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.

Identification and quantitative analysis of cellular proteins affected by treatment with withaferin a using a SILAC-based proteomics approach.

PubMed

Narayan, Malathi; Seeley, Kent W; Jinwal, Umesh K

2015-12-04

Withaferin A (WA) is a major bioactive compound isolated from the medicinal plant Withania somnifera Dunal, also known as "Ashwagandha". A number of published reports suggest various uses for WA including its function as an anti-inflammatory and anti-angiogenic drug molecule. The effects of WA at the molecular level in a cellular environment are not well understood. Knowledge of the molecular mechanism of action of WA could enhance its therapeutic value and may reveal novel pathways it may modulate. In order to identify and characterize proteins affected by treatment with WA, we used SILAC- based proteomics analysis on a mouse microglial cell line (N9), which replicates phenotypic characteristics of primary microglial cells. Using stable isotope labeling of amino acids in cell culture (SILAC) and mass spectrometry (MS), a total of 2300 unique protein groups were identified from three biological replicates, with significant expression changes in 32 non-redundant proteins. The top biological functions associated with these differentially expressed proteins include cell death and survival, free radical scavenging, and carbohydrate metabolism. Specifically, several heat shock proteins (Hsps) were found to be upregulated, which suggests that the chaperonic machinery might be regulated by WA. Furthermore, our study revealed several novel protein molecules that were not previously reported to be affected by WA. Among them, annexin A1, a key anti-inflammatory molecule in microglial cells was found to be downregulated. Hsc70, Hsp90α and Hsp105 were found to be upregulated. We also found sequestosome1/p62 (p62) to be upregulated. We performed Ingenuity Pathway Analysis (IPA) and found a number of pathways that were affected by WA treatment. SILAC-based proteomics analysis of a microglial cell model revealed several novel proteins whose expression is regulated by WA and probable pathways regulated by WA. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Persistent human Borna disease virus infection modifies the acetylome of human oligodendroglia cells towards higher energy and transporter levels

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

Liu, Xia; Liu, Siwen; Chongqing Key Laboratory of Neurobiology, Chongqing Medical University, Chongqing 400016

2015-11-15

Background: Borna disease virus (BDV) is a neurotropic RNA virus persistently infecting mammalian hosts including humans. Lysine acetylation (Kac) is a key protein post-translational modification (PTM). The unexpectedly broad regulatory scope of Kac let us to profile the entire acetylome upon BDV infection. Methods: The acetylome was profiled through stable isotope labeling for cell culture (SILAC)-based quantitative proteomics. The quantifiable proteome was annotated using bioinformatics. Results: We identified and quantified 791 Kac sites in 473 Kac proteins in human BDV Hu-H1-infected and non-infected oligodendroglial (OL) cells. Bioinformatic analysis revealed that BDV infection alters the acetylation of metabolic proteins, membrane-associated proteinsmore » and transmembrane transporter activity, and affects the acetylation of several lysine acetyltransferases (KAT). Conclusions: Upon BDV persistence the OL acetylome is manipulated towards higher energy and transporter levels necessary for shuttling BDV proteins to and from nuclear replication sites. - Highlights: • We used SILAC-based proteomics to analyze the acetylome of BDV infected OL cells. • We quantified 791Kac sites in 473 proteins. • Bioinformatic analysis revealed altered acetylation of metabolic proteins et al. • BDV manipulates the OL acetylome towards higher energy and transporter levels. • BDV infection is associated with enriched phosphate-associated metabolic processes.« less

SWATH-based proteomics identified carbonic anhydrase 2 as a potential diagnosis biomarker for nasopharyngeal carcinoma

PubMed Central

Luo, Yanzhang; Mok, Tin Seak; Lin, Xiuxian; Zhang, Wanling; Cui, Yizhi; Guo, Jiahui; Chen, Xing; Zhang, Tao; Wang, Tong

2017-01-01

Nasopharyngeal carcinoma (NPC) is a serious threat to public health, and the biomarker discovery is of urgent needs. The data-independent mode (DIA) based sequential window acquisition of all theoretical fragment-ion spectra (SWATH) mass spectrometry (MS) has been proved to be precise in protein quantitation and efficient for cancer biomarker researches. In this study, we performed the first SWATH-MS analysis comparing the NPC and normal tissues. Spike-in stable isotope labeling by amino acids in cell culture (super-SILAC) MS was used as a shotgun reference. We identified and quantified 1414 proteins across all SWATH-MS analyses. We found that SWATH-MS had a unique feature to preferentially detect proteins with smaller molecular weights than either super-SILAC MS or human proteome background. With SWATH-MS, 29 significant differentially express proteins (DEPs) were identified. Among them, carbonic anhydrase 2 (CA2) was selected for further validation per novelty, MS quality and other supporting rationale. With the tissue microarray analysis, we found that CA2 had an AUC of 0.94 in differentiating NPC from normal tissue samples. In conclusion, SWATH-MS has unique features in proteome analysis, and it leads to the identification of CA2 as a potentially new diagnostic biomarker for NPC. PMID:28117408

Global dynamics of the Escherichia coli proteome and phosphoproteome during growth in minimal medium.

PubMed

Soares, Nelson C; Spät, Philipp; Krug, Karsten; Macek, Boris

2013-06-07

Recent phosphoproteomics studies have generated relatively large data sets of bacterial proteins phosphorylated on serine, threonine, and tyrosine, implicating this type of phosphorylation in the regulation of vital processes of a bacterial cell; however, most phosphoproteomics studies in bacteria were so far qualitative. Here we applied stable isotope labeling by amino acids in cell culture (SILAC) to perform a quantitative analysis of proteome and phosphoproteome dynamics of Escherichia coli during five distinct phases of growth in the minimal medium. Combining two triple-SILAC experiments, we detected a total of 2118 proteins and quantified relative dynamics of 1984 proteins in all measured phases of growth, including 570 proteins associated with cell wall and membrane. In the phosphoproteomic experiment, we detected 150 Ser/Thr/Tyr phosphorylation events, of which 108 were localized to a specific amino acid residue and 76 were quantified in all phases of growth. Clustering analysis of SILAC ratios revealed distinct sets of coregulated proteins for each analyzed phase of growth and overrepresentation of membrane proteins in transition between exponential and stationary phases. The proteomics data indicated that proteins related to stress response typically associated with the stationary phase, including RpoS-dependent proteins, had increasing levels already during earlier phases of growth. Application of SILAC enabled us to measure median occupancies of phosphorylation sites, which were generally low (<12%). Interestingly, the phosphoproteome analysis showed a global increase of protein phosphorylation levels in the late stationary phase, pointing to a likely role of this modification in later phases of growth.

Proteomic analysis of Medulloblastoma reveals functional biology with translational potential.

PubMed

Rivero-Hinojosa, Samuel; Lau, Ling San; Stampar, Mojca; Staal, Jerome; Zhang, Huizhen; Gordish-Dressman, Heather; Northcott, Paul A; Pfister, Stefan M; Taylor, Michael D; Brown, Kristy J; Rood, Brian R

2018-06-07

Genomic characterization has begun to redefine diagnostic classifications of cancers. However, it remains a challenge to infer disease phenotypes from genomic alterations alone. To help realize the promise of genomics, we have performed a quantitative proteomics investigation using Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) and 41 tissue samples spanning the 4 genomically based subgroups of medulloblastoma and control cerebellum. We have identified and quantitated thousands of proteins across these groups and find that we are able to recapitulate the genomic subgroups based upon subgroup restricted and differentially abundant proteins while also identifying subgroup specific protein isoforms. Integrating our proteomic measurements with genomic data, we calculate a poor correlation between mRNA and protein abundance. Using EPIC 850 k methylation array data on the same tissues, we also investigate the influence of copy number alterations and DNA methylation on the proteome in an attempt to characterize the impact of these genetic features on the proteome. Reciprocally, we are able to use the proteome to identify which genomic alterations result in altered protein abundance and thus are most likely to impact biology. Finally, we are able to assemble protein-based pathways yielding potential avenues for clinical intervention. From these, we validate the EIF4F cap-dependent translation pathway as a novel druggable pathway in medulloblastoma. Thus, quantitative proteomics complements genomic platforms to yield a more complete understanding of functional tumor biology and identify novel therapeutic targets for medulloblastoma.

Multidimensional electrostatic repulsion-hydrophilic interaction chromatography (ERLIC) for quantitative analysis of the proteome and phosphoproteome in clinical and biomedical research.

PubMed

Loroch, Stefan; Schommartz, Tim; Brune, Wolfram; Zahedi, René Peiman; Sickmann, Albert

2015-05-01

Quantitative proteomics and phosphoproteomics have become key disciplines in understanding cellular processes. Fundamental research can be done using cell culture providing researchers with virtually infinite sample amounts. In contrast, clinical, pre-clinical and biomedical research is often restricted to minute sample amounts and requires an efficient analysis with only micrograms of protein. To address this issue, we generated a highly sensitive workflow for combined LC-MS-based quantitative proteomics and phosphoproteomics by refining an ERLIC-based 2D phosphoproteomics workflow into an ERLIC-based 3D workflow covering the global proteome as well. The resulting 3D strategy was successfully used for an in-depth quantitative analysis of both, the proteome and the phosphoproteome of murine cytomegalovirus-infected mouse fibroblasts, a model system for host cell manipulation by a virus. In a 2-plex SILAC experiment with 150 μg of a tryptic digest per condition, the 3D strategy enabled the quantification of ~75% more proteins and even ~134% more peptides compared to the 2D strategy. Additionally, we could quantify ~50% more phosphoproteins by non-phosphorylated peptides, concurrently yielding insights into changes on the levels of protein expression and phosphorylation. Beside its sensitivity, our novel three-dimensional ERLIC-strategy has the potential for semi-automated sample processing rendering it a suitable future perspective for clinical, pre-clinical and biomedical research. Copyright © 2015. Published by Elsevier B.V.

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

PubMed Central

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

2014-01-01

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

Find Pairs: The Module for Protein Quantification of the PeakQuant Software Suite

PubMed Central

Eisenacher, Martin; Kohl, Michael; Wiese, Sebastian; Hebeler, Romano; Meyer, Helmut E.

2012-01-01

Abstract Accurate quantification of proteins is one of the major tasks in current proteomics research. To address this issue, a wide range of stable isotope labeling techniques have been developed, allowing one to quantitatively study thousands of proteins by means of mass spectrometry. In this article, the FindPairs module of the PeakQuant software suite is detailed. It facilitates the automatic determination of protein abundance ratios based on the automated analysis of stable isotope-coded mass spectrometric data. Furthermore, it implements statistical methods to determine outliers due to biological as well as technical variance of proteome data obtained in replicate experiments. This provides an important means to evaluate the significance in obtained protein expression data. For demonstrating the high applicability of FindPairs, we focused on the quantitative analysis of proteome data acquired in 14N/15N labeling experiments. We further provide a comprehensive overview of the features of the FindPairs software, and compare these with existing quantification packages. The software presented here supports a wide range of proteomics applications, allowing one to quantitatively assess data derived from different stable isotope labeling approaches, such as 14N/15N labeling, SILAC, and iTRAQ. The software is publicly available at http://www.medizinisches-proteom-center.de/software and free for academic use. PMID:22909347

Stable isotope labelling methods in mass spectrometry-based quantitative proteomics.

PubMed

Chahrour, Osama; Cobice, Diego; Malone, John

2015-09-10

Mass-spectrometry based proteomics has evolved as a promising technology over the last decade and is undergoing a dramatic development in a number of different areas, such as; mass spectrometric instrumentation, peptide identification algorithms and bioinformatic computational data analysis. The improved methodology allows quantitative measurement of relative or absolute protein amounts, which is essential for gaining insights into their functions and dynamics in biological systems. Several different strategies involving stable isotopes label (ICAT, ICPL, IDBEST, iTRAQ, TMT, IPTL, SILAC), label-free statistical assessment approaches (MRM, SWATH) and absolute quantification methods (AQUA) are possible, each having specific strengths and weaknesses. Inductively coupled plasma mass spectrometry (ICP-MS), which is still widely recognised as elemental detector, has recently emerged as a complementary technique to the previous methods. The new application area for ICP-MS is targeting the fast growing field of proteomics related research, allowing absolute protein quantification using suitable elemental based tags. This document describes the different stable isotope labelling methods which incorporate metabolic labelling in live cells, ICP-MS based detection and post-harvest chemical label tagging for protein quantification, in addition to summarising their pros and cons. Copyright © 2015 Elsevier B.V. All rights reserved.

Machine Learning-based Classification of Diffuse Large B-cell Lymphoma Patients by Their Protein Expression Profiles.

PubMed

Deeb, Sally J; Tyanova, Stefka; Hummel, Michael; Schmidt-Supprian, Marc; Cox, Juergen; Mann, Matthias

2015-11-01

Characterization of tumors at the molecular level has improved our knowledge of cancer causation and progression. Proteomic analysis of their signaling pathways promises to enhance our understanding of cancer aberrations at the functional level, but this requires accurate and robust tools. Here, we develop a state of the art quantitative mass spectrometric pipeline to characterize formalin-fixed paraffin-embedded tissues of patients with closely related subtypes of diffuse large B-cell lymphoma. We combined a super-SILAC approach with label-free quantification (hybrid LFQ) to address situations where the protein is absent in the super-SILAC standard but present in the patient samples. Shotgun proteomic analysis on a quadrupole Orbitrap quantified almost 9,000 tumor proteins in 20 patients. The quantitative accuracy of our approach allowed the segregation of diffuse large B-cell lymphoma patients according to their cell of origin using both their global protein expression patterns and the 55-protein signature obtained previously from patient-derived cell lines (Deeb, S. J., D'Souza, R. C., Cox, J., Schmidt-Supprian, M., and Mann, M. (2012) Mol. Cell. Proteomics 11, 77-89). Expression levels of individual segregation-driving proteins as well as categories such as extracellular matrix proteins behaved consistently with known trends between the subtypes. We used machine learning (support vector machines) to extract candidate proteins with the highest segregating power. A panel of four proteins (PALD1, MME, TNFAIP8, and TBC1D4) is predicted to classify patients with low error rates. Highly ranked proteins from the support vector analysis revealed differential expression of core signaling molecules between the subtypes, elucidating aspects of their pathobiology. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Quantitative proteomics of synaptic and nonsynaptic mitochondria: insights for synaptic mitochondrial vulnerability.

PubMed

Stauch, Kelly L; Purnell, Phillip R; Fox, Howard S

2014-05-02

Synaptic mitochondria are essential for maintaining calcium homeostasis and producing ATP, processes vital for neuronal integrity and synaptic transmission. Synaptic mitochondria exhibit increased oxidative damage during aging and are more vulnerable to calcium insult than nonsynaptic mitochondria. Why synaptic mitochondria are specifically more susceptible to cumulative damage remains to be determined. In this study, the generation of a super-SILAC mix that served as an appropriate internal standard for mouse brain mitochondria mass spectrometry based analysis allowed for the quantification of the proteomic differences between synaptic and nonsynaptic mitochondria isolated from 10-month-old mice. We identified a total of 2260 common proteins between synaptic and nonsynaptic mitochondria of which 1629 were annotated as mitochondrial. Quantitative proteomic analysis of the proteins common between synaptic and nonsynaptic mitochondria revealed significant differential expression of 522 proteins involved in several pathways including oxidative phosphorylation, mitochondrial fission/fusion, calcium transport, and mitochondrial DNA replication and maintenance. In comparison to nonsynaptic mitochondria, synaptic mitochondria exhibited increased age-associated mitochondrial DNA deletions and decreased bioenergetic function. These findings provide insights into synaptic mitochondrial susceptibility to damage.

Quantitative Proteomics of Synaptic and Nonsynaptic Mitochondria: Insights for Synaptic Mitochondrial Vulnerability

PubMed Central

2015-01-01

Synaptic mitochondria are essential for maintaining calcium homeostasis and producing ATP, processes vital for neuronal integrity and synaptic transmission. Synaptic mitochondria exhibit increased oxidative damage during aging and are more vulnerable to calcium insult than nonsynaptic mitochondria. Why synaptic mitochondria are specifically more susceptible to cumulative damage remains to be determined. In this study, the generation of a super-SILAC mix that served as an appropriate internal standard for mouse brain mitochondria mass spectrometry based analysis allowed for the quantification of the proteomic differences between synaptic and nonsynaptic mitochondria isolated from 10-month-old mice. We identified a total of 2260 common proteins between synaptic and nonsynaptic mitochondria of which 1629 were annotated as mitochondrial. Quantitative proteomic analysis of the proteins common between synaptic and nonsynaptic mitochondria revealed significant differential expression of 522 proteins involved in several pathways including oxidative phosphorylation, mitochondrial fission/fusion, calcium transport, and mitochondrial DNA replication and maintenance. In comparison to nonsynaptic mitochondria, synaptic mitochondria exhibited increased age-associated mitochondrial DNA deletions and decreased bioenergetic function. These findings provide insights into synaptic mitochondrial susceptibility to damage. PMID:24708184

SILAC-based quantitative proteomic analysis reveals widespread molecular alterations in human skin keratinocytes upon chronic arsenic exposure.

PubMed

Mir, Sartaj Ahmad; Pinto, Sneha M; Paul, Somnath; Raja, Remya; Nanjappa, Vishalakshi; Syed, Nazia; Advani, Jayshree; Renuse, Santosh; Sahasrabuddhe, Nandini A; Prasad, T S Keshava; Giri, Ashok K; Gowda, Harsha; Chatterjee, Aditi

2017-03-01

Chronic exposure to arsenic is associated with dermatological and nondermatological disorders. Consumption of arsenic-contaminated drinking water results in accumulation of arsenic in liver, spleen, kidneys, lungs, and gastrointestinal tract. Although arsenic is cleared from these sites, a substantial amount of residual arsenic is left in keratin-rich tissues including skin. Epidemiological studies suggest the association of skin cancer upon arsenic exposure, however, the mechanism of arsenic-induced carcinogenesis is not completely understood. We developed a cell line based model to understand the molecular mechanisms involved in arsenic-mediated toxicity and carcinogenicity. Human skin keratinocyte cell line, HaCaT, was chronically exposed to 100 nM sodium arsenite over a period of 6 months. We observed an increase in basal ROS levels in arsenic-exposed cells. SILAC-based quantitative proteomics approach resulted in identification of 2111 proteins of which 42 proteins were found to be overexpressed and 54 downregulated (twofold) upon chronic arsenic exposure. Our analysis revealed arsenic-induced overexpression of aldo-keto reductase family 1 member C2 (AKR1C2), aldo-keto reductase family 1 member C3 (AKR1C3), glutamate-cysteine ligase catalytic subunit (GCLC), and NAD(P)H dehydrogenase [quinone] 1 (NQO1) among others. We observed downregulation of several members of the plakin family including periplakin (PPL), envoplakin (EVPL), and involucrin (IVL) that are essential for terminal differentiation of keratinocytes. MRM and Western blot analysis confirmed differential expression of several candidate proteins. Our study provides insights into molecular alterations upon chronic arsenic exposure on skin. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

QuantFusion: Novel Unified Methodology for Enhanced Coverage and Precision in Quantifying Global Proteomic Changes in Whole Tissues.

PubMed

Gunawardena, Harsha P; O'Brien, Jonathon; Wrobel, John A; Xie, Ling; Davies, Sherri R; Li, Shunqiang; Ellis, Matthew J; Qaqish, Bahjat F; Chen, Xian

2016-02-01

Single quantitative platforms such as label-based or label-free quantitation (LFQ) present compromises in accuracy, precision, protein sequence coverage, and speed of quantifiable proteomic measurements. To maximize the quantitative precision and the number of quantifiable proteins or the quantifiable coverage of tissue proteomes, we have developed a unified approach, termed QuantFusion, that combines the quantitative ratios of all peptides measured by both LFQ and label-based methodologies. Here, we demonstrate the use of QuantFusion in determining the proteins differentially expressed in a pair of patient-derived tumor xenografts (PDXs) representing two major breast cancer (BC) subtypes, basal and luminal. Label-based in-spectra quantitative peptides derived from amino acid-coded tagging (AACT, also known as SILAC) of a non-malignant mammary cell line were uniformly added to each xenograft with a constant predefined ratio, from which Ratio-of-Ratio estimates were obtained for the label-free peptides paired with AACT peptides in each PDX tumor. A mixed model statistical analysis was used to determine global differential protein expression by combining complementary quantifiable peptide ratios measured by LFQ and Ratio-of-Ratios, respectively. With minimum number of replicates required for obtaining the statistically significant ratios, QuantFusion uses the distinct mechanisms to "rescue" the missing data inherent to both LFQ and label-based quantitation. Combined quantifiable peptide data from both quantitative schemes increased the overall number of peptide level measurements and protein level estimates. In our analysis of the PDX tumor proteomes, QuantFusion increased the number of distinct peptide ratios by 65%, representing differentially expressed proteins between the BC subtypes. This quantifiable coverage improvement, in turn, not only increased the number of measurable protein fold-changes by 8% but also increased the average precision of quantitative estimates by 181% so that some BC subtypically expressed proteins were rescued by QuantFusion. Thus, incorporating data from multiple quantitative approaches while accounting for measurement variability at both the peptide and global protein levels make QuantFusion unique for obtaining increased coverage and quantitative precision for tissue proteomes. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Recent 5-year Findings and Technological Advances in the Proteomic Study of HIV-associated Disorders.

PubMed

Zhang, Lijun; Jia, Xiaofang; Jin, Jun-O; Lu, Hongzhou; Tan, Zhimi

2017-04-01

Human immunodeficiency virus-1 (HIV-1) mainly relies on host factors to complete its life cycle. Hence, it is very important to identify HIV-regulated host proteins. Proteomics is an excellent technique for this purpose because of its high throughput and sensitivity. In this review, we summarized current technological advances in proteomics, including general isobaric tags for relative and absolute quantitation (iTRAQ) and stable isotope labeling by amino acids in cell culture (SILAC), as well as subcellular proteomics and investigation of posttranslational modifications. Furthermore, we reviewed the applications of proteomics in the discovery of HIV-related diseases and HIV infection mechanisms. Proteins identified by proteomic studies might offer new avenues for the diagnosis and treatment of HIV infection and the related diseases. Copyright © 2017 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

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

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

High-Throughput Quantitative Proteomic Analysis of Dengue Virus Type 2 Infected A549 Cells

PubMed Central

Chiu, Han-Chen; Hannemann, Holger; Heesom, Kate J.; Matthews, David A.; Davidson, Andrew D.

2014-01-01

Disease caused by dengue virus is a global health concern with up to 390 million individuals infected annually worldwide. There are no vaccines or antiviral compounds available to either prevent or treat dengue disease which may be fatal. To increase our understanding of the interaction of dengue virus with the host cell, we analyzed changes in the proteome of human A549 cells in response to dengue virus type 2 infection using stable isotope labelling in cell culture (SILAC) in combination with high-throughput mass spectrometry (MS). Mock and infected A549 cells were fractionated into nuclear and cytoplasmic extracts before analysis to identify proteins that redistribute between cellular compartments during infection and reduce the complexity of the analysis. We identified and quantified 3098 and 2115 proteins in the cytoplasmic and nuclear fractions respectively. Proteins that showed a significant alteration in amount during infection were examined using gene enrichment, pathway and network analysis tools. The analyses revealed that dengue virus infection modulated the amounts of proteins involved in the interferon and unfolded protein responses, lipid metabolism and the cell cycle. The SILAC-MS results were validated for a select number of proteins over a time course of infection by Western blotting and immunofluorescence microscopy. Our study demonstrates for the first time the power of SILAC-MS for identifying and quantifying novel changes in cellular protein amounts in response to dengue virus infection. PMID:24671231

Human borna disease virus infection impacts host proteome and histone lysine acetylation in human oligodendroglia cells

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

Liu, Xia; Department of Neurology, The Fifth People's Hospital of Shanghai, School of Medicine, Fudan University, Shanghai, 200240; Zhao, Libo

2014-09-15

Background: Borna disease virus (BDV) replicates in the nucleus and establishes persistent infections in mammalian hosts. A human BDV strain was used to address the first time, how BDV infection impacts the proteome and histone lysine acetylation (Kac) of human oligodendroglial (OL) cells, thus allowing a better understanding of infection-driven pathophysiology in vitro. Methods: Proteome and histone lysine acetylation were profiled through stable isotope labeling for cell culture (SILAC)-based quantitative proteomics. The quantifiable proteome was annotated using bioinformatics. Histone acetylation changes were validated by biochemistry assays. Results: Post BDV infection, 4383 quantifiable differential proteins were identified and functionally annotated tomore » metabolism pathways, immune response, DNA replication, DNA repair, and transcriptional regulation. Sixteen of the thirty identified Kac sites in core histones presented altered acetylation levels post infection. Conclusions: BDV infection using a human strain impacted the whole proteome and histone lysine acetylation in OL cells. - Highlights: • A human strain of BDV (BDV Hu-H1) was used to infect human oligodendroglial cells (OL cells). • This study is the first to reveal the host proteomic and histone Kac profiles in BDV-infected OL cells. • BDV infection affected the expression of many transcription factors and several HATs and HDACs.« less

A Large-Scale Quantitative Proteomic Approach to Identifying Sulfur Mustard-Induced Protein Phosphorylation Cascades

DTIC Science & Technology

2010-01-01

snapshot of SM-induced toxicity. Over the past few years, innovations in systems biology and biotechnology have led to important advances in our under...perturbations. SILAC has been used to study tumor metastasis (3, 4), focal adhesion- associated proteins, growth factor signaling, and insulin regula- tion (5...stained with colloidal Coomassie blue. After it was destained, the gel lane was excised into six regions, and each region was cut into 1 mm cubes

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

PubMed

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

2016-09-01

Next-generation mass spectrometric (MS) techniques such as SWATH-MS have substantially increased the throughput and reproducibility of proteomic analysis, but ensuring consistent quantification of thousands of peptide analytes across multiple liquid chromatography-tandem MS (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 developed TRIC (http://proteomics.ethz.ch/tric/), a software tool that utilizes fragment-ion data to perform cross-run alignment, consistent peak-picking and quantification for high-throughput targeted proteomics. TRIC reduced the identification error compared to a state-of-the-art SWATH-MS analysis without alignment by more than threefold at constant recall while correcting for highly nonlinear chromatographic effects. On a pulsed-SILAC experiment performed on human induced pluripotent stem cells, TRIC was able to automatically align and quantify thousands of light and heavy isotopic peak groups. Thus, TRIC fills a gap in the pipeline for automated analysis of massively parallel targeted proteomics data sets.

SILAC proteomics of planarians identifies Ncoa5 as a conserved component of pluripotent stem cells.

PubMed

Böser, Alexander; Drexler, Hannes C A; Reuter, Hanna; Schmitz, Henning; Wu, Guangming; Schöler, Hans R; Gentile, Luca; Bartscherer, Kerstin

2013-11-27

Planarian regeneration depends on the presence of pluripotent stem cells in the adult. We developed an in vivo stable isotope labeling by amino acids in cell culture (SILAC) protocol in planarians to identify proteins that are enriched in planarian stem cells. Through a comparison of SILAC proteomes of normal and stem cell-depleted planarians and of a stem cell-enriched population of sorted cells, we identified hundreds of stem cell proteins. One of these is an ortholog of nuclear receptor coactivator-5 (Ncoa5/CIA), which is known to regulate estrogen-receptor-mediated transcription in human cells. We show that Ncoa5 is essential for the maintenance of the pluripotent stem cell population in planarians and that a putative mouse ortholog is expressed in pluripotent cells of the embryo. Our study thus identifies a conserved component of pluripotent stem cells, demonstrating that planarians, in particular, when combined with in vivo SILAC, are a powerful model in stem cell research. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Quantitative proteome-based systematic identification of SIRT7 substrates.

PubMed

Zhang, Chaohua; Zhai, Zichao; Tang, Ming; Cheng, Zhongyi; Li, Tingting; Wang, Haiying; Zhu, Wei-Guo

2017-07-01

SIRT7 is a class III histone deacetylase that is involved in numerous cellular processes. Only six substrates of SIRT7 have been reported thus far, so we aimed to systematically identify SIRT7 substrates using stable-isotope labeling with amino acids in cell culture (SILAC) coupled with quantitative mass spectrometry (MS). Using SIRT7 +/+ and SIRT7 -/- mouse embryonic fibroblasts as our model system, we identified and quantified 1493 acetylation sites in 789 proteins, of which 261 acetylation sites in 176 proteins showed ≥2-fold change in acetylation state between SIRT7 -/- and SIRT7 +/+ cells. These proteins were considered putative SIRT7 substrates and were carried forward for further analysis. We then validated the predictive efficiency of the SILAC-MS experiment by assessing substrate acetylation status in vitro in six predicted proteins. We also performed a bioinformatic analysis of the MS data, which indicated that many of the putative protein substrates were involved in metabolic processes. Finally, we expanded our list of candidate substrates by performing a bioinformatics-based prediction analysis of putative SIRT7 substrates, using our list of putative substrates as a positive training set, and again validated a subset of the proteins in vitro. In summary, we have generated a comprehensive list of SIRT7 candidate substrates. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Large-scale Proteomics Analysis of the Human Kinome

PubMed Central

Oppermann, Felix S.; Gnad, Florian; Olsen, Jesper V.; Hornberger, Renate; Greff, Zoltán; Kéri, György; Mann, Matthias; Daub, Henrik

2009-01-01

Members of the human protein kinase superfamily are the major regulatory enzymes involved in the activity control of eukaryotic signal transduction pathways. As protein kinases reside at the nodes of phosphorylation-based signal transmission, comprehensive analysis of their cellular expression and site-specific phosphorylation can provide important insights into the architecture and functionality of signaling networks. However, in global proteome studies, low cellular abundance of protein kinases often results in rather minor peptide species that are occluded by a vast excess of peptides from other cellular proteins. These analytical limitations create a rationale for kinome-wide enrichment of protein kinases prior to mass spectrometry analysis. Here, we employed stable isotope labeling by amino acids in cell culture (SILAC) to compare the binding characteristics of three kinase-selective affinity resins by quantitative mass spectrometry. The evaluated pre-fractionation tools possessed pyrido[2,3-d]pyrimidine-based kinase inhibitors as immobilized capture ligands and retained considerable subsets of the human kinome. Based on these results, an affinity resin displaying the broadly selective kinase ligand VI16832 was employed to quantify the relative expression of more than 170 protein kinases across three different, SILAC-encoded cancer cell lines. These experiments demonstrated the feasibility of comparative kinome profiling in a compact experimental format. Interestingly, we found high levels of cytoplasmic and low levels of receptor tyrosine kinases in MV4–11 leukemia cells compared with the adherent cancer lines HCT116 and MDA-MB-435S. The VI16832 resin was further exploited to pre-fractionate kinases for targeted phosphoproteomics analysis, which revealed about 1200 distinct phosphorylation sites on more than 200 protein kinases. This hitherto largest survey of site-specific phosphorylation across the kinome significantly expands the basis for functional follow-up studies on protein kinase regulation. In conclusion, the straightforward experimental procedures described here enable different implementations of kinase-selective proteomics with considerable potential for future signal transduction and kinase drug target analysis. PMID:19369195

Triple SILAC quantitative proteomic analysis reveals differential abundance of cell signaling proteins between normal and lung cancer-derived exosomes.

PubMed

Clark, David J; Fondrie, William E; Yang, Austin; Mao, Li

2016-02-05

Exosomes are 30-100 nm sized membrane vesicles released by cells into the extracellular space that mediate intercellular communication via transfer of proteins and other biological molecules. To better understand the role of these microvesicles in lung carcinogenesis, we employed a Triple SILAC quantitative proteomic strategy to examine the differential protein abundance between exosomes derived from an immortalized normal bronchial epithelial cell line and two non-small cell lung cancer (NSCLC) cell lines harboring distinct activating mutations in the cell signaling molecules: Kirsten rat sarcoma viral oncogene homolog (KRAS) or epidermal growth factor receptor (EGFR). In total, we were able to quantify 721 exosomal proteins derived from the three cell lines. Proteins associated with signal transduction, including EGFR, GRB2 and SRC, were enriched in NSCLC exosomes, and could actively regulate cell proliferation in recipient cells. This study's investigation of the NSCLC exosomal proteome has identified enriched protein cargo that can contribute to lung cancer progression, which may have potential clinical implications in biomarker development for patients with NSCLC. The high mortality associated with lung cancer is a result of late-stage diagnosis of the disease. Current screening techniques used for early detection of lung cancer lack the specificity for accurate diagnosis. Exosomes are nano-sized extracellular vesicles, and the increased abundance of select protein cargo in exosomes derived from cancer cells may be used for diagnostic purposes. In this paper, we applied quantitative proteomic analysis to elucidate abundance differences in exosomal protein cargo between two NSCLC cell lines with distinctive oncogene mutations and an immortalized normal bronchial epithelial cell line. This study revealed proteins associated with cell adhesion, the extracellular matrix, and a variety of signaling molecules were enriched in NSCLC exosomes. The present data reveals a protein profile associated with NSCLC exosomes that suggests a role these vesicles have in the progression of lung carcinogenesis, as well as identifies several promising candidates that could be utilized as a multi-marker protein panel in a diagnostic platform for NSCLC. Copyright © 2015 Elsevier B.V. All rights reserved.

Inhibition of Aurora A Kinase by Alisertib Induces Autophagy and Cell Cycle Arrest and Increases Chemosensitivity in Human Hepatocellular Carcinoma HepG2 Cells.

PubMed

Zhu, Qiaohua; Yu, Xinfa; Zhou, Zhi-Wei; Zhou, Chengyu; Chen, Xiao-Wu; Zhou, Shu-Feng

2017-01-01

Aurora A kinase represent a feasible target in cancer therapy. To evaluate the proteomic response of human liver carcinoma cells to alisertib (ALS) and identify the molecular targets of ALS, we examined the effects of ALS on the proliferation, cell cycle, autophagy, apoptosis, and chemosensitivity in HepG2 cells. The stable-isotope labeling by amino acids in cell culture (SILAC) based quantitative proteomic study was performed to evaluate the proteomic response to ALS. Cell cycle distribution and apoptosis were assessed using flow cytometry and autophagy was determined using flow cytometry and confocal microscopy. Our SILAC proteomic study showed that ALS regulated the expression of 914 proteins, with 407 molecules being up-regulated and 507 molecules being down-regulated in HepG2 cells. Ingenuity pathway analysis (IPA) and KEGG pathway analysis identified 146 and 32 signaling pathways were regulated by ALS, respectively, which were associated with cell survival, programmed cell death, and nutrition-energy metabolism. Subsequently, the verification experiments showed that ALS remarkably arrested HepG2 cells in G2/M phase and led to an accumulation of aneuploidy via regulating the expression of key cell cycle regulators. ALS induced a marked autophagy in a concentration- and time-dependent manner via the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR) signaling pathway. Autophagy inhibition promoted the pro-apoptotic effect of ALS, indicating a cyto-protective role of ALS-induced autophagy. ALS increased the chemosensitivity of HepG2 cells to cisplatin and doxorubicin. Taken together, ALS induces autophagy and cell cycle arrest in HepG2 cells via PI3K/Akt/mTOR-mediated pathway. Autophagy inhibition may promote the anticancer effect of ALS and sensitize the chemotherapy in HepG2 cells. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Multivariate proteomic profiling identifies novel accessory proteins of coated vesicles

PubMed Central

Antrobus, Robin; Hirst, Jennifer; Bhumbra, Gary S.; Kozik, Patrycja; Jackson, Lauren P.; Sahlender, Daniela A.

2012-01-01

Despite recent advances in mass spectrometry, proteomic characterization of transport vesicles remains challenging. Here, we describe a multivariate proteomics approach to analyzing clathrin-coated vesicles (CCVs) from HeLa cells. siRNA knockdown of coat components and different fractionation protocols were used to obtain modified coated vesicle-enriched fractions, which were compared by stable isotope labeling of amino acids in cell culture (SILAC)-based quantitative mass spectrometry. 10 datasets were combined through principal component analysis into a “profiling” cluster analysis. Overall, 136 CCV-associated proteins were predicted, including 36 new proteins. The method identified >93% of established CCV coat proteins and assigned >91% correctly to intracellular or endocytic CCVs. Furthermore, the profiling analysis extends to less well characterized types of coated vesicles, and we identify and characterize the first AP-4 accessory protein, which we have named tepsin. Finally, our data explain how sequestration of TACC3 in cytosolic clathrin cages causes the severe mitotic defects observed in auxilin-depleted cells. The profiling approach can be adapted to address related cell and systems biological questions. PMID:22472443

Suberoylanilide hydroxamic acid treatment reveals crosstalks among proteome, ubiquitylome and acetylome in non-small cell lung cancer A549 cell line.

PubMed

Wu, Quan; Cheng, Zhongyi; Zhu, Jun; Xu, Weiqing; Peng, Xiaojun; Chen, Chuangbin; Li, Wenting; Wang, Fengsong; Cao, Lejie; Yi, Xingling; Wu, Zhiwei; Li, Jing; Fan, Pingsheng

2015-03-31

Suberoylanilide hydroxamic acid (SAHA) is a well-known histone deacetylase (HDAC) inhibitor and has been used as practical therapy for breast cancer and non-small cell lung cancer (NSCLC). It is previously demonstrated that SAHA treatment could extensively change the profile of acetylome and proteome in cancer cells. However, little is known about the impact of SAHA on other protein modifications and the crosstalks among different modifications and proteome, hindering the deep understanding of SAHA-mediated cancer therapy. In this work, by using SILAC technique, antibody-based affinity enrichment and high-resolution LC-MS/MS analysis, we investigated quantitative proteome, acetylome and ubiquitylome as well as crosstalks among the three datasets in A549 cells toward SAHA treatment. In total, 2968 proteins, 1099 acetylation sites and 1012 ubiquitination sites were quantified in response to SAHA treatment, respectively. With the aid of intensive bioinformatics, we revealed that the proteome and ubiquitylome were negatively related upon SAHA treatment. Moreover, the impact of SAHA on acetylome resulted in 258 up-regulated and 99 down-regulated acetylation sites at the threshold of 1.5 folds. Finally, we identified 55 common sites with both acetylation and ubiquitination, among which ubiquitination level in 43 sites (78.2%) was positive related to acetylation level.

Quantitative Proteomic Analysis of BHK-21 Cells Infected with Foot-and-Mouth Disease Virus Serotype Asia 1.

PubMed

Guo, Hui-Chen; Jin, Ye; Han, Shi-Chong; Sun, Shi-Qi; Wei, Yan-Quan; Liu, Xian-Ji; Feng, Xia; Liu, Ding Xiang; Liu, Xiang-Tao

2015-01-01

Stable isotope labeling with amino acids in cell culture (SILAC) was used to quantitatively study the host cell gene expression profile, in order to achieve an unbiased overview of the protein expression changes in BHK-21 cells infected with FMDV serotype Asia 1. The SILAC-based approach identified overall 2,141 proteins, 153 of which showed significant alteration in the expression level 6 h post FMDV infection (57 up-regulated and 96 down-regulated). Among these proteins, six cellular proteins, including three down-regulated (VPS28, PKR, EVI5) and three up-regulated (LYPLA1, SEC62 and DARs), were selected according to the significance of the changes and/or the relationship with PKR. The expression level and pattern of the selected proteins were validated by immunoblotting and confocal microscopy. Furthermore, the functions of these cellular proteins were assessed by small interfering RNA-mediated depletion, and their functional importance in the replication of FMDV was demonstrated by western blot, reverse transcript PCR (RT-PCR) and 50% Tissue Culture Infective Dose (TCID50). The results suggest that FMDV infection may have effects on the expression of specific cellular proteins to create more favorable conditions for FMDV infection. This study provides novel data that can be utilized to understand the interactions between FMDV and the host cell.

In vivo relative quantitative proteomics reveals HMGB1 as a downstream mediator of oestrogen-stimulated keratinocyte migration.

PubMed

Shin, Jung U; Noh, Ji Yeon; Lee, Ju Hee; Lee, Won Jai; Yoo, Jong Shin; Kim, Jin Young; Kim, Hyeran; Jung, Inhee; Jin, Shan; Lee, Kwang Hoon

2015-06-01

It is known that oestrogen influences skin wound healing by modulating the inflammatory response, cytokine expression and extracellular matrix deposition; accelerating re-epithelialization; and stimulating angiogenesis. To identify novel proteins associated with effects of oestrogen on keratinocyte, stable isotope labelling by amino acids in cell culture (SILAC)-based mass spectrometry was performed. Using SILAC, quantification of 1085 proteins was achieved. Among these proteins, 60 proteins were upregulated and 32 proteins were downregulated. Among significantly upregulated proteins, high-mobility group protein B1 (HMGB1) has been further evaluated for its role in the effect of oestrogen on keratinocytes. HMGB1 expression was strongly induced in oestrogen-treated keratinocytes in dose- and time-dependent manner. Further, HMGB1 was able to significantly accelerate the rate of HaCaT cell migration. To determine whether HMGB1 is involved in E2-induced HaCaT cell migration, cells were transfected with HMGB1 siRNA. Knockdown of HMGB1 blocked oestrogen-induced keratinocyte migration. Collectively, these experiments demonstrate that HMGB1 is a novel downstream mediator of oestrogen-stimulated keratinocyte migration. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

In vivo SILAC-based proteomics reveals phosphoproteome changes during mouse skin carcinogenesis.

PubMed

Zanivan, Sara; Meves, Alexander; Behrendt, Kristina; Schoof, Erwin M; Neilson, Lisa J; Cox, Jürgen; Tang, Hao R; Kalna, Gabriela; van Ree, Janine H; van Deursen, Jan M; Trempus, Carol S; Machesky, Laura M; Linding, Rune; Wickström, Sara A; Fässler, Reinhard; Mann, Matthias

2013-02-21

Cancer progresses through distinct stages, and mouse models recapitulating traits of this progression are frequently used to explore genetic, morphological, and pharmacological aspects of tumor development. To complement genomic investigations of this process, we here quantify phosphoproteomic changes in skin cancer development using the SILAC mouse technology coupled to high-resolution mass spectrometry. We distill protein expression signatures from our data that distinguish between skin cancer stages. A distinct phosphoproteome of the two stages of cancer progression is identified that correlates with perturbed cell growth and implicates cell adhesion as a major driver of malignancy. Importantly, integrated analysis of phosphoproteomic data and prediction of kinase activity revealed PAK4-PKC/SRC network to be highly deregulated in SCC but not in papilloma. This detailed molecular picture, both at the proteome and phosphoproteome level, will prove useful for the study of mechanisms of tumor progression. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Quantitative proteomics and network analysis of SSA1 and SSB1 deletion mutants reveals robustness of chaperone HSP70 network in Saccharomyces cerevisiae.

PubMed

Jarnuczak, Andrew F; Eyers, Claire E; Schwartz, Jean-Marc; Grant, Christopher M; Hubbard, Simon J

2015-09-01

Molecular chaperones play an important role in protein homeostasis and the cellular response to stress. In particular, the HSP70 chaperones in yeast mediate a large volume of protein folding through transient associations with their substrates. This chaperone interaction network can be disturbed by various perturbations, such as environmental stress or a gene deletion. Here, we consider deletions of two major chaperone proteins, SSA1 and SSB1, from the chaperone network in Sacchromyces cerevisiae. We employ a SILAC-based approach to examine changes in global and local protein abundance and rationalise our results via network analysis and graph theoretical approaches. Although the deletions result in an overall increase in intracellular protein content, correlated with an increase in cell size, this is not matched by substantial changes in individual protein concentrations. Despite the phenotypic robustness to deletion of these major hub proteins, it cannot be simply explained by the presence of paralogues. Instead, network analysis and a theoretical consideration of folding workload suggest that the robustness to perturbation is a product of the overall network structure. This highlights how quantitative proteomics and systems modelling can be used to rationalise emergent network properties, and how the HSP70 system can accommodate the loss of major hubs. © 2015 The Authors. PROTEOMICS published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomic response to 5,6-dimethylxanthenone 4-acetic acid (DMXAA, vadimezan) in human non-small cell lung cancer A549 cells determined by the stable-isotope labeling by amino acids in cell culture (SILAC) approach

PubMed Central

Pan, Shu-Ting; Zhou, Zhi-Wei; He, Zhi-Xu; Zhang, Xueji; Yang, Tianxin; Yang, Yin-Xue; Wang, Dong; Qiu, Jia-Xuan; Zhou, Shu-Feng

2015-01-01

5,6-Dimethylxanthenone 4-acetic acid (DMXAA), also known as ASA404 and vadimezan, is a potent tumor blood vessel-disrupting agent and cytokine inducer used alone or in combination with other cytotoxic agents for the treatment of non-small cell lung cancer (NSCLC) and other cancers. However, the latest Phase III clinical trial has shown frustrating outcomes in the treatment of NSCLC, since the therapeutic targets and underlying mechanism for the anticancer effect of DMXAA are not yet fully understood. This study aimed to examine the proteomic response to DMXAA and unveil the global molecular targets and possible mechanisms for the anticancer effect of DMXAA in NSCLC A549 cells using a stable-isotope labeling by amino acids in cell culture (SILAC) approach. The proteomic data showed that treatment with DMXAA modulated the expression of 588 protein molecules in A549 cells, with 281 protein molecules being up regulated and 306 protein molecules being downregulated. Ingenuity pathway analysis (IPA) identified 256 signaling pathways and 184 cellular functional proteins that were regulated by DMXAA in A549 cells. These targeted molecules and signaling pathways were mostly involved in cell proliferation and survival, redox homeostasis, sugar, amino acid and nucleic acid metabolism, cell migration, and invasion and programed cell death. Subsequently, the effects of DMXAA on cell cycle distribution, apoptosis, autophagy, and reactive oxygen species (ROS) generation were experimentally verified. Flow cytometric analysis showed that DMXAA significantly induced G1 phase arrest in A549 cells. Western blotting assays demonstrated that DMXAA induced apoptosis via a mitochondria-dependent pathway and promoted autophagy, as indicated by the increased level of cytosolic cytochrome c, activation of caspase 3, and enhanced expression of beclin 1 and microtubule-associated protein 1A/1B-light chain 3 (LC3-II) in A549 cells. Moreover, DMXAA significantly promoted intracellular ROS generation in A549 cells. Collectively, this SILAC study quantitatively evaluates the proteomic response to treatment with DMXAA that helps to globally identify the potential molecular targets and elucidate the underlying mechanism of DMXAA in the treatment of NSCLC. PMID:25733813

Evaluation of Drosophila metabolic labeling strategies for in vivo quantitative proteomic analyses with applications to early pupa formation and amino acid starvation.

PubMed

Chang, Ying-Che; Tang, Hong-Wen; Liang, Suh-Yuen; Pu, Tsung-Hsien; Meng, Tzu-Ching; Khoo, Kay-Hooi; Chen, Guang-Chao

2013-05-03

Although stable isotope labeling by amino acids in cell culture (SILAC)-based quantitative proteomics was first developed as a cell culture-based technique, stable isotope-labeled amino acids have since been successfully introduced in vivo into select multicellular model organisms by manipulating the feeding diets. An earlier study by others has demonstrated that heavy lysine labeled Drosophila melanogaster can be derived by feeding with an exclusive heavy lysine labeled yeast diet. In this work, we have further evaluated the use of heavy lysine and/or arginine for metabolic labeling of fruit flies, with an aim to determine its respective quantification accuracy and versatility. In vivo conversion of heavy lysine and/or heavy arginine to several nonessential amino acids was observed in labeled flies, leading to distorted isotope pattern and underestimated heavy to light ratio. These quantification defects can nonetheless be rectified at protein level using the normalization function. The only caveat is that such a normalization strategy may not be suitable for every biological application, particularly when modified peptides need to be individually quantified at peptide level. In such cases, we showed that peptide ratios calculated from the summed intensities of all isotope peaks are less affected by the heavy amino acid conversion and therefore less sequence-dependent and more reliable. Applying either the single Lys8 or double Lys6/Arg10 metabolic labeling strategy to flies, we quantitatively mapped the proteomic changes during the onset of metamorphosis and upon amino acid deprivation. The expression of a number of steroid hormone 20-hydroxyecdysone regulated proteins was found to be changed significantly during larval-pupa transition, while several subunits of the V-ATPase complex and components regulating actomyosin were up-regulated under starvation-induced autophagy conditions.

NeuCode Labeling in Nematodes: Proteomic and Phosphoproteomic Impact of Ascaroside Treatment in Caenorhabditis elegans*

PubMed Central

Rhoads, Timothy W.; Prasad, Aman; Kwiecien, Nicholas W.; Merrill, Anna E.; Zawack, Kelson; Westphall, Michael S.; Schroeder, Frank C.; Kimble, Judith; Coon, Joshua J.

2015-01-01

The nematode Caenorhabditis elegans is an important model organism for biomedical research. We previously described NeuCode stable isotope labeling by amino acids in cell culture (SILAC), a method for accurate proteome quantification with potential for multiplexing beyond the limits of traditional stable isotope labeling by amino acids in cell culture. Here we apply NeuCode SILAC to profile the proteomic and phosphoproteomic response of C. elegans to two potent members of the ascaroside family of nematode pheromones. By consuming labeled E. coli as part of their diet, C. elegans nematodes quickly and easily incorporate the NeuCode heavy lysine isotopologues by the young adult stage. Using this approach, we report, at high confidence, one of the largest proteomic and phosphoproteomic data sets to date in C. elegans: 6596 proteins at a false discovery rate ≤ 1% and 6620 phosphorylation isoforms with localization probability ≥75%. Our data reveal a post-translational signature of pheromone sensing that includes many conserved proteins implicated in longevity and response to stress. PMID:26392051

Systems-level identification of PKA-dependent signaling in epithelial cells.

PubMed

Isobe, Kiyoshi; Jung, Hyun Jun; Yang, Chin-Rang; Claxton, J'Neka; Sandoval, Pablo; Burg, Maurice B; Raghuram, Viswanathan; Knepper, Mark A

2017-10-17

G protein stimulatory α-subunit (G αs )-coupled heptahelical receptors regulate cell processes largely through activation of protein kinase A (PKA). To identify signaling processes downstream of PKA, we deleted both PKA catalytic subunits using CRISPR-Cas9, followed by a "multiomic" analysis in mouse kidney epithelial cells expressing the G αs -coupled V2 vasopressin receptor. RNA-seq (sequencing)-based transcriptomics and SILAC (stable isotope labeling of amino acids in cell culture)-based quantitative proteomics revealed a complete loss of expression of the water-channel gene Aqp2 in PKA knockout cells. SILAC-based quantitative phosphoproteomics identified 229 PKA phosphorylation sites. Most of these PKA targets are thus far unannotated in public databases. Surprisingly, 1,915 phosphorylation sites with the motif x-(S/T)-P showed increased phosphooccupancy, pointing to increased activity of one or more MAP kinases in PKA knockout cells. Indeed, phosphorylation changes associated with activation of ERK2 were seen in PKA knockout cells. The ERK2 site is downstream of a direct PKA site in the Rap1GAP, Sipa1l1, that indirectly inhibits Raf1. In addition, a direct PKA site that inhibits the MAP kinase kinase kinase Map3k5 (ASK1) is upstream of JNK1 activation. The datasets were integrated to identify a causal network describing PKA signaling that explains vasopressin-mediated regulation of membrane trafficking and gene transcription. The model predicts that, through PKA activation, vasopressin stimulates AQP2 exocytosis by inhibiting MAP kinase signaling. The model also predicts that, through PKA activation, vasopressin stimulates Aqp2 transcription through induction of nuclear translocation of the acetyltransferase EP300, which increases histone H3K27 acetylation of vasopressin-responsive genes (confirmed by ChIP-seq).

Plant proteome analysis: a 2006 update.

PubMed

Jorrín, Jesús V; Maldonado, Ana M; Castillejo, Ma Angeles

2007-08-01

This 2006 'Plant Proteomics Update' is a continuation of the two previously published in 'Proteomics' by 2004 (Canovas et al., Proteomics 2004, 4, 285-298) and 2006 (Rossignol et al., Proteomics 2006, 6, 5529-5548) and it aims to bring up-to-date the contribution of proteomics to plant biology on the basis of the original research papers published throughout 2006, with references to those appearing last year. According to the published papers and topics addressed, we can conclude that, as observed for the three previous years, there has been a quantitative, but not qualitative leap in plant proteomics. The full potential of proteomics is far from being exploited in plant biology research, especially if compared to other organisms, mainly yeast and humans, and a number of challenges, mainly technological, remain to be tackled. The original papers published last year numbered nearly 100 and deal with the proteome of at least 26 plant species, with a high percentage for Arabidopsis thaliana (28) and rice (11). Scientific objectives ranged from proteomic analysis of organs/tissues/cell suspensions (57) or subcellular fractions (29), to the study of plant development (12), the effect of hormones and signalling molecules (8) and response to symbionts (4) and stresses (27). A small number of contributions have covered PTMs (8) and protein interactions (4). 2-DE (specifically IEF-SDS-PAGE) coupled to MS still constitutes the almost unique platform utilized in plant proteome analysis. The application of gel-free protein separation methods and 'second generation' proteomic techniques such as multidimensional protein identification technology (MudPIT), and those for quantitative proteomics including DIGE, isotope-coded affinity tags (ICAT), iTRAQ and stable isotope labelling by amino acids in cell culture (SILAC) still remains anecdotal. This review is divided into seven sections: Introduction, Methodology, Subcellular proteomes, Development, Responses to biotic and abiotic stresses, PTMs and Protein interactions. Section 8 summarizes the major pitfalls and challenges of plant proteomics.

Quantitative nucleolar proteomics reveals nuclear re-organization during stress- induced senescence in mouse fibroblast

PubMed Central

2011-01-01

Background Nucleolus is the most prominent mammalian organelle within the nucleus which is also the site for ribosomal biogenesis. There have been many reports indicating the involvement of nucleolus in the process of aging. Several proteins related to aging have been shown to localize in the nucleolus, which suggests the role of this organelle in senescence. Results In this study, we used quantitative mass spectrometry to map the flux of proteins into and out of the nucleolus during the induction of senescence in cultured mammalian cells. Changes in the abundance of 344 nucleolar proteins in sodium butyrate-induced senescence in NIH3T3 cells were studied by SILAC (stable isotope labeling by amino acids in cell culture)-based mass spectrometry. Biochemically, we have validated the proteomic results and confirmed that B23 (nucleophosmin) protein was down-regulated, while poly (ADP-ribose) polymerase (PARP) and nuclear DNA helicase II (NDH II/DHX9/RHA) were up-regulated in the nucleolus upon treatment with sodium butyrate. Accumulation of chromatin in the nucleolus was also observed, by both proteomics and microscopy, in sodium butyrate-treated cells. Similar observations were found in other models of senescence, namely, in mitoxantrone- (MTX) treated cells and primary fibroblasts from the Lamin A knockout mice. Conclusion Our data indicate an extensive nuclear organization during senescence and suggest that the redistribution of B23 protein and chromatin can be used as an important marker for senescence. PMID:21835027

Dual phosphoproteomics and chemical proteomics analysis of erlotinib and gefitinib interference in acute myeloid leukemia cells.

PubMed

Weber, Christoph; Schreiber, Thiemo B; Daub, Henrik

2012-02-02

Small molecule inhibitors of protein kinases have emerged as a major class of therapeutic agents for the treatment of hematological malignancies. Both in vitro studies and patient case reports suggest therapeutic potential of the clinical kinase inhibitors erlotinib and gefitinib in acute myeloid leukemia (AML). The drugs' cellular modes of action in AML warrant further investigation as their primary therapeutic target, the epidermal growth factor receptor, is not expressed. We therefore performed SILAC-based quantitative mass spectrometry analyses to a depth of 10,975 distinct phosphorylation sites to characterize the phosphoproteome of KG1 AML cells and its regulation upon erlotinib and gefitinib treatment. Less than 50 site-specific phosphorylations changed significantly, indicating rather specific interference with AML cell signaling. Many drug-induced changes occurred within a network of tyrosine phosphorylated proteins that included Src family kinases (SFKs) and the tyrosine kinases Btk and Syk. We further performed quantitative chemical proteomics in KG1 cell extracts and identified SFKs and Btk as direct cellular targets of both erlotinib and gefitinib. Taken together, our data suggest that cellular perturbation of SFKs and/or Btk translates into rather specific signal transduction inhibition, which in turn contributes to the antileukemic activity of erlotinib and gefitinib in AML. Copyright © 2011 Elsevier B.V. All rights reserved.

Time-resolved Analysis of Proteome Dynamics by Tandem Mass Tags and Stable Isotope Labeling in Cell Culture (TMT-SILAC) Hyperplexing*

PubMed Central

Welle, Kevin A.; Zhang, Tian; Hryhorenko, Jennifer R.; Shen, Shichen; Qu, Jun; Ghaemmaghami, Sina

2016-01-01

Recent advances in mass spectrometry have enabled system-wide analyses of protein turnover. By globally quantifying the kinetics of protein clearance and synthesis, these methodologies can provide important insights into the regulation of the proteome under varying cellular and environmental conditions. To facilitate such analyses, we have employed a methodology that combines metabolic isotopic labeling (Stable Isotope Labeling in Cell Culture - SILAC) with isobaric tagging (Tandem Mass Tags - TMT) for analysis of multiplexed samples. The fractional labeling of multiple time-points can be measured in a single mass spectrometry run, providing temporally resolved measurements of protein turnover kinetics. To demonstrate the feasibility of the approach, we simultaneously measured the kinetics of protein clearance and accumulation for more than 3000 proteins in dividing and quiescent human fibroblasts and verified the accuracy of the measurements by comparison to established non-multiplexed approaches. The results indicate that upon reaching quiescence, fibroblasts compensate for lack of cellular growth by globally downregulating protein synthesis and upregulating protein degradation. The described methodology significantly reduces the cost and complexity of temporally-resolved dynamic proteomic experiments and improves the precision of proteome-wide turnover data. PMID:27765818

A proteomic screen reveals the mitochondrial outer membrane protein Mdm34p as an essential target of the F-box protein Mdm30p.

PubMed

Ota, Kazuhisa; Kito, Keiji; Okada, Satoshi; Ito, Takashi

2008-10-01

Ubiquitination plays various critical roles in eukaryotic cellular regulation and is mediated by a cascade of enzymes including ubiquitin protein ligase (E3). The Skp1-Cullin-F-box protein complex comprises the largest E3 family, in each member of which a unique F-box protein binds its targets to define substrate specificity. Although genome sequencing uncovers a growing number of F-box proteins, most of them have remained as "orphans" because of the difficulties in identification of their substrates. To address this issue, we tested a quantitative proteomic approach by combining the stable isotope labeling by amino acids in cell culture (SILAC), parallel affinity purification (PAP) that we had developed for efficient enrichment of ubiquitinated proteins, and mass spectrometry (MS). We applied this SILAC-PAP-MS approach to compare ubiquitinated proteins between yeast cells with and without over-expressed Mdm30p, an F-box protein implicated in mitochondrial morphology. Consequently, we identified the mitochondrial outer membrane protein Mdm34p as a target of Mdm30p. Furthermore, we found that mitochondrial defects induced by deletion of MDM30 are not only recapitulated by a mutant Mdm34p defective in interaction with Mdm30p but alleviated by ubiquitination-mimicking forms of Mdm34p. These results indicate that Mdm34p is a physiologically important target of Mdm30p.

RECENT ADVANCES IN QUANTITATIVE NEUROPROTEOMICS

PubMed Central

Craft, George E; Chen, Anshu; Nairn, Angus C

2014-01-01

The field of proteomics is undergoing rapid development in a number of different areas including improvements in mass spectrometric platforms, peptide identification algorithms and bioinformatics. In particular, new and/or improved approaches have established robust methods that not only allow for in-depth and accurate peptide and protein identification and modification, but also allow for sensitive measurement of relative or absolute quantitation. These methods are beginning to be applied to the area of neuroproteomics, but the central nervous system poses many specific challenges in terms of quantitative proteomics, given the large number of different neuronal cell types that are intermixed and that exhibit distinct patterns of gene and protein expression. This review highlights the recent advances that have been made in quantitative neuroproteomics, with a focus on work published over the last five years that applies emerging methods to normal brain function as well as to various neuropsychiatric disorders including schizophrenia and drug addiction as well as of neurodegenerative diseases including Parkinson’s disease and Alzheimer’s disease. While older methods such as two-dimensional polyacrylamide electrophoresis continued to be used, a variety of more in-depth MS-based approaches including both label (ICAT, iTRAQ, TMT, SILAC, SILAM), label-free (label-free, MRM, SWATH) and absolute quantification methods, are rapidly being applied to neurobiological investigations of normal and diseased brain tissue as well as of cerebrospinal fluid (CSF). While the biological implications of many of these studies remain to be clearly established, that there is a clear need for standardization of experimental design and data analysis, and that the analysis of protein changes in specific neuronal cell types in the central nervous system remains a serious challenge, it appears that the quality and depth of the more recent quantitative proteomics studies is beginning to shed light on a number of aspects of neuroscience that relates to normal brain function as well as of the changes in protein expression and regulation that occurs in neuropsychiatric and neurodegenerative disorders. PMID:23623823

Recent advances in quantitative neuroproteomics.

PubMed

Craft, George E; Chen, Anshu; Nairn, Angus C

2013-06-15

The field of proteomics is undergoing rapid development in a number of different areas including improvements in mass spectrometric platforms, peptide identification algorithms and bioinformatics. In particular, new and/or improved approaches have established robust methods that not only allow for in-depth and accurate peptide and protein identification and modification, but also allow for sensitive measurement of relative or absolute quantitation. These methods are beginning to be applied to the area of neuroproteomics, but the central nervous system poses many specific challenges in terms of quantitative proteomics, given the large number of different neuronal cell types that are intermixed and that exhibit distinct patterns of gene and protein expression. This review highlights the recent advances that have been made in quantitative neuroproteomics, with a focus on work published over the last five years that applies emerging methods to normal brain function as well as to various neuropsychiatric disorders including schizophrenia and drug addiction as well as of neurodegenerative diseases including Parkinson's disease and Alzheimer's disease. While older methods such as two-dimensional polyacrylamide electrophoresis continued to be used, a variety of more in-depth MS-based approaches including both label (ICAT, iTRAQ, TMT, SILAC, SILAM), label-free (label-free, MRM, SWATH) and absolute quantification methods, are rapidly being applied to neurobiological investigations of normal and diseased brain tissue as well as of cerebrospinal fluid (CSF). While the biological implications of many of these studies remain to be clearly established, that there is a clear need for standardization of experimental design and data analysis, and that the analysis of protein changes in specific neuronal cell types in the central nervous system remains a serious challenge, it appears that the quality and depth of the more recent quantitative proteomics studies is beginning to shed light on a number of aspects of neuroscience that relates to normal brain function as well as of the changes in protein expression and regulation that occurs in neuropsychiatric and neurodegenerative disorders. Copyright © 2013. Published by Elsevier Inc.

SPECHT - single-stage phosphopeptide enrichment and stable-isotope chemical tagging: quantitative phosphoproteomics of insulin action in muscle.

PubMed

Kettenbach, Arminja N; Sano, Hiroyuki; Keller, Susanna R; Lienhard, Gustav E; Gerber, Scott A

2015-01-30

The study of cellular signaling remains a significant challenge for translational and clinical research. In particular, robust and accurate methods for quantitative phosphoproteomics in tissues and tumors represent significant hurdles for such efforts. In the present work, we design, implement and validate a method for single-stage phosphopeptide enrichment and stable isotope chemical tagging, or SPECHT, that enables the use of iTRAQ, TMT and/or reductive dimethyl-labeling strategies to be applied to phosphoproteomics experiments performed on primary tissue. We develop and validate our approach using reductive dimethyl-labeling and HeLa cells in culture, and find these results indistinguishable from data generated from more traditional SILAC-labeled HeLa cells mixed at the cell level. We apply the SPECHT approach to the quantitative analysis of insulin signaling in a murine myotube cell line and muscle tissue, identify known as well as new phosphorylation events, and validate these phosphorylation sites using phospho-specific antibodies. Taken together, our work validates chemical tagging post-single-stage phosphoenrichment as a general strategy for studying cellular signaling in primary tissues. Through the use of a quantitatively reproducible, proteome-wide phosphopeptide enrichment strategy, we demonstrated the feasibility of post-phosphopeptide purification chemical labeling and tagging as an enabling approach for quantitative phosphoproteomics of primary tissues. Using reductive dimethyl labeling as a generalized chemical tagging strategy, we compared the performance of post-phosphopeptide purification chemical tagging to the well established community standard, SILAC, in insulin-stimulated tissue culture cells. We then extended our method to the analysis of low-dose insulin signaling in murine muscle tissue, and report on the analytical and biological significance of our results. Copyright © 2014 Elsevier B.V. All rights reserved.

Preparation of Conjugates of Cytotoxic Lupane Triterpenes with Biotin.

PubMed

Soural, Miroslav; Hodon, Jiri; Dickinson, Niall J; Sidova, Veronika; Gurska, Sona; Dzubak, Petr; Hajduch, Marian; Sarek, Jan; Urban, Milan

2015-12-16

To better understand the mechanism of action of antitumor triterpenes, we are developing methods to identify their molecular targets. A promising method is based on combination of quantitative proteomics with SILAC and uses active compounds anchored to magnetic beads via biotin-streptavidin interaction. We developed a simple and fast solid-phase synthetic technique to connect terpenes to biotin through a linker. Betulinic acid was biotinylated from three different conjugation sites for use as a standard validation tool since many molecular targets of this triterpene are already known. Then, a set of four other cytotoxic triterpenoids was biotinylated. Biotinylated terpenes were similarly cytotoxic to their nonbiotinylated parents, which suggests that the target identification should not be influenced by linker or biotin. The developed solid-phase synthetic approach is the first attempt to use solid-phase synthesis to connect active triterpenes to biotin and is applicable as a general procedure for routine conjugation of triterpenes with other molecules of choice.

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

PubMed

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

2012-12-01

What's known on the subject? and What does the study add? Interstitial cystitis (IC) is a prevalent and debilitating pelvic disorder generally accompanied by chronic pain combined with chronic urinating problems. Over one million Americans are affected, especially middle-aged women. However, its aetiology or mechanism remains unclear. No efficient drug has been provided to patients. Several urinary biomarker candidates have been identified for IC; among the most promising is antiproliferative factor (APF), whose biological activity is detectable in urine specimens from >94% of patients with both ulcerative and non-ulcerative IC. The present study identified several important mediators of the effect of APF on bladder cell physiology, suggesting several candidate drug targets against IC. In an attempt to identify potential proteins and genes regulated by APF in vivo, and to possibly expand the APF-regulated network identified by stable isotope labelling by amino acids in cell culture (SILAC), we performed an integration analysis of our own SILAC data and the microarray data of Gamper et al. (2009) BMC Genomics 10: 199. Notably, two of the proteins (i.e. MAPKSP1 and GSPT1) that are down-regulated by APF are involved in the activation of mTORC1, suggesting that the mammalian target of rapamycin (mTOR) pathway is potentially a critical pathway regulated by APF in vivo. Several components of the mTOR pathway are currently being studied as potential therapeutic targets in other diseases. Our analysis suggests that this pathway might also be relevant in the design of diagnostic tools and medications targeting IC. • To enhance our understanding of the interstitial cystitis urine biomarker antiproliferative factor (APF), as well as interstitial cystitis biology more generally at the systems level, we reanalyzed recently published large-scale quantitative proteomics and in vivo transcriptomics data sets using an integration analysis tool that we have developed. • To identify more differentially expressed genes with a lower false discovery rate from a previously published microarray data set, an integrative hypothesis-testing statistical approach was applied. • For validation experiments, expression and phosphorylation levels of select proteins were evaluated by western blotting. • Integration analysis of this transcriptomics data set with our own quantitative proteomics data set identified 10 genes that are potentially regulated by APF in vivo from 4140 differentially expressed genes identified with a false discovery rate of 1%. • Of these, five (i.e. JUP, MAPKSP1, GSPT1, PTGS2/COX-2 and XPOT) were found to be prominent after network modelling of the common genes identified in the proteomics and microarray studies. • This molecular signature reflects the biological processes of cell adhesion, cell proliferation and inflammation, which is consistent with the known physiological effects of APF. • Lastly, we found the mammalian target of rapamycin pathway was down-regulated in response to APF. • This unbiased integration analysis of in vitro quantitative proteomics data with in vivo quantitative transcriptomics data led to the identification of potential downstream mediators of the APF signal transduction pathway. © 2012 THE AUTHORS. BJU INTERNATIONAL © 2012 BJU INTERNATIONAL.

Quantitative interaction screen of telomeric repeat-containing RNA reveals novel TERRA regulators

PubMed Central

Scheibe, Marion; Arnoult, Nausica; Kappei, Dennis; Buchholz, Frank; Decottignies, Anabelle; Butter, Falk; Mann, Matthias

2013-01-01

Telomeres are actively transcribed into telomeric repeat-containing RNA (TERRA), which has been implicated in the regulation of telomere length and heterochromatin formation. Here, we applied quantitative mass spectrometry (MS)–based proteomics to obtain a high-confidence interactome of TERRA. Using SILAC-labeled nuclear cell lysates in an RNA pull-down experiment and two different salt conditions, we distinguished 115 proteins binding specifically to TERRA out of a large set of background binders. While TERRA binders identified in two previous studies showed little overlap, using quantitative mass spectrometry we obtained many candidates reported in these two studies. To test whether novel candidates found here are involved in TERRA regulation, we performed an esiRNA-based interference analysis for 15 of them. Knockdown of 10 genes encoding candidate proteins significantly affected total cellular levels of TERRA, and RNAi of five candidates perturbed TERRA recruitment to telomeres. Notably, depletion of SRRT/ARS2, involved in miRNA processing, up-regulated both total and telomere-bound TERRA. Conversely, knockdown of MORF4L2, a component of the NuA4 histone acetyltransferase complex, reduced TERRA levels both globally and for telomere-bound TERRA. We thus identified new proteins involved in the homeostasis and telomeric abundance of TERRA, extending our knowledge of TERRA regulation. PMID:23921659

Assessing the impact of minimizing arginine conversion in fully defined SILAC culture medium in human embryonic stem cells.

PubMed

Scheerlinck, Ellen; Van Steendam, Katleen; Daled, Simon; Govaert, Elisabeth; Vossaert, Liesbeth; Meert, Paulien; Van Nieuwerburgh, Filip; Van Soom, Ann; Peelman, Luc; De Sutter, Petra; Heindryckx, Björn; Dhaenens, Maarten; Deforce, Dieter

2016-10-01

We present a fully defined culture system (adapted Essential8 TM [E8 TM ] medium in combination with vitronectin) for human embryonic stem cells that can be used for SILAC purposes. Although a complete incorporation of the labels was observed after 4 days in culture, over 90% of precursors showed at least 10% conversion. To reduce this arginine conversion, E8 TM medium was modified by adding (1) l-proline, (2) l-ornithine, (3) N ω -hydroxy-nor-l-arginine acetate, or by (4) lowering the arginine concentration. Reduction of arginine conversion was best obtained by adding 5 mM l-ornithine, followed by 3.5 mM l-proline and by lowering the arginine concentration in the medium to 99.5 μM. No major changes in pluripotency and cell amount could be observed for the adapted E8 TM media with ornithine and proline. However, our subsequent ion mobility assisted data-independent acquisition (high-definition MS) proteome analysis cautions for ongoing changes in the proteome when aiming at longer term suppression of arginine conversion. © 2016 The Authors. Proteomics Published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Hypoxia Strongly Affects Mitochondrial Ribosomal Proteins and Translocases, as Shown by Quantitative Proteomics of HeLa Cells.

PubMed

Bousquet, Paula A; Sandvik, Joe Alexander; Arntzen, Magnus Ø; Jeppesen Edin, Nina F; Christoffersen, Stine; Krengel, Ute; Pettersen, Erik O; Thiede, Bernd

2015-01-01

Hypoxia is an important and common characteristic of many human tumors. It is a challenge clinically due to the correlation with poor prognosis and resistance to radiation and chemotherapy. Understanding the biochemical response to hypoxia would facilitate the development of novel therapeutics for cancer treatment. Here, we investigate alterations in gene expression in response to hypoxia by quantitative proteome analysis using stable isotope labeling with amino acids in cell culture (SILAC) in conjunction with LCMS/MS. Human HeLa cells were kept either in a hypoxic environment or under normoxic conditions. 125 proteins were found to be regulated, with maximum alteration of 18-fold. In particular, three clusters of differentially regulated proteins were identified, showing significant upregulation of glycolysis and downregulation of mitochondrial ribosomal proteins and translocases. This interaction is likely orchestrated by HIF-1. We also investigated the effect of hypoxia on the cell cycle, which shows accumulation in G1 and a prolonged S phase under these conditions. Implications. This work not only improves our understanding of the response to hypoxia, but also reveals proteins important for malignant progression, which may be targeted in future therapies.

IDAWG: Metabolic incorporation of stable isotope labels for quantitative glycomics of cultured cells

PubMed Central

Orlando, Ron; Lim, Jae-Min; Atwood, James A.; Angel, Peggi M.; Fang, Meng; Aoki, Kazuhiro; Alvarez-Manilla, Gerardo; Moremen, Kelley W.; York, William S.; Tiemeyer, Michael; Pierce, Michael; Dalton, Stephen; Wells, Lance

2012-01-01

Robust quantification is an essential component of comparative –omic strategies. In this regard, glycomics lags behind proteomics. Although various isotope-tagging and direct quantification methods have recently enhanced comparative glycan analysis, a cell culture labeling strategy, that could provide for glycomics the advantages that SILAC provides for proteomics, has not been described. Here we report the development of IDAWG, Isotopic Detection of Aminosugars With Glutamine, for the incorporation of differential mass tags into the glycans of cultured cells. In this method, culture media containing amide-15N-Gln is used to metabolically label cellular aminosugars with heavy nitrogen. Because the amide side chain of Gln is the sole source of nitrogen for the biosynthesis of GlcNAc, GalNAc, and sialic acid, we demonstrate that culturing mouse embryonic stems cells for 72 hours in the presence of amide-15N-Gln media results in nearly complete incorporation of 15N into N-linked and O-linked glycans. The isotopically heavy monosaccharide residues provide additional information for interpreting glycan fragmentation and also allow quantification in both full MS and MS/MS modes. Thus, IDAWG is a simple to implement, yet powerful quantitative tool for the glycomics toolbox. PMID:19449840

Dynamic quantitative proteomics characterization of TNF-α-induced necroptosis.

PubMed

Wang, Yang; Huang, Zhi-Hao; Li, Yang-Jia; He, Gui-Wei; Yu, Ru-Yuan; Yang, Jie; Liu, Wan-Ting; Li, Bin; He, Qing-Yu

2016-12-01

Emerging evidence suggested that necroptosis has essential functions in many human inflammatory diseases, but the molecular mechanisms of necroptosis remain unclear. Here, we employed SILAC quantitatively dynamic proteomics to compare the protein changes during TNF-α-induced necroptosis at different time points in murine fibrosarcoma L929 cells with caspase-8 deficiency, and then performed the systematical analysis on the signaling networks involved in the progress using bioinformatics methods. Our results showed that a total of 329, 421 and 378 differentially expressed proteins were detected at three stages of necroptosis, respectively. Gene ontology and ingenuity pathway analysis (IPA) revealed that the proteins regulated at early stages of necroptosis (2, 6 h) were mainly involved in mitochondria dysfunction, oxidative phosphorylation and Nrf-2 signaling, while the expression levels of the proteins related to ubiquitin, Nrf-2, and NF-κB pathways were found to have changes at last stages of necroptosis (6, 18 h). Taken together, we demonstrated for the first time that dysfunction of mitochondria and ubiquitin-proteasome signaling contributed to the initiation and execution of necroptosis. These findings may provide clues for the identification of important regulators in necroptosis and the development of novel therapeutic strategies for the related diseases.

A framework for intelligent data acquisition and real-time database searching for shotgun proteomics.

PubMed

Graumann, Johannes; Scheltema, Richard A; Zhang, Yong; Cox, Jürgen; Mann, Matthias

2012-03-01

In the analysis of complex peptide mixtures by MS-based proteomics, many more peptides elute at any given time than can be identified and quantified by the mass spectrometer. This makes it desirable to optimally allocate peptide sequencing and narrow mass range quantification events. In computer science, intelligent agents are frequently used to make autonomous decisions in complex environments. Here we develop and describe a framework for intelligent data acquisition and real-time database searching and showcase selected examples. The intelligent agent is implemented in the MaxQuant computational proteomics environment, termed MaxQuant Real-Time. It analyzes data as it is acquired on the mass spectrometer, constructs isotope patterns and SILAC pair information as well as controls MS and tandem MS events based on real-time and prior MS data or external knowledge. Re-implementing a top10 method in the intelligent agent yields similar performance to the data dependent methods running on the mass spectrometer itself. We demonstrate the capabilities of MaxQuant Real-Time by creating a real-time search engine capable of identifying peptides "on-the-fly" within 30 ms, well within the time constraints of a shotgun fragmentation "topN" method. The agent can focus sequencing events onto peptides of specific interest, such as those originating from a specific gene ontology (GO) term, or peptides that are likely modified versions of already identified peptides. Finally, we demonstrate enhanced quantification of SILAC pairs whose ratios were poorly defined in survey spectra. MaxQuant Real-Time is flexible and can be applied to a large number of scenarios that would benefit from intelligent, directed data acquisition. Our framework should be especially useful for new instrument types, such as the quadrupole-Orbitrap, that are currently becoming available.

A Framework for Intelligent Data Acquisition and Real-Time Database Searching for Shotgun Proteomics*

PubMed Central

Graumann, Johannes; Scheltema, Richard A.; Zhang, Yong; Cox, Jürgen; Mann, Matthias

2012-01-01

In the analysis of complex peptide mixtures by MS-based proteomics, many more peptides elute at any given time than can be identified and quantified by the mass spectrometer. This makes it desirable to optimally allocate peptide sequencing and narrow mass range quantification events. In computer science, intelligent agents are frequently used to make autonomous decisions in complex environments. Here we develop and describe a framework for intelligent data acquisition and real-time database searching and showcase selected examples. The intelligent agent is implemented in the MaxQuant computational proteomics environment, termed MaxQuant Real-Time. It analyzes data as it is acquired on the mass spectrometer, constructs isotope patterns and SILAC pair information as well as controls MS and tandem MS events based on real-time and prior MS data or external knowledge. Re-implementing a top10 method in the intelligent agent yields similar performance to the data dependent methods running on the mass spectrometer itself. We demonstrate the capabilities of MaxQuant Real-Time by creating a real-time search engine capable of identifying peptides “on-the-fly” within 30 ms, well within the time constraints of a shotgun fragmentation “topN” method. The agent can focus sequencing events onto peptides of specific interest, such as those originating from a specific gene ontology (GO) term, or peptides that are likely modified versions of already identified peptides. Finally, we demonstrate enhanced quantification of SILAC pairs whose ratios were poorly defined in survey spectra. MaxQuant Real-Time is flexible and can be applied to a large number of scenarios that would benefit from intelligent, directed data acquisition. Our framework should be especially useful for new instrument types, such as the quadrupole-Orbitrap, that are currently becoming available. PMID:22171319

Cytoskeleton-centric protein transportation by exosomes transforms tumor-favorable macrophages.

PubMed

Chen, Zhipeng; Yang, Lijuan; Cui, Yizhi; Zhou, Yanlong; Yin, Xingfeng; Guo, Jiahui; Zhang, Gong; Wang, Tong; He, Qing-Yu

2016-10-11

The exosome is a key initiator of pre-metastatic niche in numerous cancers, where macrophages serve as primary inducers of tumor microenvironment. However, the proteome that can be exosomally transported from cancer cells to macrophages has not been sufficiently characterized so far. Here, we used colorectal cancer (CRC) exosomes to educate tumor-favorable macrophages. With a SILAC-based mass spectrometry strategy, we successfully traced the proteome transported from CRC exosomes to macrophages. Such a proteome primarily focused on promoting cytoskeleton rearrangement, which was biologically validated with multiple cell lines. We reproduced the exosomal transportation of functional vimentin as a proof-of-concept example. In addition, we found that some CRC exosomes could be recognized by macrophages via Fc receptors. Therefore, we revealed the active and necessary role of exosomes secreted from CRC cells to transform cancer-favorable macrophages, with the cytoskeleton-centric proteins serving as the top functional unit.

Time Series Proteome Profiling

PubMed Central

Formolo, Catherine A.; Mintz, Michelle; Takanohashi, Asako; Brown, Kristy J.; Vanderver, Adeline; Halligan, Brian; Hathout, Yetrib

2014-01-01

This chapter provides a detailed description of a method used to study temporal changes in the endoplasmic reticulum (ER) proteome of fibroblast cells exposed to ER stress agents (tunicamycin and thapsigargin). Differential stable isotope labeling by amino acids in cell culture (SILAC) is used in combination with crude ER fractionation, SDS–PAGE and LC-MS/MS to define altered protein expression in tunicamycin or thapsigargin treated cells versus untreated cells. Treated and untreated cells are harvested at different time points, mixed at a 1:1 ratio and processed for ER fractionation. Samples containing labeled and unlabeled proteins are separated by SDS–PAGE, bands are digested with trypsin and the resulting peptides analyzed by LC-MS/MS. Proteins are identified using Bioworks software and the Swiss-Prot data-base, whereas ratios of protein expression between treated and untreated cells are quantified using ZoomQuant software. Data visualization is facilitated by GeneSpring software. proteomics PMID:21082445

FOXO/DAF-16 Activation Slows Down Turnover of the Majority of Proteins in C. elegans

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

Dhondt, Ineke; Petyuk, Vladislav A.; Cai, Huaihan

2016-09-01

Cellular protein quality can be maintained by proteolytic elimination of damaged proteins and replacing them with newly synthesized copies, a process called protein turnover (Ward, 2000). Protein turnover rates have been estimated using SILAC (stable isotope labeling by amino acids in cell culture) in prokaryotes and eukaryotes. The last decade has witnessed a growing interest in the analysis of whole-organism proteome dynamics in metazoans using the same approach (Claydon and Beynon, 2012). In recent work, SILAC was applied to monitor protein synthesis throughout life in adult Caenorhabditis elegans (Vukoti et al., 2015) and to investigate food intake (Gomez-Amaro et al.,more » 2015« less

Proteomic Analysis of the Androgen Receptor via MS-compatible Purification of Biotinylated Protein on Streptavidin Resin

PubMed Central

Austin, Ryan J.; Smidansky, Heidi M.; Holstein, Carly A.; Chang, Deborah K.; Epp, Angela; Josephson, Neil C.; Martin, Daniel B.

2012-01-01

The strength of the streptavidin/biotin interaction poses challenges for the recovery of biotinylated molecules from streptavidin resins. As an alternative to high temperature elution in urea containing buffers, we show mono-biotinylated proteins can be released with relatively gentle heating in the presence of biotin and 2% SDS/Rapigest, avoiding protein carbamylation and minimizing streptavidin dissociation. We demonstrate the utility of this mild elution strategy in two studies of the human androgen receptor (AR). In the first, in which formaldehyde crosslinked complexes are analyzed in yeast, a mass spectrometry-based comparison of the AR complex using SILAC reveals an association between the androgen activated AR and the Hsp90 chaperonin, while Hsp70 chaperonins associate specifically with the unliganded complex. In the second study, the endogenous AR is quantified in the LNCaP cell line by absolute SILAC and MRM-MS showing approximately 127,000 AR copies per cell, substantially more than previously measured using radioligand binding. PMID:22116683

Myostatin deficiency but not anti-myostatin blockade induces marked proteomic changes in mouse skeletal muscle.

PubMed

Salzler, Robert R; Shah, Darshit; Doré, Anthony; Bauerlein, Roy; Miloscio, Lawrence; Latres, Esther; Papadopoulos, Nicholas J; Olson, William C; MacDonald, Douglas; Duan, Xunbao

2016-07-01

Pharmacologic blockade of the myostatin (Mstn)/activin receptor pathway is being pursued as a potential therapy for several muscle wasting disorders. The functional benefits of blocking this pathway are under investigation, in particular given the findings that greater muscle hypertrophy results from Mstn deficiency arising from genetic ablation compared to post-developmental Mstn blockade. Using high-resolution MS coupled with SILAC mouse technology, we quantitated the relative proteomic changes in gastrocnemius muscle from Mstn knockout (Mstn(-/-) ) and mice treated for 2-weeks with REGN1033, an anti-Mstn antibody. Relative to wild-type animals, Mstn(-/-) mice had a two-fold greater muscle mass and a >1.5-fold change in expression of 12.0% of 1137 quantified muscle proteins. In contrast, mice treated with REGN1033 had minimal changes in muscle proteome (0.7% of 1510 proteins >1.5-fold change, similar to biological difference 0.5% of 1310) even though the treatment induced significant 20% muscle mass increase. Functional annotation of the altered proteins in Mstn(-/-) mice corroborates the mutiple physiological changes including slow-to-fast fiber type switch. Thus, the proteome-wide protein expression differs between Mstn(-/-) mice and mice subjected to specific Mstn blockade post-developmentally, providing molecular-level insights to inform mechanistic hypotheses to explain the observed functional differences. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative Proteomic Approach Identifies Vpr Binding Protein as Novel Host Factor Supporting Influenza A Virus Infections in Human Cells.

PubMed

Sadewasser, Anne; Paki, Katharina; Eichelbaum, Katrin; Bogdanow, Boris; Saenger, Sandra; Budt, Matthias; Lesch, Markus; Hinz, Klaus-Peter; Herrmann, Andreas; Meyer, Thomas F; Karlas, Alexander; Selbach, Matthias; Wolff, Thorsten

2017-05-01

Influenza A virus (IAV) infections are a major cause for respiratory disease in humans, which affects all age groups and contributes substantially to global morbidity and mortality. IAV have a large natural host reservoir in avian species. However, many avian IAV strains lack adaptation to other hosts and hardly propagate in humans. While seasonal or pandemic IAV strains replicate efficiently in permissive human cells, many avian IAV cause abortive nonproductive infections in these hosts despite successful cell entry. However, the precise reasons for these differential outcomes are poorly defined. We hypothesized that the distinct course of an IAV infection with a given virus strain is determined by the differential interplay between specific host and viral factors. By using Spike-in SILAC mass spectrometry-based quantitative proteomics we characterized sets of cellular factors whose abundance is specifically up- or downregulated in the course of permissive versus nonpermissive IAV infection, respectively. This approach allowed for the definition and quantitative comparison of about 3500 proteins in human lung epithelial cells in response to seasonal or low-pathogenic avian H3N2 IAV. Many identified proteins were similarly regulated by both virus strains, but also 16 candidates with distinct changes in permissive versus nonpermissive infection were found. RNAi-mediated knockdown of these differentially regulated host factors identified Vpr binding protein (VprBP) as proviral host factor because its downregulation inhibited efficient propagation of seasonal IAV whereas overexpression increased viral replication of both seasonal and avian IAV. These results not only show that there are similar differences in the overall changes during permissive and nonpermissive influenza virus infections, but also provide a basis to evaluate VprBP as novel anti-IAV drug target. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Quantitative Proteomic Approach Identifies Vpr Binding Protein as Novel Host Factor Supporting Influenza A Virus Infections in Human Cells*

PubMed Central

Sadewasser, Anne; Paki, Katharina; Eichelbaum, Katrin; Bogdanow, Boris; Saenger, Sandra; Budt, Matthias; Lesch, Markus; Hinz, Klaus-Peter; Herrmann, Andreas; Meyer, Thomas F.; Karlas, Alexander; Selbach, Matthias; Wolff, Thorsten

2017-01-01

Influenza A virus (IAV) infections are a major cause for respiratory disease in humans, which affects all age groups and contributes substantially to global morbidity and mortality. IAV have a large natural host reservoir in avian species. However, many avian IAV strains lack adaptation to other hosts and hardly propagate in humans. While seasonal or pandemic IAV strains replicate efficiently in permissive human cells, many avian IAV cause abortive nonproductive infections in these hosts despite successful cell entry. However, the precise reasons for these differential outcomes are poorly defined. We hypothesized that the distinct course of an IAV infection with a given virus strain is determined by the differential interplay between specific host and viral factors. By using Spike-in SILAC mass spectrometry-based quantitative proteomics we characterized sets of cellular factors whose abundance is specifically up- or downregulated in the course of permissive versus nonpermissive IAV infection, respectively. This approach allowed for the definition and quantitative comparison of about 3500 proteins in human lung epithelial cells in response to seasonal or low-pathogenic avian H3N2 IAV. Many identified proteins were similarly regulated by both virus strains, but also 16 candidates with distinct changes in permissive versus nonpermissive infection were found. RNAi-mediated knockdown of these differentially regulated host factors identified Vpr binding protein (VprBP) as proviral host factor because its downregulation inhibited efficient propagation of seasonal IAV whereas overexpression increased viral replication of both seasonal and avian IAV. These results not only show that there are similar differences in the overall changes during permissive and nonpermissive influenza virus infections, but also provide a basis to evaluate VprBP as novel anti-IAV drug target. PMID:28289176

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

Guo, Lei; Xiao, Yongsheng; Wang, Yinsheng, E-mail: yinsheng.wang@ucr.edu

Human exposure to arsenic in drinking water is a widespread public health concern, and such exposure is known to be associated with many human diseases. The detailed molecular mechanisms about how arsenic species contribute to the adverse human health effects, however, remain incompletely understood. Monomethylarsonous acid [MMA(III)] is a highly toxic and stable metabolite of inorganic arsenic. To exploit the mechanisms through which MMA(III) exerts its cytotoxic effect, we adopted a quantitative proteomic approach, by coupling stable isotope labeling by amino acids in cell culture (SILAC) with LC-MS/MS analysis, to examine the variation in the entire proteome of GM00637 humanmore » skin fibroblasts following acute MMA(III) exposure. Among the ∼ 6500 unique proteins quantified, ∼ 300 displayed significant changes in expression after exposure with 2 μM MMA(III) for 24 h. Subsequent analysis revealed the perturbation of de novo cholesterol biosynthesis, selenoprotein synthesis and Nrf2 pathways evoked by MMA(III) exposure. Particularly, MMA(III) treatment resulted in considerable down-regulation of several enzymes involved in cholesterol biosynthesis. In addition, real-time PCR analysis showed reduced mRNA levels of select genes in this pathway. Furthermore, MMA(III) exposure contributed to a distinct decline in cellular cholesterol content and significant growth inhibition of multiple cell lines, both of which could be restored by supplementation of cholesterol to the culture media. Collectively, the present study demonstrated that the cytotoxicity of MMA(III) may arise, at least in part, from the down-regulation of cholesterol biosynthesis enzymes and the resultant decrease of cellular cholesterol content. - Highlights: • MMA(III)-induced perturbation of the entire proteome of GM00637 cells is studied. • Quantitative proteomic approach revealed alterations of multiple cellular pathways. • MMA(III) inhibits de novo cholesterol biosynthesis. • MMA(III) perturbs Nrf2 pathway and selenoprotein synthesis.« less

An integrated proteomic approach uncovers novel substrates and functions of the Lon protease in Escherichia coli.

PubMed

Arends, Jan; Griego, Marcena; Thomanek, Nikolas; Lindemann, Claudia; Kutscher, Blanka; Meyer, Helmut E; Narberhaus, Franz

2018-04-30

Controlling the cellular abundance and proper function of proteins by proteolysis is a universal process in all living organisms. In Escherichia coli, the ATP-dependent Lon protease is crucial for protein quality control and regulatory processes. To understand how diverse substrates are selected and degraded, unbiased global approaches are needed. We employed a quantitative Super-SILAC mass spectrometry approach and compared the proteomes of a lon mutant and a strain producing the protease to discover Lon-dependent physiological functions. To identify Lon substrates, we took advantage of a Lon trapping variant, which is able to translocate substrates but unable to degrade them. Lon-associated proteins were identified by label-free LC-MS/MS. The combination of both approaches revealed a total of 14 novel Lon substrates. Besides the identification of known pathways affected by Lon, for example the superoxide-stress response, our cumulative data suggests previously unrecognized fundamental functions of Lon in sulfur assimilation, nucleotide biosynthesis, amino acid and central energy metabolism. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Nanospray FAIMS Fractionation Provides Significant Increases in Proteome Coverage of Unfractionated Complex Protein Digests*

PubMed Central

Swearingen, Kristian E.; Hoopmann, Michael R.; Johnson, Richard S.; Saleem, Ramsey A.; Aitchison, John D.; Moritz, Robert L.

2012-01-01

High-field asymmetric waveform ion mobility spectrometry (FAIMS) is an atmospheric pressure ion mobility technique that can be used to reduce sample complexity and increase dynamic range in tandem mass spectrometry experiments. FAIMS fractionates ions in the gas-phase according to characteristic differences in mobilities in electric fields of different strengths. Undesired ion species such as solvated clusters and singly charged chemical background ions can be prevented from reaching the mass analyzer, thus decreasing chemical noise. To date, there has been limited success using the commercially available Thermo Fisher FAIMS device with both standard ESI and nanoLC-MS. We have modified a Thermo Fisher electrospray source to accommodate a fused silica pulled tip capillary column for nanospray ionization, which will enable standard laboratories access to FAIMS technology. Our modified source allows easily obtainable stable spray at flow rates of 300 nL/min when coupled with FAIMS. The modified electrospray source allows the use of sheath gas, which provides a fivefold increase in signal obtained when nanoLC is coupled to FAIMS. In this work, nanoLC-FAIMS-MS and nanoLC-MS were compared by analyzing a tryptic digest of a 1:1 mixture of SILAC-labeled haploid and diploid yeast to demonstrate the performance of nanoLC-FAIMS-MS, at different compensation voltages, for post-column fractionation of complex protein digests. The effective dynamic range more than doubled when FAIMS was used. In total, 10,377 unique stripped peptides and 1649 unique proteins with SILAC ratios were identified from the combined nanoLC-FAIMS-MS experiments, compared with 6908 unique stripped peptides and 1003 unique proteins with SILAC ratios identified from the combined nanoLC-MS experiments. This work demonstrates how a commercially available FAIMS device can be combined with nanoLC to improve proteome coverage in shotgun and targeted type proteomics experiments. PMID:22186714

PyQuant: A Versatile Framework for Analysis of Quantitative Mass Spectrometry Data*

PubMed Central

Mitchell, Christopher J.; Kim, Min-Sik; Na, Chan Hyun; Pandey, Akhilesh

2016-01-01

Quantitative mass spectrometry data necessitates an analytical pipeline that captures the accuracy and comprehensiveness of the experiments. Currently, data analysis is often coupled to specific software packages, which restricts the analysis to a given workflow and precludes a more thorough characterization of the data by other complementary tools. To address this, we have developed PyQuant, a cross-platform mass spectrometry data quantification application that is compatible with existing frameworks and can be used as a stand-alone quantification tool. PyQuant supports most types of quantitative mass spectrometry data including SILAC, NeuCode, 15N, 13C, or 18O and chemical methods such as iTRAQ or TMT and provides the option of adding custom labeling strategies. In addition, PyQuant can perform specialized analyses such as quantifying isotopically labeled samples where the label has been metabolized into other amino acids and targeted quantification of selected ions independent of spectral assignment. PyQuant is capable of quantifying search results from popular proteomic frameworks such as MaxQuant, Proteome Discoverer, and the Trans-Proteomic Pipeline in addition to several standalone search engines. We have found that PyQuant routinely quantifies a greater proportion of spectral assignments, with increases ranging from 25–45% in this study. Finally, PyQuant is capable of complementing spectral assignments between replicates to quantify ions missed because of lack of MS/MS fragmentation or that were omitted because of issues such as spectra quality or false discovery rates. This results in an increase of biologically useful data available for interpretation. In summary, PyQuant is a flexible mass spectrometry data quantification platform that is capable of interfacing with a variety of existing formats and is highly customizable, which permits easy configuration for custom analysis. PMID:27231314

Quantitative Proteomics Reveals Dynamic Interactions of the Minichromosome Maintenance Complex (MCM) in the Cellular Response to Etoposide Induced DNA Damage.

PubMed

Drissi, Romain; Dubois, Marie-Line; Douziech, Mélanie; Boisvert, François-Michel

2015-07-01

The minichromosome maintenance complex (MCM) proteins are required for processive DNA replication and are a target of S-phase checkpoints. The eukaryotic MCM complex consists of six proteins (MCM2-7) that form a heterohexameric ring with DNA helicase activity, which is loaded on chromatin to form the pre-replication complex. Upon entry in S phase, the helicase is activated and opens the DNA duplex to recruit DNA polymerases at the replication fork. The MCM complex thus plays a crucial role during DNA replication, but recent work suggests that MCM proteins could also be involved in DNA repair. Here, we employed a combination of stable isotope labeling with amino acids in cell culture (SILAC)-based quantitative proteomics with immunoprecipitation of green fluorescent protein-tagged fusion proteins to identify proteins interacting with the MCM complex, and quantify changes in interactions in response to DNA damage. Interestingly, the MCM complex showed very dynamic changes in interaction with proteins such as Importin7, the histone chaperone ASF1, and the Chromodomain helicase DNA binding protein 3 (CHD3) following DNA damage. These changes in interactions were accompanied by an increase in phosphorylation and ubiquitination on specific sites on the MCM proteins and an increase in the co-localization of the MCM complex with γ-H2AX, confirming the recruitment of these proteins to sites of DNA damage. In summary, our data indicate that the MCM proteins is involved in chromatin remodeling in response to DNA damage. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Exploring G protein-coupled receptor signaling networks using SILAC-based phosphoproteomics

PubMed Central

Williams, Grace R.; Bethard, Jennifer R.; Berkaw, Mary N.; Nagel, Alexis K.; Luttrell, Louis M.; Ball, Lauren E.

2015-01-01

The type 1 parathyroid hormone receptor (PTH1R) is a key regulator of calcium homeostasis and bone turnover. Here, we employed SILAC-based quantitative mass spectrometry combined with bioinformatic pathways analysis to examine global changes in protein phosphorylation following short-term stimulation of endogenously expressed PTH1R in osteoblastic cells in vitro. Following 5 min exposure to the conventional agonist, PTH(1-34), we detected significant changes in the phosphorylation of 224 distinct proteins. Kinase substrate motif enrichment demonstrated that consensus motifs for PKA and CAMK2 were the most heavily upregulated within the phosphoproteome, while consensus motifs for mitogen-activated protein kinases were strongly downregulated. Signaling pathways analysis identified ERK1/2 and AKT as important nodal kinases in the downstream network and revealed strong regulation of small GTPases involved in cytoskeletal rearrangement, cell motility, and focal adhesion complex signaling. Our data illustrate the utility of quantitative mass spectrometry in measuring dynamic changes in protein phosphorylation following GPCR activation. PMID:26160508

Establishment of a protein frequency library and its application in the reliable identification of specific protein interaction partners.

PubMed

Boulon, Séverine; Ahmad, Yasmeen; Trinkle-Mulcahy, Laura; Verheggen, Céline; Cobley, Andy; Gregor, Peter; Bertrand, Edouard; Whitehorn, Mark; Lamond, Angus I

2010-05-01

The reliable identification of protein interaction partners and how such interactions change in response to physiological or pathological perturbations is a key goal in most areas of cell biology. Stable isotope labeling with amino acids in cell culture (SILAC)-based mass spectrometry has been shown to provide a powerful strategy for characterizing protein complexes and identifying specific interactions. Here, we show how SILAC can be combined with computational methods drawn from the business intelligence field for multidimensional data analysis to improve the discrimination between specific and nonspecific protein associations and to analyze dynamic protein complexes. A strategy is shown for developing a protein frequency library (PFL) that improves on previous use of static "bead proteomes." The PFL annotates the frequency of detection in co-immunoprecipitation and pulldown experiments for all proteins in the human proteome. It can provide a flexible and objective filter for discriminating between contaminants and specifically bound proteins and can be used to normalize data values and facilitate comparisons between data obtained in separate experiments. The PFL is a dynamic tool that can be filtered for specific experimental parameters to generate a customized library. It will be continuously updated as data from each new experiment are added to the library, thereby progressively enhancing its utility. The application of the PFL to pulldown experiments is especially helpful in identifying either lower abundance or less tightly bound specific components of protein complexes that are otherwise lost among the large, nonspecific background.

Quantitative time-resolved chemoproteomics reveals that stable O-GlcNAc regulates box C/D snoRNP biogenesis

PubMed Central

Qin, Wei; Lv, Pinou; Fan, Xinqi; Quan, Baiyi; Zhu, Yuntao; Qin, Ke; Chen, Ying; Wang, Chu

2017-01-01

O-linked GlcNAcylation (O-GlcNAcylation), a ubiquitous posttranslational modification on intracellular proteins, is dynamically regulated in cells. To analyze the turnover dynamics of O-GlcNAcylated proteins, we developed a quantitative time-resolved O-linked GlcNAc proteomics (qTOP) strategy based on metabolic pulse-chase labeling with an O-GlcNAc chemical reporter and stable isotope labeling with amino acids in cell culture (SILAC). Applying qTOP, we quantified the turnover rates of 533 O-GlcNAcylated proteins in NIH 3T3 cells and discovered that about 14% exhibited minimal removal of O-GlcNAc or degradation of protein backbones. The stability of those hyperstable O-GlcNAcylated proteins was more sensitive to O-GlcNAcylation inhibition compared with the more dynamic populations. Among the hyperstable population were three core proteins of box C/D small nucleolar ribonucleoprotein complexes (snoRNPs): fibrillarin (FBL), nucleolar protein 5A (NOP56), and nucleolar protein 5 (NOP58). We showed that O-GlcNAcylation stabilized these proteins and was essential for snoRNP assembly. Blocking O-GlcNAcylation on FBL altered the 2′-O-methylation of rRNAs and impaired cancer cell proliferation and tumor formation in vivo. PMID:28760965

Terminal Galactosylation and Sialylation Switching on Membrane Glycoproteins upon TNF-Alpha-Induced Insulin Resistance in Adipocytes*

PubMed Central

Parker, Benjamin L.; Thaysen-Andersen, Morten; Fazakerley, Daniel J.; Holliday, Mira; Packer, Nicolle H.; James, David E.

2016-01-01

Insulin resistance (IR) is a complex pathophysiological state that arises from both environmental and genetic perturbations and leads to a variety of diseases, including type-2 diabetes (T2D). Obesity is associated with enhanced adipose tissue inflammation, which may play a role in disease progression. Inflammation modulates protein glycosylation in a variety of cell types, and this has been associated with biological dysregulation. Here, we have examined the effects of an inflammatory insult on protein glycosylation in adipocytes. We performed quantitative N-glycome profiling of membrane proteins derived from mouse 3T3-L1 adipocytes that had been incubated with or without the proinflammatory cytokine TNF-alpha to induce IR. We identified the regulation of specific terminal N-glycan epitopes, including an increase in terminal di-galactose- and a decrease in biantennary alpha-2,3-sialoglycans. The altered N-glycosylation of TNF-alpha-treated adipocytes correlated with the regulation of specific glycosyltransferases, including the up-regulation of B4GalT5 and Ggta1 galactosyltransferases and down-regulation of ST3Gal6 sialyltransferase. Knockdown of B4GalT5 down-regulated the terminal di-galactose N-glycans, confirming the involvement of this enzyme in the TNF-alpha-regulated N-glycome. SILAC-based quantitative glycoproteomics of enriched N-glycopeptides with and without deglycosylation were used to identify the protein and glycosylation sites modified with these regulated N-glycans. The combined proteome and glycoproteome workflow provided a relative quantification of changes in protein abundance versus N-glycosylation occupancy versus site-specific N-glycans on a proteome-wide level. This revealed the modulation of N-glycosylation on specific proteins in IR, including those previously associated with insulin-stimulated GLUT4 trafficking to the plasma membrane. PMID:26537798

Quantitative Proteomics Analysis of VEGF-Responsive Endothelial Protein S-Nitrosylation Using Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) and LC-MS/MS1

PubMed Central

Zhang, Hong-Hai; Lechuga, Thomas J.; Chen, Yuezhou; Yang, Yingying; Huang, Lan; Chen, Dong-Bao

2016-01-01

Adduction of a nitric oxide moiety (NO•) to cysteine(s), termed S-nitrosylation (SNO), is a novel mechanism for NO to regulate protein function directly. However, the endothelial SNO-protein network that is affected by endogenous and exogenous NO is obscure. This study was designed to develop a quantitative proteomics approach using stable isotope labeling by amino acids in cell culture for comparing vascular endothelial growth factor (VEGFA)- and NO donor-responsive endothelial nitroso-proteomes. Primary placental endothelial cells were labeled with “light” (L-12C614N4-Arg and L-12C614N2-Lys) or “heavy” (L-13C615N4-Arg and L-13C615N2-Lys) amino acids. The light cells were treated with an NO donor nitrosoglutathione (GSNO, 1 mM) or VEGFA (10 ng/ml) for 30 min, while the heavy cells received vehicle as control. Equal amounts of cellular proteins from the light (GSNO or VEGFA treated) and heavy cells were mixed for labeling SNO-proteins by the biotin switch technique and then trypsin digested. Biotinylated SNO-peptides were purified for identifying SNO-proteins by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Ratios of light to heavy SNO-peptides were calculated for determining the changes of the VEGFA- and GSNO-responsive endothelial nitroso-proteomes. A total of 387 light/heavy pairs of SNO-peptides were identified, corresponding to 213 SNO-proteins that include 125 common and 27 VEGFA- and 61 GSNO-responsive SNO-proteins. The specific SNO-cysteine(s) in each SNO-protein were simultaneously identified. Pathway analysis revealed that SNO-proteins are involved in various endothelial functions, including proliferation, motility, metabolism, and protein synthesis. We collectively conclude that endogenous NO on VEGFA stimulation and exogenous NO from GSNO affect common and different SNO-protein networks, implicating SNO as a critical mechanism for VEGFA stimulation of angiogenesis. PMID:27075618

PyQuant: A Versatile Framework for Analysis of Quantitative Mass Spectrometry Data.

PubMed

Mitchell, Christopher J; Kim, Min-Sik; Na, Chan Hyun; Pandey, Akhilesh

2016-08-01

Quantitative mass spectrometry data necessitates an analytical pipeline that captures the accuracy and comprehensiveness of the experiments. Currently, data analysis is often coupled to specific software packages, which restricts the analysis to a given workflow and precludes a more thorough characterization of the data by other complementary tools. To address this, we have developed PyQuant, a cross-platform mass spectrometry data quantification application that is compatible with existing frameworks and can be used as a stand-alone quantification tool. PyQuant supports most types of quantitative mass spectrometry data including SILAC, NeuCode, (15)N, (13)C, or (18)O and chemical methods such as iTRAQ or TMT and provides the option of adding custom labeling strategies. In addition, PyQuant can perform specialized analyses such as quantifying isotopically labeled samples where the label has been metabolized into other amino acids and targeted quantification of selected ions independent of spectral assignment. PyQuant is capable of quantifying search results from popular proteomic frameworks such as MaxQuant, Proteome Discoverer, and the Trans-Proteomic Pipeline in addition to several standalone search engines. We have found that PyQuant routinely quantifies a greater proportion of spectral assignments, with increases ranging from 25-45% in this study. Finally, PyQuant is capable of complementing spectral assignments between replicates to quantify ions missed because of lack of MS/MS fragmentation or that were omitted because of issues such as spectra quality or false discovery rates. This results in an increase of biologically useful data available for interpretation. In summary, PyQuant is a flexible mass spectrometry data quantification platform that is capable of interfacing with a variety of existing formats and is highly customizable, which permits easy configuration for custom analysis. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Characterization of the Saccharomyces cerevisiae ATP-Interactome using the iTRAQ-SPROX Technique

NASA Astrophysics Data System (ADS)

Geer, M. Ariel; Fitzgerald, Michael C.

2016-02-01

The stability of proteins from rates of oxidation (SPROX) technique was used in combination with an isobaric mass tagging strategy to identify adenosine triphosphate (ATP) interacting proteins in the Saccharomyces cerevisiae proteome. The SPROX methodology utilized in this work enabled 373 proteins in a yeast cell lysate to be assayed for ATP interactions (both direct and indirect) using the non-hydrolyzable ATP analog, adenylyl imidodiphosphate (AMP-PNP). A total of 28 proteins were identified with AMP-PNP-induced thermodynamic stability changes. These protein hits included 14 proteins that were previously annotated as ATP-binding proteins in the Saccharomyces Genome Database (SGD). The 14 non-annotated ATP-binding proteins included nine proteins that were previously found to be ATP-sensitive in an earlier SPROX study using a stable isotope labeling with amino acids in cell culture (SILAC)-based approach. A bioinformatics analysis of the protein hits identified here and in the earlier SILAC-SPROX experiments revealed that many of the previously annotated ATP-binding protein hits were kinases, ligases, and chaperones. In contrast, many of the newly discovered ATP-sensitive proteins were not from these protein classes, but rather were hydrolases, oxidoreductases, and nucleic acid-binding proteins.

Application of adenosine triphosphate affinity probe and scheduled multiple-reaction monitoring analysis for profiling global kinome in human cells in response to arsenite treatment.

PubMed

Guo, Lei; Xiao, Yongsheng; Wang, Yinsheng

2014-11-04

Phosphorylation of cellular components catalyzed by kinases plays important roles in cell signaling and proliferation. Quantitative assessment of perturbation in global kinome may provide crucial knowledge for elucidating the mechanisms underlying the cytotoxic effects of environmental toxicants. Here, we utilized an adenosine triphosphate (ATP) affinity probe coupled with stable isotope labeling by amino acids in cell culture (SILAC) to assess quantitatively the arsenite-induced alteration of global kinome in human cells. We constructed a SILAC-compatible kinome library for scheduled multiple-reaction monitoring (MRM) analysis and adopted on-the-fly recalibration of retention time shift, which provided better throughput of the analytical method and enabled the simultaneous quantification of the expression of ∼300 kinases in two LC-MRM runs. With this improved analytical method, we conducted an in-depth quantitative analysis of the perturbation of kinome of GM00637 human skin fibroblast cells induced by arsenite exposure. Several kinases involved in cell cycle progression, including cyclin-dependent kinases (CDK1 and CDK4) and Aurora kinases A, B, and C, were found to be hyperactivated, and the altered expression of CDK1 was further validated by Western analysis. In addition, treatment with a CDK inhibitor, flavopiridol, partially restored the arsenite-induced growth inhibition of human skin fibroblast cells. Thus, sodium arsenite may confer its cytotoxic effect partly through the aberrant activation of CDKs and the resultant perturbation of cell cycle progression. Together, we developed a high-throughput, SILAC-compatible, and MRM-based kinome profiling method and demonstrated that the method is powerful in deciphering the molecular modes of action of a widespread environmental toxicant. The method should be generally applicable for uncovering the cellular pathways triggered by other extracellular stimuli.

Application of Adenosine Triphosphate Affinity Probe and Scheduled Multiple-Reaction Monitoring Analysis for Profiling Global Kinome in Human Cells in Response to Arsenite Treatment

PubMed Central

2015-01-01

Phosphorylation of cellular components catalyzed by kinases plays important roles in cell signaling and proliferation. Quantitative assessment of perturbation in global kinome may provide crucial knowledge for elucidating the mechanisms underlying the cytotoxic effects of environmental toxicants. Here, we utilized an adenosine triphosphate (ATP) affinity probe coupled with stable isotope labeling by amino acids in cell culture (SILAC) to assess quantitatively the arsenite-induced alteration of global kinome in human cells. We constructed a SILAC-compatible kinome library for scheduled multiple-reaction monitoring (MRM) analysis and adopted on-the-fly recalibration of retention time shift, which provided better throughput of the analytical method and enabled the simultaneous quantification of the expression of ∼300 kinases in two LC-MRM runs. With this improved analytical method, we conducted an in-depth quantitative analysis of the perturbation of kinome of GM00637 human skin fibroblast cells induced by arsenite exposure. Several kinases involved in cell cycle progression, including cyclin-dependent kinases (CDK1 and CDK4) and Aurora kinases A, B, and C, were found to be hyperactivated, and the altered expression of CDK1 was further validated by Western analysis. In addition, treatment with a CDK inhibitor, flavopiridol, partially restored the arsenite-induced growth inhibition of human skin fibroblast cells. Thus, sodium arsenite may confer its cytotoxic effect partly through the aberrant activation of CDKs and the resultant perturbation of cell cycle progression. Together, we developed a high-throughput, SILAC-compatible, and MRM-based kinome profiling method and demonstrated that the method is powerful in deciphering the molecular modes of action of a widespread environmental toxicant. The method should be generally applicable for uncovering the cellular pathways triggered by other extracellular stimuli. PMID:25301106

Iron overload down-regulates the expression of the HIV-1 Rev cofactor eIF5A in infected T lymphocytes.

PubMed

Mancone, Carmine; Grimaldi, Alessio; Refolo, Giulia; Abbate, Isabella; Rozera, Gabriella; Benelli, Dario; Fimia, Gian Maria; Barnaba, Vincenzo; Tripodi, Marco; Piacentini, Mauro; Ciccosanti, Fabiola

2017-01-01

Changes in iron metabolism frequently accompany HIV-1 infection. However, while many clinical and in vitro studies report iron overload exacerbates the development of infection, many others have found no correlation. Therefore, the multi-faceted role of iron in HIV-1 infection remains enigmatic. RT-qPCR targeting the LTR region, gag , Tat and Rev were performed to measure the levels of viral RNAs in response to iron overload. Spike-in SILAC proteomics comparing i) iron-treated, ii) HIV-1-infected and iii) HIV-1-infected/iron treated T lymphocytes was performed to define modifications in the host cell proteome. Data from quantitative proteomics were integrated with the HIV-1 Human Interaction Database for assessing any viral cofactors modulated by iron overload in infected T lymphocytes. Here, we demonstrate that the iron overload down-regulates HIV-1 gene expression by decreasing the levels of viral RNAs. In addition, we found that iron overload modulates the expression of many viral cofactors. Among them, the downregulation of the REV cofactor eIF5A may correlate with the iron-induced inhibition of HIV-1 gene expression. Therefore, we demonstrated that eiF5A downregulation by shRNA resulted in a significant decrease of Nef levels, thus hampering HIV-1 replication. Our study indicates that HIV-1 cofactors influenced by iron metabolism represent potential targets for antiretroviral therapy and suggests eIF5A as a selective target for drug development.

Proteomic analysis of polyribosomes identifies splicing factors as potential regulators of translation during mitosis

PubMed Central

Hofmann, Sarah; Elman, Tamar; Shenoy, Anjana; Geiger, Tamar; Elkon, Ran; Ehrlich, Marcelo

2017-01-01

Abstract Precise regulation of mRNA translation is critical for proper cell division, but little is known about the factors that mediate it. To identify mRNA-binding proteins that regulate translation during mitosis, we analyzed the composition of polysomes from interphase and mitotic cells using unbiased quantitative mass-spectrometry (LC–MS/MS). We found that mitotic polysomes are enriched with a subset of proteins involved in RNA processing, including alternative splicing and RNA export. To demonstrate that these may indeed be regulators of translation, we focused on heterogeneous nuclear ribonucleoprotein C (hnRNP C) as a test case and confirmed that it is recruited to elongating ribosomes during mitosis. Then, using a combination of pulsed SILAC, metabolic labeling and ribosome profiling, we showed that knockdown of hnRNP C affects both global and transcript-specific translation rates and found that hnRNP C is specifically important for translation of mRNAs that encode ribosomal proteins and translation factors. Taken together, our results demonstrate how proteomic analysis of polysomes can provide insight into translation regulation under various cellular conditions of interest and suggest that hnRNP C facilitates production of translation machinery components during mitosis to provide daughter cells with the ability to efficiently synthesize proteins as they enter G1 phase. PMID:28460002

Quantitative identification of proteins that influence miRNA biogenesis by RNA pull-down-SILAC mass spectrometry (RP-SMS).

PubMed

Choudhury, Nila Roy; Michlewski, Gracjan

2018-06-08

RNA-binding proteins mediate and control gene expression. As some examples, they regulate pre-mRNA synthesis and processing; mRNA localisation, translation and decay; and microRNA (miRNA) biogenesis and function. Here, we present a detailed protocol for RNA pull-down coupled to stable isotope labelling by amino acids in cell culture (SILAC) mass spectrometry (RP-SMS) that enables quantitative, fast and specific detection of RNA-binding proteins that regulate miRNA biogenesis. In general, this method allows for the identification of RNA-protein complexes formed using in vitro or chemically synthesized RNAs and protein extracts derived from cultured cells. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Rare Disease Mechanisms Identified by Genealogical Proteomics of Copper Homeostasis Mutant Pedigrees.

PubMed

Zlatic, Stephanie A; Vrailas-Mortimer, Alysia; Gokhale, Avanti; Carey, Lucas J; Scott, Elizabeth; Burch, Reid; McCall, Morgan M; Rudin-Rush, Samantha; Davis, John Bowen; Hartwig, Cortnie; Werner, Erica; Li, Lian; Petris, Michael; Faundez, Victor

2018-03-28

Rare neurological diseases shed light onto universal neurobiological processes. However, molecular mechanisms connecting genetic defects to their disease phenotypes are elusive. Here, we obtain mechanistic information by comparing proteomes of cells from individuals with rare disorders with proteomes from their disease-free consanguineous relatives. We use triple-SILAC mass spectrometry to quantify proteomes from human pedigrees affected by mutations in ATP7A, which cause Menkes disease, a rare neurodegenerative and neurodevelopmental disorder stemming from systemic copper depletion. We identified 214 proteins whose expression was altered in ATP7A -/y fibroblasts. Bioinformatic analysis of ATP7A-mutant proteomes identified known phenotypes and processes affected in rare genetic diseases causing copper dyshomeostasis, including altered mitochondrial function. We found connections between copper dyshomeostasis and the UCHL1/PARK5 pathway of Parkinson disease, which we validated with mitochondrial respiration and Drosophila genetics assays. We propose that our genealogical "omics" strategy can be broadly applied to identify mechanisms linking a genomic locus to its phenotypes. Copyright © 2018 Elsevier Inc. All rights reserved.

Proteomic biomarkers in lung cancer.

PubMed

Pastor, M D; Nogal, A; Molina-Pinelo, S; Carnero, A; Paz-Ares, L

2013-09-01

The correct understanding of tumour development relies on the comprehensive study of proteins. They are the main orchestrators of vital processes, such as signalling pathways, which drive the carcinogenic process. Proteomic technologies can be applied to cancer research to detect differential protein expression and to assess different responses to treatment. Lung cancer is the number one cause of cancer-related death in the world. Mostly diagnosed at late stages of the disease, lung cancer has one of the lowest 5-year survival rates at 15 %. The use of different proteomic techniques such as two-dimensional gel electrophoresis (2D-PAGE), isotope labelling (ICAT, SILAC, iTRAQ) and mass spectrometry may yield new knowledge on the underlying biology of lung cancer and also allow the development of new early detection tests and the identification of changes in the cancer protein network that are associated with prognosis and drug resistance.

Altered protein expression profile associated with phenotypic changes in lung fibroblasts co-cultured with gold nanoparticle-treated small airway epithelial cells.

PubMed

Ng, Cheng-Teng; Yung, Lin-Yue Lanry; Swa, Hannah Lee-Foon; Poh, Rebecca Wan-Yan; Gunaratne, Jayantha; Bay, Boon-Huat

2015-01-01

Despite the availability of toxicity studies on cellular exposure to gold nanoparticles (AuNPs), there is scarcity of information with regard to the bystander effects induced by AuNPs on neighboring cells not exposed to the NPs. In this study, we showed that exposure of small airway epithelial cells (SAECs) to AuNPs induced changes in protein expression associated with functional effects in neighboring MRC5 lung fibroblasts in a co-culture system. Uptake of 20 nm size AuNPs by SAECs was first verified by focused ion beam scanning electron microscopy. Subsequently, pretreated SAECs were co-cultured with unexposed MRC5 lung fibroblasts, which then underwent proteome profiling using a quantitative proteomic approach. Stable-isotope labeling by amino acids in cell culture (SILAC)-based mass spectrometry identified 109 proteins (which included 47 up-regulated and 62 down-regulated proteins) that were differentially expressed in the lung fibroblasts co-cultured with AuNP pretreated SAECs. There was altered expression of proteins such as Paxillin, breast cancer anti-estrogen resistance 1 and Caveolin-1, which are known to be involved in the cell adhesion process. Morphological studies revealed that there was a concomitant increase in cell adhesion and altered F-actin stress fiber arrangement involving vinculin in the lung fibroblasts. It is likely that phenotypic changes observed in the underlying lung fibroblasts were mediated by AuNP-induced downstream signals in the pretreated SAECs and cell-cell cross talk. Copyright © 2014 Elsevier Ltd. All rights reserved.

Proteomics Quality Control: Quality Control Software for MaxQuant Results.

PubMed

Bielow, Chris; Mastrobuoni, Guido; Kempa, Stefan

2016-03-04

Mass spectrometry-based proteomics coupled to liquid chromatography has matured into an automatized, high-throughput technology, producing data on the scale of multiple gigabytes per instrument per day. Consequently, an automated quality control (QC) and quality analysis (QA) capable of detecting measurement bias, verifying consistency, and avoiding propagation of error is paramount for instrument operators and scientists in charge of downstream analysis. We have developed an R-based QC pipeline called Proteomics Quality Control (PTXQC) for bottom-up LC-MS data generated by the MaxQuant software pipeline. PTXQC creates a QC report containing a comprehensive and powerful set of QC metrics, augmented with automated scoring functions. The automated scores are collated to create an overview heatmap at the beginning of the report, giving valuable guidance also to nonspecialists. Our software supports a wide range of experimental designs, including stable isotope labeling by amino acids in cell culture (SILAC), tandem mass tags (TMT), and label-free data. Furthermore, we introduce new metrics to score MaxQuant's Match-between-runs (MBR) functionality by which peptide identifications can be transferred across Raw files based on accurate retention time and m/z. Last but not least, PTXQC is easy to install and use and represents the first QC software capable of processing MaxQuant result tables. PTXQC is freely available at https://github.com/cbielow/PTXQC .

Quantitative Proteomics Analysis of VEGF-Responsive Endothelial Protein S-Nitrosylation Using Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) and LC-MS/MS.

PubMed

Zhang, Hong-Hai; Lechuga, Thomas J; Chen, Yuezhou; Yang, Yingying; Huang, Lan; Chen, Dong-Bao

2016-05-01

Adduction of a nitric oxide moiety (NO•) to cysteine(s), termed S-nitrosylation (SNO), is a novel mechanism for NO to regulate protein function directly. However, the endothelial SNO-protein network that is affected by endogenous and exogenous NO is obscure. This study was designed to develop a quantitative proteomics approach using stable isotope labeling by amino acids in cell culture for comparing vascular endothelial growth factor (VEGFA)- and NO donor-responsive endothelial nitroso-proteomes. Primary placental endothelial cells were labeled with "light" (L-(12)C6 (14)N4-Arg and L-(12)C6 (14)N2-Lys) or "heavy" (L-(13)C6 (15)N4-Arg and L-(13)C6 (15)N2-Lys) amino acids. The light cells were treated with an NO donor nitrosoglutathione (GSNO, 1 mM) or VEGFA (10 ng/ml) for 30 min, while the heavy cells received vehicle as control. Equal amounts of cellular proteins from the light (GSNO or VEGFA treated) and heavy cells were mixed for labeling SNO-proteins by the biotin switch technique and then trypsin digested. Biotinylated SNO-peptides were purified for identifying SNO-proteins by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Ratios of light to heavy SNO-peptides were calculated for determining the changes of the VEGFA- and GSNO-responsive endothelial nitroso-proteomes. A total of 387 light/heavy pairs of SNO-peptides were identified, corresponding to 213 SNO-proteins that include 125 common and 27 VEGFA- and 61 GSNO-responsive SNO-proteins. The specific SNO-cysteine(s) in each SNO-protein were simultaneously identified. Pathway analysis revealed that SNO-proteins are involved in various endothelial functions, including proliferation, motility, metabolism, and protein synthesis. We collectively conclude that endogenous NO on VEGFA stimulation and exogenous NO from GSNO affect common and different SNO-protein networks, implicating SNO as a critical mechanism for VEGFA stimulation of angiogenesis. © 2016 by the Society for the Study of Reproduction, Inc.

Lipid remodeling and an altered membrane-associated proteome may drive the differential effects of EPA and DHA treatment on skeletal muscle glucose uptake and protein accretion.

PubMed

Jeromson, Stewart; Mackenzie, Ivor; Doherty, Mary K; Whitfield, Phillip D; Bell, Gordon; Dick, James; Shaw, Andy; Rao, Francesco V; Ashcroft, Stephen P; Philp, Andrew; Galloway, Stuart D R; Gallagher, Iain; Hamilton, D Lee

2018-06-01

In striated muscle, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) have differential effects on the metabolism of glucose and differential effects on the metabolism of protein. We have shown that, despite similar incorporation, treatment of C 2 C 12 myotubes (CM) with EPA but not DHA improves glucose uptake and protein accretion. We hypothesized that these differential effects of EPA and DHA may be due to divergent shifts in lipidomic profiles leading to altered proteomic profiles. We therefore carried out an assessment of the impact of treating CM with EPA and DHA on lipidomic and proteomic profiles. Fatty acid methyl esters (FAME) analysis revealed that both EPA and DHA led to similar but substantials changes in fatty acid profiles with the exception of arachidonic acid, which was decreased only by DHA, and docosapentanoic acid (DPA), which was increased only by EPA treatment. Global lipidomic analysis showed that EPA and DHA induced large alterations in the cellular lipid profiles and in particular, the phospholipid classes. Subsequent targeted analysis confirmed that the most differentially regulated species were phosphatidylcholines and phosphatidylethanolamines containing long-chain fatty acids with five (EPA treatment) or six (DHA treatment) double bonds. As these are typically membrane-associated lipid species we hypothesized that these treatments differentially altered the membrane-associated proteome. Stable isotope labeling by amino acids in cell culture (SILAC)-based proteomics of the membrane fraction revealed significant divergence in the effects of EPA and DHA on the membrane-associated proteome. We conclude that the EPA-specific increase in polyunsaturated long-chain fatty acids in the phospholipid fraction is associated with an altered membrane-associated proteome and these may be critical events in the metabolic remodeling induced by EPA treatment.

Nucleolar protein trafficking in response to HIV-1 Tat: rewiring the nucleolus.

PubMed

Jarboui, Mohamed Ali; Bidoia, Carlo; Woods, Elena; Roe, Barbara; Wynne, Kieran; Elia, Giuliano; Hall, William W; Gautier, Virginie W

2012-01-01

The trans-activator Tat protein is a viral regulatory protein essential for HIV-1 replication. Tat trafficks to the nucleoplasm and the nucleolus. The nucleolus, a highly dynamic and structured membrane-less sub-nuclear compartment, is the site of rRNA and ribosome biogenesis and is involved in numerous cellular functions including transcriptional regulation, cell cycle control and viral infection. Importantly, transient nucleolar trafficking of both Tat and HIV-1 viral transcripts are critical in HIV-1 replication, however, the role(s) of the nucleolus in HIV-1 replication remains unclear. To better understand how the interaction of Tat with the nucleolar machinery contributes to HIV-1 pathogenesis, we investigated the quantitative changes in the composition of the nucleolar proteome of Jurkat T-cells stably expressing HIV-1 Tat fused to a TAP tag. Using an organellar proteomic approach based on mass spectrometry, coupled with Stable Isotope Labelling in Cell culture (SILAC), we quantified 520 proteins, including 49 proteins showing significant changes in abundance in Jurkat T-cell nucleolus upon Tat expression. Numerous proteins exhibiting a fold change were well characterised Tat interactors and/or known to be critical for HIV-1 replication. This suggests that the spatial control and subcellular compartimentaliation of these cellular cofactors by Tat provide an additional layer of control for regulating cellular machinery involved in HIV-1 pathogenesis. Pathway analysis and network reconstruction revealed that Tat expression specifically resulted in the nucleolar enrichment of proteins collectively participating in ribosomal biogenesis, protein homeostasis, metabolic pathways including glycolytic, pentose phosphate, nucleotides and amino acids biosynthetic pathways, stress response, T-cell signaling pathways and genome integrity. We present here the first differential profiling of the nucleolar proteome of T-cells expressing HIV-1 Tat. We discuss how these proteins collectively participate in interconnected networks converging to adapt the nucleolus dynamic activities, which favor host biosynthetic activities and may contribute to create a cellular environment supporting robust HIV-1 production.

Nucleolar Protein Trafficking in Response to HIV-1 Tat: Rewiring the Nucleolus

PubMed Central

Jarboui, Mohamed Ali; Bidoia, Carlo; Woods, Elena; Roe, Barbara; Wynne, Kieran; Elia, Giuliano; Hall, William W.; Gautier, Virginie W.

2012-01-01

The trans-activator Tat protein is a viral regulatory protein essential for HIV-1 replication. Tat trafficks to the nucleoplasm and the nucleolus. The nucleolus, a highly dynamic and structured membrane-less sub-nuclear compartment, is the site of rRNA and ribosome biogenesis and is involved in numerous cellular functions including transcriptional regulation, cell cycle control and viral infection. Importantly, transient nucleolar trafficking of both Tat and HIV-1 viral transcripts are critical in HIV-1 replication, however, the role(s) of the nucleolus in HIV-1 replication remains unclear. To better understand how the interaction of Tat with the nucleolar machinery contributes to HIV-1 pathogenesis, we investigated the quantitative changes in the composition of the nucleolar proteome of Jurkat T-cells stably expressing HIV-1 Tat fused to a TAP tag. Using an organellar proteomic approach based on mass spectrometry, coupled with Stable Isotope Labelling in Cell culture (SILAC), we quantified 520 proteins, including 49 proteins showing significant changes in abundance in Jurkat T-cell nucleolus upon Tat expression. Numerous proteins exhibiting a fold change were well characterised Tat interactors and/or known to be critical for HIV-1 replication. This suggests that the spatial control and subcellular compartimentaliation of these cellular cofactors by Tat provide an additional layer of control for regulating cellular machinery involved in HIV-1 pathogenesis. Pathway analysis and network reconstruction revealed that Tat expression specifically resulted in the nucleolar enrichment of proteins collectively participating in ribosomal biogenesis, protein homeostasis, metabolic pathways including glycolytic, pentose phosphate, nucleotides and amino acids biosynthetic pathways, stress response, T-cell signaling pathways and genome integrity. We present here the first differential profiling of the nucleolar proteome of T-cells expressing HIV-1 Tat. We discuss how these proteins collectively participate in interconnected networks converging to adapt the nucleolus dynamic activities, which favor host biosynthetic activities and may contribute to create a cellular environment supporting robust HIV-1 production. PMID:23166591

Functional proteomic analysis reveals the involvement of KIAA1199 in breast cancer growth, motility and invasiveness

PubMed Central

2014-01-01

Background KIAA1199 is a recently identified novel gene that is up-regulated in human cancer with poor survival. Our proteomic study on signaling polarity in chemotactic cells revealed KIAA1199 as a novel protein target that may be involved in cellular chemotaxis and motility. In the present study, we examined the functional significance of KIAA1199 expression in breast cancer growth, motility and invasiveness. Methods We validated the previous microarray observation by tissue microarray immunohistochemistry using a TMA slide containing 12 breast tumor tissue cores and 12 corresponding normal tissues. We performed the shRNA-mediated knockdown of KIAA1199 in MDA-MB-231 and HS578T cells to study the role of this protein in cell proliferation, migration and apoptosis in vitro. We studied the effects of KIAA1199 knockdown in vivo in two groups of mice (n = 5). We carried out the SILAC LC-MS/MS based proteomic studies on the involvement of KIAA1199 in breast cancer. Results KIAA1199 mRNA and protein was significantly overexpressed in breast tumor specimens and cell lines as compared with non-neoplastic breast tissues from large-scale microarray and studies of breast cancer cell lines and tumors. To gain deeper insights into the novel role of KIAA1199 in breast cancer, we modulated KIAA1199 expression using shRNA-mediated knockdown in two breast cancer cell lines (MDA-MB-231 and HS578T), expressing higher levels of KIAA1199. The KIAA1199 knockdown cells showed reduced motility and cell proliferation in vitro. Moreover, when the knockdown cells were injected into the mammary fat pads of female athymic nude mice, there was a significant decrease in tumor incidence and growth. In addition, quantitative proteomic analysis revealed that knockdown of KIAA1199 in breast cancer (MDA-MB-231) cells affected a broad range of cellular functions including apoptosis, metabolism and cell motility. Conclusions Our findings indicate that KIAA1199 may play an important role in breast tumor growth and invasiveness, and that it may represent a novel target for biomarker development and a novel therapeutic target for breast cancer. PMID:24628760

Proteomic analysis of polyribosomes identifies splicing factors as potential regulators of translation during mitosis.

PubMed

Aviner, Ranen; Hofmann, Sarah; Elman, Tamar; Shenoy, Anjana; Geiger, Tamar; Elkon, Ran; Ehrlich, Marcelo; Elroy-Stein, Orna

2017-06-02

Precise regulation of mRNA translation is critical for proper cell division, but little is known about the factors that mediate it. To identify mRNA-binding proteins that regulate translation during mitosis, we analyzed the composition of polysomes from interphase and mitotic cells using unbiased quantitative mass-spectrometry (LC-MS/MS). We found that mitotic polysomes are enriched with a subset of proteins involved in RNA processing, including alternative splicing and RNA export. To demonstrate that these may indeed be regulators of translation, we focused on heterogeneous nuclear ribonucleoprotein C (hnRNP C) as a test case and confirmed that it is recruited to elongating ribosomes during mitosis. Then, using a combination of pulsed SILAC, metabolic labeling and ribosome profiling, we showed that knockdown of hnRNP C affects both global and transcript-specific translation rates and found that hnRNP C is specifically important for translation of mRNAs that encode ribosomal proteins and translation factors. Taken together, our results demonstrate how proteomic analysis of polysomes can provide insight into translation regulation under various cellular conditions of interest and suggest that hnRNP C facilitates production of translation machinery components during mitosis to provide daughter cells with the ability to efficiently synthesize proteins as they enter G1 phase. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Taperin (c9orf75), a mutated gene in nonsyndromic deafness, encodes a vertebrate specific, nuclear localized protein phosphatase one alpha (PP1α) docking protein

PubMed Central

Ferrar, Tony; Chamousset, Delphine; De Wever, Veerle; Nimick, Mhairi; Andersen, Jens; Trinkle-Mulcahy, Laura; Moorhead, Greg B. G.

2012-01-01

Summary The promiscuous activity of protein phosphatase one (PP1) is controlled in the cell by associated proteins termed regulatory or targeting subunits. Using biochemical and proteomic approaches we demonstrate that the autosomal recessive nonsyndromic hearing loss gene, taperin (C9orf75), encodes a protein that preferentially docks the alpha isoform of PP1. Taperin associates with PP1 through a classic ‘RVxF’ motif and suppresses the general phosphatase activity of the enzyme. The steady-state localization of taperin is predominantly nuclear, however we demonstrate here that the protein can shuttle between the nucleus and cytoplasm and that it is found complexed to PP1 in both of these cellular compartments. Although originally identified as a hearing loss gene, Western blot analyses with taperin-specific antibodies revealed that the protein is widely expressed across mammalian tissues as multiple splice variants. Taperin is a recent proteome addition appearing during the vertebrate lineage with the PP1 binding site embedded within the most conserved region of the protein. Taperin also shares an ancestral relationship with the cytosolic actin binding protein phostensin, another PP1 interacting partner. Quantitative Stable Isotope Labeling by Amino acids in Culture (SILAC)-based mass spectrometry was employed to uncover additional taperin binding partners, and revealed an interaction with the DNA damage response proteins Ku70, Ku80, PARP and topoisomerases I and IIα. Consistent with this, we demonstrate the active recruitment of taperin to sites of DNA damage. This makes taperin a new addition to the family of PP1 targeting subunits involved in the DNA damage repair pathway. PMID:23213405

Liquid Chromatography-Mass Spectrometry-based Quantitative Proteomics

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

Xie, Fang; Liu, Tao; Qian, Weijun

2011-07-22

Liquid chromatography-mass spectrometry (LC-MS)-based quantitative proteomics has become increasingly applied for a broad range of biological applications due to growing capabilities for broad proteome coverage and good accuracy in quantification. Herein, we review the current LC-MS-based quantification methods with respect to their advantages and limitations, and highlight their potential applications.

To label or not to label: applications of quantitative proteomics in neuroscience research.

PubMed

Filiou, Michaela D; Martins-de-Souza, Daniel; Guest, Paul C; Bahn, Sabine; Turck, Christoph W

2012-02-01

Proteomics has provided researchers with a sophisticated toolbox of labeling-based and label-free quantitative methods. These are now being applied in neuroscience research where they have already contributed to the elucidation of fundamental mechanisms and the discovery of candidate biomarkers. In this review, we evaluate and compare labeling-based and label-free quantitative proteomic techniques for applications in neuroscience research. We discuss the considerations required for the analysis of brain and central nervous system specimens, the experimental design of quantitative proteomic workflows as well as the feasibility, advantages, and disadvantages of the available techniques for neuroscience-oriented questions. Furthermore, we assess the use of labeled standards as internal controls for comparative studies in humans and review applications of labeling-based and label-free mass spectrometry approaches in relevant model organisms and human subjects. Providing a comprehensive guide of feasible and meaningful quantitative proteomic methodologies for neuroscience research is crucial not only for overcoming current limitations but also for gaining useful insights into brain function and translating proteomics from bench to bedside. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Recent advances in mass spectrometry-based proteomics of gastric cancer.

PubMed

Kang, Changwon; Lee, Yejin; Lee, J Eugene

2016-10-07

The last decade has witnessed remarkable technological advances in mass spectrometry-based proteomics. The development of proteomics techniques has enabled the reliable analysis of complex proteomes, leading to the identification and quantification of thousands of proteins in gastric cancer cells, tissues, and sera. This quantitative information has been used to profile the anomalies in gastric cancer and provide insights into the pathogenic mechanism of the disease. In this review, we mainly focus on the advances in mass spectrometry and quantitative proteomics that were achieved in the last five years and how these up-and-coming technologies are employed to track biochemical changes in gastric cancer cells. We conclude by presenting a perspective on quantitative proteomics and its future applications in the clinic and translational gastric cancer research.

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.

Redox-regulated dynamic interplay between Cox19 and the copper-binding protein Cox11 in the intermembrane space of mitochondria facilitates biogenesis of cytochrome c oxidase

PubMed Central

Bode, Manuela; Woellhaf, Michael W.; Bohnert, Maria; van der Laan, Martin; Sommer, Frederik; Jung, Martin; Zimmermann, Richard; Schroda, Michael; Herrmann, Johannes M.

2015-01-01

Members of the twin Cx9C protein family constitute the largest group of proteins in the intermembrane space (IMS) of mitochondria. Despite their conserved nature and their essential role in the biogenesis of the respiratory chain, the molecular function of twin Cx9C proteins is largely unknown. We performed a SILAC-based quantitative proteomic analysis to identify interaction partners of the conserved twin Cx9C protein Cox19. We found that Cox19 interacts in a dynamic manner with Cox11, a copper transfer protein that facilitates metalation of the Cu(B) center of subunit 1 of cytochrome c oxidase. The interaction with Cox11 is critical for the stable accumulation of Cox19 in mitochondria. Cox19 consists of a helical hairpin structure that forms a hydrophobic surface characterized by two highly conserved tyrosine-leucine dipeptides. These residues are essential for Cox19 function and its specific binding to a cysteine-containing sequence in Cox11. Our observations suggest that an oxidative modification of this cysteine residue of Cox11 stimulates Cox19 binding, pointing to a redox-regulated interplay of Cox19 and Cox11 that is critical for copper transfer in the IMS and thus for biogenesis of cytochrome c oxidase. PMID:25926683

Quantitative proteomics in the field of microbiology.

PubMed

Otto, Andreas; Becher, Dörte; Schmidt, Frank

2014-03-01

Quantitative proteomics has become an indispensable analytical tool for microbial research. Modern microbial proteomics covers a wide range of topics in basic and applied research from in vitro characterization of single organisms to unravel the physiological implications of stress/starvation to description of the proteome content of a cell at a given time. With the techniques available, ranging from classical gel-based procedures to modern MS-based quantitative techniques, including metabolic and chemical labeling, as well as label-free techniques, quantitative proteomics is today highly successful in sophisticated settings of high complexity such as host-pathogen interactions, mixed microbial communities, and microbial metaproteomics. In this review, we will focus on the vast range of techniques practically applied in current research with an introduction of the workflows used for quantitative comparisons, a description of the advantages/disadvantages of the various methods, reference to hallmark publications and presentation of applications in current microbial research. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Standardized protocols for quality control of MRM-based plasma proteomic workflows.

PubMed

Percy, Andrew J; Chambers, Andrew G; Smith, Derek S; Borchers, Christoph H

2013-01-04

Mass spectrometry (MS)-based proteomics is rapidly emerging as a viable technology for the identification and quantitation of biological samples, such as human plasma--the most complex yet commonly employed biofluid in clinical analyses. The transition from a qualitative to quantitative science is required if proteomics is going to successfully make the transition to a clinically useful technique. MS, however, has been criticized for a lack of reproducibility and interlaboratory transferability. Currently, the MS and plasma proteomics communities lack standardized protocols and reagents to ensure that high-quality quantitative data can be accurately and precisely reproduced by laboratories across the world using different MS technologies. Toward addressing this issue, we have developed standard protocols for multiple reaction monitoring (MRM)-based assays with customized isotopically labeled internal standards for quality control of the sample preparation workflow and the MS platform in quantitative plasma proteomic analyses. The development of reference standards and their application to a single MS platform is discussed herein, along with the results from intralaboratory tests. The tests highlighted the importance of the reference standards in assessing the efficiency and reproducibility of the entire bottom-up proteomic workflow and revealed errors related to the sample preparation and performance quality and deficits of the MS and LC systems. Such evaluations are necessary if MRM-based quantitative plasma proteomics is to be used in verifying and validating putative disease biomarkers across different research laboratories and eventually in clinical laboratories.

Differential proteomic analysis of mouse macrophages exposed to adsorbate-loaded heavy fuel oil derived combustion particles using an automated sample-preparation workflow.

PubMed

Kanashova, Tamara; Popp, Oliver; Orasche, Jürgen; Karg, Erwin; Harndorf, Horst; Stengel, Benjamin; Sklorz, Martin; Streibel, Thorsten; Zimmermann, Ralf; Dittmar, Gunnar

2015-08-01

Ship diesel combustion particles are known to cause broad cytotoxic effects and thereby strongly impact human health. Particles from heavy fuel oil (HFO) operated ships are considered as particularly dangerous. However, little is known about the relevant components of the ship emission particles. In particular, it is interesting to know if the particle cores, consisting of soot and metal oxides, or the adsorbate layers, consisting of semi- and low-volatile organic compounds and salts, are more relevant. We therefore sought to relate the adsorbates and the core composition of HFO combustion particles to the early cellular responses, allowing for the development of measures that counteract their detrimental effects. Hence, the semi-volatile coating of HFO-operated ship diesel engine particles was removed by stepwise thermal stripping using different temperatures. RAW 264.7 macrophages were exposed to native and thermally stripped particles in submersed culture. Proteomic changes were monitored by two different quantitative mass spectrometry approaches, stable isotope labeling by amino acids in cell culture (SILAC) and dimethyl labeling. Our data revealed that cells reacted differently to native or stripped HFO combustion particles. Cells exposed to thermally stripped particles showed a very differential reaction with respect to the composition of the individual chemical load of the particle. The cellular reactions of the HFO particles included reaction to oxidative stress, reorganization of the cytoskeleton and changes in endocytosis. Cells exposed to the 280 °C treated particles showed an induction of RNA-related processes, a number of mitochondria-associated processes as well as DNA damage response, while the exposure to 580 °C treated HFO particles mainly induced the regulation of intracellular transport. In summary, our analysis based on a highly reproducible automated proteomic sample-preparation procedure shows a diverse cellular response, depending on the soot particle composition. In particular, it was shown that both the molecules of the adsorbate layer as well as particle cores induced strong but different effects in the exposed cells.

Quantitative body fluid proteomics in medicine - A focus on minimal invasiveness.

PubMed

Csősz, Éva; Kalló, Gergő; Márkus, Bernadett; Deák, Eszter; Csutak, Adrienne; Tőzsér, József

2017-02-05

Identification of new biomarkers specific for various pathological conditions is an important field in medical sciences. Body fluids have emerging potential in biomarker studies especially those which are continuously available and can be collected by non-invasive means. Changes in the protein composition of body fluids such as tears, saliva, sweat, etc. may provide information on both local and systemic conditions of medical relevance. In this review, our aim is to discuss the quantitative proteomics techniques used in biomarker studies, and to present advances in quantitative body fluid proteomics of non-invasively collectable body fluids with relevance to biomarker identification. The advantages and limitations of the widely used quantitative proteomics techniques are also presented. Based on the reviewed literature, we suggest an ideal pipeline for body fluid analyses aiming at biomarkers discoveries: starting from identification of biomarker candidates by shotgun quantitative proteomics or protein arrays, through verification of potential biomarkers by targeted mass spectrometry, to the antibody-based validation of biomarkers. The importance of body fluids as a rich source of biomarkers is discussed. Quantitative proteomics is a challenging part of proteomics applications. The body fluids collected by non-invasive means have high relevance in medicine; they are good sources for biomarkers used in establishing the diagnosis, follow up of disease progression and predicting high risk groups. The review presents the most widely used quantitative proteomics techniques in body fluid analysis and lists the potential biomarkers identified in tears, saliva, sweat, nasal mucus and urine for local and systemic diseases. Copyright © 2016 Elsevier B.V. All rights reserved.

Using PSEA-Quant for Protein Set Enrichment Analysis of Quantitative Mass Spectrometry-Based Proteomics

PubMed Central

Lavallée-Adam, Mathieu

2017-01-01

PSEA-Quant analyzes quantitative mass spectrometry-based proteomics datasets to identify enrichments of annotations contained in repositories such as the Gene Ontology and Molecular Signature databases. It allows users to identify the annotations that are significantly enriched for reproducibly quantified high abundance proteins. PSEA-Quant is available on the web and as a command-line tool. It is compatible with all label-free and isotopic labeling-based quantitative proteomics methods. This protocol describes how to use PSEA-Quant and interpret its output. The importance of each parameter as well as troubleshooting approaches are also discussed. PMID:27010334

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.

Global Impact of Oncogenic Src on a Phosphotyrosine Proteome

PubMed Central

Luo, Weifeng; Slebos, Robbert J.; Hill, Salisha; Li, Ming; Brábek, Jan; Amanchy, Ramars; Chaerkady, Raghothama; Pandey, Akhilesh; Ham, Amy-Joan L.; Hanks, Steven K.

2008-01-01

Elevated activity of Src, the first characterized protein-tyrosine kinase, is associated with progression of many human cancers, and Src has attracted interest as a therapeutic target. Src is known to act in various receptor signaling systems to impact cell behavior, yet it remains likely that the spectrum of Src protein substrates relevant to cancer is incompletely understood. To better understand the cellular impact of deregulated Src kinase activity, we extensively applied a mass spectrometry shotgun phosphotyrosine (pTyr) proteomics strategy to obtain global pTyr profiles of Src-transformed mouse fibroblasts as well as their nontransformed counterparts. A total of 867 peptides representing 563 distinct pTyr sites on 374 different proteins were identified from the Src-transformed cells, while 514 peptides representing 275 pTyr sites on 167 proteins were identified from nontransformed cells. Distinct characteristics of the two profiles were revealed by spectral counting, indicative of pTyr site relative abundance, and by complementary quantitative analysis using stable isotope labeling with amino acids in cell culture (SILAC). While both pTyr profiles are replete with sites on signaling and adhesion/cytoskeletal regulatory proteins, the Src-transformed profile is more diverse with enrichment in sites on metabolic enzymes and RNA and protein synthesis and processing machinery. Forty-three pTyr sites (32 proteins) are predicted as major biologically relevant Src targets on the basis of frequent identification in both cell populations. This select group, of particular interest as diagnostic biomarkers, includes well-established Src sites on signaling/adhesion/cytoskeletal proteins, but also uncharacterized sites of potential relevance to the transformed cell phenotype. PMID:18563927

Systematic analysis of protein turnover in primary cells.

PubMed

Mathieson, Toby; Franken, Holger; Kosinski, Jan; Kurzawa, Nils; Zinn, Nico; Sweetman, Gavain; Poeckel, Daniel; Ratnu, Vikram S; Schramm, Maike; Becher, Isabelle; Steidel, Michael; Noh, Kyung-Min; Bergamini, Giovanna; Beck, Martin; Bantscheff, Marcus; Savitski, Mikhail M

2018-02-15

A better understanding of proteostasis in health and disease requires robust methods to determine protein half-lives. Here we improve the precision and accuracy of peptide ion intensity-based quantification, enabling more accurate protein turnover determination in non-dividing cells by dynamic SILAC-based proteomics. This approach allows exact determination of protein half-lives ranging from 10 to >1000 h. We identified 4000-6000 proteins in several non-dividing cell types, corresponding to 9699 unique protein identifications over the entire data set. We observed similar protein half-lives in B-cells, natural killer cells and monocytes, whereas hepatocytes and mouse embryonic neurons show substantial differences. Our data set extends and statistically validates the previous observation that subunits of protein complexes tend to have coherent turnover. Moreover, analysis of different proteasome and nuclear pore complex assemblies suggests that their turnover rate is architecture dependent. These results illustrate that our approach allows investigating protein turnover and its implications in various cell types.

Systematic Comparison of Label-Free, Metabolic Labeling, and Isobaric Chemical Labeling for Quantitative Proteomics on LTQ Orbitrap Velos

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

Li, Zhou; Adams, Rachel M; Chourey, Karuna

2012-01-01

A variety of quantitative proteomics methods have been developed, including label-free, metabolic labeling, and isobaric chemical labeling using iTRAQ or TMT. Here, these methods were compared in terms of the depth of proteome coverage, quantification accuracy, precision, and reproducibility using a high-performance hybrid mass spectrometer, LTQ Orbitrap Velos. Our results show that (1) the spectral counting method provides the deepest proteome coverage for identification, but its quantification performance is worse than labeling-based approaches, especially the quantification reproducibility; (2) metabolic labeling and isobaric chemical labeling are capable of accurate, precise, and reproducible quantification and provide deep proteome coverage for quantification. Isobaricmore » chemical labeling surpasses metabolic labeling in terms of quantification precision and reproducibility; (3) iTRAQ and TMT perform similarly in all aspects compared in the current study using a CID-HCD dual scan configuration. Based on the unique advantages of each method, we provide guidance for selection of the appropriate method for a quantitative proteomics study.« less

Using PSEA-Quant for Protein Set Enrichment Analysis of Quantitative Mass Spectrometry-Based Proteomics.

PubMed

Lavallée-Adam, Mathieu; Yates, John R

2016-03-24

PSEA-Quant analyzes quantitative mass spectrometry-based proteomics datasets to identify enrichments of annotations contained in repositories such as the Gene Ontology and Molecular Signature databases. It allows users to identify the annotations that are significantly enriched for reproducibly quantified high abundance proteins. PSEA-Quant is available on the Web and as a command-line tool. It is compatible with all label-free and isotopic labeling-based quantitative proteomics methods. This protocol describes how to use PSEA-Quant and interpret its output. The importance of each parameter as well as troubleshooting approaches are also discussed. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

Identification of Missing Proteins Defined by Chromosome-Centric Proteome Project in the Cytoplasmic Detergent-Insoluble Proteins.

PubMed

Chen, Yang; Li, Yaxing; Zhong, Jiayong; Zhang, Jing; Chen, Zhipeng; Yang, Lijuan; Cao, Xin; He, Qing-Yu; Zhang, Gong; Wang, Tong

2015-09-04

Finding protein evidence (PE) for protein coding genes is a primary task of the Phase I Chromosome-Centric Human Proteome Project (C-HPP). Currently, there are 2948 PE level 2-4 coding genes per neXtProt, which are deemed missing proteins in the human proteome. As most samples prepared and analyzed in the C-HPP framework were focusing on detergent soluble proteins, we posit that as a natural composition the cytoplasmic detergent-insoluble proteins (DIPs) represent a source of finding missing proteins. We optimized a workflow and separated cytoplasmic DIPs from three human lung and three human hepatoma cell lines via differential speed centrifugation. We verified that the detergent-soluble proteins (DSPs) could be sufficiently depleted and the cytoplasmic DIP isolation was partially reproducible with Spearman r > 0.70 according to two independent SILAC MS experiments. Through label-free MS, we identified 4524 and 4156 DIPs from lung and liver cells, respectively. Among them, a total of 23 missing proteins (22 PE2 and 1 PE4) were identified by MS, and 18 of them had translation evidence; in addition, six PE5 proteins were identified by MS, three with translation evidence. We showed that cytoplasmic DIPs were not an enrichment of transmembrane proteins and were chromosome-, cell type-, and tissue-specific. Furthermore, we demonstrated that DIPs were distinct from DSPs in terms of structural and physical-chemical features. In conclusion, we have found 23 missing proteins and 6 PE5 proteins from the cytoplasmic insoluble proteome that is biologically and physical-chemically different from the soluble proteome, suggesting that cytoplasmic DIPs carry comprehensive and valuable information for finding PE of missing proteins. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD001694.

GProX, a user-friendly platform for bioinformatics analysis and visualization of quantitative proteomics data.

PubMed

Rigbolt, Kristoffer T G; Vanselow, Jens T; Blagoev, Blagoy

2011-08-01

Recent technological advances have made it possible to identify and quantify thousands of proteins in a single proteomics experiment. As a result of these developments, the analysis of data has become the bottleneck of proteomics experiment. To provide the proteomics community with a user-friendly platform for comprehensive analysis, inspection and visualization of quantitative proteomics data we developed the Graphical Proteomics Data Explorer (GProX)(1). The program requires no special bioinformatics training, as all functions of GProX are accessible within its graphical user-friendly interface which will be intuitive to most users. Basic features facilitate the uncomplicated management and organization of large data sets and complex experimental setups as well as the inspection and graphical plotting of quantitative data. These are complemented by readily available high-level analysis options such as database querying, clustering based on abundance ratios, feature enrichment tests for e.g. GO terms and pathway analysis tools. A number of plotting options for visualization of quantitative proteomics data is available and most analysis functions in GProX create customizable high quality graphical displays in both vector and bitmap formats. The generic import requirements allow data originating from essentially all mass spectrometry platforms, quantitation strategies and software to be analyzed in the program. GProX represents a powerful approach to proteomics data analysis providing proteomics experimenters with a toolbox for bioinformatics analysis of quantitative proteomics data. The program is released as open-source and can be freely downloaded from the project webpage at http://gprox.sourceforge.net.

GProX, a User-Friendly Platform for Bioinformatics Analysis and Visualization of Quantitative Proteomics Data*

PubMed Central

Rigbolt, Kristoffer T. G.; Vanselow, Jens T.; Blagoev, Blagoy

2011-01-01

Recent technological advances have made it possible to identify and quantify thousands of proteins in a single proteomics experiment. As a result of these developments, the analysis of data has become the bottleneck of proteomics experiment. To provide the proteomics community with a user-friendly platform for comprehensive analysis, inspection and visualization of quantitative proteomics data we developed the Graphical Proteomics Data Explorer (GProX)1. The program requires no special bioinformatics training, as all functions of GProX are accessible within its graphical user-friendly interface which will be intuitive to most users. Basic features facilitate the uncomplicated management and organization of large data sets and complex experimental setups as well as the inspection and graphical plotting of quantitative data. These are complemented by readily available high-level analysis options such as database querying, clustering based on abundance ratios, feature enrichment tests for e.g. GO terms and pathway analysis tools. A number of plotting options for visualization of quantitative proteomics data is available and most analysis functions in GProX create customizable high quality graphical displays in both vector and bitmap formats. The generic import requirements allow data originating from essentially all mass spectrometry platforms, quantitation strategies and software to be analyzed in the program. GProX represents a powerful approach to proteomics data analysis providing proteomics experimenters with a toolbox for bioinformatics analysis of quantitative proteomics data. The program is released as open-source and can be freely downloaded from the project webpage at http://gprox.sourceforge.net. PMID:21602510

Identifying chromatin readers using a SILAC-based histone peptide pull-down approach.

PubMed

Vermeulen, Michiel

2012-01-01

Posttranslational modifications (PTMs) on core histones regulate essential processes inside the nucleus such as transcription, replication, and DNA repair. An important function of histone PTMs is the recruitment or stabilization of chromatin-modifying proteins, which are also called chromatin "readers." We have developed a generic SILAC-based peptide pull-down approach to identify such readers for histone PTMs in an unbiased manner. In this chapter, the workflow behind this method will be presented in detail. Copyright © 2012 Elsevier Inc. All rights reserved.

Solution In-Line Alpha Counter (SILAC) Instruction Manual-Version 4.00

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

Steven M. Alferink; Joel E. Farnham; Malcolm M. Fowler

2002-06-01

The Solution In-Line Alpha Counter (SILAC) provides near real-time alpha activity measurements of aqueous solutions in gloveboxes located in the Plutonium Facility (TA-55) at Los Alamos National Laboratory (LANL). The SILAC detector and its interface software were first developed by Joel Farnham at LANL [1]. This instruction manual describes the features of the SILAC interface software and contains the schematic and fabrication instructions for the detector.

The N-myristoylome of Trypanosoma cruzi

PubMed Central

Roberts, Adam J.; Fairlamb, Alan H.

2016-01-01

Protein N-myristoylation is catalysed by N-myristoyltransferase (NMT), an essential and druggable target in Trypanosoma cruzi, the causative agent of Chagas’ disease. Here we have employed whole cell labelling with azidomyristic acid and click chemistry to identify N-myristoylated proteins in different life cycle stages of the parasite. Only minor differences in fluorescent-labelling were observed between the dividing forms (the insect epimastigote and mammalian amastigote stages) and the non-dividing trypomastigote stage. Using a combination of label-free and stable isotope labelling of cells in culture (SILAC) based proteomic strategies in the presence and absence of the NMT inhibitor DDD85646, we identified 56 proteins enriched in at least two out of the three experimental approaches. Of these, 6 were likely to be false positives, with the remaining 50 commencing with amino acids MG at the N-terminus in one or more of the T. cruzi genomes. Most of these are proteins of unknown function (32), with the remainder (18) implicated in a diverse range of critical cellular and metabolic functions such as intracellular transport, cell signalling and protein turnover. In summary, we have established that 0.43–0.46% of the proteome is N-myristoylated in T. cruzi approaching that of other eukaryotic organisms (0.5–1.7%). PMID:27492267

Two flagellar BAR domain proteins in Trypanosoma brucei with stage-specific regulation

PubMed Central

Cicova, Zdenka; Dejung, Mario; Skalicky, Tomas; Eisenhuth, Nicole; Hanselmann, Steffen; Morriswood, Brooke; Figueiredo, Luisa M.; Butter, Falk; Janzen, Christian J.

2016-01-01

Trypanosomes are masters of adaptation to different host environments during their complex life cycle. Large-scale proteomic approaches provide information on changes at the cellular level, and in a systematic way. However, detailed work on single components is necessary to understand the adaptation mechanisms on a molecular level. Here, we have performed a detailed characterization of a bloodstream form (BSF) stage-specific putative flagellar host adaptation factor Tb927.11.2400, identified previously in a SILAC-based comparative proteome study. Tb927.11.2400 shares 38% amino acid identity with TbFlabarin (Tb927.11.2410), a procyclic form (PCF) stage-specific flagellar BAR domain protein. We named Tb927.11.2400 TbFlabarin-like (TbFlabarinL), and demonstrate that it originates from a gene duplication event, which occurred in the African trypanosomes. TbFlabarinL is not essential for the growth of the parasites under cell culture conditions and it is dispensable for developmental differentiation from BSF to the PCF in vitro. We generated TbFlabarinL-specific antibodies, and showed that it localizes in the flagellum. Co-immunoprecipitation experiments together with a biochemical cell fractionation suggest a dual association of TbFlabarinL with the flagellar membrane and the components of the paraflagellar rod. PMID:27779220

Development of gel-filter method for high enrichment of low-molecular weight proteins from serum.

PubMed

Chen, Lingsheng; Zhai, Linhui; Li, Yanchang; Li, Ning; Zhang, Chengpu; Ping, Lingyan; Chang, Lei; Wu, Junzhu; Li, Xiangping; Shi, Deshun; Xu, Ping

2015-01-01

The human serum proteome has been extensively screened for biomarkers. However, the large dynamic range of protein concentrations in serum and the presence of highly abundant and large molecular weight proteins, make identification and detection changes in the amount of low-molecular weight proteins (LMW, molecular weight ≤ 30kDa) difficult. Here, we developed a gel-filter method including four layers of different concentration of tricine SDS-PAGE-based gels to block high-molecular weight proteins and enrich LMW proteins. By utilizing this method, we identified 1,576 proteins (n = 2) from 10 μL serum. Among them, 559 (n = 2) proteins belonged to LMW proteins. Furthermore, this gel-filter method could identify 67.4% and 39.8% more LMW proteins than that in representative methods of glycine SDS-PAGE and optimized-DS, respectively. By utilizing SILAC-AQUA approach with labeled recombinant protein as internal standard, the recovery rate for GST spiked in serum during the treatment of gel-filter, optimized-DS, and ProteoMiner was 33.1 ± 0.01%, 18.7 ± 0.01% and 9.6 ± 0.03%, respectively. These results demonstrate that the gel-filter method offers a rapid, highly reproducible and efficient approach for screening biomarkers from serum through proteomic analyses.

The arginylation branch of the N-end rule pathway positively regulates cellular autophagic flux and clearance of proteotoxic proteins

PubMed Central

Jiang, Yanxialei; Lee, Jeeyoung; Lee, Jung Hoon; Lee, Joon Won; Kim, Ji Hyeon; Choi, Won Hoon; Yoo, Young Dong; Cha-Molstad, Hyunjoo; Kim, Bo Yeon; Kwon, Yong Tae; Noh, Sue Ah; Kim, Kwang Pyo; Lee, Min Jae

2016-01-01

ABSTRACT The N-terminal amino acid of a protein is an essential determinant of ubiquitination and subsequent proteasomal degradation in the N-end rule pathway. Using para-chloroamphetamine (PCA), a specific inhibitor of the arginylation branch of the pathway (Arg/N-end rule pathway), we identified that blocking the Arg/N-end rule pathway significantly impaired the fusion of autophagosomes with lysosomes. Under ER stress, ATE1-encoded Arg-tRNA-protein transferases carry out the N-terminal arginylation of the ER heat shock protein HSPA5 that initially targets cargo proteins, along with SQSTM1, to the autophagosome. At the late stage of autophagy, however, proteasomal degradation of arginylated HSPA5 might function as a critical checkpoint for the proper progression of autophagic flux in the cells. Consistently, the inhibition of the Arg/N-end rule pathway with PCA significantly elevated levels of MAPT and huntingtin aggregates, accompanied by increased numbers of LC3 and SQSTM1 puncta. Cells treated with the Arg/N-end rule inhibitor became more sensitized to proteotoxic stress-induced cytotoxicity. SILAC-based quantitative proteomics also revealed that PCA significantly alters various biological pathways, including cellular responses to stress, nutrient, and DNA damage, which are also closely involved in modulation of autophagic responses. Thus, our results indicate that the Arg/N-end rule pathway may function to actively protect cells from detrimental effects of cellular stresses, including proteotoxic protein accumulation, by positively regulating autophagic flux. PMID:27560450

Statistical design of quantitative mass spectrometry-based proteomic experiments.

PubMed

Oberg, Ann L; Vitek, Olga

2009-05-01

We review the fundamental principles of statistical experimental design, and their application to quantitative mass spectrometry-based proteomics. We focus on class comparison using Analysis of Variance (ANOVA), and discuss how randomization, replication and blocking help avoid systematic biases due to the experimental procedure, and help optimize our ability to detect true quantitative changes between groups. We also discuss the issues of pooling multiple biological specimens for a single mass analysis, and calculation of the number of replicates in a future study. When applicable, we emphasize the parallels between designing quantitative proteomic experiments and experiments with gene expression microarrays, and give examples from that area of research. We illustrate the discussion using theoretical considerations, and using real-data examples of profiling of disease.

Integrated proteomic and N-glycoproteomic analyses of doxorubicin sensitive and resistant ovarian cancer cells reveal glycoprotein alteration in protein abundance and glycosylation

PubMed Central

Hou, Junjie; Zhang, Chengqian; Xue, Peng; Wang, Jifeng; Chen, Xiulan; Guo, Xiaojing; Yang, Fuquan

2017-01-01

Ovarian cancer is one of the most common cancer among women in the world, and chemotherapy remains the principal treatment for patients. However, drug resistance is a major obstacle to the effective treatment of ovarian cancers and the underlying mechanism is not clear. An increased understanding of the mechanisms that underline the pathogenesis of drug resistance is therefore needed to develop novel therapeutics and diagnostic. Herein, we report the comparative analysis of the doxorubicin sensitive OVCAR8 cells and its doxorubicin-resistant variant NCI/ADR-RES cells using integrated global proteomics and N-glycoproteomics. A total of 1525 unique N-glycosite-containing peptides from 740 N-glycoproteins were identified and quantified, of which 253 N-glycosite-containing peptides showed significant change in the NCI/ADR-RES cells. Meanwhile, stable isotope labeling by amino acids in cell culture (SILAC) based comparative proteomic analysis of the two ovarian cancer cells led to the quantification of 5509 proteins. As about 50% of the identified N-glycoproteins are low-abundance membrane proteins, only 44% of quantified unique N-glycosite-containing peptides had corresponding protein expression ratios. The comparison and calibration of the N-glycoproteome versus the proteome classified 14 change patterns of N-glycosite-containing peptides, including 8 up-regulated N-glycosite-containing peptides with the increased glycosylation sites occupancy, 35 up-regulated N-glycosite-containing peptides with the unchanged glycosylation sites occupancy, 2 down-regulated N-glycosite-containing peptides with the decreased glycosylation sites occupancy, 46 down-regulated N-glycosite-containing peptides with the unchanged glycosylation sites occupancy. Integrated proteomic and N-glycoproteomic analyses provide new insights, which can help to unravel the relationship of N-glycosylation and multidrug resistance (MDR), understand the mechanism of MDR, and discover the new diagnostic and therapeutic targets. PMID:28077793

A Suite of "Minimalist" Photo-Crosslinkers for Live-Cell Imaging and Chemical Proteomics: Case Study with BRD4 Inhibitors.

PubMed

Pan, Sijun; Jang, Se-Young; Wang, Danyang; Liew, Si Si; Li, Zhengqiu; Lee, Jun-Seok; Yao, Shao Q

2017-09-18

Affinity-based probes (AfBPs) provide a powerful tool for large-scale chemoproteomic studies of drug-target interactions. The development of high-quality probes capable of recapitulating genuine drug-target engagement, however, could be challenging. "Minimalist" photo-crosslinkers, which contain an alkyl diazirine group and a chemically tractable tag, could alleviate such challenges, but few are currently available. Herein, we have developed new alkyl diazirine-containing photo-crosslinkers with different bioorthogonal tags. They were subsequently used to create a suite of AfBPs based on GW841819X (a small molecule inhibitor of BRD4). Through in vitro and in situ studies under conditions that emulated native drug-target interactions, we have obtained better insights into how a tag might affect the probe's performance. Finally, SILAC-based chemoproteomic studies have led to the discovery of a novel off-target, APEX1. Further studies showed GW841819X binds to APEX1 and caused up-regulation of endogenous DNMT1 expression under normoxia conditions. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

[Progress in stable isotope labeled quantitative proteomics methods].

PubMed

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

2013-06-01

Quantitative proteomics is an important research field in post-genomics era. There are two strategies for proteome quantification: label-free methods and stable isotope labeling methods which have become the most important strategy for quantitative proteomics at present. In the past few years, a number of quantitative methods have been developed, which support the fast development in biology research. In this work, we discuss the progress in the stable isotope labeling methods for quantitative proteomics including relative and absolute quantitative proteomics, and then give our opinions on the outlook of proteome quantification methods.

A Critical Appraisal of Techniques, Software Packages, and Standards for Quantitative Proteomic Analysis

PubMed Central

Lawless, Craig; Hubbard, Simon J.; Fan, Jun; Bessant, Conrad; Hermjakob, Henning; Jones, Andrew R.

2012-01-01

Abstract New methods for performing quantitative proteome analyses based on differential labeling protocols or label-free techniques are reported in the literature on an almost monthly basis. In parallel, a correspondingly vast number of software tools for the analysis of quantitative proteomics data has also been described in the literature and produced by private companies. In this article we focus on the review of some of the most popular techniques in the field and present a critical appraisal of several software packages available to process and analyze the data produced. We also describe the importance of community standards to support the wide range of software, which may assist researchers in the analysis of data using different platforms and protocols. It is intended that this review will serve bench scientists both as a useful reference and a guide to the selection and use of different pipelines to perform quantitative proteomics data analysis. We have produced a web-based tool (http://www.proteosuite.org/?q=other_resources) to help researchers find appropriate software for their local instrumentation, available file formats, and quantitative methodology. PMID:22804616

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.

Cd²⁺-induced alteration of the global proteome of human skin fibroblast cells.

PubMed

Prins, John M; Fu, Lijuan; Guo, Lei; Wang, Yinsheng

2014-03-07

Cadmium (Cd(2+)) is a toxic heavy metal and a well-known human carcinogen. The toxic effects of Cd(2+) on biological systems are diverse and thought to be exerted through a complex array of mechanisms. Despite the large number of studies aimed to elucidate the toxic mechanisms of action of Cd(2+), few have been targeted toward investigating the ability of Cd(2+) to disrupt multiple cellular pathways simultaneously and the overall cellular responses toward Cd(2+) exposure. In this study, we employed a quantitative proteomic method, relying on stable isotope labeling by amino acids in cell culture (SILAC) and LC-MS/MS, to assess the Cd(2+)-induced simultaneous alterations of multiple cellular pathways in cultured human skin fibroblast cells. By using this approach, we were able to quantify 2931 proteins, and 400 of them displayed significantly changed expression following Cd(2+) exposure. Our results unveiled that Cd(2+) treatment led to the marked upregulation of several antioxidant enzymes (e.g., metallothionein-1G, superoxide dismutase, pyridoxal kinase, etc.), enzymes associated with glutathione biosynthesis and homeostasis (e.g., glutathione S-transferases, glutathione synthetase, glutathione peroxidase, etc.), and proteins involved in cellular energy metabolism (e.g., glycolysis, pentose phosphate pathway, and the citric acid cycle). Additionally, we found that Cd(2+) treatment resulted in the elevated expression of two isoforms of dimethylarginine dimethylaminohydrolase (DDAH I and II), enzymes known to play a key role in regulating nitric oxide biosynthesis. Consistent with these findings, we observed elevated formation of nitric oxide in human skin (GM00637) and lung (IMR-90) fibroblast cells following Cd(2+) exposure. The upregulation of DDAH I and II suggests a role of nitric oxide synthesis in Cd(2+)-induced toxicity in human cells.

Mass spectrometric determination of early and advanced glycation in biology.

PubMed

Rabbani, Naila; Ashour, Amal; Thornalley, Paul J

2016-08-01

Protein glycation in biological systems occurs predominantly on lysine, arginine and N-terminal residues of proteins. Major quantitative glycation adducts are found at mean extents of modification of 1-5 mol percent of proteins. These are glucose-derived fructosamine on lysine and N-terminal residues of proteins, methylglyoxal-derived hydroimidazolone on arginine residues and N(ε)-carboxymethyl-lysine residues mainly formed by the oxidative degradation of fructosamine. Total glycation adducts of different types are quantified by stable isotopic dilution analysis liquid chromatography-tandem mass spectrometry (LC-MS/MS) in multiple reaction monitoring mode. Metabolism of glycated proteins is followed by LC-MS/MS of glycation free adducts as minor components of the amino acid metabolome. Glycated proteins and sites of modification within them - amino acid residues modified by the glycating agent moiety - are identified and quantified by label-free and stable isotope labelling with amino acids in cell culture (SILAC) high resolution mass spectrometry. Sites of glycation by glucose and methylglyoxal in selected proteins are listed. Key issues in applying proteomics techniques to analysis of glycated proteins are: (i) avoiding compromise of analysis by formation, loss and relocation of glycation adducts in pre-analytic processing; (ii) specificity of immunoaffinity enrichment procedures, (iii) maximizing protein sequence coverage in mass spectrometric analysis for detection of glycation sites, and (iv) development of bioinformatics tools for prediction of protein glycation sites. Protein glycation studies have important applications in biology, ageing and translational medicine - particularly on studies of obesity, diabetes, cardiovascular disease, renal failure, neurological disorders and cancer. Mass spectrometric analysis of glycated proteins has yet to find widespread use clinically. Future use in health screening, disease diagnosis and therapeutic monitoring, and drug and functional food development is expected. A protocol for high resolution mass spectrometry proteomics of glycated proteins is given.

Experimental design and data-analysis in label-free quantitative LC/MS proteomics: A tutorial with MSqRob.

PubMed

Goeminne, Ludger J E; Gevaert, Kris; Clement, Lieven

2018-01-16

Label-free shotgun proteomics is routinely used to assess proteomes. However, extracting relevant information from the massive amounts of generated data remains difficult. This tutorial provides a strong foundation on analysis of quantitative proteomics data. We provide key statistical concepts that help researchers to design proteomics experiments and we showcase how to analyze quantitative proteomics data using our recent free and open-source R package MSqRob, which was developed to implement the peptide-level robust ridge regression method for relative protein quantification described by Goeminne et al. MSqRob can handle virtually any experimental proteomics design and outputs proteins ordered by statistical significance. Moreover, its graphical user interface and interactive diagnostic plots provide easy inspection and also detection of anomalies in the data and flaws in the data analysis, allowing deeper assessment of the validity of results and a critical review of the experimental design. Our tutorial discusses interactive preprocessing, data analysis and visualization of label-free MS-based quantitative proteomics experiments with simple and more complex designs. We provide well-documented scripts to run analyses in bash mode on GitHub, enabling the integration of MSqRob in automated pipelines on cluster environments (https://github.com/statOmics/MSqRob). The concepts outlined in this tutorial aid in designing better experiments and analyzing the resulting data more appropriately. The two case studies using the MSqRob graphical user interface will contribute to a wider adaptation of advanced peptide-based models, resulting in higher quality data analysis workflows and more reproducible results in the proteomics community. We also provide well-documented scripts for experienced users that aim at automating MSqRob on cluster environments. Copyright © 2017 Elsevier B.V. All rights reserved.

A quantitative strategy to detect changes in accessibility of protein regions to chemical modification on heterodimerization

PubMed Central

Dreger, Mathias; Leung, Bo Wah; Brownlee, George G; Deng, Tao

2009-01-01

We describe a method for studying quantitative changes in accessibility of surface lysine residues of the PB1 subunit of the influenza RNA polymerase as a result of association with the PA subunit to form a PB1-PA heterodimer. Our method combines two established methods: (i) the chemical modification of surface lysine residues of native proteins by N-hydroxysuccinimidobiotin (NHS-biotin) and (ii) the stable isotope labeling of amino acids in cell culture (SILAC) followed by tryptic digestion and mass spectrometry. By linking the chemical modification with the SILAC methodology for the first time, we obtain quantitative data on chemical modification allowing subtle changes in accessibility to be described. Five regions in the PB1 monomer showed altered reactivity to NHS-biotin when compared with the [PB1-PA] heterodimer. Mutational analysis of residues in two such regions—at K265 and K481 of PB1, which were about three- and twofold, respectively, less accessible to biotinylation in the PB1-PA heterodimer compared with the PB1 monomer, demonstrated that both K265 and K481 were crucial for polymerase function. This novel assay of quantitative profiling of biotinylation patterns (Q-POP assay) highlights likely conformational changes at important functional sites, as observed here for PB1, and may provide information on protein–protein interaction interfaces. The Q-POP assay should be a generally applicable approach and may detect novel functional sites suitable for targeting by drugs. PMID:19517532

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.

Comparative Proteomic Study of Fatty Acid-treated Myoblasts Reveals Role of Cox-2 in Palmitate-induced Insulin Resistance

PubMed Central

Chen, Xiulan; Xu, Shimeng; Wei, Shasha; Deng, Yaqin; Li, Yiran; Yang, Fuquan; Liu, Pingsheng

2016-01-01

Accumulated studies demonstrate that saturated fatty acids (FAs) such as palmitic acid (PA) inhibit insulin signaling in skeletal muscle cells and monounsaturated fatty acids such as oleic acid (OA) reverse the effect of PA on insulin signaling. The detailed molecular mechanism of these opposite effects remains elusive. Here we provide a comparative proteomic study of skeletal myoblast cell line C2C12 that were untreated or treated with PA, and PA plus OA. A total of 3437 proteins were quantified using SILAC in this study and 29 proteins fall into the pattern that OA reverses PA effect. Expression of some these proteins were verified using qRT-PCR and Western blot. The most significant change was cyclooxygenase-2 (Cox-2). In addition to whole cell comparative proteomic study, we also compared lipid droplet (LD)-associated proteins and identified that Cox-2 was one of three major altered proteins under the FA treatment. This finding was then confirmed using immunofluorescence. Finally, Cox-2 selective inhibitor, celecoxib protected cells from PA-reduced insulin signaling Akt phosphorylation. Together, these results not only provide a dataset of protein expression change in FA treatment but also suggest that Cox-2 and lipid droplets (LDs) are potential players in PA- and OA-mediated cellular processes. PMID:26899878

Isobaric Tags for Relative and Absolute Quantification (iTRAQ)-Based Untargeted Quantitative Proteomic Approach To Identify Change of the Plasma Proteins by Salbutamol Abuse in Beef Cattle.

PubMed

Zhang, Kai; Tang, Chaohua; Liang, Xiaowei; Zhao, Qingyu; Zhang, Junmin

2018-01-10

Salbutamol, a selective β 2 -agonist, endangers the safety of animal products as a result of illegal use in food animals. In this study, an iTRAQ-based untargeted quantitative proteomic approach was applied to screen potential protein biomarkers in plasma of cattle before and after treatment with salbutamol for 21 days. A total of 62 plasma proteins were significantly affected by salbutamol treatment, which can be used as potential biomarkers to screen for the illegal use of salbutamol in beef cattle. Enzyme-linked immunosorbent assay measurements of five selected proteins demonstrated the reliability of iTRAQ-based proteomics in screening of candidate biomarkers among the plasma proteins. The plasma samples collected before and after salbutamol treatment were well-separated by principal component analysis (PCA) using the differentially expressed proteins. These results suggested that an iTRAQ-based untargeted quantitative proteomic strategy combined with PCA pattern recognition methods can discriminate differences in plasma protein profiles collected before and after salbutamol treatment.

QPROT: Statistical method for testing differential expression using protein-level intensity data in label-free quantitative proteomics.

PubMed

Choi, Hyungwon; Kim, Sinae; Fermin, Damian; Tsou, Chih-Chiang; Nesvizhskii, Alexey I

2015-11-03

We introduce QPROT, a statistical framework and computational tool for differential protein expression analysis using protein intensity data. QPROT is an extension of the QSPEC suite, originally developed for spectral count data, adapted for the analysis using continuously measured protein-level intensity data. QPROT offers a new intensity normalization procedure and model-based differential expression analysis, both of which account for missing data. Determination of differential expression of each protein is based on the standardized Z-statistic based on the posterior distribution of the log fold change parameter, guided by the false discovery rate estimated by a well-known Empirical Bayes method. We evaluated the classification performance of QPROT using the quantification calibration data from the clinical proteomic technology assessment for cancer (CPTAC) study and a recently published Escherichia coli benchmark dataset, with evaluation of FDR accuracy in the latter. QPROT is a statistical framework with computational software tool for comparative quantitative proteomics analysis. It features various extensions of QSPEC method originally built for spectral count data analysis, including probabilistic treatment of missing values in protein intensity data. With the increasing popularity of label-free quantitative proteomics data, the proposed method and accompanying software suite will be immediately useful for many proteomics laboratories. This article is part of a Special Issue entitled: Computational Proteomics. Copyright © 2015 Elsevier B.V. All rights reserved.

Recent advances on multidimensional liquid chromatography-mass spectrometry for proteomics: from qualitative to quantitative analysis--a review.

PubMed

Wu, Qi; Yuan, Huiming; Zhang, Lihua; Zhang, Yukui

2012-06-20

With the acceleration of proteome research, increasing attention has been paid to multidimensional liquid chromatography-mass spectrometry (MDLC-MS) due to its high peak capacity and separation efficiency. Recently, many efforts have been put to improve MDLC-based strategies including "top-down" and "bottom-up" to enable highly sensitive qualitative and quantitative analysis of proteins, as well as accelerate the whole analytical procedure. Integrated platforms with combination of sample pretreatment, multidimensional separations and identification were also developed to achieve high throughput and sensitive detection of proteomes, facilitating highly accurate and reproducible quantification. This review summarized the recent advances of such techniques and their applications in qualitative and quantitative analysis of proteomes. Copyright © 2012 Elsevier B.V. All rights reserved.

Standardization approaches in absolute quantitative proteomics with mass spectrometry.

PubMed

Calderón-Celis, Francisco; Encinar, Jorge Ruiz; Sanz-Medel, Alfredo

2017-07-31

Mass spectrometry-based approaches have enabled important breakthroughs in quantitative proteomics in the last decades. This development is reflected in the better quantitative assessment of protein levels as well as to understand post-translational modifications and protein complexes and networks. Nowadays, the focus of quantitative proteomics shifted from the relative determination of proteins (ie, differential expression between two or more cellular states) to absolute quantity determination, required for a more-thorough characterization of biological models and comprehension of the proteome dynamism, as well as for the search and validation of novel protein biomarkers. However, the physico-chemical environment of the analyte species affects strongly the ionization efficiency in most mass spectrometry (MS) types, which thereby require the use of specially designed standardization approaches to provide absolute quantifications. Most common of such approaches nowadays include (i) the use of stable isotope-labeled peptide standards, isotopologues to the target proteotypic peptides expected after tryptic digestion of the target protein; (ii) use of stable isotope-labeled protein standards to compensate for sample preparation, sample loss, and proteolysis steps; (iii) isobaric reagents, which after fragmentation in the MS/MS analysis provide a final detectable mass shift, can be used to tag both analyte and standard samples; (iv) label-free approaches in which the absolute quantitative data are not obtained through the use of any kind of labeling, but from computational normalization of the raw data and adequate standards; (v) elemental mass spectrometry-based workflows able to provide directly absolute quantification of peptides/proteins that contain an ICP-detectable element. A critical insight from the Analytical Chemistry perspective of the different standardization approaches and their combinations used so far for absolute quantitative MS-based (molecular and elemental) proteomics is provided in this review. © 2017 Wiley Periodicals, Inc.

Identification of core components and transient interactors of the peroxisomal importomer by dual-track stable isotope labeling with amino acids in cell culture analysis.

PubMed

Oeljeklaus, Silke; Reinartz, Benedikt S; Wolf, Janina; Wiese, Sebastian; Tonillo, Jason; Podwojski, Katharina; Kuhlmann, Katja; Stephan, Christian; Meyer, Helmut E; Schliebs, Wolfgang; Brocard, Cécile; Erdmann, Ralf; Warscheid, Bettina

2012-04-06

The importomer complex plays an essential role in the biogenesis of peroxisomes by mediating the translocation of matrix proteins across the organellar membrane. A central part of this highly dynamic import machinery is the docking complex consisting of Pex14p, Pex13p, and Pex17p that is linked to the RING finger complex (Pex2p, Pex10p, Pex12p) via Pex8p. To gain detailed knowledge on the molecular players governing peroxisomal matrix protein import and, thus, the integrity and functionality of peroxisomes, we aimed at a most comprehensive investigation of stable and transient interaction partners of Pex14p, the central component of the importomer. To this end, we performed a thorough quantitative proteomics study based on epitope tagging of Pex14p combined with dual-track stable isotope labeling with amino acids in cell culture-mass spectrometry (SILAC-MS) analysis of affinity-purified Pex14p complexes and statistics. The results led to the establishment of the so far most extensive Pex14p interactome, comprising 9 core and further 12 transient components. We confirmed virtually all known Pex14p interaction partners including the core constituents of the importomer as well as Pex5p, Pex11p, Pex15p, and Dyn2p. More importantly, we identified new transient interaction partners (Pex25p, Hrr25p, Esl2p, prohibitin) that provide a valuable resource for future investigations on the functionality, dynamics, and regulation of the peroxisomal importomer.

Experimental Null Method to Guide the Development of Technical Procedures and to Control False-Positive Discovery in Quantitative Proteomics.

PubMed

Shen, Xiaomeng; Hu, Qiang; Li, Jun; Wang, Jianmin; Qu, Jun

2015-10-02

Comprehensive and accurate evaluation of data quality and false-positive biomarker discovery is critical to direct the method development/optimization for quantitative proteomics, which nonetheless remains challenging largely due to the high complexity and unique features of proteomic data. Here we describe an experimental null (EN) method to address this need. Because the method experimentally measures the null distribution (either technical or biological replicates) using the same proteomic samples, the same procedures and the same batch as the case-vs-contol experiment, it correctly reflects the collective effects of technical variability (e.g., variation/bias in sample preparation, LC-MS analysis, and data processing) and project-specific features (e.g., characteristics of the proteome and biological variation) on the performances of quantitative analysis. To show a proof of concept, we employed the EN method to assess the quantitative accuracy and precision and the ability to quantify subtle ratio changes between groups using different experimental and data-processing approaches and in various cellular and tissue proteomes. It was found that choices of quantitative features, sample size, experimental design, data-processing strategies, and quality of chromatographic separation can profoundly affect quantitative precision and accuracy of label-free quantification. The EN method was also demonstrated as a practical tool to determine the optimal experimental parameters and rational ratio cutoff for reliable protein quantification in specific proteomic experiments, for example, to identify the necessary number of technical/biological replicates per group that affords sufficient power for discovery. Furthermore, we assessed the ability of EN method to estimate levels of false-positives in the discovery of altered proteins, using two concocted sample sets mimicking proteomic profiling using technical and biological replicates, respectively, where the true-positives/negatives are known and span a wide concentration range. It was observed that the EN method correctly reflects the null distribution in a proteomic system and accurately measures false altered proteins discovery rate (FADR). In summary, the EN method provides a straightforward, practical, and accurate alternative to statistics-based approaches for the development and evaluation of proteomic experiments and can be universally adapted to various types of quantitative techniques.

Mechanisms of Human Adenovirus Inactivation by Sunlight and UVC Light as Examined by Quantitative PCR and Quantitative Proteomics

PubMed Central

Bosshard, Franziska; Armand, Florence; Hamelin, Romain

2013-01-01

Human adenoviruses (HAdV) are important pathogens in both industrialized and developing nations. HAdV has been shown to be relatively resistant to monochromatic UVC light. Polychromatic UVC light, in contrast, is a more effective means of disinfection, presumably due to the involvement of viral proteins in the inactivation mechanism. Solar disinfection of HAdV, finally, is only poorly understood. In this paper, the kinetics and mechanism of HAdV inactivation by UVC light and direct and indirect solar disinfection are elucidated. PCR and mass spectrometry were employed to quantify the extent of genome and protein degradation and to localize the affected regions in the HAdV proteins. For this purpose, we used for the first time an approach involving stable isotope labeling by amino acids in cell culture (SILAC) of a human virus. Inactivation by UVC light and the full sunlight spectrum were found to efficiently inactivate HAdV, whereas UVA-visible light only caused inactivation in the presence of external sensitizers (indirect solar disinfection). Genome damage was significant for UVC but was less important for solar disinfection. In contrast, indirect solar disinfection exhibited extensive protein degradation. In particular, the fiber protein and the amino acids responsible for host binding within the fiber protein were shown to degrade. In addition, the central domain of the penton protein was damaged, which may inhibit interactions with the fiber protein and lead to a disruption of the initial stages of infection. Damage to the hexon protein, however, appeared to affect only regions not directly involved in the infectious cycle. PMID:23241978

A statistical framework for protein quantitation in bottom-up MS-based proteomics

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

Karpievitch, Yuliya; Stanley, Jeffrey R.; Taverner, Thomas

2009-08-15

ABSTRACT Motivation: Quantitative mass spectrometry-based proteomics requires protein-level estimates and confidence measures. Challenges include the presence of low-quality or incorrectly identified peptides and widespread, informative, missing data. Furthermore, models are required for rolling peptide-level information up to the protein level. Results: We present a statistical model for protein abundance in terms of peptide peak intensities, applicable to both label-based and label-free quantitation experiments. The model allows for both random and censoring missingness mechanisms and provides naturally for protein-level estimates and confidence measures. The model is also used to derive automated filtering and imputation routines. Three LC-MS datasets are used tomore » illustrate the methods. Availability: The software has been made available in the open-source proteomics platform DAnTE (Polpitiya et al. (2008)) (http://omics.pnl.gov/software/). Contact: adabney@stat.tamu.edu« less

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

A Statistical Framework for Protein Quantitation in Bottom-Up MS-Based Proteomics

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

Karpievitch, Yuliya; Stanley, Jeffrey R.; Taverner, Thomas

2009-08-15

Motivation: Quantitative mass spectrometry-based proteomics requires protein-level estimates and associated confidence measures. Challenges include the presence of low quality or incorrectly identified peptides and informative missingness. Furthermore, models are required for rolling peptide-level information up to the protein level. Results: We present a statistical model that carefully accounts for informative missingness in peak intensities and allows unbiased, model-based, protein-level estimation and inference. The model is applicable to both label-based and label-free quantitation experiments. We also provide automated, model-based, algorithms for filtering of proteins and peptides as well as imputation of missing values. Two LC/MS datasets are used to illustrate themore » methods. In simulation studies, our methods are shown to achieve substantially more discoveries than standard alternatives. Availability: The software has been made available in the opensource proteomics platform DAnTE (http://omics.pnl.gov/software/). Contact: adabney@stat.tamu.edu Supplementary information: Supplementary data are available at Bioinformatics online.« less

Will Quantitative Proteomics Redefine Some of the Key Concepts in Skeletal Muscle Physiology?

PubMed

Gizak, Agnieszka; Rakus, Dariusz

2016-01-11

Molecular and cellular biology methodology is traditionally based on the reasoning called "the mechanistic explanation". In practice, this means identifying and selecting correlations between biological processes which result from our manipulation of a biological system. In theory, a successful application of this approach requires precise knowledge about all parameters of a studied system. However, in practice, due to the systems' complexity, this requirement is rarely, if ever, accomplished. Typically, it is limited to a quantitative or semi-quantitative measurements of selected parameters (e.g., concentrations of some metabolites), and a qualitative or semi-quantitative description of expression/post-translational modifications changes within selected proteins. A quantitative proteomics approach gives a possibility of quantitative characterization of the entire proteome of a biological system, in the context of the titer of proteins as well as their post-translational modifications. This enables not only more accurate testing of novel hypotheses but also provides tools that can be used to verify some of the most fundamental dogmas of modern biology. In this short review, we discuss some of the consequences of using quantitative proteomics to verify several key concepts in skeletal muscle physiology.

pyOpenMS: a Python-based interface to the OpenMS mass-spectrometry algorithm library.

PubMed

Röst, Hannes L; Schmitt, Uwe; Aebersold, Ruedi; Malmström, Lars

2014-01-01

pyOpenMS is an open-source, Python-based interface to the C++ OpenMS library, providing facile access to a feature-rich, open-source algorithm library for MS-based proteomics analysis. It contains Python bindings that allow raw access to the data structures and algorithms implemented in OpenMS, specifically those for file access (mzXML, mzML, TraML, mzIdentML among others), basic signal processing (smoothing, filtering, de-isotoping, and peak-picking) and complex data analysis (including label-free, SILAC, iTRAQ, and SWATH analysis tools). pyOpenMS thus allows fast prototyping and efficient workflow development in a fully interactive manner (using the interactive Python interpreter) and is also ideally suited for researchers not proficient in C++. In addition, our code to wrap a complex C++ library is completely open-source, allowing other projects to create similar bindings with ease. The pyOpenMS framework is freely available at https://pypi.python.org/pypi/pyopenms while the autowrap tool to create Cython code automatically is available at https://pypi.python.org/pypi/autowrap (both released under the 3-clause BSD licence). © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Guidelines for reporting quantitative mass spectrometry based experiments in proteomics.

PubMed

Martínez-Bartolomé, Salvador; Deutsch, Eric W; Binz, Pierre-Alain; Jones, Andrew R; Eisenacher, Martin; Mayer, Gerhard; Campos, Alex; Canals, Francesc; Bech-Serra, Joan-Josep; Carrascal, Montserrat; Gay, Marina; Paradela, Alberto; Navajas, Rosana; Marcilla, Miguel; Hernáez, María Luisa; Gutiérrez-Blázquez, María Dolores; Velarde, Luis Felipe Clemente; Aloria, Kerman; Beaskoetxea, Jabier; Medina-Aunon, J Alberto; Albar, Juan P

2013-12-16

Mass spectrometry is already a well-established protein identification tool and recent methodological and technological developments have also made possible the extraction of quantitative data of protein abundance in large-scale studies. Several strategies for absolute and relative quantitative proteomics and the statistical assessment of quantifications are possible, each having specific measurements and therefore, different data analysis workflows. The guidelines for Mass Spectrometry Quantification allow the description of a wide range of quantitative approaches, including labeled and label-free techniques and also targeted approaches such as Selected Reaction Monitoring (SRM). The HUPO Proteomics Standards Initiative (HUPO-PSI) has invested considerable efforts to improve the standardization of proteomics data handling, representation and sharing through the development of data standards, reporting guidelines, controlled vocabularies and tooling. In this manuscript, we describe a key output from the HUPO-PSI-namely the MIAPE Quant guidelines, which have developed in parallel with the corresponding data exchange format mzQuantML [1]. The MIAPE Quant guidelines describe the HUPO-PSI proposal concerning the minimum information to be reported when a quantitative data set, derived from mass spectrometry (MS), is submitted to a database or as supplementary information to a journal. The guidelines have been developed with input from a broad spectrum of stakeholders in the proteomics field to represent a true consensus view of the most important data types and metadata, required for a quantitative experiment to be analyzed critically or a data analysis pipeline to be reproduced. It is anticipated that they will influence or be directly adopted as part of journal guidelines for publication and by public proteomics databases and thus may have an impact on proteomics laboratories across the world. This article is part of a Special Issue entitled: Standardization and Quality Control. Copyright © 2013 Elsevier B.V. All rights reserved.

Stable isotope dimethyl labelling for quantitative proteomics and beyond

PubMed Central

Hsu, Jue-Liang; Chen, Shu-Hui

2016-01-01

Stable-isotope reductive dimethylation, a cost-effective, simple, robust, reliable and easy-to- multiplex labelling method, is widely applied to quantitative proteomics using liquid chromatography-mass spectrometry. This review focuses on biological applications of stable-isotope dimethyl labelling for a large-scale comparative analysis of protein expression and post-translational modifications based on its unique properties of the labelling chemistry. Some other applications of the labelling method for sample preparation and mass spectrometry-based protein identification and characterization are also summarized. This article is part of the themed issue ‘Quantitative mass spectrometry’. PMID:27644970

Data from quantitative label free proteomics analysis of rat spleen.

PubMed

Dudekula, Khadar; Le Bihan, Thierry

2016-09-01

The dataset presented in this work has been obtained using a label-free quantitative proteomic analysis of rat spleen. A robust method for extraction of proteins from rat spleen tissue and LC-MS-MS analysis was developed using a urea and SDS-based buffer. Different fractionation methods were compared. A total of 3484 different proteins were identified from the pool of all experiments run in this study (a total of 2460 proteins with at least two peptides). A total of 1822 proteins were identified from nine non-fractionated pulse gels, 2288 proteins and 2864 proteins were identified by SDS-PAGE fractionation into three and five fractions respectively. The proteomics data are deposited in ProteomeXchange Consortium via PRIDE PXD003520, Progenesis and Maxquant output are presented in the supported information. The generated list of proteins under different regimes of fractionation allow assessing the nature of the identified proteins; variability in the quantitative analysis associated with the different sampling strategy and allow defining a proper number of replicates for future quantitative analysis.

Phosphoproteome and transcriptome analyses of ErbB ligand-stimulated MCF-7 cells.

PubMed

Nagashima, Takeshi; Oyama, Masaaki; Kozuka-Hata, Hiroko; Yumoto, Noriko; Sakaki, Yoshiyuki; Hatakeyama, Mariko

2008-01-01

Cellular signal transduction pathways and gene expression are tightly regulated to accommodate changes in response to physiological environments. In the current study, molecules were identified that are activated as a result of intracellular signaling and immediately expressed as mRNA in MCF-7 breast cancer cells shortly after stimulation of ErbB receptor ligands, epidermal growth factor (EGF) or heregulin (HRG). For the identification of tyrosine-phosphorylated proteins and expressed genes, a SILAC (stable isotopic labeling using amino acids in cell culture) method and Affymetrix gene expression array system, respectively, were used. Unexpectedly, the overlapping of genes appeared in two experimental datasets was very low for HRG (43 hits in the proteome data, 1,655 in the transcriptome data, and 5 hits common to both datasets), while no overlapping gene was detected for EGF (15 hits in the proteome data, 211 hits in the transcriptome data, and no hits common to both datasets). The HRG overlapping genes included ERBB2, NEDD9, MAPK3, JUP and EPHA2. Biological pathway analysis indicated that HRG-stimulated molecular activation is significantly related to cancer pathways including bladder cancer, chronic myeloid leukemia and pancreatic cancer (p < 0.05). The proteome datasets of EGF and HRG contain molecules that are related to Axon guidance, ErbB signaling and VEGF signaling at a high rate.

Dynamics of zebrafish fin regeneration using a pulsed SILAC approach.

PubMed

Nolte, Hendrik; Hölper, Soraya; Housley, Michael P; Islam, Shariful; Piller, Tanja; Konzer, Anne; Stainier, Didier Y R; Braun, Thomas; Krüger, Marcus

2015-02-01

The zebrafish owns remarkable regenerative capacities allowing regeneration of several tissues, including the heart, liver, and brain. To identify protein dynamics during fin regeneration we used a pulsed SILAC approach that enabled us to detect the incorporation of (13) C6 -lysine (Lys6) into newly synthesized proteins. Samples were taken at four different time points from noninjured and regrowing fins and incorporation rates were monitored using a combination of single-shot 4-h gradients and high-resolution tandem MS. We identified more than 5000 labeled proteins during the first 3 weeks of fin regeneration and were able to monitor proteins that are responsible for initializing and restoring the shape of these appendages. The comparison of Lys6 incorporation rates between noninjured and regrowing fins enabled us to identify proteins that are directly involved in regeneration. For example, we observed increased incorporation rates of two actinodin family members at the actinotrichia, which is a hairlike fiber structure at the tip of regrowing fins. Moreover, we used quantitative real-time RNA measurements of several candidate genes, including osteoglycin, si:ch211-288h17.3, and prostaglandin reductase 1 to correlate the mRNA expression to Lys6 incorporation data. This novel pulsed SILAC methodology in fish can be used as a versatile tool to monitor newly synthesized proteins and will help to characterize protein dynamics during regenerative processes in zebrafish beyond fin regeneration. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mass spectrometry-based proteomics for translational research: a technical overview.

PubMed

Paulo, Joao A; Kadiyala, Vivek; Banks, Peter A; Steen, Hanno; Conwell, Darwin L

2012-03-01

Mass spectrometry-based investigation of clinical samples enables the high-throughput identification of protein biomarkers. We provide an overview of mass spectrometry-based proteomic techniques that are applicable to the investigation of clinical samples. We address sample collection, protein extraction and fractionation, mass spectrometry modalities, and quantitative proteomics. Finally, we examine the limitations and further potential of such technologies. Liquid chromatography fractionation coupled with tandem mass spectrometry is well suited to handle mixtures of hundreds or thousands of proteins. Mass spectrometry-based proteome elucidation can reveal potential biomarkers and aid in the development of hypotheses for downstream investigation of the molecular mechanisms of disease.

Mass Spectrometry-Based Proteomics for Translational Research: A Technical Overview

PubMed Central

Paulo, Joao A.; Kadiyala, Vivek; Banks, Peter A.; Steen, Hanno; Conwell, Darwin L.

2012-01-01

Mass spectrometry-based investigation of clinical samples enables the high-throughput identification of protein biomarkers. We provide an overview of mass spectrometry-based proteomic techniques that are applicable to the investigation of clinical samples. We address sample collection, protein extraction and fractionation, mass spectrometry modalities, and quantitative proteomics. Finally, we examine the limitations and further potential of such technologies. Liquid chromatography fractionation coupled with tandem mass spectrometry is well suited to handle mixtures of hundreds or thousands of proteins. Mass spectrometry-based proteome elucidation can reveal potential biomarkers and aid in the development of hypotheses for downstream investigation of the molecular mechanisms of disease. PMID:22461744

A proteomics performance standard to support measurement quality in proteomics.

PubMed

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

2012-04-01

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

Mass spectrometry–based relative quantification of proteins in precatalytic and catalytically active spliceosomes by metabolic labeling (SILAC), chemical labeling (iTRAQ), and label-free spectral count

PubMed Central

Schmidt, Carla; Grønborg, Mads; Deckert, Jochen; Bessonov, Sergey; Conrad, Thomas; Lührmann, Reinhard; Urlaub, Henning

2014-01-01

The spliceosome undergoes major changes in protein and RNA composition during pre-mRNA splicing. Knowing the proteins—and their respective quantities—at each spliceosomal assembly stage is critical for understanding the molecular mechanisms and regulation of splicing. Here, we applied three independent mass spectrometry (MS)–based approaches for quantification of these proteins: (1) metabolic labeling by SILAC, (2) chemical labeling by iTRAQ, and (3) label-free spectral count for quantification of the protein composition of the human spliceosomal precatalytic B and catalytic C complexes. In total we were able to quantify 157 proteins by at least two of the three approaches. Our quantification shows that only a very small subset of spliceosomal proteins (the U5 and U2 Sm proteins, a subset of U5 snRNP-specific proteins, and the U2 snRNP-specific proteins U2A′ and U2B′′) remains unaltered upon transition from the B to the C complex. The MS-based quantification approaches classify the majority of proteins as dynamically associated specifically with the B or the C complex. In terms of experimental procedure and the methodical aspect of this work, we show that metabolically labeled spliceosomes are functionally active in terms of their assembly and splicing kinetics and can be utilized for quantitative studies. Moreover, we obtain consistent quantification results from all three methods, including the relatively straightforward and inexpensive label-free spectral count technique. PMID:24448447

Functional Module Search in Protein Networks based on Semantic Similarity Improves the Analysis of Proteomics Data*

PubMed Central

Boyanova, Desislava; Nilla, Santosh; Klau, Gunnar W.; Dandekar, Thomas; Müller, Tobias; Dittrich, Marcus

2014-01-01

The continuously evolving field of proteomics produces increasing amounts of data while improving the quality of protein identifications. Albeit quantitative measurements are becoming more popular, many proteomic studies are still based on non-quantitative methods for protein identification. These studies result in potentially large sets of identified proteins, where the biological interpretation of proteins can be challenging. Systems biology develops innovative network-based methods, which allow an integrated analysis of these data. Here we present a novel approach, which combines prior knowledge of protein-protein interactions (PPI) with proteomics data using functional similarity measurements of interacting proteins. This integrated network analysis exactly identifies network modules with a maximal consistent functional similarity reflecting biological processes of the investigated cells. We validated our approach on small (H9N2 virus-infected gastric cells) and large (blood constituents) proteomic data sets. Using this novel algorithm, we identified characteristic functional modules in virus-infected cells, comprising key signaling proteins (e.g. the stress-related kinase RAF1) and demonstrate that this method allows a module-based functional characterization of cell types. Analysis of a large proteome data set of blood constituents resulted in clear separation of blood cells according to their developmental origin. A detailed investigation of the T-cell proteome further illustrates how the algorithm partitions large networks into functional subnetworks each representing specific cellular functions. These results demonstrate that the integrated network approach not only allows a detailed analysis of proteome networks but also yields a functional decomposition of complex proteomic data sets and thereby provides deeper insights into the underlying cellular processes of the investigated system. PMID:24807868

Comparative quantitative proteomics analysis of the ABA response of roots of drought-sensitive and drought-tolerant wheat varieties identifies proteomic signatures of drought adaptability.

PubMed

Alvarez, Sophie; Roy Choudhury, Swarup; Pandey, Sona

2014-03-07

Wheat is one of the most highly cultivated cereals in the world. Like other cultivated crops, wheat production is significantly affected by abiotic stresses such as drought. Multiple wheat varieties suitable for different geographical regions of the world have been developed that are adapted to different environmental conditions; however, the molecular basis of such adaptations remains unknown in most cases. We have compared the quantitative proteomics profile of the roots of two different wheat varieties, Nesser (drought-tolerant) and Opata (drought-sensitive), in the absence and presence of abscisic acid (ABA, as a proxy for drought). A labeling LC-based quantitative proteomics approach using iTRAQ was applied to elucidate the changes in protein abundance levels. Quantitative differences in protein levels were analyzed for the evaluation of inherent differences between the two varieties as well as the overall and variety-specific effect of ABA on the root proteome. This study reveals the most elaborate ABA-responsive root proteome identified to date in wheat. A large number of proteins exhibited inherently different expression levels between Nesser and Opata. Additionally, significantly higher numbers of proteins were ABA-responsive in Nesser roots compared with Opata roots. Furthermore, several proteins showed variety-specific regulation by ABA, suggesting their role in drought adaptation.

A Comparison of Protein Extraction Methods Suitable for Gel-Based Proteomic Studies of Aphid Proteins

PubMed Central

Cilia, M.; Fish, T.; Yang, X.; Mclaughlin, M.; Thannhauser, T. W.

2009-01-01

Protein extraction methods can vary widely in reproducibility and in representation of the total proteome, yet there are limited data comparing protein isolation methods. The methodical comparison of protein isolation methods is the first critical step for proteomic studies. To address this, we compared three methods for isolation, purification, and solubilization of insect proteins. The aphid Schizaphis graminum, an agricultural pest, was the source of insect tissue. Proteins were extracted using TCA in acetone (TCA-acetone), phenol, or multi-detergents in a chaotrope solution. Extracted proteins were solubilized in a multiple chaotrope solution and examined using 1-D and 2-D electrophoresis and compared directly using 2-D Difference Gel Electrophoresis (2-D DIGE). Mass spectrometry was used to identify proteins from each extraction type. We were unable to ascribe the differences in the proteins extracted to particular physical characteristics, cell location, or biological function. The TCA-acetone extraction yielded the greatest amount of protein from aphid tissues. Each extraction method isolated a unique subset of the aphid proteome. The TCA-acetone method was explored further for its quantitative reliability using 2-D DIGE. Principal component analysis showed that little of the variation in the data was a result of technical issues, thus demonstrating that the TCA-acetone extraction is a reliable method for preparing aphid proteins for a quantitative proteomics experiment. These data suggest that although the TCA-acetone method is a suitable method for quantitative aphid proteomics, a combination of extraction approaches is recommended for increasing proteome coverage when using gel-based separation techniques. PMID:19721822

Large-Scale and Deep Quantitative Proteome Profiling Using Isobaric Labeling Coupled with Two-Dimensional LC-MS/MS

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

Gritsenko, Marina A.; Xu, Zhe; Liu, Tao

Comprehensive, quantitative information on abundances of proteins and their post-translational modifications (PTMs) can potentially provide novel biological insights into diseases pathogenesis and therapeutic intervention. Herein, we introduce a quantitative strategy utilizing isobaric stable isotope-labelling techniques combined with two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS) for large-scale, deep quantitative proteome profiling of biological samples or clinical specimens such as tumor tissues. The workflow includes isobaric labeling of tryptic peptides for multiplexed and accurate quantitative analysis, basic reversed-phase LC fractionation and concatenation for reduced sample complexity, and nano-LC coupled to high resolution and high mass accuracy MS analysis for high confidence identification andmore » quantification of proteins. This proteomic analysis strategy has been successfully applied for in-depth quantitative proteomic analysis of tumor samples, and can also be used for integrated proteome and PTM characterization, as well as comprehensive quantitative proteomic analysis across samples from large clinical cohorts.« less

Large-Scale and Deep Quantitative Proteome Profiling Using Isobaric Labeling Coupled with Two-Dimensional LC-MS/MS.

PubMed

Gritsenko, Marina A; Xu, Zhe; Liu, Tao; Smith, Richard D

2016-01-01

Comprehensive, quantitative information on abundances of proteins and their posttranslational modifications (PTMs) can potentially provide novel biological insights into diseases pathogenesis and therapeutic intervention. Herein, we introduce a quantitative strategy utilizing isobaric stable isotope-labeling techniques combined with two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS) for large-scale, deep quantitative proteome profiling of biological samples or clinical specimens such as tumor tissues. The workflow includes isobaric labeling of tryptic peptides for multiplexed and accurate quantitative analysis, basic reversed-phase LC fractionation and concatenation for reduced sample complexity, and nano-LC coupled to high resolution and high mass accuracy MS analysis for high confidence identification and quantification of proteins. This proteomic analysis strategy has been successfully applied for in-depth quantitative proteomic analysis of tumor samples and can also be used for integrated proteome and PTM characterization, as well as comprehensive quantitative proteomic analysis across samples from large clinical cohorts.

Quantitative proteomic characterization of the lung extracellular matrix in chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis.

PubMed

Åhrman, Emma; Hallgren, Oskar; Malmström, Lars; Hedström, Ulf; Malmström, Anders; Bjermer, Leif; Zhou, Xiao-Hong; Westergren-Thorsson, Gunilla; Malmström, Johan

2018-03-01

Remodeling of the extracellular matrix (ECM) is a common feature in lung diseases such as chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF). Here, we applied a sequential tissue extraction strategy to describe disease-specific remodeling of human lung tissue in disease, using end-stages of COPD and IPF. Our strategy was based on quantitative comparison of the disease proteomes, with specific focus on the matrisome, using data-independent acquisition and targeted data analysis (SWATH-MS). Our work provides an in-depth proteomic characterization of human lung tissue during impaired tissue remodeling. In addition, we show important quantitative and qualitative effects of the solubility of matrisome proteins. COPD was characterized by a disease-specific increase in ECM regulators, metalloproteinase inhibitor 3 (TIMP3) and matrix metalloproteinase 28 (MMP-28), whereas for IPF, impairment in cell adhesion proteins, such as collagen VI and laminins, was most prominent. For both diseases, we identified increased levels of proteins involved in the regulation of endopeptidase activity, with several proteins belonging to the serpin family. The established human lung quantitative proteome inventory and the construction of a tissue-specific protein assay library provides a resource for future quantitative proteomic analyses of human lung tissues. We present a sequential tissue extraction strategy to determine changes in extractability of matrisome proteins in end-stage COPD and IPF compared to healthy control tissue. Extensive quantitative analysis of the proteome changes of the disease states revealed altered solubility of matrisome proteins involved in ECM regulators and cell-ECM communication. The results highlight disease-specific remodeling mechanisms associated with COPD and IPF. Copyright © 2018 Elsevier B.V. All rights reserved.

Analysis of high accuracy, quantitative proteomics data in the MaxQB database.

PubMed

Schaab, Christoph; Geiger, Tamar; Stoehr, Gabriele; Cox, Juergen; Mann, Matthias

2012-03-01

MS-based proteomics generates rapidly increasing amounts of precise and quantitative information. Analysis of individual proteomic experiments has made great strides, but the crucial ability to compare and store information across different proteome measurements still presents many challenges. For example, it has been difficult to avoid contamination of databases with low quality peptide identifications, to control for the inflation in false positive identifications when combining data sets, and to integrate quantitative data. Although, for example, the contamination with low quality identifications has been addressed by joint analysis of deposited raw data in some public repositories, we reasoned that there should be a role for a database specifically designed for high resolution and quantitative data. Here we describe a novel database termed MaxQB that stores and displays collections of large proteomics projects and allows joint analysis and comparison. We demonstrate the analysis tools of MaxQB using proteome data of 11 different human cell lines and 28 mouse tissues. The database-wide false discovery rate is controlled by adjusting the project specific cutoff scores for the combined data sets. The 11 cell line proteomes together identify proteins expressed from more than half of all human genes. For each protein of interest, expression levels estimated by label-free quantification can be visualized across the cell lines. Similarly, the expression rank order and estimated amount of each protein within each proteome are plotted. We used MaxQB to calculate the signal reproducibility of the detected peptides for the same proteins across different proteomes. Spearman rank correlation between peptide intensity and detection probability of identified proteins was greater than 0.8 for 64% of the proteome, whereas a minority of proteins have negative correlation. This information can be used to pinpoint false protein identifications, independently of peptide database scores. The information contained in MaxQB, including high resolution fragment spectra, is accessible to the community via a user-friendly web interface at http://www.biochem.mpg.de/maxqb.

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

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

Tissue-based quantitative proteome analysis of human hepatocellular carcinoma using tandem mass tags.

PubMed

Megger, Dominik Andre; Rosowski, Kristin; Ahrens, Maike; Bracht, Thilo; Eisenacher, Martin; Schlaak, Jörg F; Weber, Frank; Hoffmann, Andreas-Claudius; Meyer, Helmut E; Baba, Hideo A; Sitek, Barbara

2017-03-01

Human hepatocellular carcinoma (HCC) is a severe malignant disease, and accurate and reliable diagnostic markers are still needed. This study was aimed for the discovery of novel marker candidates by quantitative proteomics. Proteomic differences between HCC and nontumorous liver tissue were studied by mass spectrometry. Among several significantly upregulated proteins, translocator protein 18 (TSPO) and Ras-related protein Rab-1A (RAB1A) were selected for verification by immunohistochemistry in an independent cohort. For RAB1A, a high accuracy for the discrimination of HCC and nontumorous liver tissue was observed. RAB1A was verified to be a potent biomarker candidate for HCC.

A multi-center study benchmarks software tools for label-free proteome quantification

PubMed Central

Gillet, Ludovic C; Bernhardt, Oliver M.; MacLean, Brendan; Röst, Hannes L.; Tate, Stephen A.; Tsou, Chih-Chiang; Reiter, Lukas; Distler, Ute; Rosenberger, George; Perez-Riverol, Yasset; Nesvizhskii, Alexey I.; Aebersold, Ruedi; Tenzer, Stefan

2016-01-01

The consistent and accurate quantification of proteins by mass spectrometry (MS)-based proteomics depends on the performance of instruments, acquisition methods and data analysis software. In collaboration with the software developers, we evaluated OpenSWATH, SWATH2.0, Skyline, Spectronaut and DIA-Umpire, five of the most widely used software methods for processing data from SWATH-MS (sequential window acquisition of all theoretical fragment ion spectra), a method that uses data-independent acquisition (DIA) for label-free protein quantification. We analyzed high-complexity test datasets from hybrid proteome samples of defined quantitative composition acquired on two different MS instruments using different SWATH isolation windows setups. For consistent evaluation we developed LFQbench, an R-package to calculate metrics of precision and accuracy in label-free quantitative MS, and report the identification performance, robustness and specificity of each software tool. Our reference datasets enabled developers to improve their software tools. After optimization, all tools provided highly convergent identification and reliable quantification performance, underscoring their robustness for label-free quantitative proteomics. PMID:27701404

A multicenter study benchmarks software tools for label-free proteome quantification.

PubMed

Navarro, Pedro; Kuharev, Jörg; Gillet, Ludovic C; Bernhardt, Oliver M; MacLean, Brendan; Röst, Hannes L; Tate, Stephen A; Tsou, Chih-Chiang; Reiter, Lukas; Distler, Ute; Rosenberger, George; Perez-Riverol, Yasset; Nesvizhskii, Alexey I; Aebersold, Ruedi; Tenzer, Stefan

2016-11-01

Consistent and accurate quantification of proteins by mass spectrometry (MS)-based proteomics depends on the performance of instruments, acquisition methods and data analysis software. In collaboration with the software developers, we evaluated OpenSWATH, SWATH 2.0, Skyline, Spectronaut and DIA-Umpire, five of the most widely used software methods for processing data from sequential window acquisition of all theoretical fragment-ion spectra (SWATH)-MS, which uses data-independent acquisition (DIA) for label-free protein quantification. We analyzed high-complexity test data sets from hybrid proteome samples of defined quantitative composition acquired on two different MS instruments using different SWATH isolation-window setups. For consistent evaluation, we developed LFQbench, an R package, to calculate metrics of precision and accuracy in label-free quantitative MS and report the identification performance, robustness and specificity of each software tool. Our reference data sets enabled developers to improve their software tools. After optimization, all tools provided highly convergent identification and reliable quantification performance, underscoring their robustness for label-free quantitative proteomics.

Quantitative proteomics in biological research.

PubMed

Wilm, Matthias

2009-10-01

Proteomics has enabled the direct investigation of biological material, at first through the analysis of individual proteins, then of lysates from cell cultures, and finally of extracts from tissues and biopsies from entire organisms. Its latest manifestation - quantitative proteomics - allows deeper insight into biological systems. This article reviews the different methods used to extract quantitative information from mass spectra. It follows the technical developments aimed toward global proteomics, the attempt to characterize every expressed protein in a cell by at least one peptide. When applications of the technology are discussed, the focus is placed on yeast biology. In particular, differential quantitative proteomics, the comparison between an experiment and its control, is very discriminating for proteins involved in the process being studied. When trying to understand biological processes on a molecular level, differential quantitative proteomics tends to give a clearer picture than global transcription analyses. As a result, MS has become an even more indispensable tool for biochemically motivated biological research.

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.

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.

Proteomic analysis of cow, yak, buffalo, goat and camel milk whey proteins: quantitative differential expression patterns.

PubMed

Yang, Yongxin; Bu, Dengpan; Zhao, Xiaowei; Sun, Peng; Wang, Jiaqi; Zhou, Lingyun

2013-04-05

To aid in unraveling diverse genetic and biological unknowns, a proteomic approach was used to analyze the whey proteome in cow, yak, buffalo, goat, and camel milk based on the isobaric tag for relative and absolute quantification (iTRAQ) techniques. This analysis is the first to produce proteomic data for the milk from the above-mentioned animal species: 211 proteins have been identified and 113 proteins have been categorized according to molecular function, cellular components, and biological processes based on gene ontology annotation. The results of principal component analysis showed significant differences in proteomic patterns among goat, camel, cow, buffalo, and yak milk. Furthermore, 177 differentially expressed proteins were submitted to advanced hierarchical clustering. The resulting clustering pattern included three major sample clusters: (1) cow, buffalo, and yak milk; (2) goat, cow, buffalo, and yak milk; and (3) camel milk. Certain proteins were chosen as characterization traits for a given species: whey acidic protein and quinone oxidoreductase for camel milk, biglycan for goat milk, uncharacterized protein (Accession Number: F1MK50 ) for yak milk, clusterin for buffalo milk, and primary amine oxidase for cow milk. These results help reveal the quantitative milk whey proteome pattern for analyzed species. This provides information for evaluating adulteration of specific specie milk and may provide potential directions for application of specific milk protein production based on physiological differences among animal species.

Monitoring Peptidase Activities in Complex Proteomes by MALDI-TOF Mass Spectrometry

PubMed Central

Villanueva, Josep; Nazarian, Arpi; Lawlor, Kevin; Tempst, Paul

2009-01-01

Measuring enzymatic activities in biological fluids is a form of activity-based proteomics and may be utilized as a means of developing disease biomarkers. Activity-based assays allow amplification of output signals, thus potentially visualizing low-abundant enzymes on a virtually transparent whole-proteome background. The protocol presented here describes a semi-quantitative in vitro assay of proteolytic activities in complex proteomes by monitoring breakdown of designer peptide-substrates using robotic extraction and a MALDI-TOF mass spectrometric read-out. Relative quantitation of the peptide metabolites is done by comparison with spiked internal standards, followed by statistical analysis of the resulting mini-peptidome. Partial automation provides reproducibility and throughput essential for comparing large sample sets. The approach may be employed for diagnostic or predictive purposes and enables profiling of 96 samples in 30 hours. It could be tailored to many diagnostic and pharmaco-dynamic purposes, as a read-out of catalytic and metabolic activities in body fluids or tissues. PMID:19617888

The mzTab data exchange format: communicating mass-spectrometry-based proteomics and metabolomics experimental results to a wider audience.

PubMed

Griss, Johannes; Jones, Andrew R; Sachsenberg, Timo; Walzer, Mathias; Gatto, Laurent; Hartler, Jürgen; Thallinger, Gerhard G; Salek, Reza M; Steinbeck, Christoph; Neuhauser, Nadin; Cox, Jürgen; Neumann, Steffen; Fan, Jun; Reisinger, Florian; Xu, Qing-Wei; Del Toro, Noemi; Pérez-Riverol, Yasset; Ghali, Fawaz; Bandeira, Nuno; Xenarios, Ioannis; Kohlbacher, Oliver; Vizcaíno, Juan Antonio; Hermjakob, Henning

2014-10-01

The HUPO Proteomics Standards Initiative has developed several standardized data formats to facilitate data sharing in mass spectrometry (MS)-based proteomics. These allow researchers to report their complete results in a unified way. However, at present, there is no format to describe the final qualitative and quantitative results for proteomics and metabolomics experiments in a simple tabular format. Many downstream analysis use cases are only concerned with the final results of an experiment and require an easily accessible format, compatible with tools such as Microsoft Excel or R. We developed the mzTab file format for MS-based proteomics and metabolomics results to meet this need. mzTab is intended as a lightweight supplement to the existing standard XML-based file formats (mzML, mzIdentML, mzQuantML), providing a comprehensive summary, similar in concept to the supplemental material of a scientific publication. mzTab files can contain protein, peptide, and small molecule identifications together with experimental metadata and basic quantitative information. The format is not intended to store the complete experimental evidence but provides mechanisms to report results at different levels of detail. These range from a simple summary of the final results to a representation of the results including the experimental design. This format is ideally suited to make MS-based proteomics and metabolomics results available to a wider biological community outside the field of MS. Several software tools for proteomics and metabolomics have already adapted the format as an output format. The comprehensive mzTab specification document and extensive additional documentation can be found online. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

The mzTab Data Exchange Format: Communicating Mass-spectrometry-based Proteomics and Metabolomics Experimental Results to a Wider Audience*

PubMed Central

Griss, Johannes; Jones, Andrew R.; Sachsenberg, Timo; Walzer, Mathias; Gatto, Laurent; Hartler, Jürgen; Thallinger, Gerhard G.; Salek, Reza M.; Steinbeck, Christoph; Neuhauser, Nadin; Cox, Jürgen; Neumann, Steffen; Fan, Jun; Reisinger, Florian; Xu, Qing-Wei; del Toro, Noemi; Pérez-Riverol, Yasset; Ghali, Fawaz; Bandeira, Nuno; Xenarios, Ioannis; Kohlbacher, Oliver; Vizcaíno, Juan Antonio; Hermjakob, Henning

2014-01-01

The HUPO Proteomics Standards Initiative has developed several standardized data formats to facilitate data sharing in mass spectrometry (MS)-based proteomics. These allow researchers to report their complete results in a unified way. However, at present, there is no format to describe the final qualitative and quantitative results for proteomics and metabolomics experiments in a simple tabular format. Many downstream analysis use cases are only concerned with the final results of an experiment and require an easily accessible format, compatible with tools such as Microsoft Excel or R. We developed the mzTab file format for MS-based proteomics and metabolomics results to meet this need. mzTab is intended as a lightweight supplement to the existing standard XML-based file formats (mzML, mzIdentML, mzQuantML), providing a comprehensive summary, similar in concept to the supplemental material of a scientific publication. mzTab files can contain protein, peptide, and small molecule identifications together with experimental metadata and basic quantitative information. The format is not intended to store the complete experimental evidence but provides mechanisms to report results at different levels of detail. These range from a simple summary of the final results to a representation of the results including the experimental design. This format is ideally suited to make MS-based proteomics and metabolomics results available to a wider biological community outside the field of MS. Several software tools for proteomics and metabolomics have already adapted the format as an output format. The comprehensive mzTab specification document and extensive additional documentation can be found online. PMID:24980485

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

Liu, Xing; Xu, Yanli; Meng, Qian

Colorectal cancer (CRC) is one of the most common types of malignant tumor worldwide. Currently, although many researchers have been devoting themselves in CRC studies, the process of locating biomarkers for CRC early diagnosis and prognostic is still very slow. Using a centrifugal proteomic reactor-based proteomic analysis of minute amount of colonic biopsies by enteroscopy sampling, 2620 protein groups were quantified between cancer mucosa and adjacent normal colorectal mucosa. Of which, 403 protein groups were differentially expressed with statistic significance between cancer and normal tissues, including 195 up-regulated and 208 down-regulated proteins in cancer tissues. Three proteins (SOD3, PRELP andmore » NGAL) were selected for further Western blot validation. And the resulting Western blot experimental results were consistent with the quantitative proteomic data. SOD3 and PRELP are down-regulated in CRC mucosa comparing to adjacent normal tissue, while NGAL is up-regulated in CRC mucosa. In conclusion, the centrifugal proteomic reactor-based label-free quantitative proteomic approach provides a highly sensitive and powerful tool for analyzing minute protein sample from tiny colorectal biopsies, which may facilitate CRC biomarkers discovery for diagnoses and prognoses. -- Highlights: •Minute amount of colonic biopsies by endoscopy is suitable for proteomic analysis. •Centrifugal proteomic reactor can be used for processing tiny clinic biopsy sample. •SOD3 and PRELP are down-regulated in CRC, while NGAL is up-regulated in CRC.« less

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.

Strigolactone-regulated proteins revealed by iTRAQ-based quantitative proteomics in Arabidopsis.

PubMed

Li, Zhou; Czarnecki, Olaf; Chourey, Karuna; Yang, Jun; Tuskan, Gerald A; Hurst, Gregory B; Pan, Chongle; Chen, Jin-Gui

2014-03-07

Strigolactones (SLs) are a new class of plant hormones. In addition to acting as a key inhibitor of shoot branching, SLs stimulate seed germination of root parasitic plants and promote hyphal branching and root colonization of symbiotic arbuscular mycorrhizal fungi. They also regulate many other aspects of plant growth and development. At the transcription level, SL-regulated genes have been reported. However, nothing is known about the proteome regulated by this new class of plant hormones. A quantitative proteomics approach using an isobaric chemical labeling reagent, iTRAQ, to identify the proteome regulated by SLs in Arabidopsis seedlings is presented. It was found that SLs regulate the expression of about three dozen proteins that have not been previously assigned to SL pathways. These findings provide a new tool to investigate the molecular mechanism of action of SLs.

PIQMIe: a web server for semi-quantitative proteomics data management and analysis

PubMed Central

Kuzniar, Arnold; Kanaar, Roland

2014-01-01

We present the Proteomics Identifications and Quantitations Data Management and Integration Service or PIQMIe that aids in reliable and scalable data management, analysis and visualization of semi-quantitative mass spectrometry based proteomics experiments. PIQMIe readily integrates peptide and (non-redundant) protein identifications and quantitations from multiple experiments with additional biological information on the protein entries, and makes the linked data available in the form of a light-weight relational database, which enables dedicated data analyses (e.g. in R) and user-driven queries. Using the web interface, users are presented with a concise summary of their proteomics experiments in numerical and graphical forms, as well as with a searchable protein grid and interactive visualization tools to aid in the rapid assessment of the experiments and in the identification of proteins of interest. The web server not only provides data access through a web interface but also supports programmatic access through RESTful web service. The web server is available at http://piqmie.semiqprot-emc.cloudlet.sara.nl or http://www.bioinformatics.nl/piqmie. This website is free and open to all users and there is no login requirement. PMID:24861615

PIQMIe: a web server for semi-quantitative proteomics data management and analysis.

PubMed

Kuzniar, Arnold; Kanaar, Roland

2014-07-01

We present the Proteomics Identifications and Quantitations Data Management and Integration Service or PIQMIe that aids in reliable and scalable data management, analysis and visualization of semi-quantitative mass spectrometry based proteomics experiments. PIQMIe readily integrates peptide and (non-redundant) protein identifications and quantitations from multiple experiments with additional biological information on the protein entries, and makes the linked data available in the form of a light-weight relational database, which enables dedicated data analyses (e.g. in R) and user-driven queries. Using the web interface, users are presented with a concise summary of their proteomics experiments in numerical and graphical forms, as well as with a searchable protein grid and interactive visualization tools to aid in the rapid assessment of the experiments and in the identification of proteins of interest. The web server not only provides data access through a web interface but also supports programmatic access through RESTful web service. The web server is available at http://piqmie.semiqprot-emc.cloudlet.sara.nl or http://www.bioinformatics.nl/piqmie. This website is free and open to all users and there is no login requirement. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Science, marketing and wishful thinking in quantitative proteomics.

PubMed

Hackett, Murray

2008-11-01

In a recent editorial (J. Proteome Res. 2007, 6, 1633) and elsewhere questions have been raised regarding the lack of attention paid to good analytical practice with respect to the reporting of quantitative results in proteomics. Using those comments as a starting point, several issues are discussed that relate to the challenges involved in achieving adequate sampling with MS-based methods in order to generate valid data for large-scale studies. The discussion touches on the relationships that connect sampling depth and the power to detect protein abundance change, conflict of interest, and strategies to overcome bureaucratic obstacles that impede the use of peer-to-peer technologies for transfer and storage of large data files generated in such experiments.

A tutorial for software development in quantitative proteomics using PSI standard formats☆

PubMed Central

Gonzalez-Galarza, Faviel F.; Qi, Da; Fan, Jun; Bessant, Conrad; Jones, Andrew R.

2014-01-01

The Human Proteome Organisation — Proteomics Standards Initiative (HUPO-PSI) has been working for ten years on the development of standardised formats that facilitate data sharing and public database deposition. In this article, we review three HUPO-PSI data standards — mzML, mzIdentML and mzQuantML, which can be used to design a complete quantitative analysis pipeline in mass spectrometry (MS)-based proteomics. In this tutorial, we briefly describe the content of each data model, sufficient for bioinformaticians to devise proteomics software. We also provide guidance on the use of recently released application programming interfaces (APIs) developed in Java for each of these standards, which makes it straightforward to read and write files of any size. We have produced a set of example Java classes and a basic graphical user interface to demonstrate how to use the most important parts of the PSI standards, available from http://code.google.com/p/psi-standard-formats-tutorial. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. PMID:23584085

CPTAC Evaluates Long-Term Reproducibility of Quantitative Proteomics Using Breast Cancer Xenografts | Office of Cancer Clinical Proteomics Research

Cancer.gov

Liquid chromatography tandem-mass spectrometry (LC-MS/MS)- based methods such as isobaric tags for relative and absolute quantification (iTRAQ) and tandem mass tags (TMT) have been shown to provide overall better quantification accuracy and reproducibility over other LC-MS/MS techniques. However, large scale projects like the Clinical Proteomic Tumor Analysis Consortium (CPTAC) require comparisons across many genomically characterized clinical specimens in a single study and often exceed the capability of traditional iTRAQ-based quantification.

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.

Deep Phosphoproteomic Measurements Pinpointing Drug Induced Protective Mechanisms in Neuronal Cells

PubMed Central

Yu, Chengli; Gao, Jing; Zhou, Yanting; Chen, Xiangling; Xiao, Ruoxuan; Zheng, Jing; Liu, Yansheng; Zhou, Hu

2016-01-01

Alzheimer's disease (AD) is a progressive and irreversible neurological disorder that impairs the living quality of old population and even life spans. New compounds have shown potential inneuroprotective effects in AD, such as GFKP-19, a 2-pyrrolidone derivative which has been proved to enhance the memory of dysmnesia mouse. The molecular mechanisms remain to be established for these drug candidates. Large-scale phosphoproteomic approach has been evolved rapidly in the last several years, which holds the potential to provide a useful toolkit to understand cellular signaling underlying drug effects. To establish and test such a method, we accurately analyzed the deep quantitative phosphoproteome of the neuro-2a cells treated with and without GFKP-19 using triple SILAC labeling. A total of 14,761 Class I phosphosites were quantified between controls, damaged, and protected conditions using the high resolution mass spectrometry, with a decent inter-mass spectrometer reproducibility for even subtle regulatory events. Our data suggests that GFKP-19 can reverse Aβ25−35 induced phosphorylation change in neuro-2a cells, and might protect the neuron system in two ways: firstly, it may decrease oxidative damage and inflammation induced by NO via down regulating the phosphorylation of nitric oxide synthase NOS1 at S847; Secondly, it may decrease tau protein phosphorylation through down-regulating the phosphorylation level of MAPK14 at T180. All mass spectrometry data are available via ProteomeXchange with identifier PXD005312. PMID:28066266

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

Translational value of liquid chromatography coupled with tandem mass spectrometry-based quantitative proteomics for in vitro-in vivo extrapolation of drug metabolism and transport and considerations in selecting appropriate techniques.

PubMed

Al Feteisi, Hajar; Achour, Brahim; Rostami-Hodjegan, Amin; Barber, Jill

2015-01-01

Drug-metabolizing enzymes and transporters play an important role in drug absorption, distribution, metabolism and excretion and, consequently, they influence drug efficacy and toxicity. Quantification of drug-metabolizing enzymes and transporters in various tissues is therefore essential for comprehensive elucidation of drug absorption, distribution, metabolism and excretion. Recent advances in liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) have improved the quantification of pharmacologically relevant proteins. This report presents an overview of mass spectrometry-based methods currently used for the quantification of drug-metabolizing enzymes and drug transporters, mainly focusing on applications and cost associated with various quantitative strategies based on stable isotope-labeled standards (absolute quantification peptide standards, quantification concatemers, protein standards for absolute quantification) and label-free analysis. In mass spectrometry, there is no simple relationship between signal intensity and analyte concentration. Proteomic strategies are therefore complex and several factors need to be considered when selecting the most appropriate method for an intended application, including the number of proteins and samples. Quantitative strategies require appropriate mass spectrometry platforms, yet choice is often limited by the availability of appropriate instrumentation. Quantitative proteomics research requires specialist practical skills and there is a pressing need to dedicate more effort and investment to training personnel in this area. Large-scale multicenter collaborations are also needed to standardize quantitative strategies in order to improve physiologically based pharmacokinetic models.

Temporal Profiling and Pulsed SILAC Labeling Identify Novel Secreted Proteins During Ex Vivo Osteoblast Differentiation of Human Stromal Stem Cells*

PubMed Central

Kristensen, Lars P.; Chen, Li; Nielsen, Maria Overbeck; Qanie, Diyako W.; Kratchmarova, Irina; Kassem, Moustapha; Andersen, Jens S.

2012-01-01

It is well established that bone forming cells (osteoblasts) secrete proteins with autocrine, paracrine, and endocrine function. However, the identity and functional role for the majority of these secreted and differentially expressed proteins during the osteoblast (OB) differentiation process, is not fully established. To address these questions, we quantified the temporal dynamics of the human stromal (mesenchymal, skeletal) stem cell (hMSC) secretome during ex vivo OB differentiation using stable isotope labeling by amino acids in cell culture (SILAC). In addition, we employed pulsed SILAC labeling to distinguish genuine secreted proteins from intracellular contaminants. We identified 466 potentially secreted proteins that were quantified at 5 time-points during 14-days ex vivo OB differentiation including 41 proteins known to be involved in OB functions. Among these, 315 proteins exhibited more than 2-fold up or down-regulation. The pulsed SILAC method revealed a strong correlation between the fraction of isotope labeling and the subset of proteins known to be secreted and involved in OB differentiation. We verified SILAC data using qRT-PCR analysis of 9 identified potential novel regulators of OB differentiation. Furthermore, we studied the biological effects of one of these proteins, the hormone stanniocalcin 2 (STC2) and demonstrated its autocrine effects in enhancing osteoblastic differentiation of hMSC. In conclusion, combining complete and pulsed SILAC labeling facilitated the identification of novel factors produced by hMSC with potential role in OB differentiation. Our study demonstrates that the secretome of osteoblastic cells is more complex than previously reported and supports the emerging evidence that osteoblastic cells secrete proteins with endocrine functions and regulate cellular processes beyond bone formation. PMID:22801418

Linking the proteins--elucidation of proteome-scale networks using mass spectrometry.

PubMed

Pflieger, Delphine; Gonnet, Florence; de la Fuente van Bentem, Sergio; Hirt, Heribert; de la Fuente, Alberto

2011-01-01

Proteomes are intricate. Typically, thousands of proteins interact through physical association and post-translational modifications (PTMs) to give rise to the emergent functions of cells. Understanding these functions requires one to study proteomes as "systems" rather than collections of individual protein molecules. The abstraction of the interacting proteome to "protein networks" has recently gained much attention, as networks are effective representations, that lose specific molecular details, but provide the ability to see the proteome as a whole. Mostly two aspects of the proteome have been represented by network models: proteome-wide physical protein-protein-binding interactions organized into Protein Interaction Networks (PINs), and proteome-wide PTM relations organized into Protein Signaling Networks (PSNs). Mass spectrometry (MS) techniques have been shown to be essential to reveal both of these aspects on a proteome-wide scale. Techniques such as affinity purification followed by MS have been used to elucidate protein-protein interactions, and MS-based quantitative phosphoproteomics is critical to understand the structure and dynamics of signaling through the proteome. We here review the current state-of-the-art MS-based analytical pipelines for the purpose to characterize proteome-scale networks. Copyright © 2010 Wiley Periodicals, Inc.

Design and analysis issues in quantitative proteomics studies.

PubMed

Karp, Natasha A; Lilley, Kathryn S

2007-09-01

Quantitative proteomics is the comparison of distinct proteomes which enables the identification of protein species which exhibit changes in expression or post-translational state in response to a given stimulus. Many different quantitative techniques are being utilized and generate large datasets. Independent of the technique used, these large datasets need robust data analysis to ensure valid conclusions are drawn from such studies. Approaches to address the problems that arise with large datasets are discussed to give insight into the types of statistical analyses of data appropriate for the various experimental strategies that can be employed by quantitative proteomic studies. This review also highlights the importance of employing a robust experimental design and highlights various issues surrounding the design of experiments. The concepts and examples discussed within will show how robust design and analysis will lead to confident results that will ensure quantitative proteomics delivers.

Isobaric Tags for Relative and Absolute Quantitation-Based Proteomic Analysis of Patent and Constricted Ductus Arteriosus Tissues Confirms the Systemic Regulation of Ductus Arteriosus Closure.

PubMed

Hong, Haifa; Ye, Lincai; Chen, Huiwen; Xia, Yu; Liu, Yue; Liu, Jinfen; Lu, Yanan; Zhang, Haibo

2015-08-01

We aimed to evaluate global changes in protein expression associated with patency by undertaking proteomic analysis of human constricted and patent ductus arteriosus (DA). Ten constricted and 10 patent human DAs were excised from infants with ductal-dependent heart disease during surgery. Using isobaric tags for relative and absolute quantitation-based quantitative proteomics, 132 differentially expressed proteins were identified. Of 132 proteins, voltage-gated sodium channel 1.3 (SCN3A), myosin 1d (Myo1d), Rho GTPase activating protein 26 (ARHGAP26), and retinitis pigmentosa 1 (RP1) were selected for validation by Western blot and quantitative real-time polymerase chain reaction analyses. Significant upregulation of SCN3A, Myo1d, and RP1 messenger RNA, and protein levels was observed in the patent DA group (all P ≤ 0.048). ARHGAP26 messenger RNA and protein levels were decreased in patent DA tissue (both P ≤ 0.018). Immunohistochemistry analysis revealed that Myo1d, ARHGAP26, and RP1 were specifically expressed in the subendothelial region of constricted DAs; however, diffuse expression of these proteins was noted in the patent group. Proteomic analysis revealed global changes in the expression of proteins that regulate oxygen sensing, ion channels, smooth muscle cell migration, nervous system, immune system, and metabolism, suggesting a basis for the systemic regulation of DA patency by diverse signaling pathways, which will be confirmed in further studies.

[Methods of quantitative proteomics].

PubMed

Kopylov, A T; Zgoda, V G

2007-01-01

In modern science proteomic analysis is inseparable from other fields of systemic biology. Possessing huge resources quantitative proteomics operates colossal information on molecular mechanisms of life. Advances in proteomics help researchers to solve complex problems of cell signaling, posttranslational modification, structure and functional homology of proteins, molecular diagnostics etc. More than 40 various methods have been developed in proteomics for quantitative analysis of proteins. Although each method is unique and has certain advantages and disadvantages all these use various isotope labels (tags). In this review we will consider the most popular and effective methods employing both chemical modifications of proteins and also metabolic and enzymatic methods of isotope labeling.

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.

Development of Best practices document for Peptide Standards | Office of Cancer Clinical Proteomics Research

Cancer.gov

The Assay Development Working Group (ADWG) of the CPTAC Program is currently drafting a document to propose best practices for generation, quantification, storage, and handling of peptide standards used for mass spectrometry-based assays, as well as interpretation of quantitative proteomic data based on peptide standards. The ADWG is seeking input from commercial entities that provide peptide standards for mass spectrometry-based assays or that perform amino acid analysis.

Nuclear Cytoplasmic Trafficking of Proteins is a Major Response of Human Fibroblasts to Oxidative Stress

PubMed Central

Baqader, Noor O.; Radulovic, Marko; Crawford, Mark; Stoeber, Kai; Godovac-Zimmermann, Jasminka

2014-01-01

We have used a subcellular spatial razor approach based on LC–MS/MS-based proteomics with SILAC isotope labeling to determine changes in protein abundances in the nuclear and cytoplasmic compartments of human IMR90 fibroblasts subjected to mild oxidative stress. We show that response to mild tert-butyl hydrogen peroxide treatment includes redistribution between the nucleus and cytoplasm of numerous proteins not previously associated with oxidative stress. The 121 proteins with the most significant changes encompass proteins with known functions in a wide variety of subcellular locations and of cellular functional processes (transcription, signal transduction, autophagy, iron metabolism, TCA cycle, ATP synthesis) and are consistent with functional networks that are spatially dispersed across the cell. Both nuclear respiratory factor 2 and the proline regulatory axis appear to contribute to the cellular metabolic response. Proteins involved in iron metabolism or with iron/heme as a cofactor as well as mitochondrial proteins are prominent in the response. Evidence suggesting that nuclear import/export and vesicle-mediated protein transport contribute to the cellular response was obtained. We suggest that measurements of global changes in total cellular protein abundances need to be complemented with measurements of the dynamic subcellular spatial redistribution of proteins to obtain comprehensive pictures of cellular function. PMID:25133973

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.

Benchmarking quantitative label-free LC-MS data processing workflows using a complex spiked proteomic standard dataset.

PubMed

Ramus, Claire; Hovasse, Agnès; Marcellin, Marlène; Hesse, Anne-Marie; Mouton-Barbosa, Emmanuelle; Bouyssié, David; Vaca, Sebastian; Carapito, Christine; Chaoui, Karima; Bruley, Christophe; Garin, Jérôme; Cianférani, Sarah; Ferro, Myriam; Van Dorssaeler, Alain; Burlet-Schiltz, Odile; Schaeffer, Christine; Couté, Yohann; Gonzalez de Peredo, Anne

2016-01-30

Proteomic workflows based on nanoLC-MS/MS data-dependent-acquisition analysis have progressed tremendously in recent years. High-resolution and fast sequencing instruments have enabled the use of label-free quantitative methods, based either on spectral counting or on MS signal analysis, which appear as an attractive way to analyze differential protein expression in complex biological samples. However, the computational processing of the data for label-free quantification still remains a challenge. Here, we used a proteomic standard composed of an equimolar mixture of 48 human proteins (Sigma UPS1) spiked at different concentrations into a background of yeast cell lysate to benchmark several label-free quantitative workflows, involving different software packages developed in recent years. This experimental design allowed to finely assess their performances in terms of sensitivity and false discovery rate, by measuring the number of true and false-positive (respectively UPS1 or yeast background proteins found as differential). The spiked standard dataset has been deposited to the ProteomeXchange repository with the identifier PXD001819 and can be used to benchmark other label-free workflows, adjust software parameter settings, improve algorithms for extraction of the quantitative metrics from raw MS data, or evaluate downstream statistical methods. Bioinformatic pipelines for label-free quantitative analysis must be objectively evaluated in their ability to detect variant proteins with good sensitivity and low false discovery rate in large-scale proteomic studies. This can be done through the use of complex spiked samples, for which the "ground truth" of variant proteins is known, allowing a statistical evaluation of the performances of the data processing workflow. We provide here such a controlled standard dataset and used it to evaluate the performances of several label-free bioinformatics tools (including MaxQuant, Skyline, MFPaQ, IRMa-hEIDI and Scaffold) in different workflows, for detection of variant proteins with different absolute expression levels and fold change values. The dataset presented here can be useful for tuning software tool parameters, and also testing new algorithms for label-free quantitative analysis, or for evaluation of downstream statistical methods. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

CPTAC Accelerates Precision Proteomics Biomedical Research | Office of Cancer Clinical Proteomics Research

Cancer.gov

The accurate quantitation of proteins or peptides using Mass Spectrometry (MS) is gaining prominence in the biomedical research community as an alternative method for analyte measurement. The Clinical Proteomic Tumor Analysis Consortium (CPTAC) investigators have been at the forefront in the promotion of reproducible MS techniques, through the development and application of standardized proteomic methods for protein quantitation on biologically relevant samples.

Transcriptome- Assisted Label-Free Quantitative Proteomics Analysis Reveals Novel Insights into Piper nigrum—Phytophthora capsici Phytopathosystem

PubMed Central

Mahadevan, Chidambareswaren; Krishnan, Anu; Saraswathy, Gayathri G.; Surendran, Arun; Jaleel, Abdul; Sakuntala, Manjula

2016-01-01

Black pepper (Piper nigrum L.), a tropical spice crop of global acclaim, is susceptible to Phytophthora capsici, an oomycete pathogen which causes the highly destructive foot rot disease. A systematic understanding of this phytopathosystem has not been possible owing to lack of genome or proteome information. In this study, we explain an integrated transcriptome-assisted label-free quantitative proteomics pipeline to study the basal immune components of black pepper when challenged with P. capsici. We report a global identification of 532 novel leaf proteins from black pepper, of which 518 proteins were functionally annotated using BLAST2GO tool. A label-free quantitation of the protein datasets revealed 194 proteins common to diseased and control protein datasets of which 22 proteins showed significant up-regulation and 134 showed significant down-regulation. Ninety-three proteins were identified exclusively on P. capsici infected leaf tissues and 245 were expressed only in mock (control) infected samples. In-depth analysis of our data gives novel insights into the regulatory pathways of black pepper which are compromised during the infection. Differential down-regulation was observed in a number of critical pathways like carbon fixation in photosynthetic organism, cyano-amino acid metabolism, fructose, and mannose metabolism, glutathione metabolism, and phenylpropanoid biosynthesis. The proteomics results were validated with real-time qRT-PCR analysis. We were also able to identify the complete coding sequences for all the proteins of which few selected genes were cloned and sequence characterized for further confirmation. Our study is the first report of a quantitative proteomics dataset in black pepper which provides convincing evidence on the effectiveness of a transcriptome-based label-free proteomics approach for elucidating the host response to biotic stress in a non-model spice crop like P. nigrum, for which genome information is unavailable. Our dataset will serve as a useful resource for future studies in this plant. Data are available via ProteomeXchange with identifier PXD003887. PMID:27379110

Transcriptome- Assisted Label-Free Quantitative Proteomics Analysis Reveals Novel Insights into Piper nigrum-Phytophthora capsici Phytopathosystem.

PubMed

Mahadevan, Chidambareswaren; Krishnan, Anu; Saraswathy, Gayathri G; Surendran, Arun; Jaleel, Abdul; Sakuntala, Manjula

2016-01-01

Black pepper (Piper nigrum L.), a tropical spice crop of global acclaim, is susceptible to Phytophthora capsici, an oomycete pathogen which causes the highly destructive foot rot disease. A systematic understanding of this phytopathosystem has not been possible owing to lack of genome or proteome information. In this study, we explain an integrated transcriptome-assisted label-free quantitative proteomics pipeline to study the basal immune components of black pepper when challenged with P. capsici. We report a global identification of 532 novel leaf proteins from black pepper, of which 518 proteins were functionally annotated using BLAST2GO tool. A label-free quantitation of the protein datasets revealed 194 proteins common to diseased and control protein datasets of which 22 proteins showed significant up-regulation and 134 showed significant down-regulation. Ninety-three proteins were identified exclusively on P. capsici infected leaf tissues and 245 were expressed only in mock (control) infected samples. In-depth analysis of our data gives novel insights into the regulatory pathways of black pepper which are compromised during the infection. Differential down-regulation was observed in a number of critical pathways like carbon fixation in photosynthetic organism, cyano-amino acid metabolism, fructose, and mannose metabolism, glutathione metabolism, and phenylpropanoid biosynthesis. The proteomics results were validated with real-time qRT-PCR analysis. We were also able to identify the complete coding sequences for all the proteins of which few selected genes were cloned and sequence characterized for further confirmation. Our study is the first report of a quantitative proteomics dataset in black pepper which provides convincing evidence on the effectiveness of a transcriptome-based label-free proteomics approach for elucidating the host response to biotic stress in a non-model spice crop like P. nigrum, for which genome information is unavailable. Our dataset will serve as a useful resource for future studies in this plant. Data are available via ProteomeXchange with identifier PXD003887.

IsobariQ: software for isobaric quantitative proteomics using IPTL, iTRAQ, and TMT.

PubMed

Arntzen, Magnus Ø; Koehler, Christian J; Barsnes, Harald; Berven, Frode S; Treumann, Achim; Thiede, Bernd

2011-02-04

Isobaric peptide labeling plays an important role in relative quantitative comparisons of proteomes. Isobaric labeling techniques utilize MS/MS spectra for relative quantification, which can be either based on the relative intensities of reporter ions in the low mass region (iTRAQ and TMT) or on the relative intensities of quantification signatures throughout the spectrum due to isobaric peptide termini labeling (IPTL). Due to the increased quantitative information found in MS/MS fragment spectra generated by the recently developed IPTL approach, new software was required to extract the quantitative information. IsobariQ was specifically developed for this purpose; however, support for the reporter ion techniques iTRAQ and TMT is also included. In addition, to address recently emphasized issues about heterogeneity of variance in proteomics data sets, IsobariQ employs the statistical software package R and variance stabilizing normalization (VSN) algorithms available therein. Finally, the functionality of IsobariQ is validated with data sets of experiments using 6-plex TMT and IPTL. Notably, protein substrates resulting from cleavage by proteases can be identified as shown for caspase targets in apoptosis.

PROTICdb: a web-based application to store, track, query, and compare plant proteome data.

PubMed

Ferry-Dumazet, Hélène; Houel, Gwenn; Montalent, Pierre; Moreau, Luc; Langella, Olivier; Negroni, Luc; Vincent, Delphine; Lalanne, Céline; de Daruvar, Antoine; Plomion, Christophe; Zivy, Michel; Joets, Johann

2005-05-01

PROTICdb is a web-based application, mainly designed to store and analyze plant proteome data obtained by two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) and mass spectrometry (MS). The purposes of PROTICdb are (i) to store, track, and query information related to proteomic experiments, i.e., from tissue sampling to protein identification and quantitative measurements, and (ii) to integrate information from the user's own expertise and other sources into a knowledge base, used to support data interpretation (e.g., for the determination of allelic variants or products of post-translational modifications). Data insertion into the relational database of PROTICdb is achieved either by uploading outputs of image analysis and MS identification software, or by filling web forms. 2-D PAGE annotated maps can be displayed, queried, and compared through a graphical interface. Links to external databases are also available. Quantitative data can be easily exported in a tabulated format for statistical analyses. PROTICdb is based on the Oracle or the PostgreSQL Database Management System and is freely available upon request at the following URL: http://moulon.inra.fr/ bioinfo/PROTICdb.

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

Capillary nano-immunoassays: advancing quantitative proteomics analysis, biomarker assessment, and molecular diagnostics.

PubMed

Chen, Jin-Qiu; Wakefield, Lalage M; Goldstein, David J

2015-06-06

There is an emerging demand for the use of molecular profiling to facilitate biomarker identification and development, and to stratify patients for more efficient treatment decisions with reduced adverse effects. In the past decade, great strides have been made to advance genomic, transcriptomic and proteomic approaches to address these demands. While there has been much progress with these large scale approaches, profiling at the protein level still faces challenges due to limitations in clinical sample size, poor reproducibility, unreliable quantitation, and lack of assay robustness. A novel automated capillary nano-immunoassay (CNIA) technology has been developed. This technology offers precise and accurate measurement of proteins and their post-translational modifications using either charge-based or size-based separation formats. The system not only uses ultralow nanogram levels of protein but also allows multi-analyte analysis using a parallel single-analyte format for increased sensitivity and specificity. The high sensitivity and excellent reproducibility of this technology make it particularly powerful for analysis of clinical samples. Furthermore, the system can distinguish and detect specific protein post-translational modifications that conventional Western blot and other immunoassays cannot easily capture. This review will summarize and evaluate the latest progress to optimize the CNIA system for comprehensive, quantitative protein and signaling event characterization. It will also discuss how the technology has been successfully applied in both discovery research and clinical studies, for signaling pathway dissection, proteomic biomarker assessment, targeted treatment evaluation and quantitative proteomic analysis. Lastly, a comparison of this novel system with other conventional immuno-assay platforms is performed.

Proteomics approaches advance our understanding of plant self-incompatibility response.

PubMed

Sankaranarayanan, Subramanian; Jamshed, Muhammad; Samuel, Marcus A

2013-11-01

Self-incompatibility (SI) in plants is a genetic mechanism that prevents self-fertilization and promotes out-crossing needed to maintain genetic diversity. SI has been classified into two broad categories: the gametophytic self-incompatibility (GSI) and the sporophytic self-incompatibility (SSI) based on the genetic mechanisms involved in 'self' pollen rejection. Recent proteomic approaches to identify potential candidates involved in SI have shed light onto a number of previously unidentified mechanisms required for SI response. SI proteome research has progressed from the use of isoelectric focusing in early days to the latest third-generation technique of comparative isobaric tag for relative and absolute quantitation (iTRAQ) used in recent times. We will focus on the proteome-based approaches used to study self-incompatibility (GSI and SSI), recent developments in the field of incompatibility research with emphasis on SSI and future prospects of using proteomic approaches to study self-incompatibility.

Redefining the Breast Cancer Exosome Proteome by Tandem Mass Tag Quantitative Proteomics and Multivariate Cluster Analysis.

PubMed

Clark, David J; Fondrie, William E; Liao, Zhongping; Hanson, Phyllis I; Fulton, Amy; Mao, Li; Yang, Austin J

2015-10-20

Exosomes are microvesicles of endocytic origin constitutively released by multiple cell types into the extracellular environment. With evidence that exosomes can be detected in the blood of patients with various malignancies, the development of a platform that uses exosomes as a diagnostic tool has been proposed. However, it has been difficult to truly define the exosome proteome due to the challenge of discerning contaminant proteins that may be identified via mass spectrometry using various exosome enrichment strategies. To better define the exosome proteome in breast cancer, we incorporated a combination of Tandem-Mass-Tag (TMT) quantitative proteomics approach and Support Vector Machine (SVM) cluster analysis of three conditioned media derived fractions corresponding to a 10 000g cellular debris pellet, a 100 000g crude exosome pellet, and an Optiprep enriched exosome pellet. The quantitative analysis identified 2 179 proteins in all three fractions, with known exosomal cargo proteins displaying at least a 2-fold enrichment in the exosome fraction based on the TMT protein ratios. Employing SVM cluster analysis allowed for the classification 251 proteins as "true" exosomal cargo proteins. This study provides a robust and vigorous framework for the future development of using exosomes as a potential multiprotein marker phenotyping tool that could be useful in breast cancer diagnosis and monitoring disease progression.

MASH Suite Pro: A Comprehensive Software Tool for Top-Down Proteomics*

PubMed Central

Cai, Wenxuan; Guner, Huseyin; Gregorich, Zachery R.; Chen, Albert J.; Ayaz-Guner, Serife; Peng, Ying; Valeja, Santosh G.; Liu, Xiaowen; Ge, Ying

2016-01-01

Top-down mass spectrometry (MS)-based proteomics is arguably a disruptive technology for the comprehensive analysis of all proteoforms arising from genetic variation, alternative splicing, and posttranslational modifications (PTMs). However, the complexity of top-down high-resolution mass spectra presents a significant challenge for data analysis. In contrast to the well-developed software packages available for data analysis in bottom-up proteomics, the data analysis tools in top-down proteomics remain underdeveloped. Moreover, despite recent efforts to develop algorithms and tools for the deconvolution of top-down high-resolution mass spectra and the identification of proteins from complex mixtures, a multifunctional software platform, which allows for the identification, quantitation, and characterization of proteoforms with visual validation, is still lacking. Herein, we have developed MASH Suite Pro, a comprehensive software tool for top-down proteomics with multifaceted functionality. MASH Suite Pro is capable of processing high-resolution MS and tandem MS (MS/MS) data using two deconvolution algorithms to optimize protein identification results. In addition, MASH Suite Pro allows for the characterization of PTMs and sequence variations, as well as the relative quantitation of multiple proteoforms in different experimental conditions. The program also provides visualization components for validation and correction of the computational outputs. Furthermore, MASH Suite Pro facilitates data reporting and presentation via direct output of the graphics. Thus, MASH Suite Pro significantly simplifies and speeds up the interpretation of high-resolution top-down proteomics data by integrating tools for protein identification, quantitation, characterization, and visual validation into a customizable and user-friendly interface. We envision that MASH Suite Pro will play an integral role in advancing the burgeoning field of top-down proteomics. PMID:26598644

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.

Trends in mass spectrometry instrumentation for proteomics

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

Smith, Richard D.

2002-12-01

Mass spectrometry has become a primary tool for proteomics due to its capabilities for rapid and sensitive protein identification and quantitation. It is now possible to identify thousands of proteins from microgram sample quantities in a single day and to quantify relative protein abundances. However, the needs for increased capabilities for proteome measurements are immense and are now driving both new strategies and instrument advances. These developments include those based on integration with multi-dimensional liquid separations and high accuracy mass measurements, and promise more than order of magnitude improvements in sensitivity, dynamic range, and throughput for proteomic analyses in themore » near future.« less

Quantitative proteomic view on secreted, cell surface-associated, and cytoplasmic proteins of the methicillin-resistant human pathogen Staphylococcus aureus under iron-limited conditions.

PubMed

Hempel, Kristina; Herbst, Florian-Alexander; Moche, Martin; Hecker, Michael; Becher, Dörte

2011-04-01

Staphylococcus aureus is capable of colonizing and infecting humans by its arsenal of surface-exposed and secreted proteins. Iron-limited conditions in mammalian body fluids serve as a major environmental signal to bacteria to express virulence determinants. Here we present a comprehensive, gel-free, and GeLC-MS/MS-based quantitative proteome profiling of S. aureus under this infection-relevant situation. (14)N(15)N metabolic labeling and three complementing approaches were combined for relative quantitative analyses of surface-associated proteins. The surface-exposed and secreted proteome profiling approaches comprise trypsin shaving, biotinylation, and precipitation of the supernatant. By analysis of the outer subproteomic and cytoplasmic protein fraction, 1210 proteins could be identified including 221 surface-associated proteins. Thus, access was enabled to 70% of the predicted cell wall-associated proteins, 80% of the predicted sortase substrates, two/thirds of lipoproteins and more than 50% of secreted and cytoplasmic proteins. For iron-deficiency, 158 surface-associated proteins were quantified. Twenty-nine proteins were found in altered amounts showing particularly surface-exposed proteins strongly induced, such as the iron-regulated surface determinant proteins IsdA, IsdB, IsdC and IsdD as well as lipid-anchored iron compound-binding proteins. The work presents a crucial subject for understanding S. aureus pathophysiology by the use of methods that allow quantitative surface proteome profiling.

Determination of burn patient outcome by large-scale quantitative discovery proteomics

PubMed Central

Finnerty, Celeste C.; Jeschke, Marc G.; Qian, Wei-Jun; Kaushal, Amit; Xiao, Wenzhong; Liu, Tao; Gritsenko, Marina A.; Moore, Ronald J.; Camp, David G.; Moldawer, Lyle L.; Elson, Constance; Schoenfeld, David; Gamelli, Richard; Gibran, Nicole; Klein, Matthew; Arnoldo, Brett; Remick, Daniel; Smith, Richard D.; Davis, Ronald; Tompkins, Ronald G.; Herndon, David N.

2013-01-01

Objective Emerging proteomics techniques can be used to establish proteomic outcome signatures and to identify candidate biomarkers for survival following traumatic injury. We applied high-resolution liquid chromatography-mass spectrometry (LC-MS) and multiplex cytokine analysis to profile the plasma proteome of survivors and non-survivors of massive burn injury to determine the proteomic survival signature following a major burn injury. Design Proteomic discovery study. Setting Five burn hospitals across the U.S. Patients Thirty-two burn patients (16 non-survivors and 16 survivors), 19–89 years of age, were admitted within 96 h of injury to the participating hospitals with burns covering >20% of the total body surface area and required at least one surgical intervention. Interventions None. Measurements and Main Results We found differences in circulating levels of 43 proteins involved in the acute phase response, hepatic signaling, the complement cascade, inflammation, and insulin resistance. Thirty-two of the proteins identified were not previously known to play a role in the response to burn. IL-4, IL-8, GM-CSF, MCP-1, and β2-microglobulin correlated well with survival and may serve as clinical biomarkers. Conclusions These results demonstrate the utility of these techniques for establishing proteomic survival signatures and for use as a discovery tool to identify candidate biomarkers for survival. This is the first clinical application of a high-throughput, large-scale LC-MS-based quantitative plasma proteomic approach for biomarker discovery for the prediction of patient outcome following burn, trauma or critical illness. PMID:23507713

Large Scale Mass Spectrometry-based Identifications of Enzyme-mediated Protein Methylation Are Subject to High False Discovery Rates*

PubMed Central

Hart-Smith, Gene; Yagoub, Daniel; Tay, Aidan P.; Pickford, Russell; Wilkins, Marc R.

2016-01-01

All large scale LC-MS/MS post-translational methylation site discovery experiments require methylpeptide spectrum matches (methyl-PSMs) to be identified at acceptably low false discovery rates (FDRs). To meet estimated methyl-PSM FDRs, methyl-PSM filtering criteria are often determined using the target-decoy approach. The efficacy of this methyl-PSM filtering approach has, however, yet to be thoroughly evaluated. Here, we conduct a systematic analysis of methyl-PSM FDRs across a range of sample preparation workflows (each differing in their exposure to the alcohols methanol and isopropyl alcohol) and mass spectrometric instrument platforms (each employing a different mode of MS/MS dissociation). Through 13CD3-methionine labeling (heavy-methyl SILAC) of Saccharomyces cerevisiae cells and in-depth manual data inspection, accurate lists of true positive methyl-PSMs were determined, allowing methyl-PSM FDRs to be compared with target-decoy approach-derived methyl-PSM FDR estimates. These results show that global FDR estimates produce extremely unreliable methyl-PSM filtering criteria; we demonstrate that this is an unavoidable consequence of the high number of amino acid combinations capable of producing peptide sequences that are isobaric to methylated peptides of a different sequence. Separate methyl-PSM FDR estimates were also found to be unreliable due to prevalent sources of false positive methyl-PSMs that produce high peptide identity score distributions. Incorrect methylation site localizations, peptides containing cysteinyl-S-β-propionamide, and methylated glutamic or aspartic acid residues can partially, but not wholly, account for these false positive methyl-PSMs. Together, these results indicate that the target-decoy approach is an unreliable means of estimating methyl-PSM FDRs and methyl-PSM filtering criteria. We suggest that orthogonal methylpeptide validation (e.g. heavy-methyl SILAC or its offshoots) should be considered a prerequisite for obtaining high confidence methyl-PSMs in large scale LC-MS/MS methylation site discovery experiments and make recommendations on how to reduce methyl-PSM FDRs in samples not amenable to heavy isotope labeling. Data are available via ProteomeXchange with the data identifier PXD002857. PMID:26699799

Proteomics wants cRacker: automated standardized data analysis of LC-MS derived proteomic data.

PubMed

Zauber, Henrik; Schulze, Waltraud X

2012-11-02

The large-scale analysis of thousands of proteins under various experimental conditions or in mutant lines has gained more and more importance in hypothesis-driven scientific research and systems biology in the past years. Quantitative analysis by large scale proteomics using modern mass spectrometry usually results in long lists of peptide ion intensities. The main interest for most researchers, however, is to draw conclusions on the protein level. Postprocessing and combining peptide intensities of a proteomic data set requires expert knowledge, and the often repetitive and standardized manual calculations can be time-consuming. The analysis of complex samples can result in very large data sets (lists with several 1000s to 100,000 entries of different peptides) that cannot easily be analyzed using standard spreadsheet programs. To improve speed and consistency of the data analysis of LC-MS derived proteomic data, we developed cRacker. cRacker is an R-based program for automated downstream proteomic data analysis including data normalization strategies for metabolic labeling and label free quantitation. In addition, cRacker includes basic statistical analysis, such as clustering of data, or ANOVA and t tests for comparison between treatments. Results are presented in editable graphic formats and in list files.

Differential expression profiling of serum proteins and metabolites for biomarker discovery

NASA Astrophysics Data System (ADS)

Roy, Sushmita Mimi; Anderle, Markus; Lin, Hua; Becker, Christopher H.

2004-11-01

A liquid chromatography-mass spectrometry (LC-MS) proteomics and metabolomics platform is presented for quantitative differential expression analysis. Proteome profiles obtained from 1.5 [mu]L of human serum show ~5000 de-isotoped and quantifiable molecular ions. Approximately 1500 metabolites are observed from 100 [mu]L of serum. Quantification is based on reproducible sample preparation and linear signal intensity as a function of concentration. The platform is validated using human serum, but is generally applicable to all biological fluids and tissues. The median coefficient of variation (CV) for ~5000 proteomic and ~1500 metabolomic molecular ions is approximately 25%. For the case of C-reactive protein, results agree with quantification by immunoassay. The independent contributions of two sources of variance, namely sample preparation and LC-MS analysis, are respectively quantified as 20.4 and 15.1% for the proteome, and 19.5 and 13.5% for the metabolome, for median CV values. Furthermore, biological diversity for ~20 healthy individuals is estimated by measuring the variance of ~6500 proteomic and metabolomic molecular ions in sera for each sample; the median CV is 22.3% for the proteome and 16.7% for the metabolome. Finally, quantitative differential expression profiling is applied to a clinical study comparing healthy individuals and rheumatoid arthritis (RA) patients.

Quantitative membrane proteomics reveals a role for tetraspanin enriched microdomains during entry of human cytomegalovirus

PubMed Central

John, Nessy; Malouli, Daniel

2017-01-01

Human cytomegalovirus (HCMV) depends on and modulates multiple host cell membrane proteins during each stage of the viral life cycle. To gain a global view of the impact of HCMV-infection on membrane proteins, we analyzed HCMV-induced changes in the abundance of membrane proteins in fibroblasts using stable isotope labeling with amino acids (SILAC), membrane fractionation and protein identification by two-dimensional liquid chromatography and tandem mass spectrometry. This systematic approach revealed that CD81, CD44, CD98, caveolin-1 and catenin delta-1 were down-regulated during infection whereas GRP-78 was up-regulated. Since CD81 downregulation was also observed during infection with UV-inactivated virus we hypothesized that this tetraspanin is part of the viral entry process. Interestingly, additional members of the tetraspanin family, CD9 and CD151, were also downregulated during HCMV-entry. Since tetraspanin-enriched microdomains (TEM) cluster host cell membrane proteins including known CMV receptors such as integrins, we studied whether TEMs are required for viral entry. When TEMs were disrupted with the cholesterol chelator methyl-β-cylcodextrin, viral entry was inhibited and this inhibition correlated with reduced surface levels of CD81, CD9 and CD151, whereas integrin levels remained unchanged. Furthermore, simultaneous siRNA-mediated knockdown of multiple tetraspanins inhibited viral entry whereas individual knockdown had little effect suggesting essential, but redundant roles for individual tetraspanins during entry. Taken together, our data suggest that TEM act as platforms for receptors utilized by HCMV for entry into cells. PMID:29121670

Isodeoxyelephantopin induces protective autophagy in lung cancer cells via Nrf2-p62-keap1 feedback loop

PubMed Central

Wang, Yang; Zhang, Jing; Huang, Zhi-Hao; Huang, Xiao-Hui; Zheng, Wei-Bin; Yin, Xing-Feng; Li, Yao-Lan; Li, Bin; He, Qing-Yu

2017-01-01

Isodeoxyelephantopin (ESI), isolated from Elephantopus scaber L. has been reported to exert anticancer effects. In this study, we aimed to investigate whether and how cancer cells exert protective responses against ESI treatment. Confocal fluorescence microscopy showed that ESI significantly induced autophagy flux in the lung cancer cells expressing mCherry-EGFP-LC3 reporter. Treatment of the cells with ESI increased the expression levels of the autophagy markers including LC3-II, ATG3 and Beclin1 in a dose-dependent manner. Pretreatment with autophagy inhibitor 3-methyladenine (3-MA) not only attenuated the effects of ESI on autophagy, but also enhanced the effects of ESI on cell viability and apoptosis. Mechanistically, the SILAC quantitative proteomics coupled with bioinformatics analysis revealed that the ESI-regulated proteins were mainly involved in Nrf2-mediated oxidative stress response. We found that ESI induced the nuclear translocation of Nrf2 for activating the downstream target genes including HO-1 and p62 (SQSTM1). More importantly, ESI-induced p62 could competitively bind with Keap1, and releases Nrf2 to activate downstream target gene p62 as a positive feedback loop, therefore promoting autophagy. Furthermore, knockdown of Nrf2 or p62 could abrogate the ESI-induced autophagy and significantly enhanced the anticancer effect of ESI. Taken together, we demonstrated that ESI can sustain cell survival by activating protective autophagy through Nrf2-p62-keap1 feedback loop, whereas targeting this regulatory axis combined with ESI treatment may be a promising strategy for anticancer therapy. PMID:28617433

Isodeoxyelephantopin induces protective autophagy in lung cancer cells via Nrf2-p62-keap1 feedback loop.

PubMed

Wang, Yang; Zhang, Jing; Huang, Zhi-Hao; Huang, Xiao-Hui; Zheng, Wei-Bin; Yin, Xing-Feng; Li, Yao-Lan; Li, Bin; He, Qing-Yu

2017-06-15

Isodeoxyelephantopin (ESI), isolated from Elephantopus scaber L. has been reported to exert anticancer effects. In this study, we aimed to investigate whether and how cancer cells exert protective responses against ESI treatment. Confocal fluorescence microscopy showed that ESI significantly induced autophagy flux in the lung cancer cells expressing mCherry-EGFP-LC3 reporter. Treatment of the cells with ESI increased the expression levels of the autophagy markers including LC3-II, ATG3 and Beclin1 in a dose-dependent manner. Pretreatment with autophagy inhibitor 3-methyladenine (3-MA) not only attenuated the effects of ESI on autophagy, but also enhanced the effects of ESI on cell viability and apoptosis. Mechanistically, the SILAC quantitative proteomics coupled with bioinformatics analysis revealed that the ESI-regulated proteins were mainly involved in Nrf2-mediated oxidative stress response. We found that ESI induced the nuclear translocation of Nrf2 for activating the downstream target genes including HO-1 and p62 (SQSTM1). More importantly, ESI-induced p62 could competitively bind with Keap1, and releases Nrf2 to activate downstream target gene p62 as a positive feedback loop, therefore promoting autophagy. Furthermore, knockdown of Nrf2 or p62 could abrogate the ESI-induced autophagy and significantly enhanced the anticancer effect of ESI. Taken together, we demonstrated that ESI can sustain cell survival by activating protective autophagy through Nrf2-p62-keap1 feedback loop, whereas targeting this regulatory axis combined with ESI treatment may be a promising strategy for anticancer therapy.

Click-MS: Tagless Protein Enrichment Using Bioorthogonal Chemistry for Quantitative Proteomics.

PubMed

Smits, Arne H; Borrmann, Annika; Roosjen, Mark; van Hest, Jan C M; Vermeulen, Michiel

2016-12-16

Epitope-tagging is an effective tool to facilitate protein enrichment from crude cell extracts. Traditionally, N- or C-terminal fused tags are employed, which, however, can perturb protein function. Unnatural amino acids (UAAs) harboring small reactive handles can be site-specifically incorporated into proteins, thus serving as a potential alternative for conventional protein tags. Here, we introduce Click-MS, which combines the power of site-specific UAA incorporation, bioorthogonal chemistry, and quantitative mass spectrometry-based proteomics to specifically enrich a single protein of interest from crude mammalian cell extracts. By genetic encoding of p-azido-l-phenylalanine, the protein of interest can be selectively captured using copper-free click chemistry. We use Click-MS to enrich proteins that function in different cellular compartments, and we identify protein-protein interactions, showing the great potential of Click-MS for interaction proteomics workflows.

Current trends in quantitative proteomics - an update.

PubMed

Li, H; Han, J; Pan, J; Liu, T; Parker, C E; Borchers, C H

2017-05-01

Proteins can provide insights into biological processes at the functional level, so they are very promising biomarker candidates. The quantification of proteins in biological samples has been routinely used for the diagnosis of diseases and monitoring the treatment. Although large-scale protein quantification in complex samples is still a challenging task, a great amount of effort has been made to advance the technologies that enable quantitative proteomics. Seven years ago, in 2009, we wrote an article about the current trends in quantitative proteomics. In writing this current paper, we realized that, today, we have an even wider selection of potential tools for quantitative proteomics. These tools include new derivatization reagents, novel sampling formats, new types of analyzers and scanning techniques, and recently developed software to assist in assay development and data analysis. In this review article, we will discuss these innovative methods, and their current and potential applications in proteomics. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

A Quantitative Proteomics Approach to Clinical Research with Non-Traditional Samples

PubMed Central

Licier, Rígel; Miranda, Eric; Serrano, Horacio

2016-01-01

The proper handling of samples to be analyzed by mass spectrometry (MS) can guarantee excellent results and a greater depth of analysis when working in quantitative proteomics. This is critical when trying to assess non-traditional sources such as ear wax, saliva, vitreous humor, aqueous humor, tears, nipple aspirate fluid, breast milk/colostrum, cervical-vaginal fluid, nasal secretions, bronco-alveolar lavage fluid, and stools. We intend to provide the investigator with relevant aspects of quantitative proteomics and to recognize the most recent clinical research work conducted with atypical samples and analyzed by quantitative proteomics. Having as reference the most recent and different approaches used with non-traditional sources allows us to compare new strategies in the development of novel experimental models. On the other hand, these references help us to contribute significantly to the understanding of the proportions of proteins in different proteomes of clinical interest and may lead to potential advances in the emerging field of precision medicine. PMID:28248241

A Quantitative Proteomics Approach to Clinical Research with Non-Traditional Samples.

PubMed

Licier, Rígel; Miranda, Eric; Serrano, Horacio

2016-10-17

The proper handling of samples to be analyzed by mass spectrometry (MS) can guarantee excellent results and a greater depth of analysis when working in quantitative proteomics. This is critical when trying to assess non-traditional sources such as ear wax, saliva, vitreous humor, aqueous humor, tears, nipple aspirate fluid, breast milk/colostrum, cervical-vaginal fluid, nasal secretions, bronco-alveolar lavage fluid, and stools. We intend to provide the investigator with relevant aspects of quantitative proteomics and to recognize the most recent clinical research work conducted with atypical samples and analyzed by quantitative proteomics. Having as reference the most recent and different approaches used with non-traditional sources allows us to compare new strategies in the development of novel experimental models. On the other hand, these references help us to contribute significantly to the understanding of the proportions of proteins in different proteomes of clinical interest and may lead to potential advances in the emerging field of precision medicine.

Dynamic changes in the mouse skeletal muscle proteome during denervation-induced atrophy.

PubMed

Lang, Franziska; Aravamudhan, Sriram; Nolte, Hendrik; Türk, Clara; Hölper, Soraya; Müller, Stefan; Günther, Stefan; Blaauw, Bert; Braun, Thomas; Krüger, Marcus

2017-07-01

Loss of neuronal stimulation enhances protein breakdown and reduces protein synthesis, causing rapid loss of muscle mass. To elucidate the pathophysiological adaptations that occur in atrophying muscles, we used stable isotope labelling and mass spectrometry to quantify protein expression changes accurately during denervation-induced atrophy after sciatic nerve section in the mouse gastrocnemius muscle. Additionally, mice were fed a stable isotope labelling of amino acids in cell culture (SILAC) diet containing 13 C 6 -lysine for 4, 7 or 11 days to calculate relative levels of protein synthesis in denervated and control muscles. Ubiquitin remnant peptides (K-ε-GG) were profiled by immunoaffinity enrichment to identify potential substrates of the ubiquitin-proteasomal pathway. Of the 4279 skeletal muscle proteins quantified, 850 were differentially expressed significantly within 2 weeks after denervation compared with control muscles. Moreover, pulse labelling identified Lys6 incorporation in 4786 proteins, of which 43 had differential Lys6 incorporation between control and denervated muscle. Enrichment of diglycine remnants identified 2100 endogenous ubiquitination sites and revealed a metabolic and myofibrillar protein diglycine signature, including myosin heavy chains, myomesins and titin, during denervation. Comparative analysis of these proteomic data sets with known atrogenes using a random forest approach identified 92 proteins subject to atrogene-like regulation that have not previously been associated directly with denervation-induced atrophy. Comparison of protein synthesis and proteomic data indicated that upregulation of specific proteins in response to denervation is mainly achieved by protein stabilization. This study provides the first integrated analysis of protein expression, synthesis and ubiquitin signatures during muscular atrophy in a living animal. © 2017. Published by The Company of Biologists Ltd.

iTRAQ-Based Quantitative Proteomic Analysis of the Initiation of Head Regeneration in Planarians.

PubMed

Geng, Xiaofang; Wang, Gaiping; Qin, Yanli; Zang, Xiayan; Li, Pengfei; Geng, Zhi; Xue, Deming; Dong, Zimei; Ma, Kexue; Chen, Guangwen; Xu, Cunshuan

2015-01-01

The planarian Dugesia japonica has amazing ability to regenerate a head from the anterior ends of the amputated stump with maintenance of the original anterior-posterior polarity. Although planarians present an attractive system for molecular investigation of regeneration and research has focused on clarifying the molecular mechanism of regeneration initiation in planarians at transcriptional level, but the initiation mechanism of planarian head regeneration (PHR) remains unclear at the protein level. Here, a global analysis of proteome dynamics during the early stage of PHR was performed using isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomics strategy, and our data are available via ProteomeXchange with identifier PXD002100. The results showed that 162 proteins were differentially expressed at 2 h and 6 h following amputation. Furthermore, the analysis of expression patterns and functional enrichment of the differentially expressed proteins showed that proteins involved in muscle contraction, oxidation reduction and protein synthesis were up-regulated in the initiation of PHR. Moreover, ingenuity pathway analysis showed that predominant signaling pathways such as ILK, calcium, EIF2 and mTOR signaling which were associated with cell migration, cell proliferation and protein synthesis were likely to be involved in the initiation of PHR. The results for the first time demonstrated that muscle contraction and ILK signaling might played important roles in the initiation of PHR at the global protein level. The findings of this research provide a molecular basis for further unraveling the mechanism of head regeneration initiation in planarians.

Targeted quantitative analysis of Streptococcus pyogenes virulence factors by multiple reaction monitoring.

PubMed

Lange, Vinzenz; Malmström, Johan A; Didion, John; King, Nichole L; Johansson, Björn P; Schäfer, Juliane; Rameseder, Jonathan; Wong, Chee-Hong; Deutsch, Eric W; Brusniak, Mi-Youn; Bühlmann, Peter; Björck, Lars; Domon, Bruno; Aebersold, Ruedi

2008-08-01

In many studies, particularly in the field of systems biology, it is essential that identical protein sets are precisely quantified in multiple samples such as those representing differentially perturbed cell states. The high degree of reproducibility required for such experiments has not been achieved by classical mass spectrometry-based proteomics methods. In this study we describe the implementation of a targeted quantitative approach by which predetermined protein sets are first identified and subsequently quantified at high sensitivity reliably in multiple samples. This approach consists of three steps. First, the proteome is extensively mapped out by multidimensional fractionation and tandem mass spectrometry, and the data generated are assembled in the PeptideAtlas database. Second, based on this proteome map, peptides uniquely identifying the proteins of interest, proteotypic peptides, are selected, and multiple reaction monitoring (MRM) transitions are established and validated by MS2 spectrum acquisition. This process of peptide selection, transition selection, and validation is supported by a suite of software tools, TIQAM (Targeted Identification for Quantitative Analysis by MRM), described in this study. Third, the selected target protein set is quantified in multiple samples by MRM. Applying this approach we were able to reliably quantify low abundance virulence factors from cultures of the human pathogen Streptococcus pyogenes exposed to increasing amounts of plasma. The resulting quantitative protein patterns enabled us to clearly define the subset of virulence proteins that is regulated upon plasma exposure.

Quantitation of peptides from non-invasive skin tapings using isotope dilution and tandem mass spectrometry.

PubMed

Reisdorph, Nichole; Armstrong, Michael; Powell, Roger; Quinn, Kevin; Legg, Kevin; Leung, Donald; Reisdorph, Rick

2018-05-01

Previous work from our laboratories utilized a novel skin taping method and mass spectrometry-based proteomics to discover clinical biomarkers of skin conditions; these included atopic dermatitis, Staphylococcus aureus colonization, and eczema herpeticum. While suitable for discovery purposes, semi-quantitative proteomics is generally time-consuming and expensive. Furthermore, depending on the method used, discovery-based proteomics can result in high variation and inadequate sensitivity to detect low abundant peptides. Therefore, we strove to develop a rapid, sensitive, and reproducible method to quantitate disease-related proteins from skin tapings. We utilized isotopically-labeled peptides and tandem mass spectrometry to obtain absolute quantitation values on 14 peptides from 7 proteins; these proteins had shown previous importance in skin disease. The method demonstrated good reproducibility, dynamic range, and linearity (R 2  > 0.993) when n = 3 standards were analyzed across 0.05-2.5 pmol. The method was used to determine if differences exist between skin proteins in a small group of atopic versus non-atopic individuals (n = 12). While only minimal differences were found, peptides were detected in all samples and exhibited good correlation between peptides for 5 of the 7 proteins (R 2  = 0.71-0.98). This method can be applied to larger cohorts to further establish the relationships of these proteins to skin disease. Copyright © 2017. Published by Elsevier B.V.

Bardoxolone methyl (CDDO-Me or RTA402) induces cell cycle arrest, apoptosis and autophagy via PI3K/Akt/mTOR and p38 MAPK/Erk1/2 signaling pathways in K562 cells.

PubMed

Wang, Xin-Yu; Zhang, Xue-Hong; Peng, Li; Liu, Zheng; Yang, Yin-Xue; He, Zhi-Xu; Dang, Hong-Wan; Zhou, Shu-Feng

2017-01-01

Chronic myeloid leukemia (CML) treatment remains a challenge due to drug resistance and severe side effect, rendering the need on the development of novel therapeutics. CDDO-Me (Bardoxolone methyl), a potent Nrf2 activator and NF-κB inhibitor, is a promising candidate for cancer treatment including leukemia. However, the underlying mechanism for CDDO-Me in CML treatment is unclear. This study aimed to evaluate the molecular interactome of CDDO-Me in K562 cells using the quantitative proteomics approach stable-isotope labeling by amino acids in cell culture (SILAC) and explore the underlying mechanisms using cell-based functional assays. A total of 1,555 proteins responded to CDDO-Me exposure, including FANCI, SRPK2, XPO5, HP1BP3, NELFCD, Na + ,K + -ATPase 1, etc. in K562 cells. A total of 246 signaling pathways and 25 networks regulating cell survival and death, cellular function and maintenance, energy production, protein synthesis, response to oxidative stress, and nucleic acid metabolism were involved. Our verification experiments confirmed that CDDO-Me down-regulated Na + ,K + -ATPase α1 in K562 cells, and significantly arrested cells in G 2 /M and S phases, accompanied by remarkable alterations in the expression of key cell cycle regulators. CDDO-Me caused mitochondria-, death receptor-dependent and ER stress-mediated apoptosis in K562 cells, also induced autophagy with the suppression of PI3K/Akt/mTOR signaling pathway. p38 MAPK/Erk1/2 signaling pathways contributed to both apoptosis- and autophagy-inducing effects of CDDO-Me in K562 cells. Taken together, these data demonstrate that CDDO-Me is a potential anti-cancer agent that targets cell cycle, apoptosis, and autophagy in the treatment of CML.

Bardoxolone methyl (CDDO-Me or RTA402) induces cell cycle arrest, apoptosis and autophagy via PI3K/Akt/mTOR and p38 MAPK/Erk1/2 signaling pathways in K562 cells

PubMed Central

Wang, Xin-Yu; Zhang, Xue-Hong; Peng, Li; Liu, Zheng; Yang, Yin-Xue; He, Zhi-Xu; Dang, Hong-Wan; Zhou, Shu-Feng

2017-01-01

Chronic myeloid leukemia (CML) treatment remains a challenge due to drug resistance and severe side effect, rendering the need on the development of novel therapeutics. CDDO-Me (Bardoxolone methyl), a potent Nrf2 activator and NF-κB inhibitor, is a promising candidate for cancer treatment including leukemia. However, the underlying mechanism for CDDO-Me in CML treatment is unclear. This study aimed to evaluate the molecular interactome of CDDO-Me in K562 cells using the quantitative proteomics approach stable-isotope labeling by amino acids in cell culture (SILAC) and explore the underlying mechanisms using cell-based functional assays. A total of 1,555 proteins responded to CDDO-Me exposure, including FANCI, SRPK2, XPO5, HP1BP3, NELFCD, Na+,K+-ATPase 1, etc. in K562 cells. A total of 246 signaling pathways and 25 networks regulating cell survival and death, cellular function and maintenance, energy production, protein synthesis, response to oxidative stress, and nucleic acid metabolism were involved. Our verification experiments confirmed that CDDO-Me down-regulated Na+,K+-ATPase α1 in K562 cells, and significantly arrested cells in G2/M and S phases, accompanied by remarkable alterations in the expression of key cell cycle regulators. CDDO-Me caused mitochondria-, death receptor-dependent and ER stress-mediated apoptosis in K562 cells, also induced autophagy with the suppression of PI3K/Akt/mTOR signaling pathway. p38 MAPK/Erk1/2 signaling pathways contributed to both apoptosis- and autophagy-inducing effects of CDDO-Me in K562 cells. Taken together, these data demonstrate that CDDO-Me is a potential anti-cancer agent that targets cell cycle, apoptosis, and autophagy in the treatment of CML. PMID:29118925

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

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.

Quantitative targeted proteomics for understanding the blood-brain barrier: towards pharmacoproteomics.

PubMed

Ohtsuki, Sumio; Hirayama, Mio; Ito, Shingo; Uchida, Yasuo; Tachikawa, Masanori; Terasaki, Tetsuya

2014-06-01

The blood-brain barrier (BBB) is formed by brain capillary endothelial cells linked together via complex tight junctions, and serves to prevent entry of drugs into the brain. Multiple transporters are expressed at the BBB, where they control exchange of materials between the circulating blood and brain interstitial fluid, thereby supporting and protecting the CNS. An understanding of the BBB is necessary for efficient development of CNS-acting drugs and to identify potential drug targets for treatment of CNS diseases. Quantitative targeted proteomics can provide detailed information on protein expression levels at the BBB. The present review highlights the latest applications of quantitative targeted proteomics in BBB research, specifically to evaluate species and in vivo-in vitro differences, and to reconstruct in vivo transport activity. Such a BBB quantitative proteomics approach can be considered as pharmacoproteomics.

The PROTICdb database for 2-DE proteomics.

PubMed

Langella, Olivier; Zivy, Michel; Joets, Johann

2007-01-01

PROTICdb is a web-based database mainly designed to store and analyze plant proteome data obtained by 2D polyacrylamide gel electrophoresis (2D PAGE) and mass spectrometry (MS). The goals of PROTICdb are (1) to store, track, and query information related to proteomic experiments, i.e., from tissue sampling to protein identification and quantitative measurements; and (2) to integrate information from the user's own expertise and other sources into a knowledge base, used to support data interpretation (e.g., for the determination of allelic variants or products of posttranslational modifications). Data insertion into the relational database of PROTICdb is achieved either by uploading outputs from Mélanie, PDQuest, IM2d, ImageMaster(tm) 2D Platinum v5.0, Progenesis, Sequest, MS-Fit, and Mascot software, or by filling in web forms (experimental design and methods). 2D PAGE-annotated maps can be displayed, queried, and compared through the GelBrowser. Quantitative data can be easily exported in a tabulated format for statistical analyses with any third-party software. PROTICdb is based on the Oracle or the PostgreSQLDataBase Management System (DBMS) and is freely available upon request at http://cms.moulon.inra.fr/content/view/14/44/.

Analysis of the STAT3 interactome using in-situ biotinylation and SILAC.

PubMed

Blumert, Conny; Kalkhof, Stefan; Brocke-Heidrich, Katja; Kohajda, Tibor; von Bergen, Martin; Horn, Friedemann

2013-12-06

Signal transducer and activator of transcription 3 (STAT3) is activated by a variety of cytokines and growth factors. To generate a comprehensive data set of proteins interacting specifically with STAT3, we applied stable isotope labeling with amino acids in cell culture (SILAC). For high-affinity pull-down using streptavidin, we fused STAT3 with a short peptide tag allowing biotinylation in situ (bio-tag), which did not affect STAT3 functions. By this approach, 3642 coprecipitated proteins were detected in human embryonic kidney-293 cells. Filtering using statistical and functional criteria finally extracted 136 proteins as putative interaction partners of STAT3. Both, a physical interaction network analysis and the enrichment of known and predicted interaction partners suggested that our filtering criteria successfully enriched true STAT3 interactors. Our approach identified numerous novel interactors, including ones previously predicted to associate with STAT3. By reciprocal coprecipitation, we were able to verify the physical association between STAT3 and selected interactors, including the novel interaction with TOX4, a member of the TOX high mobility group box family. Applying the same method, we next investigated the activation-dependency of the STAT3 interactome. Again, we identified both known and novel interactions. Thus, our approach allows to study protein-protein interaction effectively and comprehensively. The location, activity, function, degradation, and synthesis of proteins are significantly regulated by interactions of proteins with other proteins, biopolymers and small molecules. Thus, the comprehensive characterization of interactions of proteins in a given proteome is the next milestone on the path to understanding the biochemistry of the cell. In order to generate a comprehensive interactome dataset of proteins specifically interacting with a selected bait protein, we fused our bait protein STAT3 with a short peptide tag allowing biotinylation in situ (bio-tag). This bio-tag allows an affinity pull-down using streptavidin but affected neither the activation of STAT3 by tyrosine phosphorylation nor its transactivating potential. We combined SILAC for accurate relative protein quantification, subcellular fractionation to increase the coverage of interacting proteins, high-affinity pull-down and a stringent filtering method to successfully analyze the interactome of STAT3. With our approach we confirmed several already known and identified numerous novel STAT3 interactors. The approach applied provides a rapid and effective method, which is broadly applicable for studying protein-protein interactions and their dependency on post-translational modifications. © 2013. Published by Elsevier B.V. All rights reserved.

Coatomer subunit beta 2 (COPB2), identified by label-free quantitative proteomics, regulates cell proliferation and apoptosis in human prostate carcinoma cells.

PubMed

Mi, Yuanyuan; Sun, Chuanyu; Wei, Bingbing; Sun, Feiyu; Guo, Yijun; Hu, Qingfeng; Ding, Weihong; Zhu, Lijie; Xia, Guowei

2018-01-01

Label-free quantitative proteomics has broad applications in the identification of differentially expressed proteins. Here, we applied this method to identify differentially expressed proteins (such as coatomer subunit beta 2 [COPB2]) and evaluated the functions and molecular mechanisms of these proteins in prostate cancer (PCA) cell proliferation. Proteins extracted from surgically resected PCA tissues and adjacent tissues of 3 patients were analyzed by label-free quantitative proteomics. The target protein was confirmed by bioinformatics and GEO dataset analyses. To investigate the role of the target protein in PCA, we used lentivirus-mediated small-interfering RNA (siRNA) to knockdown protein expression in the prostate carcinoma cell line, CWR22RV1 cells and assessed gene and protein expression by reverse transcription quantitative polymerase chain reaction and western blotting. CCK8 and colony formation assays were conducted to evaluate cell proliferation. Cell cycle distributions and apoptosis were assayed by flow cytometry. We selected the differentiation-related protein COPB2 as our target protein based on the results of label-free quantitative proteomics. High expression of COPB2 was found in PCA tissue and was related to poor overall survival based on a public dataset. Cell proliferation was significantly inhibited in COPB2-knockdown CWR22RV1 cells, as demonstrated by CCK8 and colony formation assays. Additionally, the apoptosis rate and percentage of cells in the G 1 phase were increased in COPB2-knockdown cells compared with those in control cells. CDK2, CDK4, and cyclin D1 were downregulated, whereas p21 Waf1/Cip1 and p27 Kip1 were upregulated, affecting the cell cycle signaling pathway. COPB2 significantly promoted CWR22RV1 cell proliferation through the cell cycle signaling pathway. Thus, silencing of COPB2 may have therapeutic applications in PCA. Copyright © 2017 Elsevier Inc. All rights reserved.

Advances in Quantitative Proteomics of Microbes and Microbial Communities

NASA Astrophysics Data System (ADS)

Waldbauer, J.; Zhang, L.; Rizzo, A. I.

2015-12-01

Quantitative measurements of gene expression are key to developing a mechanistic, predictive understanding of how microbial metabolism drives many biogeochemical fluxes and responds to environmental change. High-throughput RNA-sequencing can afford a wealth of information about transcript-level expression patterns, but it is becoming clear that expression dynamics are often very different at the protein level where biochemistry actually occurs. These divergent dynamics between levels of biological organization necessitate quantitative proteomic measurements to address many biogeochemical questions. The protein-level expression changes that underlie shifts in the magnitude, or even the direction, of metabolic and biogeochemical fluxes can be quite subtle and test the limits of current quantitative proteomics techniques. Here we describe methodologies for high-precision, whole-proteome quantification that are applicable to both model organisms of biogeochemical interest that may not be genetically tractable, and to complex community samples from natural environments. Employing chemical derivatization of peptides with multiple isotopically-coded tags, this strategy is rapid and inexpensive, can be implemented on a wide range of mass spectrometric instrumentation, and is relatively insensitive to chromatographic variability. We demonstrate the utility of this quantitative proteomics approach in application to both isolates and natural communities of sulfur-metabolizing and photosynthetic microbes.

Recent advances in proteomics of cereals.

PubMed

Bansal, Monika; Sharma, Madhu; Kanwar, Priyanka; Goyal, Aakash

Cereals contribute a major part of human nutrition and are considered as an integral source of energy for human diets. With genomic databases already available in cereals such as rice, wheat, barley, and maize, the focus has now moved to proteome analysis. Proteomics studies involve the development of appropriate databases based on developing suitable separation and purification protocols, identification of protein functions, and can confirm their functional networks based on already available data from other sources. Tremendous progress has been made in the past decade in generating huge data-sets for covering interactions among proteins, protein composition of various organs and organelles, quantitative and qualitative analysis of proteins, and to characterize their modulation during plant development, biotic, and abiotic stresses. Proteomics platforms have been used to identify and improve our understanding of various metabolic pathways. This article gives a brief review of efforts made by different research groups on comparative descriptive and functional analysis of proteomics applications achieved in the cereal science so far.

Quantitative proteomic analysis of paired colorectal cancer and non-tumorigenic tissues reveals signature proteins and perturbed pathways involved in CRC progression and metastasis.

PubMed

Sethi, Manveen K; Thaysen-Andersen, Morten; Kim, Hoguen; Park, Cheol Keun; Baker, Mark S; Packer, Nicolle H; Paik, Young-Ki; Hancock, William S; Fanayan, Susan

2015-08-03

Modern proteomics has proven instrumental in our understanding of the molecular deregulations associated with the development and progression of cancer. Herein, we profile membrane-enriched proteome of tumor and adjacent normal tissues from eight CRC patients using label-free nanoLC-MS/MS-based quantitative proteomics and advanced pathway analysis. Of the 948 identified proteins, 184 proteins were differentially expressed (P<0.05, fold change>1.5) between the tumor and non-tumor tissue (69 up-regulated and 115 down-regulated in tumor tissues). The CRC tumor and non-tumor tissues clustered tightly in separate groups using hierarchical cluster analysis of the differentially expressed proteins, indicating a strong CRC-association of this proteome subset. Specifically, cancer associated proteins such as FN1, TNC, DEFA1, ITGB2, MLEC, CDH17, EZR and pathways including actin cytoskeleton and RhoGDI signaling were deregulated. Stage-specific proteome signatures were identified including up-regulated ribosomal proteins and down-regulated annexin proteins in early stage CRC. Finally, EGFR(+) CRC tissues showed an EGFR-dependent down-regulation of cell adhesion molecules, relative to EGFR(-) tissues. Taken together, this study provides a detailed map of the altered proteome and associated protein pathways in CRC, which enhances our mechanistic understanding of CRC biology and opens avenues for a knowledge-driven search for candidate CRC protein markers. Copyright © 2015 Elsevier B.V. All rights reserved.

Performance Metrics for Liquid Chromatography-Tandem Mass Spectrometry Systems in Proteomics Analyses*

PubMed Central

Rudnick, Paul A.; Clauser, Karl R.; Kilpatrick, Lisa E.; Tchekhovskoi, Dmitrii V.; Neta, Pedatsur; Blonder, Nikša; Billheimer, Dean D.; Blackman, Ronald K.; Bunk, David M.; Cardasis, Helene L.; Ham, Amy-Joan L.; Jaffe, Jacob D.; Kinsinger, Christopher R.; Mesri, Mehdi; Neubert, Thomas A.; Schilling, Birgit; Tabb, David L.; Tegeler, Tony J.; Vega-Montoto, Lorenzo; Variyath, Asokan Mulayath; Wang, Mu; Wang, Pei; Whiteaker, Jeffrey R.; Zimmerman, Lisa J.; Carr, Steven A.; Fisher, Susan J.; Gibson, Bradford W.; Paulovich, Amanda G.; Regnier, Fred E.; Rodriguez, Henry; Spiegelman, Cliff; Tempst, Paul; Liebler, Daniel C.; Stein, Stephen E.

2010-01-01

A major unmet need in LC-MS/MS-based proteomics analyses is a set of tools for quantitative assessment of system performance and evaluation of technical variability. Here we describe 46 system performance metrics for monitoring chromatographic performance, electrospray source stability, MS1 and MS2 signals, dynamic sampling of ions for MS/MS, and peptide identification. Applied to data sets from replicate LC-MS/MS analyses, these metrics displayed consistent, reasonable responses to controlled perturbations. The metrics typically displayed variations less than 10% and thus can reveal even subtle differences in performance of system components. Analyses of data from interlaboratory studies conducted under a common standard operating procedure identified outlier data and provided clues to specific causes. Moreover, interlaboratory variation reflected by the metrics indicates which system components vary the most between laboratories. Application of these metrics enables rational, quantitative quality assessment for proteomics and other LC-MS/MS analytical applications. PMID:19837981

Quantitative proteome analysis using isobaric peptide termini labeling (IPTL).

PubMed

Arntzen, Magnus O; Koehler, Christian J; Treumann, Achim; Thiede, Bernd

2011-01-01

The quantitative comparison of proteome level changes across biological samples has become an essential feature in proteomics that remains challenging. We have recently introduced isobaric peptide termini labeling (IPTL), a novel strategy for isobaric quantification based on the derivatization of peptide termini with complementary isotopically labeled reagents. Unlike non-isobaric quantification methods, sample complexity at the MS level is not increased, providing improved sensitivity and protein coverage. The distinguishing feature of IPTL when comparing it to more established isobaric labeling methods (iTRAQ and TMT) is the presence of quantification signatures in all sequence-determining ions in MS/MS spectra, not only in the low mass reporter ion region. This makes IPTL a quantification method that is accessible to mass spectrometers with limited capabilities in the low mass range. Also, the presence of several quantification points in each MS/MS spectrum increases the robustness of the quantification procedure.

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.

A review on recent developments in mass spectrometry instrumentation and quantitative tools advancing bacterial proteomics.

PubMed

Van Oudenhove, Laurence; Devreese, Bart

2013-06-01

Proteomics has evolved substantially since its early days, some 20 years ago. In this mini-review, we aim to provide an overview of general methodologies and more recent developments in mass spectrometric approaches used for relative and absolute quantitation of proteins. Enhancement of sensitivity of the mass spectrometers as well as improved sample preparation and protein fractionation methods are resulting in a more comprehensive analysis of proteomes. We also document some upcoming trends for quantitative proteomics such as the use of label-free quantification methods. Hopefully, microbiologists will continue to explore proteomics as a tool in their research to understand the adaptation of microorganisms to their ever changing environment. We encourage them to incorporate some of the described new developments in mass spectrometry to facilitate their analyses and improve the general knowledge of the fascinating world of microorganisms.

Identification of BCAP-{sub L} as a negative regulator of the TLR signaling-induced production of IL-6 and IL-10 in macrophages by tyrosine phosphoproteomics

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

Matsumura, Takayuki; Department of Life Science and Medical Bio-Science, Waseda University, Shinjuku-ku, Tokyo 162-8480; Oyama, Masaaki

2010-09-17

Research highlights: {yields} Twenty five tyrosine-phosphorylated proteins in LPS-stimulated macrophages were determined. {yields} BCAP is a novel tyrosine-phosphorylated protein in LPS-stimulated macrophages. {yields} BCAP-{sub L} inhibits IL-6 and IL-10 production in LPS-stimulated macrophages. -- Abstract: Toll-like receptor (TLR) signaling in macrophages is essential for anti-pathogen responses such as cytokine production and antigen presentation. Although numerous reports suggest that protein tyrosine kinases (PTKs) are involved in cytokine induction in response to lipopolysaccharides (LPS; TLR4 ligand) in macrophages, the PTK-mediated signal transduction pathway has yet to be analyzed in detail. Here, we carried out a comprehensive and quantitative dynamic tyrosine phosphoproteomic analysismore » on the TLR4-mediated host defense system in RAW264.7 macrophages using stable isotope labeling by amino acids in cell culture (SILAC). We determined the temporal profiles of 25 proteins based on SILAC-encoded peptide(s). Of these, we focused on the tyrosine phosphorylation of B-cell adaptor for phosphatidylinositol 3-kinase (BCAP) because the function of BCAP remains unknown in TLR signaling in macrophages. Furthermore, Bcap has two distinct transcripts, a full-length (Bcap-{sub L}) and an alternatively initiated or spliced (Bcap-{sub S}) mRNA, and little is known about the differential functions of the BCAP-{sub L} and BCAP-{sub S} proteins. Our study showed, for the first time, that RNAi-mediated selective depletion of BCAP-{sub L} enhanced IL-6 and IL-10 production but not TNF-{alpha} production in TLR ligand-stimulated macrophages. We propose that BCAP-{sub L} (but not BCAP-{sub S}) is a negative regulator of the TLR-mediated host defense system in macrophages.« less

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.

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.

Finding Biomass Degrading Enzymes Through an Activity-Correlated Quantitative Proteomics Platform (ACPP).

PubMed

Ma, Hongyan; Delafield, Daniel G; Wang, Zhe; You, Jianlan; Wu, Si

2017-04-01

The microbial secretome, known as a pool of biomass (i.e., plant-based materials) degrading enzymes, can be utilized to discover industrial enzyme candidates for biofuel production. Proteomics approaches have been applied to discover novel enzyme candidates through comparing protein expression profiles with enzyme activity of the whole secretome under different growth conditions. However, the activity measurement of each enzyme candidate is needed for confident "active" enzyme assignments, which remains to be elucidated. To address this challenge, we have developed an Activity-Correlated Quantitative Proteomics Platform (ACPP) that systematically correlates protein-level enzymatic activity patterns and protein elution profiles using a label-free quantitative proteomics approach. The ACPP optimized a high performance anion exchange separation for efficiently fractionating complex protein samples while preserving enzymatic activities. The detected enzymatic activity patterns in sequential fractions using microplate-based assays were cross-correlated with protein elution profiles using a customized pattern-matching algorithm with a correlation R-score. The ACPP has been successfully applied to the identification of two types of "active" biomass-degrading enzymes (i.e., starch hydrolysis enzymes and cellulose hydrolysis enzymes) from Aspergillus niger secretome in a multiplexed fashion. By determining protein elution profiles of 156 proteins in A. niger secretome, we confidently identified the 1,4-α-glucosidase as the major "active" starch hydrolysis enzyme (R = 0.96) and the endoglucanase as the major "active" cellulose hydrolysis enzyme (R = 0.97). The results demonstrated that the ACPP facilitated the discovery of bioactive enzymes from complex protein samples in a high-throughput, multiplexing, and untargeted fashion. Graphical Abstract ᅟ.

Finding Biomass Degrading Enzymes Through an Activity-Correlated Quantitative Proteomics Platform (ACPP)

NASA Astrophysics Data System (ADS)

Ma, Hongyan; Delafield, Daniel G.; Wang, Zhe; You, Jianlan; Wu, Si

2017-04-01

The microbial secretome, known as a pool of biomass (i.e., plant-based materials) degrading enzymes, can be utilized to discover industrial enzyme candidates for biofuel production. Proteomics approaches have been applied to discover novel enzyme candidates through comparing protein expression profiles with enzyme activity of the whole secretome under different growth conditions. However, the activity measurement of each enzyme candidate is needed for confident "active" enzyme assignments, which remains to be elucidated. To address this challenge, we have developed an Activity-Correlated Quantitative Proteomics Platform (ACPP) that systematically correlates protein-level enzymatic activity patterns and protein elution profiles using a label-free quantitative proteomics approach. The ACPP optimized a high performance anion exchange separation for efficiently fractionating complex protein samples while preserving enzymatic activities. The detected enzymatic activity patterns in sequential fractions using microplate-based assays were cross-correlated with protein elution profiles using a customized pattern-matching algorithm with a correlation R-score. The ACPP has been successfully applied to the identification of two types of "active" biomass-degrading enzymes (i.e., starch hydrolysis enzymes and cellulose hydrolysis enzymes) from Aspergillus niger secretome in a multiplexed fashion. By determining protein elution profiles of 156 proteins in A. niger secretome, we confidently identified the 1,4-α-glucosidase as the major "active" starch hydrolysis enzyme (R = 0.96) and the endoglucanase as the major "active" cellulose hydrolysis enzyme (R = 0.97). The results demonstrated that the ACPP facilitated the discovery of bioactive enzymes from complex protein samples in a high-throughput, multiplexing, and untargeted fashion.

Quantitative proteomics analysis using 2D-PAGE to investigate the effects of cigarette smoke and aerosol of a prototypic modified risk tobacco product on the lung proteome in C57BL/6 mice.

PubMed

Elamin, Ashraf; Titz, Bjoern; Dijon, Sophie; Merg, Celine; Geertz, Marcel; Schneider, Thomas; Martin, Florian; Schlage, Walter K; Frentzel, Stefan; Talamo, Fabio; Phillips, Blaine; Veljkovic, Emilija; Ivanov, Nikolai V; Vanscheeuwijck, Patrick; Peitsch, Manuel C; Hoeng, Julia

2016-08-11

Smoking is associated with several serious diseases, such as lung cancer and chronic obstructive pulmonary disease (COPD). Within our systems toxicology framework, we are assessing whether potential modified risk tobacco products (MRTP) can reduce smoking-related health risks compared to conventional cigarettes. In this article, we evaluated to what extent 2D-PAGE/MALDI MS/MS (2D-PAGE) can complement the iTRAQ LC-MS/MS results from a previously reported mouse inhalation study, in which we assessed a prototypic MRTP (pMRTP). Selected differentially expressed proteins identified by both LC-MS/MS and 2D-PAGE approaches were further verified using reverse-phase protein microarrays. LC-MS/MS captured the effects of cigarette smoke (CS) on the lung proteome more comprehensively than 2D-PAGE. However, an integrated analysis of both proteomics data sets showed that 2D-PAGE data complement the LC-MS/MS results by supporting the overall trend of lower effects of pMRTP aerosol than CS on the lung proteome. Biological effects of CS exposure supported by both methods included increases in immune-related, surfactant metabolism, proteasome, and actin cytoskeleton protein clusters. Overall, while 2D-PAGE has its value, especially as a complementary method for the analysis of effects on intact proteins, LC-MS/MS approaches will likely be the method of choice for proteome analysis in systems toxicology investigations. Quantitative proteomics is anticipated to play a growing role within systems toxicology assessment frameworks in the future. To further understand how different proteomics technologies can contribute to toxicity assessment, we conducted a quantitative proteomics analysis using 2D-PAGE and isobaric tag-based LC-MS/MS approaches and compared the results produced from the 2 approaches. Using a prototypic modified risk tobacco product (pMRTP) as our test item, we show compared with cigarette smoke, how 2D-PAGE results can complement and support LC-MS/MS data, demonstrating the much lower effects of pMRTP aerosol than cigarette smoke on the mouse lung proteome. The combined analysis of 2D-PAGE and LC-MS/MS data identified an effect of cigarette smoke on the proteasome and actin cytoskeleton in the lung. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Quality Assessments of Long-Term Quantitative Proteomic Analysis of Breast Cancer Xenograft Tissues

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

Zhou, Jian-Ying; Chen, Lijun; Zhang, Bai

The identification of protein biomarkers requires large-scale analysis of human specimens to achieve statistical significance. In this study, we evaluated the long-term reproducibility of an iTRAQ (isobaric tags for relative and absolute quantification) based quantitative proteomics strategy using one channel for universal normalization across all samples. A total of 307 liquid chromatography tandem mass spectrometric (LC-MS/MS) analyses were completed, generating 107 one-dimensional (1D) LC-MS/MS datasets and 8 offline two-dimensional (2D) LC-MS/MS datasets (25 fractions for each set) for human-in-mouse breast cancer xenograft tissues representative of basal and luminal subtypes. Such large-scale studies require the implementation of robust metrics to assessmore » the contributions of technical and biological variability in the qualitative and quantitative data. Accordingly, we developed a quantification confidence score based on the quality of each peptide-spectrum match (PSM) to remove quantification outliers from each analysis. After combining confidence score filtering and statistical analysis, reproducible protein identification and quantitative results were achieved from LC-MS/MS datasets collected over a 16 month period.« less

Comprehensive and quantitative proteomic analyses of zebrafish plasma reveals conserved protein profiles between genders and between zebrafish and human.

PubMed

Li, Caixia; Tan, Xing Fei; Lim, Teck Kwang; Lin, Qingsong; Gong, Zhiyuan

2016-04-13

Omic approaches have been increasingly used in the zebrafish model for holistic understanding of molecular events and mechanisms of tissue functions. However, plasma is rarely used for omic profiling because of the technical challenges in collecting sufficient blood. In this study, we employed two mass spectrometric (MS) approaches for a comprehensive characterization of zebrafish plasma proteome, i.e. conventional shotgun liquid chromatography-tandem mass spectrometry (LC-MS/MS) for an overview study and quantitative SWATH (Sequential Window Acquisition of all THeoretical fragment-ion spectra) for comparison between genders. 959 proteins were identified in the shotgun profiling with estimated concentrations spanning almost five orders of magnitudes. Other than the presence of a few highly abundant female egg yolk precursor proteins (vitellogenins), the proteomic profiles of male and female plasmas were very similar in both number and abundance and there were basically no other highly gender-biased proteins. The types of plasma proteins based on IPA (Ingenuity Pathway Analysis) classification and tissue sources of production were also very similar. Furthermore, the zebrafish plasma proteome shares significant similarities with human plasma proteome, in particular in top abundant proteins including apolipoproteins and complements. Thus, the current study provided a valuable dataset for future evaluation of plasma proteins in zebrafish.

Comprehensive and quantitative proteomic analyses of zebrafish plasma reveals conserved protein profiles between genders and between zebrafish and human

PubMed Central

Li, Caixia; Tan, Xing Fei; Lim, Teck Kwang; Lin, Qingsong; Gong, Zhiyuan

2016-01-01

Omic approaches have been increasingly used in the zebrafish model for holistic understanding of molecular events and mechanisms of tissue functions. However, plasma is rarely used for omic profiling because of the technical challenges in collecting sufficient blood. In this study, we employed two mass spectrometric (MS) approaches for a comprehensive characterization of zebrafish plasma proteome, i.e. conventional shotgun liquid chromatography-tandem mass spectrometry (LC-MS/MS) for an overview study and quantitative SWATH (Sequential Window Acquisition of all THeoretical fragment-ion spectra) for comparison between genders. 959 proteins were identified in the shotgun profiling with estimated concentrations spanning almost five orders of magnitudes. Other than the presence of a few highly abundant female egg yolk precursor proteins (vitellogenins), the proteomic profiles of male and female plasmas were very similar in both number and abundance and there were basically no other highly gender-biased proteins. The types of plasma proteins based on IPA (Ingenuity Pathway Analysis) classification and tissue sources of production were also very similar. Furthermore, the zebrafish plasma proteome shares significant similarities with human plasma proteome, in particular in top abundant proteins including apolipoproteins and complements. Thus, the current study provided a valuable dataset for future evaluation of plasma proteins in zebrafish. PMID:27071722

Systematic Evaluation of the Use of Human Plasma and Serum for Mass-Spectrometry-Based Shotgun Proteomics.

PubMed

Lan, Jiayi; Núñez Galindo, Antonio; Doecke, James; Fowler, Christopher; Martins, Ralph N; Rainey-Smith, Stephanie R; Cominetti, Ornella; Dayon, Loïc

2018-04-06

Over the last two decades, EDTA-plasma has been used as the preferred sample matrix for human blood proteomic profiling. Serum has also been employed widely. Only a few studies have assessed the difference and relevance of the proteome profiles obtained from plasma samples, such as EDTA-plasma or lithium-heparin-plasma, and serum. A more complete evaluation of the use of EDTA-plasma, heparin-plasma, and serum would greatly expand the comprehensiveness of shotgun proteomics of blood samples. In this study, we evaluated the use of heparin-plasma with respect to EDTA-plasma and serum to profile blood proteomes using a scalable automated proteomic pipeline (ASAP 2 ). The use of plasma and serum for mass-spectrometry-based shotgun proteomics was first tested with commercial pooled samples. The proteome coverage consistency and the quantitative performance were compared. Furthermore, protein measurements in EDTA-plasma and heparin-plasma samples were comparatively studied using matched sample pairs from 20 individuals from the Australian Imaging, Biomarkers and Lifestyle (AIBL) Study. We identified 442 proteins in common between EDTA-plasma and heparin-plasma samples. Overall agreement of the relative protein quantification between the sample pairs demonstrated that shotgun proteomics using workflows such as the ASAP 2 is suitable in analyzing heparin-plasma and that such sample type may be considered in large-scale clinical research studies. Moreover, the partial proteome coverage overlaps (e.g., ∼70%) showed that measures from heparin-plasma could be complementary to those obtained from EDTA-plasma.

Metabolomics and proteomics technologies to explore the herbal preparation affecting metabolic disorders using high resolution mass spectrometry.

PubMed

Zhang, Aihua; Zhou, Xiaohang; Zhao, Hongwei; Zou, Shiyu; Ma, Chung Wah; Liu, Qi; Sun, Hui; Liu, Liang; Wang, Xijun

2017-01-31

An integrative metabolomics and proteomics approach can provide novel insights in the understanding of biological systems. We have integrated proteome and metabolome data sets for a holistic view of the molecular mechanisms in disease. Using quantitative iTRAQ-LC-MS/MS proteomics coupled with UPLC-Q-TOF-HDMS based metabolomics, we determined the protein and metabolite expression changes in the kidney-yang deficiency syndrome (KYDS) rat model and further investigated the intervention effects of the Jinkui Shenqi Pill (JSP). The VIP-plot of the orthogonal PLS-DA (OPLS-DA) was used for discovering the potential biomarkers to clarify the therapeutic mechanisms of JSP in treating KYDS. The results showed that JSP can alleviate the kidney impairment induced by KYDS. Sixty potential biomarkers, including 5-l-glutamyl-taurine, phenylacetaldehyde, 4,6-dihydroxyquinoline, and xanthurenic acid etc., were definitely up- or down-regulated. The regulatory effect of JSP on the disturbed metabolic pathways was proved by the established metabonomic method. Using pathway analyses, we identified the disturbed metabolic pathways such as taurine and hypotaurine metabolism, pyrimidine metabolism, tyrosine metabolism, tryptophan metabolism, histidine metabolism, steroid hormone biosynthesis, etc. Furthermore, using iTRAQ-based quantitative proteomics analysis, seventeen differential proteins were identified and significantly altered by the JSP treatment. These proteins appear to be involved in Wnt, chemokine, PPAR, and MAPK signaling pathways, etc. Functional pathway analysis revealed that most of the proteins were found to play a key role in the regulation of metabolism pathways. Bioinformatics analysis with the IPA software found that these differentially-expressed moleculars had a strong correlation with the α-adrenergic signaling, FGF signaling, etc. Our data indicate that high-throughput metabolomics and proteomics can provide an insight on the herbal preparations affecting the metabolic disorders using high resolution mass spectrometry.

Characterization of the human aqueous humour proteome: A comparison of the genders.

PubMed

Perumal, Natarajan; Manicam, Caroline; Steinicke, Matthias; Funke, Sebastian; Pfeiffer, Norbert; Grus, Franz H

2017-01-01

Aqueous humour (AH) is an important biologic fluid that maintains normal intraocular pressure and contains proteins that regulate the homeostasis of ocular tissues. Any alterations in the protein compositions are correlated to the pathogenesis of various ocular disorders. In recent years, gender-based medicine has emerged as an important research focus considering the prevalence of certain diseases, which are higher in a particular sex. Nevertheless, the inter-gender variations in the AH proteome are unknown. Therefore, this study endeavoured to characterize the AH proteome to assess the differences between genders. Thirty AH samples of patients who underwent cataract surgery were categorized according to their gender. Label-free quantitative discovery mass spectrometry-based proteomics strategy was employed to characterize the AH proteome. A total of 147 proteins were identified with a false discovery rate of less than 1% and only the top 10 major AH proteins make up almost 90% of the total identified proteins. A large number of proteins identified were correlated to defence, immune and inflammatory mechanisms, and response to wounding. Four proteins were found to be differentially abundant between the genders, comprising SERPINF1, SERPINA3, SERPING1 and PTGDS. The findings emerging from our study provide the first insight into the gender-based proteome differences in the AH and also highlight the importance in considering potential sex-dependent changes in the proteome of ocular pathologies in future studies employing the AH.

Mastitomics, the integrated omics of bovine milk in an experimental model of Streptococcus uberis mastitis: 2. Label-free relative quantitative proteomics.

PubMed

Mudaliar, Manikhandan; Tassi, Riccardo; Thomas, Funmilola C; McNeilly, Tom N; Weidt, Stefan K; McLaughlin, Mark; Wilson, David; Burchmore, Richard; Herzyk, Pawel; Eckersall, P David; Zadoks, Ruth N

2016-08-16

Mastitis, inflammation of the mammary gland, is the most common and costly disease of dairy cattle in the western world. It is primarily caused by bacteria, with Streptococcus uberis as one of the most prevalent causative agents. To characterize the proteome during Streptococcus uberis mastitis, an experimentally induced model of intramammary infection was used. Milk whey samples obtained from 6 cows at 6 time points were processed using label-free relative quantitative proteomics. This proteomic analysis complements clinical, bacteriological and immunological studies as well as peptidomic and metabolomic analysis of the same challenge model. A total of 2552 non-redundant bovine peptides were identified, and from these, 570 bovine proteins were quantified. Hierarchical cluster analysis and principal component analysis showed clear clustering of results by stage of infection, with similarities between pre-infection and resolution stages (0 and 312 h post challenge), early infection stages (36 and 42 h post challenge) and late infection stages (57 and 81 h post challenge). Ingenuity pathway analysis identified upregulation of acute phase protein pathways over the course of infection, with dominance of different acute phase proteins at different time points based on differential expression analysis. Antimicrobial peptides, notably cathelicidins and peptidoglycan recognition protein, were upregulated at all time points post challenge and peaked at 57 h, which coincided with 10 000-fold decrease in average bacterial counts. The integration of clinical, bacteriological, immunological and quantitative proteomics and other-omic data provides a more detailed systems level view of the host response to mastitis than has been achieved previously.

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.

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.

Simulated linear test applied to quantitative proteomics.

PubMed

Pham, T V; Jimenez, C R

2016-09-01

Omics studies aim to find significant changes due to biological or functional perturbation. However, gene and protein expression profiling experiments contain inherent technical variation. In discovery proteomics studies where the number of samples is typically small, technical variation plays an important role because it contributes considerably to the observed variation. Previous methods place both technical and biological variations in tightly integrated mathematical models that are difficult to adapt for different technological platforms. Our aim is to derive a statistical framework that allows the inclusion of a wide range of technical variability. We introduce a new method called the simulated linear test, or the s-test, that is easy to implement and easy to adapt for different models of technical variation. It generates virtual data points from the observed values according to a pre-defined technical distribution and subsequently employs linear modeling for significance analysis. We demonstrate the flexibility of the proposed approach by deriving a new significance test for quantitative discovery proteomics for which missing values have been a major issue for traditional methods such as the t-test. We evaluate the result on two label-free (phospho) proteomics datasets based on ion-intensity quantitation. Available at http://www.oncoproteomics.nl/software/stest.html : t.pham@vumc.nl. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

An FD-LC-MS/MS Proteomic Strategy for Revealing Cellular Protein Networks: A Conditional Superoxide Dismutase 1 Knockout Cells

PubMed Central

Ichibangase, Tomoko; Sugawara, Yasuhiro; Yamabe, Akio; Koshiyama, Akiyo; Yoshimura, Akari; Enomoto, Takemi; Imai, Kazuhiro

2012-01-01

Systems biology aims to understand biological phenomena in terms of complex biological and molecular interactions, and thus proteomics plays an important role in elucidating protein networks. However, many proteomic methods have suffered from their high variability, resulting in only showing altered protein names. Here, we propose a strategy for elucidating cellular protein networks based on an FD-LC-MS/MS proteomic method. The strategy permits reproducible relative quantitation of differences in protein levels between different cell populations and allows for integration of the data with those obtained through other methods. We demonstrate the validity of the approach through a comparison of differential protein expression in normal and conditional superoxide dismutase 1 gene knockout cells and believe that beginning with an FD-LC-MS/MS proteomic approach will enable researchers to elucidate protein networks more easily and comprehensively. PMID:23029042

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

Trimethylation enhancement using diazomethane (TrEnDi): rapid on-column quaternization of peptide amino groups via reaction with diazomethane significantly enhances sensitivity in mass spectrometry analyses via a fixed, permanent positive charge.

PubMed

Wasslen, Karl V; Tan, Le Hoa; Manthorpe, Jeffrey M; Smith, Jeffrey C

2014-04-01

Defining cellular processes relies heavily on elucidating the temporal dynamics of proteins. To this end, mass spectrometry (MS) is an extremely valuable tool; different MS-based quantitative proteomics strategies have emerged to map protein dynamics over the course of stimuli. Herein, we disclose our novel MS-based quantitative proteomics strategy with unique analytical characteristics. By passing ethereal diazomethane over peptides on strong cation exchange resin within a microfluidic device, peptides react to contain fixed, permanent positive charges. Modified peptides display improved ionization characteristics and dissociate via tandem mass spectrometry (MS(2)) to form strong a2 fragment ion peaks. Process optimization and determination of reactive functional groups enabled a priori prediction of MS(2) fragmentation patterns for modified peptides. The strategy was tested on digested bovine serum albumin (BSA) and successfully quantified a peptide that was not observable prior to modification. Our method ionizes peptides regardless of proton affinity, thus decreasing ion suppression and permitting predictable multiple reaction monitoring (MRM)-based quantitation with improved sensitivity.

Label-free quantitative proteomic analysis of human plasma-derived microvesicles to find protein signatures of abdominal aortic aneurysms.

PubMed

Martinez-Pinna, Roxana; Gonzalez de Peredo, Anne; Monsarrat, Bernard; Burlet-Schiltz, Odile; Martin-Ventura, Jose Luis

2014-08-01

To find potential biomarkers of abdominal aortic aneurysms (AAA), we performed a differential proteomic study based on human plasma-derived microvesicles. Exosomes and microparticles isolated from plasma of AAA patients and control subjects (n = 10 each group) were analyzed by a label-free quantitative MS-based strategy. Homemade and publicly available software packages have been used for MS data analysis. The application of two kinds of bioinformatic tools allowed us to find differential protein profiles from AAA patients. Some of these proteins found by the two analysis methods belong to main pathological mechanisms of AAA such as oxidative stress, immune-inflammation, and thrombosis. Data analysis from label-free MS-based experiments requires the use of sophisticated bioinformatic approaches to perform quantitative studies from complex protein mixtures. The application of two of these bioinformatic tools provided us a preliminary list of differential proteins found in plasma-derived microvesicles not previously associated to AAA, which could help us to understand the pathological mechanisms related to this disease. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mining for Microbial Gems: Integrating Proteomics in the Postgenomic Natural Product Discovery Pipeline.

PubMed

Du, Chao; van Wezel, Gilles P

2018-04-30

Natural products (NPs) are a major source of compounds for medical, agricultural, and biotechnological industries. Many of these compounds are of microbial origin, and, in particular, from Actinobacteria or filamentous fungi. To successfully identify novel compounds that correlate to a bioactivity of interest, or discover new enzymes with desired functions, systematic multiomics approaches have been developed over the years. Bioinformatics tools harness the rapidly expanding wealth of genome sequence information, revealing previously unsuspected biosynthetic diversity. Varying growth conditions or application of elicitors are applied to activate cryptic biosynthetic gene clusters, and metabolomics provide detailed insights into the NPs they specify. Combining these technologies with proteomics-based approaches to profile the biosynthetic enzymes provides scientists with insights into the full biosynthetic potential of microorganisms. The proteomics approaches include enrichment strategies such as employing activity-based probes designed by chemical biology, as well as unbiased (quantitative) proteomics methods. In this review, the opportunities and challenges in microbial NP research are discussed, and, in particular, the application of proteomics to link biosynthetic enzymes to the molecules they produce, and vice versa. © 2018 The Authors. Proteomics Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Computer aided manual validation of mass spectrometry-based proteomic data.

PubMed

Curran, Timothy G; Bryson, Bryan D; Reigelhaupt, Michael; Johnson, Hannah; White, Forest M

2013-06-15

Advances in mass spectrometry-based proteomic technologies have increased the speed of analysis and the depth provided by a single analysis. Computational tools to evaluate the accuracy of peptide identifications from these high-throughput analyses have not kept pace with technological advances; currently the most common quality evaluation methods are based on statistical analysis of the likelihood of false positive identifications in large-scale data sets. While helpful, these calculations do not consider the accuracy of each identification, thus creating a precarious situation for biologists relying on the data to inform experimental design. Manual validation is the gold standard approach to confirm accuracy of database identifications, but is extremely time-intensive. To palliate the increasing time required to manually validate large proteomic datasets, we provide computer aided manual validation software (CAMV) to expedite the process. Relevant spectra are collected, catalogued, and pre-labeled, allowing users to efficiently judge the quality of each identification and summarize applicable quantitative information. CAMV significantly reduces the burden associated with manual validation and will hopefully encourage broader adoption of manual validation in mass spectrometry-based proteomics. Copyright © 2013 Elsevier Inc. All rights reserved.

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

PubMed

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

2018-05-15

Idiopathic dilated cardiomyopathy (iDCM) is a primary myocardial disorder with an unknown aetiology, characterized by reduced contractility and ventricular dilation of the left or both ventricles. Naturally occurring canine iDCM was used herein to identify serum proteomic signature of the disease compared to the healthy state, providing an insight into underlying mechanisms and revealing proteins with biomarker potential. To achieve this, we used high-throughput label-based quantitative LC-MS/MS proteomics approach and bioinformatics analysis of the in silico inferred interactome protein network created from the initial list of differential proteins. To complement the proteomic analysis, serum biochemical parameters and levels of know biomarkers of cardiac function were measured. Several proteins with biomarker potential were identified, such as inter-alpha-trypsin inhibitor heavy chain H4, microfibril-associated glycoprotein 4 and apolipoprotein A-IV, which were validated using an independent method (Western blotting) and showed high specificity and sensitivity according to the receiver operating characteristic curve analysis. Bioinformatics analysis revealed involvement of different pathways in iDCM, such as complement cascade activation, lipoprotein particles dynamics, elastic fibre formation, GPCR signalling and respiratory electron transport chain. Idiopathic dilated cardiomyopathy is a severe primary myocardial disease of unknown cause, affecting both humans and dogs. This study is a contribution to the canine heart disease research by means of proteomic and bioinformatic state of the art analyses, following similar approach in human iDCM research. Importantly, we used serum as non-invasive and easily accessible biological source of information and contributed to the scarce data on biofluid proteome research on this topic. Bioinformatics analysis revealed biological pathways modulated in canine iDCM with potential of further targeted research. Also, several proteins with biomarker potential have been identified and successfully validated. Copyright © 2018 Elsevier B.V. All rights reserved.

Quantitative Metaproteomics and Activity-Based Probe Enrichment Reveals Significant Alterations in Protein Expression from a Mouse Model of Inflammatory Bowel Disease.

PubMed

Mayers, Michael D; Moon, Clara; Stupp, Gregory S; Su, Andrew I; Wolan, Dennis W

2017-02-03

Tandem mass spectrometry based shotgun proteomics of distal gut microbiomes is exceedingly difficult due to the inherent complexity and taxonomic diversity of the samples. We introduce two new methodologies to improve metaproteomic studies of microbiome samples. These methods include the stable isotope labeling in mammals to permit protein quantitation across two mouse cohorts as well as the application of activity-based probes to enrich and analyze both host and microbial proteins with specific functionalities. We used these technologies to study the microbiota from the adoptive T cell transfer mouse model of inflammatory bowel disease (IBD) and compare these samples to an isogenic control, thereby limiting genetic and environmental variables that influence microbiome composition. The data generated highlight quantitative alterations in both host and microbial proteins due to intestinal inflammation and corroborates the observed phylogenetic changes in bacteria that accompany IBD in humans and mouse models. The combination of isotope labeling with shotgun proteomics resulted in the total identification of 4434 protein clusters expressed in the microbial proteomic environment, 276 of which demonstrated differential abundance between control and IBD mice. Notably, application of a novel cysteine-reactive probe uncovered several microbial proteases and hydrolases overrepresented in the IBD mice. Implementation of these methods demonstrated that substantial insights into the identity and dysregulation of host and microbial proteins altered in IBD can be accomplished and can be used in the interrogation of other microbiome-related diseases.

A quantitative telomeric chromatin isolation protocol identifies different telomeric states

NASA Astrophysics Data System (ADS)

Grolimund, Larissa; Aeby, Eric; Hamelin, Romain; Armand, Florence; Chiappe, Diego; Moniatte, Marc; Lingner, Joachim

2013-11-01

Telomere composition changes during tumourigenesis, aging and in telomere syndromes in a poorly defined manner. Here we develop a quantitative telomeric chromatin isolation protocol (QTIP) for human cells, in which chromatin is cross-linked, immunopurified and analysed by mass spectrometry. QTIP involves stable isotope labelling by amino acids in cell culture (SILAC) to compare and identify quantitative differences in telomere protein composition of cells from various states. With QTIP, we specifically enrich telomeric DNA and all shelterin components. We validate the method characterizing changes at dysfunctional telomeres, and identify and validate known, as well as novel telomere-associated polypeptides including all THO subunits, SMCHD1 and LRIF1. We apply QTIP to long and short telomeres and detect increased density of SMCHD1 and LRIF1 and increased association of the shelterins TRF1, TIN2, TPP1 and POT1 with long telomeres. Our results validate QTIP to study telomeric states during normal development and in disease.

Bioinformatics for spermatogenesis: annotation of male reproduction based on proteomics

PubMed Central

Zhou, Tao; Zhou, Zuo-Min; Guo, Xue-Jiang

2013-01-01

Proteomics strategies have been widely used in the field of male reproduction, both in basic and clinical research. Bioinformatics methods are indispensable in proteomics-based studies and are used for data presentation, database construction and functional annotation. In the present review, we focus on the functional annotation of gene lists obtained through qualitative or quantitative methods, summarizing the common and male reproduction specialized proteomics databases. We introduce several integrated tools used to find the hidden biological significance from the data obtained. We further describe in detail the information on male reproduction derived from Gene Ontology analyses, pathway analyses and biomedical analyses. We provide an overview of bioinformatics annotations in spermatogenesis, from gene function to biological function and from biological function to clinical application. On the basis of recently published proteomics studies and associated data, we show that bioinformatics methods help us to discover drug targets for sperm motility and to scan for cancer-testis genes. In addition, we summarize the online resources relevant to male reproduction research for the exploration of the regulation of spermatogenesis. PMID:23852026

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.

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.

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

EBprot: Statistical analysis of labeling-based quantitative proteomics data.

PubMed

Koh, Hiromi W L; Swa, Hannah L F; Fermin, Damian; Ler, Siok Ghee; Gunaratne, Jayantha; Choi, Hyungwon

2015-08-01

Labeling-based proteomics is a powerful method for detection of differentially expressed proteins (DEPs). The current data analysis platform typically relies on protein-level ratios, which is obtained by summarizing peptide-level ratios for each protein. In shotgun proteomics, however, some proteins are quantified with more peptides than others, and this reproducibility information is not incorporated into the differential expression (DE) analysis. Here, we propose a novel probabilistic framework EBprot that directly models the peptide-protein hierarchy and rewards the proteins with reproducible evidence of DE over multiple peptides. To evaluate its performance with known DE states, we conducted a simulation study to show that the peptide-level analysis of EBprot provides better receiver-operating characteristic and more accurate estimation of the false discovery rates than the methods based on protein-level ratios. We also demonstrate superior classification performance of peptide-level EBprot analysis in a spike-in dataset. To illustrate the wide applicability of EBprot in different experimental designs, we applied EBprot to a dataset for lung cancer subtype analysis with biological replicates and another dataset for time course phosphoproteome analysis of EGF-stimulated HeLa cells with multiplexed labeling. Through these examples, we show that the peptide-level analysis of EBprot is a robust alternative to the existing statistical methods for the DE analysis of labeling-based quantitative datasets. The software suite is freely available on the Sourceforge website http://ebprot.sourceforge.net/. All MS data have been deposited in the ProteomeXchange with identifier PXD001426 (http://proteomecentral.proteomexchange.org/dataset/PXD001426/). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comprehensive Analysis of Proteomic Differences between Escherichia coli K-12 and B Strains Using Multiplexed Isobaric Tandem Mass Tag (TMT) Labeling.

PubMed

Han, Mee-Jung

2017-11-28

The Escherichia coli K-12 and B strains are among the most frequently used bacterial hosts for scientific research and biotechnological applications. However, omics analyses have revealed that E. coli K-12 and B exhibit notably different genotypic and phenotypic attributes, even though they were derived from the same ancestor. In a previous study, we identified a limited number of proteins from the two strains using two-dimensional gel electrophoresis and tandem mass spectrometry (MS/MS). In this study, an in-depth analysis of the physiological behavior of the E. coli K-12 and B strains at the proteomic level was performed using six-plex isobaric tandem mass tag-based quantitative MS. Additionally, the best lysis buffer for increasing the efficiency of protein extraction was selected from three tested buffers prior to the quantitative proteomic analysis. This study identifies the largest number of proteins in the two E. coli strains reported to date and is the first to show the dynamics of these proteins. Notable differences in proteins associated with key cellular properties, including some metabolic pathways, the biosynthesis and degradation of amino acids, membrane integrity, cellular tolerance, and motility, were found between the two representative strains. Compared with previous studies, these proteomic results provide a more holistic view of the overall state of E. coli cells based on a single proteomic study and reveal significant insights into why the two strains show distinct phenotypes. Additionally, the resulting data provide in-depth information that will help fine-tune processes in the future.

iTRAQ-Based Quantitative Proteomic Analysis of Spirulina platensis in Response to Low Temperature Stress

PubMed Central

Li, Qingye; Chang, Rong; Sun, Yijun; Li, Bosheng

2016-01-01

Low temperature (LT) is one of the most important abiotic stresses that can significantly reduce crop yield. To gain insight into how Spirulina responds to LT stress, comprehensive physiological and proteomic analyses were conducted in this study. Significant decreases in growth and pigment levels as well as excessive accumulation of compatible osmolytes were observed in response to LT stress. An isobaric tag for relative and absolute quantitation (iTRAQ)-based quantitative proteomics approach was used to identify changes in protein abundance in Spirulina under LT. A total of 3,782 proteins were identified, of which 1,062 showed differential expression. Bioinformatics analysis indicated that differentially expressed proteins that were enriched in photosynthesis, carbohydrate metabolism, amino acid biosynthesis, and translation are important for the maintenance of cellular homeostasis and metabolic balance in Spirulina when subjected to LT stress. The up-regulation of proteins involved in gluconeogenesis, starch and sucrose metabolism, and amino acid biosynthesis served as coping mechanisms of Spirulina in response to LT stress. Moreover, the down-regulated expression of proteins involved in glycolysis, TCA cycle, pentose phosphate pathway, photosynthesis, and translation were associated with reduced energy consumption. The findings of the present study allow a better understanding of the response of Spirulina to LT stress and may facilitate in the elucidation of mechanisms underlying LT tolerance. PMID:27902743

iTRAQ-Based Quantitative Proteomic Analysis of Spirulina platensis in Response to Low Temperature Stress.

PubMed

Li, Qingye; Chang, Rong; Sun, Yijun; Li, Bosheng

2016-01-01

Low temperature (LT) is one of the most important abiotic stresses that can significantly reduce crop yield. To gain insight into how Spirulina responds to LT stress, comprehensive physiological and proteomic analyses were conducted in this study. Significant decreases in growth and pigment levels as well as excessive accumulation of compatible osmolytes were observed in response to LT stress. An isobaric tag for relative and absolute quantitation (iTRAQ)-based quantitative proteomics approach was used to identify changes in protein abundance in Spirulina under LT. A total of 3,782 proteins were identified, of which 1,062 showed differential expression. Bioinformatics analysis indicated that differentially expressed proteins that were enriched in photosynthesis, carbohydrate metabolism, amino acid biosynthesis, and translation are important for the maintenance of cellular homeostasis and metabolic balance in Spirulina when subjected to LT stress. The up-regulation of proteins involved in gluconeogenesis, starch and sucrose metabolism, and amino acid biosynthesis served as coping mechanisms of Spirulina in response to LT stress. Moreover, the down-regulated expression of proteins involved in glycolysis, TCA cycle, pentose phosphate pathway, photosynthesis, and translation were associated with reduced energy consumption. The findings of the present study allow a better understanding of the response of Spirulina to LT stress and may facilitate in the elucidation of mechanisms underlying LT tolerance.

Label free quantitative proteomics analysis on the cisplatin resistance in ovarian cancer cells.

PubMed

Wang, F; Zhu, Y; Fang, S; Li, S; Liu, S

2017-05-20

Quantitative proteomics has been made great progress in recent years. Label free quantitative proteomics analysis based on the mass spectrometry is widely used. Using this technique, we determined the differentially expressed proteins in the cisplatin-sensitive ovarian cancer cells COC1 and cisplatin-resistant cells COC1/DDP before and after the application of cisplatin. Using the GO analysis, we classified those proteins into different subgroups bases on their cellular component, biological process, and molecular function. We also used KEGG pathway analysis to determine the key signal pathways that those proteins were involved in. There are 710 differential proteins between COC1 and COC1/DDP cells, 783 between COC1 and COC1/DDP cells treated with cisplatin, 917 between the COC1/DDP cells and COC1/DDP cells treated with LaCl3, 775 between COC1/DDP cells treated with cisplatin and COC1/DDP cells treated with cisplatin and LaCl3. Among the same 411 differentially expressed proteins in cisplatin-sensitive COC1 cells and cisplain-resistant COC1/DDP cells before and after cisplatin treatment, 14% of them were localized on the cell membrane. According to the KEGG results, differentially expressed proteins were classified into 21 groups. The most abundant proteins were involved in spliceosome. This study lays a foundation for deciphering the mechanism for drug resistance in ovarian tumor.

A tutorial in displaying mass spectrometry-based proteomic data using heat maps.

PubMed

Key, Melissa

2012-01-01

Data visualization plays a critical role in interpreting experimental results of proteomic experiments. Heat maps are particularly useful for this task, as they allow us to find quantitative patterns across proteins and biological samples simultaneously. The quality of a heat map can be vastly improved by understanding the options available to display and organize the data in the heat map. This tutorial illustrates how to optimize heat maps for proteomics data by incorporating known characteristics of the data into the image. First, the concepts used to guide the creating of heat maps are demonstrated. Then, these concepts are applied to two types of analysis: visualizing spectral features across biological samples, and presenting the results of tests of statistical significance. For all examples we provide details of computer code in the open-source statistical programming language R, which can be used for biologists and clinicians with little statistical background. Heat maps are a useful tool for presenting quantitative proteomic data organized in a matrix format. Understanding and optimizing the parameters used to create the heat map can vastly improve both the appearance and the interoperation of heat map data.

Deciphering of the Human Interferon-Regulated Proteome by Mass Spectrometry-Based Quantitative Analysis Reveals Extent and Dynamics of Protein Induction and Repression

PubMed Central

Megger, Dominik A.; Philipp, Jos; Le-Trilling, Vu Thuy Khanh; Sitek, Barbara; Trilling, Mirko

2017-01-01

Interferons (IFNs) are pleotropic cytokines secreted upon encounter of pathogens and tumors. Applying their antipathogenic, antiproliferative, and immune stimulatory capacities, recombinant IFNs are frequently prescribed as drugs to treat different diseases. IFNs act by changing the gene expression profile of cells. Due to characteristics such as rapid gene induction and signaling, IFNs also represent prototypical model systems for various aspects of biomedical research (e.g., signal transduction). In regard to the signaling and activated promoters, IFNs can be subdivided into two groups. Here, alterations of the cellular proteome of human cells treated with IFNα and IFNγ were elucidated in a time-resolved manner by quantitative proteome analysis. The majority of protein regulations were strongly IFN type and time dependent. In addition to the expected upregulation of IFN-responsive proteins, an astonishing number of proteins became profoundly repressed especially by IFNγ. Thus, our comprehensive analysis revealed important insights into the human IFN-regulated proteome and its dynamics of protein induction and repression. Interestingly, the new class of IFN-repressed genes comprises known host factors for highly relevant pathogens such as HIV, dengue virus, and hepatitis C virus. PMID:28959263

Deciphering of the Human Interferon-Regulated Proteome by Mass Spectrometry-Based Quantitative Analysis Reveals Extent and Dynamics of Protein Induction and Repression.

PubMed

Megger, Dominik A; Philipp, Jos; Le-Trilling, Vu Thuy Khanh; Sitek, Barbara; Trilling, Mirko

2017-01-01

Interferons (IFNs) are pleotropic cytokines secreted upon encounter of pathogens and tumors. Applying their antipathogenic, antiproliferative, and immune stimulatory capacities, recombinant IFNs are frequently prescribed as drugs to treat different diseases. IFNs act by changing the gene expression profile of cells. Due to characteristics such as rapid gene induction and signaling, IFNs also represent prototypical model systems for various aspects of biomedical research (e.g., signal transduction). In regard to the signaling and activated promoters, IFNs can be subdivided into two groups. Here, alterations of the cellular proteome of human cells treated with IFNα and IFNγ were elucidated in a time-resolved manner by quantitative proteome analysis. The majority of protein regulations were strongly IFN type and time dependent. In addition to the expected upregulation of IFN-responsive proteins, an astonishing number of proteins became profoundly repressed especially by IFNγ. Thus, our comprehensive analysis revealed important insights into the human IFN-regulated proteome and its dynamics of protein induction and repression. Interestingly, the new class of IFN-repressed genes comprises known host factors for highly relevant pathogens such as HIV, dengue virus, and hepatitis C virus.

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

NCI's Proteome Characterization Centers Announced | Office of Cancer Clinical Proteomics Research

Cancer.gov

The National Cancer Institute (NCI), part of the National Institutes of Health, announces the launch of a Clinical Proteomic Tumor Analysis Consortium (CPTAC). CPTAC is a comprehensive, coordinated team effort to accelerate the understanding of the molecular basis of cancer through the application of robust, quantitative, proteomic technologies and workflows.

Trans-Proteomic Pipeline, a standardized data processing pipeline for large-scale reproducible proteomics informatics

PubMed Central

Deutsch, Eric W.; Mendoza, Luis; Shteynberg, David; Slagel, Joseph; Sun, Zhi; Moritz, Robert L.

2015-01-01

Democratization of genomics technologies has enabled the rapid determination of genotypes. More recently the democratization of comprehensive proteomics technologies is enabling the determination of the cellular phenotype and the molecular events that define its dynamic state. Core proteomic technologies include mass spectrometry to define protein sequence, protein:protein interactions, and protein post-translational modifications. Key enabling technologies for proteomics are bioinformatic pipelines to identify, quantitate, and summarize these events. The Trans-Proteomics Pipeline (TPP) is a robust open-source standardized data processing pipeline for large-scale reproducible quantitative mass spectrometry proteomics. It supports all major operating systems and instrument vendors via open data formats. Here we provide a review of the overall proteomics workflow supported by the TPP, its major tools, and how it can be used in its various modes from desktop to cloud computing. We describe new features for the TPP, including data visualization functionality. We conclude by describing some common perils that affect the analysis of tandem mass spectrometry datasets, as well as some major upcoming features. PMID:25631240

Trans-Proteomic Pipeline, a standardized data processing pipeline for large-scale reproducible proteomics informatics.

PubMed

Deutsch, Eric W; Mendoza, Luis; Shteynberg, David; Slagel, Joseph; Sun, Zhi; Moritz, Robert L

2015-08-01

Democratization of genomics technologies has enabled the rapid determination of genotypes. More recently the democratization of comprehensive proteomics technologies is enabling the determination of the cellular phenotype and the molecular events that define its dynamic state. Core proteomic technologies include MS to define protein sequence, protein:protein interactions, and protein PTMs. Key enabling technologies for proteomics are bioinformatic pipelines to identify, quantitate, and summarize these events. The Trans-Proteomics Pipeline (TPP) is a robust open-source standardized data processing pipeline for large-scale reproducible quantitative MS proteomics. It supports all major operating systems and instrument vendors via open data formats. Here, we provide a review of the overall proteomics workflow supported by the TPP, its major tools, and how it can be used in its various modes from desktop to cloud computing. We describe new features for the TPP, including data visualization functionality. We conclude by describing some common perils that affect the analysis of MS/MS datasets, as well as some major upcoming features. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative Shotgun Proteomics Using a Uniform 15N-Labeled Standard to Monitor Proteome Dynamics in Time Course Experiments Reveals New Insights into the Heat Stress Response of Chlamydomonas reinhardtii*

PubMed Central

Mühlhaus, Timo; Weiss, Julia; Hemme, Dorothea; Sommer, Frederik; Schroda, Michael

2011-01-01

Crop-plant-yield safety is jeopardized by temperature stress caused by the global climate change. To take countermeasures by breeding and/or transgenic approaches it is essential to understand the mechanisms underlying plant acclimation to heat stress. To this end proteomics approaches are most promising, as acclimation is largely mediated by proteins. Accordingly, several proteomics studies, mainly based on two-dimensional gel-tandem MS approaches, were conducted in the past. However, results often were inconsistent, presumably attributable to artifacts inherent to the display of complex proteomes via two-dimensional-gels. We describe here a new approach to monitor proteome dynamics in time course experiments. This approach involves full 15N metabolic labeling and mass spectrometry based quantitative shotgun proteomics using a uniform 15N standard over all time points. It comprises a software framework, IOMIQS, that features batch job mediated automated peptide identification by four parallelized search engines, peptide quantification and data assembly for the processing of large numbers of samples. We have applied this approach to monitor proteome dynamics in a heat stress time course using the unicellular green alga Chlamydomonas reinhardtii as model system. We were able to identify 3433 Chlamydomonas proteins, of which 1116 were quantified in at least three of five time points of the time course. Statistical analyses revealed that levels of 38 proteins significantly increased, whereas levels of 206 proteins significantly decreased during heat stress. The increasing proteins comprise 25 (co-)chaperones and 13 proteins involved in chromatin remodeling, signal transduction, apoptosis, photosynthetic light reactions, and yet unknown functions. Proteins decreasing during heat stress were significantly enriched in functional categories that mediate carbon flux from CO2 and external acetate into protein biosynthesis, which also correlated with a rapid, but fully reversible cell cycle arrest after onset of stress. Our approach opens up new perspectives for plant systems biology and provides novel insights into plant stress acclimation. PMID:21610104

A combination of SILAC and nucleotide acyl phosphate labelling reveals unexpected targets of the Rsk inhibitor BI-D1870.

PubMed

Edgar, Alexander J; Trost, Matthias; Watts, Colin; Zaru, Rossana

2014-02-01

Protein kinase inhibitors frequently have interesting effects that cannot be fully ascribed to the intended target kinase(s) but identifying additional targets that might explain the effects is not straightforward. By comparing two different inhibitors of the Rsk (p90 ribosomal S6 kinase) kinases, we found that the increasingly used compound BI-D1870 had biological effects in murine DCs (dendritic cells) that could not be solely ascribed to Rsk or other documented targets. We assessed the ability of BI-D1870 and a second Rsk inhibitor, BIX 02565 to protect enzyme active sites from reaction with biotinylated nucleotide acyl phosphates. Using SILAC (stable isotope labelling by amino acids in cell culture)-labelled DC lysates as a source of enzyme targets, we identify several kinases that interact with BI-D1870 but not with BIX 02565. We confirmed that these kinases, including Slk, Lok and Mst1, are inhibited by BI-D1870 but to a much lesser extent by BIX 02565 and that phosphorylation of some of their substrates is blocked by BI-D1870 in living cells. Our results suggest that the BI-D1870 inhibitor should be used with caution. The SILAC-based methodology we used should be useful for further comparative unbiased profiling of the target spectrum of kinase inhibitors with interesting biological effects under conditions that closely mimic those found in cells. © 2014 The author(s).

Elevated host lipid metabolism revealed by iTRAQ-based quantitative proteomic analysis of cerebrospinal fluid of tuberculous meningitis patients

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

Mu, Jun; Institute of Neuroscience and the Collaborative Innovation Center for Brain Science, Chongqing Medical University, Chongqing; Chongqing Key Laboratory of Neurobiology, Chongqing

Purpose: Tuberculous meningitis (TBM) remains to be one of the most deadly infectious diseases. The pathogen interacts with the host immune system, the process of which is largely unknown. Various cellular processes of Mycobacterium tuberculosis (MTB) centers around lipid metabolism. To determine the lipid metabolism related proteins, a quantitative proteomic study was performed here to identify differential proteins in the cerebrospinal fluid (CSF) obtained from TBM patients (n = 12) and healthy controls (n = 12). Methods: CSF samples were desalted, concentrated, labelled with isobaric tags for relative and absolute quantitation (iTRAQ™), and analyzed by multi-dimensional liquid chromatography-tandem mass spectrometry (LC-MS/MS). Gene ontology andmore » proteomic phenotyping analysis of the differential proteins were conducted using Database for Annotation, Visualization, and Integrated Discovery (DAVID) Bioinformatics Resources. ApoE and ApoB were selected for validation by ELISA. Results: Proteomic phenotyping of the 4 differential proteins was invloved in the lipid metabolism. ELISA showed significantly increased ApoB levels in TBM subjects compared to healthy controls. Area under the receiver operating characteristic curve analysis demonstrated ApoB levels could distinguish TBM subjects from healthy controls and viral meningitis subjects with 89.3% sensitivity and 92% specificity. Conclusions: CSF lipid metabolism disregulation, especially elevated expression of ApoB, gives insights into the pathogenesis of TBM. Further evaluation of these findings in larger studies including anti-tuberculosis medicated and unmedicated patient cohorts with other center nervous system infectious diseases is required for successful clinical translation. - Highlights: • The first proteomic study on the cerebrospinal fluid of tuberculous meningitis patients using iTRAQ. • Identify 4 differential proteins invloved in the lipid metabolism. • Elevated expression of ApoB gives insights into the pathogenesis of TBM.« less

A Proteomics Approach to the Protein Normalization Problem: Selection of Unvarying Proteins for MS-Based Proteomics and Western Blotting.

PubMed

Wiśniewski, Jacek R; Mann, Matthias

2016-07-01

Proteomics and other protein-based analysis methods such as Western blotting all face the challenge of discriminating changes in the levels of proteins of interest from inadvertent changes in the amount loaded for analysis. Mass-spectrometry-based proteomics can now estimate the relative and absolute amounts of thousands of proteins across diverse biological systems. We reasoned that this new technology could prove useful for selection of very stably expressed proteins that could serve as better loading controls than those traditionally employed. Large-scale proteomic analyses of SDS lysates of cultured cells and tissues revealed deglycase DJ-1 as the protein with the lowest variability in abundance among different cell types in human, mouse, and amphibian cells. The protein constitutes 0.069 ± 0.017% of total cellular protein and occurs at a specific concentration of 34.6 ± 8.7 pmol/mg of total protein. Since DJ-1 is ubiquitous and therefore easily detectable with several peptides, it can be helpful in normalization of proteomic data sets. In addition, DJ-1 appears to be an advantageous loading control for Western blot that is superior to those used commonly used, allowing comparisons between tissues and cells originating from evolutionarily distant vertebrate species. Notably, this is not possible by the detection and quantitation of housekeeping proteins, which are often used in the Western blot technique. The approach introduced here can be applied to select the most appropriate loading controls for MS-based proteomics or Western blotting in any biological system.

Statistical Design for Biospecimen Cohort Size in Proteomics-based Biomarker Discovery and Verification Studies

PubMed Central

Skates, Steven J.; Gillette, Michael A.; LaBaer, Joshua; Carr, Steven A.; Anderson, N. Leigh; Liebler, Daniel C.; Ransohoff, David; Rifai, Nader; Kondratovich, Marina; Težak, Živana; Mansfield, Elizabeth; Oberg, Ann L.; Wright, Ian; Barnes, Grady; Gail, Mitchell; Mesri, Mehdi; Kinsinger, Christopher R.; Rodriguez, Henry; Boja, Emily S.

2014-01-01

Protein biomarkers are needed to deepen our understanding of cancer biology and to improve our ability to diagnose, monitor and treat cancers. Important analytical and clinical hurdles must be overcome to allow the most promising protein biomarker candidates to advance into clinical validation studies. Although contemporary proteomics technologies support the measurement of large numbers of proteins in individual clinical specimens, sample throughput remains comparatively low. This problem is amplified in typical clinical proteomics research studies, which routinely suffer from a lack of proper experimental design, resulting in analysis of too few biospecimens to achieve adequate statistical power at each stage of a biomarker pipeline. To address this critical shortcoming, a joint workshop was held by the National Cancer Institute (NCI), National Heart, Lung and Blood Institute (NHLBI), and American Association for Clinical Chemistry (AACC), with participation from the U.S. Food and Drug Administration (FDA). An important output from the workshop was a statistical framework for the design of biomarker discovery and verification studies. Herein, we describe the use of quantitative clinical judgments to set statistical criteria for clinical relevance, and the development of an approach to calculate biospecimen sample size for proteomic studies in discovery and verification stages prior to clinical validation stage. This represents a first step towards building a consensus on quantitative criteria for statistical design of proteomics biomarker discovery and verification research. PMID:24063748

Statistical design for biospecimen cohort size in proteomics-based biomarker discovery and verification studies.

PubMed

Skates, Steven J; Gillette, Michael A; LaBaer, Joshua; Carr, Steven A; Anderson, Leigh; Liebler, Daniel C; Ransohoff, David; Rifai, Nader; Kondratovich, Marina; Težak, Živana; Mansfield, Elizabeth; Oberg, Ann L; Wright, Ian; Barnes, Grady; Gail, Mitchell; Mesri, Mehdi; Kinsinger, Christopher R; Rodriguez, Henry; Boja, Emily S

2013-12-06

Protein biomarkers are needed to deepen our understanding of cancer biology and to improve our ability to diagnose, monitor, and treat cancers. Important analytical and clinical hurdles must be overcome to allow the most promising protein biomarker candidates to advance into clinical validation studies. Although contemporary proteomics technologies support the measurement of large numbers of proteins in individual clinical specimens, sample throughput remains comparatively low. This problem is amplified in typical clinical proteomics research studies, which routinely suffer from a lack of proper experimental design, resulting in analysis of too few biospecimens to achieve adequate statistical power at each stage of a biomarker pipeline. To address this critical shortcoming, a joint workshop was held by the National Cancer Institute (NCI), National Heart, Lung, and Blood Institute (NHLBI), and American Association for Clinical Chemistry (AACC) with participation from the U.S. Food and Drug Administration (FDA). An important output from the workshop was a statistical framework for the design of biomarker discovery and verification studies. Herein, we describe the use of quantitative clinical judgments to set statistical criteria for clinical relevance and the development of an approach to calculate biospecimen sample size for proteomic studies in discovery and verification stages prior to clinical validation stage. This represents a first step toward building a consensus on quantitative criteria for statistical design of proteomics biomarker discovery and verification research.

Population-specific plasma proteomes of marine and freshwater three-spined sticklebacks (Gasterosteus aculeatus).

PubMed

Kültz, Dietmar; Li, Johnathon; Zhang, Xuezhen; Villarreal, Fernando; Pham, Tuan; Paguio, Darlene

2015-12-01

Molecular phenotypes that distinguish resident marine (Bodega Harbor) from landlocked freshwater (FW, Lake Solano) three-spined sticklebacks were revealed by label-free quantitative proteomics. Secreted plasma proteins involved in lipid transport, blood coagulation, proteolysis, plasminogen-activating cascades, extracellular stimulus responses, and immunity are most abundant in this species. Globulins and albumins are much less abundant than in mammalian plasma. Unbiased quantitative proteome profiling identified 45 highly population-specific plasma proteins. Population-specific abundance differences were validated by targeted proteomics based on data-independent acquisition. Gene ontology enrichment analyses and known functions of population-specific plasma proteins indicate enrichment of processes controlling cell adhesion, tissue remodeling, proteolytic processing, and defense signaling in marine sticklebacks. Moreover, fetuin B and leukocyte cell derived chemotaxin 2 are much more abundant in marine fish. These proteins promote bone morphogenesis and likely contribute to population-specific body armor differences. Plasma proteins enriched in FW fish promote translation, heme biosynthesis, and lipid transport, suggesting a greater presence of plasma microparticles. Many prominent population-specific plasma proteins (e.g. apoptosis-associated speck-like protein containing a CARD) lack any homolog of known function or adequate functional characterization. Their functional characterization and the identification of population-specific environmental contexts and selective pressures that cause plasma proteome diversification are future directions emerging from this study. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Functional Network of the Arabidopsis Plastoglobule Proteome Based on Quantitative Proteomics and Genome-Wide Coexpression Analysis1[C][W][OA

PubMed Central

Lundquist, Peter K.; Poliakov, Anton; Bhuiyan, Nazmul H.; Zybailov, Boris; Sun, Qi; van Wijk, Klaas J.

2012-01-01

Plastoglobules (PGs) in chloroplasts are thylakoid-associated monolayer lipoprotein particles containing prenyl and neutral lipids and several dozen proteins mostly with unknown functions. An integrated view of the role of the PG is lacking. Here, we better define the PG proteome and provide a conceptual framework for further studies. The PG proteome from Arabidopsis (Arabidopsis thaliana) leaf chloroplasts was determined by mass spectrometry of isolated PGs and quantitative comparison with the proteomes of unfractionated leaves, thylakoids, and stroma. Scanning electron microscopy showed the purity and size distribution of the isolated PGs. Compared with previous PG proteome analyses, we excluded several proteins and identified six new PG proteins, including an M48 metallopeptidase and two Absence of bc1 complex (ABC1) atypical kinases, confirmed by immunoblotting. This refined PG proteome consisted of 30 proteins, including six ABC1 kinases and seven fibrillins together comprising more than 70% of the PG protein mass. Other fibrillins were located predominantly in the stroma or thylakoid and not in PGs; we discovered that this partitioning can be predicted by their isoelectric point and hydrophobicity. A genome-wide coexpression network for the PG genes was then constructed from mRNA expression data. This revealed a modular network with four distinct modules that each contained at least one ABC1K and/or fibrillin gene. Each module showed clear enrichment in specific functions, including chlorophyll degradation/senescence, isoprenoid biosynthesis, plastid proteolysis, and redox regulators and phosphoregulators of electron flow. We propose a new testable model for the PGs, in which sets of genes are associated with specific PG functions. PMID:22274653

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-02-01

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

Comparison of three quantitative phosphoproteomic strategies to study receptor tyrosine kinase signaling.

PubMed

Zhang, Guoan; Neubert, Thomas A

2011-12-02

There are three quantitative phosphoproteomic strategies most commonly used to study receptor tyrosine kinase (RTK) signaling. These strategies quantify changes in: (1) all three forms of phosphosites (phosphoserine, phosphothreonine and phosphotyrosine) following enrichment of phosphopeptides by titanium dioxide or immobilized metal affinity chromatography; (2) phosphotyrosine sites following anti- phosphotyrosine antibody enrichment of phosphotyrosine peptides; or (3) phosphotyrosine proteins and their binding partners following anti-phosphotyrosine protein immunoprecipitation. However, it is not clear from literature which strategy is more effective. In this study, we assessed the utility of these three phosphoproteomic strategies in RTK signaling studies by using EphB receptor signaling as an example. We used all three strategies with stable isotope labeling with amino acids in cell culture (SILAC) to compare changes in phosphoproteomes upon EphB receptor activation. We used bioinformatic analysis to compare results from the three analyses. Our results show that the three strategies provide complementary information about RTK pathways.

Quantitative proteomic analysis of human lung tumor xenografts treated with the ectopic ATP synthase inhibitor citreoviridin.

PubMed

Wu, Yi-Hsuan; Hu, Chia-Wei; Chien, Chih-Wei; Chen, Yu-Ju; Huang, Hsuan-Cheng; Juan, Hsueh-Fen

2013-01-01

ATP synthase is present on the plasma membrane of several types of cancer cells. Citreoviridin, an ATP synthase inhibitor, selectively suppresses the proliferation and growth of lung cancer without affecting normal cells. However, the global effects of targeting ectopic ATP synthase in vivo have not been well defined. In this study, we performed quantitative proteomic analysis using isobaric tags for relative and absolute quantitation (iTRAQ) and provided a comprehensive insight into the complicated regulation by citreoviridin in a lung cancer xenograft model. With high reproducibility of the quantitation, we obtained quantitative proteomic profiling with 2,659 proteins identified. Bioinformatics analysis of the 141 differentially expressed proteins selected by their relative abundance revealed that citreoviridin induces alterations in the expression of glucose metabolism-related enzymes in lung cancer. The up-regulation of enzymes involved in gluconeogenesis and storage of glucose indicated that citreoviridin may reduce the glycolytic intermediates for macromolecule synthesis and inhibit cell proliferation. Using comprehensive proteomics, the results identify metabolic aspects that help explain the antitumorigenic effect of citreoviridin in lung cancer, which may lead to a better understanding of the links between metabolism and tumorigenesis in cancer therapy.

Quantitative Proteomic Analysis of Human Lung Tumor Xenografts Treated with the Ectopic ATP Synthase Inhibitor Citreoviridin

PubMed Central

Wu, Yi-Hsuan; Hu, Chia-Wei; Chien, Chih-Wei; Chen, Yu-Ju; Huang, Hsuan-Cheng; Juan, Hsueh-Fen

2013-01-01

ATP synthase is present on the plasma membrane of several types of cancer cells. Citreoviridin, an ATP synthase inhibitor, selectively suppresses the proliferation and growth of lung cancer without affecting normal cells. However, the global effects of targeting ectopic ATP synthase in vivo have not been well defined. In this study, we performed quantitative proteomic analysis using isobaric tags for relative and absolute quantitation (iTRAQ) and provided a comprehensive insight into the complicated regulation by citreoviridin in a lung cancer xenograft model. With high reproducibility of the quantitation, we obtained quantitative proteomic profiling with 2,659 proteins identified. Bioinformatics analysis of the 141 differentially expressed proteins selected by their relative abundance revealed that citreoviridin induces alterations in the expression of glucose metabolism-related enzymes in lung cancer. The up-regulation of enzymes involved in gluconeogenesis and storage of glucose indicated that citreoviridin may reduce the glycolytic intermediates for macromolecule synthesis and inhibit cell proliferation. Using comprehensive proteomics, the results identify metabolic aspects that help explain the antitumorigenic effect of citreoviridin in lung cancer, which may lead to a better understanding of the links between metabolism and tumorigenesis in cancer therapy. PMID:23990911

Non-gel Based Proteomics to Study Steroid Receptor Agonists in the Fathead Minnow

EPA Science Inventory

Toxicoproteomics is an emerging field that is greatly enabled by non-gel based methods using LC MS/MS for biomarker discovery and characterization for endocrine disrupting chemicals. Using iTRAQ (isobaric tagging for relative and absolute quantitation), we quantified a diverse r...

Oestrus synchronisation and superovulation alter the cervicovaginal mucus proteome of the ewe.

PubMed

Maddison, Jessie W; Rickard, Jessica P; Bernecic, Naomi C; Tsikis, Guillaume; Soleilhavoup, Clement; Labas, Valerie; Combes-Soia, Lucie; Harichaux, Gregoire; Druart, Xavier; Leahy, Tamara; de Graaf, Simon P

2017-02-23

Although essential for artificial insemination (AI) and MOET (multiple ovulation and embryo transfer), oestrus synchronisation and superovulation are associated with increased female reproductive tract mucus production and altered sperm transport. The effects of such breeding practices on the ovine cervicovaginal (CV) mucus proteome have not been detailed. The aim of this study was to qualitatively and quantitatively investigate the Merino CV mucus proteome in naturally cycling (NAT) ewes at oestrus and mid-luteal phase, and quantitatively compare CV oestrus mucus proteomes of NAT, progesterone synchronised (P4) and superovulated (SOV) ewes. Quantitative analysis revealed 60 proteins were more abundant during oestrus and 127 were more abundant during the luteal phase, with 27 oestrus specific and 40 luteal specific proteins identified. The oestrus proteins most disparate in abundance compared to mid-luteal phase were ceruloplasmin (CP), chitinase-3-like protein 1 (CHI3L1), clusterin (CLU), alkaline phosphatase (ALPL) and mucin-16 (MUC16). Exogenous hormones greatly altered the proteome with 51 and 32 proteins more abundant and 98 and 53 proteins less abundant, in P4 and SOV mucus, respectively when compared to NAT mucus. Investigation of the impact of these proteomic changes on sperm motility and longevity within mucus may help improve sperm transport and fertility following cervical AI. This manuscript is the first to detail the proteome of ovine cervicovaginal mucus using qualitative and quantitative proteomic methods over the oestrous cycle in naturally cycling ewes, and also after application of common oestrus synchronisation and superovulation practices. The investigation of the mucus proteome throughout both the follicular and luteal periods of the oestrous cycle, and also after oestrous synchronisation and superovulation provides information about the endocrine control and the effects that exogenous hormones have on protein expression in the female reproductive tract. This information contributes to the field by providing important information on the changes that occur to the cervicovaginal mucus proteome after use of exogenous hormones in controlled breeding programs, which are commonly used on farm and also in a research setting. Copyright © 2017 Elsevier B.V. All rights reserved.

freeQuant: A Mass Spectrometry Label-Free Quantification Software Tool for Complex Proteome Analysis.

PubMed

Deng, Ning; Li, Zhenye; Pan, Chao; Duan, Huilong

2015-01-01

Study of complex proteome brings forward higher request for the quantification method using mass spectrometry technology. In this paper, we present a mass spectrometry label-free quantification tool for complex proteomes, called freeQuant, which integrated quantification with functional analysis effectively. freeQuant consists of two well-integrated modules: label-free quantification and functional analysis with biomedical knowledge. freeQuant supports label-free quantitative analysis which makes full use of tandem mass spectrometry (MS/MS) spectral count, protein sequence length, shared peptides, and ion intensity. It adopts spectral count for quantitative analysis and builds a new method for shared peptides to accurately evaluate abundance of isoforms. For proteins with low abundance, MS/MS total ion count coupled with spectral count is included to ensure accurate protein quantification. Furthermore, freeQuant supports the large-scale functional annotations for complex proteomes. Mitochondrial proteomes from the mouse heart, the mouse liver, and the human heart were used to evaluate the usability and performance of freeQuant. The evaluation showed that the quantitative algorithms implemented in freeQuant can improve accuracy of quantification with better dynamic range.

Integrated Proteomic Approaches for Understanding Toxicity of Environmental Chemicals

EPA Science Inventory

To apply quantitative proteomic analysis to the evaluation of toxicity of environmental chemicals, we have developed an integrated proteomic technology platform. This platform has been applied to the analysis of the toxic effects and pathways of many important environmental chemi...

Selective labelling and eradication of antibiotic-tolerant bacterial populations in Pseudomonas aeruginosa biofilms

PubMed Central

Chua, Song Lin; Yam, Joey Kuok Hoong; Hao, Piliang; Adav, Sunil S.; Salido, May Margarette; Liu, Yang; Givskov, Michael; Sze, Siu Kwan; Tolker-Nielsen, Tim; Yang, Liang

2016-01-01

Drug resistance and tolerance greatly diminish the therapeutic potential of antibiotics against pathogens. Antibiotic tolerance by bacterial biofilms often leads to persistent infections, but its mechanisms are unclear. Here we use a proteomics approach, pulsed stable isotope labelling with amino acids (pulsed-SILAC), to quantify newly expressed proteins in colistin-tolerant subpopulations of Pseudomonas aeruginosa biofilms (colistin is a ‘last-resort' antibiotic against multidrug-resistant Gram-negative pathogens). Migration is essential for the formation of colistin-tolerant biofilm subpopulations, with colistin-tolerant cells using type IV pili to migrate onto the top of the colistin-killed biofilm. The colistin-tolerant cells employ quorum sensing (QS) to initiate the formation of new colistin-tolerant subpopulations, highlighting multicellular behaviour in antibiotic tolerance development. The macrolide erythromycin, which has been previously shown to inhibit the motility and QS of P. aeruginosa, boosts biofilm eradication by colistin. Our work provides insights on the mechanisms underlying the formation of antibiotic-tolerant populations in bacterial biofilms and indicates research avenues for designing more efficient treatments against biofilm-associated infections. PMID:26892159

The therapeutic response of CDDO-Me in the esophageal squamous cell carcinoma (ESCC) cells is mediated by CaMKIIα.

PubMed

Wang, Yan-Yang; Zhou, Shun; Zhao, Ren; Hai, Ping; Zhe, Hong

2016-01-01

CDDO-Me has exhibited a potent anticancer effect in human esophageal squamous cell carcinoma (ESCC) cells in our previous study, but the molecular interactome remains elusive. We applied the approach of stable-isotope labeling by amino acids in cell culture (SILAC) to assess the proteomic responses of CDDO-Me treatment in human ESCC Ec109 cells. The data were subsequently validated using Western blot assay. The results of our study revealed that CDDO-Me increased the expression level of 543 protein molecules, but decreased the expression level of 709 protein molecules in Ec109 cells. Among these modulated protein molecules, calcium/calmodulin-dependent protein kinase type II subunit α (CaMKIIα) was highly expressed in all tested ESCC cell lines, whereas its expression levels were substantially lower in normal control cell line. Its silencing by small interfering RNA inhibited CDDO-Me induced apoptosis and autophagy in ESCC cells. Collectively, these data demonstrate that the therapeutic response of CDDO-Me in the human ESCC cells is mediated by CaMKIIα.

Selective labelling and eradication of antibiotic-tolerant bacterial populations in Pseudomonas aeruginosa biofilms.

PubMed

Chua, Song Lin; Yam, Joey Kuok Hoong; Hao, Piliang; Adav, Sunil S; Salido, May Margarette; Liu, Yang; Givskov, Michael; Sze, Siu Kwan; Tolker-Nielsen, Tim; Yang, Liang

2016-02-19

Drug resistance and tolerance greatly diminish the therapeutic potential of antibiotics against pathogens. Antibiotic tolerance by bacterial biofilms often leads to persistent infections, but its mechanisms are unclear. Here we use a proteomics approach, pulsed stable isotope labelling with amino acids (pulsed-SILAC), to quantify newly expressed proteins in colistin-tolerant subpopulations of Pseudomonas aeruginosa biofilms (colistin is a 'last-resort' antibiotic against multidrug-resistant Gram-negative pathogens). Migration is essential for the formation of colistin-tolerant biofilm subpopulations, with colistin-tolerant cells using type IV pili to migrate onto the top of the colistin-killed biofilm. The colistin-tolerant cells employ quorum sensing (QS) to initiate the formation of new colistin-tolerant subpopulations, highlighting multicellular behaviour in antibiotic tolerance development. The macrolide erythromycin, which has been previously shown to inhibit the motility and QS of P. aeruginosa, boosts biofilm eradication by colistin. Our work provides insights on the mechanisms underlying the formation of antibiotic-tolerant populations in bacterial biofilms and indicates research avenues for designing more efficient treatments against biofilm-associated infections.

How well can morphology assess cell death modality? A proteomics study

PubMed Central

Chernobrovkin, Alexey L; Zubarev, Roman A

2016-01-01

While the focus of attempts to classify cell death programs has finally shifted in 2010s from microscopy-based morphological characteristics to biochemical assays, more recent discoveries have put the underlying assumptions of many such assays under severe stress, mostly because of the limited specificity of the assays. On the other hand, proteomics can quantitatively measure the abundances of thousands of proteins in a single experiment. Thus proteomics could develop a modern alternative to both semiquantitative morphology assessment as well as single-molecule biochemical assays. Here we tested this hypothesis by analyzing the proteomes of cells dying after been treated with various chemical agents. The most striking finding is that, for a multivariate model based on the proteome changes in three cells lines, the regulation patterns of the 200–500 most abundant proteins typically attributed to household type more accurately reflect that of the proteins directly interacting with the drug than any other protein subset grouped by common function or biological process, including cell death. This is in broad agreement with the 'rigid cell death mechanics' model where drug action mechanism and morphological changes caused by it are bijectively linked. This finding, if confirmed, will open way for a broad use of proteomics in death modality assessment. PMID:27752363

Maillard Proteomics: Opening New Pages

PubMed Central

Soboleva, Alena; Schmidt, Rico; Vikhnina, Maria; Grishina, Tatiana; Frolov, Andrej

2017-01-01

Protein glycation is a ubiquitous non-enzymatic post-translational modification, formed by reaction of protein amino and guanidino groups with carbonyl compounds, presumably reducing sugars and α-dicarbonyls. Resulting advanced glycation end products (AGEs) represent a highly heterogeneous group of compounds, deleterious in mammals due to their pro-inflammatory effect, and impact in pathogenesis of diabetes mellitus, Alzheimer’s disease and ageing. The body of information on the mechanisms and pathways of AGE formation, acquired during the last decades, clearly indicates a certain site-specificity of glycation. It makes characterization of individual glycation sites a critical pre-requisite for understanding in vivo mechanisms of AGE formation and developing adequate nutritional and therapeutic approaches to reduce it in humans. In this context, proteomics is the methodology of choice to address site-specific molecular changes related to protein glycation. Therefore, here we summarize the methods of Maillard proteomics, specifically focusing on the techniques providing comprehensive structural and quantitative characterization of glycated proteome. Further, we address the novel break-through areas, recently established in the field of Maillard research, i.e., in vitro models based on synthetic peptides, site-based diagnostics of metabolism-related diseases (e.g., diabetes mellitus), proteomics of anti-glycative defense, and dynamics of plant glycated proteome during ageing and response to environmental stress. PMID:29231845

Proteomics Is Analytical Chemistry: Fitness-for-Purpose in the Application of Top-Down and Bottom-Up Analyses.

PubMed

Coorssen, Jens R; Yergey, Alfred L

2015-12-03

Molecular mechanisms underlying health and disease function at least in part based on the flexibility and fine-tuning afforded by protein isoforms and post-translational modifications. The ability to effectively and consistently resolve these protein species or proteoforms, as well as assess quantitative changes is therefore central to proteomic analyses. Here we discuss the pros and cons of currently available and developing analytical techniques from the perspective of the full spectrum of available tools and their current applications, emphasizing the concept of fitness-for-purpose in experimental design based on consideration of sample size and complexity; this necessarily also addresses analytical reproducibility and its variance. Data quality is considered the primary criterion, and we thus emphasize that the standards of Analytical Chemistry must apply throughout any proteomic analysis.

Motile hepatocellular carcinoma cells preferentially secret sugar metabolism regulatory proteins via exosomes.

PubMed

Zhang, Jing; Lu, Shaohua; Zhou, Ye; Meng, Kun; Chen, Zhipeng; Cui, Yizhi; Shi, Yunfeng; Wang, Tong; He, Qing-Yu

2017-07-01

Exosomes are deliverers of critically functional proteins, capable of transforming target cells in numerous cancers, including hepatocellular carcinoma (HCC). We hypothesize that the motility of HCC cells can be featured by comparative proteome of exosomes. Hence, we performed the super-SILAC-based MS analysis on the exosomes secreted by three human HCC cell lines, including the non-motile Hep3B cell, and the motile 97H and LM3 cells. More than 1400 exosomal proteins were confidently quantified in each MS analysis with highly biological reproducibility. We justified that 469 and 443 exosomal proteins represented differentially expressed proteins (DEPs) in the 97H/Hep3B and LM3/Hep3B comparisons, respectively. These DEPs focused on sugar metabolism-centric canonical pathways per ingenuity pathway analysis, which was consistent with the gene ontology analysis on biological process enrichment. These pathways included glycolysis I, gluconeogenesis I and pentose phosphate pathways; and the DEPs enriched in these pathways could form a tightly connected network. By analyzing the relative abundance of proteins and translating mRNAs, we found significantly positive correlation between exosomes and cells. The involved exosomal proteins were again focusing on sugar metabolism. In conclusion, motile HCC cells tend to preferentially export more sugar metabolism-associated proteins via exosomes that differentiate them from non-motile HCC cells. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Inductively Coupled Plasma Mass Spectrometry (ICP-MS) Applications in Quantitative Proteomics.

PubMed

Chahrour, Osama; Malone, John

2017-01-01

Recent advances in inductively coupled plasma mass spectrometry (ICP-MS) hyphenated to different separation techniques have promoted it as a valuable tool in protein/peptide quantification. These emerging ICP-MS applications allow absolute quantification by measuring specific elemental responses. One approach quantifies elements already present in the structure of the target peptide (e.g. phosphorus and sulphur) as natural tags. Quantification of these natural tags allows the elucidation of the degree of protein phosphorylation in addition to absolute protein quantification. A separate approach is based on utilising bi-functional labelling substances (those containing ICP-MS detectable elements), that form a covalent chemical bond with the protein thus creating analogs which are detectable by ICP-MS. Based on the previously established stoichiometries of the labelling reagents, quantification can be achieved. This technique is very useful for the design of precise multiplexed quantitation schemes to address the challenges of biomarker screening and discovery. This review discusses the capabilities and different strategies to implement ICP-MS in the field of quantitative proteomics. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

The proteome signature of the inflammatory breast cancer plasma membrane identifies novel molecular markers of disease

PubMed Central

Suárez-Arroyo, Ivette J; Feliz-Mosquea, Yismeilin R; Pérez-Laspiur, Juliana; Arju, Rezina; Giashuddin, Shah; Maldonado-Martínez, Gerónimo; Cubano, Luis A; Schneider, Robert J; Martínez-Montemayor, Michelle M

2016-01-01

Inflammatory Breast Cancer (IBC) is the most lethal form of breast cancer with a 35% 5-year survival rate. The accurate and early diagnosis of IBC and the development of targeted therapy against this deadly disease remain a great medical challenge. Plasma membrane proteins (PMPs) such as E-cadherin and EGFR, play an important role in the progression of IBC. Because the critical role of PMPs in the oncogenic processes they are the perfect candidates as molecular markers and targets for cancer therapies. In the present study, Stable Isotope Labeling with Amino Acids in Cell Culture (SILAC) followed by mass spectrometry analysis was used to compare the relative expression levels of membrane proteins (MP) between non-cancerous mammary epithelial and IBC cells, MCF-10A and SUM-149, respectively. Six of the identified PMPs were validated by immunoblotting using the membrane fractions of non-IBC and IBC cell lines, compared with MCF-10A cells. Immunohistochemical analysis using IBC, invasive ductal carcinoma or normal mammary tissue samples was carried out to complete the validation method in nine of the PMPs. We identified and quantified 278 MPs, 76% of which classified as PMPs with 1.3-fold or higher change. We identified for the first time the overexpression of the novel plasminogen receptor, PLGRKT in IBC and of the carrier protein, SCAMP3. Furthermore, we describe the positive relationship between L1CAM expression and metastasis in IBC patients and the role of SCAMP3 as a tumor-related protein. Overall, the membrane proteomic signature of IBC reflects a global change in cellular organization and suggests additional strategies for cancer progression. Together, this study provides insight into the specialized IBC plasma membrane proteome with the potential to identify a number of novel therapeutic targets for IBC. PMID:27648361

Diminished superoxide generation is associated with respiratory chain dysfunction and changes in the mitochondrial proteome of sensory neurons from diabetic rats.

PubMed

Akude, Eli; Zherebitskaya, Elena; Chowdhury, Subir K Roy; Smith, Darrell R; Dobrowsky, Rick T; Fernyhough, Paul

2011-01-01

Impairments in mitochondrial function have been proposed to play a role in the etiology of diabetic sensory neuropathy. We tested the hypothesis that mitochondrial dysfunction in axons of sensory neurons in type 1 diabetes is due to abnormal activity of the respiratory chain and an altered mitochondrial proteome. Proteomic analysis using stable isotope labeling with amino acids in cell culture (SILAC) determined expression of proteins in mitochondria from dorsal root ganglia (DRG) of control, 22-week-old streptozotocin (STZ)-diabetic rats, and diabetic rats treated with insulin. Rates of oxygen consumption and complex activities in mitochondria from DRG were measured. Fluorescence imaging of axons of cultured sensory neurons determined the effect of diabetes on mitochondrial polarization status, oxidative stress, and mitochondrial matrix-specific reactive oxygen species (ROS). Proteins associated with mitochondrial dysfunction, oxidative phosphorylation, ubiquinone biosynthesis, and the citric acid cycle were downregulated in diabetic samples. For example, cytochrome c oxidase subunit IV (COX IV; a complex IV protein) and NADH dehydrogenase Fe-S protein 3 (NDUFS3; a complex I protein) were reduced by 29 and 36% (P < 0.05), respectively, in diabetes and confirmed previous Western blot studies. Respiration and mitochondrial complex activity was significantly decreased by 15 to 32% compared with control. The axons of diabetic neurons exhibited oxidative stress and depolarized mitochondria, an aberrant adaption to oligomycin-induced mitochondrial membrane hyperpolarization, but reduced levels of intramitochondrial superoxide compared with control. Abnormal mitochondrial function correlated with a downregulation of mitochondrial proteins, with components of the respiratory chain targeted in lumbar DRG in diabetes. The reduced activity of the respiratory chain was associated with diminished superoxide generation within the mitochondrial matrix and did not contribute to oxidative stress in axons of diabetic neurons. Alternative pathways involving polyol pathway activity appear to contribute to raised ROS in axons of diabetic neurons under high glucose concentration.

Proteotranscriptomic Profiling of 231-BR Breast Cancer Cells: Identification of Potential Biomarkers and Therapeutic Targets for Brain Metastasis*

PubMed Central

Dun, Matthew D.; Chalkley, Robert J.; Faulkner, Sam; Keene, Sheridan; Avery-Kiejda, Kelly A.; Scott, Rodney J.; Falkenby, Lasse G.; Cairns, Murray J.; Larsen, Martin R.; Bradshaw, Ralph A.; Hondermarck, Hubert

2015-01-01

Brain metastases are a devastating consequence of cancer and currently there are no specific biomarkers or therapeutic targets for risk prediction, diagnosis, and treatment. Here the proteome of the brain metastatic breast cancer cell line 231-BR has been compared with that of the parental cell line MDA-MB-231, which is also metastatic but has no organ selectivity. Using SILAC and nanoLC-MS/MS, 1957 proteins were identified in reciprocal labeling experiments and 1584 were quantified in the two cell lines. A total of 152 proteins were confidently determined to be up- or down-regulated by more than twofold in 231-BR. Of note, 112/152 proteins were decreased as compared with only 40/152 that were increased, suggesting that down-regulation of specific proteins is an important part of the mechanism underlying the ability of breast cancer cells to metastasize to the brain. When matched against transcriptomic data, 43% of individual protein changes were associated with corresponding changes in mRNA, indicating that the transcript level is a limited predictor of protein level. In addition, differential miRNA analyses showed that most miRNA changes in 231-BR were up- (36/45) as compared with down-regulations (9/45). Pathway analysis revealed that proteome changes were mostly related to cell signaling and cell cycle, metabolism and extracellular matrix remodeling. The major protein changes in 231-BR were confirmed by parallel reaction monitoring mass spectrometry and consisted in increases (by more than fivefold) in the matrix metalloproteinase-1, ephrin-B1, stomatin, myc target-1, and decreases (by more than 10-fold) in transglutaminase-2, the S100 calcium-binding protein A4, and l-plastin. The clinicopathological significance of these major proteomic changes to predict the occurrence of brain metastases, and their potential value as therapeutic targets, warrants further investigation. PMID:26041846

The mzqLibrary--An open source Java library supporting the HUPO-PSI quantitative proteomics standard.

PubMed

Qi, Da; Zhang, Huaizhong; Fan, Jun; Perkins, Simon; Pisconti, Addolorata; Simpson, Deborah M; Bessant, Conrad; Hubbard, Simon; Jones, Andrew R

2015-09-01

The mzQuantML standard has been developed by the Proteomics Standards Initiative for capturing, archiving and exchanging quantitative proteomic data, derived from mass spectrometry. It is a rich XML-based format, capable of representing data about two-dimensional features from LC-MS data, and peptides, proteins or groups of proteins that have been quantified from multiple samples. In this article we report the development of an open source Java-based library of routines for mzQuantML, called the mzqLibrary, and associated software for visualising data called the mzqViewer. The mzqLibrary contains routines for mapping (peptide) identifications on quantified features, inference of protein (group)-level quantification values from peptide-level values, normalisation and basic statistics for differential expression. These routines can be accessed via the command line, via a Java programming interface access or a basic graphical user interface. The mzqLibrary also contains several file format converters, including import converters (to mzQuantML) from OpenMS, Progenesis LC-MS and MaxQuant, and exporters (from mzQuantML) to other standards or useful formats (mzTab, HTML, csv). The mzqViewer contains in-built routines for viewing the tables of data (about features, peptides or proteins), and connects to the R statistical library for more advanced plotting options. The mzqLibrary and mzqViewer packages are available from https://code.google.com/p/mzq-lib/. © 2015 The Authors. PROTEOMICS Published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparative shotgun proteomics using spectral count data and quasi-likelihood modeling.

PubMed

Li, Ming; Gray, William; Zhang, Haixia; Chung, Christine H; Billheimer, Dean; Yarbrough, Wendell G; Liebler, Daniel C; Shyr, Yu; Slebos, Robbert J C

2010-08-06

Shotgun proteomics provides the most powerful analytical platform for global inventory of complex proteomes using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and allows a global analysis of protein changes. Nevertheless, sampling of complex proteomes by current shotgun proteomics platforms is incomplete, and this contributes to variability in assessment of peptide and protein inventories by spectral counting approaches. Thus, shotgun proteomics data pose challenges in comparing proteomes from different biological states. We developed an analysis strategy using quasi-likelihood Generalized Linear Modeling (GLM), included in a graphical interface software package (QuasiTel) that reads standard output from protein assemblies created by IDPicker, an HTML-based user interface to query shotgun proteomic data sets. This approach was compared to four other statistical analysis strategies: Student t test, Wilcoxon rank test, Fisher's Exact test, and Poisson-based GLM. We analyzed the performance of these tests to identify differences in protein levels based on spectral counts in a shotgun data set in which equimolar amounts of 48 human proteins were spiked at different levels into whole yeast lysates. Both GLM approaches and the Fisher Exact test performed adequately, each with their unique limitations. We subsequently compared the proteomes of normal tonsil epithelium and HNSCC using this approach and identified 86 proteins with differential spectral counts between normal tonsil epithelium and HNSCC. We selected 18 proteins from this comparison for verification of protein levels between the individual normal and tumor tissues using liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM-MS). This analysis confirmed the magnitude and direction of the protein expression differences in all 6 proteins for which reliable data could be obtained. Our analysis demonstrates that shotgun proteomic data sets from different tissue phenotypes are sufficiently rich in quantitative information and that statistically significant differences in proteins spectral counts reflect the underlying biology of the samples.

Comparative Shotgun Proteomics Using Spectral Count Data and Quasi-Likelihood Modeling

PubMed Central

2010-01-01

Shotgun proteomics provides the most powerful analytical platform for global inventory of complex proteomes using liquid chromatography−tandem mass spectrometry (LC−MS/MS) and allows a global analysis of protein changes. Nevertheless, sampling of complex proteomes by current shotgun proteomics platforms is incomplete, and this contributes to variability in assessment of peptide and protein inventories by spectral counting approaches. Thus, shotgun proteomics data pose challenges in comparing proteomes from different biological states. We developed an analysis strategy using quasi-likelihood Generalized Linear Modeling (GLM), included in a graphical interface software package (QuasiTel) that reads standard output from protein assemblies created by IDPicker, an HTML-based user interface to query shotgun proteomic data sets. This approach was compared to four other statistical analysis strategies: Student t test, Wilcoxon rank test, Fisher’s Exact test, and Poisson-based GLM. We analyzed the performance of these tests to identify differences in protein levels based on spectral counts in a shotgun data set in which equimolar amounts of 48 human proteins were spiked at different levels into whole yeast lysates. Both GLM approaches and the Fisher Exact test performed adequately, each with their unique limitations. We subsequently compared the proteomes of normal tonsil epithelium and HNSCC using this approach and identified 86 proteins with differential spectral counts between normal tonsil epithelium and HNSCC. We selected 18 proteins from this comparison for verification of protein levels between the individual normal and tumor tissues using liquid chromatography−multiple reaction monitoring mass spectrometry (LC−MRM-MS). This analysis confirmed the magnitude and direction of the protein expression differences in all 6 proteins for which reliable data could be obtained. Our analysis demonstrates that shotgun proteomic data sets from different tissue phenotypes are sufficiently rich in quantitative information and that statistically significant differences in proteins spectral counts reflect the underlying biology of the samples. PMID:20586475

Detergents: Friends not foes for high-performance membrane proteomics toward precision medicine.

PubMed

Zhang, Xi

2017-02-01

Precision medicine, particularly therapeutics, emphasizes the atomic-precise, dynamic, and systems visualization of human membrane proteins and their endogenous modifiers. For years, bottom-up proteomics has grappled with removing and avoiding detergents, yet faltered at the therapeutic-pivotal membrane proteins, which have been tackled by classical approaches and are known for decades refractory to single-phase aqueous or organic denaturants. Hydrophobicity and aggregation commonly challenge tissue and cell lysates, biofluids, and enriched samples. Frequently, expected membrane proteins and peptides are not identified by shotgun bottom-up proteomics, let alone robust quantitation. This review argues the cause of this proteomic crisis is not detergents per se, but the choice of detergents. Recently, inclusion of compatible detergents for membrane protein extraction and digestion has revealed stark improvements in both quantitative and structural proteomics. This review analyzes detergent properties behind recent proteomic advances, and proposes that rational use of detergents may reconcile outstanding membrane proteomics dilemmas, enabling ultradeep coverage and minimal artifacts for robust protein and endogenous PTM measurements. The simplicity of detergent tools confers bottom-up membrane proteomics the sophistication toward precision medicine. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Optimization of Statistical Methods Impact on Quantitative Proteomics Data.

PubMed

Pursiheimo, Anna; Vehmas, Anni P; Afzal, Saira; Suomi, Tomi; Chand, Thaman; Strauss, Leena; Poutanen, Matti; Rokka, Anne; Corthals, Garry L; Elo, Laura L

2015-10-02

As tools for quantitative label-free mass spectrometry (MS) rapidly develop, a consensus about the best practices is not apparent. In the work described here we compared popular statistical methods for detecting differential protein expression from quantitative MS data using both controlled experiments with known quantitative differences for specific proteins used as standards as well as "real" experiments where differences in protein abundance are not known a priori. Our results suggest that data-driven reproducibility-optimization can consistently produce reliable differential expression rankings for label-free proteome tools and are straightforward in their application.

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

Using Public Data for Comparative Proteome Analysis in Precision Medicine Programs.

PubMed

Hughes, Christopher S; Morin, Gregg B

2018-03-01

Maximizing the clinical utility of information obtained in longitudinal precision medicine programs would benefit from robust comparative analyses to known information to assess biological features of patient material toward identifying the underlying features driving their disease phenotype. Herein, the potential for utilizing publically deposited mass-spectrometry-based proteomics data to perform inter-study comparisons of cell-line or tumor-tissue materials is investigated. To investigate the robustness of comparison between MS-based proteomics studies carried out with different methodologies, deposited data representative of label-free (MS1) and isobaric tagging (MS2 and MS3 quantification) are utilized. In-depth quantitative proteomics data acquired from analysis of ovarian cancer cell lines revealed the robust recapitulation of observable gene expression dynamics between individual studies carried out using significantly different methodologies. The observed signatures enable robust inter-study clustering of cell line samples. In addition, the ability to classify and cluster tumor samples based on observed gene expression trends when using a single patient sample is established. With this analysis, relevant gene expression dynamics are obtained from a single patient tumor, in the context of a precision medicine analysis, by leveraging a large cohort of repository data as a comparator. Together, these data establish the potential for state-of-the-art MS-based proteomics data to serve as resources for robust comparative analyses in precision medicine applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Investigation of Pokemon-regulated proteins in hepatocellular carcinoma using mass spectrometry-based multiplex quantitative proteomics.

PubMed

Bi, Xin; Jin, Yibao; Gao, Xiang; Liu, Feng; Gao, Dan; Jiang, Yuyang; Liu, Hongxia

2013-01-01

Pokemon is a transcription regulator involved in embryonic development, cellular differentiation and oncogenesis. It is aberrantly overexpressed in multiple human cancers including Hepatocellular carcinoma (HCC) and is considered as a promising biomarker for HCC. In this work, the isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomics strategy was used to investigate the proteomic profile associated with Pokemon in human HCC cell line QGY7703 and human hepatocyte line HL7702. Samples were labeled with four-plex iTRAQ reagents followed by two-dimensional liquid chromatography coupled with tandem mass spectrometry analysis. A total of 24 differentially expressed proteins were selected as significant. Nine proteins were potentially up-regulated by Pokemon while 15 proteins were potentially down-regulated and many proteins were previously identified as potential biomarkers for HCC. Gene ontology (GO) term enrichment revealed that the listed proteins were mainly involved in DNA metabolism and biosynthesis process. The changes of glucose-6-phosphate 1-dehydrogenase (G6PD, up-regulated) and ribonucleoside-diphosphate reductase large sub-unit (RIM1, down-regulated) were validated by Western blotting analysis and denoted as Pokemon's function of oncogenesis. We also found that Pokemon potentially repressed the expression of highly clustered proteins (MCM3, MCM5, MCM6, MCM7) which played key roles in promoting DNA replication. Altogether, our results may help better understand the role of Pokemon in HCC and promote the clinical applications.

The Human Skeletal Muscle Proteome Project: a reappraisal of the current literature

PubMed Central

Gonzalez‐Freire, Marta; Semba, Richard D.; Ubaida‐Mohien, Ceereena; Fabbri, Elisa; Scalzo, Paul; Højlund, Kurt; Dufresne, Craig; Lyashkov, Alexey

2016-01-01

Abstract Skeletal muscle is a large organ that accounts for up to half the total mass of the human body. A progressive decline in muscle mass and strength occurs with ageing and in some individuals configures the syndrome of ‘sarcopenia’, a condition that impairs mobility, challenges autonomy, and is a risk factor for mortality. The mechanisms leading to sarcopenia as well as myopathies are still little understood. The Human Skeletal Muscle Proteome Project was initiated with the aim to characterize muscle proteins and how they change with ageing and disease. We conducted an extensive review of the literature and analysed publically available protein databases. A systematic search of peer‐reviewed studies was performed using PubMed. Search terms included ‘human’, ‘skeletal muscle’, ‘proteome’, ‘proteomic(s)’, and ‘mass spectrometry’, ‘liquid chromatography‐mass spectrometry (LC‐MS/MS)’. A catalogue of 5431 non‐redundant muscle proteins identified by mass spectrometry‐based proteomics from 38 peer‐reviewed scientific publications from 2002 to November 2015 was created. We also developed a nosology system for the classification of muscle proteins based on localization and function. Such inventory of proteins should serve as a useful background reference for future research on changes in muscle proteome assessed by quantitative mass spectrometry‐based proteomic approaches that occur with ageing and diseases. This classification and compilation of the human skeletal muscle proteome can be used for the identification and quantification of proteins in skeletal muscle to discover new mechanisms for sarcopenia and specific muscle diseases that can be targeted for the prevention and treatment. PMID:27897395

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.

ApoptoProteomics, an integrated database for analysis of proteomics data obtained from apoptotic cells.

PubMed

Arntzen, Magnus Ø; Thiede, Bernd

2012-02-01

Apoptosis is the most commonly described form of programmed cell death, and dysfunction is implicated in a large number of human diseases. Many quantitative proteome analyses of apoptosis have been performed to gain insight in proteins involved in the process. This resulted in large and complex data sets that are difficult to evaluate. Therefore, we developed the ApoptoProteomics database for storage, browsing, and analysis of the outcome of large scale proteome analyses of apoptosis derived from human, mouse, and rat. The proteomics data of 52 publications were integrated and unified with protein annotations from UniProt-KB, the caspase substrate database homepage (CASBAH), and gene ontology. Currently, more than 2300 records of more than 1500 unique proteins were included, covering a large proportion of the core signaling pathways of apoptosis. Analysis of the data set revealed a high level of agreement between the reported changes in directionality reported in proteomics studies and expected apoptosis-related function and may disclose proteins without a current recognized involvement in apoptosis based on gene ontology. Comparison between induction of apoptosis by the intrinsic and the extrinsic apoptotic signaling pathway revealed slight differences. Furthermore, proteomics has significantly contributed to the field of apoptosis in identifying hundreds of caspase substrates. The database is available at http://apoptoproteomics.uio.no.

ApoptoProteomics, an Integrated Database for Analysis of Proteomics Data Obtained from Apoptotic Cells*

PubMed Central

Arntzen, Magnus Ø.; Thiede, Bernd

2012-01-01

Apoptosis is the most commonly described form of programmed cell death, and dysfunction is implicated in a large number of human diseases. Many quantitative proteome analyses of apoptosis have been performed to gain insight in proteins involved in the process. This resulted in large and complex data sets that are difficult to evaluate. Therefore, we developed the ApoptoProteomics database for storage, browsing, and analysis of the outcome of large scale proteome analyses of apoptosis derived from human, mouse, and rat. The proteomics data of 52 publications were integrated and unified with protein annotations from UniProt-KB, the caspase substrate database homepage (CASBAH), and gene ontology. Currently, more than 2300 records of more than 1500 unique proteins were included, covering a large proportion of the core signaling pathways of apoptosis. Analysis of the data set revealed a high level of agreement between the reported changes in directionality reported in proteomics studies and expected apoptosis-related function and may disclose proteins without a current recognized involvement in apoptosis based on gene ontology. Comparison between induction of apoptosis by the intrinsic and the extrinsic apoptotic signaling pathway revealed slight differences. Furthermore, proteomics has significantly contributed to the field of apoptosis in identifying hundreds of caspase substrates. The database is available at http://apoptoproteomics.uio.no. PMID:22067098

iTRAQ-Based Quantitative Proteomics of Developing and Ripening Muscadine Grape Berry

PubMed Central

Kambiranda, Devaiah; Katam, Ramesh; Basha, Sheikh M.; Siebert, Shalom

2014-01-01

Grapes are among the widely cultivated fruit crops in the world. Grape berries like other nonclimacteric fruits undergo a complex set of dynamic, physical, physiological, and biochemical changes during ripening. Muscadine grapes are widely cultivated in the southern United States for fresh fruit and wine. To date, changes in the metabolites composition of muscadine grapes have been well documented; however, the molecular changes during berry development and ripening are not fully known. The aim of this study was to investigate changes in the berry proteome during ripening in muscadine grape cv. Noble. Isobaric tags for relative and absolute quantification (iTRAQ) MS/MS was used to detect statistically significant changes in the berry proteome. A total of 674 proteins were detected, and 76 were differentially expressed across four time points in muscadine berry. Proteins obtained were further analyzed to provide information about its potential functions during ripening. Several proteins involved in abiotic and biotic stimuli and sucrose and hexose metabolism were upregulated during berry ripening. Quantitative real-time PCR analysis validated the protein expression results for nine proteins. Identification of vicilin-like antimicrobial peptides indicates additional disease tolerance proteins are present in muscadines for berry protection during ripening. The results provide new information for characterization and understanding muscadine berry proteome and grape ripening. PMID:24251720

Quantitative Characterization of Major Hepatic UDP-Glucuronosyltransferase Enzymes in Human Liver Microsomes: Comparison of Two Proteomic Methods and Correlation with Catalytic Activity.

PubMed

Achour, Brahim; Dantonio, Alyssa; Niosi, Mark; Novak, Jonathan J; Fallon, John K; Barber, Jill; Smith, Philip C; Rostami-Hodjegan, Amin; Goosen, Theunis C

2017-10-01

Quantitative characterization of UDP-glucuronosyltransferase (UGT) enzymes is valuable in glucuronidation reaction phenotyping, predicting metabolic clearance and drug-drug interactions using extrapolation exercises based on pharmacokinetic modeling. Different quantitative proteomic workflows have been employed to quantify UGT enzymes in various systems, with reports indicating large variability in expression, which cannot be explained by interindividual variability alone. To evaluate the effect of methodological differences on end-point UGT abundance quantification, eight UGT enzymes were quantified in 24 matched liver microsomal samples by two laboratories using stable isotope-labeled (SIL) peptides or quantitative concatemer (QconCAT) standard, and measurements were assessed against catalytic activity in seven enzymes ( n = 59). There was little agreement between individual abundance levels reported by the two methods; only UGT1A1 showed strong correlation [Spearman rank order correlation (Rs) = 0.73, P < 0.0001; R 2 = 0.30; n = 24]. SIL-based abundance measurements correlated well with enzyme activities, with correlations ranging from moderate for UGTs 1A6, 1A9, and 2B15 (Rs = 0.52-0.59, P < 0.0001; R 2 = 0.34-0.58; n = 59) to strong correlations for UGTs 1A1, 1A3, 1A4, and 2B7 (Rs = 0.79-0.90, P < 0.0001; R 2 = 0.69-0.79). QconCAT-based data revealed generally poor correlation with activity, whereas moderate correlations were shown for UGTs 1A1, 1A3, and 2B7. Spurious abundance-activity correlations were identified in the cases of UGT1A4/2B4 and UGT2B7/2B15, which could be explained by correlations of protein expression between these enzymes. Consistent correlation of UGT abundance with catalytic activity, demonstrated by the SIL-based dataset, suggests that quantitative proteomic data should be validated against catalytic activity whenever possible. In addition, metabolic reaction phenotyping exercises should consider spurious abundance-activity correlations to avoid misleading conclusions. Copyright © 2017 by The American Society for Pharmacology and Experimental Therapeutics.

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

Highly Reproducible Label Free Quantitative Proteomic Analysis of RNA Polymerase Complexes*

PubMed Central

Mosley, Amber L.; Sardiu, Mihaela E.; Pattenden, Samantha G.; Workman, Jerry L.; Florens, Laurence; Washburn, Michael P.

2011-01-01

The use of quantitative proteomics methods to study protein complexes has the potential to provide in-depth information on the abundance of different protein components as well as their modification state in various cellular conditions. To interrogate protein complex quantitation using shotgun proteomic methods, we have focused on the analysis of protein complexes using label-free multidimensional protein identification technology and studied the reproducibility of biological replicates. For these studies, we focused on three highly related and essential multi-protein enzymes, RNA polymerase I, II, and III from Saccharomyces cerevisiae. We found that label-free quantitation using spectral counting is highly reproducible at the protein and peptide level when analyzing RNA polymerase I, II, and III. In addition, we show that peptide sampling does not follow a random sampling model, and we show the need for advanced computational models to predict peptide detection probabilities. In order to address these issues, we used the APEX protocol to model the expected peptide detectability based on whole cell lysate acquired using the same multidimensional protein identification technology analysis used for the protein complexes. Neither method was able to predict the peptide sampling levels that we observed using replicate multidimensional protein identification technology analyses. In addition to the analysis of the RNA polymerase complexes, our analysis provides quantitative information about several RNAP associated proteins including the RNAPII elongation factor complexes DSIF and TFIIF. Our data shows that DSIF and TFIIF are the most highly enriched RNAP accessory factors in Rpb3-TAP purifications and demonstrate our ability to measure low level associated protein abundance across biological replicates. In addition, our quantitative data supports a model in which DSIF and TFIIF interact with RNAPII in a dynamic fashion in agreement with previously published reports. PMID:21048197

Missing Value Monitoring Enhances the Robustness in Proteomics Quantitation.

PubMed

Matafora, Vittoria; Corno, Andrea; Ciliberto, Andrea; Bachi, Angela

2017-04-07

In global proteomic analysis, it is estimated that proteins span from millions to less than 100 copies per cell. The challenge of protein quantitation by classic shotgun proteomic techniques relies on the presence of missing values in peptides belonging to low-abundance proteins that lowers intraruns reproducibility affecting postdata statistical analysis. Here, we present a new analytical workflow MvM (missing value monitoring) able to recover quantitation of missing values generated by shotgun analysis. In particular, we used confident data-dependent acquisition (DDA) quantitation only for proteins measured in all the runs, while we filled the missing values with data-independent acquisition analysis using the library previously generated in DDA. We analyzed cell cycle regulated proteins, as they are low abundance proteins with highly dynamic expression levels. Indeed, we found that cell cycle related proteins are the major components of the missing values-rich proteome. Using the MvM workflow, we doubled the number of robustly quantified cell cycle related proteins, and we reduced the number of missing values achieving robust quantitation for proteins over ∼50 molecules per cell. MvM allows lower quantification variance among replicates for low abundance proteins with respect to DDA analysis, which demonstrates the potential of this novel workflow to measure low abundance, dynamically regulated proteins.

Improvement of Quantitative Measurements in Multiplex Proteomics Using High-Field Asymmetric Waveform Spectrometry.

PubMed

Pfammatter, Sibylle; Bonneil, Eric; Thibault, Pierre

2016-12-02

Quantitative proteomics using isobaric reagent tandem mass tags (TMT) or isobaric tags for relative and absolute quantitation (iTRAQ) provides a convenient approach to compare changes in protein abundance across multiple samples. However, the analysis of complex protein digests by isobaric labeling can be undermined by the relative large proportion of co-selected peptide ions that lead to distorted reporter ion ratios and affect the accuracy and precision of quantitative measurements. Here, we investigated the use of high-field asymmetric waveform ion mobility spectrometry (FAIMS) in proteomic experiments to reduce sample complexity and improve protein quantification using TMT isobaric labeling. LC-FAIMS-MS/MS analyses of human and yeast protein digests led to significant reductions in interfering ions, which increased the number of quantifiable peptides by up to 68% while significantly improving the accuracy of abundance measurements compared to that with conventional LC-MS/MS. The improvement in quantitative measurements using FAIMS is further demonstrated for the temporal profiling of protein abundance of HEK293 cells following heat shock treatment.

Design and analysis of quantitative differential proteomics investigations using LC-MS technology.

PubMed

Bukhman, Yury V; Dharsee, Moyez; Ewing, Rob; Chu, Peter; Topaloglou, Thodoros; Le Bihan, Thierry; Goh, Theo; Duewel, Henry; Stewart, Ian I; Wisniewski, Jacek R; Ng, Nancy F

2008-02-01

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics is becoming an increasingly important tool in characterizing the abundance of proteins in biological samples of various types and across conditions. Effects of disease or drug treatments on protein abundance are of particular interest for the characterization of biological processes and the identification of biomarkers. Although state-of-the-art instrumentation is available to make high-quality measurements and commercially available software is available to process the data, the complexity of the technology and data presents challenges for bioinformaticians and statisticians. Here, we describe a pipeline for the analysis of quantitative LC-MS data. Key components of this pipeline include experimental design (sample pooling, blocking, and randomization) as well as deconvolution and alignment of mass chromatograms to generate a matrix of molecular abundance profiles. An important challenge in LC-MS-based quantitation is to be able to accurately identify and assign abundance measurements to members of protein families. To address this issue, we implement a novel statistical method for inferring the relative abundance of related members of protein families from tryptic peptide intensities. This pipeline has been used to analyze quantitative LC-MS data from multiple biomarker discovery projects. We illustrate our pipeline here with examples from two of these studies, and show that the pipeline constitutes a complete workable framework for LC-MS-based differential quantitation. Supplementary material is available at http://iec01.mie.utoronto.ca/~thodoros/Bukhman/.

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

PubMed

Tu, Chengjian; Shen, Shichen; Sheng, Quanhu; Shyr, Yu; Qu, Jun

2017-01-30

Reliable quantification of low-abundance proteins in complex proteomes is challenging largely owing to the limited number of spectra/peptides identified. In this study we developed a straightforward method to improve the quantitative accuracy and precision of proteins by strategically retrieving the less confident peptides that were previously filtered out using the standard target-decoy search strategy. The filtered-out MS/MS spectra matched to confidently-identified proteins were recovered, and the peptide-spectrum-match FDR were re-calculated and controlled at a confident level of FDR≤1%, while protein FDR maintained at ~1%. We evaluated the performance of this strategy in both spectral count- and ion current-based methods. >60% increase of total quantified spectra/peptides was respectively achieved for analyzing a spike-in sample set and a public dataset from CPTAC. Incorporating the peptide retrieval strategy significantly improved the quantitative accuracy and precision, especially for low-abundance proteins (e.g. one-hit proteins). Moreover, the capacity of confidently discovering significantly-altered proteins was also enhanced substantially, as demonstrated with two spike-in datasets. In summary, improved quantitative performance was achieved by this peptide recovery strategy without compromising confidence of protein identification, which can be readily implemented in a broad range of quantitative proteomics techniques including label-free or labeling approaches. We hypothesize that more quantifiable spectra and peptides in a protein, even including less confident peptides, could help reduce variations and improve protein quantification. Hence the peptide retrieval strategy was developed and evaluated in two spike-in sample sets with different LC-MS/MS variations using both MS1- and MS2-based quantitative approach. The list of confidently identified proteins using the standard target-decoy search strategy was fixed and more spectra/peptides with less confidence matched to confident proteins were retrieved. However, the total peptide-spectrum-match false discovery rate (PSM FDR) after retrieval analysis was still controlled at a confident level of FDR≤1%. As expected, the penalty for occasionally incorporating incorrect peptide identifications is negligible by comparison with the improvements in quantitative performance. More quantifiable peptides, lower missing value rate, better quantitative accuracy and precision were significantly achieved for the same protein identifications by this simple strategy. This strategy is theoretically applicable for any quantitative approaches in proteomics and thereby provides more quantitative information, especially on low-abundance proteins. Published by Elsevier B.V.

Elevated host lipid metabolism revealed by iTRAQ-based quantitative proteomic analysis of cerebrospinal fluid of tuberculous meningitis patients.

PubMed

Mu, Jun; Yang, Yongtao; Chen, Jin; Cheng, Ke; Li, Qi; Wei, Yongdong; Zhu, Dan; Shao, Weihua; Zheng, Peng; Xie, Peng

2015-10-30

Tuberculous meningitis (TBM) remains to be one of the most deadly infectious diseases. The pathogen interacts with the host immune system, the process of which is largely unknown. Various cellular processes of Mycobacterium tuberculosis (MTB) centers around lipid metabolism. To determine the lipid metabolism related proteins, a quantitative proteomic study was performed here to identify differential proteins in the cerebrospinal fluid (CSF) obtained from TBM patients (n = 12) and healthy controls (n = 12). CSF samples were desalted, concentrated, labelled with isobaric tags for relative and absolute quantitation (iTRAQ™), and analyzed by multi-dimensional liquid chromatography-tandem mass spectrometry (LC-MS/MS). Gene ontology and proteomic phenotyping analysis of the differential proteins were conducted using Database for Annotation, Visualization, and Integrated Discovery (DAVID) Bioinformatics Resources. ApoE and ApoB were selected for validation by ELISA. Proteomic phenotyping of the 4 differential proteins was invloved in the lipid metabolism. ELISA showed significantly increased ApoB levels in TBM subjects compared to healthy controls. Area under the receiver operating characteristic curve analysis demonstrated ApoB levels could distinguish TBM subjects from healthy controls and viral meningitis subjects with 89.3% sensitivity and 92% specificity. CSF lipid metabolism disregulation, especially elevated expression of ApoB, gives insights into the pathogenesis of TBM. Further evaluation of these findings in larger studies including anti-tuberculosis medicated and unmedicated patient cohorts with other center nervous system infectious diseases is required for successful clinical translation. Copyright © 2015 Elsevier Inc. All rights reserved.

Ship diesel emission aerosols: A comprehensive study on the chemical composition, the physical properties and the molecular biological and toxicological effects on human lung cells of aerosols from a ship diesel engine operated with heavy or light diesel fuel oil

NASA Astrophysics Data System (ADS)

Zimmermann, R.; Buters, J.; Öder, S.; Dietmar, G.; Kanashova, T.; Paur, H.; Dilger, M.; Mülhopt, S.; Harndorf, H.; Stengel, B.; Rabe, R.; Hirvonen, M.; Jokiniemi, J.; Hiller, K.; Sapcariu, S.; Berube, K.; Sippula, O.; Streibel, T.; Karg, E.; Schnelle-Kreis, J.; Lintelmann, J.; Sklorz, M.; Arteaga Salas, M.; Orasche, J.; Müller, L.; Reda, A.; Passig, J.; Radischat, C.; Gröger, T.; Weiss, C.

2013-12-01

The Virtual Helmholtz Institute-HICE (www.hice-vi.eu) addresses chemical & physical properties, transformation processes and health effects of anthropogenic combustion emissions. This is performed by thorough comprehensive chemical and physical characterization of combustion aerosols (including application of advantageous on-line methods) and studying of biological effects on human lung cell-cultures. A new ALI air-liquid-interface (ALI) exposition system and a mobile S2-biological laboratory were developed for the HICE-measurements. Human alveolar basal epithelial cells (A549 etc.) are ALI-exposed to fresh, diluted (1:40-1:100) combustion aerosols and subsequently were toxicologically and molecular-biologically characterized (e.g. proteomics). By using stable isotope labeling technologies (13C-Glucose/metabolomics; 2H-Lysine/SILAC-proteomics), high sensitivity and accuracy for detection of molecular-biological effects is achievable even at sub-toxic effect dose levels. Aerosols from wood combustion and ship diesel engine (heavy/light fuel oil) have been investigated. The effect of wood combustion and ship diesel PM e.g. on the protein expression of ALI-exposed A549 cells was compared. Filtered aerosol is used as gas-reference for the isotope labeling based method (SILAC). Therefore the effects of wood combustion- and shipping diesel-PM can be directly compared. Ship diesel aerosol causes a broader distribution in the observed fold changes (log2), i.e. more proteins are significantly up-/down-regulated in case of shipping diesel PM-exposure. This corresponds to a stronger biological reaction if compared to wood combustion-PM exposure. The chemical analysis results on wood combustion- and ship diesel-PM depict more polycyclic aromatic hydrocarbons (PAH)/oxidized-PAH but less of some transition metals (V, Fe) in the wood combustion case. Interestingly, alkylated PAH are considerably more abundant in shipping PM, suggesting that PAH/Oxy-PAH may be less relevant for observed acute-toxic effects. The influence of transition metals and alkylated PAH is discussed in this context. Finally the differential biological effects of LFO- and HFO-ship emissions were investigated thoroughly. Here interesting observation were made. The chemical profile of the ship diesel engine operated with HFO and LFO is very different. Although the soot content of LFO exhaust is higher, the HFO-PM is showing considerably higher toxic- and biological-effects in the on-line cell exposure experiments. This higher particle toxicity is associated with larger aromatic structures and transition-metal contend in the PM. In addition to PM also the gas phase of the emission was investigated, e.g. by on-line photo ionization mass spectrometry and off-line techniques. Further results will be dis-cussed in the contribution. The massive differences of LFO and HFO emission are thoroughly discussed with respect to the chemical signature of gas and particulate phase. Furthermore concept and first results on a simulated aging are presented.

Quantitative proteomics reveals altered expression of extracellular matrix related proteins of human primary dermal fibroblasts in response to sulfated hyaluronan and collagen applied as artificial extracellular matrix.

PubMed

Müller, Stephan A; van der Smissen, Anja; von Feilitzsch, Margarete; Anderegg, Ulf; Kalkhof, Stefan; von Bergen, Martin

2012-12-01

Fibroblasts are the main matrix producing cells of the dermis and are also strongly regulated by their matrix environment which can be used to improve and guide skin wound healing processes. Here, we systematically investigated the molecular effects on primary dermal fibroblasts in response to high-sulfated hyaluronan [HA] (hsHA) by quantitative proteomics. The comparison of non- and high-sulfated HA revealed regulation of 84 of more than 1,200 quantified proteins. Based on gene enrichment we found that sulfation of HA alters extracellular matrix remodeling. The collagen degrading enzymes cathepsin K, matrix metalloproteinases-2 and -14 were found to be down-regulated on hsHA. Additionally protein expression of thrombospondin-1, decorin, collagen types I and XII were reduced, whereas the expression of trophoblast glycoprotein and collagen type VI were slightly increased. This study demonstrates that global proteomics provides a valuable tool for revealing proteins involved in molecular effects of growth substrates for further material optimization.

Quantitation of heat-shock proteins in clinical samples using mass spectrometry.

PubMed

Kaur, Punit; Asea, Alexzander

2011-01-01

Mass spectrometry (MS) is a powerful analytical tool for proteomics research and drug and biomarker discovery. MS enables identification and quantification of known and unknown compounds by revealing their structural and chemical properties. Proper sample preparation for MS-based analysis is a critical step in the proteomics workflow because the quality and reproducibility of sample extraction and preparation for downstream analysis significantly impact the separation and identification capabilities of mass spectrometers. The highly expressed proteins represent potential biomarkers that could aid in diagnosis, therapy, or drug development. Because the proteome is so complex, there is no one standard method for preparing protein samples for MS analysis. Protocols differ depending on the type of sample, source, experiment, and method of analysis. Molecular chaperones play significant roles in almost all biological functions due to their capacity for detecting intracellular denatured/unfolded proteins, initiating refolding or denaturation of such malfolded protein sequences and more recently for their role in the extracellular milieu as chaperokines. In this chapter, we describe the latest techniques for quantitating the expression of molecular chaperones in human clinical samples.

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

Insights from quantitative metaproteomics and protein-stable isotope probing into microbial ecology.

PubMed

von Bergen, Martin; Jehmlich, Nico; Taubert, Martin; Vogt, Carsten; Bastida, Felipe; Herbst, Florian-Alexander; Schmidt, Frank; Richnow, Hans-Hermann; Seifert, Jana

2013-10-01

The recent development of metaproteomics has enabled the direct identification and quantification of expressed proteins from microbial communities in situ, without the need for microbial enrichment. This became possible by (1) significant increases in quality and quantity of metagenome data and by improvements of (2) accuracy and (3) sensitivity of modern mass spectrometers (MS). The identification of physiologically relevant enzymes can help to understand the role of specific species within a community or an ecological niche. Beside identification, relative and absolute quantitation is also crucial. We will review label-free and label-based methods of quantitation in MS-based proteome analysis and the contribution of quantitative proteome data to microbial ecology. Additionally, approaches of protein-based stable isotope probing (protein-SIP) for deciphering community structures are reviewed. Information on the species-specific metabolic activity can be obtained when substrates or nutrients are labeled with stable isotopes in a protein-SIP approach. The stable isotopes ((13)C, (15)N, (36)S) are incorporated into proteins and the rate of incorporation can be used for assessing the metabolic activity of the corresponding species. We will focus on the relevance of the metabolic and phylogenetic information retrieved with protein-SIP studies and for detecting and quantifying the carbon flux within microbial consortia. Furthermore, the combination of protein-SIP with established tools in microbial ecology such as other stable isotope probing techniques are discussed.

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

PubMed

Zhang, Wei; Zhang, Jiyang; Xu, Changming; Li, Ning; Liu, Hui; Ma, Jie; Zhu, Yunping; Xie, Hongwei

2012-12-01

Database searching based methods for label-free quantification aim to reconstruct the peptide extracted ion chromatogram based on the identification information, which can limit the search space and thus make the data processing much faster. The random effect of the MS/MS sampling can be remedied by cross-assignment among different runs. Here, we present a new label-free fast quantitative analysis tool, LFQuant, for high-resolution LC-MS/MS proteomics data based on database searching. It is designed to accept raw data in two common formats (mzXML and Thermo RAW), and database search results from mainstream tools (MASCOT, SEQUEST, and X!Tandem), as input data. LFQuant can handle large-scale label-free data with fractionation such as SDS-PAGE and 2D LC. It is easy to use and provides handy user interfaces for data loading, parameter setting, quantitative analysis, and quantitative data visualization. LFQuant was compared with two common quantification software packages, MaxQuant and IDEAL-Q, on the replication data set and the UPS1 standard data set. The results show that LFQuant performs better than them in terms of both precision and accuracy, and consumes significantly less processing time. LFQuant is freely available under the GNU General Public License v3.0 at http://sourceforge.net/projects/lfquant/. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative analysis of cellular proteome alterations in human influenza A virus-infected mammalian cell lines.

PubMed

Vester, Diana; Rapp, Erdmann; Gade, Dörte; Genzel, Yvonne; Reichl, Udo

2009-06-01

Over the last years virus-host cell interactions were investigated in numerous studies. Viral strategies for evasion of innate immune response, inhibition of cellular protein synthesis and permission of viral RNA and protein production were disclosed. With quantitative proteome technology, comprehensive studies concerning the impact of viruses on the cellular machinery of their host cells at protein level are possible. Therefore, 2-D DIGE and nanoHPLC-nanoESI-MS/MS analysis were used to qualitatively and quantitatively determine the dynamic cellular proteome responses of two mammalian cell lines to human influenza A virus infection. A cell line used for vaccine production (MDCK) was compared with a human lung carcinoma cell line (A549) as a reference model. Analyzing 2-D gels of the proteomes of uninfected and influenza-infected host cells, 16 quantitatively altered protein spots (at least +/-1.7-fold change in relative abundance, p<0.001) were identified for both cell lines. Most significant changes were found for keratins, major components of the cytoskeleton system, and for Mx proteins, interferon-induced key components of the host cell defense. Time series analysis of infection processes allowed the identification of further proteins that are described to be involved in protein synthesis, signal transduction and apoptosis events. Most likely, these proteins are required for supporting functions during influenza viral life cycle or host cell stress response. Quantitative proteome-wide profiling of virus infection can provide insights into complexity and dynamics of virus-host cell interactions and may accelerate antiviral research and support optimization of vaccine manufacturing processes.

High-resolution proteomic profiling of spider venom: expanding the toxin diversity of Phoneutria nigriventer venom.

PubMed

Liberato, Tarcísio; Troncone, Lanfranco Ranieri Paolo; Yamashiro, Edson T; Serrano, Solange M T; Zelanis, André

2016-03-01

Here we present a proteomic characterization of Phoneutria nigriventer venom. A shotgun proteomic approach allowed the identification, for the first time, of O-glycosyl hydrolases (chitinases) in P. nigriventer venom. The electrophoretic profiles under nonreducing and reducing conditions, and protein identification by mass spectrometry, indicated the presence of oligomeric toxin structures in the venom. Complementary proteomic approaches allowed for a qualitative and semi-quantitative profiling of P. nigriventer venom complexity, expanding its known venom proteome diversity.

Generation of High-Quality SWATH® Acquisition Data for Label-free Quantitative Proteomics Studies Using TripleTOF® Mass Spectrometers

PubMed Central

Schilling, Birgit; Gibson, Bradford W.; Hunter, Christie L.

2017-01-01

Data-independent acquisition is a powerful mass spectrometry technique that enables comprehensive MS and MS/MS analysis of all detectable species, providing an information rich data file that can be mined deeply. Here, we describe how to acquire high-quality SWATH® Acquisition data to be used for large quantitative proteomic studies. We specifically focus on using variable sized Q1 windows for acquisition of MS/MS data for generating higher specificity quantitative data. PMID:28188533

Semi-quantitative proteomics of mammalian cells upon short-term exposure to non-ionizing electromagnetic fields.

PubMed

Kuzniar, Arnold; Laffeber, Charlie; Eppink, Berina; Bezstarosti, Karel; Dekkers, Dick; Woelders, Henri; Zwamborn, A Peter M; Demmers, Jeroen; Lebbink, Joyce H G; Kanaar, Roland

2017-01-01

The potential effects of non-ionizing electromagnetic fields (EMFs), such as those emitted by power-lines (in extremely low frequency range), mobile cellular systems and wireless networking devices (in radio frequency range) on human health have been intensively researched and debated. However, how exposure to these EMFs may lead to biological changes underlying possible health effects is still unclear. To reveal EMF-induced molecular changes, unbiased experiments (without a priori focusing on specific biological processes) with sensitive readouts are required. We present the first proteome-wide semi-quantitative mass spectrometry analysis of human fibroblasts, osteosarcomas and mouse embryonic stem cells exposed to three types of non-ionizing EMFs (ELF 50 Hz, UMTS 2.1 GHz and WiFi 5.8 GHz). We performed controlled in vitro EMF exposures of metabolically labeled mammalian cells followed by reliable statistical analyses of differential protein- and pathway-level regulations using an array of established bioinformatics methods. Our results indicate that less than 1% of the quantitated human or mouse proteome responds to the EMFs by small changes in protein abundance. Further network-based analysis of the differentially regulated proteins did not detect significantly perturbed cellular processes or pathways in human and mouse cells in response to ELF, UMTS or WiFi exposure. In conclusion, our extensive bioinformatics analyses of semi-quantitative mass spectrometry data do not support the notion that the short-time exposures to non-ionizing EMFs have a consistent biologically significant bearing on mammalian cells in culture.

Semi-quantitative proteomics of mammalian cells upon short-term exposure to non-ionizing electromagnetic fields

PubMed Central

Laffeber, Charlie; Eppink, Berina; Bezstarosti, Karel; Dekkers, Dick; Woelders, Henri; Zwamborn, A. Peter M.; Demmers, Jeroen; Lebbink, Joyce H. G.; Kanaar, Roland

2017-01-01

The potential effects of non-ionizing electromagnetic fields (EMFs), such as those emitted by power-lines (in extremely low frequency range), mobile cellular systems and wireless networking devices (in radio frequency range) on human health have been intensively researched and debated. However, how exposure to these EMFs may lead to biological changes underlying possible health effects is still unclear. To reveal EMF-induced molecular changes, unbiased experiments (without a priori focusing on specific biological processes) with sensitive readouts are required. We present the first proteome-wide semi-quantitative mass spectrometry analysis of human fibroblasts, osteosarcomas and mouse embryonic stem cells exposed to three types of non-ionizing EMFs (ELF 50 Hz, UMTS 2.1 GHz and WiFi 5.8 GHz). We performed controlled in vitro EMF exposures of metabolically labeled mammalian cells followed by reliable statistical analyses of differential protein- and pathway-level regulations using an array of established bioinformatics methods. Our results indicate that less than 1% of the quantitated human or mouse proteome responds to the EMFs by small changes in protein abundance. Further network-based analysis of the differentially regulated proteins did not detect significantly perturbed cellular processes or pathways in human and mouse cells in response to ELF, UMTS or WiFi exposure. In conclusion, our extensive bioinformatics analyses of semi-quantitative mass spectrometry data do not support the notion that the short-time exposures to non-ionizing EMFs have a consistent biologically significant bearing on mammalian cells in culture. PMID:28234898

Quantitative mass spectrometry of human reticulocytes reveal proteome-wide modifications during maturation.

PubMed

Chu, Trang T T; Sinha, Ameya; Malleret, Benoit; Suwanarusk, Rossarin; Park, Jung E; Naidu, Renugah; Das, Rupambika; Dutta, Bamaprasad; Ong, Seow Theng; Verma, Navin K; Chan, Jerry K; Nosten, François; Rénia, Laurent; Sze, Siu K; Russell, Bruce; Chandramohanadas, Rajesh

2018-01-01

Erythropoiesis is marked by progressive changes in morphological, biochemical and mechanical properties of erythroid precursors to generate red blood cells (RBC). The earliest enucleated forms derived in this process, known as reticulocytes, are multi-lobular and spherical. As reticulocytes mature, they undergo a series of dynamic cytoskeletal re-arrangements and the expulsion of residual organelles, resulting in highly deformable biconcave RBCs (normocytes). To understand the significant, yet neglected proteome-wide changes associated with reticulocyte maturation, we undertook a quantitative proteomics approach. Immature reticulocytes (marked by the presence of surface transferrin receptor, CD71) and mature RBCs (devoid of CD71) were isolated from human cord blood using a magnetic separation procedure. After sub-fractionation into triton-extracted membrane proteins and luminal samples (isobaric tags for relative and absolute quantitation), quantitative mass spectrometry was conducted to identify more than 1800 proteins with good confidence and coverage. While most structural proteins (such as Spectrins, Ankyrin and Band 3) as well as surface glycoproteins were conserved, proteins associated with microtubule structures, such as Talin-1/2 and ß-Tubulin, were detected only in immature reticulocytes. Atomic force microscopy (AFM)-based imaging revealed an extended network of spectrin filaments in reticulocytes (with an average length of 48 nm), which shortened during reticulocyte maturation (average spectrin length of 41 nm in normocytes). The extended nature of cytoskeletal network may partly account for increased deformability and shape changes, as reticulocytes transform to normocytes. © 2017 John Wiley & Sons Ltd.

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.

iTRAQ-based quantitative proteomics analysis of molecular mechanisms associated with Bombyx mori (Lepidoptera) larval midgut response to BmNPV in susceptible and near-isogenic strains.

PubMed

Yu, Haizhong; Wang, Xueyang; Xu, Jiaping; Ma, Yan; Zhang, Shangzhi; Yu, Dong; Fei, Dongqiong; Muhammad, Azharuddin

2017-08-08

Bombyx mori nucleopolyhedrovirus (BmNPV) has been identified as a major pathogen responsible for severe economic loss. Most silkworm strains are susceptible to BmNPV, with only a few highly resistant strains thus far identified. Here we investigated the molecular basis of silkworm resistance to BmNPV using susceptible (the recurrent parent P50) and resistant (near-isogenic line BC9) strains and a combination of iTRAQ-based quantitative proteomics, reverse-transcription quantitative PCR and Western blotting. By comparing the proteomes of infected and non-infected P50 and BC9 silkworms, we identified 793 differentially expressed proteins (DEPs). By gene ontology and KEGG enrichment analyses, we found that these DEPs are preferentially involved in metabolism, catalytic activity, amino sugar and nucleotide sugar metabolism and carbon metabolism. 114 (14.38%) DEPs were associated with the cytoskeleton, immune response, apoptosis, ubiquitination, translation, ion transport, endocytosis and endopeptidase activity. After removing the genetic background and individual immune stress response proteins, we identified 84 DEPs were found that are potentially involved in resistance to BmNPV. Further studies showed that a serine protease was down-regulated in P50 and up-regulated in BC9 after BmNPV infection. Taken together, these results provide insights into the molecular mechanism of silkworm response to BmNPV. Bombyx mori nucleopolyhedrovirus (BmNPV) is highly pathogenic, causing serious losses in sericulture every year. However, the molecular mechanisms of BmNPV infection and host defence remain unclear. Here we combined quantitative proteomic, bioinformatics, RT-qPCR and Western blotting analyses and found that BmNPV invasion causes complex protein alterations in the larval midgut, and that these changes are related to cytoskeleton, immune response, apoptosis, ubiquitination, translation, ion transport, endocytosis and endopeptidase activity. Five important differentially expression proteins were validation by independent approaches. These finding will help address the molecular mechanisms of silkworm resistance to BmNPV and provide a molecular target for resisting BmNPV. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantitative interaction proteomics using mass spectrometry.

PubMed

Wepf, Alexander; Glatter, Timo; Schmidt, Alexander; Aebersold, Ruedi; Gstaiger, Matthias

2009-03-01

We present a mass spectrometry-based strategy for the absolute quantification of protein complex components isolated through affinity purification. We quantified bait proteins via isotope-labeled reference peptides corresponding to an affinity tag sequence and prey proteins by label-free correlational quantification using the precursor ion signal intensities of proteotypic peptides generated in reciprocal purifications. We used this method to quantitatively analyze interaction stoichiometries in the human protein phosphatase 2A network.

An accurate proteomic quantification method: fluorescence labeling absolute quantification (FLAQ) using multidimensional liquid chromatography and tandem mass spectrometry.

PubMed

Liu, Junyan; Liu, Yang; Gao, Mingxia; Zhang, Xiangmin

2012-08-01

A facile proteomic quantification method, fluorescent labeling absolute quantification (FLAQ), was developed. Instead of using MS for quantification, the FLAQ method is a chromatography-based quantification in combination with MS for identification. Multidimensional liquid chromatography (MDLC) with laser-induced fluorescence (LIF) detection with high accuracy and tandem MS system were employed for FLAQ. Several requirements should be met for fluorescent labeling in MS identification: Labeling completeness, minimum side-reactions, simple MS spectra, and no extra tandem MS fragmentations for structure elucidations. A fluorescence dye, 5-iodoacetamidofluorescein, was finally chosen to label proteins on all cysteine residues. The fluorescent dye was compatible with the process of the trypsin digestion and MALDI MS identification. Quantitative labeling was achieved with optimization of reacting conditions. A synthesized peptide and model proteins, BSA (35 cysteines), OVA (five cysteines), were used for verifying the completeness of labeling. Proteins were separated through MDLC and quantified based on fluorescent intensities, followed by MS identification. High accuracy (RSD% < 1.58) and wide linearity of quantification (1-10(5) ) were achieved by LIF detection. The limit of quantitation for the model protein was as low as 0.34 amol. Parts of proteins in human liver proteome were quantified and demonstrated using FLAQ. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dynamics of plasma proteome during leptin-replacement therapy in genetically based leptin deficiency.

PubMed

Andreev, V P; Dwivedi, R C; Paz-Filho, G; Krokhin, O V; Wong, M-L; Wilkins, J A; Licinio, J

2011-06-01

The effects of leptin-replacement therapy on the plasma proteome of three unique adults with genetically based leptin deficiency were studied longitudinally during the course of recombinant human leptin-replacement treatment. Quantitative proteomics analysis was performed in plasma samples collected during four stages: before leptin treatment was initiated, after 1.5 and 6 years of leptin-replacement treatment, and after 7 weeks of temporary interruption of leptin-replacement therapy. Of 500 proteins reliably identified and quantitated in those four stages, about 100 were differentially abundant twofold or more in one or more stages. Synchronous dynamics of abundances of about 90 proteins was observed reflecting both short- and long-term effects of leptin-replacement therapy. Pathways and processes enriched with overabundant synchronous proteins were cell adhesion, cytoskeleton remodeling, cell cycle, blood coagulation, glycolysis, and gluconeogenesis. Plausible common regulators of the above synchronous proteins were identified using transcription regulation network analysis. The generated network included two transcription factors (c-Myc and androgen receptor) that are known to activate each other through a double-positive feedback loop, which may represent a potential molecular mechanism for the long-term effects of leptin-replacement therapy. Our findings may help to elucidate the effects of leptin on insulin resistance.

AUTOMATED ANALYSIS OF QUANTITATIVE IMAGE DATA USING ISOMORPHIC FUNCTIONAL MIXED MODELS, WITH APPLICATION TO PROTEOMICS DATA.

PubMed

Morris, Jeffrey S; Baladandayuthapani, Veerabhadran; Herrick, Richard C; Sanna, Pietro; Gutstein, Howard

2011-01-01

Image data are increasingly encountered and are of growing importance in many areas of science. Much of these data are quantitative image data, which are characterized by intensities that represent some measurement of interest in the scanned images. The data typically consist of multiple images on the same domain and the goal of the research is to combine the quantitative information across images to make inference about populations or interventions. In this paper, we present a unified analysis framework for the analysis of quantitative image data using a Bayesian functional mixed model approach. This framework is flexible enough to handle complex, irregular images with many local features, and can model the simultaneous effects of multiple factors on the image intensities and account for the correlation between images induced by the design. We introduce a general isomorphic modeling approach to fitting the functional mixed model, of which the wavelet-based functional mixed model is one special case. With suitable modeling choices, this approach leads to efficient calculations and can result in flexible modeling and adaptive smoothing of the salient features in the data. The proposed method has the following advantages: it can be run automatically, it produces inferential plots indicating which regions of the image are associated with each factor, it simultaneously considers the practical and statistical significance of findings, and it controls the false discovery rate. Although the method we present is general and can be applied to quantitative image data from any application, in this paper we focus on image-based proteomic data. We apply our method to an animal study investigating the effects of opiate addiction on the brain proteome. Our image-based functional mixed model approach finds results that are missed with conventional spot-based analysis approaches. In particular, we find that the significant regions of the image identified by the proposed method frequently correspond to subregions of visible spots that may represent post-translational modifications or co-migrating proteins that cannot be visually resolved from adjacent, more abundant proteins on the gel image. Thus, it is possible that this image-based approach may actually improve the realized resolution of the gel, revealing differentially expressed proteins that would not have even been detected as spots by modern spot-based analyses.

Analytical performance of reciprocal isotope labeling of proteome digests for quantitative proteomics and its application for comparative studies of aerobic and anaerobic Escherichia coli proteomes.

PubMed

Lo, Andy; Weiner, Joel H; Li, Liang

2013-09-17

Due to limited sample amounts, instrument time considerations, and reagent costs, only a small number of replicate experiments are typically performed for quantitative proteome analyses. Generation of reproducible data that can be readily assessed for consistency within a small number of datasets is critical for accurate quantification. We report our investigation of a strategy using reciprocal isotope labeling of two comparative samples as a tool for determining proteome changes. Reciprocal labeling was evaluated to determine the internal consistency of quantified proteome changes from Escherichia coli grown under aerobic and anaerobic conditions. Qualitatively, the peptide overlap between replicate analyses of the same sample and reverse labeled samples were found to be within 8%. Quantitatively, reciprocal analyses showed only a slight increase in average overall inconsistency when compared with replicate analyses (1.29 vs. 1.24-fold difference). Most importantly, reverse labeling was successfully used to identify spurious values resulting from incorrect peptide identifications and poor peak fitting. After removal of 5% of the peptide data with low reproducibility, a total of 275 differentially expressed proteins (>1.50-fold difference) were consistently identified and were then subjected to bioinformatics analysis. General considerations and guidelines for reciprocal labeling experimental design and biological significance of obtained results are discussed. Copyright © 2013 Elsevier B.V. All rights reserved.

Comparative analysis of cerebrospinal fluid from the meningo-encephalitic stage of T. b. gambiense and rhodesiense sleeping sickness patients using TMT quantitative proteomics.

PubMed

Tiberti, Natalia; Sanchez, Jean-Charles

2015-09-01

The quantitative proteomics data here reported are part of a research article entitled "Increased acute immune response during the meningo-encephalitic stage of Trypanosoma brucei rhodesiense sleeping sickness compared to Trypanosoma brucei gambiense", published by Tiberti et al., 2015. Transl. Proteomics 6, 1-9. Sleeping sickness (human African trypanosomiasis - HAT) is a deadly neglected tropical disease affecting mainly rural communities in sub-Saharan Africa. This parasitic disease is caused by the Trypanosoma brucei (T. b.) parasite, which is transmitted to the human host through the bite of the tse-tse fly. Two parasite sub-species, T. b. rhodesiense and T. b. gambiense, are responsible for two clinically different and geographically separated forms of sleeping sickness. The objective of the present study was to characterise and compare the cerebrospinal fluid (CSF) proteome of stage 2 (meningo-encephalitic stage) HAT patients suffering from T. b. gambiense or T. b. rhodesiense disease using high-throughput quantitative proteomics and the Tandem Mass Tag (TMT(®)) isobaric labelling. In order to evaluate the CSF proteome in the context of HAT pathophysiology, the protein dataset was then submitted to gene ontology and pathway analysis. Two significantly differentially expressed proteins (C-reactive protein and orosomucoid 1) were further verified on a larger population of patients (n=185) by ELISA, confirming the mass spectrometry results. By showing a predominant involvement of the acute immune response in rhodesiense HAT, the proteomics results obtained in this work will contribute to further understand the mechanisms of pathology occurring in HAT and to propose new biomarkers of potential clinical utility. The mass spectrometry raw data are available in the Pride Archive via ProteomeXchange through the identifier PXD001082.

Data Independent Acquisition analysis in ProHits 4.0.

PubMed

Liu, Guomin; Knight, James D R; Zhang, Jian Ping; Tsou, Chih-Chiang; Wang, Jian; Lambert, Jean-Philippe; Larsen, Brett; Tyers, Mike; Raught, Brian; Bandeira, Nuno; Nesvizhskii, Alexey I; Choi, Hyungwon; Gingras, Anne-Claude

2016-10-21

Affinity purification coupled with mass spectrometry (AP-MS) is a powerful technique for the identification and quantification of physical interactions. AP-MS requires careful experimental design, appropriate control selection and quantitative workflows to successfully identify bona fide interactors amongst a large background of contaminants. We previously introduced ProHits, a Laboratory Information Management System for interaction proteomics, which tracks all samples in a mass spectrometry facility, initiates database searches and provides visualization tools for spectral counting-based AP-MS approaches. More recently, we implemented Significance Analysis of INTeractome (SAINT) within ProHits to provide scoring of interactions based on spectral counts. Here, we provide an update to ProHits to support Data Independent Acquisition (DIA) with identification software (DIA-Umpire and MSPLIT-DIA), quantification tools (through DIA-Umpire, or externally via targeted extraction), and assessment of quantitative enrichment (through mapDIA) and scoring of interactions (through SAINT-intensity). With additional improvements, notably support of the iProphet pipeline, facilitated deposition into ProteomeXchange repositories and enhanced export and viewing functions, ProHits 4.0 offers a comprehensive suite of tools to facilitate affinity proteomics studies. It remains challenging to score, annotate and analyze proteomics data in a transparent manner. ProHits was previously introduced as a LIMS to enable storing, tracking and analysis of standard AP-MS data. In this revised version, we expand ProHits to include integration with a number of identification and quantification tools based on Data-Independent Acquisition (DIA). ProHits 4.0 also facilitates data deposition into public repositories, and the transfer of data to new visualization tools. Copyright © 2016 Elsevier B.V. All rights reserved.

Quantitative Clinical Chemistry Proteomics (qCCP) using mass spectrometry: general characteristics and application.

PubMed

Lehmann, Sylvain; Hoofnagle, Andrew; Hochstrasser, Denis; Brede, Cato; Glueckmann, Matthias; Cocho, José A; Ceglarek, Uta; Lenz, Christof; Vialaret, Jérôme; Scherl, Alexander; Hirtz, Christophe

2013-05-01

Proteomics studies typically aim to exhaustively detect peptides/proteins in a given biological sample. Over the past decade, the number of publications using proteomics methodologies has exploded. This was made possible due to the availability of high-quality genomic data and many technological advances in the fields of microfluidics and mass spectrometry. Proteomics in biomedical research was initially used in 'functional' studies for the identification of proteins involved in pathophysiological processes, complexes and networks. Improved sensitivity of instrumentation facilitated the analysis of even more complex sample types, including human biological fluids. It is at that point the field of clinical proteomics was born, and its fundamental aim was the discovery and (ideally) validation of biomarkers for the diagnosis, prognosis, or therapeutic monitoring of disease. Eventually, it was recognized that the technologies used in clinical proteomics studies [particularly liquid chromatography-tandem mass spectrometry (LC-MS/MS)] could represent an alternative to classical immunochemical assays. Prior to deploying MS in the measurement of peptides/proteins in the clinical laboratory, it seems likely that traditional proteomics workflows and data management systems will need to adapt to the clinical environment and meet in vitro diagnostic (IVD) regulatory constraints. This defines a new field, as reviewed in this article, that we have termed quantitative Clinical Chemistry Proteomics (qCCP).

A New Algorithm Using Cross-Assignment for Label-Free Quantitation with LC/LTQ-FT MS

PubMed Central

Andreev, Victor P.; Li, Lingyun; Cao, Lei; Gu, Ye; Rejtar, Tomas; Wu, Shiaw-Lin; Karger, Barry L.

2008-01-01

A new algorithm is described for label-free quantitation of relative protein abundances across multiple complex proteomic samples. Q-MEND is based on the denoising and peak picking algorithm, MEND, previously developed in our laboratory. Q-MEND takes advantage of the high resolution and mass accuracy of the hybrid LTQFT MS mass spectrometer (or other high resolution mass spectrometers, such as a Q-TOF MS). The strategy, termed “cross-assignment”, is introduced to increase substantially the number of quantitated proteins. In this approach, all MS/MS identifications for the set of analyzed samples are combined into a master ID list, and then each LC/MS run is searched for the features that can be assigned to a specific identification from that master list. The reliability of quantitation is enhanced by quantitating separately all peptide charge states, along with a scoring procedure to filter out less reliable peptide abundance measurements. The effectiveness of Q-MEND is illustrated in the relative quantitative analysis of E.coli samples spiked with known amounts of non-E.coli protein digests. A mean quantitation accuracy of 7% and mean precision of 15% is demonstrated. Q-MEND can perform relative quantitation of a set of LC/MS datasets without manual intervention and can generate files compatible with the Guidelines for Proteomic Data Publication. PMID:17441747

A new algorithm using cross-assignment for label-free quantitation with LC-LTQ-FT MS.

PubMed

Andreev, Victor P; Li, Lingyun; Cao, Lei; Gu, Ye; Rejtar, Tomas; Wu, Shiaw-Lin; Karger, Barry L

2007-06-01

A new algorithm is described for label-free quantitation of relative protein abundances across multiple complex proteomic samples. Q-MEND is based on the denoising and peak picking algorithm, MEND, previously developed in our laboratory. Q-MEND takes advantage of the high resolution and mass accuracy of the hybrid LTQ-FT MS mass spectrometer (or other high-resolution mass spectrometers, such as a Q-TOF MS). The strategy, termed "cross-assignment", is introduced to increase substantially the number of quantitated proteins. In this approach, all MS/MS identifications for the set of analyzed samples are combined into a master ID list, and then each LC-MS run is searched for the features that can be assigned to a specific identification from that master list. The reliability of quantitation is enhanced by quantitating separately all peptide charge states, along with a scoring procedure to filter out less reliable peptide abundance measurements. The effectiveness of Q-MEND is illustrated in the relative quantitative analysis of Escherichia coli samples spiked with known amounts of non-E. coli protein digests. A mean quantitation accuracy of 7% and mean precision of 15% is demonstrated. Q-MEND can perform relative quantitation of a set of LC-MS data sets without manual intervention and can generate files compatible with the Guidelines for Proteomic Data Publication.

Quantitative proteomics reveals the central changes of wheat in response to powdery mildew.

PubMed

Fu, Ying; Zhang, Hong; Mandal, Siddikun Nabi; Wang, Changyou; Chen, Chunhuan; Ji, Wanquan

2016-01-01

Powdery mildew (Pm), caused by Blumeria graminis f. sp. tritici (Bgt), is one of the most important crop diseases, causing severe economic losses to wheat production worldwide. However, there are few reports about the proteomic response to Bgt infection in resistant wheat. Hence, quantitative proteomic analysis of N9134, a resistant wheat line, was performed to explore the molecular mechanism of wheat in defense against Bgt. Comparing the leaf proteins of Bgt-inoculated N9134 with that of mock-inoculated controls, a total of 2182 protein-species were quantified by iTRAQ at 24, 48 and 72h postinoculation (hpi) with Bgt, of which 394 showed differential accumulation. These differentially accumulated protein-species (DAPs) mainly included pathogenesis-related (PR) polypeptides, oxidative stress responsive proteins and components involved in primary metabolic pathways. KEGG enrichment analysis showed that phenylpropanoid biosynthesis, phenylalanine metabolism and photosynthesis-antenna proteins were the key pathways in response to Bgt infection. InterProScan 5 and the Gibbs Motif Sampler cluster 394 DAPs into eight conserved motifs, which shared leucine repeats and histidine sites in the sequence motifs. Moreover, eight separate protein-protein interaction (PPI) networks were predicted from STRING database. This study provides a powerful platform for further exploration of the molecular mechanism underlying resistant wheat responding to Bgt. Powdery mildew, caused by Blumeria graminis f. sp. tritici (Bgt), is a destructive pathogenic disease in wheat-producing regions worldwide, resulting in severe yield reductions. Although many resistant wheat varieties have been cultivated, there are few reports about the proteomic response to Bgt infection in resistant wheat. Therefore, an iTRAQ-based quantitative proteomic analysis of a resistant wheat line (N9134) in response to Bgt infection has been performed. This paper provides new insights into the underlying molecular mechanism of wheat in response to Bgt. The proteomic analysis can significantly narrow the field of potential defense-related protein-species, and is conducive to recognize the critical or effector protein under Bgt infection more precisely. Taken together, large amounts of high-throughput data provide a powerful platform for further exploration of the molecular mechanism on wheat-Bgt interactions. Copyright © 2015 Elsevier B.V. All rights reserved.

Overgrazing induces alterations in the hepatic proteome of sheep (Ovis aries): an iTRAQ-based quantitative proteomic analysis.

PubMed

Ren, Weibo; Hou, Xiangyang; Wang, Yuqing; Badgery, Warwick; Li, Xiliang; Ding, Yong; Guo, Huiqin; Wu, Zinian; Hu, Ningning; Kong, Lingqi; Chang, Chun; Jiang, Chao; Zhang, Jize

2016-01-01

The degradation of the steppe of Inner Mongolia, due to overgrazing, has resulted in ecosystem damage as well as extensive reductions in sheep production. The growth performance of sheep is greatly reduced because of overgrazing, which triggers massive economic losses every year. The liver is an essential organ that has very important roles in multiple functions, such as nutrient metabolism, immunity and others, which are closely related to animal growth. However, to our knowledge, no detailed studies have evaluated hepatic metabolism adaption in sheep due to overgrazing. The molecular mechanisms that underlie these effects remain unclear. In the present study, our group applied isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomic analysis to investigate changes in the protein profiles of sheep hepatic tissues when nutrition was reduced due to overgrazing (12.0 sheep/ha), with the goal of characterizing the molecular mechanisms of hepatic metabolism adaption in sheep in an overgrazing condition. The body weight daily gain of sheep was greatly decreased due to overgrazing. Overall, 41 proteins were found to be differentially abundant in the hepatic tissue between a light grazing group and an overgrazing group. Most of the differentially expressed proteins identified are involved in protein metabolism, transcriptional and translational regulation, and immune response. In particular, the altered abundance of kynureninase (KYNU) and HAL (histidine ammonia-lyase) involved in protein metabolic function, integrated with the changes of serum levels of blood urea nitrogen (BUN) and glucose (GLU), suggest that overgrazing triggers a shift in energy resources from carbohydrates to proteins, causing poorer nitrogen utilization efficiency. Altogether, these results suggest that the reductions in animal growth induced by overgrazing are associated with liver proteomic changes, especially the proteins involved in nitrogen compounds metabolism and immunity. This provides new information that can be used for nutritional supplementation to improve the growth performance of sheep in an overgrazing condition.

Cell death proteomics database: consolidating proteomics data on cell death.

PubMed

Arntzen, Magnus Ø; Bull, Vibeke H; Thiede, Bernd

2013-05-03

Programmed cell death is a ubiquitous process of utmost importance for the development and maintenance of multicellular organisms. More than 10 different types of programmed cell death forms have been discovered. Several proteomics analyses have been performed to gain insight in proteins involved in the different forms of programmed cell death. To consolidate these studies, we have developed the cell death proteomics (CDP) database, which comprehends data from apoptosis, autophagy, cytotoxic granule-mediated cell death, excitotoxicity, mitotic catastrophe, paraptosis, pyroptosis, and Wallerian degeneration. The CDP database is available as a web-based database to compare protein identifications and quantitative information across different experimental setups. The proteomics data of 73 publications were integrated and unified with protein annotations from UniProt-KB and gene ontology (GO). Currently, more than 6,500 records of more than 3,700 proteins are included in the CDP. Comparing apoptosis and autophagy using overrepresentation analysis of GO terms, the majority of enriched processes were found in both, but also some clear differences were perceived. Furthermore, the analysis revealed differences and similarities of the proteome between autophagosomal and overall autophagy. The CDP database represents a useful tool to consolidate data from proteome analyses of programmed cell death and is available at http://celldeathproteomics.uio.no.

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.

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

ProteoSign: an end-user online differential proteomics statistical analysis platform.

PubMed

Efstathiou, Georgios; Antonakis, Andreas N; Pavlopoulos, Georgios A; Theodosiou, Theodosios; Divanach, Peter; Trudgian, David C; Thomas, Benjamin; Papanikolaou, Nikolas; Aivaliotis, Michalis; Acuto, Oreste; Iliopoulos, Ioannis

2017-07-03

Profiling of proteome dynamics is crucial for understanding cellular behavior in response to intrinsic and extrinsic stimuli and maintenance of homeostasis. Over the last 20 years, mass spectrometry (MS) has emerged as the most powerful tool for large-scale identification and characterization of proteins. Bottom-up proteomics, the most common MS-based proteomics approach, has always been challenging in terms of data management, processing, analysis and visualization, with modern instruments capable of producing several gigabytes of data out of a single experiment. Here, we present ProteoSign, a freely available web application, dedicated in allowing users to perform proteomics differential expression/abundance analysis in a user-friendly and self-explanatory way. Although several non-commercial standalone tools have been developed for post-quantification statistical analysis of proteomics data, most of them are not end-user appealing as they often require very stringent installation of programming environments, third-party software packages and sometimes further scripting or computer programming. To avoid this bottleneck, we have developed a user-friendly software platform accessible via a web interface in order to enable proteomics laboratories and core facilities to statistically analyse quantitative proteomics data sets in a resource-efficient manner. ProteoSign is available at http://bioinformatics.med.uoc.gr/ProteoSign and the source code at https://github.com/yorgodillo/ProteoSign. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Less label, more free: approaches in label-free quantitative mass spectrometry.

PubMed

Neilson, Karlie A; Ali, Naveid A; Muralidharan, Sridevi; Mirzaei, Mehdi; Mariani, Michael; Assadourian, Gariné; Lee, Albert; van Sluyter, Steven C; Haynes, Paul A

2011-02-01

In this review we examine techniques, software, and statistical analyses used in label-free quantitative proteomics studies for area under the curve and spectral counting approaches. Recent advances in the field are discussed in an order that reflects a logical workflow design. Examples of studies that follow this design are presented to highlight the requirement for statistical assessment and further experiments to validate results from label-free quantitation. Limitations of label-free approaches are considered, label-free approaches are compared with labelling techniques, and forward-looking applications for label-free quantitative data are presented. We conclude that label-free quantitative proteomics is a reliable, versatile, and cost-effective alternative to labelled quantitation. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Toxic responses of Perna viridis hepatopancreas exposed to DDT, benzo(a)pyrene and their mixture uncovered by iTRAQ-based proteomics and NMR-based metabolomics.

PubMed

Song, Qinqin; Zhou, Hailong; Han, Qian; Diao, Xiaoping

2017-11-01

Dichlorodiphenyltrichloroethane (DDT) and benzo(a)pyrene (BaP) are environmental estrogens (EEs) that are ubiquitous in the marine environment. In the present study, we integrated isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomic and nuclear magnetic resonance (NMR)-based metabolomic approaches to explore the toxic responses of green mussel hepatopancreas exposed to DDT (10μg/L), BaP (10μg/L) and their mixture. The metabolic responses indicated that BaP primarily disturbed energy metabolism and osmotic regulation in the hepatopancreas of the male green mussel P. viridis. Both DDT and the mixture of DDT and BaP perturbed the energy metabolism and osmotic regulation in P. viridis. The proteomic responses revealed that BaP affected the proteins involved in energy metabolism, material transformation, cytoskeleton, stress responses, reproduction and development in green mussels. DDT exposure could change the proteins involved in primary metabolism, stress responses, cytoskeleton and signal transduction. However, the mixture of DDT and BaP altered proteins associated with material and energy metabolism, stress responses, signal transduction, reproduction and development, cytoskeleton and apoptosis. This study showed that iTRAQ-based proteomic and NMR-based metabolomic approaches could effectively elucidate the essential molecular mechanism of disturbances in hepatopancreas function of green mussels exposed to environmental estrogens. Copyright © 2017 Elsevier B.V. All rights reserved.

High Concentrations of Atmospheric Ammonia Induce Alterations in the Hepatic Proteome of Broilers (Gallus gallus): An iTRAQ-Based Quantitative Proteomic Analysis

PubMed Central

Zhang, Jize; Li, Cong; Tang, Xiangfang; Lu, Qingping; Sa, Renna; Zhang, Hongfu

2015-01-01

With the development of the poultry industry, ammonia, as a main contaminant in the air, is causing increasing problems with broiler health. To date, most studies of ammonia toxicity have focused on the nervous system and the gastrointestinal tract in mammals. However, few detailed studies have been conducted on the hepatic response to ammonia toxicity in poultry. The molecular mechanisms that underlie these effects remain unclear. In the present study, our group applied isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomic analysis to investigate changes in the protein profile change in hepatic tissue of broilers exposed to high concentrations of atmospheric ammonia, with the goal of characterizing the molecular mechanisms of chronic liver injury from exposure to high ambient levels of ammonia. Overall, 30 differentially expressed proteins that are involved in nutrient metabolism (energy, lipid, and amino acid), immune response, transcriptional and translational regulation, stress response, and detoxification were identified. In particular, two of these proteins, beta-1 galactosidase (GLB1) and a kinase (PRKA) anchor protein 8-like (AKAP8 L), were previously suggested to be potential biomarkers of chronic liver injury. In addition to the changes in the protein profile, serum parameters and histochemical analyses of hepatic tissue also showed extensive hepatic damage in ammonia-exposed broilers. Altogether, these findings suggest that longtime exposure to high concentrations of atmospheric ammonia can trigger chronic hepatic injury in broilers via different mechanisms, providing new information that can be used for intervention using nutritional strategies in the future. PMID:25901992

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.

Compartment-resolved Proteomic Analysis of Mouse Aorta during Atherosclerotic Plaque Formation Reveals Osteoclast-specific Protein Expression.

PubMed

Wierer, Michael; Prestel, Matthias; Schiller, Herbert B; Yan, Guangyao; Schaab, Christoph; Azghandi, Sepiede; Werner, Julia; Kessler, Thorsten; Malik, Rainer; Murgia, Marta; Aherrahrou, Zouhair; Schunkert, Heribert; Dichgans, Martin; Mann, Matthias

2018-02-01

Atherosclerosis leads to vascular lesions that involve major rearrangements of the vascular proteome, especially of the extracellular matrix (ECM). Using single aortas from ApoE knock out mice, we quantified formation of plaques by single-run, high-resolution mass spectrometry (MS)-based proteomics. To probe localization on a proteome-wide scale we employed quantitative detergent solubility profiling. This compartment- and time-resolved resource of atherogenesis comprised 5117 proteins, 182 of which changed their expression status in response to vessel maturation and atherosclerotic plaque development. In the insoluble ECM proteome, 65 proteins significantly changed, including relevant collagens, matrix metalloproteinases and macrophage derived proteins. Among novel factors in atherosclerosis, we identified matrilin-2, the collagen IV crosslinking enzyme peroxidasin as well as the poorly characterized MAM-domain containing 2 (Mamdc2) protein as being up-regulated in the ECM during atherogenesis. Intriguingly, three subunits of the osteoclast specific V-ATPase complex were strongly increased in mature plaques with an enrichment in macrophages thus implying an active de-mineralization function. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

Compartment-resolved Proteomic Analysis of Mouse Aorta during Atherosclerotic Plaque Formation Reveals Osteoclast-specific Protein Expression*

PubMed Central

Wierer, Michael; Prestel, Matthias; Schiller, Herbert B.; Yan, Guangyao; Schaab, Christoph; Azghandi, Sepiede; Werner, Julia; Kessler, Thorsten; Malik, Rainer; Murgia, Marta; Aherrahrou, Zouhair; Schunkert, Heribert; Dichgans, Martin; Mann, Matthias

2018-01-01

Atherosclerosis leads to vascular lesions that involve major rearrangements of the vascular proteome, especially of the extracellular matrix (ECM). Using single aortas from ApoE knock out mice, we quantified formation of plaques by single-run, high-resolution mass spectrometry (MS)-based proteomics. To probe localization on a proteome-wide scale we employed quantitative detergent solubility profiling. This compartment- and time-resolved resource of atherogenesis comprised 5117 proteins, 182 of which changed their expression status in response to vessel maturation and atherosclerotic plaque development. In the insoluble ECM proteome, 65 proteins significantly changed, including relevant collagens, matrix metalloproteinases and macrophage derived proteins. Among novel factors in atherosclerosis, we identified matrilin-2, the collagen IV crosslinking enzyme peroxidasin as well as the poorly characterized MAM-domain containing 2 (Mamdc2) protein as being up-regulated in the ECM during atherogenesis. Intriguingly, three subunits of the osteoclast specific V-ATPase complex were strongly increased in mature plaques with an enrichment in macrophages thus implying an active de-mineralization function. PMID:29208753

Recent advances in proteomic applications for schistosomiasis research: potential clinical impact.

PubMed

Sotillo, Javier; Doolan, Denise; Loukas, Alex

2017-02-01

Schistosomiasis is a neglected tropical disease affecting hundreds of millions of people worldwide. Recent advances in the field of proteomics and the development of new and highly sensitive mass spectrometers and quantitative techniques have provided new tools for advancing the molecular biology, cell biology, diagnosis and vaccine development for public health threats such as schistosomiasis. Areas covered: In this review we describe the latest advances in research that utilizes proteomics-based tools to address some of the key challenges to developing effective interventions against schistosomiasis. We also provide information about the potential of extracellular vesicles to advance the fight against this devastating disease. Expert commentary: Different proteins are already being tested as vaccines against schistosomiasis with promising results. The re-analysis of the Schistosoma spp. proteomes using new and more sensitive mass spectrometers as well as better separation approaches will help identify more vaccine targets in a rational and informed manner. In addition, the recent development of new proteome microarrays will facilitate characterisation of novel markers of infection as well as new vaccine and diagnostic candidate antigens.

Quantitative Phospho-proteomic Analysis of TNFα/NFκB Signaling Reveals a Role for RIPK1 Phosphorylation in Suppressing Necrotic Cell Death.

PubMed

Mohideen, Firaz; Paulo, Joao A; Ordureau, Alban; Gygi, Steve P; Harper, J Wade

2017-07-01

TNFα is a potent inducer of inflammation due to its ability to promote gene expression, in part via the NFκB pathway. Moreover, in some contexts, TNFα promotes Caspase-dependent apoptosis or RIPK1/RIPK3/MLKL-dependent necrosis. Engagement of the TNF Receptor Signaling Complex (TNF-RSC), which contains multiple kinase activities, promotes phosphorylation of several downstream components, including TAK1, IKKα/IKKβ, IκBα, and NFκB. However, immediate downstream phosphorylation events occurring in response to TNFα signaling are poorly understood at a proteome-wide level. Here we use Tandem Mass Tagging-based proteomics to quantitatively characterize acute TNFα-mediated alterations in the proteome and phosphoproteome with or without inhibition of the cIAP-dependent survival arm of the pathway with a SMAC mimetic. We identify and quantify over 8,000 phosphorylated peptides, among which are numerous known sites in the TNF-RSC, NFκB, and MAP kinase signaling systems, as well as numerous previously unrecognized phosphorylation events. Functional analysis of S320 phosphorylation in RIPK1 demonstrates a role for this event in suppressing its kinase activity, association with CASPASE-8 and FADD proteins, and subsequent necrotic cell death during inflammatory TNFα stimulation. This study provides a resource for further elucidation of TNFα-dependent signaling pathways. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

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.

Proteome Analysis Using Isobaric Tags for Relative and Absolute Analysis Quantitation (iTRAQ) Reveals Alterations in Stress-Induced Dysfunctional Chicken Muscle.

PubMed

Xing, Tong; Wang, Chong; Zhao, Xue; Dai, Chen; Zhou, Guanghong; Xu, Xinglian

2017-04-05

The current study was designed to investigate changes in the protein profiles of pale, soft, and exudative (PSE)-like muscles of broilers subjected to transportation under high-temperature conditions, using isobaric tags for relative and absolute analysis quantitation (iTRAQ). Arbor Acres chickens (n = 112) were randomly divided into two treatments: unstressed control (CON) and 0.5 h of transport (T). Birds were transported according to a designed protocol. Pectoralis major (PM) muscle samples in the T group were collected and classified as normal (T-NOR) or PSE-like (T-PSE). Plasma activities of stress indicators, muscle microstructure, and proteome were measured. Results indicated that broilers in the T-PSE group exhibited higher activities of plasma stress indicators. The microstructure of T-PSE group showed a looser network and larger intercellular spaces in comparison to the other groups. Proteomic analysis, based on iTRAQ, revealed 29 differentially expressed proteins in the T-NOR and T-PSE groups that were involved in protein turnover, signal transduction, stress and defense, calcium handling, cell structure, and metabolism. In particular, proteins relating to the glycolysis pathway, calcium signaling, and molecular chaperones exhibited significant differences that may contribute to the inferior post-mortem meat quality. Overall, the proteomic results provide a further understanding of the mechanism of meat quality changes in response to stress.

Statistical Model to Analyze Quantitative Proteomics Data Obtained by 18O/16O Labeling and Linear Ion Trap Mass Spectrometry

PubMed Central

Jorge, Inmaculada; Navarro, Pedro; Martínez-Acedo, Pablo; Núñez, Estefanía; Serrano, Horacio; Alfranca, Arántzazu; Redondo, Juan Miguel; Vázquez, Jesús

2009-01-01

Statistical models for the analysis of protein expression changes by stable isotope labeling are still poorly developed, particularly for data obtained by 16O/18O labeling. Besides large scale test experiments to validate the null hypothesis are lacking. Although the study of mechanisms underlying biological actions promoted by vascular endothelial growth factor (VEGF) on endothelial cells is of considerable interest, quantitative proteomics studies on this subject are scarce and have been performed after exposing cells to the factor for long periods of time. In this work we present the largest quantitative proteomics study to date on the short term effects of VEGF on human umbilical vein endothelial cells by 18O/16O labeling. Current statistical models based on normality and variance homogeneity were found unsuitable to describe the null hypothesis in a large scale test experiment performed on these cells, producing false expression changes. A random effects model was developed including four different sources of variance at the spectrum-fitting, scan, peptide, and protein levels. With the new model the number of outliers at scan and peptide levels was negligible in three large scale experiments, and only one false protein expression change was observed in the test experiment among more than 1000 proteins. The new model allowed the detection of significant protein expression changes upon VEGF stimulation for 4 and 8 h. The consistency of the changes observed at 4 h was confirmed by a replica at a smaller scale and further validated by Western blot analysis of some proteins. Most of the observed changes have not been described previously and are consistent with a pattern of protein expression that dynamically changes over time following the evolution of the angiogenic response. With this statistical model the 18O labeling approach emerges as a very promising and robust alternative to perform quantitative proteomics studies at a depth of several thousand proteins. PMID:19181660

Label-free protein profiling of formalin-fixed paraffin-embedded (FFPE) heart tissue reveals immediate mitochondrial impairment after ionising radiation.

PubMed

Azimzadeh, Omid; Scherthan, Harry; Yentrapalli, Ramesh; Barjaktarovic, Zarko; Ueffing, Marius; Conrad, Marcus; Neff, Frauke; Calzada-Wack, Julia; Aubele, Michaela; Buske, Christian; Atkinson, Michael J; Hauck, Stefanie M; Tapio, Soile

2012-04-18

Qualitative proteome profiling of formalin-fixed, paraffin-embedded (FFPE) tissue is advancing the field of clinical proteomics. However, quantitative proteome analysis of FFPE tissue is hampered by the lack of an efficient labelling method. The usage of conventional protein labelling on FFPE tissue has turned out to be inefficient. Classical labelling targets lysine residues that are blocked by the formalin treatment. The aim of this study was to establish a quantitative proteomics analysis of FFPE tissue by combining the label-free approach with optimised protein extraction and separation conditions. As a model system we used FFPE heart tissue of control and exposed C57BL/6 mice after total body irradiation using a gamma ray dose of 3 gray. We identified 32 deregulated proteins (p≤0.05) in irradiated hearts 24h after the exposure. The proteomics data were further evaluated and validated by bioinformatics and immunoblotting investigation. In good agreement with our previous results using fresh-frozen tissue, the analysis indicated radiation-induced alterations in three main biological pathways: respiratory chain, lipid metabolism and pyruvate metabolism. The label-free approach enables the quantitative measurement of radiation-induced alterations in FFPE tissue and facilitates retrospective biomarker identification using clinical archives. Copyright © 2012 Elsevier B.V. All rights reserved.

Proteomic and transcriptional analysis of Lactobacillus johnsonii PF01 during bile salt exposure by iTRAQ shotgun proteomics and quantitative RT-PCR.

PubMed

Lee, Ji Yoon; Pajarillo, Edward Alain B; Kim, Min Jeong; Chae, Jong Pyo; Kang, Dae-Kyung

2013-01-04

Lactobacillus johnsonii PF01 has been reported to be highly resistant to bile, a key property of probiotic microorganisms. Here, we examine the nature of the bile-salt tolerance of L. johnsonii PF01. Growth inhibition and surface morphology and physiology aberrations were observed after overnight exposure to bile stress. Quantitative proteomic profiles using iTRAQ-LC-MS/MS technology identified 8307 peptides from both untreated PF01 cells and those exposed to 0.1%, 0.2%, and 0.3% bile salts. Some 215 proteins exhibited changed levels in response to bile stress; of these, levels of 94 peptides increased while those of 121 decreased. These were classified into the following categories: stress responses, cell division, transcription, translation, nucleotide metabolism, carbohydrate transport and metabolism, cell wall biosynthesis, and amino acid biosynthesis, and 16 of unidentified function. Analysis of the mRNA expression of selected genes by quantitative reverse transcriptase-PCR verified the proteomic data. Both proteomic and mRNA data provided evidence for increased phosphotransferase activity and cell wall biosynthesis. In addition, three bile salt hydrolases were significantly upregulated by bile exposure. These findings provide a basis for future evaluations of the tolerance of potential probiotic strains toward the various gastrointestinal challenges, including bile stress.

Discovery of potential protein biomarkers of lung adenocarcinoma in bronchoalveolar lavage fluid by SWATH MS data-independent acquisition and targeted data extraction.

PubMed

Ortea, I; Rodríguez-Ariza, A; Chicano-Gálvez, E; Arenas Vacas, M S; Jurado Gámez, B

2016-04-14

Lung cancer currently ranks as the neoplasia with the highest global mortality rate. Although some improvements have been introduced in recent years, new advances in diagnosis are required in order to increase survival rates. New mildly invasive endoscopy-based diagnostic techniques include the collection of bronchoalveolar lavage fluid (BALF), which is discarded after using a portion of the fluid for standard pathological procedures. BALF proteomic analysis can contribute to clinical practice with more sensitive biomarkers, and can complement cytohistological studies by aiding in the diagnosis, prognosis, and subtyping of lung cancer, as well as the monitoring of treatment response. The range of quantitative proteomics methodologies used for biomarker discovery is currently being broadened with the introduction of data-independent acquisition (DIA) analysis-related approaches that address the massive quantitation of the components of a proteome. Here we report for the first time a DIA-based quantitative proteomics study using BALF as the source for the discovery of potential lung cancer biomarkers. The results have been encouraging in terms of the number of identified and quantified proteins. A panel of candidate protein biomarkers for adenocarcinoma in BALF is reported; this points to the activation of the complement network as being strongly over-represented and suggests this pathway as a potential target for lung cancer research. In addition, the results reported for haptoglobin, complement C4-A, and glutathione S-transferase pi are consistent with previous studies, which indicates that these proteins deserve further consideration as potential lung cancer biomarkers in BALF. Our study demonstrates that the analysis of BALF proteins by liquid chromatography-tandem mass spectrometry (LC-MS/MS), combining a simple sample pre-treatment and SWATH DIA MS, is a useful method for the discovery of potential lung cancer biomarkers. Bronchoalveolar lavage fluid (BALF) analysis can contribute to clinical practice with more sensitive biomarkers, thus complementing cytohistological studies in order to aid in the diagnosis, prognosis, and subtyping of lung cancer, as well as the monitoring of treatment response. Here we report a panel of candidate protein biomarkers for adenocarcinoma in BALF. Forty-four proteins showed a fold-change higher than 3.75 among adenocarcinoma patients compared with controls. This report is the first DIA-based quantitative proteomics study to use bronchoalveolar lavage fluid (BALF) as a matrix for discovering potential biomarkers. The results are encouraging in terms of the number of identified and quantified proteins, demonstrating that the analysis of BALF proteins by a SWATH approach is a useful method for the discovery of potential biomarkers of pulmonary diseases. Copyright © 2016 Elsevier B.V. All rights reserved.

Evaluation of Rice Resistance to Southern Rice Black-Streaked Dwarf Virus and Rice Ragged Stunt Virus through Combined Field Tests, Quantitative Real-Time PCR, and Proteome Analysis.

PubMed

Wang, Zhenchao; Yu, Lu; Jin, Linhong; Wang, Wenli; Zhao, Qi; Ran, Longlu; Li, Xiangyang; Chen, Zhuo; Guo, Rong; Wei, Yongtian; Yang, Zhongcheng; Liu, Enlong; Hu, Deyu; Song, Baoan

2017-02-22

Diseases caused by southern rice black-streaked dwarf virus (SRBSDV) and rice ragged stunt virus (RRSV) considerably decrease grain yield. Therefore, determining rice cultivars with high resistance to SRBSDV and RRSV is necessary. In this study, rice cultivars with high resistance to SRBSDV and RRSV were evaluated through field trials in Shidian and Mangshi county, Yunnan province, China. SYBR Green I-based quantitative real-time polymerase chain reaction (qRT-PCR) analysis was used to quantitatively detect virus gene expression levels in different rice varieties. The following parameters were applied to evaluate rice resistance: acre yield (A.Y.), incidence of infected plants (I.I.P.), virus load (V.L.), disease index (D.I.), and insect quantity (I.Q.) per 100 clusters. Zhongzheyou1 (Z1) and Liangyou2186 (L2186) were considered the most suitable varieties with integrated higher A.Y., lower I.I.P., V.L., D.I. and I.Q. In order to investigate the mechanism of rice resistance, comparative label-free shotgun liquid chromatography tandem-mass spectrometry (LC-MS/MS) proteomic approaches were applied to comprehensively describe the proteomics of rice varieties' SRBSDV tolerance. Systemic acquired resistance (SAR)-related proteins in Z1 and L2186 may result in the superior resistance of these varieties compared with Fengyouxiangzhan (FYXZ).

Automation of dimethylation after guanidination labeling chemistry and its compatibility with common buffers and surfactants for mass spectrometry-based shotgun quantitative proteome analysis.

PubMed

Lo, Andy; Tang, Yanan; Chen, Lu; Li, Liang

2013-07-25

Isotope labeling liquid chromatography-mass spectrometry (LC-MS) is a major analytical platform for quantitative proteome analysis. Incorporation of isotopes used to distinguish samples plays a critical role in the success of this strategy. In this work, we optimized and automated a chemical derivatization protocol (dimethylation after guanidination, 2MEGA) to increase the labeling reproducibility and reduce human intervention. We also evaluated the reagent compatibility of this protocol to handle biological samples in different types of buffers and surfactants. A commercially available liquid handler was used for reagent dispensation to minimize analyst intervention and at least twenty protein digest samples could be prepared in a single run. Different front-end sample preparation methods for protein solubilization (SDS, urea, Rapigest™, and ProteaseMAX™) and two commercially available cell lysis buffers were evaluated for compatibility with the automated protocol. It was found that better than 94% desired labeling could be obtained in all conditions studied except urea, where the rate was reduced to about 92% due to carbamylation on the peptide amines. This work illustrates the automated 2MEGA labeling process can be used to handle a wide range of protein samples containing various reagents that are often encountered in protein sample preparation for quantitative proteome analysis. Copyright © 2013 Elsevier B.V. All rights reserved.

Quantitative proteomic characterization of redox-dependent post-translational modifications on protein cysteines

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

Duan, Jicheng; Gaffrey, Matthew J.; Qian, Wei-Jun

Protein cysteine thiols play a crucial role in redox signaling, regulation of enzymatic activity and protein function, and maintaining redox homeostasis in living systems. The unique chemical reactivity of thiol groups makes cysteine susceptible to oxidative modifications by reactive oxygen and nitrogen species to form a broad array of reversible and irreversible protein post-translational modifications (PTMs). The reversible modifications in particular are one of the major components of redox signaling and are involved in regulation of various cellular processes under physiological and pathological conditions. The biological significance of these redox PTMs in health and diseases has been increasingly recognized. Herein,more » we review the recent advances of quantitative proteomic approaches for investigating redox PTMs in complex biological systems, including the general considerations of sample processing, various chemical or affinity enrichment strategies, and quantitative approaches. We also highlight a number of redox proteomic approaches that enable effective profiling of redox PTMs for addressing specific biological questions. Although some technological limitations remain, redox proteomics is paving the way towards a better understanding of redox signaling and regulation in human health and diseases.« less

Proteomics analysis suggests broad functional changes in potato leaves triggered by phosphites and a complex indirect mode of action against Phytophthora infestans.

PubMed

Lim, Sanghyun; Borza, Tudor; Peters, Rick D; Coffin, Robert H; Al-Mughrabi, Khalil I; Pinto, Devanand M; Wang-Pruski, Gefu

2013-11-20

Phosphite (salts of phosphorous acid; Phi)-based fungicides are increasingly used in controlling oomycete pathogens, such as the late blight agent Phytophthora infestans. In plants, low amounts of Phi induce pathogen resistance through an indirect mode of action. We used iTRAQ-based quantitative proteomics to investigate the effects of phosphite on potato plants before and after infection with P. infestans. Ninety-three (62 up-regulated and 31 down-regulated) differentially regulated proteins, from a total of 1172 reproducibly identified proteins, were identified in the leaf proteome of Phi-treated potato plants. Four days post-inoculation with P. infestans, 16 of the 31 down-regulated proteins remained down-regulated and 42 of the 62 up-regulated proteins remained up-regulated, including 90% of the defense proteins. This group includes pathogenesis-related, stress-responsive, and detoxification-related proteins. Callose deposition and ultrastructural analyses of leaf tissues after infection were used to complement the proteomics approach. This study represents the first comprehensive proteomics analysis of the indirect mode of action of Phi, demonstrating broad effects on plant defense and plant metabolism. The proteomics data and the microscopy study suggest that Phi triggers a hypersensitive response that is responsible for induced resistance of potato leaves against P. infestans. Phosphie triggers complex functional changes in potato leaves that are responsible for the induced resistance against Phytophthora infestans. This article is part of a Special Issue entitled: Translational Plant Proteomics. Copyright © 2013 Elsevier B.V. All rights reserved.

A software suite for the generation and comparison of peptide arrays from sets of data collected by liquid chromatography-mass spectrometry.

PubMed

Li, Xiao-jun; Yi, Eugene C; Kemp, Christopher J; Zhang, Hui; Aebersold, Ruedi

2005-09-01

There is an increasing interest in the quantitative proteomic measurement of the protein contents of substantially similar biological samples, e.g. for the analysis of cellular response to perturbations over time or for the discovery of protein biomarkers from clinical samples. Technical limitations of current proteomic platforms such as limited reproducibility and low throughput make this a challenging task. A new LC-MS-based platform is able to generate complex peptide patterns from the analysis of proteolyzed protein samples at high throughput and represents a promising approach for quantitative proteomics. A crucial component of the LC-MS approach is the accurate evaluation of the abundance of detected peptides over many samples and the identification of peptide features that can stratify samples with respect to their genetic, physiological, or environmental origins. We present here a new software suite, SpecArray, that generates a peptide versus sample array from a set of LC-MS data. A peptide array stores the relative abundance of thousands of peptide features in many samples and is in a format identical to that of a gene expression microarray. A peptide array can be subjected to an unsupervised clustering analysis to stratify samples or to a discriminant analysis to identify discriminatory peptide features. We applied the SpecArray to analyze two sets of LC-MS data: one was from four repeat LC-MS analyses of the same glycopeptide sample, and another was from LC-MS analysis of serum samples of five male and five female mice. We demonstrate through these two study cases that the SpecArray software suite can serve as an effective software platform in the LC-MS approach for quantitative proteomics.

Mastitomics, the integrated omics of bovine milk in an experimental model of Streptococcus uberis mastitis: 2. Label-free relative quantitative proteomics† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c6mb00290k Click here for additional data file.

PubMed Central

Mudaliar, Manikhandan; Tassi, Riccardo; Thomas, Funmilola C.; McNeilly, Tom N.; Weidt, Stefan K.; McLaughlin, Mark; Wilson, David; Burchmore, Richard; Herzyk, Pawel; Eckersall, P. David

2016-01-01

Mastitis, inflammation of the mammary gland, is the most common and costly disease of dairy cattle in the western world. It is primarily caused by bacteria, with Streptococcus uberis as one of the most prevalent causative agents. To characterize the proteome during Streptococcus uberis mastitis, an experimentally induced model of intramammary infection was used. Milk whey samples obtained from 6 cows at 6 time points were processed using label-free relative quantitative proteomics. This proteomic analysis complements clinical, bacteriological and immunological studies as well as peptidomic and metabolomic analysis of the same challenge model. A total of 2552 non-redundant bovine peptides were identified, and from these, 570 bovine proteins were quantified. Hierarchical cluster analysis and principal component analysis showed clear clustering of results by stage of infection, with similarities between pre-infection and resolution stages (0 and 312 h post challenge), early infection stages (36 and 42 h post challenge) and late infection stages (57 and 81 h post challenge). Ingenuity pathway analysis identified upregulation of acute phase protein pathways over the course of infection, with dominance of different acute phase proteins at different time points based on differential expression analysis. Antimicrobial peptides, notably cathelicidins and peptidoglycan recognition protein, were upregulated at all time points post challenge and peaked at 57 h, which coincided with 10 000-fold decrease in average bacterial counts. The integration of clinical, bacteriological, immunological and quantitative proteomics and other-omic data provides a more detailed systems level view of the host response to mastitis than has been achieved previously. PMID:27412694

SWATH™- and iTRAQ-based quantitative proteomic analyses reveal an overexpression and biological relevance of CD109 in advanced NSCLC.

PubMed

Zhang, Fanglin; Lin, Hechun; Gu, Aiqin; Li, Jing; Liu, Lei; Yu, Tao; Cui, Yongqi; Deng, Wei; Yan, Mingxia; Li, Jinjun; Yao, Ming

2014-05-06

To identify cancer-related proteins, we used isobaric tags in a relative and absolute quantitation (iTRAQ) proteomic approach and SWATH™ quantification approach to analyze the secretome of an isogenic pair of highly metastatic and low metastatic non-small-cell lung cancer (NSCLC) cell lines. In addition, we compared two groups of pooled serum samples (12 early-stage and 12 late-stage patients) to mine data for candidates screened by iTRAQ-labeled proteomic analysis. A total of 110 proteins and 71 proteins were observed to be significantly differentially expressed in the cell line secretome and NSCLC sera, respectively. Among these proteins, CD109 was found to be highly expressed in both the highly metastatic cell line secretome and the group of late-stage patients. A sandwich ELISA assay also demonstrated an elevation of serum CD109 levels in individual NSCLC patients (n=30) compared with healthy subjects (n=19). Furthermore, CD109 displayed higher expression in lung cancer tissues compared with their matched noncancerous lung tissues (n=72). In addition, the knockdown of CD109 influenced several NSCLC cell bio-functions, for instance, depressing cell growth, affecting cell cycle phases. These phenomena suggest that CD109 plays a critical role in NSCLC progression. We simultaneously applied two quantitative proteomic approaches-iTRAQ-labeling and SWATH™-to analyze the secretome of metastatic cell lines, in order to explore the cancer-associated proteins in conditioned media. In this study, our results indicate that CD109 plays a critical role in non-small-cell lung cancer (NSCLC) progression, and is overexpressed in advanced NSCLC. Copyright © 2014 Elsevier B.V. All rights reserved.

Transcriptomic and Quantitative Proteomic Analyses Provide Insights Into the Phagocytic Killing of Hemocytes in the Oyster Crassostrea gigas

PubMed Central

Jiang, Shuai; Qiu, Limei; Wang, Lingling; Jia, Zhihao; Lv, Zhao; Wang, Mengqiang; Liu, Conghui; Xu, Jiachao; Song, Linsheng

2018-01-01

As invertebrates lack an adaptive immune system, they depend to a large extent on their innate immune system to recognize and clear invading pathogens. Although phagocytes play pivotal roles in invertebrate innate immunity, the molecular mechanisms underlying this killing remain unclear. Cells of this type from the Pacific oyster Crassostrea gigas were classified efficiently in this study via fluorescence-activated cell sorting (FACS) based on their phagocytosis of FITC-labeled latex beads. Transcriptomic and quantitative proteomic analyses revealed a series of differentially expressed genes (DEGs) and proteins present in phagocytes; of the 352 significantly high expressed proteins identified here within the phagocyte proteome, 262 corresponding genes were similarly high expressed in the transcriptome, while 140 of 205 significantly low expressed proteins within the proteome were transcriptionally low expressed. A pathway crosstalk network analysis of these significantly high expressed proteins revealed that phagocytes were highly activated in a number of antimicrobial-related biological processes, including oxidation–reduction and lysosomal proteolysis processes. A number of DEGs, including oxidase, lysosomal protease, and immune receptors, were also validated in this study using quantitative PCR, while seven lysosomal cysteine proteases, referred to as cathepsin Ls, were significantly high expressed in phagocytes. Results show that the expression level of cathepsin L protein in phagocytes [mean fluorescence intensity (MFI): 327 ± 51] was significantly higher (p < 0.01) than that in non-phagocytic hemocytes (MFI: 83 ± 26), while the cathepsin L protein was colocalized with the phagocytosed Vibrio splendidus in oyster hemocytes during this process. The results of this study collectively suggest that oyster phagocytes possess both potent oxidative killing and microbial disintegration capacities; these findings provide important insights into hemocyte phagocytic killing as a component of C. gigas innate immunity. PMID:29942306

Teaching Expression Proteomics: From the Wet-Lab to the Laptop

ERIC Educational Resources Information Center

Teixeira, Miguel C.; Santos, Pedro M.; Rodrigues, Catarina; Sa-Correia, Isabel

2009-01-01

Expression proteomics has become, in recent years, a key genome-wide expression approach in fundamental and applied life sciences. This postgenomic technology aims the quantitative analysis of all the proteins or protein forms (the so-called proteome) of a given organism in a given environmental and genetic context. It is a challenge to provide…

Accurate proteome-wide protein quantification from high-resolution 15N mass spectra

PubMed Central

2011-01-01

In quantitative mass spectrometry-based proteomics, the metabolic incorporation of a single source of 15N-labeled nitrogen has many advantages over using stable isotope-labeled amino acids. However, the lack of a robust computational framework for analyzing the resulting spectra has impeded wide use of this approach. We have addressed this challenge by introducing a new computational methodology for analyzing 15N spectra in which quantification is integrated with identification. Application of this method to an Escherichia coli growth transition reveals significant improvement in quantification accuracy over previous methods. PMID:22182234

Analysis of the variability of human normal urine by 2D-GE reveals a "public" and a "private" proteome.

PubMed

Molina, Laurence; Salvetat, Nicolas; Ameur, Randa Ben; Peres, Sabine; Sommerer, Nicolas; Jarraya, Fayçal; Ayadi, Hammadi; Molina, Franck; Granier, Claude

2011-12-10

The characterization of the normal urinary proteome is steadily progressing and represents a major interest in the assessment of clinical urinary biomarkers. To estimate quantitatively the variability of the normal urinary proteome, urines of 20 healthy people were collected. We first evaluated the impact of the sample conservation temperature on urine proteome integrity. Keeping the urine sample at RT or at +4°C until storage at -80°C seems the best way for long-term storage of samples for 2D-GE analysis. The quantitative variability of the normal urinary proteome was estimated on the 20 urines mapped by 2D-GE. The occurrence of the 910 identified spots was analysed throughout the gels and represented in a virtual 2D gel. Sixteen percent of the spots were found to occur in all samples and 23% occurred in at least 90% of urines. About 13% of the protein spots were present only in 10% or less of the samples, thus representing the most variable part of the normal urinary proteome. Twenty proteins corresponding to a fraction of the fully conserved spots were identified by mass spectrometry. In conclusion, a "public" urinary proteome, common to healthy individuals, seems to coexist with a "private" urinary proteome, which is more specific to each individual. Copyright © 2011 Elsevier B.V. All rights reserved.

A unique proteomic profile on surface IgM ligation in unmutated chronic lymphocytic leukemia

PubMed Central

Perrot, Aurore; Pionneau, Cédric; Nadaud, Sophie; Davi, Frédéric; Leblond, Véronique; Jacob, Frédéric; Merle-Béral, Hélène; Herbrecht, Raoul; Béné, Marie-Christine; Gribben, John G.; Vallat, Laurent

2011-01-01

Chronic lymphocytic leukemia (CLL) is characterized by a highly variable clinical course with 2 extreme subsets: indolent, ZAP70− and mutated immunoglobulin heavy chain gene (M-CLL); and aggressive, ZAP70+ and unmutated immunoglobulin heavy chain (UM-CLL). Given the long-term suspicion of antigenic stimulation as a primum movens in the disease, the role of the B-cell receptor has been extensively studied in various experimental settings; albeit scarcely in a comparative dynamic proteomic approach. Here we use a quantitative 2-dimensional fluorescence difference gel electrophoresis technology to compare 48 proteomic profiles of the 2 CLL subsets before and after anti-IgM ligation. Differentially expressed proteins were subsequently identified by mass spectrometry. We show that unstimulated M- and UM-CLL cells display distinct proteomic profiles. Furthermore, anti-IgM stimulation induces a specific proteomic response, more pronounced in the more aggressive CLL. Statistical analyses demonstrate several significant protein variations according to stimulation conditions. Finally, we identify an intermediate form of M-CLL cells, with an indolent profile (ZAP70−) but sharing aggressive proteomic profiles alike UM-CLL cells. Collectively, this first quantitative and dynamic proteome analysis of CLL further dissects the complex molecular pathway after B-cell receptor stimulation and depicts distinct proteomic profiles, which could lead to novel molecular stratification of the disease. PMID:21602524

Quantitative Molecular Phenotyping of Gill Remodeling in a Cichlid Fish Responding to Salinity Stress*

PubMed Central

Kültz, Dietmar; Li, Johnathon; Gardell, Alison; Sacchi, Romina

2013-01-01

A two-tiered label-free quantitative (LFQ) proteomics workflow was used to elucidate how salinity affects the molecular phenotype, i.e. proteome, of gills from a cichlid fish, the euryhaline tilapia (Oreochromis mossambicus). The workflow consists of initial global profiling of relative tryptic peptide abundances in treated versus control samples followed by targeted identification (by MS/MS) and quantitation (by chromatographic peak area integration) of validated peptides for each protein of interest. Fresh water acclimated tilapia were independently exposed in separate experiments to acute short-term (34 ppt) and gradual long-term (70 ppt, 90 ppt) salinity stress followed by molecular phenotyping of the gill proteome. The severity of salinity stress can be deduced with high technical reproducibility from the initial global label-free quantitative profiling step alone at both peptide and protein levels. However, an accurate regulation ratio can only be determined by targeted label-free quantitative profiling because not all peptides used for protein identification are also valid for quantitation. Of the three salinity challenges, gradual acclimation to 90 ppt has the most pronounced effect on gill molecular phenotype. Known salinity effects on tilapia gills, including an increase in the size and number of mitochondria-rich ionocytes, activities of specific ion transporters, and induction of specific molecular chaperones are reflected in the regulation of abundances of the corresponding proteins. Moreover, specific protein isoforms that are responsive to environmental salinity change are resolved and it is revealed that salinity effects on the mitochondrial proteome are nonuniform. Furthermore, protein NDRG1 has been identified as a novel key component of molecular phenotype restructuring during salinity-induced gill remodeling. In conclusion, besides confirming known effects of salinity on gills of euryhaline fish, molecular phenotyping reveals novel insight into proteome changes that underlie the remodeling of tilapia gill epithelium in response to environmental salinity change. PMID:24065692

A Riboproteomic Platform to Identify Novel Targets for Prostate Cancer Therapy

DTIC Science & Technology

2016-12-01

this process at the level of the translating ribosome and its associated proteins (i.e. the riboproteome). While the conventional wisdom has been...options for prostate cancer patients. 15. SUBJECT TERMS Prostate cancer, translation , riboproteome, SILAC-based mass spectrometry 16. SECURITY...riboproteomes of normal and cancer cells have been uncovered. These data suggest that the riboproteome and its associated translational landscape are

Mass Spectrometry-Based Proteomics for Pre-Eclampsia and Preterm Birth

PubMed Central

Law, Kai P.; Han, Ting-Li; Tong, Chao; Baker, Philip N.

2015-01-01

Pregnancy-related complications such as pre-eclampsia and preterm birth now represent a notable burden of adverse health. Pre-eclampsia is a hypertensive disorder unique to pregnancy. It is an important cause of maternal death worldwide and a leading cause of fetal growth restriction and iatrogenic prematurity. Fifteen million infants are born preterm each year globally, but more than one million of those do not survive their first month of life. Currently there are no predictive tests available for diagnosis of these pregnancy-related complications and the biological mechanisms of the diseases have not been fully elucidated. Mass spectrometry-based proteomics have all the necessary attributes to provide the needed breakthrough in understanding the pathophysiology of complex human diseases thorough the discovery of biomarkers. The mass spectrometry methodologies employed in the studies for pregnancy-related complications are evaluated in this article. Top-down proteomic and peptidomic profiling by laser mass spectrometry, liquid chromatography or capillary electrophoresis coupled to mass spectrometry, and bottom-up quantitative proteomics and targeted proteomics by liquid chromatography mass spectrometry have been applied to elucidate protein biomarkers and biological mechanism of pregnancy-related complications. The proteomes of serum, urine, amniotic fluid, cervical-vaginal fluid, placental tissue, and cytotrophoblastic cells have all been investigated. Numerous biomarkers or biomarker candidates that could distinguish complicated pregnancies from healthy controls have been proposed. Nevertheless, questions as to the clinically utility and the capacity to elucidate the pathogenesis of the pre-eclampsia and preterm birth remain to be answered. PMID:26006232

Global Proteomics Analysis of the Response to Starvation in C. elegans*

PubMed Central

Larance, Mark; Pourkarimi, Ehsan; Wang, Bin; Brenes Murillo, Alejandro; Kent, Robert; Lamond, Angus I.; Gartner, Anton

2015-01-01

Periodic starvation of animals induces large shifts in metabolism but may also influence many other cellular systems and can lead to adaption to prolonged starvation conditions. To date, there is limited understanding of how starvation affects gene expression, particularly at the protein level. Here, we have used mass-spectrometry-based quantitative proteomics to identify global changes in the Caenorhabditis elegans proteome due to acute starvation of young adult animals. Measuring changes in the abundance of over 5,000 proteins, we show that acute starvation rapidly alters the levels of hundreds of proteins, many involved in central metabolic pathways, highlighting key regulatory responses. Surprisingly, we also detect changes in the abundance of chromatin-associated proteins, including specific linker histones, histone variants, and histone posttranslational modifications associated with the epigenetic control of gene expression. To maximize community access to these data, they are presented in an online searchable database, the Encyclopedia of Proteome Dynamics (http://www.peptracker.com/epd/). PMID:25963834

Nanodroplet processing platform for deep and quantitative proteome profiling of 10-100 mammalian cells.

PubMed

Zhu, Ying; Piehowski, Paul D; Zhao, Rui; Chen, Jing; Shen, Yufeng; Moore, Ronald J; Shukla, Anil K; Petyuk, Vladislav A; Campbell-Thompson, Martha; Mathews, Clayton E; Smith, Richard D; Qian, Wei-Jun; Kelly, Ryan T

2018-02-28

Nanoscale or single-cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here, we report the development of a nanoPOTS (nanodroplet processing in one pot for trace samples) platform for small cell population proteomics analysis. NanoPOTS enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive liquid chromatography-MS, nanoPOTS allows identification of ~1500 to ~3000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Between Runs algorithm of MaxQuant, >3000 proteins are consistently identified from as few as 10 cells. Furthermore, we demonstrate quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.

Nanodroplet processing platform for deep and quantitative proteome profiling of 10–100 mammalian cells

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

Zhu, Ying; Piehowski, Paul D.; Zhao, Rui

Nanoscale or single-cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here in this paper, we report the development of a nanoPOTS (nanodroplet processing in one pot for trace samples) platform for small cell population proteomics analysis. NanoPOTS enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive liquid chromatography-MS, nanoPOTS allows identification of ~1500 to ~3000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Betweenmore » Runs algorithm of MaxQuant, >3000 proteins are consistently identified from as few as 10 cells. Furthermore, we demonstrate quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.« less

Nanodroplet processing platform for deep and quantitative proteome profiling of 10–100 mammalian cells

DOE PAGES

Zhu, Ying; Piehowski, Paul D.; Zhao, Rui; ...

2018-02-28

Nanoscale or single-cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here in this paper, we report the development of a nanoPOTS (nanodroplet processing in one pot for trace samples) platform for small cell population proteomics analysis. NanoPOTS enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive liquid chromatography-MS, nanoPOTS allows identification of ~1500 to ~3000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Betweenmore » Runs algorithm of MaxQuant, >3000 proteins are consistently identified from as few as 10 cells. Furthermore, we demonstrate quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.« less

Towards a proteome signature for invasive ductal breast carcinoma derived from label-free nanoscale LC-MS protein expression profiling of tumorous and glandular tissue.

PubMed

Röwer, Claudia; Vissers, Johannes P C; Koy, Cornelia; Kipping, Marc; Hecker, Michael; Reimer, Toralf; Gerber, Bernd; Thiesen, Hans-Jürgen; Glocker, Michael O

2009-12-01

As more and more alternative treatments become available for breast carcinoma, there is a need to stratify patients and individual molecular information seems to be suitable for this purpose. In this study, we applied label-free protein quantitation by nanoscale LC-MS and investigated whether this approach could be used for defining a proteome signature for invasive ductal breast carcinoma. Tissue samples from healthy breast and tumor were collected from three patients. Protein identifications were based on LC-MS peptide fragmentation data which were obtained simultaneously to the quantitative information. Hereby, an invasive ductal breast carcinoma proteome signature was generated which contains 60 protein entries. The on-column concentrations for osteoinductive factor, vimentin, GAP-DH, and NDKA are provided as examples. These proteins represent distinctive gene ontology groups of differentially expressed proteins and are discussed as risk markers for primary tumor pathogenesis. The developed methodology has been found well applicable in a clinical environment in which standard operating procedures can be kept; a prerequisite for the definition of molecular parameter sets that shall be capable for stratification of patients.

Striking against bioterrorism with advanced proteomics and reference methods.

PubMed

Armengaud, Jean

2017-01-01

The intentional use by terrorists of biological toxins as weapons has been of great concern for many years. Among the numerous toxins produced by plants, animals, algae, fungi, and bacteria, ricin is one of the most scrutinized by the media because it has already been used in biocrimes and acts of bioterrorism. Improving the analytical toolbox of national authorities to monitor these potential bioweapons all at once is of the utmost interest. MS/MS allows their absolute quantitation and exhibits advantageous sensitivity, discriminative power, multiplexing possibilities, and speed. In this issue of Proteomics, Gilquin et al. (Proteomics 2017, 17, 1600357) present a robust multiplex assay to quantify a set of eight toxins in the presence of a complex food matrix. This MS/MS reference method is based on scheduled SRM and high-quality standards consisting of isotopically labeled versions of these toxins. Their results demonstrate robust reliability based on rather loose scheduling of SRM transitions and good sensitivity for the eight toxins, lower than their oral median lethal doses. In the face of an increased threat from terrorism, relevant reference assays based on advanced proteomics and high-quality companion toxin standards are reliable and firm answers. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Absolute quantitation of isoforms of post-translationally modified proteins in transgenic organism.

PubMed

Li, Yaojun; Shu, Yiwei; Peng, Changchao; Zhu, Lin; Guo, Guangyu; Li, Ning

2012-08-01

Post-translational modification isoforms of a protein are known to play versatile biological functions in diverse cellular processes. To measure the molar amount of each post-translational modification isoform (P(isf)) of a target protein present in the total protein extract using mass spectrometry, a quantitative proteomic protocol, absolute quantitation of isoforms of post-translationally modified proteins (AQUIP), was developed. A recombinant ERF110 gene overexpression transgenic Arabidopsis plant was used as the model organism for demonstration of the proof of concept. Both Ser-62-independent (14)N-coded synthetic peptide standards and (15)N-coded ERF110 protein standard isolated from the heavy nitrogen-labeled transgenic plants were employed simultaneously to determine the concentration of all isoforms (T(isf)) of ERF110 in the whole plant cell lysate, whereas a pair of Ser-62-dependent synthetic peptide standards were used to quantitate the Ser-62 phosphosite occupancy (R(aqu)). The P(isf) was finally determined by integrating the two empirically measured variables using the following equation: P(isf) = T(isf) · R(aqu). The absolute amount of Ser-62-phosphorylated isoform of ERF110 determined using AQUIP was substantiated with a stable isotope labeling in Arabidopsis-based relative and accurate quantitative proteomic approach. The biological role of the Ser-62-phosphorylated isoform was demonstrated in transgenic plants.

High-Resolution Enabled 12-Plex DiLeu Isobaric Tags for Quantitative Proteomics

PubMed Central

2015-01-01

Multiplex isobaric tags (e.g., tandem mass tags (TMT) and isobaric tags for relative and absolute quantification (iTRAQ)) are a valuable tool for high-throughput mass spectrometry based quantitative proteomics. We have developed our own multiplex isobaric tags, DiLeu, that feature quantitative performance on par with commercial offerings but can be readily synthesized in-house as a cost-effective alternative. In this work, we achieve a 3-fold increase in the multiplexing capacity of the DiLeu reagent without increasing structural complexity by exploiting mass defects that arise from selective incorporation of 13C, 15N, and 2H stable isotopes in the reporter group. The inclusion of eight new reporter isotopologues that differ in mass from the existing four reporters by intervals of 6 mDa yields a 12-plex isobaric set that preserves the synthetic simplicity and quantitative performance of the original implementation. We show that the new reporter variants can be baseline-resolved in high-resolution higher-energy C-trap dissociation (HCD) spectra, and we demonstrate accurate 12-plex quantitation of a DiLeu-labeled Saccharomyces cerevisiae lysate digest via high-resolution nano liquid chromatography–tandem mass spectrometry (nanoLC–MS2) analysis on an Orbitrap Elite mass spectrometer. PMID:25405479

Application of survival analysis methodology to the quantitative analysis of LC-MS proteomics data.

PubMed

Tekwe, Carmen D; Carroll, Raymond J; Dabney, Alan R

2012-08-01

Protein abundance in quantitative proteomics is often based on observed spectral features derived from liquid chromatography mass spectrometry (LC-MS) or LC-MS/MS experiments. Peak intensities are largely non-normal in distribution. Furthermore, LC-MS-based proteomics data frequently have large proportions of missing peak intensities due to censoring mechanisms on low-abundance spectral features. Recognizing that the observed peak intensities detected with the LC-MS method are all positive, skewed and often left-censored, we propose using survival methodology to carry out differential expression analysis of proteins. Various standard statistical techniques including non-parametric tests such as the Kolmogorov-Smirnov and Wilcoxon-Mann-Whitney rank sum tests, and the parametric survival model and accelerated failure time-model with log-normal, log-logistic and Weibull distributions were used to detect any differentially expressed proteins. The statistical operating characteristics of each method are explored using both real and simulated datasets. Survival methods generally have greater statistical power than standard differential expression methods when the proportion of missing protein level data is 5% or more. In particular, the AFT models we consider consistently achieve greater statistical power than standard testing procedures, with the discrepancy widening with increasing missingness in the proportions. The testing procedures discussed in this article can all be performed using readily available software such as R. The R codes are provided as supplemental materials. ctekwe@stat.tamu.edu.

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.

SAFER, an Analysis Method of Quantitative Proteomic Data, Reveals New Interactors of the C. elegans Autophagic Protein LGG-1.

PubMed

Yi, Zhou; Manil-Ségalen, Marion; Sago, Laila; Glatigny, Annie; Redeker, Virginie; Legouis, Renaud; Mucchielli-Giorgi, Marie-Hélène

2016-05-06

Affinity purifications followed by mass spectrometric analysis are used to identify protein-protein interactions. Because quantitative proteomic data are noisy, it is necessary to develop statistical methods to eliminate false-positives and identify true partners. We present here a novel approach for filtering false interactors, named "SAFER" for mass Spectrometry data Analysis by Filtering of Experimental Replicates, which is based on the reproducibility of the replicates and the fold-change of the protein intensities between bait and control. To identify regulators or targets of autophagy, we characterized the interactors of LGG1, a ubiquitin-like protein involved in autophagosome formation in C. elegans. LGG-1 partners were purified by affinity, analyzed by nanoLC-MS/MS mass spectrometry, and quantified by a label-free proteomic approach based on the mass spectrometric signal intensity of peptide precursor ions. Because the selection of confident interactions depends on the method used for statistical analysis, we compared SAFER with several statistical tests and different scoring algorithms on this set of data. We show that SAFER recovers high-confidence interactors that have been ignored by the other methods and identified new candidates involved in the autophagy process. We further validated our method on a public data set and conclude that SAFER notably improves the identification of protein interactors.

Mass spectrometry data from label-free quantitative proteomic analysis of harmless and pathogenic strains of infectious microalgae, Prototheca spp.

PubMed

Murugaiyan, Jayaseelan; Eravci, Murat; Weise, Christoph; Roesler, Uwe

2017-06-01

Here, we provide the dataset associated with our research article 'label-free quantitative proteomic analysis of harmless and pathogenic strains of infectious microalgae, Prototheca spp.' (Murugaiyan et al., 2017) [1]. This dataset describes liquid chromatography-mass spectrometry (LC-MS)-based protein identification and quantification of a non-infectious strain, Prototheca zopfii genotype 1 and two strains associated with severe and mild infections, respectively, P. zopfii genotype 2 and Prototheca blaschkeae . Protein identification and label-free quantification was carried out by analysing MS raw data using the MaxQuant-Andromeda software suit. The expressional level differences of the identified proteins among the strains were computed using Perseus software and the results were presented in [1]. This DiB provides the MaxQuant output file and raw data deposited in the PRIDE repository with the dataset identifier PXD005305.

Comparative Evaluation of Small Molecular Additives and Their Effects on Peptide/Protein Identification.

PubMed

Gao, Jing; Zhong, Shaoyun; Zhou, Yanting; He, Han; Peng, Shuying; Zhu, Zhenyun; Liu, Xing; Zheng, Jing; Xu, Bin; Zhou, Hu

2017-06-06

Detergents and salts are widely used in lysis buffers to enhance protein extraction from biological samples, facilitating in-depth proteomic analysis. However, these detergents and salt additives must be efficiently removed from the digested samples prior to LC-MS/MS analysis to obtain high-quality mass spectra. Although filter-aided sample preparation (FASP), acetone precipitation (AP), followed by in-solution digestion, and strong cation exchange-based centrifugal proteomic reactors (CPRs) are commonly used for proteomic sample processing, little is known about their efficiencies at removing detergents and salt additives. In this study, we (i) developed an integrative workflow for the quantification of small molecular additives in proteomic samples, developing a multiple reaction monitoring (MRM)-based LC-MS approach for the quantification of six additives (i.e., Tris, urea, CHAPS, SDS, SDC, and Triton X-100) and (ii) systematically evaluated the relationships between the level of additive remaining in samples following sample processing and the number of peptides/proteins identified by mass spectrometry. Although FASP outperformed the other two methods, the results were complementary in terms of peptide/protein identification, as well as the GRAVY index and amino acid distributions. This is the first systematic and quantitative study of the effect of detergents and salt additives on protein identification. This MRM-based approach can be used for an unbiased evaluation of the performance of new sample preparation methods. Data are available via ProteomeXchange under identifier PXD005405.

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

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.

PANDA-view: An easy-to-use tool for statistical analysis and visualization of quantitative proteomics data.

PubMed

Chang, Cheng; Xu, Kaikun; Guo, Chaoping; Wang, Jinxia; Yan, Qi; Zhang, Jian; He, Fuchu; Zhu, Yunping

2018-05-22

Compared with the numerous software tools developed for identification and quantification of -omics data, there remains a lack of suitable tools for both downstream analysis and data visualization. To help researchers better understand the biological meanings in their -omics data, we present an easy-to-use tool, named PANDA-view, for both statistical analysis and visualization of quantitative proteomics data and other -omics data. PANDA-view contains various kinds of analysis methods such as normalization, missing value imputation, statistical tests, clustering and principal component analysis, as well as the most commonly-used data visualization methods including an interactive volcano plot. Additionally, it provides user-friendly interfaces for protein-peptide-spectrum representation of the quantitative proteomics data. PANDA-view is freely available at https://sourceforge.net/projects/panda-view/. 1987ccpacer@163.com and zhuyunping@gmail.com. Supplementary data are available at Bioinformatics online.

System-Wide Quantitative Proteomics of the Metabolic Syndrome in Mice: Genotypic and Dietary Effects.

PubMed

Terfve, Camille; Sabidó, Eduard; Wu, Yibo; Gonçalves, Emanuel; Choi, Meena; Vaga, Stefania; Vitek, Olga; Saez-Rodriguez, Julio; Aebersold, Ruedi

2017-02-03

Advances in mass spectrometry have made the quantitative measurement of proteins across multiple samples a reality, allowing for the study of complex biological systems such as the metabolic syndrome. Although the deregulation of lipid metabolism and increased hepatic storage of triacylglycerides are known to play a part in the onset of the metabolic syndrome, its molecular basis and dependency on dietary and genotypic factors are poorly characterized. Here, we used an experimental design with two different mouse strains and dietary and metabolic perturbations to generate a compendium of quantitative proteome data using three mass spectrometric techniques. The data reproduce known properties of the metabolic system and indicate differential molecular adaptation of the two mouse strains to perturbations, contributing to a better understanding of the metabolic syndrome. We show that high-quality, high-throughput proteomic data sets provide an unbiased broad overview of the behavior of complex systems after perturbation.

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

GeLC-MS-based proteomics of Chromobacterium violaceum: comparison of proteome changes elicited by hydrogen peroxide

PubMed Central

Lima, D. C.; Duarte, F. T.; Medeiros, V. K. S.; Carvalho, P. C.; Nogueira, F. C. S.; Araujo, G. D. T.; Domont, G. B.; Batistuzzo de Medeiros, S. R.

2016-01-01

Chromobacterium violaceum is a free-living bacillus with several genes that enables it survival under different harsh environments such as oxidative and temperature stresses. Here we performed a label-free quantitative proteomic study to unravel the molecular mechanisms that enable C. violaceum to survive oxidative stress. To achieve this, total proteins extracted from control and C. violaceum cultures exposed during two hours with 8 mM hydrogen peroxide were analyzed using GeLC-MS proteomics. Analysis revealed that under the stress condition, the bacterium expressed proteins that protected it from the damage caused by reactive oxygen condition and decreasing the abundance of proteins responsible for bacterial growth and catabolism. GeLC-MS proteomics analysis provided an overview of the metabolic pathways involved in the response of C. violaceum to oxidative stress ultimately aggregating knowledge of the response of this organism to environmental stress. This study identified approximately 1500 proteins, generating the largest proteomic coverage of C. violaceum so far. We also detected proteins with unknown function that we hypothesize to be part of new mechanisms related to oxidative stress defense. Finally, we identified the mechanism of clustered regularly interspaced short palindromic repeats (CRISPR), which has not yet been reported for this organism. PMID:27321545

GeLC-MS-based proteomics of Chromobacterium violaceum: comparison of proteome changes elicited by hydrogen peroxide.

PubMed

Lima, D C; Duarte, F T; Medeiros, V K S; Carvalho, P C; Nogueira, F C S; Araujo, G D T; Domont, G B; Batistuzzo de Medeiros, S R

2016-06-20

Chromobacterium violaceum is a free-living bacillus with several genes that enables it survival under different harsh environments such as oxidative and temperature stresses. Here we performed a label-free quantitative proteomic study to unravel the molecular mechanisms that enable C. violaceum to survive oxidative stress. To achieve this, total proteins extracted from control and C. violaceum cultures exposed during two hours with 8 mM hydrogen peroxide were analyzed using GeLC-MS proteomics. Analysis revealed that under the stress condition, the bacterium expressed proteins that protected it from the damage caused by reactive oxygen condition and decreasing the abundance of proteins responsible for bacterial growth and catabolism. GeLC-MS proteomics analysis provided an overview of the metabolic pathways involved in the response of C. violaceum to oxidative stress ultimately aggregating knowledge of the response of this organism to environmental stress. This study identified approximately 1500 proteins, generating the largest proteomic coverage of C. violaceum so far. We also detected proteins with unknown function that we hypothesize to be part of new mechanisms related to oxidative stress defense. Finally, we identified the mechanism of clustered regularly interspaced short palindromic repeats (CRISPR), which has not yet been reported for this organism.

A Description of the Clinical Proteomic Tumor Analysis Consortium (CPTAC) Common Data Analysis Pipeline

PubMed Central

Rudnick, Paul A.; Markey, Sanford P.; Roth, Jeri; Mirokhin, Yuri; Yan, Xinjian; Tchekhovskoi, Dmitrii V.; Edwards, Nathan J.; Thangudu, Ratna R.; Ketchum, Karen A.; Kinsinger, Christopher R.; Mesri, Mehdi; Rodriguez, Henry; Stein, Stephen E.

2016-01-01

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) has produced large proteomics datasets from the mass spectrometric interrogation of tumor samples previously analyzed by The Cancer Genome Atlas (TCGA) program. The availability of the genomic and proteomic data is enabling proteogenomic study for both reference (i.e., contained in major sequence databases) and non-reference markers of cancer. The CPTAC labs have focused on colon, breast, and ovarian tissues in the first round of analyses; spectra from these datasets were produced from 2D LC-MS/MS analyses and represent deep coverage. To reduce the variability introduced by disparate data analysis platforms (e.g., software packages, versions, parameters, sequence databases, etc.), the CPTAC Common Data Analysis Platform (CDAP) was created. The CDAP produces both peptide-spectrum-match (PSM) reports and gene-level reports. The pipeline processes raw mass spectrometry data according to the following: (1) Peak-picking and quantitative data extraction, (2) database searching, (3) gene-based protein parsimony, and (4) false discovery rate (FDR)-based filtering. The pipeline also produces localization scores for the phosphopeptide enrichment studies using the PhosphoRS program. Quantitative information for each of the datasets is specific to the sample processing, with PSM and protein reports containing the spectrum-level or gene-level (“rolled-up”) precursor peak areas and spectral counts for label-free or reporter ion log-ratios for 4plex iTRAQ™. The reports are available in simple tab-delimited formats and, for the PSM-reports, in mzIdentML. The goal of the CDAP is to provide standard, uniform reports for all of the CPTAC data, enabling comparisons between different samples and cancer types as well as across the major ‘omics fields. PMID:26860878

A Description of the Clinical Proteomic Tumor Analysis Consortium (CPTAC) Common Data Analysis Pipeline.

PubMed

Rudnick, Paul A; Markey, Sanford P; Roth, Jeri; Mirokhin, Yuri; Yan, Xinjian; Tchekhovskoi, Dmitrii V; Edwards, Nathan J; Thangudu, Ratna R; Ketchum, Karen A; Kinsinger, Christopher R; Mesri, Mehdi; Rodriguez, Henry; Stein, Stephen E

2016-03-04

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) has produced large proteomics data sets from the mass spectrometric interrogation of tumor samples previously analyzed by The Cancer Genome Atlas (TCGA) program. The availability of the genomic and proteomic data is enabling proteogenomic study for both reference (i.e., contained in major sequence databases) and nonreference markers of cancer. The CPTAC laboratories have focused on colon, breast, and ovarian tissues in the first round of analyses; spectra from these data sets were produced from 2D liquid chromatography-tandem mass spectrometry analyses and represent deep coverage. To reduce the variability introduced by disparate data analysis platforms (e.g., software packages, versions, parameters, sequence databases, etc.), the CPTAC Common Data Analysis Platform (CDAP) was created. The CDAP produces both peptide-spectrum-match (PSM) reports and gene-level reports. The pipeline processes raw mass spectrometry data according to the following: (1) peak-picking and quantitative data extraction, (2) database searching, (3) gene-based protein parsimony, and (4) false-discovery rate-based filtering. The pipeline also produces localization scores for the phosphopeptide enrichment studies using the PhosphoRS program. Quantitative information for each of the data sets is specific to the sample processing, with PSM and protein reports containing the spectrum-level or gene-level ("rolled-up") precursor peak areas and spectral counts for label-free or reporter ion log-ratios for 4plex iTRAQ. The reports are available in simple tab-delimited formats and, for the PSM-reports, in mzIdentML. The goal of the CDAP is to provide standard, uniform reports for all of the CPTAC data to enable comparisons between different samples and cancer types as well as across the major omics fields.

Identification of p90 Ribosomal S6 Kinase 2 as a Novel Host Protein in HBx Augmenting HBV Replication by iTRAQ-Based Quantitative Comparative Proteomics.

PubMed

Yan, Li-Bo; Yu, You-Jia; Zhang, Qing-Bo; Tang, Xiao-Qiong; Bai, Lang; Huang, FeiJun; Tang, Hong

2018-05-01

The aim of this study was to screen for novel host proteins that play a role in HBx augmenting Hepatitis B virus (HBV) replication. Three HepG2 cell lines stably harboring different functional domains of HBx (HBx, HBx-Cm6, and HBx-Cm16) were cultured. ITRAQ technology integrated with LC-MS/MS analysis was applied to identify the proteome differences among these three cell lines. In brief, a total of 70 different proteins were identified among HepG2-HBx, HepG2-HBx-Cm6, and HepG2-HBx-Cm16 by double repetition. Several differentially expressed proteins, including p90 ribosomal S6 kinase 2 (RSK2), were further validated. RSK2 was expressed at higher levels in HepG2-HBx and HepG2-HBx-Cm6 compared with HepG2-HBx-Cm16. Furthermore, levels of HBV replication intermediates were decreased after silencing RSK2 in HepG2.2.15. An HBx-minus HBV mutant genome led to decreased levels of HBV replication intermediates and these decreases were restored to levels similar to wild-type HBV by transient ectopic expression of HBx. After silencing RSK2 expression, the levels of HBV replication intermediates synthesized from the HBx-minus HBV mutant genome were not restored to levels that were observed with wild-type HBV by transient HBx expression. Based on iTRAQ quantitative comparative proteomics, RSK2 was identified as a novel host protein that plays a role in HBx augmenting HBV replication. © 2018 The Authors. Proteomics - Clinical Application Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An effect size filter improves the reproducibility in spectral counting-based comparative proteomics.

PubMed

Gregori, Josep; Villarreal, Laura; Sánchez, Alex; Baselga, José; Villanueva, Josep

2013-12-16

The microarray community has shown that the low reproducibility observed in gene expression-based biomarker discovery studies is partially due to relying solely on p-values to get the lists of differentially expressed genes. Their conclusions recommended complementing the p-value cutoff with the use of effect-size criteria. The aim of this work was to evaluate the influence of such an effect-size filter on spectral counting-based comparative proteomic analysis. The results proved that the filter increased the number of true positives and decreased the number of false positives and the false discovery rate of the dataset. These results were confirmed by simulation experiments where the effect size filter was used to evaluate systematically variable fractions of differentially expressed proteins. Our results suggest that relaxing the p-value cut-off followed by a post-test filter based on effect size and signal level thresholds can increase the reproducibility of statistical results obtained in comparative proteomic analysis. Based on our work, we recommend using a filter consisting of a minimum absolute log2 fold change of 0.8 and a minimum signal of 2-4 SpC on the most abundant condition for the general practice of comparative proteomics. The implementation of feature filtering approaches could improve proteomic biomarker discovery initiatives by increasing the reproducibility of the results obtained among independent laboratories and MS platforms. Quality control analysis of microarray-based gene expression studies pointed out that the low reproducibility observed in the lists of differentially expressed genes could be partially attributed to the fact that these lists are generated relying solely on p-values. Our study has established that the implementation of an effect size post-test filter improves the statistical results of spectral count-based quantitative proteomics. The results proved that the filter increased the number of true positives whereas decreased the false positives and the false discovery rate of the datasets. The results presented here prove that a post-test filter applying a reasonable effect size and signal level thresholds helps to increase the reproducibility of statistical results in comparative proteomic analysis. Furthermore, the implementation of feature filtering approaches could improve proteomic biomarker discovery initiatives by increasing the reproducibility of results obtained among independent laboratories and MS platforms. This article is part of a Special Issue entitled: Standardization and Quality Control in Proteomics. Copyright © 2013 Elsevier B.V. All rights reserved.

Next-generation sequencing-based transcriptomic and proteomic analysis of the common reed, Phragmites australis (Poaceae), reveals genes involved in invasiveness and rhizome specificity.

PubMed

He, Ruifeng; Kim, Min-Jeong; Nelson, William; Balbuena, Tiago S; Kim, Ryan; Kramer, Robin; Crow, John A; May, Greg D; Thelen, Jay J; Soderlund, Carol A; Gang, David R

2012-02-01

The common reed (Phragmites australis), one of the most widely distributed of all angiosperms, uses its rhizomes (underground stems) to invade new territory, making it one of the most successful weedy species worldwide. Characterization of the rhizome transcriptome and proteome is needed to identify candidate genes and proteins involved in rhizome growth, development, metabolism, and invasiveness. We employed next-generation sequencing technologies including 454 and Illumina platforms to characterize the reed rhizome transcriptome and used quantitative proteomics techniques to identify the rhizome proteome. Combining 336514 Roche 454 Titanium reads and 103350802 Illumina paired-end reads in a de novo hybrid assembly yielded 124450 unique transcripts with an average length of 549 bp, of which 54317 were annotated. Rhizome-specific and differentially expressed transcripts were identified between rhizome apical tips (apical meristematic region) and rhizome elongation zones. A total of 1280 nonredundant proteins were identified and quantified using GeLC-MS/MS based label-free proteomics, where 174 and 77 proteins were preferentially expressed in the rhizome elongation zone and apical tip tissues, respectively. Genes involved in allelopathy and in controlling development and potentially invasiveness were identified. In addition to being a valuable sequence and protein data resource for studying plant rhizome species, our results provide useful insights into identifying specific genes and proteins with potential roles in rhizome differentiation, development, and function.

Identification of head and neck squamous cell carcinoma biomarker candidates through proteomic analysis of cancer cell secretome.

PubMed

Marimuthu, Arivusudar; Chavan, Sandip; Sathe, Gajanan; Sahasrabuddhe, Nandini A; Srikanth, Srinivas M; Renuse, Santosh; Ahmad, Sartaj; Radhakrishnan, Aneesha; Barbhuiya, Mustafa A; Kumar, Rekha V; Harsha, H C; Sidransky, David; Califano, Joseph; Pandey, Akhilesh; Chatterjee, Aditi

2013-11-01

Protein biomarker discovery for early detection of head and neck squamous cell carcinoma (HNSCC) is a crucial unmet need to improve patient outcomes. Mass spectrometry-based proteomics has emerged as a promising tool for identification of biomarkers in different cancer types. Proteins secreted from cancer cells can serve as potential biomarkers for early diagnosis. In the current study, we have used isobaric tag for relative and absolute quantitation (iTRAQ) labeling methodology coupled with high resolution mass spectrometry to identify and quantitate secreted proteins from a panel of head and neck carcinoma cell lines. In all, we identified 2,472 proteins, of which 225 proteins were secreted at higher or lower abundance in HNSCC-derived cell lines. Of these, 148 were present in higher abundance and 77 were present in lower abundance in the cancer-cell derived secretome. We detected a higher abundance of some previously known markers for HNSCC including insulin like growth factor binding protein 3, IGFBP3 (11-fold) and opioid growth factor receptor, OGFR (10-fold) demonstrating the validity of our approach. We also identified several novel secreted proteins in HNSCC including olfactomedin-4, OLFM4 (12-fold) and hepatocyte growth factor activator, HGFA (5-fold). IHC-based validation was conducted in HNSCC using tissue microarrays which revealed overexpression of IGFBP3 and OLFM4 in 70% and 75% of the tested cases, respectively. Our study illustrates quantitative proteomics of secretome as a robust approach for identification of potential HNSCC biomarkers. This article is part of a Special Issue entitled: An Updated Secretome. Copyright © 2013 Elsevier B.V. All rights reserved.

PKA-regulated VASP phosphorylation promotes extrusion of transformed cells from the epithelium

PubMed Central

Anton, Katarzyna A.; Sinclair, John; Ohoka, Atsuko; Kajita, Mihoko; Ishikawa, Susumu; Benz, Peter M.; Renne, Thomas; Balda, Maria; Matter, Karl; Fujita, Yasuyuki

2014-01-01

ABSTRACT At the early stages of carcinogenesis, transformation occurs in single cells within tissues. In an epithelial monolayer, such mutated cells are recognized by their normal neighbors and are often apically extruded. The apical extrusion requires cytoskeletal reorganization and changes in cell shape, but the molecular switches involved in the regulation of these processes are poorly understood. Here, using stable isotope labeling by amino acids in cell culture (SILAC)-based quantitative mass spectrometry, we have identified proteins that are modulated in transformed cells upon their interaction with normal cells. Phosphorylation of VASP at serine 239 is specifically upregulated in RasV12-transformed cells when they are surrounded by normal cells. VASP phosphorylation is required for the cell shape changes and apical extrusion of Ras-transformed cells. Furthermore, PKA is activated in Ras-transformed cells that are surrounded by normal cells, leading to VASP phosphorylation. These results indicate that the PKA–VASP pathway is a crucial regulator of tumor cell extrusion from the epithelium, and they shed light on the events occurring at the early stage of carcinogenesis. PMID:24963131

Quantitative proteomics and systems analysis of cultured H9C2 cardiomyoblasts during differentiation over time supports a 'function follows form' model of differentiation.

PubMed

Kankeu, Cynthia; Clarke, Kylie; Van Haver, Delphi; Gevaert, Kris; Impens, Francis; Dittrich, Anna; Roderick, H Llewelyn; Passante, Egle; Huber, Heinrich J

2018-05-17

The rat cardiomyoblast cell line H9C2 has emerged as a valuable tool for studying cardiac development, mechanisms of disease and toxicology. We present here a rigorous proteomic analysis that monitored the changes in protein expression during differentiation of H9C2 cells into cardiomyocyte-like cells over time. Quantitative mass spectrometry followed by gene ontology (GO) enrichment analysis revealed that early changes in H9C2 differentiation are related to protein pathways of cardiac muscle morphogenesis and sphingolipid synthesis. These changes in the proteome were followed later in the differentiation time-course by alterations in the expression of proteins involved in cation transport and beta-oxidation. Studying the temporal profile of the H9C2 proteome during differentiation in further detail revealed eight clusters of co-regulated proteins that can be associated with early, late, continuous and transient up- and downregulation. Subsequent reactome pathway analysis based on these eight clusters further corroborated and detailed the results of the GO analysis. Specifically, this analysis confirmed that proteins related to pathways in muscle contraction are upregulated early and transiently, and proteins relevant to extracellular matrix organization are downregulated early. In contrast, upregulation of proteins related to cardiac metabolism occurs at later time points. Finally, independent validation of the proteomics results by immunoblotting confirmed hereto unknown regulators of cardiac structure and ionic metabolism. Our results are consistent with a 'function follows form' model of differentiation, whereby early and transient alterations of structural proteins enable subsequent changes that are relevant to the characteristic physiology of cardiomyocytes.

Guaifenesin stone matrix proteomics: a protocol for identifying proteins critical to stone formation.

PubMed

Kolbach-Mandel, A M; Mandel, N S; Cohen, S R; Kleinman, J G; Ahmed, F; Mandel, I C; Wesson, J A

2017-04-01

Drug-related kidney stones are a diagnostic problem, since they contain a large matrix (protein) fraction and are frequently incorrectly identified as matrix stones. A urine proteomics study patient produced a guaifenesin stone during her participation, allowing us to both correctly diagnose her disease and identify proteins critical to this drug stone-forming process. The patient provided three random midday urine samples for proteomics studies; one of which contained stone-like sediment with two distinct fractions. These solids were characterized with optical microscopy and Fourier transform infrared spectroscopy. Immunoblotting and quantitative mass spectrometry were used to quantitatively identify the proteins in urine and stone matrix. Infrared spectroscopy showed that the sediment was 60 % protein and 40 % guaifenesin and its metabolite guaiacol. Of the 156 distinct proteins identified in the proteomic studies, 49 were identified in the two stone-components with approximately 50 % of those proteins also found in this patient's urine. Many proteins observed in this drug-related stone have also been reported in proteomic matrix studies of uric acid and calcium containing stones. More importantly, nine proteins were highly enriched and highly abundant in the stone matrix and 8 were reciprocally depleted in urine, suggesting a critical role for these proteins in guaifenesin stone formation. Accurate stone analysis is critical to proper diagnosis and treatment of kidney stones. Many matrix proteins were common to all stone types, but likely not related to disease mechanism. This protocol defined a small set of proteins that were likely critical to guaifenesin stone formation based on their high enrichment and high abundance in stone matrix, and it should be applied to all stone types.

Comparative iTRAQ-Based Quantitative Proteomic Analysis of Pelteobagrus vachelli Liver under Acute Hypoxia: Implications in Metabolic Responses.

PubMed

Zhang, Guosong; Zhang, Jiajia; Wen, Xin; Zhao, Cheng; Zhang, Hongye; Li, Xinru; Yin, Shaowu

2017-09-01

More and more frequently these days, aquatic ecosystems are being stressed by nutrient enrichment, pollutants, and global warming, leading to a serious depletion in oxygen concentrations. Although a sudden, significant lack of oxygen will result in mortality, fishes can have an acute behavior (e.g., an increase in breathing rate, reduction in swimming frequency) and physiology responses (e.g., increase in oxygen delivery, and reduction in oxygen consumption) to hypoxia, which allows them to maintain normal physical activity. Therefore, in order to shed further light on the molecular mechanisms of hypoxia adaptation in fishes, the authors conduct comparative quantitative proteomics on Pelteobagrus vachelli livers using iTRAQ. The research identifies 511 acute hypoxia-responsive proteins in P. vachelli. Furthermore, comparison of several of the diverse key pathways studied (e.g., peroxisome pathway, PPAR signaling pathway, lipid metabolism, glycolysis/gluco-neogenesis, and amino acid metabolism) help to articulate the different mechanisms involved in the hypoxia response of P. vachelli. Data from proteome analysis shows that P. vachelli can have an acute reaction to hypoxia, including detoxification of metabolic by-products and oxidative stress in light of continued metabolic activity (e.g., peroxisomes), an activation in the capacity of catabolism to get more energy (e.g., lipolysis and amino acid catabolism), a depression in the capacity of biosynthesis to reduce energy consumption (e.g., biosynthesis of amino acids and lipids), and a shift in the aerobic and anaerobic contributions to total metabolism. The observed hypoxia-related changes in the liver proteome of the fish can help to understand or can be related to the hypoxia-related response that takes place in similar conditions in the liver or other proteomes of mammals. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative proteomics reveals the kinetics of trypsin-catalyzed protein digestion.

PubMed

Pan, Yanbo; Cheng, Kai; Mao, Jiawei; Liu, Fangjie; Liu, Jing; Ye, Mingliang; Zou, Hanfa

2014-10-01

Trypsin is the popular protease to digest proteins into peptides in shotgun proteomics, but few studies have attempted to systematically investigate the kinetics of trypsin-catalyzed protein digestion in proteome samples. In this study, we applied quantitative proteomics via triplex stable isotope dimethyl labeling to investigate the kinetics of trypsin-catalyzed cleavage. It was found that trypsin cleaves the C-terminal to lysine (K) and arginine (R) residues with higher rates for R. And the cleavage sites surrounded by neutral residues could be quickly cut, while those with neighboring charged residues (D/E/K/R) or proline residue (P) could be slowly cut. In a proteome sample, a huge number of proteins with different physical chemical properties coexists. If any type of protein could be preferably digested, then limited digestion could be applied to reduce the sample complexity. However, we found that protein abundance and other physicochemical properties, such as molecular weight (Mw), grand average of hydropathicity (GRAVY), aliphatic index, and isoelectric point (pI) have no notable correlation with digestion priority of proteins.

Proteomic analysis of acquired tamoxifen resistance in MCF-7 cells reveals expression signatures associated with enhanced migration

PubMed Central

2012-01-01

Introduction Acquired tamoxifen resistance involves complex signaling events that are not yet fully understood. Successful therapeutic intervention to delay the onset of hormone resistance depends critically on mechanistic elucidation of viable molecular targets associated with hormone resistance. This study was undertaken to investigate the global proteomic alterations in a tamoxifen resistant MCF-7 breast cancer cell line obtained by long term treatment of the wild type MCF-7 cell line with 4-hydroxytamoxifen (4-OH Tam). Methods We cultured MCF-7 cells with 4-OH Tam over a period of 12 months to obtain the resistant cell line. A gel-free, quantitative proteomic method was used to identify and quantify the proteome of the resistant cell line. Nano-flow high-performance liquid chromatography coupled to high resolution Fourier transform mass spectrometry was used to analyze fractionated peptide mixtures that were isobarically labeled from the resistant and control cell lysates. Real time quantitative PCR and Western blots were used to verify selected proteomic changes. Lentiviral vector transduction was used to generate MCF-7 cells stably expressing S100P. Online pathway analysis was performed to assess proteomic signatures in tamoxifen resistance. Survival analysis was done to evaluate clinical relevance of altered proteomic expressions. Results Quantitative proteomic analysis revealed a wide breadth of signaling events during transition to acquired tamoxifen resistance. A total of 629 proteins were found significantly changed with 364 up-regulated and 265 down-regulated. Collectively, these changes demonstrated the suppressed state of estrogen receptor (ER) and ER-regulated genes, activated survival signaling and increased migratory capacity of the resistant cell line. The protein S100P was found to play a critical role in conferring tamoxifen resistance and enhanced cell motility. Conclusions Our data demonstrate that the adaptive changes in the proteome of tamoxifen resistant breast cancer cells are characterized by down-regulated ER signaling, activation of alternative survival pathways, and enhanced cell motility through regulation of the actin cytoskeleton dynamics. Evidence also emerged that S100P mediates acquired tamoxifen resistance and migration capacity. PMID:22417809

Perturbations in the Urinary Exosome in Transplant Rejection

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

Sigdel, Tara K.; NG, Yolanda; Lee, Sangho

Background: Urine exosomes, vesicles exocytosed into urine by all renal epithelial cell types, occur under normal physiologic and disease states. Exosome contents may mirror disease-specific proteome perturbations in kidney injury. Analysis methodologies for the exosomal fraction of the urinary proteome were developed and for comparing the urinary exosomal fraction versus unfractionated proteome for biomarker discovery. Methods: Urine exosomes were isolated by centrifugal filtration from mid-stream, second morning void, urine samples collected from kidney transplant recipients with and without biopsy matched acute rejection. The proteomes of unfractionated whole urine (Uw) and urine exosomes (Uexo) underwent mass spectrometry-based quantitative proteomics analysis. Themore » proteome data were analyzed for significant differential protein abundances in acute rejection (AR). Results: Identifications of 1018 and 349 proteins, Uw and Uexo fractions, respectively, demonstrated a 279 protein overlap between the two urinary compartments with 25%(70) of overlapping proteins unique to Uexoand represented membrane bound proteins (p=9.31e-7). Of 349 urine exosomal proteins identified in transplant patients 220 were not previously identified in the normal urine exosomal fraction. Uexo proteins (11), functioning in the inflammatory / stress response, were more abundant in patients with biopsy-confirmed acute rejection, 3 of which were exclusive to Uexo. Uexo AR-specific biomarkers (8) were also detected in Uw, but since they were observed at significantly lower abundances in Uw, they were not significant for AR in Uw. Conclusions: A rapid urinary exosome isolation method and quantitative measurement of enriched Uexo proteins was applied. Urine proteins specific to the exosomal fraction were detected either in unfractionated urine (at low abundances) or by Uexo fraction analysis. Perturbed proteins in the exosomal compartment of urine collected from kidney transplant patients were specific to inflammatory responses, and were not observed in the Uexo fraction from normal healthy subjects. Uexo specific protein alterations in renal disease provide potential mechanistic insights and offer a unique panel of sensitive biomarkers for monitoring for acute transplant rejection.« less

Urine Sample Preparation in 96-Well Filter Plates for Quantitative Clinical Proteomics

PubMed Central

2015-01-01

Urine is an important, noninvasively collected body fluid source for the diagnosis and prognosis of human diseases. Liquid chromatography mass spectrometry (LC-MS) based shotgun proteomics has evolved as a sensitive and informative technique to discover candidate disease biomarkers from urine specimens. Filter-aided sample preparation (FASP) generates peptide samples from protein mixtures of cell lysate or body fluid origin. Here, we describe a FASP method adapted to 96-well filter plates, named 96FASP. Soluble urine concentrates containing ∼10 μg of total protein were processed by 96FASP and LC-MS resulting in 700–900 protein identifications at a 1% false discovery rate (FDR). The experimental repeatability, as assessed by label-free quantification and Pearson correlation analysis for shared proteins among replicates, was high (R ≥ 0.97). Application to urinary pellet lysates which is of particular interest in the context of urinary tract infection analysis was also demonstrated. On average, 1700 proteins (±398) were identified in five experiments. In a pilot study using 96FASP for analysis of eight soluble urine samples, we demonstrated that protein profiles of technical replicates invariably clustered; the protein profiles for distinct urine donors were very different from each other. Robust, highly parallel methods to generate peptide mixtures from urine and other body fluids are critical to increase cost-effectiveness in clinical proteomics projects. This 96FASP method has potential to become a gold standard for high-throughput quantitative clinical proteomics. PMID:24797144

New insights into the mechanisms of acetic acid resistance in Acetobacter pasteurianus using iTRAQ-dependent quantitative proteomic analysis.

PubMed

Xia, Kai; Zang, Ning; Zhang, Junmei; Zhang, Hong; Li, Yudong; Liu, Ye; Feng, Wei; Liang, Xinle

2016-12-05

Acetobacter pasteurianus is the main starter in rice vinegar manufacturing due to its remarkable abilities to resist and produce acetic acid. Although several mechanisms of acetic acid resistance have been proposed and only a few effector proteins have been identified, a comprehensive depiction of the biological processes involved in acetic acid resistance is needed. In this study, iTRAQ-based quantitative proteomic analysis was adopted to investigate the whole proteome of different acidic titers (3.6, 7.1 and 9.3%, w/v) of Acetobacter pasteurianus Ab3 during the vinegar fermentation process. Consequently, 1386 proteins, including 318 differentially expressed proteins (p<0.05), were identified. Compared to that in the low titer circumstance, cells conducted distinct biological processes under high acetic acid stress, where >150 proteins were differentially expressed. Specifically, proteins involved in amino acid metabolic processes and fatty acid biosynthesis were differentially expressed, which may contribute to the acetic acid resistance of Acetobacter. Transcription factors, two component systems and toxin-antitoxin systems were implicated in the modulatory network at multiple levels. In addition, the identification of proteins involved in redox homeostasis, protein metabolism, and the cell envelope suggested that the whole cellular system is mobilized in response to acid stress. These findings provide a differential proteomic profile of acetic acid resistance in Acetobacter pasteurianus and have potential application to highly acidic rice vinegar manufacturing. Copyright © 2016 Elsevier B.V. All rights reserved.

COMPASS: a suite of pre- and post-search proteomics software tools for OMSSA

PubMed Central

Wenger, Craig D.; Phanstiel, Douglas H.; Lee, M. Violet; Bailey, Derek J.; Coon, Joshua J.

2011-01-01

Here we present the Coon OMSSA Proteomic Analysis Software Suite (COMPASS): a free and open-source software pipeline for high-throughput analysis of proteomics data, designed around the Open Mass Spectrometry Search Algorithm. We detail a synergistic set of tools for protein database generation, spectral reduction, peptide false discovery rate analysis, peptide quantitation via isobaric labeling, protein parsimony and protein false discovery rate analysis, and protein quantitation. We strive for maximum ease of use, utilizing graphical user interfaces and working with data files in the original instrument vendor format. Results are stored in plain text comma-separated values files, which are easy to view and manipulate with a text editor or spreadsheet program. We illustrate the operation and efficacy of COMPASS through the use of two LC–MS/MS datasets. The first is a dataset of a highly annotated mixture of standard proteins and manually validated contaminants that exhibits the identification workflow. The second is a dataset of yeast peptides, labeled with isobaric stable isotope tags and mixed in known ratios, to demonstrate the quantitative workflow. For these two datasets, COMPASS performs equivalently or better than the current de facto standard, the Trans-Proteomic Pipeline. PMID:21298793

Dioscin Inhibits HSC-T6 Cell Migration via Adjusting SDC-4 Expression: Insights from iTRAQ-Based Quantitative Proteomics.

PubMed

Yin, Lianhong; Qi, Yan; Xu, Youwei; Xu, Lina; Han, Xu; Tao, Xufeng; Song, Shasha; Peng, Jinyong

2017-01-01

Hepatic stellate cells (HSCs) migration, an important bioprocess, contributes to the development of liver fibrosis. Our previous studies have found the potent activity of dioscin against liver fibrosis by inhibiting HSCs proliferation, triggering the senescence and inducing apoptosis of activated HSCs, but the molecular mechanisms associated with cell migration were not clarified. In this work, iTRAQ (isobaric tags for relative and absolution quantitation)-based quantitative proteomics study was carried out, and a total of 1566 differentially expressed proteins with fold change ≥2.0 and p < 0.05 were identified in HSC-T6 cells treated by dioscin (5.0 μg/mL). Based on Gene Ontology classification, String and KEGG pathway assays, the effects of dioscin to inhibit cell migration via regulating SDC-4 were carried out. The results of wound-healing, cell migration and western blotting assays indicated that dioscin significantly inhibit HSC-T6 cell migration through SDC-4-dependent signal pathway by affecting the expression levels of Fn, PKCα, Src, FAK, and ERK1/2. Specific SDC-4 knockdown by shRNA also blocked HSC-T6 cell migration, and dioscin slightly enhanced the inhibiting effect. Taken together, the present work showed that SDC-4 played a crucial role on HSC-T6 cell adhesion and migration of dioscin against liver fibrosis, which may be one potent therapeutic target for fibrotic diseases.

Quantitative iTRAQ secretome analysis of Aspergillus niger reveals novel hydrolytic enzymes.

PubMed

Adav, Sunil S; Li, An A; Manavalan, Arulmani; Punt, Peter; Sze, Siu Kwan

2010-08-06

The natural lifestyle of Aspergillus niger made them more effective secretors of hydrolytic proteins and becomes critical when this species were exploited as hosts for the commercial secretion of heterologous proteins. The protein secretion profile of A. niger and its mutant at different pH was explored using iTRAQ-based quantitative proteomics approach coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS). This study characterized 102 highly confident unique proteins in the secretome with zero false discovery rate based on decoy strategy. The iTRAQ technique identified and relatively quantified many hydrolyzing enzymes such as cellulases, hemicellulases, glycoside hydrolases, proteases, peroxidases, and protein translocating transporter proteins during fermentation. The enzymes have potential application in lignocellulosic biomass hydrolysis for biofuel production, for example, the cellulolytic and hemicellulolytic enzymes glucan 1,4-alpha-glucosidase, alpha-glucosidase C, endoglucanase, alpha l-arabinofuranosidase, beta-mannosidase, glycosyl hydrolase; proteases such as tripeptidyl-peptidase, aspergillopepsin, and other enzymes including cytochrome c oxidase, cytochrome c oxidase, glucose oxidase were highly expressed in A. niger and its mutant secretion. In addition, specific enzyme production can be stimulated by controlling pH of the culture medium. Our results showed comprehensive unique secretory protein profile of A. niger, its regulation at different pH, and the potential application of iTRAQ-based quantitative proteomics for the microbial secretome analysis.

The future of targeted peptidomics.

PubMed

Findeisen, Peter

2013-12-01

Targeted MS is becoming increasingly important for sensitive and specific quantitative detection of proteins and respective PTMs. In this article, Ceglarek et al. [Proteomics Clin. Appl. 2013, 7, 794-801] present an LC-MS-based method for simultaneous quantitation of seven apolipoproteins in serum specimens. The assay fulfills many necessities of routine diagnostic applications, namely, low cost, high throughput, and good reproducibility. We anticipate that validation of new biomarkers will speed up with this technology and the palette of laboratory-based diagnostic tools will hopefully be augmented significantly in the near future. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Application of a label-free, gel-free quantitative proteomics method for ecotoxicological studies of small fish species

EPA Science Inventory

Although two-dimensional electrophoresis (2D-GE) remains the basis for many ecotoxicoproteomic analyses, new, non gel-based methods are beginning to be applied to overcome throughput and coverage limitations of 2D-GE. The overall objective of our research was to apply a comprehe...

Thermo-msf-parser: an open source Java library to parse and visualize Thermo Proteome Discoverer msf files.

PubMed

Colaert, Niklaas; Barsnes, Harald; Vaudel, Marc; Helsens, Kenny; Timmerman, Evy; Sickmann, Albert; Gevaert, Kris; Martens, Lennart

2011-08-05

The Thermo Proteome Discoverer program integrates both peptide identification and quantification into a single workflow for peptide-centric proteomics. Furthermore, its close integration with Thermo mass spectrometers has made it increasingly popular in the field. Here, we present a Java library to parse the msf files that constitute the output of Proteome Discoverer. The parser is also implemented as a graphical user interface allowing convenient access to the information found in the msf files, and in Rover, a program to analyze and validate quantitative proteomics information. All code, binaries, and documentation is freely available at http://thermo-msf-parser.googlecode.com.

Bovine Milk Comparative Proteome Analysis from Early, Mid, and Late Lactation in the Cattle Breed, Malnad Gidda (Bos indicus).

PubMed

Mol, Praseeda; Kannegundla, Uday; Dey, Gourav; Gopalakrishnan, Lathika; Dammalli, Manjunath; Kumar, Manish; Patil, Arun H; Basavaraju, Marappa; Rao, Akhila; Ramesha, Kerekoppa P; Prasad, Thottethodi Subrahmanya Keshava

2018-03-01

Bovine milk is important for both veterinary medicine and human nutrition. Understanding the bovine milk proteome at different stages of lactation has therefore broad significance for integrative biology and clinical medicine as well. Indeed, different lactation stages have marked influence on the milk yield, milk constituents, and nourishment of the neonates. We performed a comparative proteome analysis of the bovine milk obtained at different stages of lactation from the Indian indigenous cattle Malnad Gidda (Bos indicus), a widely available breed. The milk differential proteome during the lactation stages in B. indicus has not been investigated to date. Using high-resolution mass spectrometry-based quantitative proteomics of the bovine whey proteins at early, mid, and late lactation stages, we identified a total of 564 proteins, out of which 403 proteins were found to be differentially abundant at different lactation stages. As is expected of any body fluid proteome, 51% of the proteins identified in the milk were found to have signal peptides. Gene ontology analyses were carried out to categorize proteins altered across different lactation stages based on biological process and molecular function, which enabled us to correlate their significance in each lactation stage. We also investigated the potential pathways enriched in different lactation stages using bioinformatics pathway analysis tools. To the best of our knowledge, this study represents the first and largest inventory of milk proteins identified to date for an Indian cattle breed. We believe that the current study broadly informs both veterinary omics research and the emerging field of nutriproteomics during lactation stages.

Evaluation of a High Intensity Focused Ultrasound-Immobilized Trypsin Digestion and 18O-Labeling Method for Quantitative Proteomics

PubMed Central

López-Ferrer, Daniel; Hixson, Kim K.; Smallwood, Heather; Squier, Thomas C.; Petritis, Konstantinos; Smith, Richard D.

2009-01-01

A new method that uses immobilized trypsin concomitant with ultrasonic irradiation results in ultra-rapid digestion and thorough 18O labeling for quantitative protein comparisons. The reproducible and highly efficient method provided effective digestions in <1 min with a minimized amount of enzyme required compared to traditional methods. This method was demonstrated for digestion of both simple and complex protein mixtures, including bovine serum albumin, a global proteome extract from the bacteria Shewanella oneidensis, and mouse plasma, as well as 18O labeling of such complex protein mixtures, which validated the application of this method for differential proteomic measurements. This approach is simple, reproducible, cost effective, rapid, and thus well-suited for automation. PMID:19555078

Application of tissue mesodissection to molecular cancer diagnostics.

PubMed

Krizman, David; Adey, Nils; Parry, Robert

2015-02-01

To demonstrate clinical application of a mesodissection platform that was developed to combine advantages of laser-based instrumentation with the speed/ease of manual dissection for automated dissection of tissue off standard glass slides. Genomic analysis for KRAS gene mutation was performed on formalin fixed paraffin embedded (FFPE) cancer patient tissue that was dissected using the mesodissection platform. Selected reaction monitoring proteomic analysis for quantitative Her2 protein expression was performed on FFPE patient tumour tissue dissected by a laser-based instrument and the MilliSect instrument. Genomic analysis demonstrates highly confident detection of KRAS mutation specifically in lung cancer cells and not the surrounding benign, non-tumour tissue. Proteomic analysis demonstrates Her2 quantitative protein expression in breast cancer cells dissected manually, by laser-based instrumentation and by MilliSect instrumentation (mesodissection). Slide-mounted tissue dissection is commonly performed using laser-based instruments or manually scraping tissue by scalpel. Here we demonstrate that the mesodissection platform as performed by the MilliSect instrument for tissue dissection is cost-effective; it functions comparably to laser-based dissection and which can be adopted into a clinical diagnostic workflow. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

iTRAQ-Based Quantitative Proteomic Analysis of the Antimicrobial Mechanism of Peptide F1 against Escherichia coli.

PubMed

Miao, Jianyin; Chen, Feilong; Duan, Shan; Gao, Xiangyang; Liu, Guo; Chen, Yunjiao; Dixon, William; Xiao, Hang; Cao, Yong

2015-08-19

Antimicrobial peptides have received increasing attention in the agricultural and food industries due to their potential to control pathogens. However, to facilitate the development of novel peptide-based antimicrobial agents, details regarding the molecular mechanisms of these peptides need to be elucidated. The aim of this study was to investigate the antimicrobial mechanism of peptide F1, a bacteriocin found in Tibetan kefir, against Escherichia coli at protein levels using iTRAQ-based quantitative proteomic analysis. In response to treatment with peptide F1, 31 of the 280 identified proteins in E. coli showed alterations in their expression, including 10 down-regulated proteins and 21 up-regulated proteins. These 31 proteins all possess different molecular functions and are involved in different molecular pathways, as is evident in referencing the Kyoto Encyclopedia of Genes and Genomes pathways. Specifically, pathways that were significantly altered in E. coli in response to peptide F1 treatment include the tricarboxylic acid cycle, oxidative phosphorylation, glycerophospholipid metabolism, and the cell cycle-caulobacter pathways, which was also associated with inhibition of the cell growth, induction of morphological changes, and cell death. The results provide novel insights into the molecular mechanisms of antimicrobial peptides.

Candidate-based proteomics in the search for biomarkers of cardiovascular disease

PubMed Central

Anderson, Leigh

2005-01-01

The key concept of proteomics (looking at many proteins at once) opens new avenues in the search for clinically useful biomarkers of disease, treatment response and ageing. As the number of proteins that can be detected in plasma or serum (the primary clinical diagnostic samples) increases towards 1000, a paradoxical decline has occurred in the number of new protein markers approved for diagnostic use in clinical laboratories. This review explores the limitations of current proteomics protein discovery platforms, and proposes an alternative approach, applicable to a range of biological/physiological problems, in which quantitative mass spectrometric methods developed for analytical chemistry are employed to measure limited sets of candidate markers in large sets of clinical samples. A set of 177 candidate biomarker proteins with reported associations to cardiovascular disease and stroke are presented as a starting point for such a ‘directed proteomics’ approach. PMID:15611012

Methods, Tools and Current Perspectives in Proteogenomics *

PubMed Central

Ruggles, Kelly V.; Krug, Karsten; Wang, Xiaojing; Clauser, Karl R.; Wang, Jing; Payne, Samuel H.; Fenyö, David; Zhang, Bing; Mani, D. R.

2017-01-01

With combined technological advancements in high-throughput next-generation sequencing and deep mass spectrometry-based proteomics, proteogenomics, i.e. the integrative analysis of proteomic and genomic data, has emerged as a new research field. Early efforts in the field were focused on improving protein identification using sample-specific genomic and transcriptomic sequencing data. More recently, integrative analysis of quantitative measurements from genomic and proteomic studies have identified novel insights into gene expression regulation, cell signaling, and disease. Many methods and tools have been developed or adapted to enable an array of integrative proteogenomic approaches and in this article, we systematically classify published methods and tools into four major categories, (1) Sequence-centric proteogenomics; (2) Analysis of proteogenomic relationships; (3) Integrative modeling of proteogenomic data; and (4) Data sharing and visualization. We provide a comprehensive review of methods and available tools in each category and highlight their typical applications. PMID:28456751

Proteomic and N-glycoproteomic quantification reveal aberrant changes in the human saliva of oral ulcer patients.

PubMed

Zhang, Ying; Wang, Xi; Cui, Dan; Zhu, Jun

2016-12-01

Human whole saliva is a vital body fluid for studying the physiology and pathology of the oral cavity. As a powerful technique for biomarker discovery, MS-based proteomic strategies have been introduced for saliva analysis and identified hundreds of proteins and N-glycosylation sites. However, there is still a lack of quantitative analysis, which is necessary for biomarker screening and biological research. In this study, we establish an integrated workflow by the combination of stable isotope dimethyl labeling, HILIC enrichment, and high resolution MS for both quantification of the global proteome and N-glycoproteome of human saliva from oral ulcer patients. With the help of advanced bioinformatics, we comprehensively studied oral ulcers at both protein and glycoprotein scales. Bioinformatics analyses revealed that starch digestion and protein degradation activities are inhibited while the immune response is promoted in oral ulcer saliva. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Expanding Landscape of the Thiol Redox Proteome*

PubMed Central

Yang, Jing; Carroll, Kate S.; Liebler, Daniel C.

2016-01-01

Cysteine occupies a unique place in protein chemistry. The nucleophilic thiol group allows cysteine to undergo a broad range of redox modifications beyond classical thiol-disulfide redox equilibria, including S-sulfenylation (-SOH), S-sulfinylation (-SO2H), S-sulfonylation (-SO3H), S-nitrosylation (-SNO), S-sulfhydration (-SSH), S-glutathionylation (-SSG), and others. Emerging evidence suggests that these post-translational modifications (PTM) are important in cellular redox regulation and protection against oxidative damage. Identification of protein targets of thiol redox modifications is crucial to understanding their roles in biology and disease. However, analysis of these highly labile and dynamic modifications poses challenges. Recent advances in the design of probes for thiol redox forms, together with innovative mass spectrometry based chemoproteomics methods make it possible to perform global, site-specific, and quantitative analyses of thiol redox modifications in complex proteomes. Here, we review chemical proteomic strategies used to expand the landscape of thiol redox modifications. PMID:26518762

Proteomic landscape in Central and Eastern Europe: the 9th Central and Eastern European Proteomic Conference, Poznań, Poland.

PubMed

Gadher, Suresh Jivan; Marczak, Łukasz; Łuczak, Magdalena; Stobiecki, Maciej; Widlak, Piotr; Kovarova, Hana

2016-01-01

Every year since 2007, the Central and Eastern European Proteomic Conference (CEEPC) has excelled in representing state-of-the-art proteomics in and around Central and Eastern Europe, and linking it to international institutions worldwide. Its mission remains to contribute to all approaches of proteomics including traditional and often-revisited methodologies as well as the latest technological achievements in clinical, quantitative and structural proteomics with a view to systems biology of a variety of processes. The 9th CEEPC was held from June 15th to 18th, 2015, at the Institute of Bioorganic Chemistry, Polish Academy of Sciences in Poznań, Poland. The scientific program stimulated exchange of proteomic knowledge whilst the spectacular venue of the conference allowed participants to enjoy the cobblestoned historical city of Poznań.

Spatially-Resolved Proteomics: Rapid Quantitative Analysis of Laser Capture Microdissected Alveolar Tissue Samples

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

Clair, Geremy; Piehowski, Paul D.; Nicola, Teodora

Global proteomics approaches allow characterization of whole tissue lysates to an impressive depth. However, it is now increasingly recognized that to better understand the complexity of multicellular organisms, global protein profiling of specific spatially defined regions/substructures of tissues (i.e. spatially-resolved proteomics) is essential. Laser capture microdissection (LCM) enables microscopic isolation of defined regions of tissues preserving crucial spatial information. However, current proteomics workflows entail several manual sample preparation steps and are challenged by the microscopic mass-limited samples generated by LCM, and that impact measurement robustness, quantification, and throughput. Here, we coupled LCM with a fully automated sample preparation workflow thatmore » with a single manual step allows: protein extraction, tryptic digestion, peptide cleanup and LC-MS/MS analysis of proteomes from microdissected tissues. Benchmarking against the current state of the art in ultrasensitive global proteomic analysis, our approach demonstrated significant improvements in quantification and throughput. Using our LCM-SNaPP proteomics approach, we characterized to a depth of more than 3,400 proteins, the ontogeny of protein changes during normal lung development in laser capture microdissected alveolar tissue containing ~4,000 cells per sample. Importantly, the data revealed quantitative changes for 350 low abundance transcription factors and signaling molecules, confirming earlier transcript-level observations and defining seven modules of coordinated transcription factor/signaling molecule expression patterns, suggesting that a complex network of temporal regulatory control directs normal lung development with epigenetic regulation fine-tuning pre-natal developmental processes. Our LCM-proteomics approach facilitates efficient, spatially-resolved, ultrasensitive global proteomics analyses in high-throughput that will be enabling for several clinical and biological applications.« less

Global iTRAQ-based proteomic profiling of Toxoplasma gondii oocysts during sporulation.

PubMed

Zhou, Chun-Xue; Zhu, Xing-Quan; Elsheikha, Hany M; He, Shuai; Li, Qian; Zhou, Dong-Hui; Suo, Xun

2016-10-04

Toxoplasma gondii is a medically and economically important protozoan parasite. However, the molecular mechanisms of its sporulation remain largely unknown. Here, we applied iTRAQ coupled with 2D LC-MS/MS proteomic analysis to investigate the proteomic expression profile of T. gondii oocysts during sporulation. Of the 2095 non-redundant proteins identified, 587 were identified as differentially expressed proteins (DEPs). Based on Gene Ontology enrichment and KEGG pathway analyses the majority of these DEPs were found related to the metabolism of amino acids, carbon and energy. Protein interaction network analysis generated by STRING identified ATP-citrate lyase (ACL), GMP synthase, IMP dehydrogenase (IMPDH), poly (ADP-ribose) glycohydrolase (PARG), and bifunctional dihydrofolate reductase-thymidylate synthase (DHFR-TS) as the top five hubs. We also identified 25 parasite virulence factors that were expressed at relatively high levels in sporulated oocysts compared to non-sporulated oocysts, which might contribute to the infectivity of mature oocysts. Considering the importance of oocysts in the dissemination of toxoplasmosis these findings may help in the search of protein targets with a key role in infectiousness and ecological success of oocysts, creating new opportunities for the development of better means for disease prevention. The development of new preventative interventions against T. gondii infection relies on an improved understanding of the proteome and chemical pathways of this parasite. To identify proteins required for the development of environmentally resistant and infective T. gondii oocysts, we compared the proteome of non-sporulated (immature) oocysts with the proteome of sporulated (mature, infective) oocysts. iTRAQ 2D-LC-MS/MS analysis revealed proteomic changes that distinguish non-sporulated from sporulated oocysts. Many of the differentially expressed proteins were involved in metabolic pathways and 25 virulence factors were identified upregulated in the sporulated oocysts. This work provides the first quantitative characterization of the proteomic variations that occur in T. gondii oocyst stage during sporulation. Copyright © 2016. Published by Elsevier B.V.

Quantitative proteomic view associated with resistance to clinically important antibiotics in Gram-positive bacteria: a systematic review

PubMed Central

Lee, Chang-Ro; Lee, Jung Hun; Park, Kwang Seung; Jeong, Byeong Chul; Lee, Sang Hee

2015-01-01

The increase of methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus (VRE) poses a worldwide and serious health threat. Although new antibiotics, such as daptomycin and linezolid, have been developed for the treatment of infections of Gram-positive pathogens, the emergence of daptomycin-resistant and linezolid-resistant strains during therapy has now increased clinical treatment failures. In the past few years, studies using quantitative proteomic methods have provided a considerable progress in understanding antibiotic resistance mechanisms. In this review, to understand the resistance mechanisms to four clinically important antibiotics (methicillin, vancomycin, linezolid, and daptomycin) used in the treatment of Gram-positive pathogens, we summarize recent advances in studies on resistance mechanisms using quantitative proteomic methods, and also examine proteins playing an important role in the bacterial mechanisms of resistance to the four antibiotics. Proteomic researches can identify proteins whose expression levels are changed in the resistance mechanism to only one antibiotic, such as LiaH in daptomycin resistance and PrsA in vancomycin resistance, and many proteins simultaneously involved in resistance mechanisms to various antibiotics. Most of resistance-related proteins, which are simultaneously associated with resistance mechanisms to several antibiotics, play important roles in regulating bacterial envelope biogenesis, or compensating for the fitness cost of antibiotic resistance. Therefore, proteomic data confirm that antibiotic resistance requires the fitness cost and the bacterial envelope is an important factor in antibiotic resistance. PMID:26322035

The developmental proteome of Drosophila melanogaster

PubMed Central

Casas-Vila, Nuria; Bluhm, Alina; Sayols, Sergi; Dinges, Nadja; Dejung, Mario; Altenhein, Tina; Kappei, Dennis; Altenhein, Benjamin; Roignant, Jean-Yves; Butter, Falk

2017-01-01

Drosophila melanogaster is a widely used genetic model organism in developmental biology. While this model organism has been intensively studied at the RNA level, a comprehensive proteomic study covering the complete life cycle is still missing. Here, we apply label-free quantitative proteomics to explore proteome remodeling across Drosophila’s life cycle, resulting in 7952 proteins, and provide a high temporal-resolved embryogenesis proteome of 5458 proteins. Our proteome data enabled us to monitor isoform-specific expression of 34 genes during development, to identify the pseudogene Cyp9f3Ψ as a protein-coding gene, and to obtain evidence of 268 small proteins. Moreover, the comparison with available transcriptomic data uncovered examples of poor correlation between mRNA and protein, underscoring the importance of proteomics to study developmental progression. Data integration of our embryogenesis proteome with tissue-specific data revealed spatial and temporal information for further functional studies of yet uncharacterized proteins. Overall, our high resolution proteomes provide a powerful resource and can be explored in detail in our interactive web interface. PMID:28381612

Advancing Cell Biology Through Proteomics in Space and Time (PROSPECTS)*

PubMed Central

Lamond, Angus I.; Uhlen, Mathias; Horning, Stevan; Makarov, Alexander; Robinson, Carol V.; Serrano, Luis; Hartl, F. Ulrich; Baumeister, Wolfgang; Werenskiold, Anne Katrin; Andersen, Jens S.; Vorm, Ole; Linial, Michal; Aebersold, Ruedi; Mann, Matthias

2012-01-01

The term “proteomics” encompasses the large-scale detection and analysis of proteins and their post-translational modifications. Driven by major improvements in mass spectrometric instrumentation, methodology, and data analysis, the proteomics field has burgeoned in recent years. It now provides a range of sensitive and quantitative approaches for measuring protein structures and dynamics that promise to revolutionize our understanding of cell biology and molecular mechanisms in both human cells and model organisms. The Proteomics Specification in Time and Space (PROSPECTS) Network is a unique EU-funded project that brings together leading European research groups, spanning from instrumentation to biomedicine, in a collaborative five year initiative to develop new methods and applications for the functional analysis of cellular proteins. This special issue of Molecular and Cellular Proteomics presents 16 research papers reporting major recent progress by the PROSPECTS groups, including improvements to the resolution and sensitivity of the Orbitrap family of mass spectrometers, systematic detection of proteins using highly characterized antibody collections, and new methods for absolute as well as relative quantification of protein levels. Manuscripts in this issue exemplify approaches for performing quantitative measurements of cell proteomes and for studying their dynamic responses to perturbation, both during normal cellular responses and in disease mechanisms. Here we present a perspective on how the proteomics field is moving beyond simply identifying proteins with high sensitivity toward providing a powerful and versatile set of assay systems for characterizing proteome dynamics and thereby creating a new “third generation” proteomics strategy that offers an indispensible tool for cell biology and molecular medicine. PMID:22311636

A Targeted MRM Approach for Tempo-Spatial Proteomics Analyses.

PubMed

Moradian, Annie; Porras-Yakushi, Tanya R; Sweredoski, Michael J; Hess, Sonja

2016-01-01

When deciding to perform a quantitative proteomics analysis, selectivity, sensitivity, and reproducibility are important criteria to consider. The use of multiple reaction monitoring (MRM) has emerged as a powerful proteomics technique in that regard since it avoids many of the problems typically observed in discovery-based analyses. A prerequisite for such a targeted approach is that the protein targets are known, either as a result of previous global proteomics experiments or because a specific hypothesis is to be tested. When guidelines that have been established in the pharmaceutical industry many decades ago are taken into account, setting up an MRM assay is relatively straightforward. Typically, proteotypic peptides with favorable mass spectrometric properties are synthesized with a heavy isotope for each protein that is to be monitored. Retention times and calibration curves are determined using triple-quadrupole mass spectrometers. The use of iRT peptide standards is both recommended and fully integrated into the bioinformatics pipeline. Digested biological samples are mixed with the heavy and iRT standards and quantified. Here we present a generic protocol for the development of an MRM assay.

Efficient Exploitation of Separation Space in Two-Dimensional Liquid Chromatography System for Comprehensive and Efficient Proteomic Analyses.

PubMed

Lee, Hangyeore; Mun, Dong-Gi; So, Jeong Eun; Bae, Jingi; Kim, Hokeun; Masselon, Christophe; Lee, Sang-Won

2016-12-06

Proteomics aims to achieve complete profiling of the protein content and protein modifications in cells, tissues, and biofluids and to quantitatively determine changes in their abundances. This information serves to elucidate cellular processes and signaling pathways and to identify candidate protein biomarkers and/or therapeutic targets. Analyses must therefore be both comprehensive and efficient. Here, we present a novel online two-dimensional reverse-phase/reverse-phase liquid chromatography separation platform, which is based on a newly developed online noncontiguous fractionating and concatenating device (NCFC fractionator). In bottom-up proteomics analyses of a complex proteome, this system provided significantly improved exploitation of the separation space of the two RPs, considerably increasing the numbers of peptides identified compared to a contiguous 2D-RP/RPLC method. The fully automated online 2D-NCFC-RP/RPLC system bypassed a number of labor-intensive manual processes required with the previously described offline 2D-NCFC RP/RPLC method, and thus, it offers minimal sample loss in a context of highly reproducible 2D-RP/RPLC experiments.

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.

Mass Defect Labeling of Cysteine for Improving Peptide Assignment in Shotgun Proteomic Analyses

PubMed Central

Hernandez, Hilda; Niehauser, Sarah; Boltz, Stacey A.; Gawandi, Vijay; Phillips, Robert S.; Amster, I. Jonathan

2006-01-01

A method for improving the identification of peptides in a shotgun proteome analysis using accurate mass measurement has been developed. The improvement is based upon the derivatization of cysteine residues with a novel reagent, 2,4-dibromo-(2′-iodo)acetanilide. The derivitization changes the mass defect of cysteine-containing proteolytic peptides in a manner that increases their identification specificity. Peptide masses were measured using matrix-assisted laser desorption/ionization Fourier transform ion cyclotron mass spectrometry. Reactions with protein standards show that the derivatization of cysteine is rapid and quantitative, and the data suggest that the derivatized peptides are more easily ionized or detected than unlabeled cysteine-containing peptides. The reagent was tested on a 15N-metabolically labeled proteome from M. maripaludis. Proteins were identified by their accurate mass values and from their nitrogen stoichiometry. A total of 47% of the labeled peptides are identified versus 27% for the unlabeled peptides. This procedure permits the identification of proteins from the M. maripaludis proteome that are not usually observed by the standard protocol and shows that better protein coverage is obtained with this methodology. PMID:16689545

Proteomic Challenges: Sample Preparation Techniques for Microgram-Quantity Protein Analysis from Biological Samples

PubMed Central

Feist, Peter; Hummon, Amanda B.

2015-01-01

Proteins regulate many cellular functions and analyzing the presence and abundance of proteins in biological samples are central focuses in proteomics. The discovery and validation of biomarkers, pathways, and drug targets for various diseases can be accomplished using mass spectrometry-based proteomics. However, with mass-limited samples like tumor biopsies, it can be challenging to obtain sufficient amounts of proteins to generate high-quality mass spectrometric data. Techniques developed for macroscale quantities recover sufficient amounts of protein from milligram quantities of starting material, but sample losses become crippling with these techniques when only microgram amounts of material are available. To combat this challenge, proteomicists have developed micro-scale techniques that are compatible with decreased sample size (100 μg or lower) and still enable excellent proteome coverage. Extraction, contaminant removal, protein quantitation, and sample handling techniques for the microgram protein range are reviewed here, with an emphasis on liquid chromatography and bottom-up mass spectrometry-compatible techniques. Also, a range of biological specimens, including mammalian tissues and model cell culture systems, are discussed. PMID:25664860

The mzqLibrary – An open source Java library supporting the HUPO‐PSI quantitative proteomics standard

PubMed Central

Zhang, Huaizhong; Fan, Jun; Perkins, Simon; Pisconti, Addolorata; Simpson, Deborah M.; Bessant, Conrad; Hubbard, Simon; Jones, Andrew R.

2015-01-01

The mzQuantML standard has been developed by the Proteomics Standards Initiative for capturing, archiving and exchanging quantitative proteomic data, derived from mass spectrometry. It is a rich XML‐based format, capable of representing data about two‐dimensional features from LC‐MS data, and peptides, proteins or groups of proteins that have been quantified from multiple samples. In this article we report the development of an open source Java‐based library of routines for mzQuantML, called the mzqLibrary, and associated software for visualising data called the mzqViewer. The mzqLibrary contains routines for mapping (peptide) identifications on quantified features, inference of protein (group)‐level quantification values from peptide‐level values, normalisation and basic statistics for differential expression. These routines can be accessed via the command line, via a Java programming interface access or a basic graphical user interface. The mzqLibrary also contains several file format converters, including import converters (to mzQuantML) from OpenMS, Progenesis LC‐MS and MaxQuant, and exporters (from mzQuantML) to other standards or useful formats (mzTab, HTML, csv). The mzqViewer contains in‐built routines for viewing the tables of data (about features, peptides or proteins), and connects to the R statistical library for more advanced plotting options. The mzqLibrary and mzqViewer packages are available from https://code.google.com/p/mzq‐lib/. PMID:26037908

SWATH Mass Spectrometry Performance Using Extended Peptide MS/MS Assay Libraries.

PubMed

Wu, Jemma X; Song, Xiaomin; Pascovici, Dana; Zaw, Thiri; Care, Natasha; Krisp, Christoph; Molloy, Mark P

2016-07-01

The use of data-independent acquisition methods such as SWATH for mass spectrometry based proteomics is usually performed with peptide MS/MS assay libraries which enable identification and quantitation of peptide peak areas. Reference assay libraries can be generated locally through information dependent acquisition, or obtained from community data repositories for commonly studied organisms. However, there have been no studies performed to systematically evaluate how locally generated or repository-based assay libraries affect SWATH performance for proteomic studies. To undertake this analysis, we developed a software workflow, SwathXtend, which generates extended peptide assay libraries by integration with a local seed library and delivers statistical analysis of SWATH-quantitative comparisons. We designed test samples using peptides from a yeast extract spiked into peptides from human K562 cell lysates at three different ratios to simulate protein abundance change comparisons. SWATH-MS performance was assessed using local and external assay libraries of varying complexities and proteome compositions. These experiments demonstrated that local seed libraries integrated with external assay libraries achieve better performance than local assay libraries alone, in terms of the number of identified peptides and proteins and the specificity to detect differentially abundant proteins. Our findings show that the performance of extended assay libraries is influenced by the MS/MS feature similarity of the seed and external libraries, while statistical analysis using multiple testing corrections increases the statistical rigor needed when searching against large extended assay libraries. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

SWATH Mass Spectrometry Performance Using Extended Peptide MS/MS Assay Libraries*

PubMed Central

Wu, Jemma X.; Song, Xiaomin; Pascovici, Dana; Zaw, Thiri; Care, Natasha; Krisp, Christoph; Molloy, Mark P.

2016-01-01

The use of data-independent acquisition methods such as SWATH for mass spectrometry based proteomics is usually performed with peptide MS/MS assay libraries which enable identification and quantitation of peptide peak areas. Reference assay libraries can be generated locally through information dependent acquisition, or obtained from community data repositories for commonly studied organisms. However, there have been no studies performed to systematically evaluate how locally generated or repository-based assay libraries affect SWATH performance for proteomic studies. To undertake this analysis, we developed a software workflow, SwathXtend, which generates extended peptide assay libraries by integration with a local seed library and delivers statistical analysis of SWATH-quantitative comparisons. We designed test samples using peptides from a yeast extract spiked into peptides from human K562 cell lysates at three different ratios to simulate protein abundance change comparisons. SWATH-MS performance was assessed using local and external assay libraries of varying complexities and proteome compositions. These experiments demonstrated that local seed libraries integrated with external assay libraries achieve better performance than local assay libraries alone, in terms of the number of identified peptides and proteins and the specificity to detect differentially abundant proteins. Our findings show that the performance of extended assay libraries is influenced by the MS/MS feature similarity of the seed and external libraries, while statistical analysis using multiple testing corrections increases the statistical rigor needed when searching against large extended assay libraries. PMID:27161445

iTRAQ-based Quantitative Proteomics Study in Patients with Refractory Mycoplasma pneumoniae Pneumonia.

PubMed

Yu, Jia-Lu; Song, Qi-Fang; Xie, Zhi-Wei; Jiang, Wen-Hui; Chen, Jia-Hui; Fan, Hui-Feng; Xie, Ya-Ping; Lu, Gen

2017-09-25

Mycoplasma pneumoniae (MP) is a leading cause of community-acquired pneumonia in children and young adults. Although MP pneumonia is usually benign and self-limited, in some cases it can develop into life-threating refractory MP pneumonia (RMPP). However, the pathogenesis of RMPP is poorly understood. The identification and characterization of proteins related to RMPP could provide a proof of principle to facilitate appropriate diagnostic and therapeutic strategies for treating paients with MP. In this study, we used a quantitative proteomic technique (iTRAQ) to analyze MP-related proteins in serum samples from 5 patients with RMPP, 5 patients with non-refractory MP pneumonia (NRMPP), and 5 healthy children. Functional classification, sub-cellular localization, and protein interaction network analysis were carried out based on protein annotation through evolutionary relationship (PANTHER) and Cytoscape analysis. A total of 260 differentially expressed proteins were identified in the RMPP and NRMPP groups. Compared to the control group, the NRMPP and RMPP groups showed 134 (70 up-regulated and 64 down-regulated) and 126 (63 up-regulated and 63 down-regulated) differentially expressed proteins, respectively. The complex functional classification and protein interaction network of the identified proteins reflected the complex pathogenesis of RMPP. Our study provides the first comprehensive proteome map of RMPP-related proteins from MP pneumonia. These profiles may be useful as part of a diagnostic panel, and the identified proteins provide new insights into the pathological mechanisms underlying RMPP.

Structural and metabolic transitions of C4 leaf development and differentiation defined by microscopy and quantitative proteomics in maize.

PubMed

Majeran, Wojciech; Friso, Giulia; Ponnala, Lalit; Connolly, Brian; Huang, Mingshu; Reidel, Edwin; Zhang, Cankui; Asakura, Yukari; Bhuiyan, Nazmul H; Sun, Qi; Turgeon, Robert; van Wijk, Klaas J

2010-11-01

C(4) grasses, such as maize (Zea mays), have high photosynthetic efficiency through combined biochemical and structural adaptations. C(4) photosynthesis is established along the developmental axis of the leaf blade, leading from an undifferentiated leaf base just above the ligule into highly specialized mesophyll cells (MCs) and bundle sheath cells (BSCs) at the tip. To resolve the kinetics of maize leaf development and C(4) differentiation and to obtain a systems-level understanding of maize leaf formation, the accumulation profiles of proteomes of the leaf and the isolated BSCs with their vascular bundle along the developmental gradient were determined using large-scale mass spectrometry. This was complemented by extensive qualitative and quantitative microscopy analysis of structural features (e.g., Kranz anatomy, plasmodesmata, cell wall, and organelles). More than 4300 proteins were identified and functionally annotated. Developmental protein accumulation profiles and hierarchical cluster analysis then determined the kinetics of organelle biogenesis, formation of cellular structures, metabolism, and coexpression patterns. Two main expression clusters were observed, each divided in subclusters, suggesting that a limited number of developmental regulatory networks organize concerted protein accumulation along the leaf gradient. The coexpression with BSC and MC markers provided strong candidates for further analysis of C(4) specialization, in particular transporters and biogenesis factors. Based on the integrated information, we describe five developmental transitions that provide a conceptual and practical template for further analysis. An online protein expression viewer is provided through the Plant Proteome Database.

Proteomic profiling in MPTP monkey model for early Parkinson disease biomarker discovery

PubMed Central

Lin, Xiangmin; Shi, Min; Gunasingh Masilamoni, Jeyaraj; Dator, Romel; Movius, James; Aro, Patrick; Smith, Yoland; Zhang, Jing

2015-01-01

Identification of reliable and robust biomarkers is crucial to enable early diagnosis of Parkinson disease (PD) and monitoring disease progression. While imperfect, the slow, chronic 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced non-human primate animal model system of parkinsonism is an abundant source of pre-motor or early stage PD biomarker discovery. Here, we present a study of a MPTP rhesus monkey model of PD that utilizes complementary quantitative iTRAQ-based proteomic, glycoproteomics and phosphoproteomics approaches. We compared the glycoprotein, non-glycoprotein, and phosphoprotein profiles in the putamen of asymptomatic and symptomatic MPTP-treated monkeys as well as saline injected controls. We identified 86 glycoproteins, 163 non-glycoproteins, and 71 phosphoproteins differentially expressed in the MPTP-treated groups. Functional analysis of the data sets inferred the biological processes and pathways that link to neurodegeneration in PD and related disorders. Several potential biomarkers identified in this study have already been translated for their usefulness in PD diagnosis in human subjects and further validation investigations are currently under way. In addition to providing potential early PD biomarkers, this comprehensive quantitative proteomic study may also shed insights regarding the mechanisms underlying early PD development. This article is part of a Special Issue entitled: Neuroproteomics: Applications in neuroscience and neurology. PMID:25617661

Quantitative Proteomic Analysis of Differentially Expressed Protein Profiles Involved in Pancreatic Ductal Adenocarcinoma

PubMed Central

Kuo, Kung-Kai; Kuo, Chao-Jen; Chiu, Chiang-Yen; Liang, Shih-Shin; Huang, Chun-Hao; Chi, Shu-Wen; Tsai, Kun-Bow; Chen, Chiao-Yun; Hsi, Edward; Cheng, Kuang-Hung; Chiou, Shyh-Horng

2016-01-01

Objectives The aim of this study was to identify differentially expressed proteins among various stages of pancreatic ductal adenocarcinoma (PDAC) by shotgun proteomics using nano-liquid chromatography coupled tandem mass spectrometry and stable isotope dimethyl labeling. Methods Differentially expressed proteins were identified and compared based on the mass spectral differences of their isotope-labeled peptide fragments generated from protease digestion. Results Our quantitative proteomic analysis of the differentially expressed proteins with stable isotope (deuterium/hydrogen ratio, ≥2) identified a total of 353 proteins, with at least 5 protein biomarker proteins that were significantly differentially expressed between cancer and normal mice by at least a 2-fold alteration. These 5 protein biomarker candidates include α-enolase, α-catenin, 14-3-3 β, VDAC1, and calmodulin with high confidence levels. The expression levels were also found to be in agreement with those examined by Western blot and histochemical staining. Conclusions The systematic decrease or increase of these identified marker proteins may potentially reflect the morphological aberrations and diseased stages of pancreas carcinoma throughout progressive developments leading to PDAC. The results would form a firm foundation for future work concerning validation and clinical translation of some identified biomarkers into targeted diagnosis and therapy for various stages of PDAC. PMID:26262590

Quantitative Proteomics Reveals Membrane Protein-Mediated Hypersaline Sensitivity and Adaptation in Halophilic Nocardiopsis xinjiangensis.

PubMed

Zhang, Yao; Li, Yanchang; Zhang, Yongguang; Wang, Zhiqiang; Zhao, Mingzhi; Su, Na; Zhang, Tao; Chen, Lingsheng; Wei, Wei; Luo, Jing; Zhou, Yanxia; Xu, Yongru; Xu, Ping; Li, Wenjun; Tao, Yong

2016-01-04

The genus Nocardiopsis is one of the most dominant Actinobacteria that survives in hypersaline environments. However, the adaptation mechanisms for halophilism are still unclear. Here, we performed isobaric tags for relative and absolute quantification based quantitative proteomics to investigate the functions of the membrane proteome after salt stress. A total of 683 membrane proteins were identified and quantified, of which 126 membrane proteins displayed salt-induced changes in abundance. Intriguingly, bioinformatics analyses indicated that these differential proteins showed two expression patterns, which were further validated by phenotypic changes and functional differences. The majority of ABC transporters, secondary active transporters, cell motility proteins, and signal transduction kinases were up-regulated with increasing salt concentration, whereas cell differentiation, small molecular transporter (ions and amino acids), and secondary metabolism proteins were significantly up-regulated at optimum salinity, but down-regulated or unchanged at higher salinity. The small molecule transporters and cell differentiation-related proteins acted as sensing proteins that played a more important biological role at optimum salinity. However, the ABC transporters for compatible solutes, Na(+)-dependent transporters, and cell motility proteins acted as adaptive proteins that actively counteracted higher salinity stress. Overall, regulation of membrane proteins may provide a major protection strategy against hyperosmotic stress.

Understanding rice plant resistance to the Brown Planthopper (Nilaparvata lugens): a proteomic approach.

PubMed

Wei, Zhe; Hu, Wei; Lin, Qishan; Cheng, Xiaoyan; Tong, Mengjie; Zhu, Lili; Chen, Rongzhi; He, Guangcun

2009-05-01

Engineering and breeding resistant plant varieties are the most effective and environmentally friendly ways to control agricultural pests and improve crop performance. However, the mechanism of plant resistance to pests is poorly understood. Here we used a quantitative mass-spectrometry-based proteomic approach for comparative analysis of expression profiles of proteins in rice leaf sheaths in responses to infestation by the brown planthopper (Nilaparvata lugens Stål, BPH), which is a serious rice crop pest. Proteins involved in multiple pathways showed significant changes in expression in response to BPH feeding, including jasmonic acid synthesis proteins, oxidative stress response proteins, beta-glucanases, protein; kinases, clathrin protein, glycine cleavage system protein, photosynthesis proteins and aquaporins. The corresponding genes of eight important proteins were further analyzed by quantitative RT-PCR. Proteomic and transcript responses that were related to wounding, oxidative and pathogen stress overlapped considerably between BPH-resistant (carrying the resistance gene BPH15) and susceptible rice lines. In contrast, proteins and genes related to callose metabolism remained unchanged and glycine cleavage system protein was up-regulated in the BPH-resistant lines, indicating that they have an efficient and specific defense mechanism. Our results provide new information about the interaction between rice and the BPH.

Mass spectrometry-based targeted quantitative proteomics: achieving sensitive and reproducible detection of proteins.

PubMed

Boja, Emily S; Rodriguez, Henry

2012-04-01

Traditional shotgun proteomics used to detect a mixture of hundreds to thousands of proteins through mass spectrometric analysis, has been the standard approach in research to profile protein content in a biological sample which could lead to the discovery of new (and all) protein candidates with diagnostic, prognostic, and therapeutic values. In practice, this approach requires significant resources and time, and does not necessarily represent the goal of the researcher who would rather study a subset of such discovered proteins (including their variations or posttranslational modifications) under different biological conditions. In this context, targeted proteomics is playing an increasingly important role in the accurate measurement of protein targets in biological samples in the hope of elucidating the molecular mechanism of cellular function via the understanding of intricate protein networks and pathways. One such (targeted) approach, selected reaction monitoring (or multiple reaction monitoring) mass spectrometry (MRM-MS), offers the capability of measuring multiple proteins with higher sensitivity and throughput than shotgun proteomics. Developing and validating MRM-MS-based assays, however, is an extensive and iterative process, requiring a coordinated and collaborative effort by the scientific community through the sharing of publicly accessible data and datasets, bioinformatic tools, standard operating procedures, and well characterized reagents. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparative proteomic analysis of outer membrane protein 43 (omp43)-deficient Bartonella henselae.

PubMed

Kang, Jun-Gu; Lee, Hee-Woo; Ko, Sungjin; Chae, Joon-Seok

2018-01-31

Outer membrane proteins (OMPs) of Gram-negative bacteria constitute the first line of defense protecting cells against environmental stresses including chemical, biophysical, and biological attacks. Although the 43-kDa OMP (OMP43) is major porin protein among Bartonella henselae -derived OMPs, its function remains unreported. In this study, OMP43-deficient mutant B. henselae (Δomp43) was generated to investigate OMP43 function. Interestingly, Δ omp 43 exhibited weaker proliferative ability than that of wild-type (WT) B. henselae . To study the differences in proteomic expression between WT and Δ omp 43, two-dimensional gel electrophoresis-based proteomic analysis was performed. Based on Clusters of Orthologus Groups functional assignments, 12 proteins were associated with metabolism, 7 proteins associated with information storage and processing, and 3 proteins associated with cellular processing and signaling. By semi-quantitative reverse transcriptase polymerase chain reaction, increases in tld D, efp, ntr X, pdh A, pur B, and ATPA mRNA expression and decreases in Rho and yfe A mRNA expression were confirmed in Δ omp 43. In conclusion, this is the first report showing that a loss of OMP43 expression in B. henselae leads to retarded proliferation. Furthermore, our proteomic data provide useful information for the further investigation of mechanisms related to the growth of B. henselae.

Understanding the Mechanism of Thermotolerance Distinct From Heat Shock Response Through Proteomic Analysis of Industrial Strains of Saccharomyces cerevisiae*

PubMed Central

Shui, Wenqing; Xiong, Yun; Xiao, Weidi; Qi, Xianni; Zhang, Yong; Lin, Yuping; Guo, Yufeng; Zhang, Zhidan; Wang, Qinhong; Ma, Yanhe

2015-01-01

Saccharomyces cerevisiae has been intensively studied in responses to different environmental stresses such as heat shock through global omic analysis. However, the S. cerevisiae industrial strains with superior thermotolerance have not been explored in any proteomic studies for elucidating the tolerance mechanism. Recently a new diploid strain was obtained through evolutionary engineering of a parental industrial strain, and it exhibited even higher resistance to prolonged thermal stress. Herein, we performed iTRAQ-based quantitative proteomic analysis on both the parental and evolved industrial strains to further understand the mechanism of thermotolerant adaptation. Out of ∼2600 quantifiable proteins from biological quadruplicates, 193 and 204 proteins were differentially regulated in the parental and evolved strains respectively during heat-stressed growth. The proteomic response of the industrial strains cultivated under prolonged thermal stress turned out to be substantially different from that of the laboratory strain exposed to sudden heat shock. Further analysis of transcription factors underlying the proteomic perturbation also indicated the distinct regulatory mechanism of thermotolerance. Finally, a cochaperone Mdj1 and a metabolic enzyme Adh1 were selected to investigate their roles in mediating heat-stressed growth and ethanol production of yeasts. Our proteomic characterization of the industrial strain led to comprehensive understanding of the molecular basis of thermotolerance, which would facilitate future improvement in the industrially important trait of S. cerevisiae by rational engineering. PMID:25926660

Opportunities and Challenges for Nutritional Proteomics in Cancer Prevention12

PubMed Central

Romagnolo, Donato F.; Milner, John A.

2012-01-01

Knowledge gaps persist about the efficacy of cancer prevention strategies based on dietary food components. Adaptations to nutrient supply are executed through tuning of multiple protein networks that include transcription factors, histones, modifying enzymes, translation factors, membrane and nuclear receptors, and secreted proteins. However, the simultaneous quantitative and qualitative measurement of all proteins that regulate cancer processes is not practical using traditional protein methodologies. Proteomics offers an attractive opportunity to fill this knowledge gap and unravel the effects of dietary components on protein networks that impinge on cancer. The articles presented in this supplement are from talks proffered in the “Nutrition Proteomics and Cancer Prevention” session at the American Institute for Cancer Research Annual Research Conference on Food, Nutrition, Physical Activity and Cancer held in Washington, DC on October 21 and 22, 2010. Recent advances in MS technologies suggest that studies in nutrition and cancer prevention may benefit from the adoption of proteomic tools to elucidate the impact on biological processes that govern the transition from normal to malignant phenotype; to identify protein changes that determine both positive and negative responses to food components; to assess how protein networks mediate dose-, time-, and tissue-dependent responses to food components; and, finally, for predicting responders and nonresponders. However, both the limited accessibility to proteomic technologies and research funding appear to be hampering the routine adoption of proteomic tools in nutrition and cancer prevention research. PMID:22649262

Mspire-Simulator: LC-MS shotgun proteomic simulator for creating realistic gold standard data.

PubMed

Noyce, Andrew B; Smith, Rob; Dalgleish, James; Taylor, Ryan M; Erb, K C; Okuda, Nozomu; Prince, John T

2013-12-06

The most important step in any quantitative proteomic pipeline is feature detection (aka peak picking). However, generating quality hand-annotated data sets to validate the algorithms, especially for lower abundance peaks, is nearly impossible. An alternative for creating gold standard data is to simulate it with features closely mimicking real data. We present Mspire-Simulator, a free, open-source shotgun proteomic simulator that goes beyond previous simulation attempts by generating LC-MS features with realistic m/z and intensity variance along with other noise components. It also includes machine-learned models for retention time and peak intensity prediction and a genetic algorithm to custom fit model parameters for experimental data sets. We show that these methods are applicable to data from three different mass spectrometers, including two fundamentally different types, and show visually and analytically that simulated peaks are nearly indistinguishable from actual data. Researchers can use simulated data to rigorously test quantitation software, and proteomic researchers may benefit from overlaying simulated data on actual data sets.

Mapping the Extracellular and Membrane Proteome Associated with the Vasculature and the Stroma in the Embryo*

PubMed Central

Soulet, Fabienne; Kilarski, Witold W.; Roux-Dalvai, Florence; Herbert, John M. J.; Sacewicz, Izabela; Mouton-Barbosa, Emmanuelle; Bicknell, Roy; Lalor, Patricia; Monsarrat, Bernard; Bikfalvi, Andreas

2013-01-01

In order to map the extracellular or membrane proteome associated with the vasculature and the stroma in an embryonic organism in vivo, we developed a biotinylation technique for chicken embryo and combined it with mass spectrometry and bioinformatic analysis. We also applied this procedure to implanted tumors growing on the chorioallantoic membrane or after the induction of granulation tissue. Membrane and extracellular matrix proteins were the most abundant components identified. Relative quantitative analysis revealed differential protein expression patterns in several tissues. Through a bioinformatic approach, we determined endothelial cell protein expression signatures, which allowed us to identify several proteins not yet reported to be associated with endothelial cells or the vasculature. This is the first study reported so far that applies in vivo biotinylation, in combination with robust label-free quantitative proteomics approaches and bioinformatic analysis, to an embryonic organism. It also provides the first description of the vascular and matrix proteome of the embryo that might constitute the starting point for further developments. PMID:23674615

Proteomic Adaptations to Starvation Prepare Escherichia coli for Disinfection Tolerance

PubMed Central

Du, Zhe; Nandakumar, Renu; Nickerson, Kenneth; Li, Xu

2015-01-01

Despite the low nutrient level and constant presence of secondary disinfectants, bacterial re-growth still occurs in drinking water distribution systems. The molecular mechanisms that starved bacteria use to survive low-level chlorine-based disinfectants are not well understood. The objective of this study is to investigate these molecular mechanisms at the protein level that prepare starved cells for disinfection tolerance. Two commonly used secondary disinfectants chlorine and monochloramine, both at 1 mg/L, were used in this study. The proteomes of normal and starved Escherichia coli (K12 MG1655) cells were studied using quantitative proteomics. Over 60-min disinfection, starved cells showed significantly higher disinfection tolerance than normal cells based on the inactivation curves for both chlorine and monochloramine. Proteomic analyses suggest that starvation may prepare cells for the oxidative stress that chlorine-based disinfection will cause by affecting glutathione metabolism. In addition, proteins involved in stress regulation and stress responses were among the ones up-regulated under both starvation and chlorine/monochloramine disinfection. By comparing the fold changes under different conditions, it is suggested that starvation prepares E. coli for disinfection tolerance by increasing the expression of enzymes that can help cells survive chlorine/monochloramine disinfection. Protein co-expression analyses show that proteins in glycolysis and pentose phosphate pathway that were up-regulated under starvation are also involved in disinfection tolerance. Finally, the production and detoxification of methylglyoxal may be involved in the chlorine-based disinfection and cell defense mechanisms. PMID:25463932

Proteomic adaptations to starvation prepare Escherichia coli for disinfection tolerance.

PubMed

Du, Zhe; Nandakumar, Renu; Nickerson, Kenneth W; Li, Xu

2015-02-01

Despite the low nutrient level and constant presence of secondary disinfectants, bacterial re-growth still occurs in drinking water distribution systems. The molecular mechanisms that starved bacteria use to survive low-level chlorine-based disinfectants are not well understood. The objective of this study is to investigate these molecular mechanisms at the protein level that prepare starved cells for disinfection tolerance. Two commonly used secondary disinfectants chlorine and monochloramine, both at 1 mg/L, were used in this study. The proteomes of normal and starved Escherichia coli (K12 MG1655) cells were studied using quantitative proteomics. Over 60-min disinfection, starved cells showed significantly higher disinfection tolerance than normal cells based on the inactivation curves for both chlorine and monochloramine. Proteomic analyses suggest that starvation may prepare cells for the oxidative stress that chlorine-based disinfection will cause by affecting glutathione metabolism. In addition, proteins involved in stress regulation and stress responses were among the ones up-regulated under both starvation and chlorine/monochloramine disinfection. By comparing the fold changes under different conditions, it is suggested that starvation prepares E. coli for disinfection tolerance by increasing the expression of enzymes that can help cells survive chlorine/monochloramine disinfection. Protein co-expression analyses show that proteins in glycolysis and pentose phosphate pathway that were up-regulated under starvation are also involved in disinfection tolerance. Finally, the production and detoxification of methylglyoxal may be involved in the chlorine-based disinfection and cell defense mechanisms. Copyright © 2014 Elsevier Ltd. All rights reserved.

A flexible statistical model for alignment of label-free proteomics data – incorporating ion mobility and product ion information

PubMed Central

2013-01-01

Background The goal of many proteomics experiments is to determine the abundance of proteins in biological samples, and the variation thereof in various physiological conditions. High-throughput quantitative proteomics, specifically label-free LC-MS/MS, allows rapid measurement of thousands of proteins, enabling large-scale studies of various biological systems. Prior to analyzing these information-rich datasets, raw data must undergo several computational processing steps. We present a method to address one of the essential steps in proteomics data processing - the matching of peptide measurements across samples. Results We describe a novel method for label-free proteomics data alignment with the ability to incorporate previously unused aspects of the data, particularly ion mobility drift times and product ion information. We compare the results of our alignment method to PEPPeR and OpenMS, and compare alignment accuracy achieved by different versions of our method utilizing various data characteristics. Our method results in increased match recall rates and similar or improved mismatch rates compared to PEPPeR and OpenMS feature-based alignment. We also show that the inclusion of drift time and product ion information results in higher recall rates and more confident matches, without increases in error rates. Conclusions Based on the results presented here, we argue that the incorporation of ion mobility drift time and product ion information are worthy pursuits. Alignment methods should be flexible enough to utilize all available data, particularly with recent advancements in experimental separation methods. PMID:24341404

A flexible statistical model for alignment of label-free proteomics data--incorporating ion mobility and product ion information.

PubMed

Benjamin, Ashlee M; Thompson, J Will; Soderblom, Erik J; Geromanos, Scott J; Henao, Ricardo; Kraus, Virginia B; Moseley, M Arthur; Lucas, Joseph E

2013-12-16

The goal of many proteomics experiments is to determine the abundance of proteins in biological samples, and the variation thereof in various physiological conditions. High-throughput quantitative proteomics, specifically label-free LC-MS/MS, allows rapid measurement of thousands of proteins, enabling large-scale studies of various biological systems. Prior to analyzing these information-rich datasets, raw data must undergo several computational processing steps. We present a method to address one of the essential steps in proteomics data processing--the matching of peptide measurements across samples. We describe a novel method for label-free proteomics data alignment with the ability to incorporate previously unused aspects of the data, particularly ion mobility drift times and product ion information. We compare the results of our alignment method to PEPPeR and OpenMS, and compare alignment accuracy achieved by different versions of our method utilizing various data characteristics. Our method results in increased match recall rates and similar or improved mismatch rates compared to PEPPeR and OpenMS feature-based alignment. We also show that the inclusion of drift time and product ion information results in higher recall rates and more confident matches, without increases in error rates. Based on the results presented here, we argue that the incorporation of ion mobility drift time and product ion information are worthy pursuits. Alignment methods should be flexible enough to utilize all available data, particularly with recent advancements in experimental separation methods.

Quantitative trait loci mapping of the mouse plasma proteome (pQTL).

PubMed

Holdt, Lesca M; von Delft, Annette; Nicolaou, Alexandros; Baumann, Sven; Kostrzewa, Markus; Thiery, Joachim; Teupser, Daniel

2013-02-01

A current challenge in the era of genome-wide studies is to determine the responsible genes and mechanisms underlying newly identified loci. Screening of the plasma proteome by high-throughput mass spectrometry (MALDI-TOF MS) is considered a promising approach for identification of metabolic and disease processes. Therefore, plasma proteome screening might be particularly useful for identifying responsible genes when combined with analysis of variation in the genome. Here, we describe a proteomic quantitative trait locus (pQTL) study of plasma proteome screens in an F(2) intercross of 455 mice mapped with 177 genetic markers across the genome. A total of 69 of 176 peptides revealed significant LOD scores (≥5.35) demonstrating strong genetic regulation of distinct components of the plasma proteome. Analyses were confirmed by mechanistic studies and MALDI-TOF/TOF, liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyses of the two strongest pQTLs: A pQTL for mass-to-charge ratio (m/z) 3494 (LOD 24.9, D11Mit151) was identified as the N-terminal 35 amino acids of hemoglobin subunit A (Hba) and caused by genetic variation in Hba. Another pQTL for m/z 8713 (LOD 36.4; D1Mit111) was caused by variation in apolipoprotein A2 (Apoa2) and cosegregated with HDL cholesterol. Taken together, we show that genome-wide plasma proteome profiling in combination with genome-wide genetic screening aids in the identification of causal genetic variants affecting abundance of plasma proteins.

Quantitative Trait Loci Mapping of the Mouse Plasma Proteome (pQTL)

PubMed Central

Holdt, Lesca M.; von Delft, Annette; Nicolaou, Alexandros; Baumann, Sven; Kostrzewa, Markus; Thiery, Joachim; Teupser, Daniel

2013-01-01

A current challenge in the era of genome-wide studies is to determine the responsible genes and mechanisms underlying newly identified loci. Screening of the plasma proteome by high-throughput mass spectrometry (MALDI-TOF MS) is considered a promising approach for identification of metabolic and disease processes. Therefore, plasma proteome screening might be particularly useful for identifying responsible genes when combined with analysis of variation in the genome. Here, we describe a proteomic quantitative trait locus (pQTL) study of plasma proteome screens in an F2 intercross of 455 mice mapped with 177 genetic markers across the genome. A total of 69 of 176 peptides revealed significant LOD scores (≥5.35) demonstrating strong genetic regulation of distinct components of the plasma proteome. Analyses were confirmed by mechanistic studies and MALDI-TOF/TOF, liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyses of the two strongest pQTLs: A pQTL for mass-to-charge ratio (m/z) 3494 (LOD 24.9, D11Mit151) was identified as the N-terminal 35 amino acids of hemoglobin subunit A (Hba) and caused by genetic variation in Hba. Another pQTL for m/z 8713 (LOD 36.4; D1Mit111) was caused by variation in apolipoprotein A2 (Apoa2) and cosegregated with HDL cholesterol. Taken together, we show that genome-wide plasma proteome profiling in combination with genome-wide genetic screening aids in the identification of causal genetic variants affecting abundance of plasma proteins. PMID:23172855

Immunodepletion Plasma Proteomics by TripleTOF 5600 and Orbitrap Elite/LTQ-Orbitrap Velos/Q Exactive Mass Spectrometers

PubMed Central

Patel, Bhavinkumar B.; Kelsen, Steven G.; Braverman, Alan; Swinton, Derrick J.; Gafken, Philip R.; Jones, Lisa A.; Lane, William S.; Neveu, John M.; Leung, Hon-Chiu E.; Shaffer, Scott A.; Leszyk, John D.; Stanley, Bruce A.; Fox, Todd E.; Stanley, Anne; Hall, Michael J.; Hampel, Heather; South, Christopher D.; de la Chapelle, Albert; Burt, Randall W.; Jones, David A.; Kopelovich, Levy; Yeung, Anthony T.

2013-01-01

Plasma proteomic experiments performed rapidly and economically using several of the latest high-resolution mass spectrometers were compared. Four quantitative hyperfractionated plasma proteomics experiments were analyzed in replicates by two AB SCIEX TripleTOF 5600 and three Thermo Scientific Orbitrap (Elite/LTQ-Orbitrap Velos/Q Exactive) instruments. Each experiment compared two iTRAQ isobaric-labeled immunodepleted plasma proteomes, provided as 30 labeled peptide fractions. 480 LC-MS/MS runs delivered >250 GB of data in two months. Several analysis algorithms were compared. At 1 % false discovery rate, the relative comparative findings concluded that the Thermo Scientific Q Exactive Mass Spectrometer resulted in the highest number of identified proteins and unique sequences with iTRAQ quantitation. The confidence of iTRAQ fold-change for each protein is dependent on the overall ion statistics (Mascot Protein Score) attainable by each instrument. The benchmarking also suggested how to further improve the mass spectrometry parameters and HPLC conditions. Our findings highlight the special challenges presented by the low abundance peptide ions of iTRAQ plasma proteome because the dynamic range of plasma protein abundance is uniquely high compared with cell lysates, necessitating high instrument sensitivity. PMID:24004147

A knowledge-based T2-statistic to perform pathway analysis for quantitative proteomic data

PubMed Central

Chen, Yi-Hau

2017-01-01

Approaches to identify significant pathways from high-throughput quantitative data have been developed in recent years. Still, the analysis of proteomic data stays difficult because of limited sample size. This limitation also leads to the practice of using a competitive null as common approach; which fundamentally implies genes or proteins as independent units. The independent assumption ignores the associations among biomolecules with similar functions or cellular localization, as well as the interactions among them manifested as changes in expression ratios. Consequently, these methods often underestimate the associations among biomolecules and cause false positives in practice. Some studies incorporate the sample covariance matrix into the calculation to address this issue. However, sample covariance may not be a precise estimation if the sample size is very limited, which is usually the case for the data produced by mass spectrometry. In this study, we introduce a multivariate test under a self-contained null to perform pathway analysis for quantitative proteomic data. The covariance matrix used in the test statistic is constructed by the confidence scores retrieved from the STRING database or the HitPredict database. We also design an integrating procedure to retain pathways of sufficient evidence as a pathway group. The performance of the proposed T2-statistic is demonstrated using five published experimental datasets: the T-cell activation, the cAMP/PKA signaling, the myoblast differentiation, and the effect of dasatinib on the BCR-ABL pathway are proteomic datasets produced by mass spectrometry; and the protective effect of myocilin via the MAPK signaling pathway is a gene expression dataset of limited sample size. Compared with other popular statistics, the proposed T2-statistic yields more accurate descriptions in agreement with the discussion of the original publication. We implemented the T2-statistic into an R package T2GA, which is available at https://github.com/roqe/T2GA. PMID:28622336

A knowledge-based T2-statistic to perform pathway analysis for quantitative proteomic data.

PubMed

Lai, En-Yu; Chen, Yi-Hau; Wu, Kun-Pin

2017-06-01

Approaches to identify significant pathways from high-throughput quantitative data have been developed in recent years. Still, the analysis of proteomic data stays difficult because of limited sample size. This limitation also leads to the practice of using a competitive null as common approach; which fundamentally implies genes or proteins as independent units. The independent assumption ignores the associations among biomolecules with similar functions or cellular localization, as well as the interactions among them manifested as changes in expression ratios. Consequently, these methods often underestimate the associations among biomolecules and cause false positives in practice. Some studies incorporate the sample covariance matrix into the calculation to address this issue. However, sample covariance may not be a precise estimation if the sample size is very limited, which is usually the case for the data produced by mass spectrometry. In this study, we introduce a multivariate test under a self-contained null to perform pathway analysis for quantitative proteomic data. The covariance matrix used in the test statistic is constructed by the confidence scores retrieved from the STRING database or the HitPredict database. We also design an integrating procedure to retain pathways of sufficient evidence as a pathway group. The performance of the proposed T2-statistic is demonstrated using five published experimental datasets: the T-cell activation, the cAMP/PKA signaling, the myoblast differentiation, and the effect of dasatinib on the BCR-ABL pathway are proteomic datasets produced by mass spectrometry; and the protective effect of myocilin via the MAPK signaling pathway is a gene expression dataset of limited sample size. Compared with other popular statistics, the proposed T2-statistic yields more accurate descriptions in agreement with the discussion of the original publication. We implemented the T2-statistic into an R package T2GA, which is available at https://github.com/roqe/T2GA.

Quantitative Dynamics of Proteome, Acetylome, and Succinylome during Stem-Cell Differentiation into Hepatocyte-like Cells.

PubMed

Liu, Zekun; Zhang, Qing-Bin; Bu, Chen; Wang, Dawei; Yu, Kai; Gan, Zhixue; Chang, Jianfeng; Cheng, Zhongyi; Liu, Zexian

2018-06-21

Stem-cell differentiation is a complex biological process controlled by a series of functional protein clusters and signaling transductions, especially metabolism-related pathways. Although previous studies have quantified the proteome and phosphoproteome for stem-cell differentiation, the investigation of acylation-mediated regulation is still absent. In this study, we quantitatively profiled the proteome, acetylome, and succinylome in pluripotent human embryonic stem cells (hESCs) and differentiated hepatocyte-like cells (HLCs). In total, 3843 proteins, 185 acetylation sites in 103 proteins, and 602 succinylation sites in 391 proteins were quantified. The quantitative proteome showed that in differentiated HLCs the TGF-β, JAK-STAT, and RAS signaling pathways were activated, whereas ECM-related processes such as sulfates and leucine degradation were depressed. Interestingly, it was observed that the acetylation and succinylation were more intensive in hESCs, whereas protein processing in endoplasmic reticulum and the carbon metabolic pathways were especially highly succinylated. Because the metabolism patterns in pluripotent hESCs and the differentiated HLCs were different, we proposed that the dynamic acylations, especially succinylation, might regulate the Warburg-like effect and TCA cycle during differentiation. Taken together, we systematically profiled the protein and acylation levels of regulation in pluripotent hESCs and differentiated HLCs, and the results indicated the important roles of acylation in pluripotency maintenance and differentiation.

Integrative Analysis of Subcellular Quantitative Proteomics Studies Reveals Functional Cytoskeleton Membrane-Lipid Raft Interactions in Cancer.

PubMed

Shah, Anup D; Inder, Kerry L; Shah, Alok K; Cristino, Alexandre S; McKie, Arthur B; Gabra, Hani; Davis, Melissa J; Hill, Michelle M

2016-10-07

Lipid rafts are dynamic membrane microdomains that orchestrate molecular interactions and are implicated in cancer development. To understand the functions of lipid rafts in cancer, we performed an integrated analysis of quantitative lipid raft proteomics data sets modeling progression in breast cancer, melanoma, and renal cell carcinoma. This analysis revealed that cancer development is associated with increased membrane raft-cytoskeleton interactions, with ∼40% of elevated lipid raft proteins being cytoskeletal components. Previous studies suggest a potential functional role for the raft-cytoskeleton in the action of the putative tumor suppressors PTRF/Cavin-1 and Merlin. To extend the observation, we examined lipid raft proteome modulation by an unrelated tumor suppressor opioid binding protein cell-adhesion molecule (OPCML) in ovarian cancer SKOV3 cells. In agreement with the other model systems, quantitative proteomics revealed that 39% of OPCML-depleted lipid raft proteins are cytoskeletal components, with microfilaments and intermediate filaments specifically down-regulated. Furthermore, protein-protein interaction network and simulation analysis showed significantly higher interactions among cancer raft proteins compared with general human raft proteins. Collectively, these results suggest increased cytoskeleton-mediated stabilization of lipid raft domains with greater molecular interactions as a common, functional, and reversible feature of cancer cells.

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.

Quantitative proteomic analysis of microdissected oral epithelium for cancer biomarker discovery.

PubMed

Xiao, Hua; Langerman, Alexander; Zhang, Yan; Khalid, Omar; Hu, Shen; Cao, Cheng-Xi; Lingen, Mark W; Wong, David T W

2015-11-01

Specific biomarkers are urgently needed for the detection and progression of oral cancer. The objective of this study was to discover cancer biomarkers from oral epithelium through utilizing high throughput quantitative proteomics approaches. Morphologically malignant, epithelial dysplasia, and adjacent normal epithelial tissues were laser capture microdissected (LCM) from 19 patients and used for proteomics analysis. Total proteins from each group were extracted, digested and then labelled with corresponding isobaric tags for relative and absolute quantitation (iTRAQ). Labelled peptides from each sample were combined and analyzed by liquid chromatography-mass spectrometry (LC-MS/MS) for protein identification and quantification. In total, 500 proteins were identified and 425 of them were quantified. When compared with adjacent normal oral epithelium, 17 and 15 proteins were consistently up-regulated or down-regulated in malignant and epithelial dysplasia, respectively. Half of these candidate biomarkers were discovered for oral cancer for the first time. Cornulin was initially confirmed in tissue protein extracts and was further validated in tissue microarray. Its presence in the saliva of oral cancer patients was also explored. Myoglobin and S100A8 were pre-validated by tissue microarray. These data demonstrated that the proteomic biomarkers discovered through this strategy are potential targets for oral cancer detection and salivary diagnostics. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

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.

Proteomic snapshot of the EGF-induced ubiquitin network

PubMed Central

Argenzio, Elisabetta; Bange, Tanja; Oldrini, Barbara; Bianchi, Fabrizio; Peesari, Raghunath; Mari, Sara; Di Fiore, Pier Paolo; Mann, Matthias; Polo, Simona

2011-01-01

The activity, localization and fate of many cellular proteins are regulated through ubiquitination, a process whereby one or more ubiquitin (Ub) monomers or chains are covalently attached to target proteins. While Ub-conjugated and Ub-associated proteomes have been described, we lack a high-resolution picture of the dynamics of ubiquitination in response to signaling. In this study, we describe the epidermal growth factor (EGF)-regulated Ubiproteome, as obtained by two complementary purification strategies coupled to quantitative proteomics. Our results unveil the complex impact of growth factor signaling on Ub-based intracellular networks to levels that extend well beyond what might have been expected. In addition to endocytic proteins, the EGF-regulated Ubiproteome includes a large number of signaling proteins, ubiquitinating and deubiquitinating enzymes, transporters and proteins involved in translation and transcription. The Ub-based signaling network appears to intersect both housekeeping and regulatory circuitries of cellular physiology. Finally, as proof of principle of the biological relevance of the EGF-Ubiproteome, we demonstrated that EphA2 is a novel, downstream ubiquitinated target of epidermal growth factor receptor (EGFR), critically involved in EGFR biological responses. PMID:21245847

Proteomics-based compositional analysis of complex cellulase-hemicellulase mixtures.

PubMed

Chundawat, Shishir P S; Lipton, Mary S; Purvine, Samuel O; Uppugundla, Nirmal; Gao, Dahai; Balan, Venkatesh; Dale, Bruce E

2011-10-07

Efficient deconstruction of cellulosic biomass to fermentable sugars for fuel and chemical production is accomplished by a complex mixture of cellulases, hemicellulases, and accessory enzymes (e.g., >50 extracellular proteins). Cellulolytic enzyme mixtures, produced industrially mostly using fungi like Trichoderma reesei, are poorly characterized in terms of their protein composition and its correlation to hydrolytic activity on cellulosic biomass. The secretomes of commercial glycosyl hydrolase-producing microbes was explored using a proteomics approach with high-throughput quantification using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Here, we show that proteomics-based spectral counting approach is a reasonably accurate and rapid analytical technique that can be used to determine protein composition of complex glycosyl hydrolase mixtures that also correlates with the specific activity of individual enzymes present within the mixture. For example, a strong linear correlation was seen between Avicelase activity and total cellobiohydrolase content. Reliable, quantitative and cheaper analytical methods that provide insight into the cellulosic biomass degrading fungal and bacterial secretomes would lead to further improvements toward commercialization of plant biomass-derived fuels and chemicals.

Quantitative proteomic analysis of bacterial enzymes released in cheese during ripening.

PubMed

Jardin, Julien; Mollé, Daniel; Piot, Michel; Lortal, Sylvie; Gagnaire, Valérie

2012-04-02

Due to increasingly available bacterial genomes in databases, proteomic tools have recently been used to screen proteins expressed by micro-organisms in food in order to better understand their metabolism in situ. While the main objective is the systematic identification of proteins, the next step will be to bridge the gap between identification and quantification of these proteins. For that purpose, a new mass spectrometry-based approach was applied, using isobaric tagging reagent for quantitative proteomic analysis (iTRAQ), which are amine specific and yield labelled peptides identical in mass. Experimental Swiss-type cheeses were manufactured from microfiltered milk using Streptococcus thermophilus ITG ST20 and Lactobacillus helveticus ITG LH1 as lactic acid starters. At three ripening times (7, 20 and 69 days), cheese aqueous phases were extracted and enriched in bacterial proteins by fractionation. Each sample, standardised in protein amount prior to proteomic analyses, was: i) analysed by 2D-electrophoresis for qualitative analysis and ii) submitted to trypsinolysis, and labelled with specific iTRAQ tag, one per ripening time. The three labelled samples were mixed together and analysed by nano-LC coupled on-line with ESI-QTOF mass spectrometer. Thirty proteins, both from bacterial or bovine origin, were identified and efficiently quantified. The free bacterial proteins detected were enzymes from the central carbon metabolism as well as stress proteins. Depending on the protein considered, the quantity of these proteins in the cheese aqueous extract increased from 2.5 to 20 fold in concentration from day 7 to day 69 of ripening. Copyright © 2012 Elsevier B.V. All rights reserved.

Label-free quantitative proteomics to investigate strawberry fruit proteome changes under controlled atmosphere and low temperature storage.

PubMed

Li, Li; Luo, Zisheng; Huang, Xinhong; Zhang, Lu; Zhao, Pengyu; Ma, Hongyuan; Li, Xihong; Ban, Zhaojun; Liu, Xia

2015-04-29

To elucidate the mechanisms contributing to fruit responses to senescence and stressful environmental stimuli under low temperature (LT) and controlled atmosphere (CA) storage, a label-free quantitative proteomic investigation was conducted in strawberry (Fragaria ananassa, Duch. cv. 'Akihime'). Postharvest physiological quality traits including firmness, total soluble solids, total acidity, ascorbic acid and volatile production were characterized following storage under different conditions. The observed post-storage protein expression profiles may be associated with delayed senescence features in strawberry. A total of 454 proteins were identified in differentially treated strawberry fruits. Quantitative analysis, using normalized spectral counts, revealed 73 proteins common to all treatments, which formed three clusters in a hierarchical clustering analysis. The proteins spanned a range of functions in various metabolic pathways and networks involved in carbohydrate and energy metabolism, volatile biosynthesis, phenylpropanoid activity, stress response and protein synthesis, degradation and folding. After CA and LT storage, 16 (13) and 11 (17) proteins, respectively, were significantly increased (decreased) in abundance, while expression profile of 12 proteins was significantly changed by both CA and LT. To summarize, the differential variability of abundance in strawberry proteome, working in a cooperative manner, provided an overview of the biological processes that occurred during CA and LT storage. Controlled atmosphere storage at an optimal temperature is regarded to be an effective postharvest technology to delay fruit senescence and maintain fruit quality during shelf life. Nonetheless, little information on fruit proteomic changes under controlled atmosphere and/or low temperature storage is available. The significance of this paper is that it is the first study employing a label-free approach in the investigation of strawberry fruit response to controlled atmosphere and cold storage. Changes in postharvest physiological quality traits including volatile production, firmness, ascorbic acid, soluble solids and total acidity were also characterized. Significant biological changes associated with senescence were revealed and differentially abundant proteins under various storage conditions were identified. Proteomic profiles were linked to physiological aspects of strawberry fruit senescence in order to provide new insights into possible regulation mechanisms. Findings from this study not only provide proteomic information on fruit regulation, but also pave the way for further quantitative studies at the transcriptomic and metabolomic levels. Copyright © 2015 Elsevier B.V. All rights reserved.