINDSITE-metal is freely available to the academic community at http://cssb.biology.gatech.edu/findsite-metal/. PMID:21287609

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

Validation of N-myristoyltransferase as an antimalarial drug target using an integrated chemical biology approach

NASA Astrophysics Data System (ADS)

Wright, Megan H.; Clough, Barbara; Rackham, Mark D.; Rangachari, Kaveri; Brannigan, James A.; Grainger, Munira; Moss, David K.; Bottrill, Andrew R.; Heal, William P.; Broncel, Malgorzata; Serwa, Remigiusz A.; Brady, Declan; Mann, David J.; Leatherbarrow, Robin J.; Tewari, Rita; Wilkinson, Anthony J.; Holder, Anthony A.; Tate, Edward W.

2014-02-01

Malaria is an infectious disease caused by parasites of the genus Plasmodium, which leads to approximately one million deaths per annum worldwide. Chemical validation of new antimalarial targets is urgently required in view of rising resistance to current drugs. One such putative target is the enzyme N-myristoyltransferase, which catalyses the attachment of the fatty acid myristate to protein substrates (N-myristoylation). Here, we report an integrated chemical biology approach to explore protein myristoylation in the major human parasite P. falciparum, combining chemical proteomic tools for identification of the myristoylated and glycosylphosphatidylinositol-anchored proteome with selective small-molecule N-myristoyltransferase inhibitors. We demonstrate that N-myristoyltransferase is an essential and chemically tractable target in malaria parasites both in vitro and in vivo, and show that selective inhibition of N-myristoylation leads to catastrophic and irreversible failure to assemble the inner membrane complex, a critical subcellular organelle in the parasite life cycle. Our studies provide the basis for the development of new antimalarials targeting N-myristoyltransferase.

[Proteomics and its application to determine mechanism of action of traditional Chinese medicine].

PubMed

Xin, Ping; Kuang, Hai-Xue; Li, Xiao-Liang; Wang, Yu; Zhang, Ben-Mei; Bu, He; Wang, Zhi-Bin; Meng, Yong-Hai; Wang, Yan-Hong; Wang, Qiu-Hong

2018-03-01

There is no doubt that the traditional Chinese medicine(TCM) is effective, practical and scientific after it was used for thousands of years. However, the mechanisms of action of many TCM are still unclear because of their multi-component, multi-target and multi-level features, which hinder the modernization and internationalization of the TCM. Proteomics is to analyze the composition and activity of intracellular proteins which are changing dynamically from a holistic perspective. It is consistent with the holistic and dynamic views of the TCM and brings about the hope of clarifying the mechanism of action of the TCM. In recent years, great progress has been made in the application of proteomics to determine the mechanism of the TCM. This article introduced the core technologies of proteomics and systematically summarized the applications of proteomics in the study of the mechanism of the Chinese medicinal formulae, single Chinese medicine and monomeric compounds from the TCM to provide innovative ideas and methods for reference. Copyright© by the Chinese Pharmaceutical Association.

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

Quantitative and Systems Pharmacology. 1. In Silico Prediction of Drug-Target Interactions of Natural Products Enables New Targeted Cancer Therapy.

PubMed

Fang, Jiansong; Wu, Zengrui; Cai, Chuipu; Wang, Qi; Tang, Yun; Cheng, Feixiong

2017-11-27

Natural products with diverse chemical scaffolds have been recognized as an invaluable source of compounds in drug discovery and development. However, systematic identification of drug targets for natural products at the human proteome level via various experimental assays is highly expensive and time-consuming. In this study, we proposed a systems pharmacology infrastructure to predict new drug targets and anticancer indications of natural products. Specifically, we reconstructed a global drug-target network with 7,314 interactions connecting 751 targets and 2,388 natural products and built predictive network models via a balanced substructure-drug-target network-based inference approach. A high area under receiver operating characteristic curve of 0.96 was yielded for predicting new targets of natural products during cross-validation. The newly predicted targets of natural products (e.g., resveratrol, genistein, and kaempferol) with high scores were validated by various literature studies. We further built the statistical network models for identification of new anticancer indications of natural products through integration of both experimentally validated and computationally predicted drug-target interactions of natural products with known cancer proteins. We showed that the significantly predicted anticancer indications of multiple natural products (e.g., naringenin, disulfiram, and metformin) with new mechanism-of-action were validated by various published experimental evidence. In summary, this study offers powerful computational systems pharmacology approaches and tools for the development of novel targeted cancer therapies by exploiting the polypharmacology of natural products.

NCI 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.

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

Automated selected reaction monitoring software for accurate label-free protein quantification.

PubMed

Teleman, Johan; Karlsson, Christofer; Waldemarson, Sofia; Hansson, Karin; James, Peter; Malmström, Johan; Levander, Fredrik

2012-07-06

Selected reaction monitoring (SRM) is a mass spectrometry method with documented ability to quantify proteins accurately and reproducibly using labeled reference peptides. However, the use of labeled reference peptides becomes impractical if large numbers of peptides are targeted and when high flexibility is desired when selecting peptides. We have developed a label-free quantitative SRM workflow that relies on a new automated algorithm, Anubis, for accurate peak detection. Anubis efficiently removes interfering signals from contaminating peptides to estimate the true signal of the targeted peptides. We evaluated the algorithm on a published multisite data set and achieved results in line with manual data analysis. In complex peptide mixtures from whole proteome digests of Streptococcus pyogenes we achieved a technical variability across the entire proteome abundance range of 6.5-19.2%, which was considerably below the total variation across biological samples. Our results show that the label-free SRM workflow with automated data analysis is feasible for large-scale biological studies, opening up new possibilities for quantitative proteomics and systems biology.

Global Reprogramming of Host SUMOylation during Influenza Virus Infection

PubMed Central

Domingues, Patricia; Golebiowski, Filip; Tatham, Michael H.; Lopes, Antonio M.; Taggart, Aislynn; Hay, Ronald T.; Hale, Benjamin G.

2015-01-01

Summary Dynamic nuclear SUMO modifications play essential roles in orchestrating cellular responses to proteotoxic stress, DNA damage, and DNA virus infection. Here, we describe a non-canonical host SUMOylation response to the nuclear-replicating RNA pathogen, influenza virus, and identify viral RNA polymerase activity as a major contributor to SUMO proteome remodeling. Using quantitative proteomics to compare stress-induced SUMOylation responses, we reveal that influenza virus infection triggers unique re-targeting of SUMO to 63 host proteins involved in transcription, mRNA processing, RNA quality control, and DNA damage repair. This is paralleled by widespread host deSUMOylation. Depletion screening identified ten virus-induced SUMO targets as potential antiviral factors, including C18orf25 and the SMC5/6 and PAF1 complexes. Mechanistic studies further uncovered a role for SUMOylation of the PAF1 complex component, parafibromin (CDC73), in potentiating antiviral gene expression. Our global characterization of influenza virus-triggered SUMO redistribution provides a proteomic resource to understand host nuclear SUMOylation responses to infection. PMID:26549460

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

Connecting Brain Proteomics with Behavioural Neuroscience in Translational Animal Models of Neuropsychiatric Disorders.

PubMed

Sarnyai, Zoltán; Guest, Paul C

2017-01-01

Modelling psychiatric disorders in animals has been hindered by several challenges related to our poor understanding of the disease causes. This chapter describes recent advances in translational research which may lead to animal models and relevant proteomic biomarkers that can be informative about disease mechanisms and potential new therapeutic targets. The review focuses on the behavioural and molecular correlates in models of schizophrenia and major depressive disorder, as guided by recently established Research Domain Criteria (RDoC). This approach is based on providing proteomic data for aetiologically driven, behaviourally well-characterised animal models to link discovered biomarker candidates with the human disease.

Recent advances in stable isotope labeling based techniques for proteome relative quantification.

PubMed

Zhou, Yuan; Shan, Yichu; Zhang, Lihua; Zhang, Yukui

2014-10-24

The large scale relative quantification of all proteins expressed in biological samples under different states is of great importance for discovering proteins with important biological functions, as well as screening disease related biomarkers and drug targets. Therefore, the accurate quantification of proteins at proteome level has become one of the key issues in protein science. Herein, the recent advances in stable isotope labeling based techniques for proteome relative quantification were reviewed, from the aspects of metabolic labeling, chemical labeling and enzyme-catalyzed labeling. Furthermore, the future research direction in this field was prospected. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

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

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.

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

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 RhoA proteins were the therapy targets of YQYYHTQY recipe. Copyright © 2018 Elsevier Ireland Ltd. All rights reserved.

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.

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.

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

Global analysis of the rat and human platelet proteome – the molecular blueprint for illustrating multi-functional platelets and cross-species function evolution

PubMed Central

Yu, Yanbao; Leng, Taohua; Yun, Dong; Liu, Na; Yao, Jun; Dai, Ying; Yang, Pengyuan; Chen, Xian

2013-01-01

Emerging evidences indicate that blood platelets function in multiple biological processes including immune response, bone metastasis and liver regeneration in addition to their known roles in hemostasis and thrombosis. Global elucidation of platelet proteome will provide the molecular base of these platelet functions. Here, we set up a high throughput platform for maximum exploration of the rat/human platelet proteome using integrated proteomics technologies, and then applied to identify the largest number of the proteins expressed in both rat and human platelets. After stringent statistical filtration, a total of 837 unique proteins matched with at least two unique peptides were precisely identified, making it the first comprehensive protein database so far for rat platelets. Meanwhile, quantitative analyses of the thrombin-stimulated platelets offered great insights into the biological functions of platelet proteins and therefore confirmed our global profiling data. A comparative proteomic analysis between rat and human platelets was also conducted, which revealed not only a significant similarity, but also an across-species evolutionary link that the orthologous proteins representing ‘core proteome’, and the ‘evolutionary proteome’ is actually a relatively static proteome. PMID:20443191

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

Comparative Proteomic Profiling Reveals Molecular Characteristics Associated with Oogenesis and Oocyte Maturation during Ovarian Development of Bactrocera dorsalis (Hendel)

PubMed Central

Li, Ran; Zhang, Meng-Yi; Liu, Yu-Wei; Zhang, Zheng; Smagghe, Guy; Wang, Jin-Jun

2017-01-01

Time-dependent expression of proteins in ovary is important to understand oogenesis in insects. Here, we profiled the proteomes of developing ovaries from Bactrocera dorsalis (Hendel) to obtain information about ovarian development with particular emphasis on differentially expressed proteins (DEPs) involved in oogenesis. A total of 4838 proteins were identified with an average peptide number of 8.15 and sequence coverage of 20.79%. Quantitative proteomic analysis showed that a total of 612 and 196 proteins were differentially expressed in developing and mature ovaries, respectively. Furthermore, 153, 196 and 59 potential target proteins were highly expressed in early, vitellogenic and mature ovaries and most tested DEPs had the similar trends consistent with the respective transcriptional profiles. These proteins were abundantly expressed in pre-vitellogenic and vitellogenic stages, including tropomyosin, vitellogenin, eukaryotic translation initiation factor, heat shock protein, importin protein, vitelline membrane protein, and chorion protein. Several hormone and signal pathway related proteins were also identified during ovarian development including piRNA, notch, insulin, juvenile, and ecdysone hormone signal pathways. This is the first report of a global ovary proteome of a tephritid fruit fly, and may contribute to understanding the complicate processes of ovarian development and exploring the potentially novel pest control targets. PMID:28665301

Landscape of the PARKIN-dependent ubiquitylome in response to mitochondrial depolarization.

PubMed

Sarraf, Shireen A; Raman, Malavika; Guarani-Pereira, Virginia; Sowa, Mathew E; Huttlin, Edward L; Gygi, Steven P; Harper, J Wade

2013-04-18

The PARKIN ubiquitin ligase (also known as PARK2) and its regulatory kinase PINK1 (also known as PARK6), often mutated in familial early-onset Parkinson's disease, have central roles in mitochondrial homeostasis and mitophagy. Whereas PARKIN is recruited to the mitochondrial outer membrane (MOM) upon depolarization via PINK1 action and can ubiquitylate porin, mitofusin and Miro proteins on the MOM, the full repertoire of PARKIN substrates--the PARKIN-dependent ubiquitylome--remains poorly defined. Here we use quantitative diGly capture proteomics (diGly) to elucidate the ubiquitylation site specificity and topology of PARKIN-dependent target modification in response to mitochondrial depolarization. Hundreds of dynamically regulated ubiquitylation sites in dozens of proteins were identified, with strong enrichment for MOM proteins, indicating that PARKIN dramatically alters the ubiquitylation status of the mitochondrial proteome. Using complementary interaction proteomics, we found depolarization-dependent PARKIN association with numerous MOM targets, autophagy receptors, and the proteasome. Mutation of the PARKIN active site residue C431, which has been found mutated in Parkinson's disease patients, largely disrupts these associations. Structural and topological analysis revealed extensive conservation of PARKIN-dependent ubiquitylation sites on cytoplasmic domains in vertebrate and Drosophila melanogaster MOM proteins. These studies provide a resource for understanding how the PINK1-PARKIN pathway re-sculpts the proteome to support mitochondrial homeostasis.

Highlights of the Biology and Disease-driven Human Proteome Project, 2015-2016.

PubMed

Van Eyk, Jennifer E; Corrales, Fernando J; Aebersold, Ruedi; Cerciello, Ferdinando; Deutsch, Eric W; Roncada, Paola; Sanchez, Jean-Charles; Yamamoto, Tadashi; Yang, Pengyuan; Zhang, Hui; Omenn, Gilbert S

2016-11-04

The Biology and Disease-driven Human Proteome Project (B/D-HPP) is aimed at supporting and enhancing the broad use of state-of-the-art proteomic methods to characterize and quantify proteins for in-depth understanding of the molecular mechanisms of biological processes and human disease. Based on a foundation of the pre-existing HUPO initiatives begun in 2002, the B/D-HPP is designed to provide standardized methods and resources for mass spectrometry and specific protein affinity reagents and facilitate accessibility of these resources to the broader life sciences research and clinical communities. Currently there are 22 B/D-HPP initiatives and 3 closely related HPP resource pillars. The B/D-HPP groups are working to define sets of protein targets that are highly relevant to each particular field to deliver relevant assays for the measurement of these selected targets and to disseminate and make publicly accessible the information and tools generated. Major developments are the 2016 publications of the Human SRM Atlas and of "popular protein sets" for six organ systems. Here we present the current activities and plans of the BD-HPP initiatives as highlighted in numerous B/D-HPP workshops at the 14th annual HUPO 2015 World Congress of Proteomics in Vancouver, Canada.

Proteomic analysis of mitochondria in respiratory epithelial cells infected with human respiratory syncytial virus and functional implications for virus and cell biology.

PubMed

Munday, Diane C; Howell, Gareth; Barr, John N; Hiscox, Julian A

2015-03-01

The aim of this study was to quantitatively characterise the mitochondrial proteome of airway epithelial cells infected with human respiratory syncytial virus (HRSV), a major cause of paediatric illness. Quantitative proteomics, underpinned by stable isotope labelling with amino acids in cell culture, coupled to LC-MS/MS, was applied to mitochondrial fractions prepared from HRSV-infected and mock-infected cells 12 and 24 h post-infection. Datasets were analysed using ingenuity pathway analysis, and the results were validated and characterised using bioimaging, targeted inhibition and gene depletion. The data quantitatively indicated that antiviral signalling proteins converged on mitochondria during HRSV infection. The mitochondrial receptor protein Tom70 was found to act in an antiviral manner, while its chaperone, Hsp90, was confirmed to be a positive viral factor. Proteins associated with different organelles were also co-enriched in the mitochondrial fractions from HRSV-infected cells, suggesting that alterations in organelle dynamics and membrane associations occur during virus infection. Protein and pathway-specific alterations occur to the mitochondrial proteome in a spatial and temporal manner during HRSV infection, suggesting that this organelle may have altered functions. These could be targeted as part of potential therapeutic strategies to disrupt virus biology. © 2014 Royal Pharmaceutical Society.

Identification of virulence determinants of the human pathogenic fungi Aspergillus fumigatus and Candida albicans by proteomics.

PubMed

Kniemeyer, Olaf; Schmidt, André D; Vödisch, Martin; Wartenberg, Dirk; Brakhage, Axel A

2011-06-01

Both fungi Candida albicans and Aspergillus fumigatus can cause a number of life-threatening systemic infections in humans. The commensal yeast C. albicans is one of the main causes of nosocomial fungal infectious diseases, whereas the filamentous fungus A. fumigatus has become one of the most prevalent airborne fungal pathogens. Early diagnosis of these fungal infections is challenging, only a limited number of antifungals for treatment are available, and the molecular details of pathogenicity are hardly understood. The completion of both the A. fumigatus and C. albicans genome sequence provides the opportunity to improve diagnosis, to define new drug targets, to understand the functions of many uncharacterised proteins, and to study protein regulation on a global scale. With the application of proteomic tools, particularly two-dimensional gel electrophoresis and LC/MS-based methods, a comprehensive overview about the proteins of A. fumigatus and C. albicans present or induced during environmental changes and stress conditions has been obtained in the past 5 years. However, for the discovery of further putative virulence determinants, more sensitive and targeted proteomic methods have to be applied. Here, we review the recent proteome data generated for A. fumigatus and C. albicans that are related to factors required for pathogenicity. Copyright © 2011 Elsevier GmbH. All rights reserved.

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-C. SRM analysis of Asp-N versus tryptic peptides for eight proteins determined that Asp-N yielded higher signal in five of eight cases. PMID:24696503

Multiplex High-Throughput Targeted Proteomic Assay To Identify Induced Pluripotent Stem Cells.

PubMed

Baud, Anna; Wessely, Frank; Mazzacuva, Francesca; McCormick, James; Camuzeaux, Stephane; Heywood, Wendy E; Little, Daniel; Vowles, Jane; Tuefferd, Marianne; Mosaku, Olukunbi; Lako, Majlinda; Armstrong, Lyle; Webber, Caleb; Cader, M Zameel; Peeters, Pieter; Gissen, Paul; Cowley, Sally A; Mills, Kevin

2017-02-21

Induced pluripotent stem cells have great potential as a human model system in regenerative medicine, disease modeling, and drug screening. However, their use in medical research is hampered by laborious reprogramming procedures that yield low numbers of induced pluripotent stem cells. For further applications in research, only the best, competent clones should be used. The standard assays for pluripotency are based on genomic approaches, which take up to 1 week to perform and incur significant cost. Therefore, there is a need for a rapid and cost-effective assay able to distinguish between pluripotent and nonpluripotent cells. Here, we describe a novel multiplexed, high-throughput, and sensitive peptide-based multiple reaction monitoring mass spectrometry assay, allowing for the identification and absolute quantitation of multiple core transcription factors and pluripotency markers. This assay provides simpler and high-throughput classification into either pluripotent or nonpluripotent cells in 7 min analysis while being more cost-effective than conventional genomic tests.

Proteomic analysis in type 2 diabetes patients before and after a very low calorie diet reveals potential disease state and intervention specific biomarkers.

PubMed

Sleddering, Maria A; Markvoort, Albert J; Dharuri, Harish K; Jeyakar, Skhandhan; Snel, Marieke; Juhasz, Peter; Lynch, Moira; Hines, Wade; Li, Xiaohong; Jazet, Ingrid M; Adourian, Aram; Hilbers, Peter A J; Smit, Johannes W A; Van Dijk, Ko Willems

2014-01-01

Very low calorie diets (VLCD) with and without exercise programs lead to major metabolic improvements in obese type 2 diabetes patients. The mechanisms underlying these improvements have so far not been elucidated fully. To further investigate the mechanisms of a VLCD with or without exercise and to uncover possible biomarkers associated with these interventions, blood samples were collected from 27 obese type 2 diabetes patients before and after a 16-week VLCD (Modifast ∼ 450 kcal/day). Thirteen of these patients followed an exercise program in addition to the VCLD. Plasma was obtained from 27 lean and 27 obese controls as well. Proteomic analysis was performed using mass spectrometry (MS) and targeted multiple reaction monitoring (MRM) and a large scale isobaric tags for relative and absolute quantitation (iTRAQ) approach. After the 16-week VLCD, there was a significant decrease in body weight and HbA1c in all patients, without differences between the two intervention groups. Targeted MRM analysis revealed differences in several proteins, which could be divided in diabetes-associated (fibrinogen, transthyretin), obesity-associated (complement C3), and diet-associated markers (apolipoproteins, especially apolipoprotein A-IV). To further investigate the effects of exercise, large scale iTRAQ analysis was performed. However, no proteins were found showing an exercise effect. Thus, in this study, specific proteins were found to be differentially expressed in type 2 diabetes patients versus controls and before and after a VLCD. These proteins are potential disease state and intervention specific biomarkers. Controlled-Trials.com ISRCTN76920690.

Proteomic Analysis in Type 2 Diabetes Patients before and after a Very Low Calorie Diet Reveals Potential Disease State and Intervention Specific Biomarkers

PubMed Central

Dharuri, Harish K.; Jeyakar, Skhandhan; Snel, Marieke; Juhasz, Peter; Lynch, Moira; Hines, Wade; Li, Xiaohong; Jazet, Ingrid M.; Adourian, Aram; Hilbers, Peter A. J.; Smit, Johannes W. A.; Van Dijk, Ko Willems

2014-01-01

Very low calorie diets (VLCD) with and without exercise programs lead to major metabolic improvements in obese type 2 diabetes patients. The mechanisms underlying these improvements have so far not been elucidated fully. To further investigate the mechanisms of a VLCD with or without exercise and to uncover possible biomarkers associated with these interventions, blood samples were collected from 27 obese type 2 diabetes patients before and after a 16-week VLCD (Modifast ∼450 kcal/day). Thirteen of these patients followed an exercise program in addition to the VCLD. Plasma was obtained from 27 lean and 27 obese controls as well. Proteomic analysis was performed using mass spectrometry (MS) and targeted multiple reaction monitoring (MRM) and a large scale isobaric tags for relative and absolute quantitation (iTRAQ) approach. After the 16-week VLCD, there was a significant decrease in body weight and HbA1c in all patients, without differences between the two intervention groups. Targeted MRM analysis revealed differences in several proteins, which could be divided in diabetes-associated (fibrinogen, transthyretin), obesity-associated (complement C3), and diet-associated markers (apolipoproteins, especially apolipoprotein A-IV). To further investigate the effects of exercise, large scale iTRAQ analysis was performed. However, no proteins were found showing an exercise effect. Thus, in this study, specific proteins were found to be differentially expressed in type 2 diabetes patients versus controls and before and after a VLCD. These proteins are potential disease state and intervention specific biomarkers. Trial Registration Controlled-Trials.com ISRCTN76920690 PMID:25415563

Multiplex array proteomics detects increased MMP-8 in CSF after spinal cord injury.

PubMed

Light, Matthew; Minor, Kenneth H; DeWitt, Peter; Jasper, Kyle H; Davies, Stephen J A

2012-06-11

A variety of methods have been used to study inflammatory changes in the acutely injured spinal cord. Recently novel multiplex assays have been used in an attempt to overcome limitations in numbers of available targets studied in a single experiment. Other technical challenges in developing pre-clinical rodent models to investigate biomarkers in cerebrospinal fluid (CSF) include relatively small volumes of sample and low concentrations of target proteins. The primary objective of this study was to characterize the inflammatory profile present in CSF at a subacute time point in a clinically relevant rodent model of traumatic spinal cord injury (SCI). Our other aim was to test a microarray proteomics platform specifically for this application. A 34 cytokine sandwich ELISA microarray was used to study inflammatory changes in CSF samples taken 12 days post-cervical SCI in adult rats. The difference between the median foreground signal and the median background signal was measured. Bonferroni and Benjamini-Hochburg multiple testing corrections were applied to limit the False Discovery Rate (FDR), and a linear mixed model was used to account for repeated measures in the array. We report a novel subacute SCI biomarker, elevated levels of matrix metalloproteinase-8 protein in CSF, and discuss application of statistical models designed for multiplex testing. Major advantages of this assay over conventional methods include high-throughput format, good sensitivity, and reduced sample consumption. This method can be useful for creating comprehensive inflammatory profiles, and biomarkers can be used in the clinic to assess injury severity and to objectively grade response to therapy.

A molecular characterization of the choroid plexus and stress-induced gene regulation

PubMed Central

Sathyanesan, M; Girgenti, M J; Banasr, M; Stone, K; Bruce, C; Guilchicek, E; Wilczak-Havill, K; Nairn, A; Williams, K; Sass, S; Duman, J G; Newton, S S

2012-01-01

The role of the choroid plexus (CP) in brain homeostasis is being increasingly recognized and recent studies suggest that the CP has a more important role in physiological and pathological brain functions than currently appreciated. To obtain additional insight on the CP function, we performed a proteomics and transcriptomics characterization employing a combination of high resolution tandem mass spectrometry and gene expression analyses in normal rodent brain. Using multiple protein fractionation approaches, we identified 1400 CP proteins in adult CP. Microarray-based comparison of CP gene expression with the kidney, cortex and hippocampus showed significant overlap between the CP and the kidney. CP gene profiles were validated by in situ hybridization analysis of several target genes including klotho, CLIC 6, OATP 14 and Ezrin. Immunohistochemical analyses were performed for CP and enpendyma detection of several target proteins including cytokeratin, Rab7, klotho, tissue inhibitor of metalloprotease 1 (TIMP1), MMP9 and glial fibrillary acidic protein (GFAP). The molecular functions associated with various proteins of the CP proteome indicate that it is a blood–cerebrospinal fluid (CSF) barrier that exhibits high levels of metabolic activity. We also analyzed the gene expression changes induced by stress, an exacerbating factor for many illnesses, particularly mood disorders. Chronic stress altered the expression of several genes, downregulating 5HT2C, glucocorticoid receptor and the cilia genes IFT88 and smoothened while upregulating 5HT2A, BDNF, TNFα and IL-1b. The data presented here attach additional significance to the emerging importance of CP function in brain health and CNS disease states. PMID:22781172

PROTEOMICS OF THE AMNIOTIC FLUID IN ASSESSMENT OF THE PLACENTA – RELEVANCE FOR PRETERM BIRTH

PubMed Central

Buhimschi, Irina A.; Buhimschi, Catalin S.

2008-01-01

Proteomics is the study of expressed proteins and has emerged as a complement to genomic research. The major advantage of proteomics over DNA-RNA based technologies is that it more closely relates to phenotype and not the source code. Proteomics thus holds the promise of providing direct insight into the true mechanisms of human disease. Historically, examination of the placenta was the first modality to subclassify pathogenetical entities responsible for preterm birth. Because placenta is a key pathophysiological participant in several major obstetrical syndromes (preterm birth, preeclampsia, intrauterine growth restriction) identification of relevant biomarkers of placental function can profoundly impact on the prediction of fetal outcome and treatment efficacy. Proteomics is a young science and studies that associate proteomic patterns with long-term outcome require follow-up of children up to school age. In the interim, placental pathological footprints of cellular injury can be useful as intermediate outcomes. Furthermore, knowledge of the identity of the dys-regulated proteins may provide the necessary insight into novel pathophysiological pathways and unravel possible targets for therapeutic intervention that could not have been envisioned through hypothesis-driven approaches. PMID:18191197

Visualization and dissemination of multidimensional proteomics data comparing protein abundance during Caenorhabditis elegans development.

PubMed

Riffle, Michael; Merrihew, Gennifer E; Jaschob, Daniel; Sharma, Vagisha; Davis, Trisha N; Noble, William S; MacCoss, Michael J

2015-11-01

Regulation of protein abundance is a critical aspect of cellular function, organism development, and aging. Alternative splicing may give rise to multiple possible proteoforms of gene products where the abundance of each proteoform is independently regulated. Understanding how the abundances of these distinct gene products change is essential to understanding the underlying mechanisms of many biological processes. Bottom-up proteomics mass spectrometry techniques may be used to estimate protein abundance indirectly by sequencing and quantifying peptides that are later mapped to proteins based on sequence. However, quantifying the abundance of distinct gene products is routinely confounded by peptides that map to multiple possible proteoforms. In this work, we describe a technique that may be used to help mitigate the effects of confounding ambiguous peptides and multiple proteoforms when quantifying proteins. We have applied this technique to visualize the distribution of distinct gene products for the whole proteome across 11 developmental stages of the model organism Caenorhabditis elegans. The result is a large multidimensional dataset for which web-based tools were developed for visualizing how translated gene products change during development and identifying possible proteoforms. The underlying instrument raw files and tandem mass spectra may also be downloaded. The data resource is freely available on the web at http://www.yeastrc.org/wormpes/ . Graphical Abstract ᅟ.

Effect of posttranslational modifications on enzyme function and assembly.

PubMed

Ryšlavá, Helena; Doubnerová, Veronika; Kavan, Daniel; Vaněk, Ondřej

2013-10-30

The detailed examination of enzyme molecules by mass spectrometry and other techniques continues to identify hundreds of distinct PTMs. Recently, global analyses of enzymes using methods of contemporary proteomics revealed widespread distribution of PTMs on many key enzymes distributed in all cellular compartments. Critically, patterns of multiple enzymatic and nonenzymatic PTMs within a single enzyme are now functionally evaluated providing a holistic picture of a macromolecule interacting with low molecular mass compounds, some of them being substrates, enzyme regulators, or activated precursors for enzymatic and nonenzymatic PTMs. Multiple PTMs within a single enzyme molecule and their mutual interplays are critical for the regulation of catalytic activity. Full understanding of this regulation will require detailed structural investigation of enzymes, their structural analogs, and their complexes. Further, proteomics is now integrated with molecular genetics, transcriptomics, and other areas leading to systems biology strategies. These allow the functional interrogation of complex enzymatic networks in their natural environment. In the future, one might envisage the use of robust high throughput analytical techniques that will be able to detect multiple PTMs on a global scale of individual proteomes from a number of carefully selected cells and cellular compartments. This article is part of a Special Issue entitled: Posttranslational Protein modifications in biology and Medicine. Copyright © 2013 Elsevier B.V. All rights reserved.

FDRAnalysis: a tool for the integrated analysis of tandem mass spectrometry identification results from multiple search engines.

PubMed

Wedge, David C; Krishna, Ritesh; Blackhurst, Paul; Siepen, Jennifer A; Jones, Andrew R; Hubbard, Simon J

2011-04-01

Confident identification of peptides via tandem mass spectrometry underpins modern high-throughput proteomics. This has motivated considerable recent interest in the postprocessing of search engine results to increase confidence and calculate robust statistical measures, for example through the use of decoy databases to calculate false discovery rates (FDR). FDR-based analyses allow for multiple testing and can assign a single confidence value for both sets and individual peptide spectrum matches (PSMs). We recently developed an algorithm for combining the results from multiple search engines, integrating FDRs for sets of PSMs made by different search engine combinations. Here we describe a web-server and a downloadable application that makes this routinely available to the proteomics community. The web server offers a range of outputs including informative graphics to assess the confidence of the PSMs and any potential biases. The underlying pipeline also provides a basic protein inference step, integrating PSMs into protein ambiguity groups where peptides can be matched to more than one protein. Importantly, we have also implemented full support for the mzIdentML data standard, recently released by the Proteomics Standards Initiative, providing users with the ability to convert native formats to mzIdentML files, which are available to download.

FDRAnalysis: A tool for the integrated analysis of tandem mass spectrometry identification results from multiple search engines

PubMed Central

Wedge, David C; Krishna, Ritesh; Blackhurst, Paul; Siepen, Jennifer A; Jones, Andrew R.; Hubbard, Simon J.

2013-01-01

Confident identification of peptides via tandem mass spectrometry underpins modern high-throughput proteomics. This has motivated considerable recent interest in the post-processing of search engine results to increase confidence and calculate robust statistical measures, for example through the use of decoy databases to calculate false discovery rates (FDR). FDR-based analyses allow for multiple testing and can assign a single confidence value for both sets and individual peptide spectrum matches (PSMs). We recently developed an algorithm for combining the results from multiple search engines, integrating FDRs for sets of PSMs made by different search engine combinations. Here we describe a web-server, and a downloadable application, which makes this routinely available to the proteomics community. The web server offers a range of outputs including informative graphics to assess the confidence of the PSMs and any potential biases. The underlying pipeline provides a basic protein inference step, integrating PSMs into protein ambiguity groups where peptides can be matched to more than one protein. Importantly, we have also implemented full support for the mzIdentML data standard, recently released by the Proteomics Standards Initiative, providing users with the ability to convert native formats to mzIdentML files, which are available to download. PMID:21222473

Ursgal, Universal Python Module Combining Common Bottom-Up Proteomics Tools for Large-Scale Analysis.

PubMed

Kremer, Lukas P M; Leufken, Johannes; Oyunchimeg, Purevdulam; Schulze, Stefan; Fufezan, Christian

2016-03-04

Proteomics data integration has become a broad field with a variety of programs offering innovative algorithms to analyze increasing amounts of data. Unfortunately, this software diversity leads to many problems as soon as the data is analyzed using more than one algorithm for the same task. Although it was shown that the combination of multiple peptide identification algorithms yields more robust results, it is only recently that unified approaches are emerging; however, workflows that, for example, aim to optimize search parameters or that employ cascaded style searches can only be made accessible if data analysis becomes not only unified but also and most importantly scriptable. Here we introduce Ursgal, a Python interface to many commonly used bottom-up proteomics tools and to additional auxiliary programs. Complex workflows can thus be composed using the Python scripting language using a few lines of code. Ursgal is easily extensible, and we have made several database search engines (X!Tandem, OMSSA, MS-GF+, Myrimatch, MS Amanda), statistical postprocessing algorithms (qvality, Percolator), and one algorithm that combines statistically postprocessed outputs from multiple search engines ("combined FDR") accessible as an interface in Python. Furthermore, we have implemented a new algorithm ("combined PEP") that combines multiple search engines employing elements of "combined FDR", PeptideShaker, and Bayes' theorem.

Visualization and Dissemination of Multidimensional Proteomics Data Comparing Protein Abundance During Caenorhabditis elegans Development

NASA Astrophysics Data System (ADS)

Riffle, Michael; Merrihew, Gennifer E.; Jaschob, Daniel; Sharma, Vagisha; Davis, Trisha N.; Noble, William S.; MacCoss, Michael J.

2015-11-01

Regulation of protein abundance is a critical aspect of cellular function, organism development, and aging. Alternative splicing may give rise to multiple possible proteoforms of gene products where the abundance of each proteoform is independently regulated. Understanding how the abundances of these distinct gene products change is essential to understanding the underlying mechanisms of many biological processes. Bottom-up proteomics mass spectrometry techniques may be used to estimate protein abundance indirectly by sequencing and quantifying peptides that are later mapped to proteins based on sequence. However, quantifying the abundance of distinct gene products is routinely confounded by peptides that map to multiple possible proteoforms. In this work, we describe a technique that may be used to help mitigate the effects of confounding ambiguous peptides and multiple proteoforms when quantifying proteins. We have applied this technique to visualize the distribution of distinct gene products for the whole proteome across 11 developmental stages of the model organism Caenorhabditis elegans. The result is a large multidimensional dataset for which web-based tools were developed for visualizing how translated gene products change during development and identifying possible proteoforms. The underlying instrument raw files and tandem mass spectra may also be downloaded. The data resource is freely available on the web at http://www.yeastrc.org/wormpes/.

A Community Standard Format for the Representation of Protein Affinity Reagents*

PubMed Central

Gloriam, David E.; Orchard, Sandra; Bertinetti, Daniela; Björling, Erik; Bongcam-Rudloff, Erik; Borrebaeck, Carl A. K.; Bourbeillon, Julie; Bradbury, Andrew R. M.; de Daruvar, Antoine; Dübel, Stefan; Frank, Ronald; Gibson, Toby J.; Gold, Larry; Haslam, Niall; Herberg, Friedrich W.; Hiltke, Tara; Hoheisel, Jörg D.; Kerrien, Samuel; Koegl, Manfred; Konthur, Zoltán; Korn, Bernhard; Landegren, Ulf; Montecchi-Palazzi, Luisa; Palcy, Sandrine; Rodriguez, Henry; Schweinsberg, Sonja; Sievert, Volker; Stoevesandt, Oda; Taussig, Michael J.; Ueffing, Marius; Uhlén, Mathias; van der Maarel, Silvère; Wingren, Christer; Woollard, Peter; Sherman, David J.; Hermjakob, Henning

2010-01-01

Protein affinity reagents (PARs), most commonly antibodies, are essential reagents for protein characterization in basic research, biotechnology, and diagnostics as well as the fastest growing class of therapeutics. Large numbers of PARs are available commercially; however, their quality is often uncertain. In addition, currently available PARs cover only a fraction of the human proteome, and their cost is prohibitive for proteome scale applications. This situation has triggered several initiatives involving large scale generation and validation of antibodies, for example the Swedish Human Protein Atlas and the German Antibody Factory. Antibodies targeting specific subproteomes are being pursued by members of Human Proteome Organisation (plasma and liver proteome projects) and the United States National Cancer Institute (cancer-associated antigens). ProteomeBinders, a European consortium, aims to set up a resource of consistently quality-controlled protein-binding reagents for the whole human proteome. An ultimate PAR database resource would allow consumers to visit one on-line warehouse and find all available affinity reagents from different providers together with documentation that facilitates easy comparison of their cost and quality. However, in contrast to, for example, nucleotide databases among which data are synchronized between the major data providers, current PAR producers, quality control centers, and commercial companies all use incompatible formats, hindering data exchange. Here we propose Proteomics Standards Initiative (PSI)-PAR as a global community standard format for the representation and exchange of protein affinity reagent data. The PSI-PAR format is maintained by the Human Proteome Organisation PSI and was developed within the context of ProteomeBinders by building on a mature proteomics standard format, PSI-molecular interaction, which is a widely accepted and established community standard for molecular interaction data. Further information and documentation are available on the PSI-PAR web site. PMID:19674966

PECAN: Library Free Peptide Detection for Data-Independent Acquisition Tandem Mass Spectrometry Data

PubMed Central

Ting, Ying S.; Egertson, Jarrett D.; Bollinger, James G.; Searle, Brian C.; Payne, Samuel H.; Noble, William Stafford; MacCoss, Michael J.

2017-01-01

In mass spectrometry-based shogun proteomics, data-independent acquisition (DIA) is an emerging technique for unbiased and reproducible measurement of protein mixtures. Without targeting a specific precursor ion, DIA MS/MS spectra are often highly multiplexed, containing product ions from multiple co-fragmenting precursors. Thus, detecting peptides directly from DIA data is challenging; most DIA data analyses require spectral libraries. Here we present a new library-free, peptide-centric tool PECAN that detects peptides directly from DIA data. PECAN reports evidence of detection based on product ion scoring, enabling detection of low abundance analytes with poor precursor ion signal. We benchmarked PECAN with chromatographic peak picking accuracy and peptide detection capability. We further validated PECAN detection with data-dependent acquisition and targeted analyses. Last, we used PECAN to build a library from DIA data and to query sequence variants. Together, these results show that PECAN detects peptides robustly and accurately from DIA data without using a library. PMID:28783153

Transduction of Redox Signaling by Electrophile-Protein Reactions

PubMed Central

Rudolph, Tanja K.; Freeman, Bruce A.

2014-01-01

Over the last 50 years, the posttranslational modification (PTM) of proteins has emerged as a central mechanism for cells to regulate metabolism, growth, differentiation, cell-cell interactions, and immune responses. By influencing protein structure and function, PTM leads to a multiplication of proteome diversity. Redox-dependent PTMs, mediated by environmental and endogenously generated reactive species, induce cell signaling responses and can have toxic effects in organisms. PTMs induced by the electrophilic by-products of redox reactions most frequently occur at protein thiols; other nucleophilic amino acids serve as less favorable targets. Advances in mass spectrometry and affinity-chemistry strategies have improved the detection of electrophile-induced protein modifications both in vitro and in vivo and have revealed a high degree of amino acid and protein selectivity of electrophilic PTM. The identification of biological targets of electrophiles has motivated further study of the functional impact of various PTM reactions on specific signaling pathways and how this might affect organisms. PMID:19797270

Template-based protein structure modeling using the RaptorX web server.

PubMed

Källberg, Morten; Wang, Haipeng; Wang, Sheng; Peng, Jian; Wang, Zhiyong; Lu, Hui; Xu, Jinbo

2012-07-19

A key challenge of modern biology is to uncover the functional role of the protein entities that compose cellular proteomes. To this end, the availability of reliable three-dimensional atomic models of proteins is often crucial. This protocol presents a community-wide web-based method using RaptorX (http://raptorx.uchicago.edu/) for protein secondary structure prediction, template-based tertiary structure modeling, alignment quality assessment and sophisticated probabilistic alignment sampling. RaptorX distinguishes itself from other servers by the quality of the alignment between a target sequence and one or multiple distantly related template proteins (especially those with sparse sequence profiles) and by a novel nonlinear scoring function and a probabilistic-consistency algorithm. Consequently, RaptorX delivers high-quality structural models for many targets with only remote templates. At present, it takes RaptorX ~35 min to finish processing a sequence of 200 amino acids. Since its official release in August 2011, RaptorX has processed ~6,000 sequences submitted by ~1,600 users from around the world.

Template-based protein structure modeling using the RaptorX web server

PubMed Central

Källberg, Morten; Wang, Haipeng; Wang, Sheng; Peng, Jian; Wang, Zhiyong; Lu, Hui; Xu, Jinbo

2016-01-01

A key challenge of modern biology is to uncover the functional role of the protein entities that compose cellular proteomes. To this end, the availability of reliable three-dimensional atomic models of proteins is often crucial. This protocol presents a community-wide web-based method using RaptorX (http://raptorx.uchicago.edu/) for protein secondary structure prediction, template-based tertiary structure modeling, alignment quality assessment and sophisticated probabilistic alignment sampling. RaptorX distinguishes itself from other servers by the quality of the alignment between a target sequence and one or multiple distantly related template proteins (especially those with sparse sequence profiles) and by a novel nonlinear scoring function and a probabilistic-consistency algorithm. Consequently, RaptorX delivers high-quality structural models for many targets with only remote templates. At present, it takes RaptorX ~35 min to finish processing a sequence of 200 amino acids. Since its official release in August 2011, RaptorX has processed ~6,000 sequences submitted by ~1,600 users from around the world. PMID:22814390

IgY14 and SuperMix immunoaffinity separations coupled with liquid chromatography-mass spectrometry for human plasma proteomic biomarker discovery

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

Shi, Tujin; Zhou, Jianying; Gritsenko, Marina A.

2012-02-01

Interest in the application of advanced proteomics technologies to human blood plasma- or serum-based clinical samples for the purpose of discovering disease biomarkers continues to grow; however, the enormous dynamic range of protein concentrations in these types of samples (often >10 orders of magnitude) represents a significant analytical challenge, particularly for detecting low-abundance candidate biomarkers. In response, immunoaffinity separation methods for depleting multiple high- and moderate-abundance proteins have become key tools for enriching low-abundance proteins and enhancing detection of these proteins in plasma proteomics. Herein, we describe IgY14 and tandem IgY14-Supermix separation methods for removing 14 high-abundance and up tomore » 60 moderate-abundance proteins, respectively, from human blood plasma and highlight their utility when combined with liquid chromatography-tandem mass spectrometry for interrogating the human plasma proteome.« less

Preparation of the low molecular weight serum proteome for mass spectrometry analysis.

PubMed

Waybright, Timothy J; Chan, King C; Veenstra, Timothy D; Xiao, Zhen

2013-01-01

The discovery of viable biomarkers or indicators of disease states is complicated by the inherent complexity of the chosen biological specimen. Every sample, whether it is serum, plasma, urine, tissue, cells, or a host of others, contains thousands of large and small components, each interacting in multiple ways. The need to concentrate on a group of these components to narrow the focus on a potential biomarker candidate becomes, out of necessity, a priority, especially in the search for immune-related low molecular weight serum biomarkers. One such method in the field of proteomics is to divide the sample proteome into groups based on the size of the protein, analyze each group, and mine the data for statistically significant items. This chapter details a portion of this method, concentrating on a method for fractionating and analyzing the low molecular weight proteome of human serum.

P-MartCancer-Interactive Online Software to Enable Analysis of Shotgun Cancer Proteomic Datasets.

PubMed

Webb-Robertson, Bobbie-Jo M; Bramer, Lisa M; Jensen, Jeffrey L; Kobold, Markus A; Stratton, Kelly G; White, Amanda M; Rodland, Karin D

2017-11-01

P-MartCancer is an interactive web-based software environment that enables statistical analyses of peptide or protein data, quantitated from mass spectrometry-based global proteomics experiments, without requiring in-depth knowledge of statistical programming. P-MartCancer offers a series of statistical modules associated with quality assessment, peptide and protein statistics, protein quantification, and exploratory data analyses driven by the user via customized workflows and interactive visualization. Currently, P-MartCancer offers access and the capability to analyze multiple cancer proteomic datasets generated through the Clinical Proteomics Tumor Analysis Consortium at the peptide, gene, and protein levels. P-MartCancer is deployed as a web service (https://pmart.labworks.org/cptac.html), alternatively available via Docker Hub (https://hub.docker.com/r/pnnl/pmart-web/). Cancer Res; 77(21); e47-50. ©2017 AACR . ©2017 American Association for Cancer Research.

Adaptation of Decoy Fusion Strategy for Existing Multi-Stage Search Workflows

NASA Astrophysics Data System (ADS)

Ivanov, Mark V.; Levitsky, Lev I.; Gorshkov, Mikhail V.

2016-09-01

A number of proteomic database search engines implement multi-stage strategies aiming at increasing the sensitivity of proteome analysis. These approaches often employ a subset of the original database for the secondary stage of analysis. However, if target-decoy approach (TDA) is used for false discovery rate (FDR) estimation, the multi-stage strategies may violate the underlying assumption of TDA that false matches are distributed uniformly across the target and decoy databases. This violation occurs if the numbers of target and decoy proteins selected for the second search are not equal. Here, we propose a method of decoy database generation based on the previously reported decoy fusion strategy. This method allows unbiased TDA-based FDR estimation in multi-stage searches and can be easily integrated into existing workflows utilizing popular search engines and post-search algorithms.

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 genome sequences, though there are over lapped proteins. Based on the demonstrated application of data stored in the database for functional analyses, it is suggested that these data will be useful for analyses of biological mechanisms in soybean. Furthermore, coupled with recent advances in information and communication technology, the usefulness of this database would increase in the analyses of biological mechanisms. Copyright © 2017 Elsevier B.V. All rights reserved.

Target identification in Fusobacterium nucleatum by subtractive genomics approach and enrichment analysis of host-pathogen protein-protein interactions.

PubMed

Kumar, Amit; Thotakura, Pragna Lakshmi; Tiwary, Basant Kumar; Krishna, Ramadas

2016-05-12

Fusobacterium nucleatum, a well studied bacterium in periodontal diseases, appendicitis, gingivitis, osteomyelitis and pregnancy complications has recently gained attention due to its association with colorectal cancer (CRC) progression. Treatment with berberine was shown to reverse F. nucleatum-induced CRC progression in mice by balancing the growth of opportunistic pathogens in tumor microenvironment. Intestinal microbiota imbalance and the infections caused by F. nucleatum might be regulated by therapeutic intervention. Hence, we aimed to predict drug target proteins in F. nucleatum, through subtractive genomics approach and host-pathogen protein-protein interactions (HP-PPIs). We also carried out enrichment analysis of host interacting partners to hypothesize the possible mechanisms involved in CRC progression due to F. nucleatum. In subtractive genomics approach, the essential, virulence and resistance related proteins were retrieved from RefSeq proteome of F. nucleatum by searching against Database of Essential Genes (DEG), Virulence Factor Database (VFDB) and Antibiotic Resistance Gene-ANNOTation (ARG-ANNOT) tool respectively. A subsequent hierarchical screening to identify non-human homologous, metabolic pathway-independent/pathway-specific and druggable proteins resulted in eight pathway-independent and 27 pathway-specific druggable targets. Co-aggregation of F. nucleatum with host induces proinflammatory gene expression thereby potentiates tumorigenesis. Hence, proteins from IBDsite, a database for inflammatory bowel disease (IBD) research and those involved in colorectal adenocarcinoma as interpreted from The Cancer Genome Atlas (TCGA) were retrieved to predict drug targets based on HP-PPIs with F. nucleatum proteome. Prediction of HP-PPIs exhibited 186 interactions contributed by 103 host and 76 bacterial proteins. Bacterial interacting partners were accounted as putative targets. And enrichment analysis of host interacting partners showed statistically enriched terms that were in positive correlation with CRC, atherosclerosis, cardiovascular, osteoporosis, Alzheimer's and other diseases. Subtractive genomics analysis provided a set of target proteins suggested to be indispensable for survival and pathogenicity of F. nucleatum. These target proteins might be considered for designing potent inhibitors to abrogate F. nucleatum infections. From enrichment analysis, it was hypothesized that F. nucleatum infection might enhance CRC progression by simultaneously regulating multiple signaling cascades which could lead to up-regulation of proinflammatory responses, oncogenes, modulation of host immune defense mechanism and suppression of DNA repair system.

NCI Requests 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, NCI's Antibody Characterization Program requests cancer-related protein targets for affinity production and distribution. Submissions will be accepted through July 9, 2012.

iTRAQ-based proteomic analysis of LI-F type peptides produced by Paenibacillus polymyxa JSa-9 mode of action against Bacillus cereus.

PubMed

Han, Jinzhi; Gao, Peng; Zhao, Shengming; Bie, Xiaomei; Lu, Zhaoxin; Zhang, Chong; Lv, Fengxia

2017-01-06

LI-F type peptides (AMP-jsa9) produced by Paenibacillus polymyxa JSa-9 are a group of cyclic lipodepsipeptide antibiotics that exhibit a broad antimicrobial spectrum against Gram-positive bacteria and filamentous fungi, especially Bacillus cereus and Fusarium moniliforme. In this study, to better understand the antibacterial mechanism of AMP-jsa9 against B. cereus, the ultrastructure of AMP-jsa9-treated B. cereus cells was observed by both atomic force microscopy and transmission electron microscopy, and quantitative proteomic analysis was performed on proteins extracted from treated and untreated bacterial cells by using isobaric tag for relative and absolute quantitation (iTRAQ) labeling and LC-MS/MS analysis to access differentially expressed proteins. Furthermore, multiple experiments were conducted to validate the results of the proteomic analysis, including determinations of ATP, NAD (+) H, NADP (+) H, reactive oxygen species (ROS), the activities of catalase (CAT) and superoxide dismutase (SOD), and the relative expression of target genes by quantitative real-time PCR. Bacterial cells exposed to AMP-jsa9 showed irregular surfaces with bleb projections and concaves; we hypothesize that AMP-jsa9 penetrated the cell wall and was anchored on the cytoplasmic membrane and that ROS accumulated in the cell membrane after treatment with AMP-jsa9, modulating the bacterial membrane properties and increasing membrane permeability. Consequently, the blebs were formed on the cell wall by the impulsive force of the leakage of intercellular contents. iTRAQ-based proteomic analysis detected a total of 1317 proteins, including 176 differentially expressed proteins (75 upregulated (fold >2) and 101 downregulated (fold <0.5)). Based on proteome analysis, the putative pathways of AMP-jsa9 action against B. cereus can be summarized as: (i) inhibition of bacterial sporulation, thiamine biosynthesis, energy metabolism, DNA transcription and translation, and cell wall biosynthesis, through direct regulation of protein levels; and (ii) indirect effects on the same pathways through the accumulation of ROS and the consequent impairment of cellular functions, resulting from downregulation of antioxidant proteins, especially CAT and SOD. The mode of action of LI-F type antimicrobial peptides (AMP-jsa9) against B. cereus was elucidated at the proteomic level. Two pathways of AMP-jsa9 action upon B. cereus cells were identified and the mechanism of bleb formation on the surfaces of bacterial cells was predicted based on the results of ultrastructural observation and proteomic analysis. These results are helpful in understanding the mechanism of LI-F type peptides and in providing the theoretical base for applying AMP-jsa9 or its analogs to combat Gram-positive pathogenic bacteria in the food and feed industries. Copyright © 2016 Elsevier B.V. All rights reserved.

Structural systems pharmacology: a new frontier in discovering novel drug targets.

PubMed

Tan, Hepan; Ge, Xiaoxia; Xie, Lei

2013-08-01

The modern target-based drug discovery process, characterized by the one-drug-one-gene paradigm, has been of limited success. In contrast, phenotype-based screening produces thousands of active compounds but gives no hint as to what their molecular targets are or which ones merit further research. This presents a question: What is a suitable target for an efficient and safe drug? In this paper, we argue that target selection should take into account the proteome-wide energetic and kinetic landscape of drug-target interactions, as well as their cellular and organismal consequences. We propose a new paradigm of structural systems pharmacology to deconvolute the molecular targets of successful drugs as well as to identify druggable targets and their drug-like binders. Here we face two major challenges in structural systems pharmacology: How do we characterize and analyze the structural and energetic origins of drug-target interactions on a proteome scale? How do we correlate the dynamic molecular interactions to their in vivo activity? We will review recent advances in developing new computational tools for biophysics, bioinformatics, chemoinformatics, and systems biology related to the identification of genome-wide target profiles. We believe that the integration of these tools will realize structural systems pharmacology, enabling us to both efficiently develop effective therapeutics for complex diseases and combat drug resistance.

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.

EMUDRA: Ensemble of Multiple Drug Repositioning Approaches to Improve Prediction Accuracy.

PubMed

Zhou, Xianxiao; Wang, Minghui; Katsyv, Igor; Irie, Hanna; Zhang, Bin

2018-04-24

Availability of large-scale genomic, epigenetic and proteomic data in complex diseases makes it possible to objectively and comprehensively identify therapeutic targets that can lead to new therapies. The Connectivity Map has been widely used to explore novel indications of existing drugs. However, the prediction accuracy of the existing methods, such as Kolmogorov-Smirnov statistic remains low. Here we present a novel high-performance drug repositioning approach that improves over the state-of-the-art methods. We first designed an expression weighted cosine method (EWCos) to minimize the influence of the uninformative expression changes and then developed an ensemble approach termed EMUDRA (Ensemble of Multiple Drug Repositioning Approaches) to integrate EWCos and three existing state-of-the-art methods. EMUDRA significantly outperformed individual drug repositioning methods when applied to simulated and independent evaluation datasets. We predicted using EMUDRA and experimentally validated an antibiotic rifabutin as an inhibitor of cell growth in triple negative breast cancer. EMUDRA can identify drugs that more effectively target disease gene signatures and will thus be a useful tool for identifying novel therapies for complex diseases and predicting new indications for existing drugs. The EMUDRA R package is available at doi:10.7303/syn11510888. bin.zhang@mssm.edu or zhangb@hotmail.com. Supplementary data are available at Bioinformatics online.

The impact of proteomics on the understanding of functions and biogenesis of fungal extracellular vesicles.

PubMed

Rodrigues, Marcio L; Nakayasu, Ernesto S; Almeida, Igor C; Nimrichter, Leonardo

2014-01-31

Several microbial molecules are released to the extracellular space in vesicle-like structures. In pathogenic fungi, these molecules include pigments, polysaccharides, lipids, and proteins, which traverse the cell wall in vesicles that accumulate in the extracellular space. The diverse composition of fungal extracellular vesicles (EV) is indicative of multiple mechanisms of cellular biogenesis, a hypothesis that was supported by EV proteomic studies in a set of Saccharomyces cerevisiae strains with defects in both conventional and unconventional secretory pathways. In the human pathogens Cryptococcus neoformans, Histoplasma capsulatum, and Paracoccidioides brasiliensis, extracellular vesicle proteomics revealed the presence of proteins with both immunological and pathogenic activities. In fact, fungal EV have been demonstrated to interfere with the activity of immune effector cells and to increase fungal pathogenesis. In this review, we discuss the impact of proteomics on the understanding of functions and biogenesis of fungal EV, as well as the potential role of these structures in fungal pathogenesis. This article is part of a Special Issue entitled: Trends in Microbial Proteomics. Copyright © 2013 Elsevier B.V. All rights reserved.

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.

Mass spectrometry-assisted gel-based proteomics in cancer biomarker discovery: approaches and application

PubMed Central

Huang, Rongrong; Chen, Zhongsi; He, Lei; He, Nongyue; Xi, Zhijiang; Li, Zhiyang; Deng, Yan; Zeng, Xin

2017-01-01

There is a critical need for the discovery of novel biomarkers for early detection and targeted therapy of cancer, a major cause of deaths worldwide. In this respect, proteomic technologies, such as mass spectrometry (MS), enable the identification of pathologically significant proteins in various types of samples. MS is capable of high-throughput profiling of complex biological samples including blood, tissues, urine, milk, and cells. MS-assisted proteomics has contributed to the development of cancer biomarkers that may form the foundation for new clinical tests. It can also aid in elucidating the molecular mechanisms underlying cancer. In this review, we discuss MS principles and instrumentation as well as approaches in MS-based proteomics, which have been employed in the development of potential biomarkers. Furthermore, the challenges in validation of MS biomarkers for their use in clinical practice are also reviewed. PMID:28912895

Mass spectrometry based biomarker discovery, verification, and validation--quality assurance and control of protein biomarker assays.

PubMed

Parker, Carol E; Borchers, Christoph H

2014-06-01

In its early years, mass spectrometry (MS)-based proteomics focused on the cataloging of proteins found in different species or different tissues. By 2005, proteomics was being used for protein quantitation, typically based on "proteotypic" peptides which act as surrogates for the parent proteins. Biomarker discovery is usually done by non-targeted "shotgun" proteomics, using relative quantitation methods to determine protein expression changes that correlate with disease (output given as "up-or-down regulation" or "fold-increases"). MS-based techniques can also perform "absolute" quantitation which is required for clinical applications (output given as protein concentrations). Here we describe the differences between these methods, factors that affect the precision and accuracy of the results, and some examples of recent studies using MS-based proteomics to verify cancer-related biomarkers. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

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.

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.

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.

Proteomic Profiling of the Pituitary Gland in Studies of Psychiatric Disorders.

PubMed

Krishnamurthy, Divya; Rahmoune, Hassan; Guest, Paul C

2017-01-01

Psychiatric disorders have been associated with perturbations of the hypothalamic-pituitary-adrenal axis. Therefore, proteomic studies of the pituitary gland have the potential to provide new insights into the underlying pathways affected in these conditions as well as identify new biomarkers or targets for use in developing improved medications. This chapter describes a protocol for preparation of pituitary protein extracts followed by characterization of the pituitary proteome by label-free liquid chromatography-tandem mass spectrometry in expression mode (LC-MS E ). The main focus was on establishing a method for identifying the major pituitary hormones and accessory proteins as many of these have already been implicated in psychiatric diseases.

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.

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

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 nonoptimal culture conditions but also provide valuable insights into intriguing biological principles, including the balance of proteome resource allocation and the role of gene duplication in evolutionary history. PMID:26560065

Yeast Interspecies Comparative Proteomics Reveals Divergence in Expression Profiles and Provides Insights into Proteome Resource Allocation and Evolutionary Roles of Gene Duplication.

PubMed

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 nonoptimal culture conditions but also provide valuable insights into intriguing biological principles, including the balance of proteome resource allocation and the role of gene duplication in evolutionary history. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

NCI Requests 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, NCI's Antibody Characterization Program requests cancer-related protein targets for affinity production and distribution. Submissions will be accepted through February 5, 2016.