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

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

PubMed

Butler, Georgina S; Overall, Christopher M

2009-11-24

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

Unbiased Protein Association Study on the Public Human Proteome Reveals Biological Connections between Co-Occurring Protein Pairs

PubMed Central

2017-01-01

Mass-spectrometry-based, high-throughput proteomics experiments produce large amounts of data. While typically acquired to answer specific biological questions, these data can also be reused in orthogonal ways to reveal new biological knowledge. We here present a novel method for such orthogonal data reuse of public proteomics data. Our method elucidates biological relationships between proteins based on the co-occurrence of these proteins across human experiments in the PRIDE database. The majority of the significantly co-occurring protein pairs that were detected by our method have been successfully mapped to existing biological knowledge. The validity of our novel method is substantiated by the extremely few pairs that can be mapped to existing knowledge based on random associations between the same set of proteins. Moreover, using literature searches and the STRING database, we were able to derive meaningful biological associations for unannotated protein pairs that were detected using our method, further illustrating that as-yet unknown associations present highly interesting targets for follow-up analysis. PMID:28480704

Mitochondrial proteome remodelling in pressure overload-induced heart failure: the role of mitochondrial oxidative stress

PubMed Central

Dai, Dao-Fu; Hsieh, Edward J.; Liu, Yonggang; Chen, Tony; Beyer, Richard P.; Chin, Michael T.; MacCoss, Michael J.; Rabinovitch, Peter S.

2012-01-01

Aims We investigate the role of mitochondrial oxidative stress in mitochondrial proteome remodelling using mouse models of heart failure induced by pressure overload. Methods and results We demonstrate that mice overexpressing catalase targeted to mitochondria (mCAT) attenuate pressure overload-induced heart failure. An improved method of label-free unbiased analysis of the mitochondrial proteome was applied to the mouse model of heart failure induced by transverse aortic constriction (TAC). A total of 425 mitochondrial proteins were compared between wild-type and mCAT mice receiving TAC or sham surgery. The changes in the mitochondrial proteome in heart failure included decreased abundance of proteins involved in fatty acid metabolism, an increased abundance of proteins in glycolysis, apoptosis, mitochondrial unfolded protein response and proteolysis, transcription and translational control, and developmental processes as well as responses to stimuli. Overexpression of mCAT better preserved proteins involved in fatty acid metabolism and attenuated the increases in apoptotic and proteolytic enzymes. Interestingly, gene ontology analysis also showed that monosaccharide metabolic processes and protein folding/proteolysis were only overrepresented in mCAT but not in wild-type mice in response to TAC. Conclusion This is the first study to demonstrate that scavenging mitochondrial reactive oxygen species (ROS) by mCAT not only attenuates most of the mitochondrial proteome changes in heart failure, but also induces a subset of unique alterations. These changes represent processes that are adaptive to the increased work and metabolic requirements of pressure overload, but which are normally inhibited by overproduction of mitochondrial ROS. PMID:22012956

Defining the human deubiquitinating enzyme interaction landscape.

PubMed

Sowa, Mathew E; Bennett, Eric J; Gygi, Steven P; Harper, J Wade

2009-07-23

Deubiquitinating enzymes (Dubs) function to remove covalently attached ubiquitin from proteins, thereby controlling substrate activity and/or abundance. For most Dubs, their functions, targets, and regulation are poorly understood. To systematically investigate Dub function, we initiated a global proteomic analysis of Dubs and their associated protein complexes. This was accomplished through the development of a software platform called CompPASS, which uses unbiased metrics to assign confidence measurements to interactions from parallel nonreciprocal proteomic data sets. We identified 774 candidate interacting proteins associated with 75 Dubs. Using Gene Ontology, interactome topology classification, subcellular localization, and functional studies, we link Dubs to diverse processes, including protein turnover, transcription, RNA processing, DNA damage, and endoplasmic reticulum-associated degradation. This work provides the first glimpse into the Dub interaction landscape, places previously unstudied Dubs within putative biological pathways, and identifies previously unknown interactions and protein complexes involved in this increasingly important arm of the ubiquitin-proteasome pathway.

Defining the Human Deubiquitinating Enzyme Interaction Landscape

PubMed Central

Sowa, Mathew E.; Bennett, Eric J.; Gygi, Steven P.; Harper, J. Wade

2009-01-01

Summary Deubiquitinating enzymes (Dubs) function to remove covalently attached ubiquitin from proteins, thereby controlling substrate activity and/or abundance. For most Dubs, their functions, targets, and regulation are poorly understood. To systematically investigate Dub function, we initiated a global proteomic analysis of Dubs and their associated protein complexes. This was accomplished through the development of a software platform, called CompPASS, which uses unbiased metrics to assign confidence measurements to interactions from parallel non-reciprocal proteomic datasets. We identified 774 candidate interacting proteins associated with 75 Dubs. Using Gene Ontology, interactome topology classification, sub-cellular localization and functional studies, we link Dubs to diverse processes, including protein turnover, transcription, RNA processing, DNA damage, and endoplasmic reticulum-associated degradation. This work provides the first glimpse into the Dub interaction landscape, places previously unstudied Dubs within putative biological pathways, and identifies previously unknown interactions and protein complexes involved in this increasingly important arm of the ubiquitin-proteasome pathway. PMID:19615732

Proteome and Secretome Analysis Reveals Differential Post-transcriptional Regulation of Toll-like Receptor Responses*

PubMed Central

Koppenol-Raab, Marijke; Sjoelund, Virginie; Manes, Nathan P.; Gottschalk, Rachel A.; Dutta, Bhaskar; Benet, Zachary L.; Fraser, Iain D. C.

2017-01-01

The innate immune system is the organism's first line of defense against pathogens. Pattern recognition receptors (PRRs) are responsible for sensing the presence of pathogen-associated molecules. The prototypic PRRs, the membrane-bound receptors of the Toll-like receptor (TLR) family, recognize pathogen-associated molecular patterns (PAMPs) and initiate an innate immune response through signaling pathways that depend on the adaptor molecules MyD88 and TRIF. Deciphering the differences in the complex signaling events that lead to pathogen recognition and initiation of the correct response remains challenging. Here we report the discovery of temporal changes in the protein signaling components involved in innate immunity. Using an integrated strategy combining unbiased proteomics, transcriptomics and macrophage stimulations with three different PAMPs, we identified differences in signaling between individual TLRs and revealed specifics of pathway regulation at the protein level. PMID:28235783

Characterization of human pineal gland proteome.

PubMed

Yelamanchi, Soujanya D; Kumar, Manish; Madugundu, Anil K; Gopalakrishnan, Lathika; Dey, Gourav; Chavan, Sandip; Sathe, Gajanan; Mathur, Premendu P; Gowda, Harsha; Mahadevan, Anita; Shankar, Susarla K; Prasad, T S Keshava

2016-11-15

The pineal gland is a neuroendocrine gland located at the center of the brain. It is known to regulate various physiological functions in the body through secretion of the neurohormone melatonin. Comprehensive characterization of the human pineal gland proteome has not been undertaken to date. We employed a high-resolution mass spectrometry-based approach to characterize the proteome of the human pineal gland. A total of 5874 proteins were identified from the human pineal gland in this study. Of these, 5820 proteins were identified from the human pineal gland for the first time. Interestingly, 1136 proteins from the human pineal gland were found to contain a signal peptide domain, which indicates the secretory nature of these proteins. An unbiased global proteomic profile of this biomedically important organ should benefit molecular research to unravel the role of the pineal gland in neuropsychiatric and neurodegenerative diseases.

Proteomics/phosphoproteomics of left ventricular biopsies from patients with surgical coronary revascularization and pigs with coronary occlusion/reperfusion: remote ischemic preconditioning.

PubMed

Gedik, Nilgün; Krüger, Marcus; Thielmann, Matthias; Kottenberg, Eva; Skyschally, Andreas; Frey, Ulrich H; Cario, Elke; Peters, Jürgen; Jakob, Heinz; Heusch, Gerd; Kleinbongard, Petra

2017-08-09

Remote ischemic preconditioning (RIPC) by repeated brief cycles of limb ischemia/reperfusion reduces myocardial ischemia/reperfusion injury. In left ventricular (LV) biopsies from patients undergoing coronary artery bypass grafting (CABG), only the activation of signal transducer and activator of transcription 5 was associated with RIPC's cardioprotection. We have now used an unbiased, non-hypothesis-driven proteomics and phosphoproteomics approach to analyze LV biopsies from patients undergoing CABG and from pigs undergoing coronary occlusion/reperfusion without (sham) and with RIPC. False discovery rate-based statistics identified a higher prostaglandin reductase 2 expression at early reperfusion with RIPC than with sham in patients. In pigs, the phosphorylation of 116 proteins was different between baseline and early reperfusion with RIPC and/or with sham. The identified proteins were not identical for patients and pigs, but in-silico pathway analysis of proteins with ≥2-fold higher expression/phosphorylation at early reperfusion with RIPC in comparison to sham revealed a relation to mitochondria and cytoskeleton in both species. Apart from limitations of the proteomics analysis per se, the small cohorts, the sampling/sample processing and the number of uncharacterized/unverifiable porcine proteins may have contributed to this largely unsatisfactory result.

QCloud: A cloud-based quality control system for mass spectrometry-based proteomics laboratories

PubMed Central

Chiva, Cristina; Olivella, Roger; Borràs, Eva; Espadas, Guadalupe; Pastor, Olga; Solé, Amanda

2018-01-01

The increasing number of biomedical and translational applications in mass spectrometry-based proteomics poses new analytical challenges and raises the need for automated quality control systems. Despite previous efforts to set standard file formats, data processing workflows and key evaluation parameters for quality control, automated quality control systems are not yet widespread among proteomics laboratories, which limits the acquisition of high-quality results, inter-laboratory comparisons and the assessment of variability of instrumental platforms. Here we present QCloud, a cloud-based system to support proteomics laboratories in daily quality assessment using a user-friendly interface, easy setup, automated data processing and archiving, and unbiased instrument evaluation. QCloud supports the most common targeted and untargeted proteomics workflows, it accepts data formats from different vendors and it enables the annotation of acquired data and reporting incidences. A complete version of the QCloud system has successfully been developed and it is now open to the proteomics community (http://qcloud.crg.eu). QCloud system is an open source project, publicly available under a Creative Commons License Attribution-ShareAlike 4.0. PMID:29324744

A proteomic network approach across the ALS-FTD disease spectrum resolves clinical phenotypes and genetic vulnerability in human brain.

PubMed

Umoh, Mfon E; Dammer, Eric B; Dai, Jingting; Duong, Duc M; Lah, James J; Levey, Allan I; Gearing, Marla; Glass, Jonathan D; Seyfried, Nicholas T

2018-01-01

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are neurodegenerative diseases with overlap in clinical presentation, neuropathology, and genetic underpinnings. The molecular basis for the overlap of these disorders is not well established. We performed a comparative unbiased mass spectrometry-based proteomic analysis of frontal cortical tissues from postmortem cases clinically defined as ALS, FTD, ALS and FTD (ALS/FTD), and controls. We also included a subset of patients with the C9orf72 expansion mutation, the most common genetic cause of both ALS and FTD Our systems-level analysis of the brain proteome integrated both differential expression and co-expression approaches to assess the relationship of these differences to clinical and pathological phenotypes. Weighted co-expression network analysis revealed 15 modules of co-expressed proteins, eight of which were significantly different across the ALS-FTD disease spectrum. These included modules associated with RNA binding proteins, synaptic transmission, and inflammation with cell-type specificity that showed correlation with TDP-43 pathology and cognitive dysfunction. Modules were also examined for their overlap with TDP-43 protein-protein interactions, revealing one module enriched with RNA-binding proteins and other causal ALS genes that increased in FTD/ALS and FTD cases. A module enriched with astrocyte and microglia proteins was significantly increased in ALS cases carrying the C9orf72 mutation compared to sporadic ALS cases, suggesting that the genetic expansion is associated with inflammation in the brain even without clinical evidence of dementia. Together, these findings highlight the utility of integrative systems-level proteomic approaches to resolve clinical phenotypes and genetic mechanisms underlying the ALS-FTD disease spectrum in human brain. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

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

PubMed Central

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

2012-01-01

Most proteomic studies use liquid chromatography coupled to tandem mass spectrometry to identify and quantify the peptides generated by the proteolysis of a biological sample. However, with the current methods it remains challenging to rapidly, consistently, reproducibly, accurately, and sensitively detect and quantify large fractions of proteomes across multiple samples. Here we present a new strategy that systematically queries sample sets for the presence and quantity of essentially any protein of interest. It consists of using the information available in fragment ion spectral libraries to mine the complete fragment ion maps generated using a data-independent acquisition method. For this study, the data were acquired on a fast, high resolution quadrupole-quadrupole time-of-flight (TOF) instrument by repeatedly cycling through 32 consecutive 25-Da precursor isolation windows (swaths). This SWATH MS acquisition setup generates, in a single sample injection, time-resolved fragment ion spectra for all the analytes detectable within the 400–1200 m/z precursor range and the user-defined retention time window. We show that suitable combinations of fragment ions extracted from these data sets are sufficiently specific to confidently identify query peptides over a dynamic range of 4 orders of magnitude, even if the precursors of the queried peptides are not detectable in the survey scans. We also show that queried peptides are quantified with a consistency and accuracy comparable with that of selected reaction monitoring, the gold standard proteomic quantification method. Moreover, targeted data extraction enables ad libitum quantification refinement and dynamic extension of protein probing by iterative re-mining of the once-and-forever acquired data sets. This combination of unbiased, broad range precursor ion fragmentation and targeted data extraction alleviates most constraints of present proteomic methods and should be equally applicable to the comprehensive analysis of other classes of analytes, beyond proteomics. PMID:22261725

Multi-Omics Driven Assembly and Annotation of the Sandalwood (Santalum album) Genome.

PubMed

Mahesh, Hirehally Basavarajegowda; Subba, Pratigya; Advani, Jayshree; Shirke, Meghana Deepak; Loganathan, Ramya Malarini; Chandana, Shankara Lingu; Shilpa, Siddappa; Chatterjee, Oishi; Pinto, Sneha Maria; Prasad, Thottethodi Subrahmanya Keshava; Gowda, Malali

2018-04-01

Indian sandalwood ( Santalum album ) is an important tropical evergreen tree known for its fragrant heartwood-derived essential oil and its valuable carving wood. Here, we applied an integrated genomic, transcriptomic, and proteomic approach to assemble and annotate the Indian sandalwood genome. Our genome sequencing resulted in the establishment of a draft map of the smallest genome for any woody tree species to date (221 Mb). The genome annotation predicted 38,119 protein-coding genes and 27.42% repetitive DNA elements. In-depth proteome analysis revealed the identities of 72,325 unique peptides, which confirmed 10,076 of the predicted genes. The addition of transcriptomic and proteogenomic approaches resulted in the identification of 53 novel proteins and 34 gene-correction events that were missed by genomic approaches. Proteogenomic analysis also helped in reassigning 1,348 potential noncoding RNAs as bona fide protein-coding messenger RNAs. Gene expression patterns at the RNA and protein levels indicated that peptide sequencing was useful in capturing proteins encoded by nuclear and organellar genomes alike. Mass spectrometry-based proteomic evidence provided an unbiased approach toward the identification of proteins encoded by organellar genomes. Such proteins are often missed in transcriptome data sets due to the enrichment of only messenger RNAs that contain poly(A) tails. Overall, the use of integrated omic approaches enhanced the quality of the assembly and annotation of this nonmodel plant genome. The availability of genomic, transcriptomic, and proteomic data will enhance genomics-assisted breeding, germplasm characterization, and conservation of sandalwood trees. © 2018 American Society of Plant Biologists. All Rights Reserved.

Tools to covisualize and coanalyze proteomic data with genomes and transcriptomes: validation of genes and alternative mRNA splicing.

PubMed

Pang, Chi Nam Ignatius; Tay, Aidan P; Aya, Carlos; Twine, Natalie A; Harkness, Linda; Hart-Smith, Gene; Chia, Samantha Z; Chen, Zhiliang; Deshpande, Nandan P; Kaakoush, Nadeem O; Mitchell, Hazel M; Kassem, Moustapha; Wilkins, Marc R

2014-01-03

Direct links between proteomic and genomic/transcriptomic data are not frequently made, partly because of lack of appropriate bioinformatics tools. To help address this, we have developed the PG Nexus pipeline. The PG Nexus allows users to covisualize peptides in the context of genomes or genomic contigs, along with RNA-seq reads. This is done in the Integrated Genome Viewer (IGV). A Results Analyzer reports the precise base position where LC-MS/MS-derived peptides cover genes or gene isoforms, on the chromosomes or contigs where this occurs. In prokaryotes, the PG Nexus pipeline facilitates the validation of genes, where annotation or gene prediction is available, or the discovery of genes using a "virtual protein"-based unbiased approach. We illustrate this with a comprehensive proteogenomics analysis of two strains of Campylobacter concisus . For higher eukaryotes, the PG Nexus facilitates gene validation and supports the identification of mRNA splice junction boundaries and splice variants that are protein-coding. This is illustrated with an analysis of splice junctions covered by human phosphopeptides, and other examples of relevance to the Chromosome-Centric Human Proteome Project. The PG Nexus is open-source and available from https://github.com/IntersectAustralia/ap11_Samifier. It has been integrated into Galaxy and made available in the Galaxy tool shed.

Proteomics Insights into Autophagy.

PubMed

Cudjoe, Emmanuel K; Saleh, Tareq; Hawkridge, Adam M; Gewirtz, David A

2017-10-01

Autophagy, a conserved cellular process by which cells recycle their contents either to maintain basal homeostasis or in response to external stimuli, has for the past two decades become one of the most studied physiological processes in cell biology. The 2016 Nobel Prize in Medicine and Biology awarded to Dr. Ohsumi Yoshinori, one of the first scientists to characterize this cellular mechanism, attests to its importance. The induction and consequent completion of the process of autophagy results in wide ranging changes to the cellular proteome as well as the secretome. MS-based proteomics affords the ability to measure, in an unbiased manner, the ubiquitous changes that occur when autophagy is initiated and progresses in the cell. The continuous improvements and advances in mass spectrometers, especially relating to ionization sources and detectors, coupled with advances in proteomics experimental design, has made it possible to study autophagy, among other process, in great detail. Innovative labeling strategies and protein separation techniques as well as complementary methods including immuno-capture/blotting/staining have been used in proteomics studies to provide more specific protein identification. In this review, we will discuss recent advances in proteomics studies focused on autophagy. © 2017 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.

Consistency of the Proteome in Primary Human Keratinocytes With Respect to Gender, Age, and Skin Localization*

PubMed Central

Sprenger, Adrian; Weber, Sebastian; Zarai, Mostafa; Engelke, Rudolf; Nascimento, Juliana M.; Gretzmeier, Christine; Hilpert, Martin; Boerries, Melanie; Has, Cristina; Busch, Hauke; Bruckner-Tuderman, Leena; Dengjel, Jörn

2013-01-01

Keratinocytes account for 95% of all cells of the epidermis, the stratified squamous epithelium forming the outer layer of the skin, in which a significant number of skin diseases takes root. Immortalized keratinocyte cell lines are often used as research model systems providing standardized, reproducible, and homogenous biological material. Apart from that, primary human keratinocytes are frequently used for medical studies because the skin provides an important route for drug administration and is readily accessible for biopsies. However, comparability of these cell systems is not known. Cell lines may undergo phenotypic shifts and may differ from the in vivo situation in important aspects. Primary cells, on the other hand, may vary in biological functions depending on gender and age of the donor and localization of the biopsy specimen. Here we employed metabolic labeling in combination with quantitative mass spectrometry-based proteomics to assess A431 and HaCaT cell lines for their suitability as model systems. Compared with cell lines, comprehensive profiling of the primary human keratinocyte proteome with respect to gender, age, and skin localization identified an unexpected high proteomic consistency. The data were analyzed by an improved ontology enrichment analysis workflow designed for the study of global proteomics experiments. It enables a quick, comprehensive and unbiased overview of altered biological phenomena and links experimental data to literature. We guide through our workflow, point out its advantages compared with other methods and apply it to visualize differences of cell lines compared with primary human keratinocytes. PMID:23722187

Phenotypic and functional analyses show stem cell-derived hepatocyte-like cells better mimic fetal rather than adult hepatocytes

PubMed Central

Baxter, Melissa; Withey, Sarah; Harrison, Sean; Segeritz, Charis-Patricia; Zhang, Fang; Atkinson-Dell, Rebecca; Rowe, Cliff; Gerrard, Dave T.; Sison-Young, Rowena; Jenkins, Roz; Henry, Joanne; Berry, Andrew A.; Mohamet, Lisa; Best, Marie; Fenwick, Stephen W.; Malik, Hassan; Kitteringham, Neil R.; Goldring, Chris E.; Piper Hanley, Karen; Vallier, Ludovic; Hanley, Neil A.

2015-01-01

Background & Aims Hepatocyte-like cells (HLCs), differentiated from pluripotent stem cells by the use of soluble factors, can model human liver function and toxicity. However, at present HLC maturity and whether any deficit represents a true fetal state or aberrant differentiation is unclear and compounded by comparison to potentially deteriorated adult hepatocytes. Therefore, we generated HLCs from multiple lineages, using two different protocols, for direct comparison with fresh fetal and adult hepatocytes. Methods Protocols were developed for robust differentiation. Multiple transcript, protein and functional analyses compared HLCs to fresh human fetal and adult hepatocytes. Results HLCs were comparable to those of other laboratories by multiple parameters. Transcriptional changes during differentiation mimicked human embryogenesis and showed more similarity to pericentral than periportal hepatocytes. Unbiased proteomics demonstrated greater proximity to liver than 30 other human organs or tissues. However, by comparison to fresh material, HLC maturity was proven by transcript, protein and function to be fetal-like and short of the adult phenotype. The expression of 81% phase 1 enzymes in HLCs was significantly upregulated and half were statistically not different from fetal hepatocytes. HLCs secreted albumin and metabolized testosterone (CYP3A) and dextrorphan (CYP2D6) like fetal hepatocytes. In seven bespoke tests, devised by principal components analysis to distinguish fetal from adult hepatocytes, HLCs from two different source laboratories consistently demonstrated fetal characteristics. Conclusions HLCs from different sources are broadly comparable with unbiased proteomic evidence for faithful differentiation down the liver lineage. This current phenotype mimics human fetal rather than adult hepatocytes. PMID:25457200

Proteomic analysis highlights the molecular complexities of native Kv4 channel macromolecular complexes.

PubMed

Marionneau, Céline; Townsend, R Reid; Nerbonne, Jeanne M

2011-04-01

Voltage-gated K(+) (Kv) channels are key determinants of membrane excitability in the nervous and cardiovascular systems, functioning to control resting membrane potentials, shape action potential waveforms and influence the responses to neurotransmitters and neurohormones. Consistent with this functional diversity, multiple types of Kv currents, with distinct biophysical properties and cellular/subcellular distributions, have been identified. Rapidly activating and inactivating Kv currents, typically referred to as I(A) (A-type) in neurons, for example, regulate repetitive firing rates, action potential back-propagation (into dendrites) and modulate synaptic responses. Currents with similar properties, referred to as I(to,f) (fast transient outward), expressed in cardiomyocytes, control the early phase of myocardial action potential repolarization. A number of studies have demonstrated critical roles for pore-forming (α) subunits of the Kv4 subfamily in the generation of native neuronal I(A) and cardiac I(to,f) channels. Studies in heterologous cells have also suggested important roles for a number of Kv channel accessory and regulatory proteins in the generation of functional I(A) and I(to,f) channels. Quantitative mass spectrometry-based proteomic analysis is increasingly recognized as a rapid and, importantly, unbiased, approach to identify the components of native macromolecular protein complexes. The recent application of proteomic approaches to identify the components of native neuronal (and cardiac) Kv4 channel complexes has revealed even greater complexity than anticipated. The continued emphasis on development of improved biochemical and analytical proteomic methods seems certain to accelerate progress and to provide important new insights into the molecular determinants of native ion channel protein complexes. Copyright © 2010 Elsevier Ltd. All rights reserved.

The peripheral blood proteome signature of idiopathic pulmonary fibrosis is distinct from normal and is associated with novel immunological processes.

PubMed

O'Dwyer, David N; Norman, Katy C; Xia, Meng; Huang, Yong; Gurczynski, Stephen J; Ashley, Shanna L; White, Eric S; Flaherty, Kevin R; Martinez, Fernando J; Murray, Susan; Noth, Imre; Arnold, Kelly B; Moore, Bethany B

2017-04-25

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal interstitial pneumonia. The disease pathophysiology is poorly understood and the etiology remains unclear. Recent advances have generated new therapies and improved knowledge of the natural history of IPF. These gains have been brokered by advances in technology and improved insight into the role of various genes in mediating disease, but gene expression and protein levels do not always correlate. Thus, in this paper we apply a novel large scale high throughput aptamer approach to identify more than 1100 proteins in the peripheral blood of well-characterized IPF patients and normal volunteers. We use systems biology approaches to identify a unique IPF proteome signature and give insight into biological processes driving IPF. We found IPF plasma to be altered and enriched for proteins involved in defense response, wound healing and protein phosphorylation when compared to normal human plasma. Analysis also revealed a minimal protein signature that differentiated IPF patients from normal controls, which may allow for accurate diagnosis of IPF based on easily-accessible peripheral blood. This report introduces large scale unbiased protein discovery analysis to IPF and describes distinct biological processes that further inform disease biology.

Proteomics and metabolomics for mechanistic insights and biomarker discovery in cardiovascular disease.

PubMed

Barallobre-Barreiro, Javier; Chung, Yuen-Li; Mayr, Manuel

2013-08-01

In the last decade, proteomics and metabolomics have contributed substantially to our understanding of cardiovascular diseases. The unbiased assessment of pathophysiological processes without a priori assumptions complements other molecular biology techniques that are currently used in a reductionist approach. In this review, we highlight some of the "omics" methods used to assess protein and metabolite changes in cardiovascular disease. A discrete biological function is very rarely attributed to a single molecule; more often it is the combined input of many proteins. In contrast to the reductionist approach, in which molecules are studied individually, "omics" platforms allow the study of more complex interactions in biological systems. Combining proteomics and metabolomics to quantify changes in metabolites and their corresponding enzymes will advance our understanding of pathophysiological mechanisms and aid the identification of novel biomarkers for cardiovascular disease. Copyright © 2013 Sociedad Española de Cardiología. Published by Elsevier Espana. All rights reserved.

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.

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

Proteomics technique opens new frontiers in mobilome research.

PubMed

Davidson, Andrew D; Matthews, David A; Maringer, Kevin

2017-01-01

A large proportion of the genome of most eukaryotic organisms consists of highly repetitive mobile genetic elements. The sum of these elements is called the "mobilome," which in eukaryotes is made up mostly of transposons. Transposable elements contribute to disease, evolution, and normal physiology by mediating genetic rearrangement, and through the "domestication" of transposon proteins for cellular functions. Although 'omics studies of mobilome genomes and transcriptomes are common, technical challenges have hampered high-throughput global proteomics analyses of transposons. In a recent paper, we overcame these technical hurdles using a technique called "proteomics informed by transcriptomics" (PIT), and thus published the first unbiased global mobilome-derived proteome for any organism (using cell lines derived from the mosquito Aedes aegypti ). In this commentary, we describe our methods in more detail, and summarise our major findings. We also use new genome sequencing data to show that, in many cases, the specific genomic element expressing a given protein can be identified using PIT. This proteomic technique therefore represents an important technological advance that will open new avenues of research into the role that proteins derived from transposons and other repetitive and sequence diverse genetic elements, such as endogenous retroviruses, play in health and disease.

Proteomic Changes in Cerebrospinal Fluid of Presymptomatic and Affected Persons Carrying Familial Alzheimer Disease Mutations

PubMed Central

Ringman, John M.; Schulman, Howard; Becker, Chris; Jones, Ted; Bai, Yuchen; Immermann, Fred; Cole, Gregory; Sokolow, Sophie; Gylys, Karen; Geschwind, Daniel H.; Cummings, Jeffrey L.; Wan, Hong I.

2013-01-01

Objective To identify cerebrospinal fluid (CSF) protein changes in persons who will develop familial Alzheimer disease (FAD) due to PSEN1 and APP mutations, using unbiased proteomics. Design We compared proteomic profiles of CSF from individuals with FAD who were mutation carriers (MCs) and related noncarriers (NCs). Abundant proteins were depleted and samples were analyzed using liquid chromatography– electrospray ionization–mass spectrometry on a high-resolution time-of-flight instrument. Tryptic peptides were identified by tandem mass spectrometry. Proteins differing in concentration between the MCs and NCs were identified. Setting A tertiary dementia referral center and a proteomic biomarker discovery laboratory. Participants Fourteen FAD MCs (mean age, 34.2 years; 10 are asymptomatic, 12 have presenilin-1 [PSEN1] gene mutations, and 2 have amyloid precursor protein [APP] gene mutations) and 5 related NCs (mean age, 37.6 years). Results Fifty-six proteins were identified, represented by multiple tryptic peptides showing significant differences between MCs and NCs (46 upregulated and 10 downregulated); 40 of these proteins differed when the analysis was restricted to asymptomatic individuals. Fourteen proteins have been reported in prior proteomic studies in late-onset AD, including amyloid precursor protein, transferrin, α1β-glycoprotein, complement components, afamin precursor, spondin 1, plasminogen, hemopexin, and neuronal pentraxin receptor. Many other proteins were unique to our study, including calsyntenin 3, AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid) 4 glutamate receptor, CD99 antigen, di-N-acetyl-chitobiase, and secreted phosphoprotein 1. Conclusions We found much overlap in CSF protein changes between individuals with presymptomatic and symptomatic FAD and those with late-onset AD. Our results are consistent with inflammation and synaptic loss early in FAD and suggest new presymptomatic biomarkers of potential usefulness in drug development. PMID:22232349

Phenotypic and functional analyses show stem cell-derived hepatocyte-like cells better mimic fetal rather than adult hepatocytes.

PubMed

Baxter, Melissa; Withey, Sarah; Harrison, Sean; Segeritz, Charis-Patricia; Zhang, Fang; Atkinson-Dell, Rebecca; Rowe, Cliff; Gerrard, Dave T; Sison-Young, Rowena; Jenkins, Roz; Henry, Joanne; Berry, Andrew A; Mohamet, Lisa; Best, Marie; Fenwick, Stephen W; Malik, Hassan; Kitteringham, Neil R; Goldring, Chris E; Piper Hanley, Karen; Vallier, Ludovic; Hanley, Neil A

2015-03-01

Hepatocyte-like cells (HLCs), differentiated from pluripotent stem cells by the use of soluble factors, can model human liver function and toxicity. However, at present HLC maturity and whether any deficit represents a true fetal state or aberrant differentiation is unclear and compounded by comparison to potentially deteriorated adult hepatocytes. Therefore, we generated HLCs from multiple lineages, using two different protocols, for direct comparison with fresh fetal and adult hepatocytes. Protocols were developed for robust differentiation. Multiple transcript, protein and functional analyses compared HLCs to fresh human fetal and adult hepatocytes. HLCs were comparable to those of other laboratories by multiple parameters. Transcriptional changes during differentiation mimicked human embryogenesis and showed more similarity to pericentral than periportal hepatocytes. Unbiased proteomics demonstrated greater proximity to liver than 30 other human organs or tissues. However, by comparison to fresh material, HLC maturity was proven by transcript, protein and function to be fetal-like and short of the adult phenotype. The expression of 81% phase 1 enzymes in HLCs was significantly upregulated and half were statistically not different from fetal hepatocytes. HLCs secreted albumin and metabolized testosterone (CYP3A) and dextrorphan (CYP2D6) like fetal hepatocytes. In seven bespoke tests, devised by principal components analysis to distinguish fetal from adult hepatocytes, HLCs from two different source laboratories consistently demonstrated fetal characteristics. HLCs from different sources are broadly comparable with unbiased proteomic evidence for faithful differentiation down the liver lineage. This current phenotype mimics human fetal rather than adult hepatocytes. Copyright © 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Unbiased Proteomics of Early Lewy Body Formation Model Implicates Active Microtubule Affinity-Regulating Kinases (MARKs) in Synucleinopathies

PubMed Central

Riddle, Dawn M.; Zhang, Bin

2017-01-01

Parkinson's disease (PD) patients progressively accumulate intracytoplasmic inclusions formed by misfolded α-synuclein known as Lewy bodies (LBs). LBs also contain other proteins that may or may not be relevant in the disease process. To identify proteins involved early in LB formation, we performed proteomic analysis of insoluble proteins in a primary neuron culture model of α-synuclein pathology. We identified proteins previously found in authentic LBs in PD as well as several novel proteins, including the microtubule affinity-regulating kinase 1 (MARK1), one of the most enriched proteins in this model of LB formation. Activated MARK proteins (MARKs) accumulated in LB-like inclusions in this cell-based model as well as in a mouse model of LB disease and in LBs of postmortem synucleinopathy brains. Inhibition of MARKs dramatically exacerbated α-synuclein pathology. These findings implicate MARKs early in synucleinopathy pathogenesis and as potential therapeutic drug targets. SIGNIFICANCE STATEMENT Neurodegenerative diseases are diagnosed definitively only in postmortem brains by the presence of key misfolded and aggregated disease proteins, but cellular processes leading to accumulation of these proteins have not been well elucidated. Parkinson's disease (PD) patients accumulate misfolded α-synuclein in LBs, the diagnostic signatures of PD. Here, unbiased mass spectrometry was used to identify the microtubule affinity-regulating kinase family (MARKs) as activated and insoluble in a neuronal culture PD model. Aberrant activation of MARKs was also found in a PD mouse model and in postmortem PD brains. Further, inhibition of MARKs led to increased pathological α-synuclein burden. We conclude that MARKs play a role in PD pathogenesis. PMID:28522732

Proteome analysis of the triton-insoluble erythrocyte membrane skeleton.

PubMed

Basu, Avik; Harper, Sandra; Pesciotta, Esther N; Speicher, Kaye D; Chakrabarti, Abhijit; Speicher, David W

2015-10-14

Erythrocyte shape and membrane integrity is imparted by the membrane skeleton, which can be isolated as a Triton X-100 insoluble structure that retains the biconcave shape of intact erythrocytes, indicating isolation of essentially intact membrane skeletons. These erythrocyte "Triton Skeletons" have been studied morphologically and biochemically, but unbiased proteome analysis of this substructure of the membrane has not been reported. In this study, different extraction buffers and in-depth proteome analyses were used to more fully define the protein composition of this functionally critical macromolecular complex. As expected, the major, well-characterized membrane skeleton proteins and their associated membrane anchors were recovered in good yield. But surprisingly, a substantial number of additional proteins that are not considered in erythrocyte membrane skeleton models were recovered in high yields, including myosin-9, lipid raft proteins (stomatin, flotillin1 and 2), multiple chaperone proteins (HSPs, protein disulfide isomerase and calnexin), and several other proteins. These results show that the membrane skeleton is substantially more complex than previous biochemical studies indicated, and it apparently has localized regions with unique protein compositions and functions. This comprehensive catalog of the membrane skeleton should lead to new insights into erythrocyte membrane biology and pathogenic mutations that perturb membrane stability. Biological significance Current models of erythrocyte membranes describe fairly simple homogenous structures that are incomplete. Proteome analysis of the erythrocyte membrane skeleton shows that it is quite complex and includes a substantial number of proteins whose roles and locations in the membrane are not well defined. Further elucidation of interactions involving these proteins and definition of microdomains in the membrane that contain these proteins should yield novel insights into how the membrane skeleton produces the normal biconcave erythrocyte shape and how it is perturbed in pathological conditions that destabilize the membrane. Copyright © 2015 Elsevier B.V. All rights reserved.

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

PubMed

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

2015-09-01

Calculating the number of confidently identified proteins and estimating false discovery rate (FDR) is a challenge when analyzing very large proteomic data sets such as entire human proteomes. Biological and technical heterogeneity in proteomic experiments further add to the challenge and there are strong differences in opinion regarding the conceptual validity of a protein FDR and no consensus regarding the methodology for protein FDR determination. There are also limitations inherent to the widely used classic target-decoy strategy that particularly show when analyzing very large data sets and that lead to a strong over-representation of decoy identifications. In this study, we investigated the merits of the classic, as well as a novel target-decoy-based protein FDR estimation approach, taking advantage of a heterogeneous data collection comprised of ∼19,000 LC-MS/MS runs deposited in ProteomicsDB (https://www.proteomicsdb.org). The "picked" protein FDR approach treats target and decoy sequences of the same protein as a pair rather than as individual entities and chooses either the target or the decoy sequence depending on which receives the highest score. We investigated the performance of this approach in combination with q-value based peptide scoring to normalize sample-, instrument-, and search engine-specific differences. The "picked" target-decoy strategy performed best when protein scoring was based on the best peptide q-value for each protein yielding a stable number of true positive protein identifications over a wide range of q-value thresholds. We show that this simple and unbiased strategy eliminates a conceptual issue in the commonly used "classic" protein FDR approach that causes overprediction of false-positive protein identification in large data sets. The approach scales from small to very large data sets without losing performance, consistently increases the number of true-positive protein identifications and is readily implemented in proteomics analysis software. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

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

PubMed Central

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

2015-01-01

Calculating the number of confidently identified proteins and estimating false discovery rate (FDR) is a challenge when analyzing very large proteomic data sets such as entire human proteomes. Biological and technical heterogeneity in proteomic experiments further add to the challenge and there are strong differences in opinion regarding the conceptual validity of a protein FDR and no consensus regarding the methodology for protein FDR determination. There are also limitations inherent to the widely used classic target–decoy strategy that particularly show when analyzing very large data sets and that lead to a strong over-representation of decoy identifications. In this study, we investigated the merits of the classic, as well as a novel target–decoy-based protein FDR estimation approach, taking advantage of a heterogeneous data collection comprised of ∼19,000 LC-MS/MS runs deposited in ProteomicsDB (https://www.proteomicsdb.org). The “picked” protein FDR approach treats target and decoy sequences of the same protein as a pair rather than as individual entities and chooses either the target or the decoy sequence depending on which receives the highest score. We investigated the performance of this approach in combination with q-value based peptide scoring to normalize sample-, instrument-, and search engine-specific differences. The “picked” target–decoy strategy performed best when protein scoring was based on the best peptide q-value for each protein yielding a stable number of true positive protein identifications over a wide range of q-value thresholds. We show that this simple and unbiased strategy eliminates a conceptual issue in the commonly used “classic” protein FDR approach that causes overprediction of false-positive protein identification in large data sets. The approach scales from small to very large data sets without losing performance, consistently increases the number of true-positive protein identifications and is readily implemented in proteomics analysis software. PMID:25987413

Identification of candidate cerebrospinal fluid biomarkers in parkinsonism using quantitative proteomics.

PubMed

Magdalinou, N K; Noyce, A J; Pinto, R; Lindstrom, E; Holmén-Larsson, J; Holtta, M; Blennow, K; Morris, H R; Skillbäck, T; Warner, T T; Lees, A J; Pike, I; Ward, M; Zetterberg, H; Gobom, J

2017-04-01

Neurodegenerative parkinsonian syndromes have significant clinical and pathological overlap, making early diagnosis difficult. Cerebrospinal fluid (CSF) biomarkers may aid the differentiation of these disorders, but other than α-synuclein and neurofilament light chain protein, which have limited diagnostic power, specific protein biomarkers remain elusive. To study disease mechanisms and identify possible CSF diagnostic biomarkers through discovery proteomics, which discriminate parkinsonian syndromes from healthy controls. CSF was collected consecutively from 134 participants; Parkinson's disease (n = 26), atypical parkinsonian syndromes (n = 78, including progressive supranuclear palsy (n = 36), multiple system atrophy (n = 28), corticobasal syndrome (n = 14)), and elderly healthy controls (n = 30). Participants were divided into a discovery and a validation set for analysis. The samples were subjected to tryptic digestion, followed by liquid chromatography-mass spectrometry analysis for identification and relative quantification by isobaric labelling. Candidate protein biomarkers were identified based on the relative abundances of the identified tryptic peptides. Their predictive performance was evaluated by analysis of the validation set. 79 tryptic peptides, derived from 26 proteins were found to differ significantly between atypical parkinsonism patients and controls. They included acute phase/inflammatory markers and neuronal/synaptic markers, which were respectively increased or decreased in atypical parkinsonism, while their levels in PD subjects were intermediate between controls and atypical parkinsonism. Using an unbiased proteomic approach, proteins were identified that were able to differentiate atypical parkinsonian syndrome patients from healthy controls. Our study indicates that markers that may reflect neuronal function and/or plasticity, such as the amyloid precursor protein, and inflammatory markers may hold future promise as candidate biomarkers in parkinsonism. Copyright © 2017. Published by Elsevier Ltd.

Proteomics technique opens new frontiers in mobilome research

PubMed Central

Davidson, Andrew D.; Matthews, David A.

2017-01-01

ABSTRACT A large proportion of the genome of most eukaryotic organisms consists of highly repetitive mobile genetic elements. The sum of these elements is called the “mobilome,” which in eukaryotes is made up mostly of transposons. Transposable elements contribute to disease, evolution, and normal physiology by mediating genetic rearrangement, and through the “domestication” of transposon proteins for cellular functions. Although ‘omics studies of mobilome genomes and transcriptomes are common, technical challenges have hampered high-throughput global proteomics analyses of transposons. In a recent paper, we overcame these technical hurdles using a technique called “proteomics informed by transcriptomics” (PIT), and thus published the first unbiased global mobilome-derived proteome for any organism (using cell lines derived from the mosquito Aedes aegypti). In this commentary, we describe our methods in more detail, and summarise our major findings. We also use new genome sequencing data to show that, in many cases, the specific genomic element expressing a given protein can be identified using PIT. This proteomic technique therefore represents an important technological advance that will open new avenues of research into the role that proteins derived from transposons and other repetitive and sequence diverse genetic elements, such as endogenous retroviruses, play in health and disease. PMID:28932623

Analysis of the Plasma Proteome in COPD: Novel Low Abundance Proteins Reflect the Severity of Lung Remodeling

PubMed Central

Merali, Salim; Barrero, Carlos A.; Bowler, Russell P.; Chen, Diane Er; Criner, Gerard; Braverman, Alan; Litwin, Samuel; Yeung, Anthony; Kelsen, Steven G.

2015-01-01

The search for COPD biomarkers has largely employed a targeted approach that focuses on plasma proteins involved in the systemic inflammatory response and in lung injury and repair. This proof of concept study was designed to test the idea that an open, unbiased, in-depth proteomics approach could identify novel, low abundance plasma proteins i.e., ng/mL concentration, which could serve as potential biomarkers. Differentially expressed proteins were identified in a discovery group with severe COPD (FEV1 <45% predicted; n = 10). Subjects with normal lung function matched for age, sex, ethnicity and smoking history served as controls (n = 10). Pooled plasma from each group was exhaustively immunodepleted of abundant proteins, d separated by 1-D gel electrophoresis and extensively fractionated prior to LC-tandem mass spectroscopy (GeLC-MS). Thirty one differentially expressed proteins were identified in the discovery group including markers of lung defense against oxidant stress, alveolar macrophage activation, and lung tissue injury and repair. Four of the 31 proteins (i.e., GRP78, soluble CD163, IL1AP and MSPT9) were measured in a separate verification group of 80 subjects with varying COPD severity by immunoassay. All 4 were significantly altered in COPD and 2 (GRP78 and soluble CD163) correlated with both FEV1 and the extent of emphysema. In-depth, plasma proteomic analysis identified a group of novel, differentially expressed, low abundance proteins that reflect known pathogenic mechanisms and the severity of lung remodeling in COPD. These proteins may also prove useful as COPD biomarkers. PMID:24111704

Analysis of the plasma proteome in COPD: Novel low abundance proteins reflect the severity of lung remodeling.

PubMed

Merali, Salim; Barrero, Carlos A; Bowler, Russell P; Chen, Diane Er; Criner, Gerard; Braverman, Alan; Litwin, Samuel; Yeung, Anthony; Kelsen, Steven G

2014-04-01

The search for COPD biomarkers has largely employed a targeted approach that focuses on plasma proteins involved in the systemic inflammatory response and in lung injury and repair. This proof of concept study was designed to test the idea that an open, unbiased, in-depth proteomics approach could identify novel, low abundance plasma proteins i.e., ng/mL concentration, which could serve as potential biomarkers. Differentially expressed proteins were identified in a discovery group with severe COPD (FEV1 <45% predicted; n = 10). Subjects with normal lung function matched for age, sex, ethnicity and smoking history served as controls (n = 10). Pooled plasma from each group was exhaustively immunodepleted of abundant proteins, d separated by 1-D gel electrophoresis and extensively fractionated prior to LC-tandem mass spectroscopy (GeLC-MS). Thirty one differentially expressed proteins were identified in the discovery group including markers of lung defense against oxidant stress, alveolar macrophage activation, and lung tissue injury and repair. Four of the 31 proteins (i.e., GRP78, soluble CD163, IL1AP and MSPT9) were measured in a separate verification group of 80 subjects with varying COPD severity by immunoassay. All 4 were significantly altered in COPD and 2 (GRP78 and soluble CD163) correlated with both FEV1 and the extent of emphysema. In-depth, plasma proteomic analysis identified a group of novel, differentially expressed, low abundance proteins that reflect known pathogenic mechanisms and the severity of lung remodeling in COPD. These proteins may also prove useful as COPD biomarkers.

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

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

Systems analysis of apoptotic priming in ovarian cancer identifies vulnerabilities and predictors of drug response.

PubMed

Zervantonakis, Ioannis K; Iavarone, Claudia; Chen, Hsing-Yu; Selfors, Laura M; Palakurthi, Sangeetha; Liu, Joyce F; Drapkin, Ronny; Matulonis, Ursula; Leverson, Joel D; Sampath, Deepak; Mills, Gordon B; Brugge, Joan S

2017-08-28

The lack of effective chemotherapies for high-grade serous ovarian cancers (HGS-OvCa) has motivated a search for alternative treatment strategies. Here, we present an unbiased systems-approach to interrogate a panel of 14 well-annotated HGS-OvCa patient-derived xenografts for sensitivity to PI3K and PI3K/mTOR inhibitors and uncover cell death vulnerabilities. Proteomic analysis reveals that PI3K/mTOR inhibition in HGS-OvCa patient-derived xenografts induces both pro-apoptotic and anti-apoptotic signaling responses that limit cell killing, but also primes cells for inhibitors of anti-apoptotic proteins. In-depth quantitative analysis of BCL-2 family proteins and other apoptotic regulators, together with computational modeling and selective anti-apoptotic protein inhibitors, uncovers new mechanistic details about apoptotic regulators that are predictive of drug sensitivity (BIM, caspase-3, BCL-X L ) and resistance (MCL-1, XIAP). Our systems-approach presents a strategy for systematic analysis of the mechanisms that limit effective tumor cell killing and the identification of apoptotic vulnerabilities to overcome drug resistance in ovarian and other cancers.High-grade serous ovarian cancers (HGS-OvCa) frequently develop chemotherapy resistance. Here, the authors through a systematic analysis of proteomic and drug response data of 14 HGS-OvCa PDXs demonstrate that targeting apoptosis regulators can improve response of these tumors to inhibitors of the PI3K/mTOR pathway.

Complementary Proteomic and Biochemical Analysis of Peptidases in Lobster Gastric Juice Uncovers the Functional Role of Individual Enzymes in Food Digestion.

PubMed

Bibo-Verdugo, Betsaida; O'Donoghue, Anthony J; Rojo-Arreola, Liliana; Craik, Charles S; García-Carreño, Fernando

2016-04-01

Crustaceans are a diverse group, distributed in widely variable environmental conditions for which they show an equally extensive range of biochemical adaptations. Some digestive enzymes have been studied by purification/characterization approaches. However, global analysis is crucial to understand how digestive enzymes interplay. Here, we present the first proteomic analysis of the digestive fluid from a crustacean (Homarus americanus) and identify glycosidases and peptidases as the most abundant classes of hydrolytic enzymes. The digestion pathway of complex carbohydrates was predicted by comparing the lobster enzymes to similar enzymes from other crustaceans. A novel and unbiased substrate profiling approach was used to uncover the global proteolytic specificity of gastric juice and determine the contribution of cysteine and aspartic acid peptidases. These enzymes were separated by gel electrophoresis and their individual substrate specificities uncovered from the resulting gel bands. This new technique is called zymoMSP. Each cysteine peptidase cleaves a set of unique peptide bonds and the S2 pocket determines their substrate specificity. Finally, affinity chromatography was used to enrich for a digestive cathepsin D1 to compare its substrate specificity and cold-adapted enzymatic properties to mammalian enzymes. We conclude that the H. americanus digestive peptidases may have useful therapeutic applications, due to their cold-adaptation properties and ability to hydrolyze collagen.

Quantification of Cysteinyl-S-Nitrosylation by Fluorescence in Unbiased Proteomic Studies*

PubMed Central

Wiktorowicz, John E.; Stafford, Susan; Rea, Harriet; Urvil, Petri; Soman, Kizhake; Kurosky, Alexander; Perez-Polo, J. Regino; Savidge, Tor C.

2011-01-01

Cysteinyl-S-nitrosylation has emerged as an important post-translational modification affecting protein function in health and disease. Great emphasis has been placed on global, unbiased quantification of S-nitrosylated proteins due to physiologic and oxidative stimuli. However, current strategies have been hampered by sample loss and altered protein electrophoretic mobility. Here, we describe a novel quantitative approach that combines accurate, sensitive fluorescence modification of cysteine S-nitrosylation that leaves electrophoretic mobility unaffected (SNOFlo), and introduce unique concepts for measuring changes in S-nitrosylation status relative to protein abundance. Its efficacy in defining the functional S-nitrosoproteome is demonstrated in two diverse biological applications: an in vivo rat hypoxia-ischemia reperfusion model, and antimicrobial S-nitrosoglutathione-driven transnitrosylation of an enteric microbial pathogen. The suitability of this approach for investigating endogenous S-nitrosylation is further demonstrated using Ingenuity Pathways analysis that identified nervous system and cellular development networks as the top two networks. Functional analysis of differentially S-nitrosylated proteins indicated their involvement in apoptosis, branching morphogenesis of axons, cortical neurons, and sympathetic neurites, neurogenesis, and calcium signaling. Major abundance changes were also observed for fibrillar proteins known to be stress-responsive in neurons and glia. Thus, both examples demonstrate the technique’s power in confirming the widespread involvement of S-nitrosylation in hypoxia-ischemia/reperfusion injury and in antimicrobial host responses. PMID:21615140

Analytical Utility of Mass Spectral Binning in Proteomic Experiments by SPectral Immonium Ion Detection (SPIID)*

PubMed Central

Kelstrup, Christian D.; Frese, Christian; Heck, Albert J. R.; Olsen, Jesper V.; Nielsen, Michael L.

2014-01-01

Unambiguous identification of tandem mass spectra is a cornerstone in mass-spectrometry-based proteomics. As the study of post-translational modifications (PTMs) by means of shotgun proteomics progresses in depth and coverage, the ability to correctly identify PTM-bearing peptides is essential, increasing the demand for advanced data interpretation. Several PTMs are known to generate unique fragment ions during tandem mass spectrometry, the so-called diagnostic ions, which unequivocally identify a given mass spectrum as related to a specific PTM. Although such ions offer tremendous analytical advantages, algorithms to decipher MS/MS spectra for the presence of diagnostic ions in an unbiased manner are currently lacking. Here, we present a systematic spectral-pattern-based approach for the discovery of diagnostic ions and new fragmentation mechanisms in shotgun proteomics datasets. The developed software tool is designed to analyze large sets of high-resolution peptide fragmentation spectra independent of the fragmentation method, instrument type, or protease employed. To benchmark the software tool, we analyzed large higher-energy collisional activation dissociation datasets of samples containing phosphorylation, ubiquitylation, SUMOylation, formylation, and lysine acetylation. Using the developed software tool, we were able to identify known diagnostic ions by comparing histograms of modified and unmodified peptide spectra. Because the investigated tandem mass spectra data were acquired with high mass accuracy, unambiguous interpretation and determination of the chemical composition for the majority of detected fragment ions was feasible. Collectively we present a freely available software tool that allows for comprehensive and automatic analysis of analogous product ions in tandem mass spectra and systematic mapping of fragmentation mechanisms related to common amino acids. PMID:24895383

Exploring the Human Plasma Proteome for Humoral Mediators of Remote Ischemic Preconditioning - A Word of Caution

PubMed Central

Helgeland, Erik; Breivik, Lars Ertesvåg; Vaudel, Marc; Svendsen, Øyvind Sverre; Garberg, Hilde; Nordrehaug, Jan Erik; Berven, Frode Steingrimsen; Jonassen, Anne Kristine

2014-01-01

Despite major advances in early revascularization techniques, cardiovascular diseases are still the leading cause of death worldwide, and myocardial infarctions contribute heavily to this. Over the past decades, it has become apparent that reperfusion of blood to a previously ischemic area of the heart causes damage in and of itself, and that this ischemia reperfusion induced injury can be reduced by up to 50% by mechanical manipulation of the blood flow to the heart. The recent discovery of remote ischemic preconditioning (RIPC) provides a non-invasive approach of inducing this cardioprotection at a distance. Finding its endogenous mediators and their operative mode is an important step toward increasing the ischemic tolerance. The release of humoral factor(s) upon RIPC was recently demonstrated and several candidate proteins were published as possible mediators of the cardioprotection. Before clinical applicability, these potential biomarkers and their efficiency must be validated, a task made challenging by the large heterogeneity in reported data and results. Here, in an attempt to reproduce and provide more experimental data on these mediators, we conducted an unbiased in-depth analysis of the human plasma proteome before and after RIPC. From the 68 protein markers reported in the literature, only 28 could be mapped to manually reviewed (Swiss-Prot) protein sequences. 23 of them were monitored in our untargeted experiment. However, their significant regulation could not be reproducibly estimated. In fact, among the 394 plasma proteins we accurately quantified, no significant regulation could be confidently and reproducibly assessed. This indicates that it is difficult to both monitor and reproduce published data from experiments exploring for RIPC induced plasma proteomic regulations, and suggests that further work should be directed towards small humoral factors. To simplify this task, we made our proteomic dataset available via ProteomeXchange, where scientists can mine for novel potential targets. PMID:25333471

Proteomic analysis of protein phosphatase Z1 from Candida albicans

PubMed Central

Pfliegler, Walter P.; Petrényi, Katalin; Boros, Enikő; Pócsi, István; Tőzsér, József; Dombrádi, Viktor

2017-01-01

Protein phosphatase Z is a “novel type” fungus specific serine/threonine protein phosphatase. Previously our research group identified the CaPPZ1 gene in the opportunistic pathogen Candida albicans and reported that the gene deletion had several important physiological consequences. In order to reveal the protein targets and the associated mechanisms behind the functions of the phosphatase a proteomic method was adopted for the comparison of the cappz1 deletion mutant and the genetically matching QMY23 control strain. Proteins extracted from the control and deletion mutant strains were separated by two-dimensional gel electrophoresis and the protein spots were stained with RuBPS and Pro-Q Diamond in order to visualize the total proteome and the phosphoproteome, respectively. The alterations in spot intensities were determined by densitometry and were analysed with the Delta2D (Decodon) software. Spots showing significantly different intensities between the mutant and control strains were excised from the gels and were digested with trypsin. The resulting peptides were identified by LC-MS/MS mass spectrometry. As many as 15 protein spots were found that exhibited significant changes in their intensity upon the deletion of the phosphatase and 20 phosphoproteins were identified in which the level of phosphorylation was modified significantly in the mutant. In agreement with previous findings we found that the affected proteins function in protein synthesis, oxidative stress response, regulation of morphology and metabolism. Among these proteins we identified two potential CaPpz1 substrates (Eft2 and Rpp0) that may regulate the elongation step of translation. RT-qPCR experiments revealed that the expression of the genes coding for the affected proteins was not altered significantly. Thus, the absence of CaPpz1 exerted its effects via protein synthesis/degradation and phosphorylation/dephosphorylation. In addition, our proteomics data strongly suggested a role for CaPpz1 in biofilm formation, was confirmed experimentally. Thus our unbiased proteomic approach lead to the discovery of a novel function for this phosphatase in C. albicans. PMID:28837603

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.

A proteome-scale map of the human interactome network

PubMed Central

Rolland, Thomas; Taşan, Murat; Charloteaux, Benoit; Pevzner, Samuel J.; Zhong, Quan; Sahni, Nidhi; Yi, Song; Lemmens, Irma; Fontanillo, Celia; Mosca, Roberto; Kamburov, Atanas; Ghiassian, Susan D.; Yang, Xinping; Ghamsari, Lila; Balcha, Dawit; Begg, Bridget E.; Braun, Pascal; Brehme, Marc; Broly, Martin P.; Carvunis, Anne-Ruxandra; Convery-Zupan, Dan; Corominas, Roser; Coulombe-Huntington, Jasmin; Dann, Elizabeth; Dreze, Matija; Dricot, Amélie; Fan, Changyu; Franzosa, Eric; Gebreab, Fana; Gutierrez, Bryan J.; Hardy, Madeleine F.; Jin, Mike; Kang, Shuli; Kiros, Ruth; Lin, Guan Ning; Luck, Katja; MacWilliams, Andrew; Menche, Jörg; Murray, Ryan R.; Palagi, Alexandre; Poulin, Matthew M.; Rambout, Xavier; Rasla, John; Reichert, Patrick; Romero, Viviana; Ruyssinck, Elien; Sahalie, Julie M.; Scholz, Annemarie; Shah, Akash A.; Sharma, Amitabh; Shen, Yun; Spirohn, Kerstin; Tam, Stanley; Tejeda, Alexander O.; Trigg, Shelly A.; Twizere, Jean-Claude; Vega, Kerwin; Walsh, Jennifer; Cusick, Michael E.; Xia, Yu; Barabási, Albert-László; Iakoucheva, Lilia M.; Aloy, Patrick; De Las Rivas, Javier; Tavernier, Jan; Calderwood, Michael A.; Hill, David E.; Hao, Tong; Roth, Frederick P.; Vidal, Marc

2014-01-01

SUMMARY Just as reference genome sequences revolutionized human genetics, reference maps of interactome networks will be critical to fully understand genotype-phenotype relationships. Here, we describe a systematic map of ~14,000 high-quality human binary protein-protein interactions. At equal quality, this map is ~30% larger than what is available from small-scale studies published in the literature in the last few decades. While currently available information is highly biased and only covers a relatively small portion of the proteome, our systematic map appears strikingly more homogeneous, revealing a “broader” human interactome network than currently appreciated. The map also uncovers significant inter-connectivity between known and candidate cancer gene products, providing unbiased evidence for an expanded functional cancer landscape, while demonstrating how high quality interactome models will help “connect the dots” of the genomic revolution. PMID:25416956

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.

A proteomic approach to identify endosomal cargoes controlling cancer invasiveness

PubMed Central

Diaz-Vera, Jesica; Palmer, Sarah; Hernandez-Fernaud, Juan Ramon; Dornier, Emmanuel; Mitchell, Louise E.; Macpherson, Iain; Edwards, Joanne; Zanivan, Sara

2017-01-01

ABSTRACT We have previously shown that Rab17, a small GTPase associated with epithelial polarity, is specifically suppressed by ERK2 (also known as MAPK1) signalling to promote an invasive phenotype. However, the mechanisms through which Rab17 loss permits invasiveness, and the endosomal cargoes that are responsible for mediating this, are unknown. Using quantitative mass spectrometry-based proteomics, we have found that knockdown of Rab17 leads to a highly selective reduction in the cellular levels of a v-SNARE (Vamp8). Moreover, proteomics and immunofluorescence indicate that Vamp8 is associated with Rab17 at late endosomes. Reduced levels of Vamp8 promote transition between ductal carcinoma in situ (DCIS) and a more invasive phenotype. We developed an unbiased proteomic approach to elucidate the complement of receptors that redistributes between endosomes and the plasma membrane, and have pin-pointed neuropilin-2 (NRP2) as a key pro-invasive cargo of Rab17- and Vamp8-regulated trafficking. Indeed, reduced Rab17 or Vamp8 levels lead to increased mobilisation of NRP2-containing late endosomes and upregulated cell surface expression of NRP2. Finally, we show that NRP2 is required for the basement membrane disruption that accompanies the transition between DCIS and a more invasive phenotype. PMID:28062852

Integrative Analysis of Many RNA-Seq Datasets to Study Alternative Splicing

PubMed Central

Li, Wenyuan; Dai, Chao; Kang, Shuli; Zhou, Xianghong Jasmine

2014-01-01

Alternative splicing is an important gene regulatory mechanism that dramatically increases the complexity of the proteome. However, how alternative splicing is regulated and how transcription and splicing are coordinated are still poorly understood, and functions of transcript isoforms have been studied only in a few limited cases. Nowadays, RNA-seq technology provides an exceptional opportunity to study alternative splicing on genome-wide scales and in an unbiased manner. With the rapid accumulation of data in public repositories, new challenges arise from the urgent need to effectively integrate many different RNA-seq datasets for study alterative splicing. This paper discusses a set of advanced computational methods that can integrate and analyze many RNA-seq datasets to systematically identify splicing modules, unravel the coupling of transcription and splicing, and predict the functions of splicing isoforms on a genome-wide scale. PMID:24583115

Protein-phosphotyrosine proteome profiling by superbinder-SH2 domain affinity purification mass spectrometry, sSH2-AP-MS.

PubMed

Tong, Jiefei; Cao, Biyin; Martyn, Gregory D; Krieger, Jonathan R; Taylor, Paul; Yates, Bradley; Sidhu, Sachdev S; Li, Shawn S C; Mao, Xinliang; Moran, Michael F

2017-03-01

Recently, "superbinder" SH2 domain variants with three amino acid substitutions (sSH2) were reported to have 100-fold or greater affinity for protein-phosphotyrosine (pY) than natural SH2 domains. Here we report a protocol in which His-tagged Src sSH2 efficiently captures pY-peptides from protease-digested HeLa cell total protein extracts. Affinity purification of pY-peptides by this method shows little bias for pY-proximal amino acid sequences, comparable to that achieved by using antibodies to pY, but with equal or higher yield. Superbinder-SH2 affinity purification mass spectrometry (sSH2-AP-MS) therefore provides an efficient and economical approach for unbiased pY-directed phospho-proteome profiling without the use of antibodies. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Standardized Profiling of The Membrane-Enriched Proteome of Mouse Dorsal Root Ganglia (DRG) Provides Novel Insights Into Chronic Pain.

PubMed

Rouwette, Tom; Sondermann, Julia; Avenali, Luca; Gomez-Varela, David; Schmidt, Manuela

2016-06-01

Chronic pain is a complex disease with limited treatment options. Several profiling efforts have been employed with the aim to dissect its molecular underpinnings. However, generated results are often inconsistent and nonoverlapping, which is largely because of inherent technical constraints. Emerging data-independent acquisition (DIA)-mass spectrometry (MS) has the potential to provide unbiased, reproducible and quantitative proteome maps - a prerequisite for standardization among experiments. Here, we designed a DIA-based proteomics workflow to profile changes in the abundance of dorsal root ganglia (DRG) proteins in two mouse models of chronic pain, inflammatory and neuropathic. We generated a DRG-specific spectral library containing 3067 DRG proteins, which enables their standardized quantification by means of DIA-MS in any laboratory. Using this resource, we profiled 2526 DRG proteins in each biological replicate of both chronic pain models and respective controls with unprecedented reproducibility. We detected numerous differentially regulated proteins, the majority of which exhibited pain model-specificity. Our approach recapitulates known biology and discovers dozens of proteins that have not been characterized in the somatosensory system before. Functional validation experiments and analysis of mouse pain behaviors demonstrate that indeed meaningful protein alterations were discovered. These results illustrate how the application of DIA-MS can open new avenues to achieve the long-awaited standardization in the molecular dissection of pathologies of the somatosensory system. Therefore, our findings provide a valuable framework to qualitatively extend our understanding of chronic pain and somatosensation. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Quantitative proteomics identifies NCOA4 as the cargo receptor mediating ferritinophagy.

PubMed

Mancias, Joseph D; Wang, Xiaoxu; Gygi, Steven P; Harper, J Wade; Kimmelman, Alec C

2014-05-01

Autophagy, the process by which proteins and organelles are sequestered in double-membrane structures called autophagosomes and delivered to lysosomes for degradation, is critical in diseases such as cancer and neurodegeneration. Much of our understanding of this process has emerged from analysis of bulk cytoplasmic autophagy, but our understanding of how specific cargo, including organelles, proteins or intracellular pathogens, are targeted for selective autophagy is limited. Here we use quantitative proteomics to identify a cohort of novel and known autophagosome-enriched proteins in human cells, including cargo receptors. Like known cargo receptors, nuclear receptor coactivator 4 (NCOA4) was highly enriched in autophagosomes, and associated with ATG8 proteins that recruit cargo-receptor complexes into autophagosomes. Unbiased identification of NCOA4-associated proteins revealed ferritin heavy and light chains, components of an iron-filled cage structure that protects cells from reactive iron species but is degraded via autophagy to release iron through an unknown mechanism. We found that delivery of ferritin to lysosomes required NCOA4, and an inability of NCOA4-deficient cells to degrade ferritin led to decreased bioavailable intracellular iron. This work identifies NCOA4 as a selective cargo receptor for autophagic turnover of ferritin (ferritinophagy), which is critical for iron homeostasis, and provides a resource for further dissection of autophagosomal cargo-receptor connectivity.

Aptamer-based multiplexed proteomic technology for biomarker discovery.

PubMed

Gold, Larry; Ayers, Deborah; Bertino, Jennifer; Bock, Christopher; Bock, Ashley; Brody, Edward N; Carter, Jeff; Dalby, Andrew B; Eaton, Bruce E; Fitzwater, Tim; Flather, Dylan; Forbes, Ashley; Foreman, Trudi; Fowler, Cate; Gawande, Bharat; Goss, Meredith; Gunn, Magda; Gupta, Shashi; Halladay, Dennis; Heil, Jim; Heilig, Joe; Hicke, Brian; Husar, Gregory; Janjic, Nebojsa; Jarvis, Thale; Jennings, Susan; Katilius, Evaldas; Keeney, Tracy R; Kim, Nancy; Koch, Tad H; Kraemer, Stephan; Kroiss, Luke; Le, Ngan; Levine, Daniel; Lindsey, Wes; Lollo, Bridget; Mayfield, Wes; Mehan, Mike; Mehler, Robert; Nelson, Sally K; Nelson, Michele; Nieuwlandt, Dan; Nikrad, Malti; Ochsner, Urs; Ostroff, Rachel M; Otis, Matt; Parker, Thomas; Pietrasiewicz, Steve; Resnicow, Daniel I; Rohloff, John; Sanders, Glenn; Sattin, Sarah; Schneider, Daniel; Singer, Britta; Stanton, Martin; Sterkel, Alana; Stewart, Alex; Stratford, Suzanne; Vaught, Jonathan D; Vrkljan, Mike; Walker, Jeffrey J; Watrobka, Mike; Waugh, Sheela; Weiss, Allison; Wilcox, Sheri K; Wolfson, Alexey; Wolk, Steven K; Zhang, Chi; Zichi, Dom

2010-12-07

The interrogation of proteomes ("proteomics") in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma). Our current assay measures 813 proteins with low limits of detection (1 pM median), 7 logs of overall dynamic range (~100 fM-1 µM), and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states. We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.

Proteomic and genomic studies of non-alcoholic fatty liver disease - clues in the pathogenesis

PubMed Central

Lim, Jun Wei; Dillon, John; Miller, Michael

2014-01-01

Non-alcoholic fatty liver disease (NAFLD) is a widely prevalent hepatic disorder that covers wide spectrum of liver pathology. NAFLD is strongly associated with liver inflammation, metabolic hyperlipidaemia and insulin resistance. Frequently, NAFLD has been considered as the hepatic manifestation of metabolic syndrome. The pathophysiology of NAFLD has not been fully elucidated. Some patients can remain in the stage of simple steatosis, which generally is a benign condition; whereas others can develop liver inflammation and progress into non-alcoholic steatohepatitis, fibrosis, cirrhosis and hepatocellular carcinoma. The mechanism behind the progression is still not fully understood. Much ongoing proteomic researches have focused on discovering the unbiased circulating biochemical markers to allow early detection and treatment of NAFLD. Comprehensive genomic studies have also begun to provide new insights into the gene polymorphism to understand patient-disease variations. Therefore, NAFLD is considered a complex and mutifactorial disease phenotype resulting from environmental exposures acting on a susceptible polygenic background. This paper reviewed the current status of proteomic and genomic studies that have contributed to the understanding of NAFLD pathogenesis. For proteomics section, this review highlighted functional proteins that involved in: (1) transportation; (2) metabolic pathway; (3) acute phase reaction; (4) anti-inflammatory; (5) extracellular matrix; and (6) immune system. In the genomic studies, this review will discuss genes which involved in: (1) lipolysis; (2) adipokines; and (3) cytokines production. PMID:25024592

Haem-activated promiscuous targeting of artemisinin in Plasmodium falciparum.

PubMed

Wang, Jigang; Zhang, Chong-Jing; Chia, Wan Ni; Loh, Cheryl C Y; Li, Zhengjun; Lee, Yew Mun; He, Yingke; Yuan, Li-Xia; Lim, Teck Kwang; Liu, Min; Liew, Chin Xia; Lee, Yan Quan; Zhang, Jianbin; Lu, Nianci; Lim, Chwee Teck; Hua, Zi-Chun; Liu, Bin; Shen, Han-Ming; Tan, Kevin S W; Lin, Qingsong

2015-12-22

The mechanism of action of artemisinin and its derivatives, the most potent of the anti-malarial drugs, is not completely understood. Here we present an unbiased chemical proteomics analysis to directly explore this mechanism in Plasmodium falciparum. We use an alkyne-tagged artemisinin analogue coupled with biotin to identify 124 artemisinin covalent binding protein targets, many of which are involved in the essential biological processes of the parasite. Such a broad targeting spectrum disrupts the biochemical landscape of the parasite and causes its death. Furthermore, using alkyne-tagged artemisinin coupled with a fluorescent dye to monitor protein binding, we show that haem, rather than free ferrous iron, is predominantly responsible for artemisinin activation. The haem derives primarily from the parasite's haem biosynthesis pathway at the early ring stage and from haemoglobin digestion at the latter stages. Our results support a unifying model to explain the action and specificity of artemisinin in parasite killing.

Haem-activated promiscuous targeting of artemisinin in Plasmodium falciparum

PubMed Central

Wang, Jigang; Zhang, Chong-Jing; Chia, Wan Ni; Loh, Cheryl C. Y.; Li, Zhengjun; Lee, Yew Mun; He, Yingke; Yuan, Li-Xia; Lim, Teck Kwang; Liu, Min; Liew, Chin Xia; Lee, Yan Quan; Zhang, Jianbin; Lu, Nianci; Lim, Chwee Teck; Hua, Zi-Chun; Liu, Bin; Shen, Han-Ming; Tan, Kevin S. W.; Lin, Qingsong

2015-01-01

The mechanism of action of artemisinin and its derivatives, the most potent of the anti-malarial drugs, is not completely understood. Here we present an unbiased chemical proteomics analysis to directly explore this mechanism in Plasmodium falciparum. We use an alkyne-tagged artemisinin analogue coupled with biotin to identify 124 artemisinin covalent binding protein targets, many of which are involved in the essential biological processes of the parasite. Such a broad targeting spectrum disrupts the biochemical landscape of the parasite and causes its death. Furthermore, using alkyne-tagged artemisinin coupled with a fluorescent dye to monitor protein binding, we show that haem, rather than free ferrous iron, is predominantly responsible for artemisinin activation. The haem derives primarily from the parasite's haem biosynthesis pathway at the early ring stage and from haemoglobin digestion at the latter stages. Our results support a unifying model to explain the action and specificity of artemisinin in parasite killing. PMID:26694030

Protein Expression Profile of Rat Type Two Alveolar Epithelial Cells During Hyperoxic Stress and Recovery

NASA Astrophysics Data System (ADS)

Bhargava, Maneesh

Rationale: In rodent model systems, the sequential changes in lung morphology resulting from hyperoxic injury are well characterized, and are similar to changes in human acute respiratory distress syndrome (ARDS). In the injured lung, alveolar type two (AT2) epithelial cells play a critical role restoring the normal alveolar structure. Thus characterizing the changes in AT2 cells will provide insights into the mechanisms underpinning the recovery from lung injury. Methods: We applied an unbiased systems level proteomics approach to elucidate molecular mechanisms contributing to lung repair in a rat hyperoxic lung injury model. AT2 cells were isolated from rat lungs at predetermined intervals during hyperoxic injury and recovery. Protein expression profiles were determined by using iTRAQRTM with tandem mass spectrometry. Results: Of 959 distinct proteins identified, 183 significantly changed in abundance during the injury-recovery cycle. Gene Ontology enrichment analysis identified cell cycle, cell differentiation, cell metabolism, ion homeostasis, programmed cell death, ubiquitination, and cell migration to be significantly enriched by these proteins. Gene Set Enrichment Analysis of data acquired during lung repair revealed differential expression of gene sets that control multicellular organismal development, systems development, organ development, and chemical homeostasis. More detailed analysis identified activity in two regulatory pathways, JNK and miR 374. A Short Time-series Expression Miner (STEM) algorithm identified protein clusters with coherent changes during injury and repair. Conclusion: Coherent changes occur in the AT2 cell proteome in response to hyperoxic stress. These findings offer guidance regarding the specific molecular mechanisms governing repair of the injured lung.

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

PubMed

Wesseling, Hendrik; Elgersma, Ype; Bahn, Sabine

2017-01-01

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

Proteomic Profiling Reveals Adaptive Responses to Surgical Myocardial Ischemia Reperfusion in Hibernating Arctic Ground Squirrels Compared to Rats

PubMed Central

Quinones, Quintin J.; Zhang, Zhiquan; Ma, Qing; Smith, Michael P.; Soderblom, Erik; Moseley, M. Arthur; Bain, James; Newgard, Christopher B.; Muehlbauer, Michael J.; Hirschey, Matthew; Drew, Kelly L.; Barnes, Brian M.; Podgoreanu, Mihai V.

2016-01-01

Background Hibernation is an adaptation to extreme environments known to provide organ protection against ischemia-reperfusion (I/R) injury. An unbiased systems approach was utilized to investigate hibernation-induced changes characteristic of the hibernator cardioprotective phenotype, by comparing the myocardial proteome of winter hibernating arctic ground squirrels (HIB AGS), summer active (SA) AGS, and rats subjected to I/R, and further correlating with targeted metabolic changes. Methods In a well-defined rodent model of I/R by deep hypothermic circulatory arrest followed by 3h or 24h of reperfusion or sham, myocardial protein abundance in AGS (HIB, SA) and rats (n=4-5/group) was quantified by label-free proteomics (n=4-5/group), and correlated with metabolic changes. Results Compared to rats, HIB AGS displayed markedly reduced plasma levels of Troponin I, myocardial apoptosis, and left ventricular contractile dysfunction. Of the 1,320 rat and 1,478 AGS proteins identified, 545 were differentially expressed between HIB AGS and rat hearts (47% upregulated, 53% downregulated). Gene ontology analysis revealed downregulation in HIB AGS hearts of most proteins involved in mitochondrial energy transduction, including electron transport chain complexes, acetyl CoA biosynthesis, Krebs cycle, glycolysis and ketogenesis. Conversely, fatty acid oxidation enzymes and Sirtuin-3 were upregulated in HIB AGS, with preserved peroxisome proliferator activated receptor-α activity and reduced tissue levels of acylcarnitines and ceramides following I/R. Conclusions Natural cardioprotective adaptations in hibernators involve extensive metabolic remodeling, featuring increased expression of fatty acid metabolic proteins and reduced levels of toxic lipid metabolites. Robust upregulation of Sirtuin-3 suggests that post-translational modifications may underlie organ protection in hibernating mammals. PMID:27187119

Matrix metalloproteinase proteomics: substrates, targets, and therapy.

PubMed

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

2009-10-01

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

Isocitrate dehydrogenase mutations confer dasatinib hypersensitivity and SRC-dependence in intrahepatic cholangiocarcinoma

PubMed Central

Saha, Supriya K.; Gordan, John D.; Kleinstiver, Benjamin P.; Vu, Phuong; Najem, Mortada S.; Yeo, Jia-Chi; Shi, Lei; Kato, Yasutaka; Levin, Rebecca S.; Webber, James T.; Damon, Leah J.; Egan, Regina K.; Greninger, Patricia; McDermott, Ultan; Garnett, Mathew J.; Jenkins, Roger L.; Rieger-Christ, Kimberly M.; Sullivan, Travis B.; Hezel, Aram F.; Liss, Andrew S.; Mizukami, Yusuke; Goyal, Lipika; Ferrone, Cristina R.; Zhu, Andrew X.; Joung, J. Keith; Shokat, Kevan M.; Benes, Cyril H.; Bardeesy, Nabeel

2017-01-01

Intrahepatic cholangiocarcinoma (ICC) is an aggressive liver bile duct malignancy exhibiting frequent isocitrate dehydrogenase (IDH1/IDH2) mutations. Through a high-throughput drug screen of a large panel of cancer cell lines including 17 biliary tract cancers, we found that IDH mutant (IDHm) ICC cells demonstrate a striking response to the multi-kinase inhibitor dasatinib, with the highest sensitivity among 682 solid tumor cell lines. Using unbiased proteomics to capture the activated kinome and CRISPR/Cas9-based genome editing to introduce dasatinib-resistant ‘gatekeeper’ mutant kinases, we identified SRC as a critical dasatinib target in IDHm ICC. Importantly, dasatinib-treated IDHm xenografts exhibited pronounced apoptosis and tumor regression. Our results show that IDHm ICC cells have a unique dependency on SRC and suggest that dasatinib may have therapeutic benefit against IDHm ICC. Moreover, these proteomic and genome-editing strategies provide a systematic and broadly applicable approach to define targets of kinase inhibitors underlying drug responsiveness. PMID:27231123

Aptamer-Based Multiplexed Proteomic Technology for Biomarker Discovery

PubMed Central

Gold, Larry; Ayers, Deborah; Bertino, Jennifer; Bock, Christopher; Bock, Ashley; Brody, Edward N.; Carter, Jeff; Dalby, Andrew B.; Eaton, Bruce E.; Fitzwater, Tim; Flather, Dylan; Forbes, Ashley; Foreman, Trudi; Fowler, Cate; Gawande, Bharat; Goss, Meredith; Gunn, Magda; Gupta, Shashi; Halladay, Dennis; Heil, Jim; Heilig, Joe; Hicke, Brian; Husar, Gregory; Janjic, Nebojsa; Jarvis, Thale; Jennings, Susan; Katilius, Evaldas; Keeney, Tracy R.; Kim, Nancy; Koch, Tad H.; Kraemer, Stephan; Kroiss, Luke; Le, Ngan; Levine, Daniel; Lindsey, Wes; Lollo, Bridget; Mayfield, Wes; Mehan, Mike; Mehler, Robert; Nelson, Sally K.; Nelson, Michele; Nieuwlandt, Dan; Nikrad, Malti; Ochsner, Urs; Ostroff, Rachel M.; Otis, Matt; Parker, Thomas; Pietrasiewicz, Steve; Resnicow, Daniel I.; Rohloff, John; Sanders, Glenn; Sattin, Sarah; Schneider, Daniel; Singer, Britta; Stanton, Martin; Sterkel, Alana; Stewart, Alex; Stratford, Suzanne; Vaught, Jonathan D.; Vrkljan, Mike; Walker, Jeffrey J.; Watrobka, Mike; Waugh, Sheela; Weiss, Allison; Wilcox, Sheri K.; Wolfson, Alexey; Wolk, Steven K.; Zhang, Chi; Zichi, Dom

2010-01-01

Background The interrogation of proteomes (“proteomics”) in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine. Methodology/Principal Findings We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma). Our current assay measures 813 proteins with low limits of detection (1 pM median), 7 logs of overall dynamic range (∼100 fM–1 µM), and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states. Conclusions/Significance We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine. PMID:21165148

In Planta Determination of the mRNA-Binding Proteome of Arabidopsis Etiolated Seedlings

PubMed Central

Evers, Maurits; Alleaume, Anne-Marie; Horos, Rastislav

2016-01-01

RNA binding proteins (RBPs) control the fate and expression of a transcriptome. Despite this fundamental importance, our understanding of plant RBPs is rudimentary, being mainly derived via bioinformatic extrapolation from other kingdoms. Here, we adapted the mRNA-protein interactome capture method to investigate the RNA binding proteome in planta. From Arabidopsis thaliana etiolated seedlings, we captured more than 700 proteins, including 300 with high confidence that we have defined as the At-RBP set. Approximately 75% of these At-RBPs are bioinformatically linked with RNA biology, containing a diversity of canonical RNA binding domains (RBDs). As no prior experimental RNA binding evidence exists for the majority of these proteins, their capture now authenticates them as RBPs. Moreover, we identified protein families harboring emerging and potentially novel RBDs, including WHIRLY, LIM, ALBA, DUF1296, and YTH domain-containing proteins, the latter being homologous to animal RNA methylation readers. Other At-RBP set proteins include major signaling proteins, cytoskeleton-associated proteins, membrane transporters, and enzymes, suggesting the scope and function of RNA-protein interactions within a plant cell is much broader than previously appreciated. Therefore, our foundation data set has provided an unbiased insight into the RNA binding proteome of plants, on which future investigations into plant RBPs can be based. PMID:27729395

Acid sphingomyelinase deficiency in Western diet-fed mice protects against adipocyte hypertrophy and diet-induced liver steatosis.

PubMed

Sydor, Svenja; Sowa, Jan-Peter; Megger, Dominik A; Schlattjan, Martin; Jafoui, Sami; Wingerter, Lena; Carpinteiro, Alexander; Baba, Hideo A; Bechmann, Lars P; Sitek, Barbara; Gerken, Guido; Gulbins, Erich; Canbay, Ali

2017-05-01

Alterations in sphingolipid and ceramide metabolism have been associated with various diseases, including nonalcoholic fatty liver disease (NAFLD). Acid sphingomyelinase (ASM) converts the membrane lipid sphingomyelin to ceramide, thereby affecting membrane composition and domain formation. We investigated the ways in which the Asm knockout (Smpd1 -/- ) genotype affects diet-induced NAFLD. Smpd1 -/- mice and wild type controls were fed either a standard or Western diet (WD) for 6 weeks. Liver and adipose tissue morphology and mRNA expression were assessed. Quantitative proteome analysis of liver tissue was performed. Expression of selected genes was quantified in adipose and liver tissue of obese NAFLD patients. Although Smpd1 -/- mice exhibited basal steatosis with normal chow, no aggravation of NAFLD-type injury was observed with a Western diet. This protective effect was associated with the absence of adipocyte hypertrophy and the increased expression of genes associated with brown adipocyte differentiation. In white adipose tissue from obese patients with NAFLD, no expression of these genes was detectable. To further elucidate which pathways in liver tissue may be affected by Smpd1 -/- , we performed an unbiased proteome analysis. Protein expression in WD-fed Smpd1 -/- mice indicated a reduction in Rictor (mTORC2) activity; this reduction was confirmed by diminished Akt phosphorylation and altered mRNA expression of Rictor target genes. These findings indicate that the protective effect of Asm deficiency on diet-induced steatosis is conferred by alterations in adipocyte morphology and lipid metabolism and by reductions in Rictor activation.

Determination of Protein Interactome of Transcription Factor Sox2 in Embryonic Stem Cells Engineered for Inducible Expression of Four Reprogramming Factors*

PubMed Central

Gao, Zhiguang; Cox, Jesse L.; Gilmore, Joshua M.; Ormsbee, Briana D.; Mallanna, Sunil K.; Washburn, Michael P.; Rizzino, Angie

2012-01-01

Unbiased proteomic screens provide a powerful tool for defining protein-protein interaction networks. Previous studies employed multidimensional protein identification technology to identify the Sox2-interactome in embryonic stem cells (ESC) undergoing differentiation in response to a small increase in the expression of epitope-tagged Sox2. Thus far the Sox2-interactome in ESC has not been determined. To identify the Sox2-interactome in ESC, we engineered ESC for inducible expression of different combinations of epitope-tagged Sox2 along with Oct4, Klf4, and c-Myc. Epitope-tagged Sox2 was used to circumvent the lack of suitable Sox2 antibodies needed to perform an unbiased proteomic screen of Sox2-associated proteins. Although i-OS-ESC differentiate when both Oct4 and Sox2 are elevated, i-OSKM-ESC do not differentiate even when the levels of the four transcription factors are coordinately elevated ∼2–3-fold. Our findings with i-OS-ESC and i-OSKM-ESC provide new insights into the reasons why ESC undergo differentiation when Sox2 and Oct4 are elevated in ESC. Importantly, the use of i-OSKM-ESC enabled us to identify the Sox2-interactome in undifferentiated ESC. Using multidimensional protein identification technology, we identified >70 proteins that associate with Sox2 in ESC. We extended these findings by testing the function of the Sox2-assoicated protein Smarcd1 and demonstrate that knockdown of Smarcd1 disrupts the self-renewal of ESC and induces their differentiation. Together, our work provides the first description of the Sox2-interactome in ESC and indicates that Sox2 along with other master regulators is part of a highly integrated protein-protein interaction landscape in ESC. PMID:22334693

Examining hemodialyzer membrane performance using proteomic technologies

PubMed Central

Bonomini, Mario; Pieroni, Luisa; Di Liberato, Lorenzo; Sirolli, Vittorio; Urbani, Andrea

2018-01-01

The success and the quality of hemodialysis therapy are mainly related to both clearance and biocompatibility properties of the artificial membrane packed in the hemodialyzer. Performance of a membrane is strongly influenced by its interaction with the plasma protein repertoire during the extracorporeal procedure. Recognition that a number of medium–high molecular weight solutes, including proteins and protein-bound molecules, are potentially toxic has prompted the development of more permeable membranes. Such membrane engineering, however, may cause loss of vital proteins, with membrane removal being nonspecific. In addition, plasma proteins can be adsorbed onto the membrane surface upon blood contact during dialysis. Adsorption can contribute to the removal of toxic compounds and governs the biocompatibility of a membrane, since surface-adsorbed proteins may trigger a variety of biologic blood pathways with pathophysiologic consequences. Over the last years, use of proteomic approaches has allowed polypeptide spectrum involved in the process of hemodialysis, a key issue previously hampered by lack of suitable technology, to be assessed in an unbiased manner and in its full complexity. Proteomics has been successfully applied to identify and quantify proteins in complex mixtures such as dialysis outflow fluid and fluid desorbed from dialysis membrane containing adsorbed proteins. The identified proteins can also be characterized by their involvement in metabolic and signaling pathways, molecular networks, and biologic processes through application of bioinformatics tools. Proteomics may thus provide an actual functional definition as to the effect of a membrane material on plasma proteins during hemodialysis. Here, we review the results of proteomic studies on the performance of hemodialysis membranes, as evaluated in terms of solute removal efficiency and blood–membrane interactions. The evidence collected indicates that the information provided by proteomic investigations yields improved molecular and functional knowledge and may lead to the development of more efficient membranes for the potential benefit of the patient. PMID:29296087

Examining hemodialyzer membrane performance using proteomic technologies.

PubMed

Bonomini, Mario; Pieroni, Luisa; Di Liberato, Lorenzo; Sirolli, Vittorio; Urbani, Andrea

2018-01-01

The success and the quality of hemodialysis therapy are mainly related to both clearance and biocompatibility properties of the artificial membrane packed in the hemodialyzer. Performance of a membrane is strongly influenced by its interaction with the plasma protein repertoire during the extracorporeal procedure. Recognition that a number of medium-high molecular weight solutes, including proteins and protein-bound molecules, are potentially toxic has prompted the development of more permeable membranes. Such membrane engineering, however, may cause loss of vital proteins, with membrane removal being nonspecific. In addition, plasma proteins can be adsorbed onto the membrane surface upon blood contact during dialysis. Adsorption can contribute to the removal of toxic compounds and governs the biocompatibility of a membrane, since surface-adsorbed proteins may trigger a variety of biologic blood pathways with pathophysiologic consequences. Over the last years, use of proteomic approaches has allowed polypeptide spectrum involved in the process of hemodialysis, a key issue previously hampered by lack of suitable technology, to be assessed in an unbiased manner and in its full complexity. Proteomics has been successfully applied to identify and quantify proteins in complex mixtures such as dialysis outflow fluid and fluid desorbed from dialysis membrane containing adsorbed proteins. The identified proteins can also be characterized by their involvement in metabolic and signaling pathways, molecular networks, and biologic processes through application of bioinformatics tools. Proteomics may thus provide an actual functional definition as to the effect of a membrane material on plasma proteins during hemodialysis. Here, we review the results of proteomic studies on the performance of hemodialysis membranes, as evaluated in terms of solute removal efficiency and blood-membrane interactions. The evidence collected indicates that the information provided by proteomic investigations yields improved molecular and functional knowledge and may lead to the development of more efficient membranes for the potential benefit of the patient.

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.

Proteomic interactions in the mouse vitreous-retina complex.

PubMed

Skeie, Jessica M; Mahajan, Vinit B

2013-01-01

Human vitreoretinal diseases are due to presumed abnormal mechanical interactions between the vitreous and retina, and translational models are limited. This study determined whether nonstructural proteins and potential retinal biomarkers were expressed by the normal mouse vitreous and retina. Vitreous and retina samples from mice were collected by evisceration and analyzed by liquid chromatography-tandem mass spectrometry. Identified proteins were further analyzed for differential expression and functional interactions using bioinformatic software. We identified 1,680 unique proteins in the retina and 675 unique proteins in the vitreous. Unbiased clustering identified protein pathways that distinguish retina from vitreous including oxidative phosphorylation and neurofilament cytoskeletal remodeling, whereas the vitreous expressed oxidative stress and innate immunology pathways. Some intracellular protein pathways were found in both retina and vitreous, such as glycolysis and gluconeogenesis and neuronal signaling, suggesting proteins might be shuttled between the retina and vitreous. We also identified human disease biomarkers represented in the mouse vitreous and retina, including carbonic anhydrase-2 and 3, crystallins, macrophage inhibitory factor, glutathione peroxidase, peroxiredoxins, S100 precursors, and von Willebrand factor. Our analysis suggests the vitreous expresses nonstructural proteins that functionally interact with the retina to manage oxidative stress, immune reactions, and intracellular proteins may be exchanged between the retina and vitreous. This novel proteomic dataset can be used for investigating human vitreoretinopathies in mouse models. Validation of vitreoretinal biomarkers for human ocular diseases will provide a critical tool for diagnostics and an avenue for therapeutics.

Effect of Processing Intensity on Immunologically Active Bovine Milk Serum Proteins.

PubMed

Brick, Tabea; Ege, Markus; Boeren, Sjef; Böck, Andreas; von Mutius, Erika; Vervoort, Jacques; Hettinga, Kasper

2017-08-31

Consumption of raw cow's milk instead of industrially processed milk has been reported to protect children from developing asthma, allergies, and respiratory infections. Several heat-sensitive milk serum proteins have been implied in this effect though unbiased assessment of milk proteins in general is missing. The aim of this study was to compare the native milk serum proteome between raw cow's milk and various industrially applied processing methods, i.e., homogenization, fat separation, pasteurization, ultra-heat treatment (UHT), treatment for extended shelf-life (ESL), and conventional boiling. Each processing method was applied to the same three pools of raw milk. Levels of detectable proteins were quantified by liquid chromatography/tandem mass spectrometry following filter aided sample preparation. In total, 364 milk serum proteins were identified. The 140 proteins detectable in 66% of all samples were entered in a hierarchical cluster analysis. The resulting proteomics pattern separated mainly as high (boiling, UHT, ESL) versus no/low heat treatment (raw, skimmed, pasteurized). Comparing these two groups revealed 23 individual proteins significantly reduced by heating, e.g., lactoferrin (log2-fold change = -0.37, p = 0.004), lactoperoxidase (log2-fold change = -0.33, p = 0.001), and lactadherin (log2-fold change = -0.22, p = 0.020). The abundance of these heat sensitive proteins found in higher quantity in native cow's milk compared to heat treated milk, renders them potential candidates for protection from asthma, allergies, and respiratory infections.

Automated systematic random sampling and Cavalieri stereology of histologic sections demonstrating acute tubular necrosis after cardiac arrest and cardiopulmonary resuscitation in the mouse.

PubMed

Wakasaki, Rumie; Eiwaz, Mahaba; McClellan, Nicholas; Matsushita, Katsuyuki; Golgotiu, Kirsti; Hutchens, Michael P

2018-06-14

A technical challenge in translational models of kidney injury is determination of the extent of cell death. Histologic sections are commonly analyzed by area morphometry or unbiased stereology, but stereology requires specialized equipment. Therefore, a challenge to rigorous quantification would be addressed by an unbiased stereology tool with reduced equipment dependence. We hypothesized that it would be feasible to build a novel software component which would facilitate unbiased stereologic quantification on scanned slides, and that unbiased stereology would demonstrate greater precision and decreased bias compared with 2D morphometry. We developed a macro for the widely used image analysis program, Image J, and performed cardiac arrest with cardiopulmonary resuscitation (CA/CPR, a model of acute cardiorenal syndrome) in mice. Fluorojade-B stained kidney sections were analyzed using three methods to quantify cell death: gold standard stereology using a controlled stage and commercially-available software, unbiased stereology using the novel ImageJ macro, and quantitative 2D morphometry also using the novel macro. There was strong agreement between both methods of unbiased stereology (bias -0.004±0.006 with 95% limits of agreement -0.015 to 0.007). 2D morphometry demonstrated poor agreement and significant bias compared to either method of unbiased stereology. Unbiased stereology is facilitated by a novel macro for ImageJ and results agree with those obtained using gold-standard methods. Automated 2D morphometry overestimated tubular epithelial cell death and correlated modestly with values obtained from unbiased stereology. These results support widespread use of unbiased stereology for analysis of histologic outcomes of injury models.

Focused Metabolite Profiling for Dissecting Cellular and Molecular Processes of Living Organisms in Space Environments

NASA Technical Reports Server (NTRS)

2008-01-01

Regulatory control in biological systems is exerted at all levels within the central dogma of biology. Metabolites are the end products of all cellular regulatory processes and reflect the ultimate outcome of potential changes suggested by genomics and proteomics caused by an environmental stimulus or genetic modification. Following on the heels of genomics, transcriptomics, and proteomics, metabolomics has become an inevitable part of complete-system biology because none of the lower "-omics" alone provide direct information about how changes in mRNA or protein are coupled to changes in biological function. The challenges are much greater than those encountered in genomics because of the greater number of metabolites and the greater diversity of their chemical structures and properties. To meet these challenges, much developmental work is needed, including (1) methodologies for unbiased extraction of metabolites and subsequent quantification, (2) algorithms for systematic identification of metabolites, (3) expertise and competency in handling a large amount of information (data set), and (4) integration of metabolomics with other "omics" and data mining (implication of the information). This article reviews the project accomplishments.

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.

Protein 3-Nitrotyrosine in Complex Biological Samples: Quantification by High-Pressure Liquid Chromatography/Electrochemical Detection and Emergence of Proteomic Approaches for Unbiased Identification of Modification Sites

PubMed Central

Nuriel, Tal; Deeb, Ruba S.; Hajjar, David P.; Gross, Steven S.

2008-01-01

Nitration of tyrosine residues by nitric oxide (NO)-derived species results in the accumulation of 3-nitrotyrosine in proteins, a hallmark of nitrosative stress in cells and tissues. Tyrosine nitration is recognized as one of the multiple signaling modalities used by NO-derived species for the regulation of protein structure and function in health and disease. Various methods have been described for the quantification of protein 3-nitrotyrosine residues, and several strategies have been presented toward the goal of proteome-wide identification of protein tyrosine modification sites. This chapter details a useful protocol for the quantification of 3-nitrotyrosine in cells and tissues using high-pressure liquid chromatography with electrochemical detection. Additionally, this chapter describes a novel biotin-tagging strategy for specific enrichment of 3-nitrotyrosine-containing peptides. Application of this strategy, in conjunction with high-throughput MS/MS-based peptide sequencing, is anticipated to fuel efforts in developing comprehensive inventories of nitrosative stress-induced protein-tyrosine modification sites in cells and tissues. PMID:18554526

Completed | Office of Cancer Clinical Proteomics Research

Cancer.gov

Prior to the current Clinical Proteomic Tumor Analysis Consortium (CPTAC), previously funded initiatives associated with clinical proteomics research included: Clinical Proteomic Tumor Analysis Consortium (CPTAC 2.0) Clinical Proteomic Technologies for Cancer Initiative (CPTC) Mouse Proteomic Technologies Initiative

The Krebs cycle and mitochondrial mass are early victims of endothelial dysfunction: proteomic approach.

PubMed

Addabbo, Francesco; Ratliff, Brian; Park, Hyeong-Cheon; Kuo, Mei-Chuan; Ungvari, Zoltan; Csiszar, Anna; Ciszar, Anna; Krasnikov, Boris; Krasnikof, Boris; Sodhi, Komal; Zhang, Fung; Nasjletti, Alberto; Goligorsky, Michael S

2009-01-01

Endothelial cell dysfunction is associated with bioavailable nitric oxide deficiency and an excessive generation of reactive oxygen species. We modeled this condition by chronically inhibiting nitric oxide generation with subpressor doses of N(G)-monomethyl-L-arginine (L-NMMA) in C57B6 and Tie-2/green fluorescent protein mouse strains. L-NMMA-treated mice exhibited a slight reduction in vasorelaxation ability, as well as detectable abnormalities in soluble adhesion molecules (soluble intercellular adhesion molecule-1 and vascular cellular adhesion molecule-1, and matrix metalloproteinase 9), which represent surrogate indicators of endothelial dysfunction. Proteomic analysis of the isolated microvasculature using 2-dimensional gel electrophoresis and matrix-assisted laser desorption/ionization time-of-flight mass spectroscopy revealed abnormal expression of a cluster of mitochondrial enzymes, which was confirmed using immunodetection. Aconitase-2 and enoyl-CoA-hydratase-1 expression levels were decreased in L-NMMA-treated animals; this phenotype was absent in nitric oxide synthase-1 and -3 knockout mice. Depletion of aconitase-2 and enoyl-CoA-hydratase-1 resulted in the inhibition of the Krebs cycle and enhanced pyruvate shunting toward the glycolytic pathway. To assess mitochondrial mass in vivo, co-localization of green fluorescent protein and MitoTracker fluorescence was detected by intravital microscopy. Quantitative analysis of fluorescence intensity showed that L-NMMA-treated animals exhibited lower fluorescence of MitoTracker in microvascular endothelia as a result of reduced mitochondrial mass. These findings provide conclusive and unbiased evidence that mitochondriopathy represents an early manifestation of endothelial dysfunction, shifting cell metabolism toward "metabolic hypoxia" through the selective depletion of both aconitase-2 and enoyl-CoA-hydratase-1. These findings may contribute to an early preclinical diagnosis of endothelial dysfunction.

Up-regulation of the G3PDH 'housekeeping' gene by estrogen.

PubMed

Galal, Nadia; El-Beialy, Waleed; Deyama, Yoshiaki; Yoshimura, Yoshitaka; Tei, Kanchu; Suzuki, Kuniaki; Totsuka, Yasunori

2010-01-01

Proteomic and genomic studies commonly involve the assessment of mRNA levels using reverse transcription-polymerase chain reaction (PCR) and real-time quantitative PCR. An internal standard RNA is fundamentally analyzed along with the investigated mRNA to document the specificity of the effect(s) on mRNA and to correct for inter-sample variations. In our studies implementing estrogen treatments on different cell lines, we initially used glyceraldehyde-3-phosphate dehydrogenase (G3PDH) as an internal standard. However, the results of PCR amplification demonstrated that 17β-estradiol enhanced the expression of the G3PDH gene, rendering it impossible to use G3PDH as an unbiased comparative control.

The effects of aging on the BTBR mouse model of autism spectrum disorder

PubMed Central

Jasien, Joan M.; Daimon, Caitlin M.; Wang, Rui; Shapiro, Bruce K.; Martin, Bronwen; Maudsley, Stuart

2014-01-01

Autism spectrum disorder (ASD) is a complex heterogeneous neurodevelopmental disorder characterized by alterations in social functioning, communicative abilities, and engagement in repetitive or restrictive behaviors. The process of aging in individuals with autism and related neurodevelopmental disorders is not well understood, despite the fact that the number of individuals with ASD aged 65 and older is projected to increase by over half a million individuals in the next 20 years. To elucidate the effects of aging in the context of a modified central nervous system, we investigated the effects of age on the BTBR T + tf/j mouse, a well characterized and widely used mouse model that displays an ASD-like phenotype. We found that a reduction in social behavior persists into old age in male BTBR T + tf/j mice. We employed quantitative proteomics to discover potential alterations in signaling systems that could regulate aging in the BTBR mice. Unbiased proteomic analysis of hippocampal and cortical tissue of BTBR mice compared to age-matched wild-type controls revealed a significant decrease in brain derived neurotrophic factor and significant increases in multiple synaptic markers (spinophilin, Synapsin I, PSD 95, NeuN), as well as distinct changes in functional pathways related to these proteins, including “Neural synaptic plasticity regulation” and “Neurotransmitter secretion regulation.” Taken together, these results contribute to our understanding of the effects of aging on an ASD-like mouse model in regards to both behavior and protein alterations, though additional studies are needed to fully understand the complex interplay underlying aging in mouse models displaying an ASD-like phenotype. PMID:25225482

A Unique Four-Hub Protein Cluster Associates to Glioblastoma Progression

PubMed Central

Simeone, Pasquale; Trerotola, Marco; Urbanella, Andrea; Lattanzio, Rossano; Ciavardelli, Domenico; Di Giuseppe, Fabrizio; Eleuterio, Enrica; Sulpizio, Marilisa; Eusebi, Vincenzo; Pession, Annalisa; Piantelli, Mauro; Alberti, Saverio

2014-01-01

Gliomas are the most frequent brain tumors. Among them, glioblastomas are malignant and largely resistant to available treatments. Histopathology is the gold standard for classification and grading of brain tumors. However, brain tumor heterogeneity is remarkable and histopathology procedures for glioma classification remain unsatisfactory for predicting disease course as well as response to treatment. Proteins that tightly associate with cancer differentiation and progression, can bear important prognostic information. Here, we describe the identification of protein clusters differentially expressed in high-grade versus low-grade gliomas. Tissue samples from 25 high-grade tumors, 10 low-grade tumors and 5 normal brain cortices were analyzed by 2D-PAGE and proteomic profiling by mass spectrometry. This led to identify 48 differentially expressed protein markers between tumors and normal samples. Protein clustering by multivariate analyses (PCA and PLS-DA) provided discrimination between pathological samples to an unprecedented extent, and revealed a unique network of deranged proteins. We discovered a novel glioblastoma control module centered on four major network hubs: Huntingtin, HNF4α, c-Myc and 14-3-3ζ. Immunohistochemistry, western blotting and unbiased proteome-wide meta-analysis revealed altered expression of this glioblastoma control module in human glioma samples as compared with normal controls. Moreover, the four-hub network was found to cross-talk with both p53 and EGFR pathways. In summary, the findings of this study indicate the existence of a unifying signaling module controlling glioblastoma pathogenesis and malignant progression, and suggest novel targets for development of diagnostic and therapeutic procedures. PMID:25050814

[Myonuclear domain and microtubule proteome during skeletal muscle maturation].

PubMed

Couturier, Nathalie; Gache, Vincent

2017-11-01

In the normal course of muscle fiber development, myonuclei actively position and adapt a precise localization in mature fibers, shaping MyoNuclear Domains (MNDs). Myonuclei positioning in fibers appears to be essential for muscle function as defects in MNDs settings are always associated with dysfunction (i.e., centronuclear myopathy, sarcopenia). Previous studies have shown that myonuclei positioning in fibers is reversible, suggesting that in pathologies presenting MNDs impairment, myonuclei could be re-addressed to the "correct" position in fibers and this could benefit to muscle function. Cytoskeleton networks, and particularly microtubules, have been implicated in early nuclei localization in myotubes. As the microtubule network is completely redesigned during muscle maturation, we hypothesized that "microtubules associated proteomes" would change between immature and mature fibers and contribute to a microtubule-dependent process resulting in MNDs setting and maintenance in mature fibers. We performed an in vitro biochemical approach to isolate microtubules partners in immature (myotubes) and mature myofibers. Using mass-spectrometry identification, we selected 244 candidates, differentially associated/expressed with microtubules during myofiber maturation and potentially controlling MNDs settings. We are currently conducting a siRNA screen approach on these candidates to decipher their respective implication in early and late phases of MNDs establishment, using an unbiased assay developed by our team allowing statistical analysis of MNDs regarding myonuclei content. This approach will lead to the identification of new pathways related to nuclear positioning and MNDs setting in normal condition and in myopathies associated to MNDs impairment such as CNMs. © 2017 médecine/sciences – Inserm.

Chronic intermittent ethanol exposure and withdrawal leads to adaptations in nucleus accumbens core postsynaptic density proteome and dendritic spines.

PubMed

Uys, Joachim D; McGuier, Natalie S; Gass, Justin T; Griffin, William C; Ball, Lauren E; Mulholland, Patrick J

2016-05-01

Alcohol use disorder is a chronic relapsing brain disease characterized by the loss of ability to control alcohol (ethanol) intake despite knowledge of detrimental health or personal consequences. Clinical and pre-clinical models provide strong evidence for chronic ethanol-associated alterations in glutamatergic signaling and impaired synaptic plasticity in the nucleus accumbens (NAc). However, the neural mechanisms that contribute to aberrant glutamatergic signaling in ethanol-dependent individuals in this critical brain structure remain unknown. Using an unbiased proteomic approach, we investigated the effects of chronic intermittent ethanol (CIE) exposure on neuroadaptations in postsynaptic density (PSD)-enriched proteins in the NAc of ethanol-dependent mice. Compared with controls, CIE exposure significantly changed expression levels of 50 proteins in the PSD-enriched fraction. Systems biology and functional annotation analyses demonstrated that the dysregulated proteins are expressed at tetrapartite synapses and critically regulate cellular morphology. To confirm this latter finding, the density and morphology of dendritic spines were examined in the NAc core of ethanol-dependent mice. We found that CIE exposure and withdrawal differentially altered dendrite diameter and dendritic spine density and morphology. Through the use of quantitative proteomics and functional annotation, these series of experiments demonstrate that ethanol dependence produces neuroadaptations in proteins that modify dendritic spine morphology. In addition, these studies identified novel PSD-related proteins that contribute to the neurobiological mechanisms of ethanol dependence that drive maladaptive structural plasticity of NAc neurons. © 2015 Society for the Study of Addiction.

Multi-species Identification of Polymorphic Peptide Variants via Propagation in Spectral Networks

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

Na, Seungjin; Payne, Samuel H.; Bandeira, Nuno

The spectral networks approach enables the detection of pairs of spectra from related peptides and thus allows for the propagation of annotations from identified peptides to unidentified spectra. Beyond allowing for unbiased discovery of unexpected post-translational modifications, spectral networks are also applicable to multi-species comparative proteomics or metaproteomics to identify numerous orthologous versions of a protein. We present algorithmic and statistical advances in spectral networks that have made it possible to rigorously assess the statistical significance of spectral pairs and accurately estimate the error rate of identifications via propagation. In the analysis of three related Cyanothece species, a model organismmore » for biohydrogen production, spectral networks identified peptides with highly divergent sequences with up to dozens of variants per peptide, including many novel peptides in species that lack a sequenced genome. Furthermore, spectral networks strongly suggested the presence of novel peptides even in genomically characterized species (i.e. missing from databases) in that a significant portion of unidentified multi-species networks included at least two polymorphic peptide variants.« less

Identification of MAPK Substrates Using Quantitative Phosphoproteomics.

PubMed

Zhang, Tong; Schneider, Jacqueline D; Zhu, Ning; Chen, Sixue

2017-01-01

Activation of mitogen-activated protein kinases (MAPKs) under diverse biotic and abiotic factors and identification of an array of downstream MAPK target proteins are hot topics in plant signal transduction. Through interactions with a plethora of substrate proteins, MAPK cascades regulate many physiological processes in the course of plant growth, development, and response to environmental factors. Identification and quantification of potential MAPK substrates are essential, but have been technically challenging. With the recent advancement in phosphoproteomics, here we describe a method that couples metal dioxide for phosphopeptide enrichment with tandem mass tags (TMT) mass spectrometry (MS) for large-scale MAPK substrate identification and quantification. We have applied this method to a transient expression system carrying a wild type (WT) and a constitutive active (CA) version of a MAPK. This combination of genetically engineered MAPKs and phosphoproteomics provides a high-throughput, unbiased analysis of MAPK-triggered phosphorylation changes on the proteome scale. Therefore, it is a robust method for identifying potential MAPK substrates and should be applicable in the study of other kinase cascades in plants as well as in other organisms.

Interaction of cellular proteins with BCL-xL targeted to cytoplasmic inclusion bodies in adenovirus infected cells.

PubMed

Subramanian, T; Vijayalingam, S; Kuppuswamy, M; Chinnadurai, G

2015-09-01

Adenovirus-mediated apoptosis was suppressed when cellular anti-apoptosis proteins (BCL-2 and BCL-xL) were substituted for the viral E1B-19K. For unbiased proteomic analysis of proteins targeted by BCL-xL in adenovirus-infected cells and to visualize the interactions with target proteins, BCL-xL was targeted to cytosolic inclusion bodies utilizing the orthoreovirus µNS protein sequences. The chimeric protein was localized in non-canonical cytosolic factory-like sites and promoted survival of virus-infected cells. The BCL-xL-associated proteins were isolated from the cytosolic inclusion bodies in adenovirus-infected cells and analyzed by LC-MS. These proteins included BAX, BAK, BID, BIK and BIM as well as mitochondrial proteins such as prohibitin 2, ATP synthase and DNA-PKcs. Our studies suggested that in addition to the interaction with various pro-apoptotic proteins, the association with certain mitochondrial proteins such as DNA-PKcs and prohibitins might augment the survival function of BCL-xL in virus infected cells. Copyright © 2015 Elsevier Inc. All rights reserved.

New molecular medicine: Diagnomics and pharmacogenomics

NASA Astrophysics Data System (ADS)

Kauffman, Michael G.

1999-04-01

Millennium Predictive Medicine (MPMx), a subsidiary of Millennium Pharmaceuticals, is focusing on the discovery and clinical validation of Diagnomic and Pharmacogenomic Tests which will replace many of the subjective elements of clinical decision making. Diagnomics are molecular diagnostic markers with prognostic and economic impact. While the majority of currently available diagnostics represent data points, Diagnomics allow patients and physicians to make scientifically based, individualized decisions about their disease and its therapy. Pharmacogenomics are diagnostics that specify the use or avoidance of specific therapeutics based on an individual genotype and/or disease subtype. MPMx uses the broad Millennium genomics, proteomics, and bioinformatics technologies in the analysis of human disease and drug response. These technologies permit global and unbiased approaches towards the elucidation of disease pathways and mechanisms at the molecular level. Germline or somatic mutations, RNA levels, or protein levels comprising these pathways and mechanisms are currently being evaluated as markers for disease predisposition, stage, aggressiveness, and likely drug response or drug toxicity. Diagnomic and Pharmacogenomic Tests are part of the new molecular medicine that is transforming clinical practice forma symptom/pathology-based art into a pre-symptom, mechanism- based science.

Discovery of a Chemical Probe Bisamide (CCT251236): An Orally Bioavailable Efficacious Pirin Ligand from a Heat Shock Transcription Factor 1 (HSF1) Phenotypic Screen

PubMed Central

2016-01-01

Phenotypic screens, which focus on measuring and quantifying discrete cellular changes rather than affinity for individual recombinant proteins, have recently attracted renewed interest as an efficient strategy for drug discovery. In this article, we describe the discovery of a new chemical probe, bisamide (CCT251236), identified using an unbiased phenotypic screen to detect inhibitors of the HSF1 stress pathway. The chemical probe is orally bioavailable and displays efficacy in a human ovarian carcinoma xenograft model. By developing cell-based SAR and using chemical proteomics, we identified pirin as a high affinity molecular target, which was confirmed by SPR and crystallography. PMID:28004573

Mechanisms of Severe Acute Respiratory Syndrome Coronavirus-Induced Acute Lung Injury

PubMed Central

Gralinski, Lisa E.; Bankhead, Armand; Jeng, Sophia; Menachery, Vineet D.; Proll, Sean; Belisle, Sarah E.; Matzke, Melissa; Webb-Robertson, Bobbie-Jo M.; Luna, Maria L.; Shukla, Anil K.; Ferris, Martin T.; Bolles, Meagan; Chang, Jean; Aicher, Lauri; Waters, Katrina M.; Smith, Richard D.; Metz, Thomas O.; Law, G. Lynn; Katze, Michael G.; McWeeney, Shannon; Baric, Ralph S.

2013-01-01

ABSTRACT Systems biology offers considerable promise in uncovering novel pathways by which viruses and other microbial pathogens interact with host signaling and expression networks to mediate disease severity. In this study, we have developed an unbiased modeling approach to identify new pathways and network connections mediating acute lung injury, using severe acute respiratory syndrome coronavirus (SARS-CoV) as a model pathogen. We utilized a time course of matched virologic, pathological, and transcriptomic data within a novel methodological framework that can detect pathway enrichment among key highly connected network genes. This unbiased approach produced a high-priority list of 4 genes in one pathway out of over 3,500 genes that were differentially expressed following SARS-CoV infection. With these data, we predicted that the urokinase and other wound repair pathways would regulate lethal versus sublethal disease following SARS-CoV infection in mice. We validated the importance of the urokinase pathway for SARS-CoV disease severity using genetically defined knockout mice, proteomic correlates of pathway activation, and pathological disease severity. The results of these studies demonstrate that a fine balance exists between host coagulation and fibrinolysin pathways regulating pathological disease outcomes, including diffuse alveolar damage and acute lung injury, following infection with highly pathogenic respiratory viruses, such as SARS-CoV. PMID:23919993

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

Notice of Pre-Application Webinar (RFA-CA-15-021, RFA-CA-15-022, RFA-CA-15-023) | Office of Cancer Clinical Proteomics Research

Cancer.gov

The National Cancer Institute will hold a public pre-application webinar on Friday, December 11 at 12:00 p.m. (EST) for the Funding Opportunity Announcements (FOAs) RFA-CA-15-021 entitled “Proteome Characterization Centers for Clinical Proteomic Tumor Analysis Consortium (U24), RFA-CA-15-022 entitled “Proteogenomic Translational Research Centers for Clinical Proteomic Tumor Analysis Consortium (U01)”, and RFA-CA-15-023 entitled “Proteogenomic Data Analysis Centers for Clinical Proteomic Tumor Analysis Consortium (U24)”.

Suboptimal T-cell receptor signaling compromises protein translation, ribosome biogenesis, and proliferation of mouse CD8 T cells.

PubMed

Tan, Thomas C J; Knight, John; Sbarrato, Thomas; Dudek, Kate; Willis, Anne E; Zamoyska, Rose

2017-07-25

Global transcriptomic and proteomic analyses of T cells have been rich sources of unbiased data for understanding T-cell activation. Lack of full concordance of these datasets has illustrated that important facets of T-cell activation are controlled at the level of translation. We undertook translatome analysis of CD8 T-cell activation, combining polysome profiling and microarray analysis. We revealed that altering T-cell receptor stimulation influenced recruitment of mRNAs to heavy polysomes and translation of subsets of genes. A major pathway that was compromised, when TCR signaling was suboptimal, was linked to ribosome biogenesis, a rate-limiting factor in both cell growth and proliferation. Defective TCR signaling affected transcription and processing of ribosomal RNA precursors, as well as the translation of specific ribosomal proteins and translation factors. Mechanistically, IL-2 production was compromised in weakly stimulated T cells, affecting the abundance of Myc protein, a known regulator of ribosome biogenesis. Consequently, weakly activated T cells showed impaired production of ribosomes and a failure to maintain proliferative capacity after stimulation. We demonstrate that primary T cells respond to various environmental cues by regulating ribosome biogenesis and mRNA translation at multiple levels to sustain proliferation and differentiation.

Four photon parametric amplification. [in unbiased Josephson junction

NASA Technical Reports Server (NTRS)

Parrish, P. T.; Feldman, M. J.; Ohta, H.; Chiao, R. Y.

1974-01-01

An analysis is presented describing four-photon parametric amplification in an unbiased Josephson junction. Central to the theory is the model of the Josephson effect as a nonlinear inductance. Linear, small signal analysis is applied to the two-fluid model of the Josephson junction. The gain, gain-bandwidth product, high frequency limit, and effective noise temperature are calculated for a cavity reflection amplifier. The analysis is extended to multiple (series-connected) junctions and subharmonic pumping.

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.

H1N1 viral proteome peptide microarray predicts individuals at risk for H1N1 infection and segregates infection versus Pandemrix® vaccination

PubMed Central

Ambati, Aditya; Valentini, Davide; Montomoli, Emanuele; Lapini, Guilia; Biuso, Fabrizio; Wenschuh, Holger; Magalhaes, Isabelle; Maeurer, Markus

2015-01-01

A high content peptide microarray containing the entire influenza A virus [A/California/08/2009(H1N1)] proteome and haemagglutinin proteins from 12 other influenza A subtypes, including the haemagglutinin from the [A/South Carolina/1/1918(H1N1)] strain, was used to gauge serum IgG epitope signatures before and after Pandemrix® vaccination or H1N1 infection in a Swedish cohort during the pandemic influenza season 2009. A very narrow pattern of pandemic flu-specific IgG epitope recognition was observed in the serum from individuals who later contracted H1N1 infection. Moreover, the pandemic influenza infection generated IgG reactivity to two adjacent epitopes of the neuraminidase protein. The differential serum IgG recognition was focused on haemagglutinin 1 (H1) and restricted to classical antigenic sites (Cb) in both the vaccinated controls and individuals with flu infections. We further identified a novel epitope VEPGDKITFEATGNL on the Ca antigenic site (251–265) of the pandemic flu haemagglutinin, which was exclusively recognized in serum from individuals with previous vaccinations and never in serum from individuals with H1N1 infection (confirmed by RNA PCR analysis from nasal swabs). This epitope was mapped to the receptor-binding domain of the influenza haemagglutinin and could serve as a correlate of immune protection in the context of pandemic flu. The study shows that unbiased epitope mapping using peptide microarray technology leads to the identification of biologically and clinically relevant target structures. Most significantly an H1N1 infection induced a different footprint of IgG epitope recognition patterns compared with the pandemic H1N1 vaccine. PMID:25639813

Identification of Protein Targets of 4-Hydroxynonenal Using Click Chemistry for Ex Vivo Biotinylation of Azido and Alkynyl Derivatives

PubMed Central

Vila, Andrew; Tallman, Keri A.; Jacobs, Aaron T.; Liebler, Daniel C.; Porter, Ned A.; Marnett, Lawrence J.

2009-01-01

Polyunsaturated fatty acids (PUFA) are primary targets of free radical damage during oxidative stress. Diffusible electrophilic α, β-unsaturated aldehydes, such as 4-hydroxynonenal (HNE), have been shown to modify proteins that mediate cell signaling (e.g. IKK and Keap1) and alter gene expression pathways responsible for inducing antioxidant genes, heat shock proteins, and the DNA damage response. To fully understand cellular responses to HNE, it is important to determine its protein targets in an unbiased fashion. This requires a strategy for detecting and isolating HNE-modified proteins regardless of the nature of the chemical linkage between HNE and its targets. Azido or alkynyl derivatives of HNE were synthesized and demonstrated to be equivalent to HNE in their ability to induce heme oxygenase induction and induce apoptosis in colon cancer (RKO) cells. Cells exposed to the tagged HNE derivatives were lysed and exposed to reagents to effect Staudinger ligation or copper-catalyzed Huisgen 1,3 dipolar cycloaddition reaction (click chemistry) to conjugate HNE-adducted proteins with biotin for subsequent affinity purification. Both strategies yielded efficient biotinylation of tagged HNE-protein conjugates but click chemistry was found to be superior for recovery of biotinylated proteins from streptavidin-coated beads. Biotinylated proteins were detected in lysates from RKO cell incubations with azido-HNE at concentrations as low as 1 μM. These proteins were affinity purified with streptavidin beads and proteomic analysis was performed by linear ion trap mass spectrometry. Proteomic analysis revealed a dose-dependent increase in labeled proteins with increased sequence coverage at higher concentrations. Several proteins involved in stress signaling (heat shock proteins 70 and 90, and the 78-kDa glucose-regulated protein) were selectively adducted by azido- and alkynyl-HNE. The use of azido and alkynyl derivatives in conjunction with click chemistry appears to be a valuable approach for the identification of the protein targets of HNE. PMID:18232660

Approaches for assessing and discovering protein interactions in cancer

PubMed Central

Mohammed, Hisham; Carroll, Jason S.

2013-01-01

Significant insight into the function of proteins, can be delineated by discovering and characterising interacting proteins. There are numerous methods for the discovery of unknown associated protein networks, with purification of the bait (the protein of interest) followed by Mass Spectrometry (MS) as a common theme. In recent years, advances have permitted the purification of endogenous proteins and methods for scaling down starting material. As such, approaches for rapid, unbiased identification of protein interactomes are becoming a standard tool in the researchers toolbox, rather than a technique that is only available to specialists. This review will highlight some of the recent technical advances in proteomic based discovery approaches, the pros and cons of various methods and some of the key findings in cancer related systems. PMID:24072816

Nature Neuroscience Review

PubMed Central

Maze, Ian; Shen, Li; Zhang, Bin; Garcia, Benjamin A.; Shao, Ningyi; Mitchell, Amanda; Sun, HaoSheng; Akbarian, Schahram; Allis, C. David; Nestler, Eric J.

2014-01-01

Over the past decade, rapid advances in epigenomics research have extensively characterized critical roles for chromatin regulatory events during normal periods of eukaryotic cell development and plasticity, as well as part of aberrant processes implicated in human disease. Application of such approaches to studies of the central nervous system (CNS), however, is more recent. Here, we provide a comprehensive overview of currently available tools to analyze neuroepigenomics data, as well as a discussion of pending challenges specific to the field of neuroscience. Integration of numerous unbiased genome-wide and proteomic approaches will be necessary to fully understand the neuroepigenome and the extraordinarily complex nature of the human brain. This will be critical to the development of future diagnostic and therapeutic strategies aimed at alleviating the vast array of heterogeneous and genetically distinct disorders of the CNS. PMID:25349914

CPTAC Releases Largest-Ever Breast Cancer Proteome Dataset from Previously Genome Characterized Tumors | Office of Cancer Clinical Proteomics Research

Cancer.gov

National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) scientists have released a dataset of proteins and  phosphopeptides identified through deep proteomic and phosphoproteomic analysis of breast tumor samples, previously genomically analyzed by The Cancer Genome Atlas (TCGA).

CPTAC Releases Largest-Ever Ovarian Cancer Proteome Dataset from Previously Genome Characterized Tumors | Office of Cancer Clinical Proteomics Research

Cancer.gov

National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) scientists have just released a comprehensive dataset of the proteomic analysis of high grade serous ovarian tumor samples, previously genomically analyzed by The Cancer Genome Atlas (TCGA).  This is one of the largest public datasets covering the proteome, phosphoproteome and glycoproteome with complementary deep genomic sequencing data on the same tumor.

Low Cost, Scalable Proteomics Data Analysis Using Amazon's Cloud Computing Services and Open Source Search Algorithms

PubMed Central

Halligan, Brian D.; Geiger, Joey F.; Vallejos, Andrew K.; Greene, Andrew S.; Twigger, Simon N.

2009-01-01

One of the major difficulties for many laboratories setting up proteomics programs has been obtaining and maintaining the computational infrastructure required for the analysis of the large flow of proteomics data. We describe a system that combines distributed cloud computing and open source software to allow laboratories to set up scalable virtual proteomics analysis clusters without the investment in computational hardware or software licensing fees. Additionally, the pricing structure of distributed computing providers, such as Amazon Web Services, allows laboratories or even individuals to have large-scale computational resources at their disposal at a very low cost per run. We provide detailed step by step instructions on how to implement the virtual proteomics analysis clusters as well as a list of current available preconfigured Amazon machine images containing the OMSSA and X!Tandem search algorithms and sequence databases on the Medical College of Wisconsin Proteomics Center website (http://proteomics.mcw.edu/vipdac). PMID:19358578

Low cost, scalable proteomics data analysis using Amazon's cloud computing services and open source search algorithms.

PubMed

Halligan, Brian D; Geiger, Joey F; Vallejos, Andrew K; Greene, Andrew S; Twigger, Simon N

2009-06-01

One of the major difficulties for many laboratories setting up proteomics programs has been obtaining and maintaining the computational infrastructure required for the analysis of the large flow of proteomics data. We describe a system that combines distributed cloud computing and open source software to allow laboratories to set up scalable virtual proteomics analysis clusters without the investment in computational hardware or software licensing fees. Additionally, the pricing structure of distributed computing providers, such as Amazon Web Services, allows laboratories or even individuals to have large-scale computational resources at their disposal at a very low cost per run. We provide detailed step-by-step instructions on how to implement the virtual proteomics analysis clusters as well as a list of current available preconfigured Amazon machine images containing the OMSSA and X!Tandem search algorithms and sequence databases on the Medical College of Wisconsin Proteomics Center Web site ( http://proteomics.mcw.edu/vipdac ).

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

New Funding Opportunity Announcements (FOAs): Reissuance of Clinical Proteomic Tumor Analysis Consortium (CPTAC) | Office of Cancer Clinical Proteomics Research

Cancer.gov

The National Cancer Institute is soliciting applications for the reissuance of its Clinical Proteomic Tumor Analysis Consortium (CPTAC) program.   CPTAC will support broad efforts focused on several cancer types to explore further the complexities of cancer proteomes and their connections to abnormalities in cancer genomes.

Maximum unbiased validation (MUV) data sets for virtual screening based on PubChem bioactivity data.

PubMed

Rohrer, Sebastian G; Baumann, Knut

2009-02-01

Refined nearest neighbor analysis was recently introduced for the analysis of virtual screening benchmark data sets. It constitutes a technique from the field of spatial statistics and provides a mathematical framework for the nonparametric analysis of mapped point patterns. Here, refined nearest neighbor analysis is used to design benchmark data sets for virtual screening based on PubChem bioactivity data. A workflow is devised that purges data sets of compounds active against pharmaceutically relevant targets from unselective hits. Topological optimization using experimental design strategies monitored by refined nearest neighbor analysis functions is applied to generate corresponding data sets of actives and decoys that are unbiased with regard to analogue bias and artificial enrichment. These data sets provide a tool for Maximum Unbiased Validation (MUV) of virtual screening methods. The data sets and a software package implementing the MUV design workflow are freely available at http://www.pharmchem.tu-bs.de/lehre/baumann/MUV.html.

Biomarkers for Cognitive Impairment in Parkinson Disease

PubMed Central

Shi, Min; Huber, Bertrand R.; Zhang, Jing

2010-01-01

Cognitive impairment, including dementia, is commonly seen in those afflicted with Parkinson disease (PD), particularly at advanced disease stages. Pathologically, PD with dementia (PD-D) is most often associated with the presence of cortical Lewy bodies, as is the closely related dementia with Lewy bodies (DLB). Both PD-D and DLB are also frequently complicated by the presence of neurofibrillary tangles and amyloid plaques, features most often attributed to Alzheimer disease. Biomarkers are urgently needed to differentiate among these disease processes and predict dementia in PD as well as monitor responses of patients to new therapies. A few clinical assessments, along with structural and functional neuroimaging, have been utilized in the last few years with some success in this area. Additionally, a number of other strategies have been employed to identify biochemical/molecular biomarkers associated with cognitive impairment and dementia in PD, e.g., targeted analysis of candidate proteins known to be important to PD pathogenesis and progression in cerebrospinal fluid or blood. Finally, interesting results are emerging from preliminary studies with unbiased and high throughput genomic, proteomic and metabolomic techniques. The current findings and perspectives of applying these strategies and techniques are reviewed in this article, together with potential areas of advancement. PMID:20522092

The quest to make fully functional human pancreatic beta cells from embryonic stem cells: climbing a mountain in the clouds.

PubMed

Johnson, James D

2016-10-01

The production of fully functional insulin-secreting cells to treat diabetes is a major goal of regenerative medicine. In this article, I review progress towards this goal over the last 15 years from the perspective of a beta cell biologist. I describe the current state-of-the-art, and speculate on the general approaches that will be required to identify and achieve our ultimate goal of producing functional beta cells. The need for deeper phenotyping of heterogeneous cultures of stem cell derived islet-like cells in parallel with a better understanding of the heterogeneity of the target cell type(s) is emphasised. This deep phenotyping should include high-throughput single-cell analysis, as well as comprehensive 'omics technologies to provide unbiased characterisation of cell products and human beta cells. There are justified calls for more detailed and well-powered studies of primary human pancreatic beta cell physiology, and I propose online databases of standardised human beta cell responses to physiological stimuli, including both functional and metabolomic/proteomic/transcriptomic profiles. With a concerted, community-wide effort, including both basic and applied scientists, beta cell replacement will become a clinical reality for patients with diabetes.

CPTAC | Office of Cancer Clinical Proteomics Research

Cancer.gov

The National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics.

Comparative bioinformatics analyses and profiling of lysosome-related organelle proteomes

NASA Astrophysics Data System (ADS)

Hu, Zhang-Zhi; Valencia, Julio C.; Huang, Hongzhan; Chi, An; Shabanowitz, Jeffrey; Hearing, Vincent J.; Appella, Ettore; Wu, Cathy

2007-01-01

Complete and accurate profiling of cellular organelle proteomes, while challenging, is important for the understanding of detailed cellular processes at the organelle level. Mass spectrometry technologies coupled with bioinformatics analysis provide an effective approach for protein identification and functional interpretation of organelle proteomes. In this study, we have compiled human organelle reference datasets from large-scale proteomic studies and protein databases for seven lysosome-related organelles (LROs), as well as the endoplasmic reticulum and mitochondria, for comparative organelle proteome analysis. Heterogeneous sources of human organelle proteins and rodent homologs are mapped to human UniProtKB protein entries based on ID and/or peptide mappings, followed by functional annotation and categorization using the iProXpress proteomic expression analysis system. Cataloging organelle proteomes allows close examination of both shared and unique proteins among various LROs and reveals their functional relevance. The proteomic comparisons show that LROs are a closely related family of organelles. The shared proteins indicate the dynamic and hybrid nature of LROs, while the unique transmembrane proteins may represent additional candidate marker proteins for LROs. This comparative analysis, therefore, provides a basis for hypothesis formulation and experimental validation of organelle proteins and their functional roles.

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.

Human body fluid proteome analysis

PubMed Central

Hu, Shen; Loo, Joseph A.; Wong, David T.

2010-01-01

The focus of this article is to review the recent advances in proteome analysis of human body fluids, including plasma/serum, urine, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, synovial fluid, nipple aspirate fluid, tear fluid, and amniotic fluid, as well as its applications to human disease biomarker discovery. We aim to summarize the proteomics technologies currently used for global identification and quantification of body fluid proteins, and elaborate the putative biomarkers discovered for a variety of human diseases through human body fluid proteome (HBFP) analysis. Some critical concerns and perspectives in this emerging field are also discussed. With the advances made in proteomics technologies, the impact of HBFP analysis in the search for clinically relevant disease biomarkers would be realized in the future. PMID:17083142

Human body fluid proteome analysis.

PubMed

Hu, Shen; Loo, Joseph A; Wong, David T

2006-12-01

The focus of this article is to review the recent advances in proteome analysis of human body fluids, including plasma/serum, urine, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, synovial fluid, nipple aspirate fluid, tear fluid, and amniotic fluid, as well as its applications to human disease biomarker discovery. We aim to summarize the proteomics technologies currently used for global identification and quantification of body fluid proteins, and elaborate the putative biomarkers discovered for a variety of human diseases through human body fluid proteome (HBFP) analysis. Some critical concerns and perspectives in this emerging field are also discussed. With the advances made in proteomics technologies, the impact of HBFP analysis in the search for clinically relevant disease biomarkers would be realized in the future.

Micro-proteomics with iterative data analysis: Proteome analysis in C. elegans at the single worm level.

PubMed

Bensaddek, Dalila; Narayan, Vikram; Nicolas, Armel; Murillo, Alejandro Brenes; Gartner, Anton; Kenyon, Cynthia J; Lamond, Angus I

2016-02-01

Proteomics studies typically analyze proteins at a population level, using extracts prepared from tens of thousands to millions of cells. The resulting measurements correspond to average values across the cell population and can mask considerable variation in protein expression and function between individual cells or organisms. Here, we report the development of micro-proteomics for the analysis of Caenorhabditis elegans, a eukaryote composed of 959 somatic cells and ∼1500 germ cells, measuring the worm proteome at a single organism level to a depth of ∼3000 proteins. This includes detection of proteins across a wide dynamic range of expression levels (>6 orders of magnitude), including many chromatin-associated factors involved in chromosome structure and gene regulation. We apply the micro-proteomics workflow to measure the global proteome response to heat-shock in individual nematodes. This shows variation between individual animals in the magnitude of proteome response following heat-shock, including variable induction of heat-shock proteins. The micro-proteomics pipeline thus facilitates the investigation of stochastic variation in protein expression between individuals within an isogenic population of C. elegans. All data described in this study are available online via the Encyclopedia of Proteome Dynamics (http://www.peptracker.com/epd), an open access, searchable database resource. © 2015 The Authors. PROTEOMICS Published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Extending unbiased stereology of brain ultrastructure to three-dimensional volumes

NASA Technical Reports Server (NTRS)

Fiala, J. C.; Harris, K. M.; Koslow, S. H. (Principal Investigator)

2001-01-01

OBJECTIVE: Analysis of brain ultrastructure is needed to reveal how neurons communicate with one another via synapses and how disease processes alter this communication. In the past, such analyses have usually been based on single or paired sections obtained by electron microscopy. Reconstruction from multiple serial sections provides a much needed, richer representation of the three-dimensional organization of the brain. This paper introduces a new reconstruction system and new methods for analyzing in three dimensions the location and ultrastructure of neuronal components, such as synapses, which are distributed non-randomly throughout the brain. DESIGN AND MEASUREMENTS: Volumes are reconstructed by defining transformations that align the entire area of adjacent sections. Whole-field alignment requires rotation, translation, skew, scaling, and second-order nonlinear deformations. Such transformations are implemented by a linear combination of bivariate polynomials. Computer software for generating transformations based on user input is described. Stereological techniques for assessing structural distributions in reconstructed volumes are the unbiased bricking, disector, unbiased ratio, and per-length counting techniques. A new general method, the fractional counter, is also described. This unbiased technique relies on the counting of fractions of objects contained in a test volume. A volume of brain tissue from stratum radiatum of hippocampal area CA1 is reconstructed and analyzed for synaptic density to demonstrate and compare the techniques. RESULTS AND CONCLUSIONS: Reconstruction makes practicable volume-oriented analysis of ultrastructure using such techniques as the unbiased bricking and fractional counter methods. These analysis methods are less sensitive to the section-to-section variations in counts and section thickness, factors that contribute to the inaccuracy of other stereological methods. In addition, volume reconstruction facilitates visualization and modeling of structures and analysis of three-dimensional relationships such as synaptic connectivity.

Dissecting tumor metabolic heterogeneity: Telomerase and large cell size metabolically define a sub-population of stem-like, mitochondrial-rich, cancer cells

PubMed Central

Lamb, Rebecca; Ozsvari, Bela; Bonuccelli, Gloria; Smith, Duncan L.; Pestell, Richard G.; Martinez-Outschoorn, Ubaldo E.; Clarke, Robert B.; Sotgia, Federica; Lisanti, Michael P.

2015-01-01

Tumor cell metabolic heterogeneity is thought to contribute to tumor recurrence, distant metastasis and chemo-resistance in cancer patients, driving poor clinical outcome. To better understand tumor metabolic heterogeneity, here we used the MCF7 breast cancer line as a model system to metabolically fractionate a cancer cell population. First, MCF7 cells were stably transfected with an hTERT-promoter construct driving GFP expression, as a surrogate marker of telomerase transcriptional activity. To enrich for immortal stem-like cancer cells, MCF7 cells expressing the highest levels of GFP (top 5%) were then isolated by FACS analysis. Notably, hTERT-GFP(+) MCF7 cells were significantly more efficient at forming mammospheres (i.e., stem cell activity) and showed increased mitochondrial mass and mitochondrial functional activity, all relative to hTERT-GFP(−) cells. Unbiased proteomics analysis of hTERT-GFP(+) MCF7 cells directly demonstrated the over-expression of 33 key mitochondrial proteins, 17 glycolytic enzymes, 34 ribosome-related proteins and 17 EMT markers, consistent with an anabolic cancer stem-like phenotype. Interestingly, MT-CO2 (cytochrome c oxidase subunit 2; Complex IV) expression was increased by >20-fold. As MT-CO2 is encoded by mt-DNA, this finding is indicative of increased mitochondrial biogenesis in hTERT-GFP(+) MCF7 cells. Importantly, most of these candidate biomarkers were transcriptionally over-expressed in human breast cancer epithelial cells in vivo. Similar results were obtained using cell size (forward/side scatter) to fractionate MCF7 cells. Larger stem-like cells also showed increased hTERT-GFP levels, as well as increased mitochondrial mass and function. Thus, this simple and rapid approach for the enrichment of immortal anabolic stem-like cancer cells will allow us and others to develop new prognostic biomarkers and novel anti-cancer therapies, by specifically and selectively targeting this metabolic sub-population of aggressive cancer cells. Based on our proteomics and functional analysis, FDA-approved inhibitors of protein synthesis and/or mitochondrial biogenesis, may represent novel treatment options for targeting these anabolic stem-like cancer cells. PMID:26323205

MASPECTRAS: a platform for management and analysis of proteomics LC-MS/MS data

PubMed Central

Hartler, Jürgen; Thallinger, Gerhard G; Stocker, Gernot; Sturn, Alexander; Burkard, Thomas R; Körner, Erik; Rader, Robert; Schmidt, Andreas; Mechtler, Karl; Trajanoski, Zlatko

2007-01-01

Background The advancements of proteomics technologies have led to a rapid increase in the number, size and rate at which datasets are generated. Managing and extracting valuable information from such datasets requires the use of data management platforms and computational approaches. Results We have developed the MAss SPECTRometry Analysis System (MASPECTRAS), a platform for management and analysis of proteomics LC-MS/MS data. MASPECTRAS is based on the Proteome Experimental Data Repository (PEDRo) relational database schema and follows the guidelines of the Proteomics Standards Initiative (PSI). Analysis modules include: 1) import and parsing of the results from the search engines SEQUEST, Mascot, Spectrum Mill, X! Tandem, and OMSSA; 2) peptide validation, 3) clustering of proteins based on Markov Clustering and multiple alignments; and 4) quantification using the Automated Statistical Analysis of Protein Abundance Ratios algorithm (ASAPRatio). The system provides customizable data retrieval and visualization tools, as well as export to PRoteomics IDEntifications public repository (PRIDE). MASPECTRAS is freely available at Conclusion Given the unique features and the flexibility due to the use of standard software technology, our platform represents significant advance and could be of great interest to the proteomics community. PMID:17567892

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...

Thioredoxin Inhibitors Attenuate Platelet Function and Thrombus Formation

PubMed Central

Metcalfe, Clive; Ramasubramoni, Anjana; Pula, Giordano; Harper, Matthew T.; Mundell, Stuart J.; Coxon, Carmen H.

2016-01-01

Thioredoxin (Trx) is an oxidoreductase with important physiological function. Imbalances in the NADPH/thioredoxin reductase/thioredoxin system are associated with a number of pathologies, particularly cancer, and a number of clinical trials for thioredoxin and thioredoxin reductase inhibitors have been carried out or are underway. Due to the emerging role and importance of oxidoreductases for haemostasis and the current interest in developing inhibitors for clinical use, we thought it pertinent to assess whether inhibition of the NADPH/thioredoxin reductase/thioredoxin system affects platelet function and thrombosis. We used small molecule inhibitors of Trx (PMX 464 and PX-12) to determine whether Trx activity influences platelet function, as well as an unbiased proteomics approach to identify potential Trx substrates on the surface of platelets that might contribute to platelet reactivity and function. Using LC-MS/MS we found that PMX 464 and PX-12 affected the oxidation state of thiols in a number of cell surface proteins. Key surface receptors for platelet adhesion and activation were affected, including the collagen receptor GPVI and the von Willebrand factor receptor, GPIb. To experimentally validate these findings we assessed platelet function in the presence of PMX 464, PX-12, and rutin (a selective inhibitor of the related protein disulphide isomerase). In agreement with the proteomics data, small molecule inhibitors of thioredoxin selectively inhibited GPVI-mediated platelet activation, and attenuated ristocetin-induced GPIb-vWF-mediated platelet agglutination, thus validating the findings of the proteomics study. These data reveal a novel role for thioredoxin in regulating platelet reactivity via proteins required for early platelet responses at sites of vessel injury (GPVI and GPIb). This work also highlights a potential opportunity for repurposing of PMX 464 and PX-12 as antiplatelet agents. PMID:27716777

Thioredoxin Inhibitors Attenuate Platelet Function and Thrombus Formation.

PubMed

Metcalfe, Clive; Ramasubramoni, Anjana; Pula, Giordano; Harper, Matthew T; Mundell, Stuart J; Coxon, Carmen H

2016-01-01

Thioredoxin (Trx) is an oxidoreductase with important physiological function. Imbalances in the NADPH/thioredoxin reductase/thioredoxin system are associated with a number of pathologies, particularly cancer, and a number of clinical trials for thioredoxin and thioredoxin reductase inhibitors have been carried out or are underway. Due to the emerging role and importance of oxidoreductases for haemostasis and the current interest in developing inhibitors for clinical use, we thought it pertinent to assess whether inhibition of the NADPH/thioredoxin reductase/thioredoxin system affects platelet function and thrombosis. We used small molecule inhibitors of Trx (PMX 464 and PX-12) to determine whether Trx activity influences platelet function, as well as an unbiased proteomics approach to identify potential Trx substrates on the surface of platelets that might contribute to platelet reactivity and function. Using LC-MS/MS we found that PMX 464 and PX-12 affected the oxidation state of thiols in a number of cell surface proteins. Key surface receptors for platelet adhesion and activation were affected, including the collagen receptor GPVI and the von Willebrand factor receptor, GPIb. To experimentally validate these findings we assessed platelet function in the presence of PMX 464, PX-12, and rutin (a selective inhibitor of the related protein disulphide isomerase). In agreement with the proteomics data, small molecule inhibitors of thioredoxin selectively inhibited GPVI-mediated platelet activation, and attenuated ristocetin-induced GPIb-vWF-mediated platelet agglutination, thus validating the findings of the proteomics study. These data reveal a novel role for thioredoxin in regulating platelet reactivity via proteins required for early platelet responses at sites of vessel injury (GPVI and GPIb). This work also highlights a potential opportunity for repurposing of PMX 464 and PX-12 as antiplatelet agents.

Deep Proteome Profiling Reveals Common Prevalence of MZB1-Positive Plasma B Cells in Human Lung and Skin Fibrosis.

PubMed

Schiller, Herbert B; Mayr, Christoph H; Leuschner, Gabriela; Strunz, Maximilian; Staab-Weijnitz, Claudia; Preisendörfer, Stefan; Eckes, Beate; Moinzadeh, Pia; Krieg, Thomas; Schwartz, David A; Hatz, Rudolf A; Behr, Jürgen; Mann, Matthias; Eickelberg, Oliver

2017-11-15

Analyzing the molecular heterogeneity of different forms of organ fibrosis may reveal common and specific factors and thus identify potential future therapeutic targets. We sought to use proteome-wide profiling of human tissue fibrosis to (1) identify common and specific signatures across end-stage interstitial lung disease (ILD) cases, (2) characterize ILD subgroups in an unbiased fashion, and (3) identify common and specific features of lung and skin fibrosis. We collected samples of ILD tissue (n = 45) and healthy donor control samples (n = 10), as well as fibrotic skin lesions from localized scleroderma and uninvolved skin (n = 6). Samples were profiled by quantitative label-free mass spectrometry, Western blotting, or confocal imaging. We determined the abundance of more than 7,900 proteins and stratified these proteins according to their detergent solubility profiles. Common protein regulations across all ILD cases, as well as distinct ILD subsets, were observed. Proteomic comparison of lung and skin fibrosis identified a common upregulation of marginal zone B- and B1-cell-specific protein (MZB1), the expression of which identified MZB1 + /CD38 + /CD138 + /CD27 + /CD45 - /CD20 - plasma B cells in fibrotic lung and skin tissue. MZB1 levels correlated positively with tissue IgG and negatively with diffusing capacity of the lung for carbon monoxide. Despite the presumably high molecular and cellular heterogeneity of ILD, common protein regulations are observed, even across organ boundaries. The surprisingly high prevalence of MZB1-positive plasma B cells in tissue fibrosis warrants future investigations regarding the causative role of antibody-mediated autoimmunity in idiopathic cases of organ fibrosis, such as idiopathic pulmonary fibrosis.

Early-branching Gut Fungi Possess A Large, And Comprehensive Array Of Biomass-Degrading Enzymes

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

Solomon, Kevin V.; Haitjema, Charles; Henske, John K.

The fungal kingdom is the source of almost all industrial enzymes in use for lignocellulose bioprocessing. Its more primitive members, however, remain relatively unexploited. We developed a systems-level approach that integrates RNA-Seq, proteomics, phenotype and biochemical studies of relatively unexplored early-branching free-living fungi. Anaerobic gut fungi isolated from herbivores produce a large array of biomass-degrading enzymes that synergistically degrade crude, unpretreated plant biomass, and are competitive with optimized commercial preparations from Aspergillus and Trichoderma. Compared to these model platforms, gut fungal enzymes are unbiased in substrate preference due to a wealth of xylan-degrading enzymes. These enzymes are universally catabolite repressed,more » and are further regulated by a rich landscape of noncoding regulatory RNAs. Furthermore, we identified several promising sequence divergent enzyme candidates for lignocellulosic bioprocessing.« less

CPTAC Releases Cancer Proteome Confirmatory Colon Study Data | Office of Cancer Clinical Proteomics Research

Cancer.gov

The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) announces the release of the cancer proteome confirmatory colon study data. The goal of the study is to analyze the proteomes of approximately 100 confirmatory colon tumor patients, which includes tumor and adjacent normal samples, with liquid chromatography-tandem mass spectrometry (LC-MS/MS) global proteomic and phosphoproteomic profiling.

CPTAC Proteomics Data on UCSC Genome Browser | Office of Cancer Clinical Proteomics Research

Cancer.gov

The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium scientists are working together with the University of California, Santa Cruz (UCSC) Genomics Institute to provide public access to cancer proteomics data via the UCSC Genome Browser. This effort extends accessibility of the CPTAC data to more researchers and provides an additional level of analysis to assist the cancer biology community.

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.

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

Cancer.gov

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

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

PubMed Central

Tezel, Gülgün

2013-01-01

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

Phosphoproteomic network analysis in the sea urchin Strongylocentrotus purpuratus reveals new candidates in egg activation.

PubMed

Guo, Hongbo; Garcia-Vedrenne, Ana Elisa; Isserlin, Ruth; Lugowski, Andrew; Morada, Anthony; Sun, Alex; Miao, Yishen; Kuzmanov, Uros; Wan, Cuihong; Ma, Hongyue; Foltz, Kathy; Emili, Andrew

2015-12-01

Fertilization triggers a dynamic symphony of molecular transformations induced by a rapid rise in intracellular calcium. Most prominent are surface alterations, metabolic activation, cytoskeletal reorganization, and cell-cycle reentry. While the activation process appears to be broadly evolutionarily conserved, and protein phosphorylation is known to play a key role, the signaling networks mediating the response to fertilization are not well described. To address this gap, we performed a time course phosphoproteomic analysis of egg activation in the sea urchin Strongylocentrotus purpuratus, a system that offers biochemical tractability coupled with exquisite synchronicity. By coupling large-scale phosphopeptide enrichment with unbiased quantitative MS, we identified striking changes in global phosphoprotein patterns at 2- and 5-min postfertilization as compared to unfertilized eggs. Overall, we mapped 8796 distinct phosphosite modifications on 2833 phosphoproteins, of which 15% were differentially regulated in early egg activation. Activated kinases were identified by phosphosite mapping, while enrichment analyses revealed conserved signaling cascades not previously associated with egg activation. This work represents the most comprehensive study of signaling associated with egg activation to date, suggesting novel mechanisms that can be experimentally tested and providing a valuable resource for the broader research community. All MS data have been deposited in the ProteomeXchange with identifier PXD002239 (http://proteomecentral.proteomexchange.org/dataset/PXD002239). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Top-down proteomics for the analysis of proteolytic events - Methods, applications and perspectives.

PubMed

Tholey, Andreas; Becker, Alexander

2017-11-01

Mass spectrometry based proteomics is an indispensable tool for almost all research areas relevant for the understanding of proteolytic processing, ranging from the identification of substrates, products and cleavage sites up to the analysis of structural features influencing protease activity. The majority of methods for these studies are based on bottom-up proteomics performing analysis at peptide level. As this approach is characterized by a number of pitfalls, e.g. loss of molecular information, there is an ongoing effort to establish top-down proteomics, performing separation and MS analysis both at intact protein level. We briefly introduce major approaches of bottom-up proteomics used in the field of protease research and highlight the shortcomings of these methods. We then discuss the present state-of-the-art of top-down proteomics. Together with the discussion of known challenges we show the potential of this approach and present a number of successful applications of top-down proteomics in protease research. This article is part of a Special Issue entitled: Proteolysis as a Regulatory Event in Pathophysiology edited by Stefan Rose-John. Copyright © 2017 Elsevier B.V. All rights reserved.

Shotgun proteomics of plant plasma membrane and microdomain proteins using nano-LC-MS/MS.

PubMed

Takahashi, Daisuke; Li, Bin; Nakayama, Takato; Kawamura, Yukio; Uemura, Matsuo

2014-01-01

Shotgun proteomics allows the comprehensive analysis of proteins extracted from plant cells, subcellular organelles, and membranes. Previously, two-dimensional gel electrophoresis-based proteomics was used for mass spectrometric analysis of plasma membrane proteins. In order to get comprehensive proteome profiles of the plasma membrane including highly hydrophobic proteins with a number of transmembrane domains, a mass spectrometry-based shotgun proteomics method using nano-LC-MS/MS for proteins from the plasma membrane proteins and plasma membrane microdomain fraction is described. The results obtained are easily applicable to label-free protein semiquantification.

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.

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

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.

The Escherichia coli Proteome: Past, Present, and Future Prospects†

PubMed Central

Han, Mee-Jung; Lee, Sang Yup

2006-01-01

Proteomics has emerged as an indispensable methodology for large-scale protein analysis in functional genomics. The Escherichia coli proteome has been extensively studied and is well defined in terms of biochemical, biological, and biotechnological data. Even before the entire E. coli proteome was fully elucidated, the largest available data set had been integrated to decipher regulatory circuits and metabolic pathways, providing valuable insights into global cellular physiology and the development of metabolic and cellular engineering strategies. With the recent advent of advanced proteomic technologies, the E. coli proteome has been used for the validation of new technologies and methodologies such as sample prefractionation, protein enrichment, two-dimensional gel electrophoresis, protein detection, mass spectrometry (MS), combinatorial assays with n-dimensional chromatographies and MS, and image analysis software. These important technologies will not only provide a great amount of additional information on the E. coli proteome but also synergistically contribute to other proteomic studies. Here, we review the past development and current status of E. coli proteome research in terms of its biological, biotechnological, and methodological significance and suggest future prospects. PMID:16760308

Derivative component analysis for mass spectral serum proteomic profiles.

PubMed

Han, Henry

2014-01-01

As a promising way to transform medicine, mass spectrometry based proteomics technologies have seen a great progress in identifying disease biomarkers for clinical diagnosis and prognosis. However, there is a lack of effective feature selection methods that are able to capture essential data behaviors to achieve clinical level disease diagnosis. Moreover, it faces a challenge from data reproducibility, which means that no two independent studies have been found to produce same proteomic patterns. Such reproducibility issue causes the identified biomarker patterns to lose repeatability and prevents it from real clinical usage. In this work, we propose a novel machine-learning algorithm: derivative component analysis (DCA) for high-dimensional mass spectral proteomic profiles. As an implicit feature selection algorithm, derivative component analysis examines input proteomics data in a multi-resolution approach by seeking its derivatives to capture latent data characteristics and conduct de-noising. We further demonstrate DCA's advantages in disease diagnosis by viewing input proteomics data as a profile biomarker via integrating it with support vector machines to tackle the reproducibility issue, besides comparing it with state-of-the-art peers. Our results show that high-dimensional proteomics data are actually linearly separable under proposed derivative component analysis (DCA). As a novel multi-resolution feature selection algorithm, DCA not only overcomes the weakness of the traditional methods in subtle data behavior discovery, but also suggests an effective resolution to overcoming proteomics data's reproducibility problem and provides new techniques and insights in translational bioinformatics and machine learning. The DCA-based profile biomarker diagnosis makes clinical level diagnostic performances reproducible across different proteomic data, which is more robust and systematic than the existing biomarker discovery based diagnosis. Our findings demonstrate the feasibility and power of the proposed DCA-based profile biomarker diagnosis in achieving high sensitivity and conquering the data reproducibility issue in serum proteomics. Furthermore, our proposed derivative component analysis suggests the subtle data characteristics gleaning and de-noising are essential in separating true signals from red herrings for high-dimensional proteomic profiles, which can be more important than the conventional feature selection or dimension reduction. In particular, our profile biomarker diagnosis can be generalized to other omics data for derivative component analysis (DCA)'s nature of generic data analysis.

Tumor Cold Ischemia | Office of Cancer Clinical Proteomics Research

Cancer.gov

In a recently published manuscript in the journal of Molecular and Cellular Proteomics, researchers from the National Cancer Institutes (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) investigated the effect of cold ischemia on the proteome of fresh frozen tumors.

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.

Building ProteomeTools based on a complete synthetic human proteome

PubMed Central

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

2018-01-01

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

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

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.

Characterization of individual mouse cerebrospinal fluid proteomes

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

Smith, Jeffrey S.; Angel, Thomas E.; Chavkin, Charles

2014-03-20

Analysis of cerebrospinal fluid (CSF) offers key insight into the status of the central nervous system. Characterization of murine CSF proteomes can provide a valuable resource for studying central nervous system injury and disease in animal models. However, the small volume of CSF in mice has thus far limited individual mouse proteome characterization. Through non-terminal CSF extractions in C57Bl/6 mice and high-resolution liquid chromatography-mass spectrometry analysis of individual murine samples, we report the most comprehensive proteome characterization of individual murine CSF to date. Utilizing stringent protein inclusion criteria that required the identification of at least two unique peptides (1% falsemore » discovery rate at the peptide level) we identified a total of 566 unique proteins, including 128 proteins from three individual CSF samples that have been previously identified in brain tissue. Our methods and analysis provide a mechanism for individual murine CSF proteome analysis.« less

The dependability of medical students' performance ratings as documented on in-training evaluations.

PubMed

van Barneveld, Christina

2005-03-01

To demonstrate an approach to obtain an unbiased estimate of the dependability of students' performance ratings during training, when the data-collection design includes nesting of student in rater, unbalanced nest sizes, and dependent observations. In 2003, two variance components analyses of in-training evaluation (ITE) report data were conducted using urGENOVA software. In the first analysis, the dependability for the nested and unbalanced data-collection design was calculated. In the second analysis, an approach using multiple generalizability studies was used to obtain an unbiased estimate of the student variance component, resulting in an unbiased estimate of dependability. Results suggested that there is bias in estimates of the dependability of students' performance on ITEs that are attributable to the data-collection design. When the bias was corrected, the results indicated that the dependability of ratings of student performance was almost zero. The combination of the multiple generalizability studies method and the use of specialized software provides an unbiased estimate of the dependability of ratings of student performance on ITE scores for data-collection designs that include nesting of student in rater, unbalanced nest sizes, and dependent observations.

[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.

Ataxin-2 (Atxn2)-Knock-Out Mice Show Branched Chain Amino Acids and Fatty Acids Pathway Alterations.

PubMed

Meierhofer, David; Halbach, Melanie; Şen, Nesli Ece; Gispert, Suzana; Auburger, Georg

2016-05-01

Human Ataxin-2 (ATXN2) gene locus variants have been associated with obesity, diabetes mellitus type 1,and hypertension in genome-wide association studies, whereas mouse studies showed the knock-out of Atxn2 to lead to obesity, insulin resistance, and dyslipidemia. Intriguingly, the deficiency of ATXN2 protein orthologs in yeast and flies rescues the neurodegeneration process triggered by TDP-43 and Ataxin-1 toxicity. To understand the molecular effects of ATXN2 deficiency by unbiased approaches, we quantified the global proteome and metabolome of Atxn2-knock-out mice with label-free mass spectrometry. In liver tissue, significant downregulations of the proteins ACADS, ALDH6A1, ALDH7A1, IVD, MCCC2, PCCA, OTC, together with bioinformatic enrichment of downregulated pathways for branched chain and other amino acid metabolism, fatty acids, and citric acid cycle were observed. Statistical trends in the cerebellar proteome and in the metabolomic profiles supported these findings. They are in good agreement with recent claims that PBP1, the yeast ortholog of ATXN2, sequestrates the nutrient sensor TORC1 in periods of cell stress. Overall, ATXN2 appears to modulate nutrition and metabolism, and its activity changes are determinants of growth excess or cell atrophy. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Comprehensive Analysis of Temporal Alterations in Cellular Proteome of Bacillus subtilis under Curcumin Treatment

PubMed Central

Reddy, Panga Jaipal; Sinha, Sneha; Ray, Sandipan; Sathe, Gajanan J.; Chatterjee, Aditi; Prasad, T. S. Keshava; Dhali, Snigdha; Srikanth, Rapole; Panda, Dulal; Srivastava, Sanjeeva

2015-01-01

Curcumin is a natural dietary compound with antimicrobial activity against various gram positive and negative bacteria. This study aims to investigate the proteome level alterations in Bacillus subtilis due to curcumin treatment and identification of its molecular/cellular targets to understand the mechanism of action. We have performed a comprehensive proteomic analysis of B. subtilis AH75 strain at different time intervals of curcumin treatment (20, 60 and 120 min after the drug exposure, three replicates) to compare the protein expression profiles using two complementary quantitative proteomic techniques, 2D-DIGE and iTRAQ. To the best of our knowledge, this is the first comprehensive longitudinal investigation describing the effect of curcumin treatment on B. subtilis proteome. The proteomics analysis revealed several interesting targets such UDP-N-acetylglucosamine 1-carboxyvinyltransferase 1, putative septation protein SpoVG and ATP-dependent Clp protease proteolytic subunit. Further, in silico pathway analysis using DAVID and KOBAS has revealed modulation of pathways related to the fatty acid metabolism and cell wall synthesis, which are crucial for cell viability. Our findings revealed that curcumin treatment lead to inhibition of the cell wall and fatty acid synthesis in addition to differential expression of many crucial proteins involved in modulation of bacterial metabolism. Findings obtained from proteomics analysis were further validated using 5-cyano-2,3-ditolyl tetrazolium chloride (CTC) assay for respiratory activity, resazurin assay for metabolic activity and membrane integrity assay by potassium and inorganic phosphate leakage measurement. The gene expression analysis of selected cell wall biosynthesis enzymes has strengthened the proteomics findings and indicated the major effect of curcumin on cell division. PMID:25874956

Comprehensive analysis of temporal alterations in cellular proteome of Bacillus subtilis under curcumin treatment.

PubMed

Reddy, Panga Jaipal; Sinha, Sneha; Ray, Sandipan; Sathe, Gajanan J; Chatterjee, Aditi; Prasad, T S Keshava; Dhali, Snigdha; Srikanth, Rapole; Panda, Dulal; Srivastava, Sanjeeva

2015-01-01

Curcumin is a natural dietary compound with antimicrobial activity against various gram positive and negative bacteria. This study aims to investigate the proteome level alterations in Bacillus subtilis due to curcumin treatment and identification of its molecular/cellular targets to understand the mechanism of action. We have performed a comprehensive proteomic analysis of B. subtilis AH75 strain at different time intervals of curcumin treatment (20, 60 and 120 min after the drug exposure, three replicates) to compare the protein expression profiles using two complementary quantitative proteomic techniques, 2D-DIGE and iTRAQ. To the best of our knowledge, this is the first comprehensive longitudinal investigation describing the effect of curcumin treatment on B. subtilis proteome. The proteomics analysis revealed several interesting targets such UDP-N-acetylglucosamine 1-carboxyvinyltransferase 1, putative septation protein SpoVG and ATP-dependent Clp protease proteolytic subunit. Further, in silico pathway analysis using DAVID and KOBAS has revealed modulation of pathways related to the fatty acid metabolism and cell wall synthesis, which are crucial for cell viability. Our findings revealed that curcumin treatment lead to inhibition of the cell wall and fatty acid synthesis in addition to differential expression of many crucial proteins involved in modulation of bacterial metabolism. Findings obtained from proteomics analysis were further validated using 5-cyano-2,3-ditolyl tetrazolium chloride (CTC) assay for respiratory activity, resazurin assay for metabolic activity and membrane integrity assay by potassium and inorganic phosphate leakage measurement. The gene expression analysis of selected cell wall biosynthesis enzymes has strengthened the proteomics findings and indicated the major effect of curcumin on cell division.

Analyzing large-scale proteomics projects with latent semantic indexing.

PubMed

Klie, Sebastian; Martens, Lennart; Vizcaíno, Juan Antonio; Côté, Richard; Jones, Phil; Apweiler, Rolf; Hinneburg, Alexander; Hermjakob, Henning

2008-01-01

Since the advent of public data repositories for proteomics data, readily accessible results from high-throughput experiments have been accumulating steadily. Several large-scale projects in particular have contributed substantially to the amount of identifications available to the community. Despite the considerable body of information amassed, very few successful analyses have been performed and published on this data, leveling off the ultimate value of these projects far below their potential. A prominent reason published proteomics data is seldom reanalyzed lies in the heterogeneous nature of the original sample collection and the subsequent data recording and processing. To illustrate that at least part of this heterogeneity can be compensated for, we here apply a latent semantic analysis to the data contributed by the Human Proteome Organization's Plasma Proteome Project (HUPO PPP). Interestingly, despite the broad spectrum of instruments and methodologies applied in the HUPO PPP, our analysis reveals several obvious patterns that can be used to formulate concrete recommendations for optimizing proteomics project planning as well as the choice of technologies used in future experiments. It is clear from these results that the analysis of large bodies of publicly available proteomics data by noise-tolerant algorithms such as the latent semantic analysis holds great promise and is currently underexploited.

Single cell-type comparative metabolomics of epidermal bladder cells from the halophyte Mesembryanthemum crystallinum

PubMed Central

Barkla, Bronwyn J.; Vera-Estrella, Rosario

2015-01-01

One of the remarkable adaptive features of the halophyte Mesembryanthemum crystallinum are the specialized modified trichomes called epidermal bladder cells (EBC) which cover the leaves, stems, and peduncle of the plant. They are present from an early developmental stage but upon salt stress rapidly expand due to the accumulation of water and sodium. This particular plant feature makes it an attractive system for single cell type studies, with recent proteomics and transcriptomics studies of the EBC establishing that these cells are metabolically active and have roles other than sodium sequestration. To continue our investigation into the function of these unusual cells we carried out a comprehensive global analysis of the metabolites present in the EBC extract by gas chromatography Time-of-Flight mass spectrometry (GC-TOF) and identified 194 known and 722 total molecular features. Statistical analysis of the metabolic changes between control and salt-treated samples identified 352 significantly differing metabolites (268 after correction for FDR). Principal components analysis provided an unbiased evaluation of the data variance structure. Biochemical pathway enrichment analysis suggested significant perturbations in 13 biochemical pathways as defined in KEGG. More than 50% of the metabolites that show significant changes in the EBC, can be classified as compatible solutes and include sugars, sugar alcohols, protein and non-protein amino acids, and organic acids, highlighting the need to maintain osmotic homeostasis to balance the accumulation of Na+ and Cl− ions. Overall, the comparison of metabolic changes in salt treated relative to control samples suggests large alterations in M. crystallinum epidermal bladder cells. PMID:26113856

Single cell-type comparative metabolomics of epidermal bladder cells from the halophyte Mesembryanthemum crystallinum.

PubMed

Barkla, Bronwyn J; Vera-Estrella, Rosario

2015-01-01

One of the remarkable adaptive features of the halophyte Mesembryanthemum crystallinum are the specialized modified trichomes called epidermal bladder cells (EBC) which cover the leaves, stems, and peduncle of the plant. They are present from an early developmental stage but upon salt stress rapidly expand due to the accumulation of water and sodium. This particular plant feature makes it an attractive system for single cell type studies, with recent proteomics and transcriptomics studies of the EBC establishing that these cells are metabolically active and have roles other than sodium sequestration. To continue our investigation into the function of these unusual cells we carried out a comprehensive global analysis of the metabolites present in the EBC extract by gas chromatography Time-of-Flight mass spectrometry (GC-TOF) and identified 194 known and 722 total molecular features. Statistical analysis of the metabolic changes between control and salt-treated samples identified 352 significantly differing metabolites (268 after correction for FDR). Principal components analysis provided an unbiased evaluation of the data variance structure. Biochemical pathway enrichment analysis suggested significant perturbations in 13 biochemical pathways as defined in KEGG. More than 50% of the metabolites that show significant changes in the EBC, can be classified as compatible solutes and include sugars, sugar alcohols, protein and non-protein amino acids, and organic acids, highlighting the need to maintain osmotic homeostasis to balance the accumulation of Na(+) and Cl(-) ions. Overall, the comparison of metabolic changes in salt treated relative to control samples suggests large alterations in M. crystallinum epidermal bladder cells.

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

Cancer.gov

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

PECAN: library-free peptide detection for data-independent acquisition tandem mass spectrometry data

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

Ting, Ying S.; Egertson, Jarrett D.; Bollinger, James G.

Data-independent acquisition (DIA) is an emerging mass spectrometry (MS)-based technique for unbiased and reproducible measurement of protein mixtures. DIA tandem mass spectrometry spectra are often highly multiplexed, containing product ions from multiple cofragmenting precursors. Detecting peptides directly from DIA data is therefore challenging; most DIA data analyses require spectral libraries. Here we present PECECAN (http://pecan.maccosslab.org), a library-free, peptide-centric tool that robustly and accurately detects peptides directly from DIA data. PECECAN reports evidence of detection based on product ion scoring, which enables detection of low-abundance analytes with poor precursor ion signal. We demonstrate the chromatographic peak picking accuracy and peptide detectionmore » capability of PECECAN, and we further validate its detection with data-dependent acquisition and targeted analyses. Lastly, we used PECECAN to build a plasma proteome library from DIA data and to query known sequence variants.« less

ATRX Directs Binding of PRC2 to Xist RNA and Polycomb Targets

PubMed Central

Sarma, Kavitha; Cifuentes-Rojas, Catherine; Ergun, Ayla; del Rosario, Amanda; Jeon, Yesu; White, Forest; Sadreyev, Ruslan; Lee, Jeannie T.

2015-01-01

SUMMARY X chromosome inactivation (XCI) depends on the long noncoding RNA Xist and its recruitment of Polycomb Repressive Complex 2 (PRC2). PRC2 is also targeted to other sites throughout the genome to effect transcriptional repression. Using XCI as a model, we apply an unbiased proteomics approach to isolate Xist and PRC2 regulators and identified ATRX. ATRX unexpectedly functions as a high-affinity RNA-binding protein that directly interacts with RepA/Xist RNA to promote loading of PRC2 in vivo. Without ATRX, PRC2 cannot load onto Xist RNA nor spread in cis along the X chromosome. Moreover, epigenomic profiling reveals that genome-wide targeting of PRC2 depends on ATRX, as loss of ATRX leads to spatial redistribution of PRC2 and derepression of Polycomb responsive genes. Thus, ATRX is a required specificity determinant for PRC2 targeting and function. PMID:25417162

Neuroprotective Drug for Nerve Trauma Revealed Using Artificial Intelligence.

PubMed

Romeo-Guitart, David; Forés, Joaquim; Herrando-Grabulosa, Mireia; Valls, Raquel; Leiva-Rodríguez, Tatiana; Galea, Elena; González-Pérez, Francisco; Navarro, Xavier; Petegnief, Valerie; Bosch, Assumpció; Coma, Mireia; Mas, José Manuel; Casas, Caty

2018-01-30

Here we used a systems biology approach and artificial intelligence to identify a neuroprotective agent for the treatment of peripheral nerve root avulsion. Based on accumulated knowledge of the neurodegenerative and neuroprotective processes that occur in motoneurons after root avulsion, we built up protein networks and converted them into mathematical models. Unbiased proteomic data from our preclinical models were used for machine learning algorithms and for restrictions to be imposed on mathematical solutions. Solutions allowed us to identify combinations of repurposed drugs as potential neuroprotective agents and we validated them in our preclinical models. The best one, NeuroHeal, neuroprotected motoneurons, exerted anti-inflammatory properties and promoted functional locomotor recovery. NeuroHeal endorsed the activation of Sirtuin 1, which was essential for its neuroprotective effect. These results support the value of network-centric approaches for drug discovery and demonstrate the efficacy of NeuroHeal as adjuvant treatment with surgical repair for nervous system trauma.

Testing and Validation of Computational Methods for Mass Spectrometry.

PubMed

Gatto, Laurent; Hansen, Kasper D; Hoopmann, Michael R; Hermjakob, Henning; Kohlbacher, Oliver; Beyer, Andreas

2016-03-04

High-throughput methods based on mass spectrometry (proteomics, metabolomics, lipidomics, etc.) produce a wealth of data that cannot be analyzed without computational methods. The impact of the choice of method on the overall result of a biological study is often underappreciated, but different methods can result in very different biological findings. It is thus essential to evaluate and compare the correctness and relative performance of computational methods. The volume of the data as well as the complexity of the algorithms render unbiased comparisons challenging. This paper discusses some problems and challenges in testing and validation of computational methods. We discuss the different types of data (simulated and experimental validation data) as well as different metrics to compare methods. We also introduce a new public repository for mass spectrometric reference data sets ( http://compms.org/RefData ) that contains a collection of publicly available data sets for performance evaluation for a wide range of different methods.

ATG proteins: Are we always looking at autophagy?

PubMed

Mauthe, Mario; Reggiori, Fulvio

2016-12-01

Autophagy is an intracellular degradation pathway that is regulated by the autophagy-related (ATG) proteins. For a long time it has been thought that ATG proteins were exclusively required for autophagy, but recent experimental evidence has revealed that these proteins are part of other cellular pathways, individually or as a functional group. To estimate the extent of these so-called unconventional functions of the ATG proteins, we decided to perform an unbiased siRNA screen targeting the entire ATG proteome and used viral replication as the readout. Our results have uncovered that a surprisingly high number of ATG proteins (36%) have a positive or negative role in promoting virus replication outside their classical role in autophagy. With the increasing knowledge about ATG protein unconventional functions and our investigation results, the interpretations about the possible involvement of autophagy in cellular or organismal functions that solely rely on the depletion of a single ATG protein, should be considered cautiously.

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

Clinical proteomic analysis of scrub typhus infection.

PubMed

Park, Edmond Changkyun; Lee, Sang-Yeop; Yun, Sung Ho; Choi, Chi-Won; Lee, Hayoung; Song, Hyun Seok; Jun, Sangmi; Kim, Gun-Hwa; Lee, Chang-Seop; Kim, Seung Il

2018-01-01

Scrub typhus is an acute and febrile infectious disease caused by the Gram-negative α-proteobacterium Orientia tsutsugamushi from the family Rickettsiaceae that is widely distributed in Northern, Southern and Eastern Asia. In the present study, we analysed the serum proteome of scrub typhus patients to investigate specific clinical protein patterns in an attempt to explain pathophysiology and discover potential biomarkers of infection. Serum samples were collected from three patients (before and after treatment with antibiotics) and three healthy subjects. One-dimensional sodium dodecyl sulphate-polyacrylamide gel electrophoresis followed by liquid chromatography-tandem mass spectrometry was performed to identify differentially abundant proteins using quantitative proteomic approaches. Bioinformatic analysis was then performed using Ingenuity Pathway Analysis. Proteomic analysis identified 236 serum proteins, of which 32 were differentially expressed in normal subjects, naive scrub typhus patients and patients treated with antibiotics. Comparative bioinformatic analysis of the identified proteins revealed up-regulation of proteins involved in immune responses, especially complement system, following infection with O. tsutsugamushi , and normal expression was largely rescued by antibiotic treatment. This is the first proteomic study of clinical serum samples from scrub typhus patients. Proteomic analysis identified changes in protein expression upon infection with O. tsutsugamushi and following antibiotic treatment. Our results provide valuable information for further investigation of scrub typhus therapy and diagnosis.

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.

Identification of Maturation-Specific Proteins by Single-Cell Proteomics of Human Oocytes

PubMed Central

Virant-Klun, Irma; Leicht, Stefan; Hughes, Christopher; Krijgsveld, Jeroen

2016-01-01

Oocytes undergo a range of complex processes via oogenesis, maturation, fertilization, and early embryonic development, eventually giving rise to a fully functioning organism. To understand proteome composition and diversity during maturation of human oocytes, here we have addressed crucial aspects of oocyte collection and proteome analysis, resulting in the first proteome and secretome maps of human oocytes. Starting from 100 oocytes collected via a novel serum-free hanging drop culture system, we identified 2,154 proteins, whose function indicate that oocytes are largely resting cells with a proteome that is tailored for homeostasis, cellular attachment, and interaction with its environment via secretory factors. In addition, we have identified 158 oocyte-enriched proteins (such as ECAT1, PIWIL3, NLRP7)1 not observed in high-coverage proteomics studies of other human cell lines or tissues. Exploiting SP3, a novel technology for proteomic sample preparation using magnetic beads, we scaled down proteome analysis to single cells. Despite the low protein content of only ∼100 ng per cell, we consistently identified ∼450 proteins from individual oocytes. When comparing individual oocytes at the germinal vesicle (GV) and metaphase II (MII) stage, we found that the Tudor and KH domain-containing protein (TDRKH) is preferentially expressed in immature oocytes, while Wee2, PCNA, and DNMT1 were enriched in mature cells, collectively indicating that maintenance of genome integrity is crucial during oocyte maturation. This study demonstrates that an innovative proteomics workflow facilitates analysis of single human oocytes to investigate human oocyte biology and preimplantation development. The approach presented here paves the way for quantitative proteomics in other quantity-limited tissues and cell types. Data associated with this study are available via ProteomeXchange with identifier PXD004142. PMID:27215607

Identification of Maturation-Specific Proteins by Single-Cell Proteomics of Human Oocytes.

PubMed

Virant-Klun, Irma; Leicht, Stefan; Hughes, Christopher; Krijgsveld, Jeroen

2016-08-01

Oocytes undergo a range of complex processes via oogenesis, maturation, fertilization, and early embryonic development, eventually giving rise to a fully functioning organism. To understand proteome composition and diversity during maturation of human oocytes, here we have addressed crucial aspects of oocyte collection and proteome analysis, resulting in the first proteome and secretome maps of human oocytes. Starting from 100 oocytes collected via a novel serum-free hanging drop culture system, we identified 2,154 proteins, whose function indicate that oocytes are largely resting cells with a proteome that is tailored for homeostasis, cellular attachment, and interaction with its environment via secretory factors. In addition, we have identified 158 oocyte-enriched proteins (such as ECAT1, PIWIL3, NLRP7)(1) not observed in high-coverage proteomics studies of other human cell lines or tissues. Exploiting SP3, a novel technology for proteomic sample preparation using magnetic beads, we scaled down proteome analysis to single cells. Despite the low protein content of only ∼100 ng per cell, we consistently identified ∼450 proteins from individual oocytes. When comparing individual oocytes at the germinal vesicle (GV) and metaphase II (MII) stage, we found that the Tudor and KH domain-containing protein (TDRKH) is preferentially expressed in immature oocytes, while Wee2, PCNA, and DNMT1 were enriched in mature cells, collectively indicating that maintenance of genome integrity is crucial during oocyte maturation. This study demonstrates that an innovative proteomics workflow facilitates analysis of single human oocytes to investigate human oocyte biology and preimplantation development. The approach presented here paves the way for quantitative proteomics in other quantity-limited tissues and cell types. Data associated with this study are available via ProteomeXchange with identifier PXD004142. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Marine proteomics: a critical assessment of an emerging technology.

PubMed

Slattery, Marc; Ankisetty, Sridevi; Corrales, Jone; Marsh-Hunkin, K Erica; Gochfeld, Deborah J; Willett, Kristine L; Rimoldi, John M

2012-10-26

The application of proteomics to marine sciences has increased in recent years because the proteome represents the interface between genotypic and phenotypic variability and, thus, corresponds to the broadest possible biomarker for eco-physiological responses and adaptations. Likewise, proteomics can provide important functional information regarding biosynthetic pathways, as well as insights into mechanism of action, of novel marine natural products. The goal of this review is to (1) explore the application of proteomics methodologies to marine systems, (2) assess the technical approaches that have been used, and (3) evaluate the pros and cons of this proteomic research, with the intent of providing a critical analysis of its future roles in marine sciences. To date, proteomics techniques have been utilized to investigate marine microbe, plant, invertebrate, and vertebrate physiology, developmental biology, seafood safety, susceptibility to disease, and responses to environmental change. However, marine proteomics studies often suffer from poor experimental design, sample processing/optimization difficulties, and data analysis/interpretation issues. Moreover, a major limitation is the lack of available annotated genomes and proteomes for most marine organisms, including several "model species". Even with these challenges in mind, there is no doubt that marine proteomics is a rapidly expanding and powerful integrative molecular research tool from which our knowledge of the marine environment, and the natural products from this resource, will be significantly expanded.

Preprocessing and Analysis of LC-MS-Based Proteomic Data

PubMed Central

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

2016-01-01

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

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.

Proteomics in medical microbiology.

PubMed

Cash, P

2000-04-01

The techniques of proteomics (high resolution two-dimensional electrophoresis and protein characterisation) are widely used for microbiological research to analyse global protein synthesis as an indicator of gene expression. The rapid progress in microbial proteomics has been achieved through the wide availability of whole genome sequences for a number of bacterial groups. Beyond providing a basic understanding of microbial gene expression, proteomics has also played a role in medical areas of microbiology. Progress has been made in the use of the techniques for investigating the epidemiology and taxonomy of human microbial pathogens, the identification of novel pathogenic mechanisms and the analysis of drug resistance. In each of these areas, proteomics has provided new insights that complement genomic-based investigations. This review describes the current progress in these research fields and highlights some of the technical challenges existing for the application of proteomics in medical microbiology. The latter concern the analysis of genetically heterogeneous bacterial populations and the integration of the proteomic and genomic data for these bacteria. The characterisation of the proteomes of bacterial pathogens growing in their natural hosts remains a future challenge.

Proteomic analysis of ligamentum flavum from patients with lumbar spinal stenosis.

PubMed

Kamita, Masahiro; Mori, Taiki; Sakai, Yoshihito; Ito, Sadayuki; Gomi, Masahiro; Miyamoto, Yuko; Harada, Atsushi; Niida, Shumpei; Yamada, Tesshi; Watanabe, Ken; Ono, Masaya

2015-05-01

Lumbar spinal stenosis (LSS) is a syndromic degenerative spinal disease and is characterized by spinal canal narrowing with subsequent neural compression causing gait disturbances. Although LSS is a major age-related musculoskeletal disease that causes large decreases in the daily living activities of the elderly, its molecular pathology has not been investigated using proteomics. Thus, we used several proteomic technologies to analyze the ligamentum flavum (LF) of individuals with LSS. Using comprehensive proteomics with strong cation exchange fractionation, we detected 1288 proteins in these LF samples. A GO analysis of the comprehensive proteome revealed that more than 30% of the identified proteins were extracellular. Next, we used 2D image converted analysis of LC/MS to compare LF obtained from individuals with LSS to that obtained from individuals with disc herniation (nondegenerative control). We detected 64 781 MS peaks and identified 1675 differentially expressed peptides derived from 286 proteins. We verified four differentially expressed proteins (fibronectin, serine protease HTRA1, tenascin, and asporin) by quantitative proteomics using SRM/MRM. The present proteomic study is the first to identify proteins from degenerated and hypertrophied LF in LSS, which will help in studying LSS. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Label-free proteomic analysis to confirm the predicted proteome of Corynebacterium pseudotuberculosis under nitrosative stress mediated by nitric oxide.

PubMed

Silva, Wanderson M; Carvalho, Rodrigo D; Soares, Siomar C; Bastos, Isabela Fs; Folador, Edson L; Souza, Gustavo Hmf; Le Loir, Yves; Miyoshi, Anderson; Silva, Artur; Azevedo, Vasco

2014-12-04

Corynebacterium pseudotuberculosis biovar ovis is a facultative intracellular pathogen, and the etiological agent of caseous lymphadenitis in small ruminants. During the infection process, the bacterium is subjected to several stress conditions, including nitrosative stress, which is caused by nitric oxide (NO). In silico analysis of the genome of C. pseudotuberculosis ovis 1002 predicted several genes that could influence the resistance of this pathogen to nitrosative stress. Here, we applied high-throughput proteomics using high definition mass spectrometry to characterize the functional genome of C. pseudotuberculosis ovis 1002 in the presence of NO-donor Diethylenetriamine/nitric oxide adduct (DETA/NO), with the aim of identifying proteins involved in nitrosative stress resistance. We characterized 835 proteins, representing approximately 41% of the predicted proteome of C. pseudotuberculosis ovis 1002, following exposure to nitrosative stress. In total, 102 proteins were exclusive to the proteome of DETA/NO-induced cells, and a further 58 proteins were differentially regulated between the DETA/NO and control conditions. An interactomic analysis of the differential proteome of C. pseudotuberculosis in response to nitrosative stress was also performed. Our proteomic data set suggested the activation of both a general stress response and a specific nitrosative stress response, as well as changes in proteins involved in cellular metabolism, detoxification, transcriptional regulation, and DNA synthesis and repair. Our proteomic analysis validated previously-determined in silico data for C. pseudotuberculosis ovis 1002. In addition, proteomic screening performed in the presence of NO enabled the identification of a set of factors that can influence the resistance and survival of C. pseudotuberculosis during exposure to nitrosative stress.

CPTAC Prospective Biospecimen Collection Solicitation | Office of Cancer Clinical Proteomics Research

Cancer.gov

A new funding opportunity in support of the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) seeks to prospectively procure tumor samples, collected for proteomics investigation.

Proteomics: a new approach to the study of disease.

PubMed

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

2000-11-01

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

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

Birth of plant proteomics in India: a new horizon.

PubMed

Narula, Kanika; Pandey, Aarti; Gayali, Saurabh; Chakraborty, Niranjan; Chakraborty, Subhra

2015-09-08

In the post-genomic era, proteomics is acknowledged as the next frontier for biological research. Although India has a long and distinguished tradition in protein research, the initiation of proteomics studies was a new horizon. Protein research witnessed enormous progress in protein separation, high-resolution refinements, biochemical identification of the proteins, protein-protein interaction, and structure-function analysis. Plant proteomics research, in India, began its journey on investigation of the proteome profiling, complexity analysis, protein trafficking, and biochemical modeling. The research article by Bhushan et al. in 2006 marked the birth of the plant proteomics research in India. Since then plant proteomics studies expanded progressively and are now being carried out in various institutions spread across the country. The compilation presented here seeks to trace the history of development in the area during the past decade based on publications till date. In this review, we emphasize on outcomes of the field providing prospects on proteomic pathway analyses. Finally, we discuss the connotation of strategies and the potential that would provide the framework of plant proteome research. The past decades have seen rapidly growing number of sequenced plant genomes and associated genomic resources. To keep pace with this increasing body of data, India is in the provisional phase of proteomics research to develop a comparative hub for plant proteomes and protein families, but it requires a strong impetus from intellectuals, entrepreneurs, and government agencies. Here, we aim to provide an overview of past, present and future of Indian plant proteomics, which would serve as an evaluation platform for those seeking to incorporate proteomics into their research programs. This article is part of a Special Issue entitled: Proteomics in India. Copyright © 2015 Elsevier B.V. All rights reserved.

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

Cancer.gov

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

CPTAC Releases Largest-Ever Colorectal Cancer Proteome Dataset from Previously Genome Characterized Tumors | Office of Cancer Clinical Proteomics Research

Cancer.gov

On September 4, 2013, NCI’s Clinical Proteomics Tumor Analysis Consortium (CPTAC) publicly released proteomic data produced from colorectal tumor samples previously analyzed by The Cancer Genome Atlas (TCGA).  This is the initial release of proteomic tumor data designed to complement genomic data on the same tumors. The data is publicly available at the CPTAC data portal.

A Simple Method for Rapid Depletion of Rubisco from Soybean (Glycine max) Leaf for Proteomic Analysis of Lower Abundance Proteins

USDA-ARS?s Scientific Manuscript database

2-DE analysis of complex plant proteomes has limited dynamic resolution because only abundant proteins can be detected. Proteomic assessment of the low abundance proteins within leaf tissue is difficult when it is comprised of 30 – 50% of the CO2 fixation enzyme Rubisco. Resolution can be improved t...

Xylem sap proteomics.

PubMed

de Bernonville, Thomas Dugé; Albenne, Cécile; Arlat, Matthieu; Hoffmann, Laurent; Lauber, Emmanuelle; Jamet, Elisabeth

2014-01-01

Proteomic analysis of xylem sap has recently become a major field of interest to understand several biological questions related to plant development and responses to environmental clues. The xylem sap appears as a dynamic fluid undergoing changes in its proteome upon abiotic and biotic stresses. Unlike cell compartments which are amenable to purification in sufficient amount prior to proteomic analysis, the xylem sap has to be collected in particular conditions to avoid contamination by intracellular proteins and to obtain enough material. A model plant like Arabidopsis thaliana is not suitable for such an analysis because efficient harvesting of xylem sap is difficult. The analysis of the xylem sap proteome also requires specific procedures to concentrate proteins and to focus on proteins predicted to be secreted. Indeed, xylem sap proteins appear to be synthesized and secreted in the root stele or to originate from dying differentiated xylem cells. This chapter describes protocols to collect xylem sap from Brassica species and to prepare total and N-glycoprotein extracts for identification of proteins by mass spectrometry analyses and bioinformatics.

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.

Establishing Substantial Equivalence: Proteomics

NASA Astrophysics Data System (ADS)

Lovegrove, Alison; Salt, Louise; Shewry, Peter R.

Wheat is a major crop in world agriculture and is consumed after processing into a range of food products. It is therefore of great importance to determine the consequences (intended and unintended) of transgenesis in wheat and whether genetically modified lines are substantially equivalent to those produced by conventional plant breeding. Proteomic analysis is one of several approaches which can be used to address these questions. Two-dimensional PAGE (2D PAGE) remains the most widely available method for proteomic analysis, but is notoriously difficult to reproduce between laboratories. We therefore describe methods which have been developed as standard operating procedures in our laboratory to ensure the reproducibility of proteomic analyses of wheat using 2D PAGE analysis of grain proteins.

Integrated Analysis of Transcriptomic and Proteomic Data

PubMed Central

Haider, Saad; Pal, Ranadip

2013-01-01

Until recently, understanding the regulatory behavior of cells has been pursued through independent analysis of the transcriptome or the proteome. Based on the central dogma, it was generally assumed that there exist a direct correspondence between mRNA transcripts and generated protein expressions. However, recent studies have shown that the correlation between mRNA and Protein expressions can be low due to various factors such as different half lives and post transcription machinery. Thus, a joint analysis of the transcriptomic and proteomic data can provide useful insights that may not be deciphered from individual analysis of mRNA or protein expressions. This article reviews the existing major approaches for joint analysis of transcriptomic and proteomic data. We categorize the different approaches into eight main categories based on the initial algorithm and final analysis goal. We further present analogies with other domains and discuss the existing research problems in this area. PMID:24082820

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

PubMed

Welker, F

2018-02-20

The study of ancient protein sequences is increasingly focused on the analysis of older samples, including those of ancient hominins. The analysis of such ancient proteomes thereby potentially suffers from "cross-species proteomic effects": the loss of peptide and protein identifications at increased evolutionary distances due to a larger number of protein sequence differences between the database sequence and the analyzed organism. Error-tolerant proteomic search algorithms should theoretically overcome this problem at both the peptide and protein level; however, this has not been demonstrated. If error-tolerant searches do not overcome the cross-species proteomic issue then there might be inherent biases in the identified proteomes. Here, a bioinformatics experiment is performed to test this using a set of modern human bone proteomes and three independent searches against sequence databases at increasing evolutionary distances: the human (0 Ma), chimpanzee (6-8 Ma) and orangutan (16-17 Ma) reference proteomes, respectively. Incorrectly suggested amino acid substitutions are absent when employing adequate filtering criteria for mutable Peptide Spectrum Matches (PSMs), but roughly half of the mutable PSMs were not recovered. As a result, peptide and protein identification rates are higher in error-tolerant mode compared to non-error-tolerant searches but did not recover protein identifications completely. Data indicates that peptide length and the number of mutations between the target and database sequences are the main factors influencing mutable PSM identification. The error-tolerant results suggest that the cross-species proteomics problem is not overcome at increasing evolutionary distances, even at the protein level. Peptide and protein loss has the potential to significantly impact divergence dating and proteome comparisons when using ancient samples as there is a bias towards the identification of conserved sequences and proteins. Effects are minimized between moderately divergent proteomes, as indicated by almost complete recovery of informative positions in the search against the chimpanzee proteome (≈90%, 6-8 Ma). This provides a bioinformatic background to future phylogenetic and proteomic analysis of ancient hominin proteomes, including the future description of novel hominin amino acid sequences, but also has negative implications for the study of fast-evolving proteins in hominins, non-hominin animals, and ancient bacterial proteins in evolutionary contexts.

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.

Allowable SEM noise for unbiased LER measurement

NASA Astrophysics Data System (ADS)

Papavieros, George; Constantoudis, Vassilios; Gogolides, Evangelos

2018-03-01

Recently, a novel method for the calculation of unbiased Line Edge Roughness based on Power Spectral Density analysis has been proposed. In this paper first an alternative method is discussed and investigated, utilizing the Height-Height Correlation Function (HHCF) of edges. The HHCF-based method enables the unbiased determination of the whole triplet of LER parameters including besides rms the correlation length and roughness exponent. The key of both methods is the sensitivity of PSD and HHCF on noise at high frequencies and short distance respectively. Secondly, we elaborate a testbed of synthesized SEM images with controlled LER and noise to justify the effectiveness of the proposed unbiased methods. Our main objective is to find out the boundaries of the method in respect to noise levels and roughness characteristics, for which the method remains reliable, i.e the maximum amount of noise allowed, for which the output results cope with the controllable known inputs. At the same time, we will also set the extremes of roughness parameters for which the methods hold their accuracy.

Systems Proteomics for Translational Network Medicine

PubMed Central

Arrell, D. Kent; Terzic, Andre

2012-01-01

Universal principles underlying network science, and their ever-increasing applications in biomedicine, underscore the unprecedented capacity of systems biology based strategies to synthesize and resolve massive high throughput generated datasets. Enabling previously unattainable comprehension of biological complexity, systems approaches have accelerated progress in elucidating disease prediction, progression, and outcome. Applied to the spectrum of states spanning health and disease, network proteomics establishes a collation, integration, and prioritization algorithm to guide mapping and decoding of proteome landscapes from large-scale raw data. Providing unparalleled deconvolution of protein lists into global interactomes, integrative systems proteomics enables objective, multi-modal interpretation at molecular, pathway, and network scales, merging individual molecular components, their plurality of interactions, and functional contributions for systems comprehension. As such, network systems approaches are increasingly exploited for objective interpretation of cardiovascular proteomics studies. Here, we highlight network systems proteomic analysis pipelines for integration and biological interpretation through protein cartography, ontological categorization, pathway and functional enrichment and complex network analysis. PMID:22896016

HTAPP: High-Throughput Autonomous Proteomic Pipeline

PubMed Central

Yu, Kebing; Salomon, Arthur R.

2011-01-01

Recent advances in the speed and sensitivity of mass spectrometers and in analytical methods, the exponential acceleration of computer processing speeds, and the availability of genomic databases from an array of species and protein information databases have led to a deluge of proteomic data. The development of a lab-based automated proteomic software platform for the automated collection, processing, storage, and visualization of expansive proteomic datasets is critically important. The high-throughput autonomous proteomic pipeline (HTAPP) described here is designed from the ground up to provide critically important flexibility for diverse proteomic workflows and to streamline the total analysis of a complex proteomic sample. This tool is comprised of software that controls the acquisition of mass spectral data along with automation of post-acquisition tasks such as peptide quantification, clustered MS/MS spectral database searching, statistical validation, and data exploration within a user-configurable lab-based relational database. The software design of HTAPP focuses on accommodating diverse workflows and providing missing software functionality to a wide range of proteomic researchers to accelerate the extraction of biological meaning from immense proteomic data sets. Although individual software modules in our integrated technology platform may have some similarities to existing tools, the true novelty of the approach described here is in the synergistic and flexible combination of these tools to provide an integrated and efficient analysis of proteomic samples. PMID:20336676

Achievements and perspectives of top-down proteomics.

PubMed

Armirotti, Andrea; Damonte, Gianluca

2010-10-01

Over the last years, top-down (TD) MS has gained a remarkable space in proteomics, rapidly trespassing the limit between a promising approach and a solid, established technique. Several research groups worldwide have implemented TD analysis in their routine work on proteomics, deriving structural information on proteins with the level of accuracy that is impossible to achieve with classical bottom-up approaches. Complete maps of PTMs and assessment of single aminoacid polymorphisms are only a few of the results that can be obtained with this technique. Despite some existing technical and economical limitations, TD analysis is at present the most powerful instrument for MS-based proteomics and its implementation in routine workflow is a rapidly approaching turning point in proteomics. In this review article, the state-of-the-art of TD approach is described along with its major advantages and drawbacks and the most recent trends in TD analysis are discussed. References for all the covered topics are reported in the text, with the aim to support both newcomers and mass spectrometrists already introduced to TD proteomics.

Toward the Standardization of Mitochondrial Proteomics: The Italian Mitochondrial Human Proteome Project Initiative.

PubMed

Alberio, Tiziana; Pieroni, Luisa; Ronci, Maurizio; Banfi, Cristina; Bongarzone, Italia; Bottoni, Patrizia; Brioschi, Maura; Caterino, Marianna; Chinello, Clizia; Cormio, Antonella; Cozzolino, Flora; Cunsolo, Vincenzo; Fontana, Simona; Garavaglia, Barbara; Giusti, Laura; Greco, Viviana; Lucacchini, Antonio; Maffioli, Elisa; Magni, Fulvio; Monteleone, Francesca; Monti, Maria; Monti, Valentina; Musicco, Clara; Petrosillo, Giuseppe; Porcelli, Vito; Saletti, Rosaria; Scatena, Roberto; Soggiu, Alessio; Tedeschi, Gabriella; Zilocchi, Mara; Roncada, Paola; Urbani, Andrea; Fasano, Mauro

2017-12-01

The Mitochondrial Human Proteome Project aims at understanding the function of the mitochondrial proteome and its crosstalk with the proteome of other organelles. Being able to choose a suitable and validated enrichment protocol of functional mitochondria, based on the specific needs of the downstream proteomics analysis, would greatly help the researchers in the field. Mitochondrial fractions from ten model cell lines were prepared using three enrichment protocols and analyzed on seven different LC-MS/MS platforms. All data were processed using neXtProt as reference database. The data are available for the Human Proteome Project purposes through the ProteomeXchange Consortium with the identifier PXD007053. The processed data sets were analyzed using a suite of R routines to perform a statistical analysis and to retrieve subcellular and submitochondrial localizations. Although the overall number of identified total and mitochondrial proteins was not significantly dependent on the enrichment protocol, specific line to line differences were observed. Moreover, the protein lists were mapped to a network representing the functional mitochondrial proteome, encompassing mitochondrial proteins and their first interactors. More than 80% of the identified proteins resulted in nodes of this network but with a different ability in coisolating mitochondria-associated structures for each enrichment protocol/cell line pair.

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.

Multidimensional proteomics for cell biology.

PubMed

Larance, Mark; Lamond, Angus I

2015-05-01

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

CPTAC Releases Cancer Proteome Confirmatory Ovarian Study Data | Office of Cancer Clinical Proteomics Research

Cancer.gov

A catalogue of molecular aberrations that cause ovarian cancer is critical for developing and deploying diagnostics and therapies that will improve patients’ lives. Because a comprehensive molecular view of cancer is important for ultimately guiding treatment, the National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) has released the cancer proteome confirmatory ovarian study data sets.

Proteome Profiles of Outer Membrane Vesicles and Extracellular Matrix of Pseudomonas aeruginosa Biofilms.

PubMed

Couto, Narciso; Schooling, Sarah R; Dutcher, John R; Barber, Jill

2015-10-02

In the present work, two different proteomic platforms, gel-based and gel-free, were used to map the matrix and outer membrane vesicle exoproteomes of Pseudomonas aeruginosa PAO1 biofilms. These two proteomic strategies allowed us a confident identification of 207 and 327 proteins from enriched outer membrane vesicles and whole matrix isolated from biofilms. Because of the physicochemical characteristics of these subproteomes, the two strategies showed complementarity, and thus, the most comprehensive analysis of P. aeruginosa exoproteome to date was achieved. Under our conditions, outer membrane vesicles contribute approximately 20% of the whole matrix proteome, demonstrating that membrane vesicles are an important component of the matrix. The proteomic profiles were analyzed in terms of their biological context, namely, a biofilm. Accordingly relevant metabolic processes involved in cellular adaptation to the biofilm lifestyle as well as those related to P. aeruginosa virulence capabilities were a key feature of the analyses. The diversity of the matrix proteome corroborates the idea of high heterogeneity within the biofilm; cells can display different levels of metabolism and can adapt to local microenvironments making this proteomic analysis challenging. In addition to analyzing our own primary data, we extend the analysis to published data by other groups in order to deepen our understanding of the complexity inherent within biofilm populations.

Advances of Proteomic Sciences in Dentistry.

PubMed

Khurshid, Zohaib; Zohaib, Sana; Najeeb, Shariq; Zafar, Muhammad Sohail; Rehman, Rabia; Rehman, Ihtesham Ur

2016-05-13

Applications of proteomics tools revolutionized various biomedical disciplines such as genetics, molecular biology, medicine, and dentistry. The aim of this review is to highlight the major milestones in proteomics in dentistry during the last fifteen years. Human oral cavity contains hard and soft tissues and various biofluids including saliva and crevicular fluid. Proteomics has brought revolution in dentistry by helping in the early diagnosis of various diseases identified by the detection of numerous biomarkers present in the oral fluids. This paper covers the role of proteomics tools for the analysis of oral tissues. In addition, dental materials proteomics and their future directions are discussed.

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

PubMed

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

2008-09-01

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

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

Cancer.gov

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

CPTAC Releases Cancer Proteome Confirmatory Breast Study Data | Office of Cancer Clinical Proteomics Research

Cancer.gov

An estimated 252,710 new cases of female breast cancer, accounting for 15% of all new cancer cases, occurred in 2017. To better understand proteogenomic abnormalities in breast cancer, the National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) announces the release of the cancer proteome confirmatory breast study data. The goal of the study was to comprehensively characterize the proteome and phosphoproteome on approximately 100 prospectively collected breast tumor and adjacent normal tissues.

A secretomics analysis reveals major differences in the macrophage responses towards different types of carbon nanotubes.

PubMed

Palomäki, Jaana; Sund, Jukka; Vippola, Minnamari; Kinaret, Pia; Greco, Dario; Savolainen, Kai; Puustinen, Anne; Alenius, Harri

2015-01-01

Certain types of carbon nanotubes (CNT) can evoke inflammation, fibrosis and mesothelioma in vivo, raising concerns about their potential health effects. It has been recently postulated that NLRP3 inflammasome activation is important in the CNT-induced toxicity. However, more comprehensive studies of the protein secretion induced by CNT can provide new information about their possible pathogenic mechanisms. Here, we studied protein secretion from human macrophages with a proteomic approach in an unbiased way. Human monocyte-derived macrophages (MDM) were exposed to tangled or rigid, long multi-walled CNT (MWCNT) or crocidolite asbestos for 6 h. The growth media was concentrated and secreted proteins were analyzed using 2D-DIGE and DeCyder software. Subsequently, significantly up- or down-regulated protein spots were in-gel digested and identified with an LC-MS/MS approach. Bioinformatics analysis was performed to reveal the different patterns of protein secretion induced by these materials. The results show that both long rigid MWCNT and asbestos elicited ample and highly similar protein secretion. In contrast, exposure to long tangled MWCNT induced weaker protein secretion with a more distinct profile. Secretion of lysosomal proteins followed the exposure to all materials, suggesting lysosomal damage. However, only long rigid MWCNT was associated with apoptosis. This analysis suggests that the CNT toxicity in human MDM is mediated via vigorous secretion of inflammation-related proteins and apoptosis. This study provides new insights into the mechanisms of toxicity of high aspect ratio nanomaterials and indicates that not all types of CNT are as hazardous as asbestos fibers.

Abiotic Stress Tolerance of Charophyte Green Algae: New Challenges for Omics Techniques

PubMed Central

Holzinger, Andreas; Pichrtová, Martina

2016-01-01

Charophyte green algae are a paraphyletic group of freshwater and terrestrial green algae, comprising the classes of Chlorokybophyceae, Coleochaetophyceae, Klebsormidiophyceae, Zygnematophyceae, Mesostigmatophyceae, and Charo- phyceae. Zygnematophyceae (Conjugating green algae) are considered to be closest algal relatives to land plants (Embryophyta). Therefore, they are ideal model organisms for studying stress tolerance mechanisms connected with transition to land, one of the most important events in plant evolution and the Earth’s history. In Zygnematophyceae, but also in Coleochaetophyceae, Chlorokybophyceae, and Klebsormidiophyceae terrestrial members are found which are frequently exposed to naturally occurring abiotic stress scenarios like desiccation, freezing and high photosynthetic active (PAR) as well as ultraviolet (UV) irradiation. Here, we summarize current knowledge about various stress tolerance mechanisms including insight provided by pioneer transcriptomic and proteomic studies. While formation of dormant spores is a typical strategy of freshwater classes, true terrestrial groups are stress tolerant in vegetative state. Aggregation of cells, flexible cell walls, mucilage production and accumulation of osmotically active compounds are the most common desiccation tolerance strategies. In addition, high photophysiological plasticity and accumulation of UV-screening compounds are important protective mechanisms in conditions with high irradiation. Now a shift from classical chemical analysis to next-generation genome sequencing, gene reconstruction and annotation, genome-scale molecular analysis using omics technologies followed by computer-assisted analysis will give new insights in a systems biology approach. For example, changes in transcriptome and role of phytohormone signaling in Klebsormidium during desiccation were recently described. Application of these modern approaches will deeply enhance our understanding of stress reactions in an unbiased non-targeted view in an evolutionary context. PMID:27242877

Proteomic analysis of bovine nucleolus.

PubMed

Patel, Amrutlal K; Olson, Doug; Tikoo, Suresh K

2010-09-01

Nucleolus is the most prominent subnuclear structure, which performs a wide variety of functions in the eukaryotic cellular processes. In order to understand the structural and functional role of the nucleoli in bovine cells, we analyzed the proteomic composition of the bovine nucleoli. The nucleoli were isolated from Madin Darby bovine kidney cells and subjected to proteomic analysis by LC-MS/MS after fractionation by SDS-PAGE and strong cation exchange chromatography. Analysis of the data using the Mascot database search and the GPM database search identified 311 proteins in the bovine nucleoli, which contained 22 proteins previously not identified in the proteomic analysis of human nucleoli. Analysis of the identified proteins using the GoMiner software suggested that the bovine nucleoli contained proteins involved in ribosomal biogenesis, cell cycle control, transcriptional, translational and post-translational regulation, transport, and structural organization. Copyright © 2010 Beijing Genomics Institute. Published by Elsevier Ltd. All rights reserved.

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

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.

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.

Halobacterium salinarum NRC-1 PeptideAtlas: strategies for targeted proteomics

PubMed Central

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

2009-01-01

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

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

PubMed

Kamada, Haruhiko

2012-01-01

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

Autocorrelation analysis for the unbiased determination of power-law exponents in single-quantum-dot blinking.

PubMed

Houel, Julien; Doan, Quang T; Cajgfinger, Thomas; Ledoux, Gilles; Amans, David; Aubret, Antoine; Dominjon, Agnès; Ferriol, Sylvain; Barbier, Rémi; Nasilowski, Michel; Lhuillier, Emmanuel; Dubertret, Benoît; Dujardin, Christophe; Kulzer, Florian

2015-01-27

We present an unbiased and robust analysis method for power-law blinking statistics in the photoluminescence of single nanoemitters, allowing us to extract both the bright- and dark-state power-law exponents from the emitters' intensity autocorrelation functions. As opposed to the widely used threshold method, our technique therefore does not require discriminating the emission levels of bright and dark states in the experimental intensity timetraces. We rely on the simultaneous recording of 450 emission timetraces of single CdSe/CdS core/shell quantum dots at a frame rate of 250 Hz with single photon sensitivity. Under these conditions, our approach can determine ON and OFF power-law exponents with a precision of 3% from a comparison to numerical simulations, even for shot-noise-dominated emission signals with an average intensity below 1 photon per frame and per quantum dot. These capabilities pave the way for the unbiased, threshold-free determination of blinking power-law exponents at the microsecond time scale.

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.

Michael T. Guarnieri | NREL

Science.gov Websites

accumulation," J. Proteomics (2013) "Comparative Proteomics Lends Insight into Genotype-Specific Pathogenicity," J. Proteomics (2013) "De Novo Transcriptomic Analysis of Hydrogen Production in the amino acid changes in the small envelope protein and rescued by a novel glycosolation site," J

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

Advances of Proteomic Sciences in Dentistry

PubMed Central

Khurshid, Zohaib; Zohaib, Sana; Najeeb, Shariq; Zafar, Muhammad Sohail; Rehman, Rabia; Rehman, Ihtesham Ur

2016-01-01

Applications of proteomics tools revolutionized various biomedical disciplines such as genetics, molecular biology, medicine, and dentistry. The aim of this review is to highlight the major milestones in proteomics in dentistry during the last fifteen years. Human oral cavity contains hard and soft tissues and various biofluids including saliva and crevicular fluid. Proteomics has brought revolution in dentistry by helping in the early diagnosis of various diseases identified by the detection of numerous biomarkers present in the oral fluids. This paper covers the role of proteomics tools for the analysis of oral tissues. In addition, dental materials proteomics and their future directions are discussed. PMID:27187379

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.

SAFE Software and FED Database to Uncover Protein-Protein Interactions using Gene Fusion Analysis.

PubMed

Tsagrasoulis, Dimosthenis; Danos, Vasilis; Kissa, Maria; Trimpalis, Philip; Koumandou, V Lila; Karagouni, Amalia D; Tsakalidis, Athanasios; Kossida, Sophia

2012-01-01

Domain Fusion Analysis takes advantage of the fact that certain proteins in a given proteome A, are found to have statistically significant similarity with two separate proteins in another proteome B. In other words, the result of a fusion event between two separate proteins in proteome B is a specific full-length protein in proteome A. In such a case, it can be safely concluded that the protein pair has a common biological function or even interacts physically. In this paper, we present the Fusion Events Database (FED), a database for the maintenance and retrieval of fusion data both in prokaryotic and eukaryotic organisms and the Software for the Analysis of Fusion Events (SAFE), a computational platform implemented for the automated detection, filtering and visualization of fusion events (both available at: http://www.bioacademy.gr/bioinformatics/projects/ProteinFusion/index.htm). Finally, we analyze the proteomes of three microorganisms using these tools in order to demonstrate their functionality.

SAFE Software and FED Database to Uncover Protein-Protein Interactions using Gene Fusion Analysis

PubMed Central

Tsagrasoulis, Dimosthenis; Danos, Vasilis; Kissa, Maria; Trimpalis, Philip; Koumandou, V. Lila; Karagouni, Amalia D.; Tsakalidis, Athanasios; Kossida, Sophia

2012-01-01

Domain Fusion Analysis takes advantage of the fact that certain proteins in a given proteome A, are found to have statistically significant similarity with two separate proteins in another proteome B. In other words, the result of a fusion event between two separate proteins in proteome B is a specific full-length protein in proteome A. In such a case, it can be safely concluded that the protein pair has a common biological function or even interacts physically. In this paper, we present the Fusion Events Database (FED), a database for the maintenance and retrieval of fusion data both in prokaryotic and eukaryotic organisms and the Software for the Analysis of Fusion Events (SAFE), a computational platform implemented for the automated detection, filtering and visualization of fusion events (both available at: http://www.bioacademy.gr/bioinformatics/projects/ProteinFusion/index.htm). Finally, we analyze the proteomes of three microorganisms using these tools in order to demonstrate their functionality. PMID:22267904

Proteomics Analysis of Bladder Cancer Exosomes*

PubMed Central

Welton, Joanne L.; Khanna, Sanjay; Giles, Peter J.; Brennan, Paul; Brewis, Ian A.; Staffurth, John; Mason, Malcolm D.; Clayton, Aled

2010-01-01

Exosomes are nanometer-sized vesicles, secreted by various cell types, present in biological fluids that are particularly rich in membrane proteins. Ex vivo analysis of exosomes may provide biomarker discovery platforms and form non-invasive tools for disease diagnosis and monitoring. These vesicles have never before been studied in the context of bladder cancer, a major malignancy of the urological tract. We present the first proteomics analysis of bladder cancer cell exosomes. Using ultracentrifugation on a sucrose cushion, exosomes were highly purified from cultured HT1376 bladder cancer cells and verified as low in contaminants by Western blotting and flow cytometry of exosome-coated beads. Solubilization in a buffer containing SDS and DTT was essential for achieving proteomics analysis using an LC-MALDI-TOF/TOF MS approach. We report 353 high quality identifications with 72 proteins not previously identified by other human exosome proteomics studies. Overrepresentation analysis to compare this data set with previous exosome proteomics studies (using the ExoCarta database) revealed that the proteome was consistent with that of various exosomes with particular overlap with exosomes of carcinoma origin. Interrogating the Gene Ontology database highlighted a strong association of this proteome with carcinoma of bladder and other sites. The data also highlighted how homology among human leukocyte antigen haplotypes may confound MASCOT designation of major histocompatability complex Class I nomenclature, requiring data from PCR-based human leukocyte antigen haplotyping to clarify anomalous identifications. Validation of 18 MS protein identifications (including basigin, galectin-3, trophoblast glycoprotein (5T4), and others) was performed by a combination of Western blotting, flotation on linear sucrose gradients, and flow cytometry, confirming their exosomal expression. Some were confirmed positive on urinary exosomes from a bladder cancer patient. In summary, the exosome proteomics data set presented is of unrivaled quality. The data will aid in the development of urine exosome-based clinical tools for monitoring disease and will inform follow-up studies into varied aspects of exosome manufacture and function. PMID:20224111

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

PubMed

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

2013-10-01

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

Advances in Proteomics Data Analysis and Display Using an Accurate Mass and Time Tag Approach

PubMed Central

Zimmer, Jennifer S.D.; Monroe, Matthew E.; Qian, Wei-Jun; Smith, Richard D.

2007-01-01

Proteomics has recently demonstrated utility in understanding cellular processes on the molecular level as a component of systems biology approaches and for identifying potential biomarkers of various disease states. The large amount of data generated by utilizing high efficiency (e.g., chromatographic) separations coupled to high mass accuracy mass spectrometry for high-throughput proteomics analyses presents challenges related to data processing, analysis, and display. This review focuses on recent advances in nanoLC-FTICR-MS-based proteomics approaches and the accompanying data processing tools that have been developed to display and interpret the large volumes of data being produced. PMID:16429408

Rice proteome analysis: a step toward functional analysis of the rice genome.

PubMed

Komatsu, Setsuko; Tanaka, Naoki

2005-03-01

The technique of proteome analysis using 2-DE has the power to monitor global changes that occur in the protein complement of tissues and subcellular compartments. In this review, we describe construction of the rice proteome database, the cataloging of rice proteins, and the functional characterization of some of the proteins identified. Initially, proteins extracted from various tissues and organelles were separated by 2-DE and an image analyzer was used to construct a display or reference map of the proteins. The rice proteome database currently contains 23 reference maps based on 2-DE of proteins from different rice tissues and subcellular compartments. These reference maps comprise 13 129 rice proteins, and the amino acid sequences of 5092 of these proteins are entered in the database. Major proteins involved in growth or stress responses have been identified by using a proteomics approach and some of these proteins have unique functions. Furthermore, initial work has also begun on analyzing the phosphoproteome and protein-protein interactions in rice. The information obtained from the rice proteome database will aid in the molecular cloning of rice genes and in predicting the function of unknown proteins.

Placental Proteomics: A Shortcut to Biological Insight

PubMed Central

Robinson, John M.; Vandré, Dale D.; Ackerman, William E.

2012-01-01

Proteomics analysis of biological samples has the potential to identify novel protein expression patterns and/or changes in protein expression patterns in different developmental or disease states. An important component of successful proteomics research, at least in its present form, is to reduce the complexity of the sample if it is derived from cells or tissues. One method to simplify complex tissues is to focus on a specific, highly purified sub-proteome. Using this approach we have developed methods to prepare highly enriched fractions of the apical plasma membrane of the syncytiotrophoblast. Through proteomics analysis of this fraction we have identified over five hundred proteins several of which were previously not known to reside in the syncytiotrophoblast. Herein, we focus on two of these, dysferlin and myoferlin. These proteins, largely known from studies of skeletal muscle, may not have been found in the human placenta were it not for discovery-based proteomics analysis. This new knowledge, acquired through a discovery-driven approach, can now be applied for the generation of hypothesis-based experimentation. Thus discovery-based and hypothesis-based research are complimentary approaches that when coupled together can hasten scientific discoveries. PMID:19070895

Application of an Improved Proteomics Method for Abundant Protein Cleanup: Molecular and Genomic Mechanisms Study in Plant Defense*

PubMed Central

Zhang, Yixiang; Gao, Peng; Xing, Zhuo; Jin, Shumei; Chen, Zhide; Liu, Lantao; Constantino, Nasie; Wang, Xinwang; Shi, Weibing; Yuan, Joshua S.; Dai, Susie Y.

2013-01-01

High abundance proteins like ribulose-1,5-bisphosphate carboxylase oxygenase (Rubisco) impose a consistent challenge for the whole proteome characterization using shot-gun proteomics. To address this challenge, we developed and evaluated Polyethyleneimine Assisted Rubisco Cleanup (PARC) as a new method by combining both abundant protein removal and fractionation. The new approach was applied to a plant insect interaction study to validate the platform and investigate mechanisms for plant defense against herbivorous insects. Our results indicated that PARC can effectively remove Rubisco, improve the protein identification, and discover almost three times more differentially regulated proteins. The significantly enhanced shot-gun proteomics performance was translated into in-depth proteomic and molecular mechanisms for plant insect interaction, where carbon re-distribution was used to play an essential role. Moreover, the transcriptomic validation also confirmed the reliability of PARC analysis. Finally, functional studies were carried out for two differentially regulated genes as revealed by PARC analysis. Insect resistance was induced by over-expressing either jacalin-like or cupin-like genes in rice. The results further highlighted that PARC can serve as an effective strategy for proteomics analysis and gene discovery. PMID:23943779

Metabolomic and proteomic analysis of a clonal insulin-producing beta-cell line (INS-1 832/13).

PubMed

Fernandez, Céline; Fransson, Ulrika; Hallgard, Elna; Spégel, Peter; Holm, Cecilia; Krogh, Morten; Wårell, Kristofer; James, Peter; Mulder, Hindrik

2008-01-01

Metabolites generated from fuel metabolism in pancreatic beta-cells control exocytosis of insulin, a process which fails in type 2 diabetes. To identify and quantify these metabolites, global and unbiased analysis of cellular metabolism is required. To this end, polar metabolites, extracted from the clonal 832/13 beta-cell line cultured at 2.8 and 16.7 mM glucose for 48 h, were derivatized followed by identification and quantification, using gas chromatography (GC) and mass spectrometry (MS). After culture at 16.7 mM glucose for 48 h, 832/13 beta-cells exhibited a phenotype reminiscent of glucotoxicity with decreased content and secretion of insulin. The metabolomic analysis revealed alterations in the levels of 7 metabolites derived from glycolysis, the TCA cycle and pentose phosphate shunt, and 4 amino acids. Principal component analysis of the metabolite data showed two clusters, corresponding to the cells cultured at 2.8 and 16.7 mM glucose, respectively. Concurrent changes in protein expression were analyzed by 2-D gel electrophoresis followed by LC-MS/MS. The identities of 86 spots corresponding to 75 unique proteins that were significantly different in 832/13 beta-cells cultured at 16.7 mM glucose were established. Only 5 of these were found to be metabolic enzymes that could be involved in the metabolomic alterations observed. Anticipated changes in metabolite levels in cells exposed to increased glucose were observed, while changes in enzyme levels were much less profound. This suggests that substrate availability, allosteric regulation, and/or post-translational modifications are more important determinants of metabolite levels than enzyme expression at the protein level.

Automated image alignment for 2D gel electrophoresis in a high-throughput proteomics pipeline.

PubMed

Dowsey, Andrew W; Dunn, Michael J; Yang, Guang-Zhong

2008-04-01

The quest for high-throughput proteomics has revealed a number of challenges in recent years. Whilst substantial improvements in automated protein separation with liquid chromatography and mass spectrometry (LC/MS), aka 'shotgun' proteomics, have been achieved, large-scale open initiatives such as the Human Proteome Organization (HUPO) Brain Proteome Project have shown that maximal proteome coverage is only possible when LC/MS is complemented by 2D gel electrophoresis (2-DE) studies. Moreover, both separation methods require automated alignment and differential analysis to relieve the bioinformatics bottleneck and so make high-throughput protein biomarker discovery a reality. The purpose of this article is to describe a fully automatic image alignment framework for the integration of 2-DE into a high-throughput differential expression proteomics pipeline. The proposed method is based on robust automated image normalization (RAIN) to circumvent the drawbacks of traditional approaches. These use symbolic representation at the very early stages of the analysis, which introduces persistent errors due to inaccuracies in modelling and alignment. In RAIN, a third-order volume-invariant B-spline model is incorporated into a multi-resolution schema to correct for geometric and expression inhomogeneity at multiple scales. The normalized images can then be compared directly in the image domain for quantitative differential analysis. Through evaluation against an existing state-of-the-art method on real and synthetically warped 2D gels, the proposed analysis framework demonstrates substantial improvements in matching accuracy and differential sensitivity. High-throughput analysis is established through an accelerated GPGPU (general purpose computation on graphics cards) implementation. Supplementary material, software and images used in the validation are available at http://www.proteomegrid.org/rain/.

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.

Proteomic analysis of tissue samples in translational breast cancer research.

PubMed

Gromov, Pavel; Moreira, José M A; Gromova, Irina

2014-06-01

In the last decade, many proteomic technologies have been applied, with varying success, to the study of tissue samples of breast carcinoma for protein expression profiling in order to discover protein biomarkers/signatures suitable for: characterization and subtyping of tumors; early diagnosis, and both prognosis and prediction of outcome of chemotherapy. The purpose of this review is to critically appraise what has been achieved to date using proteomic technologies and to bring forward novel strategies - based on the analysis of clinically relevant samples - that promise to accelerate the translation of basic discoveries into the daily breast cancer clinical practice. In particular, we address major issues in experimental design by reviewing the strengths and weaknesses of current proteomic strategies in the context of the analysis of human breast tissue specimens.

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

PubMed

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

2014-01-01

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

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

Comparative analysis of inflamed and non-inflamed colon biopsies reveals strong proteomic inflammation profile in patients with ulcerative colitis

PubMed Central

2012-01-01

Background Accurate diagnostic and monitoring tools for ulcerative colitis (UC) are missing. Our aim was to describe the proteomic profile of UC and search for markers associated with disease exacerbation. Therefore, we aimed to characterize specific proteins associated with inflamed colon mucosa from patients with acute UC using mass spectrometry-based proteomic analysis. Methods Biopsies were sampled from rectum, sigmoid colon and left colonic flexure from twenty patients with active proctosigmoiditis and from four healthy controls for proteomics and histology. Proteomic profiles of whole colonic biopsies were characterized using 2D-gel electrophoresis, and peptide mass fingerprinting using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was applied for identification of differently expressed protein spots. Results A total of 597 spots were annotated by image analysis and 222 of these had a statistically different protein level between inflamed and non-inflamed tissue in the patient group. Principal component analysis clearly grouped non-inflamed samples separately from the inflamed samples indicating that the proteomic signature of colon mucosa with acute UC is strong. Totally, 43 individual protein spots were identified, including proteins involved in energy metabolism (triosephosphate isomerase, glycerol-3-phosphate-dehydrogenase, alpha enolase and L-lactate dehydrogenase B-chain) and in oxidative stress (superoxide dismutase, thioredoxins and selenium binding protein). Conclusions A distinct proteomic profile of inflamed tissue in UC patients was found. Specific proteins involved in energy metabolism and oxidative stress were identified as potential candidate markers for UC. PMID:22726388

Missing continuous outcomes under covariate dependent missingness in cluster randomised trials

PubMed Central

Diaz-Ordaz, Karla; Bartlett, Jonathan W

2016-01-01

Attrition is a common occurrence in cluster randomised trials which leads to missing outcome data. Two approaches for analysing such trials are cluster-level analysis and individual-level analysis. This paper compares the performance of unadjusted cluster-level analysis, baseline covariate adjusted cluster-level analysis and linear mixed model analysis, under baseline covariate dependent missingness in continuous outcomes, in terms of bias, average estimated standard error and coverage probability. The methods of complete records analysis and multiple imputation are used to handle the missing outcome data. We considered four scenarios, with the missingness mechanism and baseline covariate effect on outcome either the same or different between intervention groups. We show that both unadjusted cluster-level analysis and baseline covariate adjusted cluster-level analysis give unbiased estimates of the intervention effect only if both intervention groups have the same missingness mechanisms and there is no interaction between baseline covariate and intervention group. Linear mixed model and multiple imputation give unbiased estimates under all four considered scenarios, provided that an interaction of intervention and baseline covariate is included in the model when appropriate. Cluster mean imputation has been proposed as a valid approach for handling missing outcomes in cluster randomised trials. We show that cluster mean imputation only gives unbiased estimates when missingness mechanism is the same between the intervention groups and there is no interaction between baseline covariate and intervention group. Multiple imputation shows overcoverage for small number of clusters in each intervention group. PMID:27177885

Missing continuous outcomes under covariate dependent missingness in cluster randomised trials.

PubMed

Hossain, Anower; Diaz-Ordaz, Karla; Bartlett, Jonathan W

2017-06-01

Attrition is a common occurrence in cluster randomised trials which leads to missing outcome data. Two approaches for analysing such trials are cluster-level analysis and individual-level analysis. This paper compares the performance of unadjusted cluster-level analysis, baseline covariate adjusted cluster-level analysis and linear mixed model analysis, under baseline covariate dependent missingness in continuous outcomes, in terms of bias, average estimated standard error and coverage probability. The methods of complete records analysis and multiple imputation are used to handle the missing outcome data. We considered four scenarios, with the missingness mechanism and baseline covariate effect on outcome either the same or different between intervention groups. We show that both unadjusted cluster-level analysis and baseline covariate adjusted cluster-level analysis give unbiased estimates of the intervention effect only if both intervention groups have the same missingness mechanisms and there is no interaction between baseline covariate and intervention group. Linear mixed model and multiple imputation give unbiased estimates under all four considered scenarios, provided that an interaction of intervention and baseline covariate is included in the model when appropriate. Cluster mean imputation has been proposed as a valid approach for handling missing outcomes in cluster randomised trials. We show that cluster mean imputation only gives unbiased estimates when missingness mechanism is the same between the intervention groups and there is no interaction between baseline covariate and intervention group. Multiple imputation shows overcoverage for small number of clusters in each intervention group.

Combining proteomics and metabolite analyses to unravel cadmium stress-response in poplar leaves.

PubMed

Kieffer, Pol; Planchon, Sébastien; Oufir, Mouhssin; Ziebel, Johanna; Dommes, Jacques; Hoffmann, Lucien; Hausman, Jean-François; Renaut, Jenny

2009-01-01

A proteomic analysis of poplar leaves exposed to cadmium, combined with biochemical analysis of pigments and carbohydrates revealed changes in primary carbon metabolism. Proteomic results suggested that photosynthesis was slightly affected. Together with a growth inhibition, photoassimilates were less needed for developmental processes and could be stored in the form of hexoses or complex sugars, acting also as osmoprotectants. Simultaneously, mitochondrial respiration was upregulated, providing energy needs of cadmium-exposed plants.

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

A Comprehensive Guide for Performing Sample Preparation and Top-Down Protein Analysis

PubMed Central

Padula, Matthew P.; Berry, Iain J.; O′Rourke, Matthew B.; Raymond, Benjamin B.A.; Santos, Jerran; Djordjevic, Steven P.

2017-01-01

Methodologies for the global analysis of proteins in a sample, or proteome analysis, have been available since 1975 when Patrick O′Farrell published the first paper describing two-dimensional gel electrophoresis (2D-PAGE). This technique allowed the resolution of single protein isoforms, or proteoforms, into single ‘spots’ in a polyacrylamide gel, allowing the quantitation of changes in a proteoform′s abundance to ascertain changes in an organism′s phenotype when conditions change. In pursuit of the comprehensive profiling of the proteome, significant advances in technology have made the identification and quantitation of intact proteoforms from complex mixtures of proteins more routine, allowing analysis of the proteome from the ‘Top-Down’. However, the number of proteoforms detected by Top-Down methodologies such as 2D-PAGE or mass spectrometry has not significantly increased since O’Farrell’s paper when compared to Bottom-Up, peptide-centric techniques. This article explores and explains the numerous methodologies and technologies available to analyse the proteome from the Top-Down with a strong emphasis on the necessity to analyse intact proteoforms as a better indicator of changes in biology and phenotype. We arrive at the conclusion that the complete and comprehensive profiling of an organism′s proteome is still, at present, beyond our reach but the continuing evolution of protein fractionation techniques and mass spectrometry brings comprehensive Top-Down proteome profiling closer. PMID:28387712

A Comprehensive Guide for Performing Sample Preparation and Top-Down Protein Analysis.

PubMed

Padula, Matthew P; Berry, Iain J; O Rourke, Matthew B; Raymond, Benjamin B A; Santos, Jerran; Djordjevic, Steven P

2017-04-07

Methodologies for the global analysis of proteins in a sample, or proteome analysis, have been available since 1975 when Patrick O'Farrell published the first paper describing two-dimensional gel electrophoresis (2D-PAGE). This technique allowed the resolution of single protein isoforms, or proteoforms, into single 'spots' in a polyacrylamide gel, allowing the quantitation of changes in a proteoform's abundance to ascertain changes in an organism's phenotype when conditions change. In pursuit of the comprehensive profiling of the proteome, significant advances in technology have made the identification and quantitation of intact proteoforms from complex mixtures of proteins more routine, allowing analysis of the proteome from the 'Top-Down'. However, the number of proteoforms detected by Top-Down methodologies such as 2D-PAGE or mass spectrometry has not significantly increased since O'Farrell's paper when compared to Bottom-Up, peptide-centric techniques. This article explores and explains the numerous methodologies and technologies available to analyse the proteome from the Top-Down with a strong emphasis on the necessity to analyse intact proteoforms as a better indicator of changes in biology and phenotype. We arrive at the conclusion that the complete and comprehensive profiling of an organism's proteome is still, at present, beyond our reach but the continuing evolution of protein fractionation techniques and mass spectrometry brings comprehensive Top-Down proteome profiling closer.

Processing Shotgun Proteomics Data on the Amazon Cloud with the Trans-Proteomic Pipeline*

PubMed Central

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

2015-01-01

Cloud computing, where scalable, on-demand compute cycles and storage are available as a service, has the potential to accelerate mass spectrometry-based proteomics research by providing simple, expandable, and affordable large-scale computing to all laboratories regardless of location or information technology expertise. We present new cloud computing functionality for the Trans-Proteomic Pipeline, a free and open-source suite of tools for the processing and analysis of tandem mass spectrometry datasets. Enabled with Amazon Web Services cloud computing, the Trans-Proteomic Pipeline now accesses large scale computing resources, limited only by the available Amazon Web Services infrastructure, for all users. The Trans-Proteomic Pipeline runs in an environment fully hosted on Amazon Web Services, where all software and data reside on cloud resources to tackle large search studies. In addition, it can also be run on a local computer with computationally intensive tasks launched onto the Amazon Elastic Compute Cloud service to greatly decrease analysis times. We describe the new Trans-Proteomic Pipeline cloud service components, compare the relative performance and costs of various Elastic Compute Cloud service instance types, and present on-line tutorials that enable users to learn how to deploy cloud computing technology rapidly with the Trans-Proteomic Pipeline. We provide tools for estimating the necessary computing resources and costs given the scale of a job and demonstrate the use of cloud enabled Trans-Proteomic Pipeline by performing over 1100 tandem mass spectrometry files through four proteomic search engines in 9 h and at a very low cost. PMID:25418363

Processing shotgun proteomics data on the Amazon cloud with the trans-proteomic pipeline.

PubMed

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

2015-02-01

Cloud computing, where scalable, on-demand compute cycles and storage are available as a service, has the potential to accelerate mass spectrometry-based proteomics research by providing simple, expandable, and affordable large-scale computing to all laboratories regardless of location or information technology expertise. We present new cloud computing functionality for the Trans-Proteomic Pipeline, a free and open-source suite of tools for the processing and analysis of tandem mass spectrometry datasets. Enabled with Amazon Web Services cloud computing, the Trans-Proteomic Pipeline now accesses large scale computing resources, limited only by the available Amazon Web Services infrastructure, for all users. The Trans-Proteomic Pipeline runs in an environment fully hosted on Amazon Web Services, where all software and data reside on cloud resources to tackle large search studies. In addition, it can also be run on a local computer with computationally intensive tasks launched onto the Amazon Elastic Compute Cloud service to greatly decrease analysis times. We describe the new Trans-Proteomic Pipeline cloud service components, compare the relative performance and costs of various Elastic Compute Cloud service instance types, and present on-line tutorials that enable users to learn how to deploy cloud computing technology rapidly with the Trans-Proteomic Pipeline. We provide tools for estimating the necessary computing resources and costs given the scale of a job and demonstrate the use of cloud enabled Trans-Proteomic Pipeline by performing over 1100 tandem mass spectrometry files through four proteomic search engines in 9 h and at a very low cost. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Translational plant proteomics: a perspective.

PubMed

Agrawal, Ganesh Kumar; Pedreschi, Romina; Barkla, Bronwyn J; Bindschedler, Laurence Veronique; Cramer, Rainer; Sarkar, Abhijit; Renaut, Jenny; Job, Dominique; Rakwal, Randeep

2012-08-03

Translational proteomics is an emerging sub-discipline of the proteomics field in the biological sciences. Translational plant proteomics aims to integrate knowledge from basic sciences to translate it into field applications to solve issues related but not limited to the recreational and economic values of plants, food security and safety, and energy sustainability. In this review, we highlight the substantial progress reached in plant proteomics during the past decade which has paved the way for translational plant proteomics. Increasing proteomics knowledge in plants is not limited to model and non-model plants, proteogenomics, crop improvement, and food analysis, safety, and nutrition but to many more potential applications. Given the wealth of information generated and to some extent applied, there is the need for more efficient and broader channels to freely disseminate the information to the scientific community. This article is part of a Special Issue entitled: Translational Proteomics. Copyright © 2012 Elsevier B.V. All rights reserved.

Biochemical and genetic analysis of the yeast proteome with a movable ORF collection

PubMed Central

Gelperin, Daniel M.; White, Michael A.; Wilkinson, Martha L.; Kon, Yoshiko; Kung, Li A.; Wise, Kevin J.; Lopez-Hoyo, Nelson; Jiang, Lixia; Piccirillo, Stacy; Yu, Haiyuan; Gerstein, Mark; Dumont, Mark E.; Phizicky, Eric M.; Snyder, Michael; Grayhack, Elizabeth J.

2005-01-01

Functional analysis of the proteome is an essential part of genomic research. To facilitate different proteomic approaches, a MORF (moveable ORF) library of 5854 yeast expression plasmids was constructed, each expressing a sequence-verified ORF as a C-terminal ORF fusion protein, under regulated control. Analysis of 5573 MORFs demonstrates that nearly all verified ORFs are expressed, suggests the authenticity of 48 ORFs characterized as dubious, and implicates specific processes including cytoskeletal organization and transcriptional control in growth inhibition caused by overexpression. Global analysis of glycosylated proteins identifies 109 new confirmed N-linked and 345 candidate glycoproteins, nearly doubling the known yeast glycome. PMID:16322557

Mass spectrometry based proteomics profiling as diagnostic tool in oncology: current status and future perspective.

PubMed

Findeisen, Peter; Neumaier, Michael

2009-01-01

Proteomics analysis has been heralded as a novel tool for identifying new and specific biomarkers that may improve diagnosis and monitoring of various disease states. Recent years have brought a number of proteomics profiling technologies. Although proteomics profiling has resulted in the detection of disease-associated differences and modification of proteins, current proteomics technologies display certain limitations that are hampering the introduction of these new technologies into clinical laboratory diagnostics and routine applications. In this review, we summarize current advances in mass spectrometry based biomarker discovery. The promises and challenges of this new technology are discussed with particular emphasis on diagnostic perspectives of mass-spectrometry based proteomics profiling for malignant diseases.

Nanoliter-Scale Oil-Air-Droplet Chip-Based Single Cell Proteomic Analysis.

PubMed

Li, Zi-Yi; Huang, Min; Wang, Xiu-Kun; Zhu, Ying; Li, Jin-Song; Wong, Catherine C L; Fang, Qun

2018-04-17

Single cell proteomic analysis provides crucial information on cellular heterogeneity in biological systems. Herein, we describe a nanoliter-scale oil-air-droplet (OAD) chip for achieving multistep complex sample pretreatment and injection for single cell proteomic analysis in the shotgun mode. By using miniaturized stationary droplet microreaction and manipulation techniques, our system allows all sample pretreatment and injection procedures to be performed in a nanoliter-scale droplet with minimum sample loss and a high sample injection efficiency (>99%), thus substantially increasing the analytical sensitivity for single cell samples. We applied the present system in the proteomic analysis of 100 ± 10, 50 ± 5, 10, and 1 HeLa cell(s), and protein IDs of 1360, 612, 192, and 51 were identified, respectively. The OAD chip-based system was further applied in single mouse oocyte analysis, with 355 protein IDs identified at the single oocyte level, which demonstrated its special advantages of high enrichment of sequence coverage, hydrophobic proteins, and enzymatic digestion efficiency over the traditional in-tube system.

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.

Affinity Proteomics in the mountains: Alpbach 2015.

PubMed

Taussig, Michael J

2016-09-25

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

Sherlock Holmes and the proteome--a detective story.

PubMed

Righetti, Pier Giorgio; Boschetti, Egisto

2007-02-01

The performance of a hexapeptide ligand library in capturing the 'hidden proteome' is illustrated and evaluated. This library, insolubilized on an organic polymer and available under the trade name 'Equalizer Bead Technology', acts by capturing all components of a given proteome, by concentrating rare and very rare proteins, and simultaneously diluting the abundant ones. This results in a proteome of 'normalized' relative abundances, amenable to analysis by MS and any other analytical tool. Examples are given of analysis of human urine and serum, as well as cell and tissue lysates, such as Escherichia coli and Saccharomyces cerevisiae extracts. Another important application is impurity tracking and polishing of recombinant DNA products, especially biopharmaceuticals meant for human consumption.

Comparison of methods for profiling O-glycosylation: Human Proteome Organisation Human Disease Glycomics/Proteome Initiative multi-institutional study of IgA1.

PubMed

Wada, Yoshinao; Dell, Anne; Haslam, Stuart M; Tissot, Bérangère; Canis, Kévin; Azadi, Parastoo; Bäckström, Malin; Costello, Catherine E; Hansson, Gunnar C; Hiki, Yoshiyuki; Ishihara, Mayumi; Ito, Hiromi; Kakehi, Kazuaki; Karlsson, Niclas; Hayes, Catherine E; Kato, Koichi; Kawasaki, Nana; Khoo, Kay-Hooi; Kobayashi, Kunihiko; Kolarich, Daniel; Kondo, Akihiro; Lebrilla, Carlito; Nakano, Miyako; Narimatsu, Hisashi; Novak, Jan; Novotny, Milos V; Ohno, Erina; Packer, Nicolle H; Palaima, Elizabeth; Renfrow, Matthew B; Tajiri, Michiko; Thomsson, Kristina A; Yagi, Hirokazu; Yu, Shin-Yi; Taniguchi, Naoyuki

2010-04-01

The Human Proteome Organisation Human Disease Glycomics/Proteome Initiative recently coordinated a multi-institutional study that evaluated methodologies that are widely used for defining the N-glycan content in glycoproteins. The study convincingly endorsed mass spectrometry as the technique of choice for glycomic profiling in the discovery phase of diagnostic research. The present study reports the extension of the Human Disease Glycomics/Proteome Initiative's activities to an assessment of the methodologies currently used for O-glycan analysis. Three samples of IgA1 isolated from the serum of patients with multiple myeloma were distributed to 15 laboratories worldwide for O-glycomics analysis. A variety of mass spectrometric and chromatographic procedures representative of current methodologies were used. Similar to the previous N-glycan study, the results convincingly confirmed the pre-eminent performance of MS for O-glycan profiling. Two general strategies were found to give the most reliable data, namely direct MS analysis of mixtures of permethylated reduced glycans in the positive ion mode and analysis of native reduced glycans in the negative ion mode using LC-MS approaches. In addition, mass spectrometric methodologies to analyze O-glycopeptides were also successful.

Proteomic analysis of three gonad types of swamp eel reveals genes differentially expressed during sex reversal.

PubMed

Sheng, Yue; Zhao, Wei; Song, Ying; Li, Zhigang; Luo, Majing; Lei, Quan; Cheng, Hanhua; Zhou, Rongjia

2015-05-18

A variety of mechanisms are engaged in sex determination in vertebrates. The teleost fish swamp eel undergoes sex reversal naturally and is an ideal model for vertebrate sexual development. However, the importance of proteome-wide scanning for gonad reversal was not previously determined. We report a 2-D electrophoresis analysis of three gonad types of proteomes during sex reversal. MS/MS analysis revealed a group of differentially expressed proteins during ovary to ovotestis to testis transformation. Cbx3 is up-regulated during gonad reversal and is likely to have a role in spermatogenesis. Rab37 is down-regulated during the reversal and is mainly associated with oogenesis. Both Cbx3 and Rab37 are linked up in a protein network. These datasets in gonadal proteomes provide a new resource for further studies in gonadal development.

Analysis of PNGase F-resistant N-glycopeptides using SugarQb for Proteome Discoverer 2.1 reveals cryptic substrate specificities.

PubMed

Stadlmann, Johannes; Hoi, David M; Taubenschmid, Jasmin; Mechtler, Karl; Penninger, Josef M

2018-05-18

SugarQb (www.imba.oeaw.ac.at/sugarqb) is a freely available collection of computational tools for the automated identification of intact glycopeptides from high-resolution HCD MS/MS data-sets in the Proteome Discoverer environment. We report the migration of SugarQb to the latest and free version of Proteome Discoverer 2.1, and apply it to the analysis of PNGase F-resistant N-glycopeptides from mouse embryonic stem cells. The analysis of intact glycopeptides highlights unexpected technical limitations to PNGase F-dependent glycoproteomic workflows at the proteome level, and warrants a critical re-interpretation of seminal data-sets in the context of N-glycosylation-site prediction. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes

PubMed Central

Zhang, Yanling; Zhang, Yong; Adachi, Jun; Olsen, Jesper V.; Shi, Rong; de Souza, Gustavo; Pasini, Erica; Foster, Leonard J.; Macek, Boris; Zougman, Alexandre; Kumar, Chanchal; Wiśniewski, Jacek R.; Jun, Wang; Mann, Matthias

2007-01-01

Mass spectrometry (MS)-based proteomics has become a powerful technology to map the protein composition of organelles, cell types and tissues. In our department, a large-scale effort to map these proteomes is complemented by the Max-Planck Unified (MAPU) proteome database. MAPU contains several body fluid proteomes; including plasma, urine, and cerebrospinal fluid. Cell lines have been mapped to a depth of several thousand proteins and the red blood cell proteome has also been analyzed in depth. The liver proteome is represented with 3200 proteins. By employing high resolution MS and stringent validation criteria, false positive identification rates in MAPU are lower than 1:1000. Thus MAPU datasets can serve as reference proteomes in biomarker discovery. MAPU contains the peptides identifying each protein, measured masses, scores and intensities and is freely available at using a clickable interface of cell or body parts. Proteome data can be queried across proteomes by protein name, accession number, sequence similarity, peptide sequence and annotation information. More than 4500 mouse and 2500 human proteins have already been identified in at least one proteome. Basic annotation information and links to other public databases are provided in MAPU and we plan to add further analysis tools. PMID:17090601

Proteomics of filamentous fungi.

PubMed

Kim, Yonghyun; Nandakumar, M P; Marten, Mark R

2007-09-01

Proteomic analysis, defined here as the global assessment of cellular proteins expressed in a particular biological state, is a powerful tool that can provide a systematic understanding of events at the molecular level. Proteomic studies of filamentous fungi have only recently begun to appear in the literature, despite the prevalence of these organisms in the biotechnology industry, and their importance as both human and plant pathogens. Here, we review recent publications that have used a proteomic approach to develop a better understanding of filamentous fungi, highlighting sample preparation methods and whole-cell cytoplasmic proteomics, as well as subproteomics of cell envelope, mitochondrial and secreted proteins.

Glucose deprivation activates a metabolic and signaling amplification loop leading to cell death

PubMed Central

Graham, Nicholas A; Tahmasian, Martik; Kohli, Bitika; Komisopoulou, Evangelia; Zhu, Maggie; Vivanco, Igor; Teitell, Michael A; Wu, Hong; Ribas, Antoni; Lo, Roger S; Mellinghoff, Ingo K; Mischel, Paul S; Graeber, Thomas G

2012-01-01

The altered metabolism of cancer can render cells dependent on the availability of metabolic substrates for viability. Investigating the signaling mechanisms underlying cell death in cells dependent upon glucose for survival, we demonstrate that glucose withdrawal rapidly induces supra-physiological levels of phospho-tyrosine signaling, even in cells expressing constitutively active tyrosine kinases. Using unbiased mass spectrometry-based phospho-proteomics, we show that glucose withdrawal initiates a unique signature of phospho-tyrosine activation that is associated with focal adhesions. Building upon this observation, we demonstrate that glucose withdrawal activates a positive feedback loop involving generation of reactive oxygen species (ROS) by NADPH oxidase and mitochondria, inhibition of protein tyrosine phosphatases by oxidation, and increased tyrosine kinase signaling. In cells dependent on glucose for survival, glucose withdrawal-induced ROS generation and tyrosine kinase signaling synergize to amplify ROS levels, ultimately resulting in ROS-mediated cell death. Taken together, these findings illustrate the systems-level cross-talk between metabolism and signaling in the maintenance of cancer cell homeostasis. PMID:22735335

A Signaling Network Induced by β2 Integrin Controls the Polarization of Lytic Granulesin Cytotoxic Cells

PubMed Central

Zhang, Minggang; March, Michael E.; Lane, William S.; Long, Eric O.

2014-01-01

Cytotoxic lymphocyte skill target cells by polarized release of the content of perforin-containing granules. In natural killer cells, the binding of β2 integrin to its ligand ICAM-1 is sufficient to promote not only adhesion but also lytic granule polarization. This provided a unique opportunity to study polarization in the absence of degranulation, and β2 integrin signaling independently of inside-out signals from other receptors. Using an unbiased proteomics approach we identified a signaling network centered on an integrin-linked kinase (ILK)–Pyk2–Paxillin core that was required for granule polarization. Downstream of ILK, the highly conserved Cdc42–Par6 signaling pathway that controls cell polarity was activated and required for granule polarization. These results delineate two connected signaling networks induced upon β2 integrin engagement alone, which are integrated to control polarization of the microtubule organizing center and associated lytic granules toward the site of contact with target cells during cellular cytotoxicity. PMID:25292215

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

PubMed Central

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

2017-01-01

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

Inflammatory signaling in human Tuberculosis granulomas is spatially organized

PubMed Central

Marakalala, Mohlopheni J.; Raju, Ravikiran M.; Sharma, Kirti; Zhang, Yanjia J.; Eugenin, Eliseo A.; Prideaux, Brendan; Daudelin, Isaac B.; Chen, Pei-Yu; Booty, Matthew G.; Kim, Jin Hee; Eum, Seok Yong; Via, Laura E.; Behar, Samuel M.; Barry, Clifton E.; Mann, Matthias; Dartois, Véronique; Rubin, Eric J.

2016-01-01

Granulomas are the pathological hallmark of tuberculosis (TB). However, their function and mechanisms of formation remain poorly understood. To understand the role of granulomas in TB, we analyzed the proteomes of granulomas from subjects with tuberculosis in an unbiased fashion. Using laser capture microdissection, mass spectrometry and confocal microscopy, we generated detailed molecular maps of human granulomas. We found that the centers of granulomas possess a pro-inflammatory environment characterized by anti-microbial peptides, ROS and pro-inflammatory eicosanoids. Conversely, the tissue surrounding the caseum possesses a comparatively anti-inflammatory signature. These findings are consistent across a set of six subjects and in rabbits. While the balance between systemic pro- and anti-inflammatory signals is crucial to TB disease outcome, here we find that these signals are physically segregated within each granuloma. The protein and lipid snapshots of human and rabbit lesions analysed here suggest that the pathologic response to TB is shaped by the precise anatomical localization of these inflammatory pathways during the development of the granuloma. PMID:27043495

No evidence for a local renin-angiotensin system in liver mitochondria

PubMed Central

Astin, Ronan; Bentham, Robert; Djafarzadeh, Siamak; Horscroft, James A.; Kuc, Rhoda E.; Leung, Po Sing; Skipworth, James R. A.; Vicencio, Jose M.; Davenport, Anthony P.; Murray, Andrew J.; Takala, Jukka; Jakob, Stephan M.; Montgomery, Hugh; Szabadkai, Gyorgy

2013-01-01

The circulating, endocrine renin-angiotensin system (RAS) is important to circulatory homeostasis, while ubiquitous tissue and cellular RAS play diverse roles, including metabolic regulation. Indeed, inhibition of RAS is associated with improved cellular oxidative capacity. Recently it has been suggested that an intra-mitochondrial RAS directly impacts on metabolism. Here we sought to rigorously explore this hypothesis. Radiolabelled ligand-binding and unbiased proteomic approaches were applied to purified mitochondrial sub-fractions from rat liver, and the impact of AngII on mitochondrial function assessed. Whilst high-affinity AngII binding sites were found in the mitochondria-associated membrane (MAM) fraction, no RAS components could be detected in purified mitochondria. Moreover, AngII had no effect on the function of isolated mitochondria at physiologically relevant concentrations. We thus found no evidence of endogenous mitochondrial AngII production, and conclude that the effects of AngII on cellular energy metabolism are not mediated through its direct binding to mitochondrial targets. PMID:23959064

Comparative Testis Tissue Proteomics Using 2-Dye Versus 3-Dye DIGE Analysis.

PubMed

Holland, Ashling

2018-01-01

Comparative tissue proteomics aims to analyze alterations of the proteome in response to a stimulus. Two-dimensional difference gel electrophoresis (2D-DIGE) is a modified and advanced form of 2D gel electrophoresis. DIGE is a powerful biochemical method that compares two or three protein samples on the same analytical gel, and can be used to establish differentially expressed protein levels between healthy normal and diseased pathological tissue sample groups. Minimal DIGE labeling can be used via a 2-dye system with Cy3 and Cy5 or a 3-dye system with Cy2, Cy3, and Cy5 to fluorescently label samples with CyDye flours pre-electrophoresis. DIGE circumvents gel-to-gel variability by multiplexing samples to a single gel and through the use of a pooled internal standard for normalization. This form of quantitative high-resolution proteomics facilitates the comparative analysis and evaluation of tissue protein compositions. Comparing tissue groups under different conditions is crucially important for advancing the biomedical field by characterization of cellular processes, understanding pathophysiological development and tissue biomarker discovery. This chapter discusses 2D-DIGE as a comparative tissue proteomic technique and describes in detail the experimental steps required for comparative proteomic analysis employing both options of 2-dye and 3-dye DIGE minimal labeling.

Studies of a biochemical factory: tomato trichome deep expressed sequence tag sequencing and proteomics.

PubMed

Schilmiller, Anthony L; Miner, Dennis P; Larson, Matthew; McDowell, Eric; Gang, David R; Wilkerson, Curtis; Last, Robert L

2010-07-01

Shotgun proteomics analysis allows hundreds of proteins to be identified and quantified from a single sample at relatively low cost. Extensive DNA sequence information is a prerequisite for shotgun proteomics, and it is ideal to have sequence for the organism being studied rather than from related species or accessions. While this requirement has limited the set of organisms that are candidates for this approach, next generation sequencing technologies make it feasible to obtain deep DNA sequence coverage from any organism. As part of our studies of specialized (secondary) metabolism in tomato (Solanum lycopersicum) trichomes, 454 sequencing of cDNA was combined with shotgun proteomics analyses to obtain in-depth profiles of genes and proteins expressed in leaf and stem glandular trichomes of 3-week-old plants. The expressed sequence tag and proteomics data sets combined with metabolite analysis led to the discovery and characterization of a sesquiterpene synthase that produces beta-caryophyllene and alpha-humulene from E,E-farnesyl diphosphate in trichomes of leaf but not of stem. This analysis demonstrates the utility of combining high-throughput cDNA sequencing with proteomics experiments in a target tissue. These data can be used for dissection of other biochemical processes in these specialized epidermal cells.

Studies of a Biochemical Factory: Tomato Trichome Deep Expressed Sequence Tag Sequencing and Proteomics1[W][OA

PubMed Central

Schilmiller, Anthony L.; Miner, Dennis P.; Larson, Matthew; McDowell, Eric; Gang, David R.; Wilkerson, Curtis; Last, Robert L.

2010-01-01

Shotgun proteomics analysis allows hundreds of proteins to be identified and quantified from a single sample at relatively low cost. Extensive DNA sequence information is a prerequisite for shotgun proteomics, and it is ideal to have sequence for the organism being studied rather than from related species or accessions. While this requirement has limited the set of organisms that are candidates for this approach, next generation sequencing technologies make it feasible to obtain deep DNA sequence coverage from any organism. As part of our studies of specialized (secondary) metabolism in tomato (Solanum lycopersicum) trichomes, 454 sequencing of cDNA was combined with shotgun proteomics analyses to obtain in-depth profiles of genes and proteins expressed in leaf and stem glandular trichomes of 3-week-old plants. The expressed sequence tag and proteomics data sets combined with metabolite analysis led to the discovery and characterization of a sesquiterpene synthase that produces β-caryophyllene and α-humulene from E,E-farnesyl diphosphate in trichomes of leaf but not of stem. This analysis demonstrates the utility of combining high-throughput cDNA sequencing with proteomics experiments in a target tissue. These data can be used for dissection of other biochemical processes in these specialized epidermal cells. PMID:20431087

Challenges and Strategies for Proteome Analysis of the Interaction of Human Pathogenic Fungi with Host Immune Cells.

PubMed

Krüger, Thomas; Luo, Ting; Schmidt, Hella; Shopova, Iordana; Kniemeyer, Olaf

2015-12-14

Opportunistic human pathogenic fungi including the saprotrophic mold Aspergillus fumigatus and the human commensal Candida albicans can cause severe fungal infections in immunocompromised or critically ill patients. The first line of defense against opportunistic fungal pathogens is the innate immune system. Phagocytes such as macrophages, neutrophils and dendritic cells are an important pillar of the innate immune response and have evolved versatile defense strategies against microbial pathogens. On the other hand, human-pathogenic fungi have sophisticated virulence strategies to counteract the innate immune defense. In this context, proteomic approaches can provide deeper insights into the molecular mechanisms of the interaction of host immune cells with fungal pathogens. This is crucial for the identification of both diagnostic biomarkers for fungal infections and therapeutic targets. Studying host-fungal interactions at the protein level is a challenging endeavor, yet there are few studies that have been undertaken. This review draws attention to proteomic techniques and their application to fungal pathogens and to challenges, difficulties, and limitations that may arise in the course of simultaneous dual proteome analysis of host immune cells interacting with diverse morphotypes of fungal pathogens. On this basis, we discuss strategies to overcome these multifaceted experimental and analytical challenges including the viability of immune cells during co-cultivation, the increased and heterogeneous protein complexity of the host proteome dynamically interacting with the fungal proteome, and the demands on normalization strategies in terms of relative quantitative proteome analysis.

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.

Mutually unbiased product bases for multiple qudits

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

McNulty, Daniel; Pammer, Bogdan; Weigert, Stefan

We investigate the interplay between mutual unbiasedness and product bases for multiple qudits of possibly different dimensions. A product state of such a system is shown to be mutually unbiased to a product basis only if each of its factors is mutually unbiased to all the states which occur in the corresponding factors of the product basis. This result implies both a tight limit on the number of mutually unbiased product bases which the system can support and a complete classification of mutually unbiased product bases for multiple qubits or qutrits. In addition, only maximally entangled states can be mutuallymore » unbiased to a maximal set of mutually unbiased product bases.« less

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.

Transformative Impact of Proteomics on Cardiovascular Health and Disease: A Scientific Statement From the American Heart Association.

PubMed

Lindsey, Merry L; Mayr, Manuel; Gomes, Aldrin V; Delles, Christian; Arrell, D Kent; Murphy, Anne M; Lange, Richard A; Costello, Catherine E; Jin, Yu-Fang; Laskowitz, Daniel T; Sam, Flora; Terzic, Andre; Van Eyk, Jennifer; Srinivas, Pothur R

2015-09-01

The year 2014 marked the 20th anniversary of the coining of the term proteomics. The purpose of this scientific statement is to summarize advances over this period that have catalyzed our capacity to address the experimental, translational, and clinical implications of proteomics as applied to cardiovascular health and disease and to evaluate the current status of the field. Key successes that have energized the field are delineated; opportunities for proteomics to drive basic science research, facilitate clinical translation, and establish diagnostic and therapeutic healthcare algorithms are discussed; and challenges that remain to be solved before proteomic technologies can be readily translated from scientific discoveries to meaningful advances in cardiovascular care are addressed. Proteomics is the result of disruptive technologies, namely, mass spectrometry and database searching, which drove protein analysis from 1 protein at a time to protein mixture analyses that enable large-scale analysis of proteins and facilitate paradigm shifts in biological concepts that address important clinical questions. Over the past 20 years, the field of proteomics has matured, yet it is still developing rapidly. The scope of this statement will extend beyond the reaches of a typical review article and offer guidance on the use of next-generation proteomics for future scientific discovery in the basic research laboratory and clinical settings. © 2015 American Heart Association, Inc.

Identification of Trypanosome Proteins in Plasma from African Sleeping Sickness Patients Infected with T. b. rhodesiense

PubMed Central

Enyaru, John C.; Carr, Steven A.; Pearson, Terry W.

2013-01-01

Control of human African sleeping sickness, caused by subspecies of the protozoan parasite Trypanosoma brucei, is based on preventing transmission by elimination of the tsetse vector and by active diagnostic screening and treatment of infected patients. To identify trypanosome proteins that have potential as biomarkers for detection and monitoring of African sleeping sickness, we have used a ‘deep-mining” proteomics approach to identify trypanosome proteins in human plasma. Abundant human plasma proteins were removed by immunodepletion. Depleted plasma samples were then digested to peptides with trypsin, fractionated by basic reversed phase and each fraction analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). This sample processing and analysis method enabled identification of low levels of trypanosome proteins in pooled plasma from late stage sleeping sickness patients infected with Trypanosoma brucei rhodesiense. A total of 254 trypanosome proteins were confidently identified. Many of the parasite proteins identified were of unknown function, although metabolic enzymes, chaperones, proteases and ubiquitin-related/acting proteins were found. This approach to the identification of conserved, soluble trypanosome proteins in human plasma offers a possible route to improved disease diagnosis and monitoring, since these molecules are potential biomarkers for the development of a new generation of antigen-detection assays. The combined immuno-depletion/mass spectrometric approach can be applied to a variety of infectious diseases for unbiased biomarker identification. PMID:23951171

Mitochondrial “power” drives tamoxifen resistance: NQO1 and GCLC are new therapeutic targets in breast cancer

PubMed Central

Fiorillo, Marco; Sotgia, Federica; Sisci, Diego; Cappello, Anna Rita; Lisanti, Michael P.

2017-01-01

Here, we identified two new molecular targets, which are functionally sufficient to metabolically confer the tamoxifen-resistance phenotype in human breast cancer cells. Briefly, ~20 proteins were first selected as potential candidates, based on unbiased proteomics analysis, using tamoxifen-resistant cell lines. Then, the cDNAs of the most promising candidates were systematically transduced into MCF-7 cells. Remarkably, NQO1 and GCLC were both functionally sufficient to autonomously confer a tamoxifen-resistant metabolic phenotype, characterized by i) increased mitochondrial biogenesis, ii) increased ATP production and iii) reduced glutathione levels. Thus, we speculate that pharmacological inhibition of NQO1 and GCLC may be new therapeutic strategies for overcoming tamoxifen-resistance in breast cancer patients. In direct support of this notion, we demonstrate that treatment with a known NQO1 inhibitor (dicoumarol) is indeed sufficient to revert the tamoxifen-resistance phenotype. As such, these findings could have important translational significance for the prevention of tumor recurrence in ER(+) breast cancers, which is due to an endocrine resistance phenotype. Importantly, we also show here that NQO1 has significant prognostic value as a biomarker for the prediction of tumor recurrence. More specifically, higher levels of NQO1 mRNA strongly predict patient relapse in high-risk ER(+) breast cancer patients receiving endocrine therapy (mostly tamoxifen; H.R. > 2.15; p = 0.007). PMID:28411284

Ketone bodies and two-compartment tumor metabolism

PubMed Central

Martinez-Outschoorn, Ubaldo E.; Lin, Zhao; Whitaker-Menezes, Diana; Howell, Anthony; Lisanti, Michael P.; Sotgia, Federica

2012-01-01

We have previously suggested that ketone body metabolism is critical for tumor progression and metastasis. Here, using a co-culture system employing human breast cancer cells (MCF7) and hTERT-immortalized fibroblasts, we provide new evidence to directly support this hypothesis. More specifically, we show that the enzymes required for ketone body production are highly upregulated within cancer-associated fibroblasts. This appears to be mechanistically controlled by the stromal expression of caveolin-1 (Cav-1) and/or serum starvation. In addition, treatment with ketone bodies (such as 3-hydroxy-butyrate, and/or butanediol) is sufficient to drive mitochondrial biogenesis in human breast cancer cells. This observation was also validated by unbiased proteomic analysis. Interestingly, an MCT1 inhibitor was sufficient to block the onset of mitochondrial biogenesis in human breast cancer cells, suggesting a possible avenue for anticancer therapy. Finally, using human breast cancer tumor samples, we directly confirmed that the enzymes associated with ketone body production (HMGCS2, HMGCL and BDH1) were preferentially expressed in the tumor stroma. Conversely, enzymes associated with ketone re-utilization (ACAT1) and mitochondrial biogenesis (HSP60) were selectively associated with the epithelial tumor cell compartment. Our current findings are consistent with the “two-compartment tumor metabolism” model. Furthermore, they suggest that we should target ketone body metabolism as a new area for drug discovery, for the prevention and treatment of human cancers. PMID:23082721

Identification of Trypanosome proteins in plasma from African sleeping sickness patients infected with T. b. rhodesiense.

PubMed

Eyford, Brett A; Ahmad, Rushdy; Enyaru, John C; Carr, Steven A; Pearson, Terry W

2013-01-01

Control of human African sleeping sickness, caused by subspecies of the protozoan parasite Trypanosoma brucei, is based on preventing transmission by elimination of the tsetse vector and by active diagnostic screening and treatment of infected patients. To identify trypanosome proteins that have potential as biomarkers for detection and monitoring of African sleeping sickness, we have used a 'deep-mining" proteomics approach to identify trypanosome proteins in human plasma. Abundant human plasma proteins were removed by immunodepletion. Depleted plasma samples were then digested to peptides with trypsin, fractionated by basic reversed phase and each fraction analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). This sample processing and analysis method enabled identification of low levels of trypanosome proteins in pooled plasma from late stage sleeping sickness patients infected with Trypanosoma brucei rhodesiense. A total of 254 trypanosome proteins were confidently identified. Many of the parasite proteins identified were of unknown function, although metabolic enzymes, chaperones, proteases and ubiquitin-related/acting proteins were found. This approach to the identification of conserved, soluble trypanosome proteins in human plasma offers a possible route to improved disease diagnosis and monitoring, since these molecules are potential biomarkers for the development of a new generation of antigen-detection assays. The combined immuno-depletion/mass spectrometric approach can be applied to a variety of infectious diseases for unbiased biomarker identification.

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.

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

A comparative proteomic strategy for subcellular proteome research: ICAT approach coupled with bioinformatics prediction to ascertain rat liver mitochondrial proteins and indication of mitochondrial localization for catalase.

PubMed

Jiang, Xiao-Sheng; Dai, Jie; Sheng, Quan-Hu; Zhang, Lei; Xia, Qi-Chang; Wu, Jia-Rui; Zeng, Rong

2005-01-01

Subcellular proteomics, as an important step to functional proteomics, has been a focus in proteomic research. However, the co-purification of "contaminating" proteins has been the major problem in all the subcellular proteomic research including all kinds of mitochondrial proteome research. It is often difficult to conclude whether these "contaminants" represent true endogenous partners or artificial associations induced by cell disruption or incomplete purification. To solve such a problem, we applied a high-throughput comparative proteome experimental strategy, ICAT approach performed with two-dimensional LC-MS/MS analysis, coupled with combinational usage of different bioinformatics tools, to study the proteome of rat liver mitochondria prepared with traditional centrifugation (CM) or further purified with a Nycodenz gradient (PM). A total of 169 proteins were identified and quantified convincingly in the ICAT analysis, in which 90 proteins have an ICAT ratio of PM:CM>1.0, while another 79 proteins have an ICAT ratio of PM:CM<1.0. Almost all the proteins annotated as mitochondrial according to Swiss-Prot annotation, bioinformatics prediction, and literature reports have a ratio of PM:CM>1.0, while proteins annotated as extracellular or secreted, cytoplasmic, endoplasmic reticulum, ribosomal, and so on have a ratio of PM:CM<1.0. Catalase and AP endonuclease 1, which have been known as peroxisomal and nuclear, respectively, have shown a ratio of PM:CM>1.0, confirming the reports about their mitochondrial location. Moreover, the 125 proteins with subcellular location annotation have been used as a testing dataset to evaluate the efficiency for ascertaining mitochondrial proteins by ICAT analysis and the bioinformatics tools such as PSORT, TargetP, SubLoc, MitoProt, and Predotar. The results indicated that ICAT analysis coupled with combinational usage of different bioinformatics tools could effectively ascertain mitochondrial proteins and distinguish contaminant proteins and even multilocation proteins. Using such a strategy, many novel proteins, known proteins without subcellular location annotation, and even known proteins that have been annotated as other locations have been strongly indicated for their mitochondrial location.

Proteome dynamics of cold-acclimating Rhododendron species contrasting in their freezing tolerance and thermonasty response

USDA-ARS?s Scientific Manuscript database

In the present study we used 2D-DIGE technique to document the Rhododendron proteome during the seasonal development of cold hardiness. We selected two genotypes with different cold hardiness levels. This enabled us to perform comparative analysis of their proteome profiles and screen differentially...

Quantum key distribution for composite dimensional finite systems

NASA Astrophysics Data System (ADS)

Shalaby, Mohamed; Kamal, Yasser

2017-06-01

The application of quantum mechanics contributes to the field of cryptography with very important advantage as it offers a mechanism for detecting the eavesdropper. The pioneering work of quantum key distribution uses mutually unbiased bases (MUBs) to prepare and measure qubits (or qudits). Weak mutually unbiased bases (WMUBs) have weaker properties than MUBs properties, however, unlike MUBs, a complete set of WMUBs can be constructed for systems with composite dimensions. In this paper, we study the use of weak mutually unbiased bases (WMUBs) in quantum key distribution for composite dimensional finite systems. We prove that the security analysis of using a complete set of WMUBs to prepare and measure the quantum states in the generalized BB84 protocol, gives better results than using the maximum number of MUBs that can be constructed, when they are analyzed against the intercept and resend attack.

Proteomics of Skin Proteins in Psoriasis: From Discovery and Verification in a Mouse Model to Confirmation in Humans*

PubMed Central

Lundberg, Kathleen C.; Fritz, Yi; Johnston, Andrew; Foster, Alexander M.; Baliwag, Jaymie; Gudjonsson, Johann E.; Schlatzer, Daniela; Gokulrangan, Giridharan; McCormick, Thomas S.; Chance, Mark R.; Ward, Nicole L.

2015-01-01

Herein, we demonstrate the efficacy of an unbiased proteomics screening approach for studying protein expression changes in the KC-Tie2 psoriasis mouse model, identifying multiple protein expression changes in the mouse and validating these changes in human psoriasis. KC-Tie2 mouse skin samples (n = 3) were compared with littermate controls (n = 3) using gel-based fractionation followed by label-free protein expression analysis. 5482 peptides mapping to 1281 proteins were identified and quantitated: 105 proteins exhibited fold-changes ≥2.0 including: stefin A1 (average fold change of 342.4 and an average p = 0.0082; cystatin A, human ortholog); slc25a5 (average fold change of 46.2 and an average p = 0.0318); serpinb3b (average fold change of 35.6 and an average p = 0.0345; serpinB1, human ortholog); and kallikrein related peptidase 6 (average fold change of 4.7 and an average p = 0.2474; KLK6). We independently confirmed mouse gene expression-based increases of selected genes including serpinb3b (17.4-fold, p < 0.0001), KLK6 (9-fold, p = 0.002), stefin A1 (7.3-fold; p < 0.001), and slc25A5 (1.5-fold; p = 0.05) using qRT-PCR on a second cohort of animals (n = 8). Parallel LC/MS/MS analyses on these same samples verified protein-level increases of 1.3-fold (slc25a5; p < 0.05), 29,000-fold (stefinA1; p < 0.01), 322-fold (KLK6; p < 0.0001) between KC-Tie2 and control mice. To underscore the utility and translatability of our combined approach, we analyzed gene and protein expression levels in psoriasis patient skin and primary keratinocytes versus healthy controls. Increases in gene expression for slc25a5 (1.8-fold), cystatin A (3-fold), KLK6 (5.8-fold), and serpinB1 (76-fold; all p < 0.05) were observed between healthy controls and involved lesional psoriasis skin and primary psoriasis keratinocytes. Moreover, slc25a5, cystatin A, KLK6, and serpinB1 protein were all increased in lesional psoriasis skin compared with normal skin. These results highlight the usefulness of preclinical disease models using readily-available mouse skin and demonstrate the utility of proteomic approaches for identifying novel peptides/proteins that are differentially regulated in psoriasis that could serve as sources of auto-antigens or provide novel therapeutic targets for the development of new anti-psoriatic treatments. PMID:25351201

Complex and extensive post-transcriptional regulation revealed by integrative proteomic and transcriptomic analysis of metabolite stress response in Clostridium acetobutylicum.

PubMed

Venkataramanan, Keerthi P; Min, Lie; Hou, Shuyu; Jones, Shawn W; Ralston, Matthew T; Lee, Kelvin H; Papoutsakis, E Terry

2015-01-01

Clostridium acetobutylicum is a model organism for both clostridial biology and solvent production. The organism is exposed to its own toxic metabolites butyrate and butanol, which trigger an adaptive stress response. Integrative analysis of proteomic and RNAseq data may provide novel insights into post-transcriptional regulation. The identified iTRAQ-based quantitative stress proteome is made up of 616 proteins with a 15 % genome coverage. The differentially expressed proteome correlated poorly with the corresponding differential RNAseq transcriptome. Up to 31 % of the differentially expressed proteins under stress displayed patterns opposite to those of the transcriptome, thus suggesting significant post-transcriptional regulation. The differential proteome of the translation machinery suggests that cells employ a different subset of ribosomal proteins under stress. Several highly upregulated proteins but with low mRNA levels possessed mRNAs with long 5'UTRs and strong RBS scores, thus supporting the argument that regulatory elements on the long 5'UTRs control their translation. For example, the oxidative stress response rubrerythrin was upregulated only at the protein level up to 40-fold without significant mRNA changes. We also identified many leaderless transcripts, several displaying different transcriptional start sites, thus suggesting mRNA-trimming mechanisms under stress. Downregulation of Rho and partner proteins pointed to changes in transcriptional elongation and termination under stress. The integrative proteomic-transcriptomic analysis demonstrated complex expression patterns of a large fraction of the proteome. Such patterns could not have been detected with one or the other omic analyses. Our analysis proposes the involvement of specific molecular mechanisms of post-transcriptional regulation to explain the observed complex stress response.

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

Two independent proteomic approaches provide a comprehensive analysis of the synovial fluid proteome response to Autologous Chondrocyte Implantation.

PubMed

Hulme, Charlotte H; Wilson, Emma L; Fuller, Heidi R; Roberts, Sally; Richardson, James B; Gallacher, Pete; Peffers, Mandy J; Shirran, Sally L; Botting, Catherine H; Wright, Karina T

2018-05-02

Autologous chondrocyte implantation (ACI) has a failure rate of approximately 20%, but it is yet to be fully understood why. Biomarkers are needed that can pre-operatively predict in which patients it is likely to fail, so that alternative or individualised therapies can be offered. We previously used label-free quantitation (LF) with a dynamic range compression proteomic approach to assess the synovial fluid (SF) of ACI responders and non-responders. However, we were able to identify only a few differentially abundant proteins at baseline. In the present study, we built upon these previous findings by assessing higher-abundance proteins within this SF, providing a more global proteomic analysis on the basis of which more of the biology underlying ACI success or failure can be understood. Isobaric tagging for relative and absolute quantitation (iTRAQ) proteomic analysis was used to assess SF from ACI responders (mean Lysholm improvement of 33; n = 14) and non-responders (mean Lysholm decrease of 14; n = 13) at the two stages of surgery (cartilage harvest and chondrocyte implantation). Differentially abundant proteins in iTRAQ and combined iTRAQ and LF datasets were investigated using pathway and network analyses. iTRAQ proteomic analysis confirmed our previous finding that there is a marked proteomic shift in response to cartilage harvest (70 and 54 proteins demonstrating ≥ 2.0-fold change and p < 0.05 between stages I and II in responders and non-responders, respectively). Further, it highlighted 28 proteins that were differentially abundant between responders and non-responders to ACI, which were not found in the LF study, 16 of which were altered at baseline. The differential expression of two proteins (complement C1s subcomponent and matrix metalloproteinase 3) was confirmed biochemically. Combination of the iTRAQ and LF proteomic datasets generated in-depth SF proteome information that was used to generate interactome networks representing ACI success or failure. Functional pathways that are dysregulated in ACI non-responders were identified, including acute-phase response signalling. Several candidate biomarkers for baseline prediction of ACI outcome were identified. A holistic overview of the SF proteome in responders and non-responders to ACI  has been profiled, providing a better understanding of the biological pathways underlying clinical outcome, particularly the differential response to cartilage harvest in non-responders.

Time-resolved Global and Chromatin Proteomics during Herpes Simplex Virus Type 1 (HSV-1) Infection*

PubMed Central

Kulej, Katarzyna; Avgousti, Daphne C.; Sidoli, Simone; Herrmann, Christin; Della Fera, Ashley N.; Kim, Eui Tae; Garcia, Benjamin A.; Weitzman, Matthew D.

2017-01-01

Herpes simplex virus (HSV-1) lytic infection results in global changes to the host cell proteome and the proteins associated with host chromatin. We present a system level characterization of proteome dynamics during infection by performing a multi-dimensional analysis during HSV-1 lytic infection of human foreskin fibroblast (HFF) cells. Our study includes identification and quantification of the host and viral proteomes, phosphoproteomes, chromatin bound proteomes and post-translational modifications (PTMs) on cellular histones during infection. We analyzed proteomes across six time points of virus infection (0, 3, 6, 9, 12 and 15 h post-infection) and clustered trends in abundance using fuzzy c-means. Globally, we accurately quantified more than 4000 proteins, 200 differently modified histone peptides and 9000 phosphorylation sites on cellular proteins. In addition, we identified 67 viral proteins and quantified 571 phosphorylation events (465 with high confidence site localization) on viral proteins, which is currently the most comprehensive map of HSV-1 phosphoproteome. We investigated chromatin bound proteins by proteomic analysis of the high-salt chromatin fraction and identified 510 proteins that were significantly different in abundance during infection. We found 53 histone marks significantly regulated during virus infection, including a steady increase of histone H3 acetylation (H3K9ac and H3K14ac). Our data provide a resource of unprecedented depth for human and viral proteome dynamics during infection. Collectively, our results indicate that the proteome composition of the chromatin of HFF cells is highly affected during HSV-1 infection, and that phosphorylation events are abundant on viral proteins. We propose that our epi-proteomics approach will prove to be important in the characterization of other model infectious systems that involve changes to chromatin composition. PMID:28179408

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

PubMed

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

2017-09-01

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

Comprehensive Proteomic Analysis of Human Milk-derived Extracellular Vesicles Unveils a Novel Functional Proteome Distinct from Other Milk Components*

PubMed Central

van Herwijnen, Martijn J.C.; Zonneveld, Marijke I.; Goerdayal, Soenita; Nolte – 't Hoen, Esther N.M.; Garssen, Johan; Stahl, Bernd; Maarten Altelaar, A.F.; Redegeld, Frank A.; Wauben, Marca H.M.

2016-01-01

Breast milk contains several macromolecular components with distinctive functions, whereby milk fat globules and casein micelles mainly provide nutrition to the newborn, and whey contains molecules that can stimulate the newborn's developing immune system and gastrointestinal tract. Although extracellular vesicles (EV) have been identified in breast milk, their physiological function and composition has not been addressed in detail. EV are submicron sized vehicles released by cells for intercellular communication via selectively incorporated lipids, nucleic acids, and proteins. Because of the difficulty in separating EV from other milk components, an in-depth analysis of the proteome of human milk-derived EV is lacking. In this study, an extensive LC-MS/MS proteomic analysis was performed of EV that had been purified from breast milk of seven individual donors using a recently established, optimized density-gradient-based EV isolation protocol. A total of 1963 proteins were identified in milk-derived EV, including EV-associated proteins like CD9, Annexin A5, and Flotillin-1, with a remarkable overlap between the different donors. Interestingly, 198 of the identified proteins are not present in the human EV database Vesiclepedia, indicating that milk-derived EV harbor proteins not yet identified in EV of different origin. Similarly, the proteome of milk-derived EV was compared with that of other milk components. For this, data from 38 published milk proteomic studies were combined in order to construct the total milk proteome, which consists of 2698 unique proteins. Remarkably, 633 proteins identified in milk-derived EV have not yet been identified in human milk to date. Interestingly, these novel proteins include proteins involved in regulation of cell growth and controlling inflammatory signaling pathways, suggesting that milk-derived EVs could support the newborn's developing gastrointestinal tract and immune system. Overall, this study provides an expansion of the whole milk proteome and illustrates that milk-derived EV are macromolecular components with a unique functional proteome. PMID:27601599

Proteomic analysis of single mammalian cells enabled by microfluidic nanodroplet sample preparation and ultrasensitive nanoLC-MS.

PubMed

Zhu, Ying; Clair, Geremy; Chrisler, William; Shen, Yufeng; Zhao, Rui; Shukla, Anil; Moore, Ronald; Misra, Ravi; Pryhuber, Gloria; Smith, Richard; Ansong, Charles; Kelly, Ryan T

2018-05-24

We report on the quantitative proteomic analysis of single mammalian cells. Fluorescence-activated cell sorting was employed to deposit cells into a newly developed nanodroplet sample processing chip, after which samples were analysed by ultrasensitive nanoLC-MS. An average of ~670 protein groups were confidently identified from single HeLa cells, which is a far greater level of proteome coverage for single cells than has been previously reported. We demonstrate that the single cell proteomics platform can be used to differentiate cell types from enzyme-dissociated human lung primary cells and identify specific protein markers for epithelial and mesenchymal cells. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomic approaches and their application to plant gravitropism.

PubMed

Basu, Proma; Luesse, Darron R; Wyatt, Sarah E

2015-01-01

Proteomics is a powerful technique that allows researchers a window into how an organism responds to a mutation, a specific environment, or at a distinct point during development by quantifying relative protein abundance and posttranslational modifications. Here, we describe methods for the proteomic analysis of Arabidopsis thaliana tissue. Extraction protocols are provided for isolation of soluble, plasma membrane, and tonoplast proteins. In addition, basic analysis and quality metrics for MS/MS data are discussed. The protocols outlined have the potential to unlock new avenues of research that are not possible through basic genetics or transcriptomic approaches. By combining proteomic information with known gene regulatory patterns, researchers can gain a complete picture of how molecular pathways, such as those required for gravitropism, are initiated, regulated, and terminated.

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

Cancer.gov

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

GENOMIC AND PROTEOMIC ANALYSIS OF SURROGATE TISSUES FOR ASSESSING TOXIC EXPOSURES AND DISEASE STATES

EPA Science Inventory

Genomic and Proteomic Analysis of Surrogate Tissues for Assessing Toxic Exposures and Disease States
David J. Dix and John C. Rockett
Reproductive Toxicology Division, National Health and Environmental Effects Research Laboratory, Office of Research and Development, USEPA, ...

Proteomic analysis of cell cycle progression in asynchronous cultures, including mitotic subphases, using PRIMMUS

PubMed Central

Whigham, Arlene; Clarke, Rosemary; Brenes-Murillo, Alejandro J; Estes, Brett; Madhessian, Diana; Lundberg, Emma; Wadsworth, Patricia

2017-01-01

The temporal regulation of protein abundance and post-translational modifications is a key feature of cell division. Recently, we analysed gene expression and protein abundance changes during interphase under minimally perturbed conditions (Ly et al., 2014, 2015). Here, we show that by using specific intracellular immunolabelling protocols, FACS separation of interphase and mitotic cells, including mitotic subphases, can be combined with proteomic analysis by mass spectrometry. Using this PRIMMUS (PRoteomic analysis of Intracellular iMMUnolabelled cell Subsets) approach, we now compare protein abundance and phosphorylation changes in interphase and mitotic fractions from asynchronously growing human cells. We identify a set of 115 phosphorylation sites increased during G2, termed ‘early risers’. This set includes phosphorylation of S738 on TPX2, which we show is important for TPX2 function and mitotic progression. Further, we use PRIMMUS to provide the first a proteome-wide analysis of protein abundance remodeling between prophase, prometaphase and anaphase. PMID:29052541

A DIGE proteomic analysis for high-intensity exercise-trained rat skeletal muscle.

PubMed

Yamaguchi, Wataru; Fujimoto, Eri; Higuchi, Mitsuru; Tabata, Izumi

2010-09-01

Exercise training induces various adaptations in skeletal muscles. However, the mechanisms remain unclear. In this study, we conducted 2D-DIGE proteomic analysis, which has not yet been used for elucidating adaptations of skeletal muscle after high-intensity exercise training (HIT). For 5 days, rats performed HIT, which consisted of 14 20-s swimming exercise bouts carrying a weight (14% of the body weight), and 10-s pause between bouts. The 2D-DIGE analysis was conducted on epitrochlearis muscles excised 18 h after the final training exercise. Proteomic profiling revealed that out of 800 detected and matched spots, 13 proteins exhibited changed expression by HIT compared with sedentary rats. All proteins were identified by MALDI-TOF/MS. Furthermore, using western immunoblot analyses, significantly changed expressions of NDUFS1 and parvalbumin (PV) were validated in relation to HIT. In conclusion, the proteomic 2D-DIGE analysis following HIT-identified expressions of NDUFS1 and PV, previously unknown to have functions related to exercise-training adaptations.

Progress in Top-Down Proteomics and the Analysis of Proteoforms

PubMed Central

Toby, Timothy K.; Fornelli, Luca; Kelleher, Neil L.

2017-01-01

From a molecular perspective, enactors of function in biology are intact proteins that can be variably modified at the genetic, transcriptional, or post-translational level. Over the past 30 years, mass spectrometry (MS) has become a powerful method for the analysis of proteomes. Prevailing bottom-up proteomics operates at the level of the peptide, leading to issues with protein inference, connectivity, and incomplete sequence/modification information. Top-down proteomics (TDP), alternatively, applies MS at the proteoform level to analyze intact proteins with diverse sources of intramolecular complexity preserved during analysis. Fortunately, advances in prefractionation workflows, MS instrumentation, and dissociation methods for whole-protein ions have helped TDP emerge as an accessible and potentially disruptive modality with increasingly translational value. In this review, we discuss technical and conceptual advances in TDP, along with the growing power of proteoform-resolved measurements in clinical and translational research. PMID:27306313

Sex-Specific Biology of the Human Malaria Parasite Revealed from the Proteomes of Mature Male and Female Gametocytes.

PubMed

Miao, Jun; Chen, Zhao; Wang, Zenglei; Shrestha, Sony; Li, Xiaolian; Li, Runze; Cui, Liwang

2017-04-01

The gametocytes of the malaria parasites are obligate for perpetuating the parasite's life cycle through mosquitoes, but the sex-specific biology of gametocytes is poorly understood. We generated a transgenic line in the human malaria parasite Plasmodium falciparum , which allowed us to accurately separate male and female gametocytes by flow cytometry. In-depth analysis of the proteomes by liquid chromatography-tandem mass spectrometry identified 1244 and 1387 proteins in mature male and female gametocytes, respectively. GFP-tagging of nine selected proteins confirmed their sex-partitions to be agreeable with the results from the proteomic analysis. The sex-specific proteomes showed significant differences that are consistent with the divergent functions of the two sexes. Although the male-specific proteome (119 proteins) is enriched in proteins associated with the flagella and genome replication, the female-specific proteome (262 proteins) is more abundant in proteins involved in metabolism, translation and organellar functions. Compared with the Plasmodium berghei sex-specific proteomes, this study revealed both extensive conservation and considerable divergence between these two species, which reflect the disparities between the two species in proteins involved in cytoskeleton, lipid metabolism and protein degradation. Comparison with three sex-specific proteomes allowed us to obtain high-confidence lists of 73 and 89 core male- and female-specific/biased proteins conserved in Plasmodium The identification of sex-specific/biased proteomes in Plasmodium lays a solid foundation for understanding the molecular mechanisms underlying the unique sex-specific biology in this early-branching eukaryote. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Sex-Specific Biology of the Human Malaria Parasite Revealed from the Proteomes of Mature Male and Female Gametocytes *

PubMed Central

Miao, Jun; Chen, Zhao; Wang, Zenglei; Shrestha, Sony; Li, Xiaolian; Li, Runze; Cui, Liwang

2017-01-01

The gametocytes of the malaria parasites are obligate for perpetuating the parasite's life cycle through mosquitoes, but the sex-specific biology of gametocytes is poorly understood. We generated a transgenic line in the human malaria parasite Plasmodium falciparum, which allowed us to accurately separate male and female gametocytes by flow cytometry. In-depth analysis of the proteomes by liquid chromatography-tandem mass spectrometry identified 1244 and 1387 proteins in mature male and female gametocytes, respectively. GFP-tagging of nine selected proteins confirmed their sex-partitions to be agreeable with the results from the proteomic analysis. The sex-specific proteomes showed significant differences that are consistent with the divergent functions of the two sexes. Although the male-specific proteome (119 proteins) is enriched in proteins associated with the flagella and genome replication, the female-specific proteome (262 proteins) is more abundant in proteins involved in metabolism, translation and organellar functions. Compared with the Plasmodium berghei sex-specific proteomes, this study revealed both extensive conservation and considerable divergence between these two species, which reflect the disparities between the two species in proteins involved in cytoskeleton, lipid metabolism and protein degradation. Comparison with three sex-specific proteomes allowed us to obtain high-confidence lists of 73 and 89 core male- and female-specific/biased proteins conserved in Plasmodium. The identification of sex-specific/biased proteomes in Plasmodium lays a solid foundation for understanding the molecular mechanisms underlying the unique sex-specific biology in this early-branching eukaryote. PMID:28126901

Estimating genetic effects and quantifying missing heritability explained by identified rare-variant associations.

PubMed

Liu, Dajiang J; Leal, Suzanne M

2012-10-05

Next-generation sequencing has led to many complex-trait rare-variant (RV) association studies. Although single-variant association analysis can be performed, it is grossly underpowered. Therefore, researchers have developed many RV association tests that aggregate multiple variant sites across a genetic region (e.g., gene), and test for the association between the trait and the aggregated genotype. After these aggregate tests detect an association, it is only possible to estimate the average genetic effect for a group of RVs. As a result of the "winner's curse," such an estimate can be biased. Although for common variants one can obtain unbiased estimates of genetic parameters by analyzing a replication sample, for RVs it is desirable to obtain unbiased genetic estimates for the study where the association is identified. This is because there can be substantial heterogeneity of RV sites and frequencies even among closely related populations. In order to obtain an unbiased estimate for aggregated RV analysis, we developed bootstrap-sample-split algorithms to reduce the bias of the winner's curse. The unbiased estimates are greatly important for understanding the population-specific contribution of RVs to the heritability of complex traits. We also demonstrate both theoretically and via simulations that for aggregate RV analysis the genetic variance for a gene or region will always be underestimated, sometimes substantially, because of the presence of noncausal variants or because of the presence of causal variants with effects of different magnitudes or directions. Therefore, even if RVs play a major role in the complex-trait etiologies, a portion of the heritability will remain missing, and the contribution of RVs to the complex-trait etiologies will be underestimated. Copyright © 2012 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Bacterial membrane proteomics.

PubMed

Poetsch, Ansgar; Wolters, Dirk

2008-10-01

About one quarter to one third of all bacterial genes encode proteins of the inner or outer bacterial membrane. These proteins perform essential physiological functions, such as the import or export of metabolites, the homeostasis of metal ions, the extrusion of toxic substances or antibiotics, and the generation or conversion of energy. The last years have witnessed completion of a plethora of whole-genome sequences of bacteria important for biotechnology or medicine, which is the foundation for proteome and other functional genome analyses. In this review, we discuss the challenges in membrane proteome analysis, starting from sample preparation and leading to MS-data analysis and quantification. The current state of available proteomics technologies as well as their advantages and disadvantages will be described with a focus on shotgun proteomics. Then, we will briefly introduce the most abundant proteins and protein families present in bacterial membranes before bacterial membrane proteomics studies of the last years will be presented. It will be shown how these works enlarged our knowledge about the physiological adaptations that take place in bacteria during fine chemical production, bioremediation, protein overexpression, and during infections. Furthermore, several examples from literature demonstrate the suitability of membrane proteomics for the identification of antigens and different pathogenic strains, as well as the elucidation of membrane protein structure and function.

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.

MitoMiner: a data warehouse for mitochondrial proteomics data

PubMed Central

Smith, Anthony C.; Blackshaw, James A.; Robinson, Alan J.

2012-01-01

MitoMiner (http://mitominer.mrc-mbu.cam.ac.uk/) is a data warehouse for the storage and analysis of mitochondrial proteomics data gathered from publications of mass spectrometry and green fluorescent protein tagging studies. In MitoMiner, these data are integrated with data from UniProt, Gene Ontology, Online Mendelian Inheritance in Man, HomoloGene, Kyoto Encyclopaedia of Genes and Genomes and PubMed. The latest release of MitoMiner stores proteomics data sets from 46 studies covering 11 different species from eumetazoa, viridiplantae, fungi and protista. MitoMiner is implemented by using the open source InterMine data warehouse system, which provides a user interface allowing users to upload data for analysis, personal accounts to store queries and results and enables queries of any data in the data model. MitoMiner also provides lists of proteins for use in analyses, including the new MitoMiner mitochondrial proteome reference sets that specify proteins with substantial experimental evidence for mitochondrial localization. As further mitochondrial proteomics data sets from normal and diseased tissue are published, MitoMiner can be used to characterize the variability of the mitochondrial proteome between tissues and investigate how changes in the proteome may contribute to mitochondrial dysfunction and mitochondrial-associated diseases such as cancer, neurodegenerative diseases, obesity, diabetes, heart failure and the ageing process. PMID:22121219

Proteome-wide analysis and diel proteomic profiling of the cyanobacterium Arthrospira platensis PCC 8005.

PubMed

Matallana-Surget, Sabine; Derock, Jérémy; Leroy, Baptiste; Badri, Hanène; Deschoenmaeker, Frédéric; Wattiez, Ruddy

2014-01-01

The filamentous cyanobacterium Arthrospira platensis has a long history of use as a food supply and it has been used by the European Space Agency in the MELiSSA project, an artificial microecosystem which supports life during long-term manned space missions. This study assesses progress in the field of cyanobacterial shotgun proteomics and light/dark diurnal cycles by focusing on Arthrospira platensis. Several fractionation workflows including gel-free and gel-based protein/peptide fractionation procedures were used and combined with LC-MS/MS analysis, enabling the overall identification of 1306 proteins, which represents 21% coverage of the theoretical proteome. A total of 30 proteins were found to be significantly differentially regulated under light/dark growth transition. Interestingly, most of the proteins showing differential abundance were related to photosynthesis, the Calvin cycle and translation processes. A novel aspect and major achievement of this work is the successful improvement of the cyanobacterial proteome coverage using a 3D LC-MS/MS approach, based on an immobilized metal affinity chromatography, a suitable tool that enabled us to eliminate the most abundant protein, the allophycocyanin. We also demonstrated that cell growth follows a light/dark cycle in A. platensis. This preliminary proteomic study has highlighted new characteristics of the Arthrospira platensis proteome in terms of diurnal regulation.

Proteome-Wide Analysis and Diel Proteomic Profiling of the Cyanobacterium Arthrospira platensis PCC 8005

PubMed Central

Matallana-Surget, Sabine; Derock, Jérémy; Leroy, Baptiste; Badri, Hanène; Deschoenmaeker, Frédéric; Wattiez, Ruddy

2014-01-01

The filamentous cyanobacterium Arthrospira platensis has a long history of use as a food supply and it has been used by the European Space Agency in the MELiSSA project, an artificial microecosystem which supports life during long-term manned space missions. This study assesses progress in the field of cyanobacterial shotgun proteomics and light/dark diurnal cycles by focusing on Arthrospira platensis. Several fractionation workflows including gel-free and gel-based protein/peptide fractionation procedures were used and combined with LC-MS/MS analysis, enabling the overall identification of 1306 proteins, which represents 21% coverage of the theoretical proteome. A total of 30 proteins were found to be significantly differentially regulated under light/dark growth transition. Interestingly, most of the proteins showing differential abundance were related to photosynthesis, the Calvin cycle and translation processes. A novel aspect and major achievement of this work is the successful improvement of the cyanobacterial proteome coverage using a 3D LC-MS/MS approach, based on an immobilized metal affinity chromatography, a suitable tool that enabled us to eliminate the most abundant protein, the allophycocyanin. We also demonstrated that cell growth follows a light/dark cycle in A. platensis. This preliminary proteomic study has highlighted new characteristics of the Arthrospira platensis proteome in terms of diurnal regulation. PMID:24914774

The Challenge of Human Spermatozoa Proteome: A Systematic Review.

PubMed

Gilany, Kambiz; Minai-Tehrani, Arash; Amini, Mehdi; Agharezaee, Niloofar; Arjmand, Babak

2017-01-01

Currently, there are 20,197 human protein-coding genes in the most expertly curated database (UniProtKB/Swiss-Pro). Big efforts have been made by the international consortium, the Chromosome-Centric Human Proteome Project (C-HPP) and independent researchers, to map human proteome. In brief, anno 2017 the human proteome was outlined. The male factor contributes to 50% of infertility in couples. However, there are limited human spermatozoa proteomic studies. Firstly, the development of the mapping of the human spermatozoa was analyzed. The human spermatozoa have been used as a model for missing proteins. It has been shown that human spermatozoa are excellent sources for finding missing proteins. Y chromosome proteome mapping is led by Iran. However, it seems that it is extremely challenging to map the human spermatozoa Y chromosome proteins based on current mass spectrometry-based proteomics technology. Post-translation modifications (PTMs) of human spermatozoa proteome are the most unexplored area and currently the exact role of PTMs in male infertility is unknown. Additionally, the clinical human spermatozoa proteomic analysis, anno 2017 was done in this study.

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.

PatternLab for proteomics 4.0: A one-stop shop for analyzing shotgun proteomic data

PubMed Central

Carvalho, Paulo C; Lima, Diogo B; Leprevost, Felipe V; Santos, Marlon D M; Fischer, Juliana S G; Aquino, Priscila F; Moresco, James J; Yates, John R; Barbosa, Valmir C

2017-01-01

PatternLab for proteomics is an integrated computational environment that unifies several previously published modules for analyzing shotgun proteomic data. PatternLab contains modules for formatting sequence databases, performing peptide spectrum matching, statistically filtering and organizing shotgun proteomic data, extracting quantitative information from label-free and chemically labeled data, performing statistics for differential proteomics, displaying results in a variety of graphical formats, performing similarity-driven studies with de novo sequencing data, analyzing time-course experiments, and helping with the understanding of the biological significance of data in the light of the Gene Ontology. Here we describe PatternLab for proteomics 4.0, which closely knits together all of these modules in a self-contained environment, covering the principal aspects of proteomic data analysis as a freely available and easily installable software package. All updates to PatternLab, as well as all new features added to it, have been tested over the years on millions of mass spectra. PMID:26658470

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

PubMed

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

2014-02-01

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

Expanding the bovine milk proteome through extensive fractionation.

PubMed

Nissen, Asger; Bendixen, Emøke; Ingvartsen, Klaus Lønne; Røntved, Christine Maria

2013-01-01

Bovine milk is an agricultural product of tremendous value worldwide. It contains proteins, fat, lactose, vitamins, and minerals. It provides nutrition and immunological protection (e.g., in the gastrointestinal tract) to the newborn and young calf. It also forms an important part of human nutrition. The repertoire of proteins in milk (i.e., its proteome) is vast and complex. The milk proteome can be described in detail by mass spectrometry-based proteomics. However, the high concentration of dominating proteins in milk reduces mass spectrometry detection sensitivity and limits detection of low abundant proteins. Further, the general health and udder health of the dairy cows delivering the milk may influence the composition of the milk proteome. To gain a more exhaustive and true picture of the milk proteome, we performed an extensive preanalysis fractionation of raw composite milk collected from documented healthy cows in early lactation. Four simple and industrially applicable techniques exploring the physical and chemical properties of milk, including acidification, filtration, and centrifugation, were used for separation of the proteins. This resulted in 5 different fractions, whose content of proteins were compared with the proteins of nonfractionated milk using 2-dimensional liquid chromatography tandem mass spectrometry analysis. To validate the proteome analysis, spectral counts and ELISA were performed on 7 proteins using the ELISA for estimation of the detection sensitivity limit of the 2-dimensional liquid chromatography tandem mass spectrometry analysis. Each fractionation technique resulted in identification of a unique subset of proteins. However, high-speed centrifugation of milk to whey was by far the best method to achieve high and repeatable proteome coverage. The total number of milk proteins initially detected in nonfractionated milk and the fractions were 635 in 2 replicates. Removal of dominant proteins and filtering for redundancy across the different fractions reduced the number to 376 unique proteins in 2 replicates. In addition, 366 proteins were detected by this process in 1 replicate. Hence, by applying different fractionation techniques to milk, we expanded the milk proteome. The milk proteome map may serve as a reference for scientists working in the dairy sector. Copyright © 2013 American Dairy Science Association. Published by 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.

Optimizing of MALDI-ToF-based low-molecular-weight serum proteome pattern analysis in detection of breast cancer patients; the effect of albumin removal on classification performance.

PubMed

Pietrowska, M; Marczak, L; Polanska, J; Nowicka, E; Behrent, K; Tarnawski, R; Stobiecki, M; Polanski, A; Widlak, P

2010-01-01

Mass spectrometry-based analysis of the serum proteome allows identifying multi-peptide patterns/signatures specific for blood of cancer patients, thus having high potential value for cancer diagnostics. However, because of problems with optimization and standardization of experimental and computational design, none of identified proteome patterns/signatures was approved for diagnostics in clinical practice as yet. Here we compared two methods of serum sample preparation for mass spectrometry-based proteome pattern analysis aimed to identify biomarkers that could be used in early detection of breast cancer patients. Blood samples were collected in a group of 92 patients diagnosed at early (I and II) stages of the disease before the start of therapy, and in a group of age-matched healthy controls (104 women). Serum specimens were purified and analyzed using MALDI-ToF spectrometry, either directly or after membrane filtration (50 kDa cut-off) to remove albumin and other large serum proteins. Mass spectra of the low-molecular-weight fraction (2-10 kDa) of the serum proteome were resolved using the Gaussian mixture decomposition, and identified spectral components were used to build classifiers that differentiated samples from breast cancer patients and healthy persons. Mass spectra of complete serum and membrane-filtered albumin-depleted samples have apparently different structure and peaks specific for both types of samples could be identified. The optimal classifier built for the complete serum specimens consisted of 8 spectral components, and had 81% specificity and 72% sensitivity, while that built for the membrane-filtered samples consisted of 4 components, and had 80% specificity and 81% sensitivity. We concluded that pre-processing of samples to remove albumin might be recommended before MALDI-ToF mass spectrometric analysis of the low-molecular-weight components of human serum Keywords: albumin removal; breast cancer; clinical proteomics; mass spectrometry; pattern analysis; serum proteome.

A comprehensive and scalable database search system for metaproteomics.

PubMed

Chatterjee, Sandip; Stupp, Gregory S; Park, Sung Kyu Robin; Ducom, Jean-Christophe; Yates, John R; Su, Andrew I; Wolan, Dennis W

2016-08-16

Mass spectrometry-based shotgun proteomics experiments rely on accurate matching of experimental spectra against a database of protein sequences. Existing computational analysis methods are limited in the size of their sequence databases, which severely restricts the proteomic sequencing depth and functional analysis of highly complex samples. The growing amount of public high-throughput sequencing data will only exacerbate this problem. We designed a broadly applicable metaproteomic analysis method (ComPIL) that addresses protein database size limitations. Our approach to overcome this significant limitation in metaproteomics was to design a scalable set of sequence databases assembled for optimal library querying speeds. ComPIL was integrated with a modified version of the search engine ProLuCID (termed "Blazmass") to permit rapid matching of experimental spectra. Proof-of-principle analysis of human HEK293 lysate with a ComPIL database derived from high-quality genomic libraries was able to detect nearly all of the same peptides as a search with a human database (~500x fewer peptides in the database), with a small reduction in sensitivity. We were also able to detect proteins from the adenovirus used to immortalize these cells. We applied our method to a set of healthy human gut microbiome proteomic samples and showed a substantial increase in the number of identified peptides and proteins compared to previous metaproteomic analyses, while retaining a high degree of protein identification accuracy and allowing for a more in-depth characterization of the functional landscape of the samples. The combination of ComPIL with Blazmass allows proteomic searches to be performed with database sizes much larger than previously possible. These large database searches can be applied to complex meta-samples with unknown composition or proteomic samples where unexpected proteins may be identified. The protein database, proteomic search engine, and the proteomic data files for the 5 microbiome samples characterized and discussed herein are open source and available for use and additional analysis.

Comparative analysis of genomics and proteomics in Bacillus thuringiensis 4.0718.

PubMed

Rang, Jie; He, Hao; Wang, Ting; Ding, Xuezhi; Zuo, Mingxing; Quan, Meifang; Sun, Yunjun; Yu, Ziquan; Hu, Shengbiao; Xia, Liqiu

2015-01-01

Bacillus thuringiensis is a widely used biopesticide that produced various insecticidal active substances during its life cycle. Separation and purification of numerous insecticide active substances have been difficult because of the relatively short half-life of such substances. On the other hand, substances can be synthetized at different times during development, so samples at different stages have to be studied, further complicating the analysis. A dual genomic and proteomic approach would enhance our ability to identify such substances, and particularily using mass spectrometry-based proteomic methods. The comparative analysis for genomic and proteomic data have showed that not all of the products deduced from the annotated genome could be identified among the proteomic data. For instance, genome annotation results showed that 39 coding sequences in the whole genome were related to insect pathogenicity, including five cry genes. However, Cry2Ab, Cry1Ia, Cytotoxin K, Bacteriocin, Exoenzyme C3 and Alveolysin could not be detected in the proteomic data obtained. The sporulation-related proteins were also compared analysis, results showed that the great majority sporulation-related proteins can be detected by mass spectrometry. This analysis revealed Spo0A~P, SigF, SigE(+), SigK(+) and SigG(+), all known to play an important role in the process of spore formation regulatory network, also were displayed in the proteomic data. Through the comparison of the two data sets, it was possible to infer that some genes were silenced or were expressed at very low levels. For instance, found that cry2Ab seems to lack a functional promoter while cry1Ia may not be expressed due to the presence of transposons. With this comparative study a relatively complete database can be constructed and used to transform hereditary material, thereby prompting the high expression of toxic proteins. A theoretical basis is provided for constructing highly virulent engineered bacteria and for promoting the application of proteogenomics in the life sciences.

MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes.

PubMed

Zhang, Yanling; Zhang, Yong; Adachi, Jun; Olsen, Jesper V; Shi, Rong; de Souza, Gustavo; Pasini, Erica; Foster, Leonard J; Macek, Boris; Zougman, Alexandre; Kumar, Chanchal; Wisniewski, Jacek R; Jun, Wang; Mann, Matthias

2007-01-01

Mass spectrometry (MS)-based proteomics has become a powerful technology to map the protein composition of organelles, cell types and tissues. In our department, a large-scale effort to map these proteomes is complemented by the Max-Planck Unified (MAPU) proteome database. MAPU contains several body fluid proteomes; including plasma, urine, and cerebrospinal fluid. Cell lines have been mapped to a depth of several thousand proteins and the red blood cell proteome has also been analyzed in depth. The liver proteome is represented with 3200 proteins. By employing high resolution MS and stringent validation criteria, false positive identification rates in MAPU are lower than 1:1000. Thus MAPU datasets can serve as reference proteomes in biomarker discovery. MAPU contains the peptides identifying each protein, measured masses, scores and intensities and is freely available at http://www.mapuproteome.com using a clickable interface of cell or body parts. Proteome data can be queried across proteomes by protein name, accession number, sequence similarity, peptide sequence and annotation information. More than 4500 mouse and 2500 human proteins have already been identified in at least one proteome. Basic annotation information and links to other public databases are provided in MAPU and we plan to add further analysis tools.

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

PubMed

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

2018-04-06

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

Advanced proteomic liquid chromatography

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

Xie, Fang; Smith, Richard D.; Shen, Yufeng

2012-10-26

Liquid chromatography coupled with mass spectrometry is the predominant platform used to analyze proteomics samples consisting of large numbers of proteins and their proteolytic products (e.g., truncated polypeptides) and spanning a wide range of relative concentrations. This review provides an overview of advanced capillary liquid chromatography techniques and methodologies that greatly improve separation resolving power and proteomics analysis coverage, sensitivity, and throughput.

CPTAC Contributes to Healthdata.gov | Office of Cancer Clinical Proteomics Research

Cancer.gov

Recently, proteomic data generated by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) funded by National Cancer Institute (NCI) was highlighted to the wider research community at Healthdata.gov. Healthdata.gov aims to make health data more accessible to entrepreneurs, researchers, and policy makers in the hopes of improving health outcomes f

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…

Mapping and proteomic analysis of albumin and globulin proteins in hexaploid wheat kernels (Triticum aestivum L.).

PubMed

Merlino, Marielle; Leroy, Philippe; Chambon, Christophe; Branlard, Gérard

2009-05-01

Albumins and globulins of wheat endosperm represent 20% of total kernel protein. They are soluble proteins, mainly enzymes and proteins involved in cell functions. Two-dimensional gel immobiline electrophoresis (2DE) (pH 4-7) x SDS-Page revealed around 2,250 spots. Ninety percent of the spots were common between the very distantly related cultivars 'Opata 85' and 'Synthetic W7984', the two parents of the International Triticeae Mapping Initiative (ITMI) progeny. 'Opata' had 130 specific spots while 'Synthetic' had 96. 2DE and image analysis of the soluble proteins present in 112 recombinant inbred lines of the F9-mapped ITMI progeny enabled 120 unbiased segregating spots to be mapped on 21 wheat (Triticum aestivum L. em. Thell) chromosomes. After trypsic digestion, mapped spots were subjected to MALDI-Tof or tandem mass spectrometry for protein identification by database mining. Among the 'Opata' and 'Synthetic' spots identified, many enzymes have already been mapped in the barley and rice genomes. Multigene families of Heat Shock Proteins, beta-amylases, UDP-glucose pyrophosphorylases, peroxydases and thioredoxins were successfully identified. Although other proteins remain to be identified, some differences were found in the number of segregating proteins involved in response to stress: 11 proteins found in the modern selected cultivar 'Opata 85' as compared to 4 in the new hexaploid ;Synthetic W7984'. In addition, 'Opata' and 'Synthetic' differed in the number of proteins involved in protein folding (2 and 10, respectively). The usefulness of the mapped enzymes for future research on seed composition and characteristics is discussed.

Proteomic analysis of chromoplasts from six crop species reveals insights into chromoplast function and development

USDA-ARS?s Scientific Manuscript database

Chromoplasts are unique plastids that accumulate massive amounts of carotenoids. To gain a general and comparative characterization of chromoplast proteins, we performed proteomic analysis of chromoplasts from six carotenoid-rich crops: watermelon, tomato, carrot, orange cauliflower, red papaya, and...

The wheat chloroplastic proteome.

PubMed

Kamal, Abu Hena Mostafa; Cho, Kun; Choi, Jong-Soon; Bae, Kwang-Hee; Komatsu, Setsuko; Uozumi, Nobuyuki; Woo, Sun Hee

2013-11-20

With the availability of plant genome sequencing, analysis of plant proteins with mass spectrometry has become promising and admired. Determining the proteome of a cell is still a challenging assignment, which is convoluted by proteome dynamics and convolution. Chloroplast is fastidious curiosity for plant biologists due to their intricate biochemical pathways for indispensable metabolite functions. In this review, an overview on proteomic studies conducted in wheat with a special focus on subcellular proteomics of chloroplast, salt and water stress. In recent years, we and other groups have attempted to understand the photosynthesis in wheat and abiotic stress under salt imposed and water deficit during vegetative stage. Those studies provide interesting results leading to better understanding of the photosynthesis and identifying the stress-responsive proteins. Indeed, recent studies aimed at resolving the photosynthesis pathway in wheat. Proteomic analysis combining two complementary approaches such as 2-DE and shotgun methods couple to high through put mass spectrometry (LTQ-FTICR and MALDI-TOF/TOF) in order to better understand the responsible proteins in photosynthesis and abiotic stress (salt and water) in wheat chloroplast will be focused. In this review we discussed the identification of the most abundant protein in wheat chloroplast and stress-responsive under salt and water stress in chloroplast of wheat seedlings, thus providing the proteomic view of the events during the development of this seedling under stress conditions. Chloroplast is fastidious curiosity for plant biologists due to their intricate biochemical pathways for indispensable metabolite functions. An overview on proteomic studies conducted in wheat with a special focus on subcellular proteomics of chloroplast, salt and water stress. We have attempted to understand the photosynthesis in wheat and abiotic stress under salt imposed and water deficit during seedling stage. Those studies provide interesting results leading to a better understanding of the photosynthesis and identifying the stress-responsive proteins. In reality, our studies aspired at resolving the photosynthesis pathway in wheat. Proteomic analysis united two complementary approaches such as Tricine SDS-PAGE and 2-DE methods couple to high through put mass spectrometry (LTQ-FTICR and MALDI-TOF/TOF) in order to better understand the responsible proteins in photosynthesis and abiotic stress (salt and water) in wheat chloroplast will be highlighted. This article is part of a Special Issue entitled: Translational Plant Proteomics. Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.

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.

Proteomics identifies the composition and manufacturing recipe of the 2500-year old sourdough bread from Subeixi cemetery in China.

PubMed

Shevchenko, Anna; Yang, Yimin; Knaust, Andrea; Thomas, Henrik; Jiang, Hongen; Lu, Enguo; Wang, Changsui; Shevchenko, Andrej

2014-06-13

We report on the geLC-MS/MS proteomics analysis of cereals and cereal food excavated in Subeixi cemetery (500-300BC) in Xinjiang, China. Proteomics provided direct evidence that at the Subexi sourdough bread was made from barley and broomcorn millet by leavening with a renewable starter comprising baker's yeast and lactic acid bacteria. The baking recipe and flour composition indicated that barley and millet bread belonged to the staple food already in the first millennium BC and suggested the role of Turpan basin as a major route for cultural communication between Western and Eastern Eurasia in antiquity. This article is part of a Special Issue entitled: Proteomics of non-model organisms. We demonstrate that organic residues of thousand year old foods unearthed by archeological excavations can be analyzed by geLC-MS/MS proteomics with good representation of protein source organisms and coverage of sequences of identified proteins. In-depth look into the foods proteome identifies the food type and its individual ingredients, reveals ancient food processing technologies, projects their social and economic impact and provides evidence of intercultural communication between ancient populations. Proteomics analysis of ancient organic residues is direct, quantitative and informative and therefore has the potential to develop into a valuable, generally applicable tool in archaeometry. This article is part of a Special Issue entitled: Proteomics of non-model organisms. Copyright © 2013. Published by Elsevier B.V.

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.

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

PubMed Central

Zhang, Qiang; Cundiff, Judy K.; Maria, Sarah D.; McMahon, Robert J.; Woo, Jessica G.; Davidson, Barbara S.; Morrow, Ardythe L.

2013-01-01

In-depth understanding of the changing functions of human milk (HM) proteins and the corresponding physiological adaptions of the lactating mammary gland has been inhibited by incomplete knowledge of the HM proteome. We analyzed the HM whey proteome (n = 10 women with samples at 1 week and 1, 3, 6, 9 and 12 months) using a quantitative proteomic approach. One thousand three hundred and thirty three proteins were identified with 615 being quantified. Principal component analysis revealed a transition in the HM whey proteome-throughout the first year of lactation. Abundance changes in IgG, sIgA and sIgM display distinct features during the first year. Complement components and other acute-phase proteins are generally at higher levels in early lactation. Proteomic analysis further suggests that the sources of milk fatty acids (FA) shift from more direct blood influx to more de novo mammary synthesis over lactation. The abundances of the majority of glycoproteins decline over lactation, which is consistent with increased enzyme expression in glycoprotein degradation and decreased enzyme expression in glycoprotein synthesis. Cellular detoxification machinery may be transformed as well, thereby accommodating increased metabolic activities in late lactation. The multiple developing functions of HM proteins and the corresponding mammary adaption become more apparent from this study. PMID:28250401

Molecular Diagnosis and Biomarker Identification on SELDI proteomics data by ADTBoost method.

PubMed

Wang, Lu-Yong; Chakraborty, Amit; Comaniciu, Dorin

2005-01-01

Clinical proteomics is an emerging field that will have great impact on molecular diagnosis, identification of disease biomarkers, drug discovery and clinical trials in the post-genomic era. Protein profiling in tissues and fluids in disease and pathological control and other proteomics techniques will play an important role in molecular diagnosis with therapeutics and personalized healthcare. We introduced a new robust diagnostic method based on ADTboost algorithm, a novel algorithm in proteomics data analysis to improve classification accuracy. It generates classification rules, which are often smaller and easier to interpret. This method often gives most discriminative features, which can be utilized as biomarkers for diagnostic purpose. Also, it has a nice feature of providing a measure of prediction confidence. We carried out this method in amyotrophic lateral sclerosis (ALS) disease data acquired by surface enhanced laser-desorption/ionization-time-of-flight mass spectrometry (SELDI-TOF MS) experiments. Our method is shown to have outstanding prediction capacity through the cross-validation, ROC analysis results and comparative study. Our molecular diagnosis method provides an efficient way to distinguish ALS disease from neurological controls. The results are expressed in a simple and straightforward alternating decision tree format or conditional format. We identified most discriminative peaks in proteomic data, which can be utilized as biomarkers for diagnosis. It will have broad application in molecular diagnosis through proteomics data analysis and personalized medicine in this post-genomic era.

The proteome pattern cGvHD_MS14 allows early and accurate prediction of chronic GvHD after allogeneic stem cell transplantation.

PubMed

Weissinger, E M; Human, C; Metzger, J; Hambach, L; Wolf, D; Greinix, H T; Dickinson, A M; Mullen, W; Jonigk, D; Kuzmina, Z; Kreipe, H; Schweier, P; Böhm, O; Türüchanow, I; Ihlenburg-Schwarz, D; Raad, J; Durban, A; Schiemann, M; Könecke, C; Diedrich, H; Holler, E; Beutel, G; Krauter, J; Ganser, A; Stadler, M

2017-03-01

Allogeneic hematopoietic stem cell transplantation (allo-HSCT) may be curative, but is associated with significant morbidity and mortality. Chronic graft-versus-host disease (cGvHD), characterized by inflammation and fibrosis of multiple target organs, considerably contributes to the morbidity and mortality even years after allo-HSCT. Diagnosis of cGvHD is based on clinical features and histology of biopsies. Here, we report the generation of a urinary cGvHD-specific proteome-pattern (cGvHD_MS14) established by capillary electrophoresis-mass spectrometry to predict onset and severity of cGvHD as an unbiased laboratory test. cGvHD_MS14 was evaluated on samples from 412 patients collected prospectively in four transplant centers. Sensitivity and specificity was 84 and 76% by cGvHD_MS14 classification. Sensitivity further increased to 93% by combination of cGvHD_MS14 with relevant clinical variables to a logistic regression model. cGvHD was predicted up to 55 days prior to clinical diagnosis. Acute GvHD is not recognized by cGvHD_MS14. cGvHD_MS14 consists of 14 differentially excreted peptides, six of those have been sequenced to date and are fragments from thymosin β-4, eukaryotic translation initiation factor 4γ2, fibrinogen β-chain or collagens. In conclusion, the cGvHD_MS14-pattern allows early, highly sensitive and specific prediction of cGvHD as an independent diagnostic criterion of clinical diagnosis potentially allowing early therapeutic intervention.

Instant Integrated Ultradeep Quantitative-structural Membrane Proteomics Discovered Post-translational Modification Signatures for Human Cys-loop Receptor Subunit Bias*

PubMed Central

Zhang, Xi

2016-01-01

Neurotransmitter ligand-gated ion channels (LGICs) are widespread and pivotal in brain functions. Unveiling their structure-function mechanisms is crucial to drive drug discovery, and demands robust proteomic quantitation of expression, post-translational modifications (PTMs) and dynamic structures. Yet unbiased digestion of these modified transmembrane proteins—at high efficiency and peptide reproducibility—poses the obstacle. Targeting both enzyme-substrate contacts and PTMs for peptide formation and detection, we devised flow-and-detergent-facilitated protease and de-PTM digestions for deep sequencing (FDD) method that combined omni-compatible detergent, tandem immobilized protease/PNGase columns, and Cys-selective reduction/alkylation, to achieve streamlined ultradeep peptide preparation within minutes not days, at high peptide reproducibility and low abundance-bias. FDD transformed enzyme-protein contacts into equal catalytic travel paths through enzyme-excessive columns regardless of protein abundance, removed products instantly preventing inhibition, tackled intricate structures via sequential multiple micro-digestions along the flow, and precisely controlled peptide formation by flow rate. Peptide-stage reactions reduced steric bias; low contamination deepened MS/MS scan; distinguishing disulfide from M oxidation and avoiding gain/loss artifacts unmasked protein-endogenous oxidation states. Using a recent interactome of 285-kDa human GABA type A receptor, this pilot study validated FDD platform's applicability to deep sequencing (up to 99% coverage), H/D-exchange and TMT-based structural mapping. FDD discovered novel subunit-specific PTM signatures, including unusual nontop-surface N-glycosylations, that may drive subunit biases in human Cys-loop LGIC assembly and pharmacology, by redefining subunit/ligand interfaces and connecting function domains. PMID:27073180

Proteome Characterization Centers - TCGA

Cancer.gov

The centers, a component of NCI’s Clinical Proteomic Tumor Analysis Consortium, will analyze a subset of TCGA samples to define proteins translated from cancer genomes and their related biological processes.

Graph-state formalism for mutually unbiased bases

NASA Astrophysics Data System (ADS)

Spengler, Christoph; Kraus, Barbara

2013-11-01

A pair of orthonormal bases is called mutually unbiased if all mutual overlaps between any element of one basis and an arbitrary element of the other basis coincide. In case the dimension, d, of the considered Hilbert space is a power of a prime number, complete sets of d+1 mutually unbiased bases (MUBs) exist. Here we present a method based on the graph-state formalism to construct such sets of MUBs. We show that for n p-level systems, with p being prime, one particular graph suffices to easily construct a set of pn+1 MUBs. In fact, we show that a single n-dimensional vector, which is associated with this graph, can be used to generate a complete set of MUBs and demonstrate that this vector can be easily determined. Finally, we discuss some advantages of our formalism regarding the analysis of entanglement structures in MUBs, as well as experimental realizations.

Diallel analysis for sex-linked and maternal effects.

PubMed

Zhu, J; Weir, B S

1996-01-01

Genetic models including sex-linked and maternal effects as well as autosomal gene effects are described. Monte Carlo simulations were conducted to compare efficiencies of estimation by minimum norm quadratic unbiased estimation (MINQUE) and restricted maximum likelihood (REML) methods. MINQUE(1), which has 1 for all prior values, has a similar efficiency to MINQUE(θ), which requires prior estimates of parameter values. MINQUE(1) has the advantage over REML of unbiased estimation and convenient computation. An adjusted unbiased prediction (AUP) method is developed for predicting random genetic effects. AUP is desirable for its easy computation and unbiasedness of both mean and variance of predictors. The jackknife procedure is appropriate for estimating the sampling variances of estimated variances (or covariances) and of predicted genetic effects. A t-test based on jackknife variances is applicable for detecting significance of variation. Worked examples from mice and silkworm data are given in order to demonstrate variance and covariance estimation and genetic effect prediction.

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

PubMed Central

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

2014-01-01

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

Optimization of quantitative proteomic analysis of clots generated from plasma of patients with venous thromboembolism.

PubMed

Stachowicz, Aneta; Siudut, Jakub; Suski, Maciej; Olszanecki, Rafał; Korbut, Ryszard; Undas, Anetta; Wiśniewski, Jacek R

2017-01-01

It is well known that fibrin network binds a large variety of proteins, including inhibitors and activators of fibrinolysis, which may affect clot properties, such as stability and susceptibility to fibrinolysis. Specific plasma clot composition differs between individuals and may change in disease states. However, the plasma clot proteome has not yet been in-depth analyzed, mainly due to technical difficulty related to the presence of a highly abundant protein-fibrinogen and fibrin that forms a plasma clot. The aim of our study was to optimize quantitative proteomic analysis of fibrin clots prepared ex vivo from citrated plasma of the peripheral blood drawn from patients with prior venous thromboembolism (VTE). We used a multiple enzyme digestion filter aided sample preparation, a multienzyme digestion (MED) FASP method combined with LC-MS/MS analysis performed on a Proxeon Easy-nLC System coupled to the Q Exactive HF mass spectrometer. We also evaluated the impact of peptide fractionation with pipet-tip strong anion exchange (SAX) method on the obtained results. Our proteomic approach revealed 476 proteins repeatedly identified in the plasma fibrin clots from patients with VTE including extracellular vesicle-derived proteins, lipoproteins, fibrinolysis inhibitors, and proteins involved in immune responses. The MED FASP method using three different enzymes: LysC, trypsin and chymotrypsin increased the number of identified peptides and proteins and their sequence coverage as compared to a single step digestion. Peptide fractionation with a pipet-tip strong anion exchange (SAX) protocol increased the depth of proteomic analyses, but also extended the time needed for sample analysis with LC-MS/MS. The MED FASP method combined with a label-free quantification is an excellent proteomic approach for the analysis of fibrin clots prepared ex vivo from citrated plasma of patients with prior VTE.

Tissue proteomics of the low-molecular weight proteome using an integrated cLC-ESI-QTOFMS approach.

PubMed

Alvarez, MeiHwa Tanielle Bench; Shah, Dipti Jigar; Thulin, Craig D; Graves, Steven W

2013-05-01

Analysis of the protein/peptide composition of tissue has provided meaningful insights into tissue biology and even disease mechanisms. However, little has been published regarding top down methods to investigate lower molecular weight (MW) (500-5000 Da) species in tissue. Here, we evaluate a tissue proteomics approach involving tissue homogenization followed by depletion of large proteins and then cLC-MS (where c stands for capillary) analysis to interrogate the low MW/low abundance tissue proteome. In the development of this method, sheep heart, lung, liver, kidney, and spleen were surveyed to test our ability to observe tissue differences. After categorical tissue differences were demonstrated, a detailed study of this method's reproducibility was undertaken to determine whether or not it is suitable for analyzing more subtle differences in the abundance of small proteins and peptides. Our results suggest that this method should be useful in exploring the low MW proteome of tissues. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative Analysis of Global Proteome and Lysine Acetylome Reveal the Differential Impacts of VPA and SAHA on HL60 Cells.

PubMed

Zhu, Xiaoyu; Liu, Xin; Cheng, Zhongyi; Zhu, Jun; Xu, Lei; Wang, Fengsong; Qi, Wulin; Yan, Jiawei; Liu, Ning; Sun, Zimin; Liu, Huilan; Peng, Xiaojun; Hao, Yingchan; Zheng, Nan; Wu, Quan

2016-01-29

Valproic acid (VPA) and suberoylanilide hydroxamic acid (SAHA) are both HDAC inhibitors (HDACi). Previous studies indicated that both inhibitors show therapeutic effects on acute myeloid leukaemia (AML), while the differential impacts of the two different HDACi on AML treatment still remains elusive. In this study, using 3-plex SILAC based quantitative proteomics technique, anti-acetyllysine antibody based affinity enrichment, high resolution LC-MS/MS and intensive bioinformatic analysis, the quantitative proteome and acetylome in SAHA and VPA treated AML HL60 cells were extensively studied. In total, 5,775 proteins and 1,124 lysine acetylation sites were successfully obtained in response to VAP and SAHA treatment. It is found that VPA and SAHA treatment differently induced proteome and acetylome profiling in AML HL60 cells. This study revealed the differential impacts of VPA and SAHA on proteome/acetylome in AML cells, deepening our understanding of HDAC inhibitor mediated AML therapeutics.

Noninvasive diagnosis of intraamniotic infection: proteomic biomarkers in vaginal fluid.

PubMed

Hitti, Jane; Lapidus, Jodi A; Lu, Xinfang; Reddy, Ashok P; Jacob, Thomas; Dasari, Surendra; Eschenbach, David A; Gravett, Michael G; Nagalla, Srinivasa R

2010-07-01

We analyzed the vaginal fluid proteome to identify biomarkers of intraamniotic infection among women in preterm labor. Proteome analysis was performed on vaginal fluid specimens from women with preterm labor, using multidimensional liquid chromatography, tandem mass spectrometry, and label-free quantification. Enzyme immunoassays were used to quantify candidate proteins. Classification accuracy for intraamniotic infection (positive amniotic fluid bacterial culture and/or interleukin-6 >2 ng/mL) was evaluated using receiver-operator characteristic curves obtained by logistic regression. Of 170 subjects, 30 (18%) had intraamniotic infection. Vaginal fluid proteome analysis revealed 338 unique proteins. Label-free quantification identified 15 proteins differentially expressed in intraamniotic infection, including acute-phase reactants, immune modulators, high-abundance amniotic fluid proteins and extracellular matrix-signaling factors; these findings were confirmed by enzyme immunoassay. A multi-analyte algorithm showed accurate classification of intraamniotic infection. Vaginal fluid proteome analyses identified proteins capable of discriminating between patients with and without intraamniotic infection. Copyright (c) 2010 Mosby, Inc. All rights reserved.

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

PubMed Central

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

2015-01-01

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

Unbiased metabolite profiling by liquid chromatography-quadrupole time-of-flight mass spectrometry and multivariate data analysis for herbal authentication: classification of seven Lonicera species flower buds.

PubMed

Gao, Wen; Yang, Hua; Qi, Lian-Wen; Liu, E-Hu; Ren, Mei-Ting; Yan, Yu-Ting; Chen, Jun; Li, Ping

2012-07-06

Plant-based medicines become increasingly popular over the world. Authentication of herbal raw materials is important to ensure their safety and efficacy. Some herbs belonging to closely related species but differing in medicinal properties are difficult to be identified because of similar morphological and microscopic characteristics. Chromatographic fingerprinting is an alternative method to distinguish them. Existing approaches do not allow a comprehensive analysis for herbal authentication. We have now developed a strategy consisting of (1) full metabolic profiling of herbal medicines by rapid resolution liquid chromatography (RRLC) combined with quadrupole time-of-flight mass spectrometry (QTOF MS), (2) global analysis of non-targeted compounds by molecular feature extraction algorithm, (3) multivariate statistical analysis for classification and prediction, and (4) marker compounds characterization. This approach has provided a fast and unbiased comparative multivariate analysis of the metabolite composition of 33-batch samples covering seven Lonicera species. Individual metabolic profiles are performed at the level of molecular fragments without prior structural assignment. In the entire set, the obtained classifier for seven Lonicera species flower buds showed good prediction performance and a total of 82 statistically different components were rapidly obtained by the strategy. The elemental compositions of discriminative metabolites were characterized by the accurate mass measurement of the pseudomolecular ions and their chemical types were assigned by the MS/MS spectra. The high-resolution, comprehensive and unbiased strategy for metabolite data analysis presented here is powerful and opens the new direction of authentication in herbal analysis. Copyright © 2012 Elsevier B.V. All rights reserved.

Enhanced Missing Proteins Detection in NCI60 Cell Lines Using an Integrative Search Engine Approach.

PubMed

Guruceaga, Elizabeth; Garin-Muga, Alba; Prieto, Gorka; Bejarano, Bartolomé; Marcilla, Miguel; Marín-Vicente, Consuelo; Perez-Riverol, Yasset; Casal, J Ignacio; Vizcaíno, Juan Antonio; Corrales, Fernando J; Segura, Victor

2017-12-01

The Human Proteome Project (HPP) aims deciphering the complete map of the human proteome. In the past few years, significant efforts of the HPP teams have been dedicated to the experimental detection of the missing proteins, which lack reliable mass spectrometry evidence of their existence. In this endeavor, an in depth analysis of shotgun experiments might represent a valuable resource to select a biological matrix in design validation experiments. In this work, we used all the proteomic experiments from the NCI60 cell lines and applied an integrative approach based on the results obtained from Comet, Mascot, OMSSA, and X!Tandem. This workflow benefits from the complementarity of these search engines to increase the proteome coverage. Five missing proteins C-HPP guidelines compliant were identified, although further validation is needed. Moreover, 165 missing proteins were detected with only one unique peptide, and their functional analysis supported their participation in cellular pathways as was also proposed in other studies. Finally, we performed a combined analysis of the gene expression levels and the proteomic identifications from the common cell lines between the NCI60 and the CCLE project to suggest alternatives for further validation of missing protein observations.

Enhanced Missing Proteins Detection in NCI60 Cell Lines Using an Integrative Search Engine Approach

PubMed Central

2017-01-01

The Human Proteome Project (HPP) aims deciphering the complete map of the human proteome. In the past few years, significant efforts of the HPP teams have been dedicated to the experimental detection of the missing proteins, which lack reliable mass spectrometry evidence of their existence. In this endeavor, an in depth analysis of shotgun experiments might represent a valuable resource to select a biological matrix in design validation experiments. In this work, we used all the proteomic experiments from the NCI60 cell lines and applied an integrative approach based on the results obtained from Comet, Mascot, OMSSA, and X!Tandem. This workflow benefits from the complementarity of these search engines to increase the proteome coverage. Five missing proteins C-HPP guidelines compliant were identified, although further validation is needed. Moreover, 165 missing proteins were detected with only one unique peptide, and their functional analysis supported their participation in cellular pathways as was also proposed in other studies. Finally, we performed a combined analysis of the gene expression levels and the proteomic identifications from the common cell lines between the NCI60 and the CCLE project to suggest alternatives for further validation of missing protein observations. PMID:28960077

Hepatic SILAC proteomic data from PANDER transgenic model.

PubMed

Athanason, Mark G; Stevens, Stanley M; Burkhardt, Brant R

2016-12-01

This article contains raw and processed data related to research published in "Quantitative Proteomic Profiling Reveals Hepatic Lipogenesis and Liver X Receptor Activation in the PANDER Transgenic Model" (M.G. Athanason, W.A. Ratliff, D. Chaput, C.B. MarElia, M.N. Kuehl, S.M., Jr. Stevens, B.R. Burkhardt (2016)) [1], and was generated by "spike-in" SILAC-based proteomic analysis of livers obtained from the PANcreatic-Derived factor (PANDER) transgenic mouse (PANTG) under various metabolic conditions [1]. The mass spectrometry output of the PANTG and wild-type B6SJLF mice liver tissue and resulting proteome search from MaxQuant 1.2.2.5 employing the Andromeda search algorithm against the UniprotKB reference database for Mus musculus has been deposited to the ProteomeXchange Consortium (http://www.proteomexchange.org) via the PRIDE partner repository with dataset identifiers PRIDE: PXD004171 and doi:10.6019/PXD004171. Protein ratio values representing PANTG/wild-type obtained by MaxQuant analysis were input into the Perseus processing suite to determine statistical significance using the Significance A outlier test (p<0.05). Differentially expressed proteins using this approach were input into Ingenuity Pathway Analysis to determined altered pathways and upstream regulators that were altered in PANTG mice.

Evaluation of different multidimensional LC-MS/MS pipelines for iTRAQ-based proteomic analysis of potato tubers in response to cold storage

USDA-ARS?s Scientific Manuscript database

Cold-induced sweetening in potato tubers is a costly problem for food industry. To systematically identify the proteins associated with this process, we employed a comparative proteomics approach using isobaric, stable isotope coded labels to compare the proteomes of potato tubers after 0 and 5 mont...

Advanced proteomic liquid chromatography

PubMed Central

Xie, Fang; Smith, Richard D.; Shen, Yufeng

2012-01-01

Liquid chromatography coupled with mass spectrometry is the predominant platform used to analyze proteomics samples consisting of large numbers of proteins and their proteolytic products (e.g., truncated polypeptides) and spanning a wide range of relative concentrations. This review provides an overview of advanced capillary liquid chromatography techniques and methodologies that greatly improve separation resolving power and proteomics analysis coverage, sensitivity, and throughput. PMID:22840822

Rice proteome database: a step toward functional analysis of the rice genome.

PubMed

Komatsu, Setsuko

2005-09-01

The technique of proteome analysis using two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) has the power to monitor global changes that occur in the protein complement of tissues and subcellular compartments. In this study, the proteins of rice were cataloged, a rice proteome database was constructed, and a functional characterization of some of the identified proteins was undertaken. Proteins extracted from various tissues and subcellular compartments in rice were separated by 2D-PAGE and an image analyzer was used to construct a display of the proteins. The Rice Proteome Database contains 23 reference maps based on 2D-PAGE of proteins from various rice tissues and subcellular compartments. These reference maps comprise 13129 identified proteins, and the amino acid sequences of 5092 proteins are entered in the database. Major proteins involved in growth or stress responses were identified using the proteome approach. Some of these proteins, including a beta-tubulin, calreticulin, and ribulose-1,5-bisphosphate carboxylase/oxygenase activase in rice, have unexpected functions. The information obtained from the Rice Proteome Database will aid in cloning the genes for and predicting the function of unknown proteins.

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

Tentacle Transcriptome and Venom Proteome of the Pacific Sea Nettle, Chrysaora fuscescens (Cnidaria: Scyphozoa).

PubMed

Ponce, Dalia; Brinkman, Diane L; Potriquet, Jeremy; Mulvenna, Jason

2016-04-05

Jellyfish venoms are rich sources of toxins designed to capture prey or deter predators, but they can also elicit harmful effects in humans. In this study, an integrated transcriptomic and proteomic approach was used to identify putative toxins and their potential role in the venom of the scyphozoan jellyfish Chrysaora fuscescens. A de novo tentacle transcriptome, containing more than 23,000 contigs, was constructed and used in proteomic analysis of C. fuscescens venom to identify potential toxins. From a total of 163 proteins identified in the venom proteome, 27 were classified as putative toxins and grouped into six protein families: proteinases, venom allergens, C-type lectins, pore-forming toxins, glycoside hydrolases and enzyme inhibitors. Other putative toxins identified in the transcriptome, but not the proteome, included additional proteinases as well as lipases and deoxyribonucleases. Sequence analysis also revealed the presence of ShKT domains in two putative venom proteins from the proteome and an additional 15 from the transcriptome, suggesting potential ion channel blockade or modulatory activities. Comparison of these potential toxins to those from other cnidarians provided insight into their possible roles in C. fuscescens venom and an overview of the diversity of potential toxin families in cnidarian venoms.

UNiquant, a program for quantitative proteomics analysis using stable isotope labeling.

PubMed

Huang, Xin; Tolmachev, Aleksey V; Shen, Yulei; Liu, Miao; Huang, Lin; Zhang, Zhixin; Anderson, Gordon A; Smith, Richard D; Chan, Wing C; Hinrichs, Steven H; Fu, Kai; Ding, Shi-Jian

2011-03-04

Stable isotope labeling (SIL) methods coupled with nanoscale liquid chromatography and high resolution tandem mass spectrometry are increasingly useful for elucidation of the proteome-wide differences between multiple biological samples. Development of more effective programs for the sensitive identification of peptide pairs and accurate measurement of the relative peptide/protein abundance are essential for quantitative proteomic analysis. We developed and evaluated the performance of a new program, termed UNiquant, for analyzing quantitative proteomics data using stable isotope labeling. UNiquant was compared with two other programs, MaxQuant and Mascot Distiller, using SILAC-labeled complex proteome mixtures having either known or unknown heavy/light ratios. For the SILAC-labeled Jeko-1 cell proteome digests with known heavy/light ratios (H/L = 1:1, 1:5, and 1:10), UNiquant quantified a similar number of peptide pairs as MaxQuant for the H/L = 1:1 and 1:5 mixtures. In addition, UNiquant quantified significantly more peptides than MaxQuant and Mascot Distiller in the H/L = 1:10 mixtures. UNiquant accurately measured relative peptide/protein abundance without the need for postmeasurement normalization of peptide ratios, which is required by the other programs.

UNiquant, a Program for Quantitative Proteomics Analysis Using Stable Isotope Labeling

PubMed Central

Huang, Xin; Tolmachev, Aleksey V.; Shen, Yulei; Liu, Miao; Huang, Lin; Zhang, Zhixin; Anderson, Gordon A.; Smith, Richard D.; Chan, Wing C.; Hinrichs, Steven H.; Fu, Kai; Ding, Shi-Jian

2011-01-01

Stable isotope labeling (SIL) methods coupled with nanoscale liquid chromatography and high resolution tandem mass spectrometry are increasingly useful for elucidation of the proteome-wide differences between multiple biological samples. Development of more effective programs for the sensitive identification of peptide pairs and accurate measurement of the relative peptide/protein abundance are essential for quantitative proteomic analysis. We developed and evaluated the performance of a new program, termed UNiquant, for analyzing quantitative proteomics data using stable isotope labeling. UNiquant was compared with two other programs, MaxQuant and Mascot Distiller, using SILAC-labeled complex proteome mixtures having either known or unknown heavy/light ratios. For the SILAC-labeled Jeko-1 cell proteome digests with known heavy/light ratios (H/L = 1:1, 1:5, and 1:10), UNiquant quantified a similar number of peptide pairs as MaxQuant for the H/L = 1:1 and 1:5 mixtures. In addition, UNiquant quantified significantly more peptides than MaxQuant and Mascot Distiller in the H/L = 1:10 mixtures. UNiquant accurately measured relative peptide/protein abundance without the need for post-measurement normalization of peptide ratios, which is required by the other programs. PMID:21158445

Proteomic Analysis of the Human Skin Proteome after In Vivo Treatment with Sodium Dodecyl Sulphate

PubMed Central

Parkinson, Erika; Skipp, Paul; Aleksic, Maja; Garrow, Andrew; Dadd, Tony; Hughes, Michael; Clough, Geraldine; O′Connor, C. David

2014-01-01

Background Skin has a variety of functions that are incompletely understood at the molecular level. As the most accessible tissue in the body it often reveals the first signs of inflammation or infection and also represents a potentially valuable source of biomarkers for several diseases. In this study we surveyed the skin proteome qualitatively using gel electrophoresis, liquid chromatography tandem mass spectrometry (GeLC-MS/MS) and quantitatively using an isobaric tagging strategy (iTRAQ) to characterise the response of human skin following exposure to sodium dodecyl sulphate (SDS). Results A total of 653 skin proteins were assigned, 159 of which were identified using GeLC-MS/MS and 616 using iTRAQ, representing the most comprehensive proteomic study in human skin tissue. Statistical analysis of the available iTRAQ data did not reveal any significant differences in the measured skin proteome after 4 hours exposure to the model irritant SDS. Conclusions This study represents the first step in defining the critical response to an irritant at the level of the proteome and provides a valuable resource for further studies at the later stages of irritant exposure. PMID:24849295

Comparative proteomics analysis of placenta from pregnant women with intrahepatic cholestasis of pregnancy.

PubMed

Zhang, Ting; Guo, Yueshuai; Guo, Xuejiang; Zhou, Tao; Chen, Daozhen; Xiang, Jingying; Zhou, Zuomin

2013-01-01

Intrahepatic cholestasis of pregnancy (ICP) usually occurs in the third trimester and associated with increased risks in fetal complications. Currently, the exact cause of this disease is unknown. In this study we aim to investigate the potential proteins in placenta, which may participate in the molecular mechanisms of ICP-related fetal complications using iTRAQ-based proteomics approach. The iTRAQ analysis combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS) was performed to separate differentially expressed placental proteins from 4 pregnant women with ICP and 4 healthy pregnant women. Bioinformatics analysis was used to find the relative processes that these differentially expressed proteins were involved in. Three apoptosis related proteins ERp29, PRDX6 and MPO that resulted from iTRAQ-based proteomics were further verified in placenta by Western blotting and immunohistochemistry. Placental apoptosis was also detected by TUNEL assay. Proteomics results showed there were 38 differentially expressed proteins from pregnant women with ICP and healthy pregnant women, 29 were upregulated and 9 were downregulated in placenta from pregnant women with ICP. Bioinformatics analysis showed most of the identified proteins was functionally related to specific cell processes, including apoptosis, oxidative stress, lipid metabolism. The expression levels of ERp29, PRDX6 and MPO were consistent with the proteomics data. The apoptosis index in placenta from ICP patients was significantly increased. This preliminary work provides a better understanding of the proteomic alterations of placenta from pregnant women with ICP and may provide us some new insights into the pathophysiology and potential novel treatment targets for ICP.

Proteomic approaches to understanding the role of the cytoskeleton in host-defense mechanisms

PubMed Central

Radulovic, Marko; Godovac-Zimmermann, Jasminka

2014-01-01

The cytoskeleton is a cellular scaffolding system whose functions include maintenance of cellular shape, enabling cellular migration, division, intracellular transport, signaling and membrane organization. In addition, in immune cells, the cytoskeleton is essential for phagocytosis. Following the advances in proteomics technology over the past two decades, cytoskeleton proteome analysis in resting and activated immune cells has emerged as a possible powerful approach to expand our understanding of cytoskeletal composition and function. However, so far there have only been a handful of studies of the cytoskeleton proteome in immune cells. This article considers promising proteomics strategies that could augment our understanding of the role of the cytoskeleton in host-defense mechanisms. PMID:21329431

The UniProtKB guide to the human proteome

PubMed Central

Breuza, Lionel; Poux, Sylvain; Estreicher, Anne; Famiglietti, Maria Livia; Magrane, Michele; Tognolli, Michael; Bridge, Alan; Baratin, Delphine; Redaschi, Nicole

2016-01-01

Advances in high-throughput and advanced technologies allow researchers to routinely perform whole genome and proteome analysis. For this purpose, they need high-quality resources providing comprehensive gene and protein sets for their organisms of interest. Using the example of the human proteome, we will describe the content of a complete proteome in the UniProt Knowledgebase (UniProtKB). We will show how manual expert curation of UniProtKB/Swiss-Prot is complemented by expert-driven automatic annotation to build a comprehensive, high-quality and traceable resource. We will also illustrate how the complexity of the human proteome is captured and structured in UniProtKB. Database URL: www.uniprot.org PMID:26896845

Proteomic approaches in cancer risk and response assessment.

PubMed

Petricoin, Emanuel F; Liotta, Lance A

2004-02-01

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

A-to-I RNA Editing Contributes to Proteomic Diversity in Cancer. | Office of Cancer Genomics

Cancer.gov

Adenosine (A) to inosine (I) RNA editing introduces many nucleotide changes in cancer transcriptomes. However, due to the complexity of post-transcriptional regulation, the contribution of RNA editing to proteomic diversity in human cancers remains unclear. Here, we performed an integrated analysis of TCGA genomic data and CPTAC proteomic data. Despite limited site diversity, we demonstrate that A-to-I RNA editing contributes to proteomic diversity in breast cancer through changes in amino acid sequences. We validate the presence of editing events at both RNA and protein levels.

Comparison of sample preparation techniques and data analysis for the LC-MS/MS-based identification of proteins in human follicular fluid.

PubMed

Lehmann, Roland; Schmidt, André; Pastuschek, Jana; Müller, Mario M; Fritzsche, Andreas; Dieterle, Stefan; Greb, Robert R; Markert, Udo R; Slevogt, Hortense

2018-06-25

The proteomic analysis of complex body fluids by liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis requires the selection of suitable sample preparation techniques and optimal parameter settings in data analysis software packages to obtain reliable results. Proteomic analysis of follicular fluid, as a representative of a complex body fluid similar to serum or plasma, is difficult as it contains a vast amount of high abundant proteins and a variety of proteins with different concentrations. However, the accessibility of this complex body fluid for LC-MS/MS analysis is an opportunity to gain insights into the status, the composition of fertility-relevant proteins including immunological factors or for the discovery of new diagnostic and prognostic markers for, for example, the treatment of infertility. In this study, we compared different sample preparation methods (FASP, eFASP and in-solution digestion) and three different data analysis software packages (Proteome Discoverer with SEQUEST, Mascot and MaxQuant with Andromeda) combined with semi- and full-tryptic databank search options to obtain a maximum coverage of the follicular fluid proteome. We found that the most comprehensive proteome coverage is achieved by the eFASP sample preparation method using SDS in the initial denaturing step and the SEQUEST-based semi-tryptic data analysis. In conclusion, we have developed a fractionation-free methodical workflow for in depth LC-MS/MS-based analysis for the standardized investigation of human follicle fluid as an important representative of a complex body fluid. Taken together, we were able to identify a total of 1392 proteins in follicular fluid. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Proteomic and Bioinformatic Profile of Primary Human Oral Epithelial Cells

PubMed Central

Ghosh, Santosh K.; Yohannes, Elizabeth; Bebek, Gurkan; Weinberg, Aaron; Jiang, Bin; Willard, Belinda; Chance, Mark R.; Kinter, Michael T.; McCormick, Thomas S.

2012-01-01

Wounding of the oral mucosa occurs frequently in a highly septic environment. Remarkably, these wounds heal quickly and the oral cavity, for the most part, remains healthy. Deciphering the normal human oral epithelial cell (NHOEC) proteome is critical for understanding the mechanism(s) of protection elicited when the mucosal barrier is intact, as well as when it is breached. Combining 2D gel electrophoresis with shotgun proteomics resulted in identification of 1662 NHOEC proteins. Proteome annotations were performed based on protein classes, molecular functions, disease association and membership in canonical and metabolic signaling pathways. Comparing the NHOEC proteome with a database of innate immunity-relevant interactions (InnateDB) identified 64 common proteins associated with innate immunity. Comparison with published salivary proteomes revealed that 738/1662 NHOEC proteins were common, suggesting that significant numbers of salivary proteins are of epithelial origin. Gene ontology analysis showed similarities in the distributions of NHOEC and saliva proteomes with regard to biological processes, and molecular functions. We also assessed the inter-individual variability of the NHOEC proteome and observed it to be comparable with other primary cells. The baseline proteome described in this study should serve as a resource for proteome studies of the oral mucosa, especially in relation to disease processes. PMID:23035736

The application of proteomics in different aspects of hepatocellular carcinoma research.

PubMed

Xing, Xiaohua; Liang, Dong; Huang, Yao; Zeng, Yongyi; Han, Xiao; Liu, Xiaolong; Liu, Jingfeng

2016-08-11

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors, which is causing the second leading cancer-related death worldwide. With the significant advances of high-throughput protein analysis techniques, the proteomics offered an extremely useful and versatile analytical platform for biomedical researches. In recent years, different proteomic strategies have been widely applied in the various aspects of HCC studies, ranging from screening the early diagnostic and prognostic biomarkers to in-depth investigating the underlying molecular mechanisms. In this review, we would like to systematically summarize the current applications of proteomics in hepatocellular carcinoma study, and discuss the challenges of applying proteomics in study clinical samples, as well as discuss the possible application of proteomics in precision medicine. In this review, we have systematically summarized the current applications of proteomics in hepatocellular carcinoma study, ranging from screening biomarkers to in-depth investigating the underlying molecular mechanisms. In addition, we have discussed the challenges of applying proteomics in study clinical samples, as well as the possible applications of proteomics in precision medicine. We believe that this review would help readers to be better familiar with the recent progresses of clinical proteomics, especially in the field of hepatocellular carcinoma research. Copyright © 2016 Elsevier B.V. All rights reserved.

Introducing the CPL/MUW proteome database: interpretation of human liver and liver cancer proteome profiles by referring to isolated primary cells.

PubMed

Wimmer, Helge; Gundacker, Nina C; Griss, Johannes; Haudek, Verena J; Stättner, Stefan; Mohr, Thomas; Zwickl, Hannes; Paulitschke, Verena; Baron, David M; Trittner, Wolfgang; Kubicek, Markus; Bayer, Editha; Slany, Astrid; Gerner, Christopher

2009-06-01

Interpretation of proteome data with a focus on biomarker discovery largely relies on comparative proteome analyses. Here, we introduce a database-assisted interpretation strategy based on proteome profiles of primary cells. Both 2-D-PAGE and shotgun proteomics are applied. We obtain high data concordance with these two different techniques. When applying mass analysis of tryptic spot digests from 2-D gels of cytoplasmic fractions, we typically identify several hundred proteins. Using the same protein fractions, we usually identify more than thousand proteins by shotgun proteomics. The data consistency obtained when comparing these independent data sets exceeds 99% of the proteins identified in the 2-D gels. Many characteristic differences in protein expression of different cells can thus be independently confirmed. Our self-designed SQL database (CPL/MUW - database of the Clinical Proteomics Laboratories at the Medical University of Vienna accessible via www.meduniwien.ac.at/proteomics/database) facilitates (i) quality management of protein identification data, which are based on MS, (ii) the detection of cell type-specific proteins and (iii) of molecular signatures of specific functional cell states. Here, we demonstrate, how the interpretation of proteome profiles obtained from human liver tissue and hepatocellular carcinoma tissue is assisted by the Clinical Proteomics Laboratories at the Medical University of Vienna-database. Therefore, we suggest that the use of reference experiments supported by a tailored database may substantially facilitate data interpretation of proteome profiling experiments.

Polyphemus, Odysseus and the ovine milk proteome.

PubMed

Cunsolo, Vincenzo; Fasoli, Elisa; Di Francesco, Antonella; Saletti, Rosaria; Muccilli, Vera; Gallina, Serafina; Righetti, Pier Giorgio; Foti, Salvatore

2017-01-30

In the last years the amount of ovine milk production, mainly used to formulate a wide range of different and exclusive dairy products often categorized as gourmet food, has been progressively increasing. Taking also into account that sheep milk (SM) also appears to be potentially less allergenic than cow's one, an in-depth information about its protein composition is essential to improve the comprehension of its potential benefits for human consumption. The present work reports the results of an in-depth characterization of SM whey proteome, carried out by coupling the CPLL technology with SDS-PAGE and high resolution UPLC-nESI MS/MS analysis. This approach allowed the identification of 718 different protein components, 644 of which are from unique genes. Particularly, this identification has expanded literature data about sheep whey proteome by 193 novel proteins previously undetected, many of which are involved in the defence/immunity mechanisms or in the nutrient delivery system. A comparative analysis of SM proteome known to date with cow's milk proteome, evidenced that while about 29% of SM proteins are also present in CM, 71% of the identified components appear to be unique of SM proteome and include a heterogeneous group of components which seem to have health-promoting benefits. The data have been deposited to the ProteomeXchange with identifier . Copyright © 2016 Elsevier B.V. All rights reserved.

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

Proteomic analysis of hyperadhesive Candida glabrata clinical isolates reveals a core wall proteome and differential incorporation of adhesins.

PubMed

Gómez-Molero, Emilia; de Boer, Albert D; Dekker, Henk L; Moreno-Martínez, Ana; Kraneveld, Eef A; Ichsan; Chauhan, Neeraj; Weig, Michael; de Soet, Johannes J; de Koster, Chris G; Bader, Oliver; de Groot, Piet W J

2015-12-01

Attachment to human host tissues or abiotic medical devices is a key step in the development of infections by Candida glabrata. The genome of this pathogenic yeast codes for a large number of adhesins, but proteomic work using reference strains has shown incorporation of only few adhesins in the cell wall. By making inventories of the wall proteomes of hyperadhesive clinical isolates and reference strain CBS138 using mass spectrometry, we describe the cell wall proteome of C. glabrata and tested the hypothesis that hyperadhesive isolates display differential incorporation of adhesins. Two clinical strains (PEU382 and PEU427) were selected, which both were hyperadhesive to polystyrene and showed high surface hydrophobicity. Cell wall proteome analysis under biofilm-forming conditions identified a core proteome of about 20 proteins present in all C. glabrata strains. In addition, 12 adhesin-like wall proteins were identified in the hyperadherent strains, including six novel adhesins (Awp8-13) of which only Awp12 was also present in CBS138. We conclude that the hyperadhesive capacity of these two clinical C. glabrata isolates is correlated with increased and differential incorporation of cell wall adhesins. Future studies should elucidate the role of the identified proteins in the establishment of C. glabrata infections. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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.

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

PubMed Central

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

2011-01-01

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

Time-resolved Global and Chromatin Proteomics during Herpes Simplex Virus Type 1 (HSV-1) Infection.

PubMed

Kulej, Katarzyna; Avgousti, Daphne C; Sidoli, Simone; Herrmann, Christin; Della Fera, Ashley N; Kim, Eui Tae; Garcia, Benjamin A; Weitzman, Matthew D

2017-04-01

Herpes simplex virus (HSV-1) lytic infection results in global changes to the host cell proteome and the proteins associated with host chromatin. We present a system level characterization of proteome dynamics during infection by performing a multi-dimensional analysis during HSV-1 lytic infection of human foreskin fibroblast (HFF) cells. Our study includes identification and quantification of the host and viral proteomes, phosphoproteomes, chromatin bound proteomes and post-translational modifications (PTMs) on cellular histones during infection. We analyzed proteomes across six time points of virus infection (0, 3, 6, 9, 12 and 15 h post-infection) and clustered trends in abundance using fuzzy c-means. Globally, we accurately quantified more than 4000 proteins, 200 differently modified histone peptides and 9000 phosphorylation sites on cellular proteins. In addition, we identified 67 viral proteins and quantified 571 phosphorylation events (465 with high confidence site localization) on viral proteins, which is currently the most comprehensive map of HSV-1 phosphoproteome. We investigated chromatin bound proteins by proteomic analysis of the high-salt chromatin fraction and identified 510 proteins that were significantly different in abundance during infection. We found 53 histone marks significantly regulated during virus infection, including a steady increase of histone H3 acetylation (H3K9ac and H3K14ac). Our data provide a resource of unprecedented depth for human and viral proteome dynamics during infection. Collectively, our results indicate that the proteome composition of the chromatin of HFF cells is highly affected during HSV-1 infection, and that phosphorylation events are abundant on viral proteins. We propose that our epi-proteomics approach will prove to be important in the characterization of other model infectious systems that involve changes to chromatin composition. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Statistical Methods for Proteomic Biomarker Discovery based on Feature Extraction or Functional Modeling Approaches.

PubMed

Morris, Jeffrey S

2012-01-01

In recent years, developments in molecular biotechnology have led to the increased promise of detecting and validating biomarkers, or molecular markers that relate to various biological or medical outcomes. Proteomics, the direct study of proteins in biological samples, plays an important role in the biomarker discovery process. These technologies produce complex, high dimensional functional and image data that present many analytical challenges that must be addressed properly for effective comparative proteomics studies that can yield potential biomarkers. Specific challenges include experimental design, preprocessing, feature extraction, and statistical analysis accounting for the inherent multiple testing issues. This paper reviews various computational aspects of comparative proteomic studies, and summarizes contributions I along with numerous collaborators have made. First, there is an overview of comparative proteomics technologies, followed by a discussion of important experimental design and preprocessing issues that must be considered before statistical analysis can be done. Next, the two key approaches to analyzing proteomics data, feature extraction and functional modeling, are described. Feature extraction involves detection and quantification of discrete features like peaks or spots that theoretically correspond to different proteins in the sample. After an overview of the feature extraction approach, specific methods for mass spectrometry ( Cromwell ) and 2D gel electrophoresis ( Pinnacle ) are described. The functional modeling approach involves modeling the proteomic data in their entirety as functions or images. A general discussion of the approach is followed by the presentation of a specific method that can be applied, wavelet-based functional mixed models, and its extensions. All methods are illustrated by application to two example proteomic data sets, one from mass spectrometry and one from 2D gel electrophoresis. While the specific methods presented are applied to two specific proteomic technologies, MALDI-TOF and 2D gel electrophoresis, these methods and the other principles discussed in the paper apply much more broadly to other expression proteomics technologies.

MALDI-TOF MS of Trichoderma: A model system for the identification of microfungi

USDA-ARS?s Scientific Manuscript database

This investigation aimed to assess whether MALDI-TOF MS analysis of proteomics could be applied to the study of Trichoderma, a fungal genus selected because it includes many species and is phylogenetically well defined. We also investigated whether MALDI-TOF MS analysis of proteomics would reveal ap...

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

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.

iAB-RBC-283: A proteomically derived knowledge-base of erythrocyte metabolism that can be used to simulate its physiological and patho-physiological states.

PubMed

Bordbar, Aarash; Jamshidi, Neema; Palsson, Bernhard O

2011-07-12

The development of high-throughput technologies capable of whole cell measurements of genes, proteins, and metabolites has led to the emergence of systems biology. Integrated analysis of the resulting omic data sets has proved to be hard to achieve. Metabolic network reconstructions enable complex relationships amongst molecular components to be represented formally in a biologically relevant manner while respecting physical constraints. In silico models derived from such reconstructions can then be queried or interrogated through mathematical simulations. Proteomic profiling studies of the mature human erythrocyte have shown more proteins present related to metabolic function than previously thought; however the significance and the causal consequences of these findings have not been explored. Erythrocyte proteomic data was used to reconstruct the most expansive description of erythrocyte metabolism to date, following extensive manual curation, assessment of the literature, and functional testing. The reconstruction contains 281 enzymes representing functions from glycolysis to cofactor and amino acid metabolism. Such a comprehensive view of erythrocyte metabolism implicates the erythrocyte as a potential biomarker for different diseases as well as a 'cell-based' drug-screening tool. The analysis shows that 94 erythrocyte enzymes are implicated in morbid single nucleotide polymorphisms, representing 142 pathologies. In addition, over 230 FDA-approved and experimental pharmaceuticals have enzymatic targets in the erythrocyte. The advancement of proteomic technologies and increased generation of high-throughput proteomic data have created the need for a means to analyze these data in a coherent manner. Network reconstructions provide a systematic means to integrate and analyze proteomic data in a biologically meaning manner. Analysis of the red cell proteome has revealed an unexpected level of complexity in the functional capabilities of human erythrocyte metabolism.

Proteomic approaches in brain research and neuropharmacology.

PubMed

Vercauteren, Freya G G; Bergeron, John J M; Vandesande, Frans; Arckens, Lut; Quirion, Rémi

2004-10-01

Numerous applications of genomic technologies have enabled the assembly of unprecedented inventories of genes, expressed in cells under specific physiological and pathophysiological conditions. Complementing the valuable information generated through functional genomics with the integrative knowledge of protein expression and function should enable the development of more efficient diagnostic tools and therapeutic agents. Proteomic analyses are particularly suitable to elucidate posttranslational modifications, expression levels and protein-protein interactions of thousands of proteins at a time. In this review, two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) investigations of brain tissues in neurodegenerative diseases such as Alzheimer's disease, Down syndrome and schizophrenia, and the construction of 2D-PAGE proteome maps of the brain are discussed. The role of the Human Proteome Organization (HUPO) as an international coordinating organization for proteomic efforts, as well as challenges for proteomic technologies and data analysis are also addressed. It is expected that the use of proteomic strategies will have significant impact in neuropharmacology over the coming decade.

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

PubMed Central

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

2012-01-01

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

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.

How many proteins can be identified in a 2DE gel spot within an analysis of a complex human cancer tissue proteome?

PubMed

Zhan, Xianquan; Yang, Haiyan; Peng, Fang; Li, Jianglin; Mu, Yun; Long, Ying; Cheng, Tingting; Huang, Yuda; Li, Zhao; Lu, Miaolong; Li, Na; Li, Maoyu; Liu, Jianping; Jungblut, Peter R

2018-04-01

Two-dimensional gel electrophoresis (2DE) in proteomics is traditionally assumed to contain only one or two proteins in each 2DE spot. However, 2DE resolution is being complemented by the rapid development of high sensitivity mass spectrometers. Here we compared MALDI-MS, LC-Q-TOF MS and LC-Orbitrap Velos MS for the identification of proteins within one spot. With LC-Orbitrap Velos MS each Coomassie Blue-stained 2DE spot contained an average of at least 42 and 63 proteins/spot in an analysis of a human glioblastoma proteome and a human pituitary adenoma proteome, respectively, if a single gel spot was analyzed. If a pool of three matched gel spots was analyzed this number further increased up to an average of 230 and 118 proteins/spot for glioblastoma and pituitary adenoma proteome, respectively. Multiple proteins per spot confirm the necessity of isotopic labeling in large-scale quantification of different protein species in a proteome. Furthermore, a protein abundance analysis revealed that most of the identified proteins in each analyzed 2DE spot were low-abundance proteins. Many proteins were present in several of the analyzed spots showing the ability of 2DE-MS to separate at the protein species level. Therefore, 2DE coupled with high-sensitivity LC-MS has a clearly higher sensitivity as expected until now to detect, identify and quantify low abundance proteins in a complex human proteome with an estimated resolution of about 500 000 protein species. This clearly exceeds the resolution power of bottom-up LC-MS investigations. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

On the use and misuse of scalar scores of confounders in design and analysis of observational studies.

PubMed

Pfeiffer, R M; Riedl, R

2015-08-15

We assess the asymptotic bias of estimates of exposure effects conditional on covariates when summary scores of confounders, instead of the confounders themselves, are used to analyze observational data. First, we study regression models for cohort data that are adjusted for summary scores. Second, we derive the asymptotic bias for case-control studies when cases and controls are matched on a summary score, and then analyzed either using conditional logistic regression or by unconditional logistic regression adjusted for the summary score. Two scores, the propensity score (PS) and the disease risk score (DRS) are studied in detail. For cohort analysis, when regression models are adjusted for the PS, the estimated conditional treatment effect is unbiased only for linear models, or at the null for non-linear models. Adjustment of cohort data for DRS yields unbiased estimates only for linear regression; all other estimates of exposure effects are biased. Matching cases and controls on DRS and analyzing them using conditional logistic regression yields unbiased estimates of exposure effect, whereas adjusting for the DRS in unconditional logistic regression yields biased estimates, even under the null hypothesis of no association. Matching cases and controls on the PS yield unbiased estimates only under the null for both conditional and unconditional logistic regression, adjusted for the PS. We study the bias for various confounding scenarios and compare our asymptotic results with those from simulations with limited sample sizes. To create realistic correlations among multiple confounders, we also based simulations on a real dataset. Copyright © 2015 John Wiley & Sons, Ltd.

CPTAC Launches Proteomics Data Portal | Office of Cancer Clinical Proteomics Research

Cancer.gov

The National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) announces the launch of the CPTAC Data Portal. The Data Portal hosts all the data that is currently being produced by the consortium with additional historic data from CPTAC 1. The total amount of hosted data exceeds over 500 GB of RAW data in over 800 files.

Comprehensive Proteomic Analysis of Human Milk-derived Extracellular Vesicles Unveils a Novel Functional Proteome Distinct from Other Milk Components.

PubMed

van Herwijnen, Martijn J C; Zonneveld, Marijke I; Goerdayal, Soenita; Nolte-'t Hoen, Esther N M; Garssen, Johan; Stahl, Bernd; Maarten Altelaar, A F; Redegeld, Frank A; Wauben, Marca H M

2016-11-01

Breast milk contains several macromolecular components with distinctive functions, whereby milk fat globules and casein micelles mainly provide nutrition to the newborn, and whey contains molecules that can stimulate the newborn's developing immune system and gastrointestinal tract. Although extracellular vesicles (EV) have been identified in breast milk, their physiological function and composition has not been addressed in detail. EV are submicron sized vehicles released by cells for intercellular communication via selectively incorporated lipids, nucleic acids, and proteins. Because of the difficulty in separating EV from other milk components, an in-depth analysis of the proteome of human milk-derived EV is lacking. In this study, an extensive LC-MS/MS proteomic analysis was performed of EV that had been purified from breast milk of seven individual donors using a recently established, optimized density-gradient-based EV isolation protocol. A total of 1963 proteins were identified in milk-derived EV, including EV-associated proteins like CD9, Annexin A5, and Flotillin-1, with a remarkable overlap between the different donors. Interestingly, 198 of the identified proteins are not present in the human EV database Vesiclepedia, indicating that milk-derived EV harbor proteins not yet identified in EV of different origin. Similarly, the proteome of milk-derived EV was compared with that of other milk components. For this, data from 38 published milk proteomic studies were combined in order to construct the total milk proteome, which consists of 2698 unique proteins. Remarkably, 633 proteins identified in milk-derived EV have not yet been identified in human milk to date. Interestingly, these novel proteins include proteins involved in regulation of cell growth and controlling inflammatory signaling pathways, suggesting that milk-derived EVs could support the newborn's developing gastrointestinal tract and immune system. Overall, this study provides an expansion of the whole milk proteome and illustrates that milk-derived EV are macromolecular components with a unique functional proteome. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Proteome-wide analysis of Anopheles culicifacies mosquito midgut: new insights into the mechanism of refractoriness.

PubMed

Vijay, Sonam; Rawal, Ritu; Kadian, Kavita; Singh, Jagbir; Adak, Tridibesh; Sharma, Arun

2018-05-08

Midgut invasion, a major bottleneck for malaria parasites transmission is considered as a potential target for vector-parasite interaction studies. New intervention strategies are required to explore the midgut proteins and their potential role in refractoriness for malaria control in Anopheles mosquitoes. To better understand the midgut functional proteins of An. culicifacies susceptible and refractory species, proteomic approaches coupled with bioinformatics analysis is an effective means in order to understand the mechanism of refractoriness. In the present study, an integrated in solution- in gel trypsin digestion approach, along with Isobaric tag for relative and absolute quantitation (iTRAQ)-Liquid chromatography/Mass spectrometry (LC/MS/MS) and data mining were performed to identify the proteomic profile and differentially expressed proteins in Anopheles culicifacies susceptible species A and refractory species B. Shot gun proteomics approaches led to the identification of 80 proteins in An. culicifacies susceptible species A and 92 in refractory species B and catalogue was prepared. iTRAQ based proteomic analysis identified 48 differentially expressed proteins from total 130 proteins. Of these, 41 were downregulated and 7 were upregulated in refractory species B in comparison to susceptible species A. We report that the altered midgut proteins identified in naturally refractory mosquitoes are involved in oxidative phosphorylation, antioxidant and proteolysis process that may suggest their role in parasite growth inhibition. Furthermore, real time polymerase chain reaction (PCR) analysis of few proteins indicated higher expression of iTRAQ upregulated protein in refractory species than susceptible species. This study elucidates the first proteome of the midguts of An. culicifacies sibling species that attempts to analyze unique proteogenomic interactions to provide insights for better understanding of the mechanism of refractoriness. Functional implications of these upregulated proteins in refractory species may reflect the phenotypic characteristics of the mosquitoes and will improve our understandings of blood meal digestion process, parasite vector interactions and proteomes of other vectors of human diseases for development of novel vector control strategies.

An Automatic Method for Generating an Unbiased Intensity Normalizing Factor in Positron Emission Tomography Image Analysis After Stroke.

PubMed

Nie, Binbin; Liang, Shengxiang; Jiang, Xiaofeng; Duan, Shaofeng; Huang, Qi; Zhang, Tianhao; Li, Panlong; Liu, Hua; Shan, Baoci

2018-06-07

Positron emission tomography (PET) imaging of functional metabolism has been widely used to investigate functional recovery and to evaluate therapeutic efficacy after stroke. The voxel intensity of a PET image is the most important indicator of cellular activity, but is affected by other factors such as the basal metabolic ratio of each subject. In order to locate dysfunctional regions accurately, intensity normalization by a scale factor is a prerequisite in the data analysis, for which the global mean value is most widely used. However, this is unsuitable for stroke studies. Alternatively, a specified scale factor calculated from a reference region is also used, comprising neither hyper- nor hypo-metabolic voxels. But there is no such recognized reference region for stroke studies. Therefore, we proposed a totally data-driven automatic method for unbiased scale factor generation. This factor was generated iteratively until the residual deviation of two adjacent scale factors was reduced by < 5%. Moreover, both simulated and real stroke data were used for evaluation, and these suggested that our proposed unbiased scale factor has better sensitivity and accuracy for stroke studies.

Active site specificity profiling datasets of matrix metalloproteinases (MMPs) 1, 2, 3, 7, 8, 9, 12, 13 and 14.

PubMed

Eckhard, Ulrich; Huesgen, Pitter F; Schilling, Oliver; Bellac, Caroline L; Butler, Georgina S; Cox, Jennifer H; Dufour, Antoine; Goebeler, Verena; Kappelhoff, Reinhild; Auf dem Keller, Ulrich; Klein, Theo; Lange, Philipp F; Marino, Giada; Morrison, Charlotte J; Prudova, Anna; Rodriguez, David; Starr, Amanda E; Wang, Yili; Overall, Christopher M

2016-06-01

The data described provide a comprehensive resource for the family-wide active site specificity portrayal of the human matrix metalloproteinase family. We used the high-throughput proteomic technique PICS (Proteomic Identification of protease Cleavage Sites) to comprehensively assay 9 different MMPs. We identified more than 4300 peptide cleavage sites, spanning both the prime and non-prime sides of the scissile peptide bond allowing detailed subsite cooperativity analysis. The proteomic cleavage data were expanded by kinetic analysis using a set of 6 quenched-fluorescent peptide substrates designed using these results. These datasets represent one of the largest specificity profiling efforts with subsequent structural follow up for any protease family and put the spotlight on the specificity similarities and differences of the MMP family. A detailed analysis of this data may be found in Eckhard et al. (2015) [1]. The raw mass spectrometry data and the corresponding metadata have been deposited in PRIDE/ProteomeXchange with the accession number PXD002265.

Isolation and proteomic analysis of Chlamydomonas centrioles.

PubMed

Keller, Lani C; Marshall, Wallace F

2008-01-01

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

Comparative Proteome Analysis between High Lipid-Producing Strain Mucor circinelloides WJ11 and Low Lipid-Producing Strain CBS 277.49.

PubMed

Tang, Xin; Chen, Haiqin; Gu, Zhennan; Zhang, Hao; Chen, Yong Q; Song, Yuanda; Chen, Wei

2017-06-21

Mucor circinelloides is one of few oleaginous fungi that produces a useful oil rich in γ-linolenic acid, but it usually only produces <25% total lipid. Nevertheless, we isolated a new strain WJ11 that can produce up to 36% lipid of cell dry weight. In this study, we have systematically analyzed the global changes in protein levels between the high lipid-producing strain WJ11 and the low lipid-producing strain CBS 277.49 (15%, lipid/cell dry weight) at lipid accumulation phase through comparative proteome analysis. Proteome analysis demonstrated that the branched-chain amino acid and lysine metabolism, glycolytic pathway, and pentose phosphate pathway in WJ11 were up-regulated, while the activities of tricarboxylic acid cycle and branch point enzyme for synthesis of isoprenoids were retarded compared with CBS 277.49. The coordinated regulation at proteome level indicate that more acetyl-CoA and NADPH are provided for fatty acid biosynthesis in WJ11 compared with CBS 277.49.

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 Analysis of Synovial Fluid Obtained From a Dog Diagnosed With Idiopathic Immune-Mediated Polyarthritis.

PubMed

Tan, Wei Miao; Lau, Seng Fong; Ajat, Mokrish; Mansor, Rozaihan; Abd Rani, Puteri Azaziah Megat; Rahmad, Norasfaliza Binti

2017-03-01

This case study is to report the proteins detected by proteomic analysis of synovial fluid from a dog diagnosed with idiopathic immune-mediated polyarthritis, and to compare it with healthy dogs. Synovial fluid was collected via arthrocentesis from a dog diagnosed with immune-mediated polyarthritis. Protein precipitation was performed on the synovial fluid, followed by isoelectric focusing and 2-dimensional gel electrophoresis. The spots on the 2-dimensional gels were analyzed using MALDI-TOF/MS. The results were then analyzed against the MASCOT database. The results from the proteomic analysis revealed an abundance of several types of immunoglobulins together with the presence of complement C4b-binding protein alpha chain. Actin and keratin were also among the proteins detected. Proteomic studies, facilitate a better understanding of the different levels of proteins expressed during disease activity. Potential disease biomarkers can aid in the diagnosis of disease, as well as help in monitoring treatment efficacy and providing prognosis for the patient. Copyright © 2017 Elsevier Inc. All rights reserved.

The Monkey King: a personal view of the long journey towards a proteomic Nirvana.

PubMed

Righetti, Pier Giorgio

2014-07-31

The review covers about fifty years of progress in "proteome" analysis, starting from primitive two-dimensional (2D) map attempts in the early sixties of last century. The polar star in 2D mapping arose in 1975 with the classic paper by O'Farrell in J Biol. Chem. It became the compass for all proteome navigators. Perfection came, though, only with the introduction of immobilized pH gradients, which fixed the polypeptide spots in the 2D plane. Great impetus in proteome analysis came with the introduction of informatic tools and creating databases, among which Swiss Prot remains the site of excellence. Towards the end of the nineties, 2D chromatography, epitomized by coupling strong cation exchangers with C18 resins, began to be a serious challenge to electrophoretic 2D mapping, although up to the present both techniques are still much in vogue and appear to give complementary results. Yet the migration of "proteomics" into the third millennium was made possible only by mass spectrometry (MS), which today represents the standard analytical tool in any lab dealing with proteomic analysis. Another major improvement has been the introduction of combinatorial peptide ligand libraries (CPLL), which, when properly used, enhance the visibility of low-abundance species by 3 to 4 orders of magnitude. Coupling MS to CPLLs permits the exploration of at least 8 orders of magnitude in dynamic range on any proteome. The present review is a personal recollection highlighting the developments that led to present-day proteomics on a long march that lasted about 50years. It is meant to give to young scientists an overview on how science grows, which ones are the quantum jumps in science and which research is of particular significance in general and in the field of proteomics in particular. It also gives some real-life episodes of greater-than-life figures. As such, it can be viewed as a tutorial to stimulate the young generation to be creative (and use their imagination too!).This article is part of a Special Issue entitled: 20years of Proteomics in memory of Viatliano Pallini. Guest Editors: Luca Bini, Juan J. Calvete, Natacha Turck, Denis Hochstrasser and Jean-Charles Sanchez. Copyright © 2013 Elsevier B.V. All rights reserved.

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.

Comparative proteomics analysis of oral cancer cell lines: identification of cancer associated proteins

PubMed Central

2014-01-01

Background A limiting factor in performing proteomics analysis on cancerous cells is the difficulty in obtaining sufficient amounts of starting material. Cell lines can be used as a simplified model system for studying changes that accompany tumorigenesis. This study used two-dimensional gel electrophoresis (2DE) to compare the whole cell proteome of oral cancer cell lines vs normal cells in an attempt to identify cancer associated proteins. Results Three primary cell cultures of normal cells with a limited lifespan without hTERT immortalization have been successfully established. 2DE was used to compare the whole cell proteome of these cells with that of three oral cancer cell lines. Twenty four protein spots were found to have changed in abundance. MALDI TOF/TOF was then used to determine the identity of these proteins. Identified proteins were classified into seven functional categories – structural proteins, enzymes, regulatory proteins, chaperones and others. IPA core analysis predicted that 18 proteins were related to cancer with involvements in hyperplasia, metastasis, invasion, growth and tumorigenesis. The mRNA expressions of two proteins – 14-3-3 protein sigma and Stress-induced-phosphoprotein 1 – were found to correlate with the corresponding proteins’ abundance. Conclusions The outcome of this analysis demonstrated that a comparative study of whole cell proteome of cancer versus normal cell lines can be used to identify cancer associated proteins. PMID:24422745

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.

Proteomics and Systems Biology: Current and Future Applications in the Nutritional Sciences1

PubMed Central

Moore, J. Bernadette; Weeks, Mark E.

2011-01-01

In the last decade, advances in genomics, proteomics, and metabolomics have yielded large-scale datasets that have driven an interest in global analyses, with the objective of understanding biological systems as a whole. Systems biology integrates computational modeling and experimental biology to predict and characterize the dynamic properties of biological systems, which are viewed as complex signaling networks. Whereas the systems analysis of disease-perturbed networks holds promise for identification of drug targets for therapy, equally the identified critical network nodes may be targeted through nutritional intervention in either a preventative or therapeutic fashion. As such, in the context of the nutritional sciences, it is envisioned that systems analysis of normal and nutrient-perturbed signaling networks in combination with knowledge of underlying genetic polymorphisms will lead to a future in which the health of individuals will be improved through predictive and preventative nutrition. Although high-throughput transcriptomic microarray data were initially most readily available and amenable to systems analysis, recent technological and methodological advances in MS have contributed to a linear increase in proteomic investigations. It is now commonplace for combined proteomic technologies to generate complex, multi-faceted datasets, and these will be the keystone of future systems biology research. This review will define systems biology, outline current proteomic methodologies, highlight successful applications of proteomics in nutrition research, and discuss the challenges for future applications of systems biology approaches in the nutritional sciences. PMID:22332076

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.

Maximal Unbiased Benchmarking Data Sets for Human Chemokine Receptors and Comparative Analysis.

PubMed

Xia, Jie; Reid, Terry-Elinor; Wu, Song; Zhang, Liangren; Wang, Xiang Simon

2018-05-29

Chemokine receptors (CRs) have long been druggable targets for the treatment of inflammatory diseases and HIV-1 infection. As a powerful technique, virtual screening (VS) has been widely applied to identifying small molecule leads for modern drug targets including CRs. For rational selection of a wide variety of VS approaches, ligand enrichment assessment based on a benchmarking data set has become an indispensable practice. However, the lack of versatile benchmarking sets for the whole CRs family that are able to unbiasedly evaluate every single approach including both structure- and ligand-based VS somewhat hinders modern drug discovery efforts. To address this issue, we constructed Maximal Unbiased Benchmarking Data sets for human Chemokine Receptors (MUBD-hCRs) using our recently developed tools of MUBD-DecoyMaker. The MUBD-hCRs encompasses 13 subtypes out of 20 chemokine receptors, composed of 404 ligands and 15756 decoys so far and is readily expandable in the future. It had been thoroughly validated that MUBD-hCRs ligands are chemically diverse while its decoys are maximal unbiased in terms of "artificial enrichment", "analogue bias". In addition, we studied the performance of MUBD-hCRs, in particular CXCR4 and CCR5 data sets, in ligand enrichment assessments of both structure- and ligand-based VS approaches in comparison with other benchmarking data sets available in the public domain and demonstrated that MUBD-hCRs is very capable of designating the optimal VS approach. MUBD-hCRs is a unique and maximal unbiased benchmarking set that covers major CRs subtypes so far.

Proteomics data repositories

PubMed Central

Riffle, Michael; Eng, Jimmy K.

2010-01-01

The field of proteomics, particularly the application of mass spectrometry analysis to protein samples, is well-established and growing rapidly. Proteomics studies generate large volumes of raw experimental data and inferred biological results. To facilitate the dissemination of these data, centralized data repositories have been developed that make the data and results accessible to proteomics researchers and biologists alike. This review of proteomics data repositories focuses exclusively on freely-available, centralized data resources that disseminate or store experimental mass spectrometry data and results. The resources chosen reflect a current “snapshot” of the state of resources available with an emphasis placed on resources that may be of particular interest to yeast researchers. Resources are described in terms of their intended purpose and the features and functionality provided to users. PMID:19795424

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

PubMed Central

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

2017-01-01

Metformin is a commonly prescribed antihyperglycemic drug, and has been investigated in vivo and in vitro for its effect to improve the comorbidity of diabetes and various types of cancers. Several studies investigated the therapeutic mechanisms of metformin on cancer cells, but the exact mechanism of metformin’s effect on the proteomic pathways of cancer cells is yet to be further investigated. The main objective of our research line is to discover safe and alternative therapeutic options for breast cancer, we aimed in this study to design a novel “bottom up proteomics workflow” in which proteins were first broken into peptides to reveal their identity, then the proteomes were precisely evaluated using spectrometry analysis. In our study, metformin suppressed cell proliferation and induced apoptosis in human breast carcinoma cell line MCF-7 with minimal toxicity to normal breast epithelial cells MCF-10. Metformin induced apoptosis by arresting cells in G1 phase as evaluated by flow cytometric analysis. Moreover, The G1 phase arrest for the MCF-7 has been confirmed by increased expression levels of p21 and reduction in cyclin D1 level. Additionally, metformin increased the expression levels of p53, Bax, Bad while it reduced expression levels of Akt, Bcl-2, and Mdm2. The study employed a serviceable strategy that investigates metformin-dependent changes in the proteome using a literature-derived network. The protein extracts of the treated and untreated cell lines were analyzed employing proteomic approaches; the findings conveyed a proposed mechanism of the effectual tactics of metformin on breast cancer cells. Metformin proposed an antibreast cancer effect through the examination of the proteomic pathways upon the MCF-7 and MCF-10A exposure to the drug. Our findings proposed prolific proteomic changes that revealed the therapeutic mechanisms of metformin on breast cancer cells upon their exposure. In conclusion, the reported proteomic pathways lead to increase the understanding of breast cancer prognosis and permit future studies to examine the effect of metformin on the proteomic pathways against other types of cancers. Finally, it suggests the possibility to develop further therapeutic generations of metformin with increased anticancer effect through targeting specific proteomes. PMID:29085821

P2P proteomics -- data sharing for enhanced protein identification

PubMed Central

2012-01-01

Background In order to tackle the important and challenging problem in proteomics of identifying known and new protein sequences using high-throughput methods, we propose a data-sharing platform that uses fully distributed P2P technologies to share specifications of peer-interaction protocols and service components. By using such a platform, information to be searched is no longer centralised in a few repositories but gathered from experiments in peer proteomics laboratories, which can subsequently be searched by fellow researchers. Methods The system distributively runs a data-sharing protocol specified in the Lightweight Communication Calculus underlying the system through which researchers interact via message passing. For this, researchers interact with the system through particular components that link to database querying systems based on BLAST and/or OMSSA and GUI-based visualisation environments. We have tested the proposed platform with data drawn from preexisting MS/MS data reservoirs from the 2006 ABRF (Association of Biomolecular Resource Facilities) test sample, which was extensively tested during the ABRF Proteomics Standards Research Group 2006 worldwide survey. In particular we have taken the data available from a subset of proteomics laboratories of Spain's National Institute for Proteomics, ProteoRed, a network for the coordination, integration and development of the Spanish proteomics facilities. Results and Discussion We performed queries against nine databases including seven ProteoRed proteomics laboratories, the NCBI Swiss-Prot database and the local database of the CSIC/UAB Proteomics Laboratory. A detailed analysis of the results indicated the presence of a protein that was supported by other NCBI matches and highly scored matches in several proteomics labs. The analysis clearly indicated that the protein was a relatively high concentrated contaminant that could be present in the ABRF sample. This fact is evident from the information that could be derived from the proposed P2P proteomics system, however it is not straightforward to arrive to the same conclusion by conventional means as it is difficult to discard organic contamination of samples. The actual presence of this contaminant was only stated after the ABRF study of all the identifications reported by the laboratories. PMID:22293032

Proteome Studies of Filamentous Fungi

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

Baker, Scott E.; Panisko, Ellen A.

2011-04-20

The continued fast pace of fungal genome sequence generation has enabled proteomic analysis of a wide breadth of organisms that span the breadth of the Kingdom Fungi. There is some phylogenetic bias to the current catalog of fungi with reasonable DNA sequence databases (genomic or EST) that could be analyzed at a global proteomic level. However, the rapid development of next generation sequencing platforms has lowered the cost of genome sequencing such that in the near future, having a genome sequence will no longer be a time or cost bottleneck for downstream proteomic (and transcriptomic) analyses. High throughput, non-gel basedmore » proteomics offers a snapshot of proteins present in a given sample at a single point in time. There are a number of different variations on the general method and technologies for identifying peptides in a given sample. We present a method that can serve as a “baseline” for proteomic studies of fungi.« less

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

PubMed

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

2016-01-01

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

Proteome studies of filamentous fungi.

PubMed

Baker, Scott E; Panisko, Ellen A

2011-01-01

The continued fast pace of fungal genome sequence generation has enabled proteomic analysis of a wide variety of organisms that span the breadth of the Kingdom Fungi. There is some phylogenetic bias to the current catalog of fungi with reasonable DNA sequence databases (genomic or EST) that could be analyzed at a global proteomic level. However, the rapid development of next generation sequencing platforms has lowered the cost of genome sequencing such that in the near future, having a genome sequence will no longer be a time or cost bottleneck for downstream proteomic (and transcriptomic) analyses. High throughput, nongel-based proteomics offers a snapshot of proteins present in a given sample at a single point in time. There are a number of variations on the general methods and technologies for identifying peptides in a given sample. We present a method that can serve as a "baseline" for proteomic studies of fungi.

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.

Mining the human plasma proteome with three-dimensional strategies by high-resolution Quadrupole Orbitrap Mass Spectrometry.

PubMed

Zhao, Yan; Chang, Cheng; Qin, Peibin; Cao, Qichen; Tian, Fang; Jiang, Jing; Li, Xianyu; Yu, Wenfeng; Zhu, Yunping; He, Fuchu; Ying, Wantao; Qian, Xiaohong

2016-01-21

Human plasma is a readily available clinical sample that reflects the status of the body in normal physiological and disease states. Although the wide dynamic range and immense complexity of plasma proteins are obstacles, comprehensive proteomic analysis of human plasma is necessary for biomarker discovery and further verification. Various methods such as immunodepletion, protein equalization and hyper fractionation have been applied to reduce the influence of high-abundance proteins (HAPs) and to reduce the high level of complexity. However, the depth at which the human plasma proteome has been explored in a relatively short time frame has been limited, which impedes the transfer of proteomic techniques to clinical research. Development of an optimal strategy is expected to improve the efficiency of human plasma proteome profiling. Here, five three-dimensional strategies combining HAP depletion (the 1st dimension) and protein fractionation (the 2nd dimension), followed by LC-MS/MS analysis (the 3rd dimension) were developed and compared for human plasma proteome profiling. Pros and cons of the five strategies are discussed for two issues: HAP depletion and complexity reduction. Strategies A and B used proteome equalization and tandem Seppro IgY14 immunodepletion, respectively, as the first dimension. Proteome equalization (strategy A) was biased toward the enrichment of basic and low-molecular weight proteins and had limited ability to enrich low-abundance proteins. By tandem removal of HAPs (strategy B), the efficiency of HAP depletion was significantly increased, whereas more off-target proteins were subtracted simultaneously. In the comparison of complexity reduction, strategy D involved a deglycosylation step before high-pH RPLC separation. However, the increase in sequence coverage did not increase the protein number as expected. Strategy E introduced SDS-PAGE separation of proteins, and the results showed oversampling of HAPs and identification of fewer proteins. Strategy C combined single Seppro IgY14 immunodepletion, high-pH RPLC fractionation and LC-MS/MS analysis. It generated the largest dataset, containing 1544 plasma protein groups and 258 newly identified proteins in a 30-h-machine-time analysis, making it the optimum three-dimensional strategy in our study. Further analysis of the integrated data from the five strategies showed identical distribution patterns in terms of sequence features and GO functional analysis with the 1929-plasma-protein dataset, further supporting the reliability of our plasma protein identifications. The characterization of 20 cytokines in the concentration range from sub-nanograms/milliliter to micrograms/milliliter demonstrated the sensitivity of the current strategies. Copyright © 2015 Elsevier B.V. All rights reserved.

Proteomics Analysis of the Causative Agent of Typhoid Fever

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

Ansong, Charles; Yoon, Hyunjin; Norbeck, Angela D.

2008-02-01

Typhoid fever is a potentially fatal disease caused by the bacterial pathogen Salmonella enterica serovar Typhi (S. typhi). S. typhi infection is a complex process that involves numerous bacterially-encoded virulence determinants, and these are thought to confer both stringent human host specificity and a high mortality rate. In the present study we used a liquid chromatography-mass spectrometry (LC-MS) based proteomics strategy to investigate the proteome of logarithmic, stationary phase, and low pH/low magnesium (MgM) S. typhi cultures. This represents the first large scale comprehensive characterization of the S. typhi proteome. Our analysis identified a total of 2066 S. typhi proteins.more » In an effort to identify putative S. typhi-specific virulence factors, we then compared our S. typhi results to those obtained in a previously published study of the S. typhimurium proteome under similar conditions (Adkins J.N. et al (2006) Mol Cell Prot). Comparative proteomic analysis of S. typhi (strain Ty2) and S. typhimurium (strains LT2 and 14028) revealed a subset of highly expressed proteins unique to S. typhi that were exclusively detected under conditions that mimic the infective state in macrophage cells. These proteins included CdtB, HlyE, and a conserved protein encoded by t1476. The differential expression of selected proteins was confirmed by Western blot analysis. Taken together with the current literature, our observations suggest that this subset of proteins may play a role in S. typhi pathogenesis and human host specificity. In addition, we observed products of the biotin (bio) operon displayed a higher abundance in the more virulent strains S. typhi-Ty2 and S. typhimurium-14028 compared to the virulence attenuated S. typhimurium strain LT2, suggesting bio proteins may contribute to Salmonella pathogenesis.« less

Proteomics-based network analysis characterizes biological processes and pathways activated by preconditioned mesenchymal stem cells in cardiac repair mechanisms.

PubMed

Di Silvestre, Dario; Brambilla, Francesca; Scardoni, Giovanni; Brunetti, Pietro; Motta, Sara; Matteucci, Marco; Laudanna, Carlo; Recchia, Fabio A; Lionetti, Vincenzo; Mauri, Pierluigi

2017-05-01

We have demonstrated that intramyocardial delivery of human mesenchymal stem cells preconditioned with a hyaluronan mixed ester of butyric and retinoic acid (MSCp + ) is more effective in preventing the decay of regional myocardial contractility in a swine model of myocardial infarction (MI). However, the understanding of the role of MSCp + in proteomic remodeling of cardiac infarcted tissue is not complete. We therefore sought to perform a comprehensive analysis of the proteome of infarct remote (RZ) and border zone (BZ) of pigs treated with MSCp + or unconditioned stem cells. Heart tissues were analyzed by MudPIT and differentially expressed proteins were selected by a label-free approach based on spectral counting. Protein profiles were evaluated by using PPI networks and their topological analysis. The proteomic remodeling was largely prevented in MSCp + group. Extracellular proteins involved in fibrosis were down-regulated, while energetic pathways were globally up-regulated. Cardioprotectant pathways involved in the production of keto acid metabolites were also activated. Additionally, we found that new hub proteins support the cardioprotective phenotype characterizing the left ventricular BZ treated with MSCp + . In fact, the up-regulation of angiogenic proteins NCL and RAC1 can be explained by the increase of capillary density induced by MSCp + . Our results show that angiogenic pathways appear to be uniquely positioned to integrate signaling with energetic pathways involving cardiac repair. Our findings prompt the use of proteomics-based network analysis to optimize new approaches preventing the post-ischemic proteomic remodeling that may underlie the limited self-repair ability of adult heart. Copyright © 2017 Elsevier B.V. All rights reserved.

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

PubMed Central

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

2016-01-01

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

ProCon - PROteomics CONversion tool.

PubMed

Mayer, Gerhard; Stephan, Christian; Meyer, Helmut E; Kohl, Michael; Marcus, Katrin; Eisenacher, Martin

2015-11-03

With the growing amount of experimental data produced in proteomics experiments and the requirements/recommendations of journals in the proteomics field to publicly make available data described in papers, a need for long-term storage of proteomics data in public repositories arises. For such an upload one needs proteomics data in a standardized format. Therefore, it is desirable, that the proprietary vendor's software will integrate in the future such an export functionality using the standard formats for proteomics results defined by the HUPO-PSI group. Currently not all search engines and analysis tools support these standard formats. In the meantime there is a need to provide user-friendly free-to-use conversion tools that can convert the data into such standard formats in order to support wet-lab scientists in creating proteomics data files ready for upload into the public repositories. ProCon is such a conversion tool written in Java for conversion of proteomics identification data into standard formats mzIdentML and Pride XML. It allows the conversion of Sequest™/Comet .out files, of search results from the popular and often used ProteomeDiscoverer® 1.x (x=versions 1.1 to1.4) software and search results stored in the LIMS systems ProteinScape® 1.3 and 2.1 into mzIdentML and PRIDE XML. This article is part of a Special Issue entitled: Computational Proteomics. Copyright © 2015. Published by Elsevier B.V.

Application of proteomics to ecology and population biology.

PubMed

Karr, T L

2008-02-01

Proteomics is a relatively new scientific discipline that merges protein biochemistry, genome biology and bioinformatics to determine the spatial and temporal expression of proteins in cells, tissues and whole organisms. There has been very little application of proteomics to the fields of behavioral genetics, evolution, ecology and population dynamics, and has only recently been effectively applied to the closely allied fields of molecular evolution and genetics. However, there exists considerable potential for proteomics to impact in areas related to functional ecology; this review will introduce the general concepts and methodologies that define the field of proteomics and compare and contrast the advantages and disadvantages with other methods. Examples of how proteomics can aid, complement and indeed extend the study of functional ecology will be discussed including the main tool of ecological studies, population genetics with an emphasis on metapopulation structure analysis. Because proteomic analyses provide a direct measure of gene expression, it obviates some of the limitations associated with other genomic approaches, such as microarray and EST analyses. Likewise, in conjunction with associated bioinformatics and molecular evolutionary tools, proteomics can provide the foundation of a systems-level integration approach that can enhance ecological studies. It can be envisioned that proteomics will provide important new information on issues specific to metapopulation biology and adaptive processes in nature. A specific example of the application of proteomics to sperm ageing is provided to illustrate the potential utility of the approach.

CPTAC Establishes Formal Relationships with Two Academic Institutions in Taiwan | Office of Cancer Clinical Proteomics Research

Cancer.gov

The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) has entered into memorandum of understandings (MOUs) with Chang Gung University and Academia Sinica, in Taipei, Taiwan.

CPTAC Biospecimen Collection Solicitation | Office of Cancer Clinical Proteomics Research

Cancer.gov

A funding opportunity in support of the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) seeks to prospectively procure tumor samples, collected for proteomics investigation. The scope of work under this Statement of Work encompasses the activities needed to prospectively procure high quality, clinically annotated human tumor samples, blood and plasma, and when feasible, normal tissue from volunteer patients suffering from colon, ovarian, and breast cancer.

Comparative proteomic analysis of lung tissue from guinea pigs with Leptospiral Pulmonary Haemorrhage Syndrome (LPHS) reveals a decrease in abundance of host proteins involved in cytoskeletal and cellular organization

USDA-ARS?s Scientific Manuscript database

The recent completion of the complete genome sequence of the guinea pig (Cavia porcellus) provides innovative opportunities to apply proteomic technologies to an important animal model of disease. In this study, a 2-D guinea pig proteome lung map was used to investigate the pathogenic mechanisms of ...

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.

Multidimensional protein fractionation using ProteomeLab PF 2D™ for profiling amyotrophic lateral sclerosis immunity: A preliminary report

PubMed Central

Schlautman, Joshua D; Rozek, Wojciech; Stetler, Robert; Mosley, R Lee; Gendelman, Howard E; Ciborowski, Pawel

2008-01-01

Background The ProteomeLab™ PF 2D platform is a relatively new approach to global protein profiling. Herein, it was used for investigation of plasma proteome changes in amyotrophic lateral sclerosis (ALS) patients before and during immunization with glatiramer acetate (GA) in a clinical trial. Results The experimental design included immunoaffinity depletion of 12 most abundant proteins from plasma samples with the ProteomeLab™ IgY-12 LC10 column kit as first dimension separation, also referred to as immuno-partitioning. Second and third dimension separations of the enriched proteome were performed on the PF 2D platform utilizing 2D isoelectric focusing and RP-HPLC with the resulting fractions collected for analysis. 1D gel electrophoresis was added as a fourth dimension when sufficient protein was available. Protein identification from collected fractions was performed using nano-LC-MS/MS approach. Analysis of differences in the resulting two-dimensional maps of fractions obtained from the PF 2D and the ability to identify proteins from these fractions allowed sensitivity threshold measurements. Masked proteins in the PF 2D fractions are discussed. Conclusion We offer some insight into the strengths and limitations of this emerging proteomic platform. PMID:18789151

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.

Tentacle Transcriptome and Venom Proteome of the Pacific Sea Nettle, Chrysaora fuscescens (Cnidaria: Scyphozoa)

PubMed Central

Ponce, Dalia; Brinkman, Diane L.; Potriquet, Jeremy; Mulvenna, Jason

2016-01-01

Jellyfish venoms are rich sources of toxins designed to capture prey or deter predators, but they can also elicit harmful effects in humans. In this study, an integrated transcriptomic and proteomic approach was used to identify putative toxins and their potential role in the venom of the scyphozoan jellyfish Chrysaora fuscescens. A de novo tentacle transcriptome, containing more than 23,000 contigs, was constructed and used in proteomic analysis of C. fuscescens venom to identify potential toxins. From a total of 163 proteins identified in the venom proteome, 27 were classified as putative toxins and grouped into six protein families: proteinases, venom allergens, C-type lectins, pore-forming toxins, glycoside hydrolases and enzyme inhibitors. Other putative toxins identified in the transcriptome, but not the proteome, included additional proteinases as well as lipases and deoxyribonucleases. Sequence analysis also revealed the presence of ShKT domains in two putative venom proteins from the proteome and an additional 15 from the transcriptome, suggesting potential ion channel blockade or modulatory activities. Comparison of these potential toxins to those from other cnidarians provided insight into their possible roles in C. fuscescens venom and an overview of the diversity of potential toxin families in cnidarian venoms. PMID:27058558

Quantitative Assessment of In-solution Digestion Efficiency Identifies Optimal Protocols for Unbiased Protein Analysis*

PubMed Central

León, Ileana R.; Schwämmle, Veit; Jensen, Ole N.; Sprenger, Richard R.

2013-01-01

The majority of mass spectrometry-based protein quantification studies uses peptide-centric analytical methods and thus strongly relies on efficient and unbiased protein digestion protocols for sample preparation. We present a novel objective approach to assess protein digestion efficiency using a combination of qualitative and quantitative liquid chromatography-tandem MS methods and statistical data analysis. In contrast to previous studies we employed both standard qualitative as well as data-independent quantitative workflows to systematically assess trypsin digestion efficiency and bias using mitochondrial protein fractions. We evaluated nine trypsin-based digestion protocols, based on standard in-solution or on spin filter-aided digestion, including new optimized protocols. We investigated various reagents for protein solubilization and denaturation (dodecyl sulfate, deoxycholate, urea), several trypsin digestion conditions (buffer, RapiGest, deoxycholate, urea), and two methods for removal of detergents before analysis of peptides (acid precipitation or phase separation with ethyl acetate). Our data-independent quantitative liquid chromatography-tandem MS workflow quantified over 3700 distinct peptides with 96% completeness between all protocols and replicates, with an average 40% protein sequence coverage and an average of 11 peptides identified per protein. Systematic quantitative and statistical analysis of physicochemical parameters demonstrated that deoxycholate-assisted in-solution digestion combined with phase transfer allows for efficient, unbiased generation and recovery of peptides from all protein classes, including membrane proteins. This deoxycholate-assisted protocol was also optimal for spin filter-aided digestions as compared with existing methods. PMID:23792921

Proteomic Analysis of the Cell Cycle of Procylic Form Trypanosoma brucei.

PubMed

Crozier, Thomas W M; Tinti, Michele; Wheeler, Richard J; Ly, Tony; Ferguson, Michael A J; Lamond, Angus I

2018-06-01

We describe a single-step centrifugal elutriation method to produce synchronous Gap1 (G1)-phase procyclic trypanosomes at a scale amenable for proteomic analysis of the cell cycle. Using ten-plex tandem mass tag (TMT) labeling and mass spectrometry (MS)-based proteomics technology, the expression levels of 5325 proteins were quantified across the cell cycle in this parasite. Of these, 384 proteins were classified as cell-cycle regulated and subdivided into nine clusters with distinct temporal regulation. These groups included many known cell cycle regulators in trypanosomes, which validates the approach. In addition, we identify 40 novel cell cycle regulated proteins that are essential for trypanosome survival and thus represent potential future drug targets for the prevention of trypanosomiasis. Through cross-comparison to the TrypTag endogenous tagging microscopy database, we were able to validate the cell-cycle regulated patterns of expression for many of the proteins of unknown function detected in our proteomic analysis. A convenient interface to access and interrogate these data is also presented, providing a useful resource for the scientific community. Data are available via ProteomeXchange with identifier PXD008741 (https://www.ebi.ac.uk/pride/archive/). © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

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.

Label-Free LC-MS/MS Proteomic Analysis of Cerebrospinal Fluid Identifies Protein/Pathway Alterations and Candidate Biomarkers for Amyotrophic Lateral Sclerosis.

PubMed

Collins, Mahlon A; An, Jiyan; Hood, Brian L; Conrads, Thomas P; Bowser, Robert P

2015-11-06

Analysis of the cerebrospinal fluid (CSF) proteome has proven valuable to the study of neurodegenerative disorders. To identify new protein/pathway alterations and candidate biomarkers for amyotrophic lateral sclerosis (ALS), we performed comparative proteomic profiling of CSF from sporadic ALS (sALS), healthy control (HC), and other neurological disease (OND) subjects using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS). A total of 1712 CSF proteins were detected and relatively quantified by spectral counting. Levels of several proteins with diverse biological functions were significantly altered in sALS samples. Enrichment analysis was used to link these alterations to biological pathways, which were predominantly related to inflammation, neuronal activity, and extracellular matrix regulation. We then used our CSF proteomic profiles to create a support vector machines classifier capable of discriminating training set ALS from non-ALS (HC and OND) samples. Four classifier proteins, WD repeat-containing protein 63, amyloid-like protein 1, SPARC-like protein 1, and cell adhesion molecule 3, were identified by feature selection and externally validated. The resultant classifier distinguished ALS from non-ALS samples with 83% sensitivity and 100% specificity in an independent test set. Collectively, our results illustrate the utility of CSF proteomic profiling for identifying ALS protein/pathway alterations and candidate disease biomarkers.

A new calibrant for MALDI-TOF-TOF-PSD-MS/MS of non-digested proteins for top-down proteomic analysis

USDA-ARS?s Scientific Manuscript database

RATIONALE: Matrix-assisted laser desorption/ionization (MALDI) time-of-flight-time-of-flight (TOF-TOF) tandem mass spectrometry (MS/MS) has seen increasing use for post-source decay (PSD)-MS/MS analysis of non-digested protein ions for top-down proteomic identification. However, there is no commonl...

Functional analysis of proteins and protein species using shotgun proteomics and linear mathematics.

PubMed

Hoehenwarter, Wolfgang; Chen, Yanmei; Recuenco-Munoz, Luis; Wienkoop, Stefanie; Weckwerth, Wolfram

2011-07-01

Covalent post-translational modification of proteins is the primary modulator of protein function in the cell. It greatly expands the functional potential of the proteome compared to the genome. In the past few years shotgun proteomics-based research, where the proteome is digested into peptides prior to mass spectrometric analysis has been prolific in this area. It has determined the kinetics of tens of thousands of sites of covalent modification on an equally large number of proteins under various biological conditions and uncovered a transiently active regulatory network that extends into diverse branches of cellular physiology. In this review, we discuss this work in light of the concept of protein speciation, which emphasizes the entire post-translationally modified molecule and its interactions and not just the modification site as the functional entity. Sometimes, particularly when considering complex multisite modification, all of the modified molecular species involved in the investigated condition, the protein species must be completely resolved for full understanding. We present a mathematical technique that delivers a good approximation for shotgun proteomics data.

Saliva Proteomics Analysis Offers Insights on Type 1 Diabetes Pathology in a Pediatric Population

PubMed Central

Pappa, Eftychia; Vastardis, Heleni; Mermelekas, George; Gerasimidi-Vazeou, Andriani; Zoidakis, Jerome; Vougas, Konstantinos

2018-01-01

The composition of the salivary proteome is affected by pathological conditions. We analyzed by high resolution mass spectrometry approaches saliva samples collected from children and adolescents with type 1 diabetes and healthy controls. The list of more than 2000 high confidence protein identifications constitutes a comprehensive characterization of the salivary proteome. Patients with good glycemic regulation and healthy individuals have comparable proteomic profiles. In contrast, a significant number of differentially expressed proteins were identified in the saliva of patients with poor glycemic regulation compared to patients with good glycemic control and healthy children. These proteins are involved in biological processes relevant to diabetic pathology such as endothelial damage and inflammation. Moreover, a putative preventive therapeutic approach was identified based on bioinformatic analysis of the deregulated salivary proteins. Thus, thorough characterization of saliva proteins in diabetic pediatric patients established a connection between molecular changes and disease pathology. This proteomic and bioinformatic approach highlights the potential of salivary diagnostics in diabetes pathology and opens the way for preventive treatment of the disease. PMID:29755368

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

Salt stress induces changes in the proteomic profile of micropropagated sugarcane shoots

PubMed Central

Reis, Ricardo S.; Heringer, Angelo S.; Rangel, Patricia L.; Santa-Catarina, Claudete; Grativol, Clícia; Veiga, Carlos F. M.; Souza-Filho, Gonçalo A.

2017-01-01

Salt stress is one of the most common stresses in agricultural regions worldwide. In particular, sugarcane is affected by salt stress conditions, and no sugarcane cultivar presently show high productivity accompanied by a tolerance to salt stress. Proteomic analysis allows elucidation of the important pathways involved in responses to various abiotic stresses at the biochemical and molecular levels. Thus, this study aimed to analyse the proteomic effects of salt stress in micropropagated shoots of two sugarcane cultivars (CB38-22 and RB855536) using a label-free proteomic approach. The mass spectrometry proteomics data are available via ProteomeXchange with identifier PXD006075. The RB855536 cultivar is more tolerant to salt stress than CB38-22. A quantitative label-free shotgun proteomic analysis identified 1172 non-redundant proteins, and 1160 of these were observed in both cultivars in the presence or absence of NaCl. Compared with CB38-22, the RB855536 cultivar showed a greater abundance of proteins involved in non-enzymatic antioxidant mechanisms, ion transport, and photosynthesis. Some proteins, such as calcium-dependent protein kinase, photosystem I, phospholipase D, and glyceraldehyde-3-phosphate dehydrogenase, were more abundant in the RB855536 cultivar under salt stress. Our results provide new insights into the response of sugarcane to salt stress, and the changes in the abundance of these proteins might be important for the acquisition of ionic and osmotic homeostasis during exposure to salt stress. PMID:28419154

Mutually unbiased projectors and duality between lines and bases in finite quantum systems

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

Shalaby, M.; Vourdas, A., E-mail: a.vourdas@bradford.ac.uk

2013-10-15

Quantum systems with variables in the ring Z(d) are considered, and the concepts of weak mutually unbiased bases and mutually unbiased projectors are discussed. The lines through the origin in the Z(d)×Z(d) phase space, are classified into maximal lines (sets of d points), and sublines (sets of d{sub i} points where d{sub i}|d). The sublines are intersections of maximal lines. It is shown that there exists a duality between the properties of lines (resp., sublines), and the properties of weak mutually unbiased bases (resp., mutually unbiased projectors). -- Highlights: •Lines in discrete phase space. •Bases in finite quantum systems. •Dualitymore » between bases and lines. •Weak mutually unbiased bases.« less

Enrichment and separation techniques for large-scale proteomics analysis of the protein post-translational modifications.

PubMed

Huang, Junfeng; Wang, Fangjun; Ye, Mingliang; Zou, Hanfa

2014-11-06

Comprehensive analysis of the post-translational modifications (PTMs) on proteins at proteome level is crucial to elucidate the regulatory mechanisms of various biological processes. In the past decades, thanks to the development of specific PTM enrichment techniques and efficient multidimensional liquid chromatography (LC) separation strategy, the identification of protein PTMs have made tremendous progress. A huge number of modification sites for some major protein PTMs have been identified by proteomics analysis. In this review, we first introduced the recent progresses of PTM enrichment methods for the analysis of several major PTMs including phosphorylation, glycosylation, ubiquitination, acetylation, methylation, and oxidation/reduction status. We then briefly summarized the challenges for PTM enrichment. Finally, we introduced the fractionation and separation techniques for efficient separation of PTM peptides in large-scale PTM analysis. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

Implementation of proteomics for cancer research: past, present, and future.

PubMed

Karimi, Parisa; Shahrokni, Armin; Ranjbar, Mohammad R Nezami

2014-01-01

Cancer is the leading cause of the death, accounts for about 13% of all annual deaths worldwide. Many different fields of science are collaborating together studying cancer to improve our knowledge of this lethal disease, and find better solutions for diagnosis and treatment. Proteomics is one of the most recent and rapidly growing areas in molecular biology that helps understanding cancer from an omics data analysis point of view. The human proteome project was officially initiated in 2008. Proteomics enables the scientists to interrogate a variety of biospecimens for their protein contents and measure the concentrations of these proteins. Current necessary equipment and technologies for cancer proteomics are mass spectrometry, protein microarrays, nanotechnology and bioinformatics. In this paper, we provide a brief review on proteomics and its application in cancer research. After a brief introduction including its definition, we summarize the history of major previous work conducted by researchers, followed by an overview on the role of proteomics in cancer studies. We also provide a list of different utilities in cancer proteomics and investigate their advantages and shortcomings from theoretical and practical angles. Finally, we explore some of the main challenges and conclude the paper with future directions in this field.

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

Top-down Proteomics in Health and Disease: Challenges and Opportunities

PubMed Central

Gregorich, Zachery R.; Ge, Ying

2014-01-01

Proteomics is essential for deciphering how molecules interact as a system and for understanding the functions of cellular systems in human disease; however, the unique characteristics of the human proteome, which include a high dynamic range of protein expression and extreme complexity due to a plethora of post-translational modifications (PTMs) and sequence variations, make such analyses challenging. An emerging “top-down” mass spectrometry (MS)-based proteomics approach, which provides a “bird’s eye” view of all proteoforms, has unique advantages for the assessment of PTMs and sequence variations. Recently, a number of studies have showcased the potential of top-down proteomics for unraveling of disease mechanisms and discovery of new biomarkers. Nevertheless, the top-down approach still faces significant challenges in terms of protein solubility, separation, and the detection of large intact proteins, as well as the under-developed data analysis tools. Consequently, new technological developments are urgently needed to advance the field of top-down proteomics. Herein, we intend to provide an overview of the recent applications of top-down proteomics in biomedical research. Moreover, we will outline the challenges and opportunities facing top-down proteomics strategies aimed at understanding and diagnosing human diseases. PMID:24723472

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.

Integrated proteomic and genomic analysis of colorectal cancer

Cancer.gov

Investigators who analyzed 95 human colorectal tumor samples have determined how gene alterations identified in previous analyses of the same samples are expressed at the protein level. The integration of proteomic and genomic data, or proteogenomics, pro

CPTAC Teams | Office of Cancer Clinical Proteomics Research

Cancer.gov

The following are the current CPTAC teams, representing a network of Proteome Characterization Centers (PCCs), Proteogenomic Translational Research Centers (PTRCs), and Proteogenomic Data Analysis Centers (PGDACs). Teams are listed alphabetically by institution, with their respective Principal Investigators:

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.

Proteomic methods for analysis of S-nitrosation⋄

PubMed Central

Kettenhofen, Nicholas; Broniowska, Katarzyna; Keszler, Agnes; Zhang, Yanhong; Hogg, Neil

2007-01-01

This review discusses proteomic methods to detect and identify S-nitrosated proteins. Protein S-nitrosation, the post-translational modification of thiol residues to form S-nitrosothiols, has been suggested to be a mechanism of cellular redox signaling by which nitric oxide can alter cellular function through modification of protein thiol residues. It has become apparent that methods that will detect and identify low levels of S-nitrosated protein in complex protein mixtures are required in order to fully appreciate the range, extent and selectivity of this modification in both physiological and pathological conditions. While many advances have been made in the detection of either total cellular S-nitrosation or individual S-nitrosothiols, proteomic methods for the detection of S-nitrosation are in relative infancy. This review will discuss the major methods that have been used for the proteomic analysis of protein S-nitrosation and discuss the pros and cons of this methodology. PMID:17360249

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.

Combined metabolome and proteome analysis of the mantle tissue from Pacific oyster Crassostrea gigas exposed to elevated pCO2.

PubMed

Wei, Lei; Wang, Qing; Ning, Xuanxuan; Mu, Changkao; Wang, Chunlin; Cao, Ruiwen; Wu, Huifeng; Cong, Ming; Li, Fei; Ji, Chenglong; Zhao, Jianmin

2015-03-01

Ocean acidification (OA) has been found to affect an array of normal physiological processes in mollusks, especially posing a significant threat to the fabrication process of mollusk shell. In the current study, the impact of exposure to elevated pCO2 condition was investigated in mantle tissue of Crassostrea gigas by an integrated metabolomic and proteomic approach. Analysis of metabolome and proteome revealed that elevated pCO2 could affect energy metabolism in oyster C. gigas, marked by differentially altered ATP, succinate, MDH, PEPCK and ALDH levels. Moreover, the up-regulated calponin-2, tropomyosins and myosin light chains indicated that elevated pCO2 probably caused disturbances in cytoskeleton structure in mantle tissue of oyster C. gigas. This work demonstrated that a combination of proteomics and metabolomics could provide important insights into the effects of OA at molecular levels. Copyright © 2014 Elsevier Inc. All rights reserved.

Dividing to unveil protein microheterogeneities: A Traveling Wave Ion Mobility study

PubMed Central

Halgand, F.; Habchi, Johnny; Cravello, Laetitia; Martinho, Marlène; Guigliarelli, Bruno; Longhi, Sonia

2011-01-01

Over-expression of a protein in a foreign host is often the only route toward an exhaustive characterization especially when purification from the natural source(s) is hardly achievable. The key issue in these studies relies on quality control of the purified recombinant protein to precisely determining its identity as well as any undesirable micro-heterogeneities. While standard proteomics approaches preclude unbiased search for modifications, the optional technique of top down MSMS requires the use of highly accurate and highly resolved experiments to reveal subtle sequence modifications. In the present study, the top down MSMS approach combined with Traveling Wave Ion Mobility (TWIM) separation was evaluated for its ability to achieve high sequence coverage and to reveal subtle micro-heterogeneities that were hitherto only accessible with FTICR-MS instruments. The power of this approach is herein illustrated in an in-depth analysis of both wt and K496C variant of the recombinant X domain (XD, aa 459-507) of the measles virus phosphoprotein expressed in E. coli. Using top down MSMS combined to TWIM, we show that XD samples occasionally exhibit a micro-heterogeneity that could not be anticipated from the nucleotide sequence of the encoding constructs and that likely reflects a genetic drift, neutral or not, occurring during expression. In addition, an MTSL nitroxide probe that was grafted on the K496C XD variant was shown to undergo oxidation and/or protonation in the ESI source leading to artifactual mass increases. PMID:21800924

Genome-wide screen uncovers novel pathways for tRNA processing and nuclear-cytoplasmic dynamics.

PubMed

Wu, Jingyan; Bao, Alicia; Chatterjee, Kunal; Wan, Yao; Hopper, Anita K

2015-12-15

Transfer ribonucleic acids (tRNAs) are essential for protein synthesis. However, key gene products involved in tRNA biogenesis and subcellular movement remain to be discovered. We conducted the first comprehensive unbiased analysis of the role of nearly an entire proteome in tRNA biology and describe 162 novel and 12 previously known Saccharomyces cerevisiae gene products that function in tRNA processing, turnover, and subcellular movement. tRNA nuclear export is of particular interest because it is essential, but the known tRNA exporters (Los1 [exportin-t] and Msn5 [exportin-5]) are unessential. We report that mutations of CRM1 (Exportin-1), MEX67/MTR2 (TAP/p15), and five nucleoporins cause accumulation of unspliced tRNA, a hallmark of defective tRNA nuclear export. CRM1 mutation genetically interacts with los1Δ and causes altered tRNA nuclear-cytoplasmic distribution. The data implicate roles for the protein and mRNA nuclear export machineries in tRNA nuclear export. Mutations of genes encoding actin cytoskeleton components and mitochondrial outer membrane proteins also cause accumulation of unspliced tRNA, likely due to defective splicing on mitochondria. Additional gene products, such as chromatin modification enzymes, have unanticipated effects on pre-tRNA end processing. Thus, this genome-wide screen uncovered putative novel pathways for tRNA nuclear export and extensive links between tRNA biology and other aspects of cell physiology. © 2015 Wu et al.; Published by Cold Spring Harbor Laboratory Press.

Genome-wide screen uncovers novel pathways for tRNA processing and nuclear–cytoplasmic dynamics

PubMed Central

Wu, Jingyan; Bao, Alicia; Chatterjee, Kunal; Wan, Yao; Hopper, Anita K.

2015-01-01

Transfer ribonucleic acids (tRNAs) are essential for protein synthesis. However, key gene products involved in tRNA biogenesis and subcellular movement remain to be discovered. We conducted the first comprehensive unbiased analysis of the role of nearly an entire proteome in tRNA biology and describe 162 novel and 12 previously known Saccharomyces cerevisiae gene products that function in tRNA processing, turnover, and subcellular movement. tRNA nuclear export is of particular interest because it is essential, but the known tRNA exporters (Los1 [exportin-t] and Msn5 [exportin-5]) are unessential. We report that mutations of CRM1 (Exportin-1), MEX67/MTR2 (TAP/p15), and five nucleoporins cause accumulation of unspliced tRNA, a hallmark of defective tRNA nuclear export. CRM1 mutation genetically interacts with los1Δ and causes altered tRNA nuclear–cytoplasmic distribution. The data implicate roles for the protein and mRNA nuclear export machineries in tRNA nuclear export. Mutations of genes encoding actin cytoskeleton components and mitochondrial outer membrane proteins also cause accumulation of unspliced tRNA, likely due to defective splicing on mitochondria. Additional gene products, such as chromatin modification enzymes, have unanticipated effects on pre-tRNA end processing. Thus, this genome-wide screen uncovered putative novel pathways for tRNA nuclear export and extensive links between tRNA biology and other aspects of cell physiology. PMID:26680305

Inter-lab proteomics: data mining in collaborative projects on the basis of the HUPO brain proteome project's pilot studies.

PubMed

Hamacher, Michael; Gröttrup, Bernd; Eisenacher, Martin; Marcus, Katrin; Park, Young Mok; Meyer, Helmut E; Kwon, Kyung-Hoon; Stephan, Christian

2011-01-01

Several projects were initiated by the Human Proteome Organisation (HUPO) focusing on the proteome analysis of distinct human organs. The initiative dedicated to the brain, its development and correlated diseases is the HUPO Brain Proteome Project (HUPO BPP). An objective data submission, storage, and reprocessing strategy have been established with the help of the results gained in a pilot study phase and within subsequent studies. The bioinformatic relevance of the data is drawn from the inter-laboratory comparisons as well as from the recalculation of all data sets submitted by the different groups. In the following, results of the single groups as well as the centralised reprocessing effort are summarised, demonstrating the added-value of this concerted work.

Head and neck cancer: proteomic advances and biomarker achievements.

PubMed

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

2010-11-01

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

Improvement of Soybean Products Through the Response Mechanism Analysis Using Proteomic Technique.

PubMed

Wang, Xin; Komatsu, Setsuko

Soybean is rich in protein/vegetable oil and contains several phytochemicals such as isoflavones and phenolic compounds. Because of the predominated nutritional values, soybean is considered as traditional health benefit food. Soybean is a widely cultivated crop; however, its growth and yield are markedly affected by adverse environmental conditions. Proteomic techniques make it feasible to map protein profiles both during soybean growth and under unfavorable conditions. The stress-responsive mechanisms during soybean growth have been uncovered with the help of proteomic studies. In this review, the history of soybean as food and the morphology/physiology of soybean are described. The utilization of proteomics during soybean germination and development is summarized. In addition, the stress-responsive mechanisms explored using proteomic techniques are reviewed in soybean. © 2017 Elsevier Inc. All rights reserved.

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.

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

PubMed Central

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

2016-01-01

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

Advancing Clinical Proteomics via Analysis Based on Biological Complexes: A Tale of Five Paradigms.

PubMed

Goh, Wilson Wen Bin; Wong, Limsoon

2016-09-02

Despite advances in proteomic technologies, idiosyncratic data issues, for example, incomplete coverage and inconsistency, resulting in large data holes, persist. Moreover, because of naïve reliance on statistical testing and its accompanying p values, differential protein signatures identified from such proteomics data have little diagnostic power. Thus, deploying conventional analytics on proteomics data is insufficient for identifying novel drug targets or precise yet sensitive biomarkers. Complex-based analysis is a new analytical approach that has potential to resolve these issues but requires formalization. We categorize complex-based analysis into five method classes or paradigms and propose an even-handed yet comprehensive evaluation rubric based on both simulated and real data. The first four paradigms are well represented in the literature. The fifth and newest paradigm, the network-paired (NP) paradigm, represented by a method called Extremely Small SubNET (ESSNET), dominates in precision-recall and reproducibility, maintains strong performance in small sample sizes, and sensitively detects low-abundance complexes. In contrast, the commonly used over-representation analysis (ORA) and direct-group (DG) test paradigms maintain good overall precision but have severe reproducibility issues. The other two paradigms considered here are the hit-rate and rank-based network analysis paradigms; both of these have good precision-recall and reproducibility, but they do not consider low-abundance complexes. Therefore, given its strong performance, NP/ESSNET may prove to be a useful approach for improving the analytical resolution of proteomics data. Additionally, given its stability, it may also be a powerful new approach toward functional enrichment tests, much like its ORA and DG counterparts.

Proteomics of the Human Placenta: Promises and Realities

PubMed Central

Robinson, J.M.; Ackerman, W.E.; Kniss, D.A.; Takizawa, T.; Vandré, D.D.

2015-01-01

Proteomics is an area of study that sets as its ultimate goal the global analysis of all of the proteins expressed in a biological system of interest. However, technical limitations currently hamper proteome-wide analyses of complex systems. In a more practical sense, a desired outcome of proteomics research is the translation of large protein data sets into formats that provide meaningful information regarding clinical conditions (e.g., biomarkers to serve as diagnostic and/or prognostic indicators of disease). Herein, we discuss placental proteomics by describing existing studies, pointing out their strengths and weaknesses. In so doing, we strive to inform investigators interested in this area of research about the current gap between hyperbolic promises and realities. Additionally, we discuss the utility of proteomics in discovery-based research, particularly as regards the capacity to unearth novel insights into placental biology. Importantly, when considering under studied systems such as the human placenta and diseases associated with abnormalities in placental function, proteomics can serve as a robust ‘shortcut’ to obtaining information unlikely to be garnered using traditional approaches. PMID:18222537

Mixed model approaches for diallel analysis based on a bio-model.

PubMed

Zhu, J; Weir, B S

1996-12-01

A MINQUE(1) procedure, which is minimum norm quadratic unbiased estimation (MINQUE) method with 1 for all the prior values, is suggested for estimating variance and covariance components in a bio-model for diallel crosses. Unbiasedness and efficiency of estimation were compared for MINQUE(1), restricted maximum likelihood (REML) and MINQUE theta which has parameter values for the prior values. MINQUE(1) is almost as efficient as MINQUE theta for unbiased estimation of genetic variance and covariance components. The bio-model is efficient and robust for estimating variance and covariance components for maternal and paternal effects as well as for nuclear effects. A procedure of adjusted unbiased prediction (AUP) is proposed for predicting random genetic effects in the bio-model. The jack-knife procedure is suggested for estimation of sampling variances of estimated variance and covariance components and of predicted genetic effects. Worked examples are given for estimation of variance and covariance components and for prediction of genetic merits.

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.

A Bioinformatics Workflow for Variant Peptide Detection in Shotgun Proteomics*

PubMed Central

Li, Jing; Su, Zengliu; Ma, Ze-Qiang; Slebos, Robbert J. C.; Halvey, Patrick; Tabb, David L.; Liebler, Daniel C.; Pao, William; Zhang, Bing

2011-01-01

Shotgun proteomics data analysis usually relies on database search. However, commonly used protein sequence databases do not contain information on protein variants and thus prevent variant peptides and proteins from been identified. Including known coding variations into protein sequence databases could help alleviate this problem. Based on our recently published human Cancer Proteome Variation Database, we have created a protein sequence database that comprehensively annotates thousands of cancer-related coding variants collected in the Cancer Proteome Variation Database as well as noncancer-specific ones from the Single Nucleotide Polymorphism Database (dbSNP). Using this database, we then developed a data analysis workflow for variant peptide identification in shotgun proteomics. The high risk of false positive variant identifications was addressed by a modified false discovery rate estimation method. Analysis of colorectal cancer cell lines SW480, RKO, and HCT-116 revealed a total of 81 peptides that contain either noncancer-specific or cancer-related variations. Twenty-three out of 26 variants randomly selected from the 81 were confirmed by genomic sequencing. We further applied the workflow on data sets from three individual colorectal tumor specimens. A total of 204 distinct variant peptides were detected, and five carried known cancer-related mutations. Each individual showed a specific pattern of cancer-related mutations, suggesting potential use of this type of information for personalized medicine. Compatibility of the workflow has been tested with four popular database search engines including Sequest, Mascot, X!Tandem, and MyriMatch. In summary, we have developed a workflow that effectively uses existing genomic data to enable variant peptide detection in proteomics. PMID:21389108

Subnanogram proteomics: impact of LC column selection, MS instrumentation and data analysis strategy on proteome coverage for trace samples

DOE PAGES

Zhu, Ying; Zhao, Rui; Piehowski, Paul D.; ...

2017-09-01

One of the greatest challenges for mass spectrometry (MS)-based proteomics is the limited ability to analyze small samples. Here in this study, we investigate the relative contributions of liquid chromatography (LC), MS instrumentation and data analysis methods with the aim of improving proteome coverage for sample sizes ranging from 0.5 ng to 50 ng. We show that the LC separations utilizing 30-μm-i.d. columns increase signal intensity by >3-fold relative to those using 75-μm-i.d. columns, leading to 32% increase in peptide identifications. The Orbitrap Fusion Lumos MS significantly boosted both sensitivity and sequencing speed relative to earlier generation Orbitraps (e.g., LTQ-Orbitrap),more » leading to a ~3-fold increase in peptide identifications and 1.7-fold increase in identified protein groups for 2 ng tryptic digests of the bacterium S. oneidensis. The Match Between Runs algorithm of open-source MaxQuant software further increased proteome coverage by ~95% for 0.5 ng samples and by ~42% for 2 ng samples. Using the best combination of the above variables, we were able to identify >3,000 proteins from 10 ng tryptic digests from both HeLa and THP-1 mammalian cell lines. We also identified >950 proteins from subnanogram archaeal/bacterial cocultures. Finally, the present ultrasensitive LC-MS platform achieves a level of proteome coverage not previously realized for ultra-small sample loadings, and is expected to facilitate the analysis of subnanogram samples, including single mammalian cells.« less

Top-down proteomics reveals a unique protein S-thiolation switch in Salmonella Typimurium in response to infection-like conditions

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

Ansong, Charles; Wu, Si; Meng, Da

Characterization of the mature protein complement in cells is crucial for a better understanding of cellular processes on a systems-wide scale. Bottom-up proteomic approaches often lead to loss of critical information about an endogenous protein’s actual state due to post translational modifications (PTMs) and other processes. Top-down approaches that involve analysis of the intact protein can address this concern but present significant analytical challenges related to the separation quality needed, measurement sensitivity, and speed that result in low throughput and limited coverage. Here we used single-dimension ultra high pressure liquid chromatography mass spectrometry to investigate the comprehensive ‘intact’ proteome ofmore » the Gram negative bacterial pathogen Salmonella Typhimurium. Top-down proteomics analysis revealed 563 unique proteins including 1665 proteoforms generated by PTMs, representing the largest microbial top-down dataset reported to date. Our analysis not only confirmed several previously recognized aspects of Salmonella biology and bacterial PTMs in general, but also revealed several novel biological insights. Of particular interest was differential utilization of the protein S-thiolation forms S-glutathionylation and S-cysteinylation in response to infection-like conditions versus basal conditions, which was corroborated by changes in corresponding biosynthetic pathways. This differential utilization highlights underlying metabolic mechanisms that modulate changes in cellular signaling, and represents to our knowledge the first report of S-cysteinylation in Gram negative bacteria. The demonstrated utility of our simple proteome-wide intact protein level measurement strategy for gaining biological insight should promote broader adoption and applications of top-down proteomics approaches.« less

Proteomic Analysis of Serum from Patients with Major Depressive Disorder to Compare Their Depressive and Remission Statuses

PubMed Central

Lee, Jiyeong; Joo, Eun-Jeong; Lim, Hee-Joung; Park, Jong-Moon; Lee, Kyu Young; Park, Arum; Seok, AeEun

2015-01-01

Objective Currently, there are a few biological markers to aid in the diagnosis and treatment of depression. However, it is not sufficient for diagnosis. We attempted to identify differentially expressed proteins during depressive moods as putative diagnostic biomarkers by using quantitative proteomic analysis of serum. Methods Blood samples were collected twice from five patients with major depressive disorder (MDD) at depressive status before treatment and at remission status during treatment. Samples were individually analyzed by liquid chromatography-tandem mass spectrometry for protein profiling. Differentially expressed proteins were analyzed by label-free quantification. Enzyme-linked immunosorbent assay (ELISA) results and receiver-operating characteristic (ROC) curves were used to validate the differentially expressed proteins. For validation, 8 patients with MDD including 3 additional patients and 8 matched normal controls were analyzed. Results The quantitative proteomic studies identified 10 proteins that were consistently upregulated or downregulated in 5 MDD patients. ELISA yielded results consistent with the proteomic analysis for 3 proteins. Expression levels were significantly different between normal controls and MDD patients. The 3 proteins were ceruloplasmin, inter-alpha-trypsin inhibitor heavy chain H4 and complement component 1qC, which were upregulated during the depressive status. The depressive status could be distinguished from the euthymic status from the ROC curves for these proteins, and this discrimination was enhanced when all 3 proteins were analyzed together. Conclusion This is the first proteomic study in MDD patients to compare intra-individual differences dependent on mood. This technique could be a useful approach to identify MDD biomarkers, but requires additional proteomic studies for validation. PMID:25866527

Image analysis tools and emerging algorithms for expression proteomics

PubMed Central

English, Jane A.; Lisacek, Frederique; Morris, Jeffrey S.; Yang, Guang-Zhong; Dunn, Michael J.

2012-01-01

Since their origins in academic endeavours in the 1970s, computational analysis tools have matured into a number of established commercial packages that underpin research in expression proteomics. In this paper we describe the image analysis pipeline for the established 2-D Gel Electrophoresis (2-DE) technique of protein separation, and by first covering signal analysis for Mass Spectrometry (MS), we also explain the current image analysis workflow for the emerging high-throughput ‘shotgun’ proteomics platform of Liquid Chromatography coupled to MS (LC/MS). The bioinformatics challenges for both methods are illustrated and compared, whilst existing commercial and academic packages and their workflows are described from both a user’s and a technical perspective. Attention is given to the importance of sound statistical treatment of the resultant quantifications in the search for differential expression. Despite wide availability of proteomics software, a number of challenges have yet to be overcome regarding algorithm accuracy, objectivity and automation, generally due to deterministic spot-centric approaches that discard information early in the pipeline, propagating errors. We review recent advances in signal and image analysis algorithms in 2-DE, MS, LC/MS and Imaging MS. Particular attention is given to wavelet techniques, automated image-based alignment and differential analysis in 2-DE, Bayesian peak mixture models and functional mixed modelling in MS, and group-wise consensus alignment methods for LC/MS. PMID:21046614

Entropic uncertainty relations and locking: Tight bounds for mutually unbiased bases

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

Ballester, Manuel A.; Wehner, Stephanie

We prove tight entropic uncertainty relations for a large number of mutually unbiased measurements. In particular, we show that a bound derived from the result by Maassen and Uffink [Phys. Rev. Lett. 60, 1103 (1988)] for two such measurements can in fact be tight for up to {radical}(d) measurements in mutually unbiased bases. We then show that using more mutually unbiased bases does not always lead to a better locking effect. We prove that the optimal bound for the accessible information using up to {radical}(d) specific mutually unbiased bases is log d/2, which is the same as can be achievedmore » by using only two bases. Our result indicates that merely using mutually unbiased bases is not sufficient to achieve a strong locking effect and we need to look for additional properties.« less

YahO protein as a calibrant for top-down proteomic identification of Shiga toxin using MALDI-TOF-TOF-MS/MS and post-source decay

USDA-ARS?s Scientific Manuscript database

Matrix-assisted laser desorption/ionization tandem time-of-flight (MALDI-TOF-TOF) mass spectrometry is increasingly utilized for rapid top-down proteomic identification of proteins. This identification may involve analysis of either a pure protein or a protein mixture. For analysis of a pure protein...

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

The RasGAP Proteins Ira2 and Neurofibromin Are Negatively Regulated by Gpb1 in Yeast and ETEA in Humans▿

PubMed Central

Phan, Vernon T.; Ding, Vivianne W.; Li, Fenglei; Chalkley, Robert J.; Burlingame, Alma; McCormick, Frank

2010-01-01

The neurofibromatosis type 1 (NF1) gene encodes the GTPase-activating protein (GAP) neurofibromin, which negatively regulates Ras activity. The yeast Saccharomyces cerevisiae has two neurofibromin homologs, Ira1 and Ira2. To understand how these proteins are regulated, we utilized an unbiased proteomics approach to identify Ira2 and neurofibromin binding partners. We demonstrate that the Gpb1/Krh2 protein binds and negatively regulates Ira2 by promoting its ubiquitin-dependent proteolysis. We extended our findings to show that in mammalian cells, the ETEA/UBXD8 protein directly interacts with and negatively regulates neurofibromin. ETEA contains both UBA and UBX domains. Overexpression of ETEA downregulates neurofibromin in human cells. Purified ETEA, but not a mutant of ETEA that lacks the UBX domain, ubiquitinates the neurofibromin GAP-related domain in vitro. Silencing of ETEA expression increases neurofibromin levels and downregulates Ras activity. These findings provide evidence for conserved ubiquitination pathways regulating the RasGAP proteins Ira2 (in yeast) and neurofibromin (in humans). PMID:20160012

Inflammatory signaling in human tuberculosis granulomas is spatially organized.

PubMed

Marakalala, Mohlopheni J; Raju, Ravikiran M; Sharma, Kirti; Zhang, Yanjia J; Eugenin, Eliseo A; Prideaux, Brendan; Daudelin, Isaac B; Chen, Pei-Yu; Booty, Matthew G; Kim, Jin Hee; Eum, Seok Yong; Via, Laura E; Behar, Samuel M; Barry, Clifton E; Mann, Matthias; Dartois, Véronique; Rubin, Eric J

2016-05-01

Granulomas are the pathological hallmark of tuberculosis (TB). However, their function and mechanisms of formation remain poorly understood. To understand the role of granulomas in TB, we analyzed the proteomes of granulomas from subjects with tuberculosis in an unbiased manner. Using laser-capture microdissection, mass spectrometry and confocal microscopy, we generated detailed molecular maps of human granulomas. We found that the centers of granulomas have a pro-inflammatory environment that is characterized by the presence of antimicrobial peptides, reactive oxygen species and pro-inflammatory eicosanoids. Conversely, the tissue surrounding the caseum has a comparatively anti-inflammatory signature. These findings are consistent across a set of six human subjects and in rabbits. Although the balance between systemic pro- and anti-inflammatory signals is crucial to TB disease outcome, here we find that these signals are physically segregated within each granuloma. From the protein and lipid snapshots of human and rabbit lesions analyzed here, we hypothesize that the pathologic response to TB is shaped by the precise anatomical localization of these inflammatory pathways during the development of the granuloma.

Screening the receptorome to discover the molecular targets for plant-derived psychoactive compounds: a novel approach for CNS drug discovery.

PubMed

Roth, Bryan L; Lopez, Estela; Beischel, Scott; Westkaemper, Richard B; Evans, Jon M

2004-05-01

Because psychoactive plants exert profound effects on human perception, emotion, and cognition, discovering the molecular mechanisms responsible for psychoactive plant actions will likely yield insights into the molecular underpinnings of human consciousness. Additionally, it is likely that elucidation of the molecular targets responsible for psychoactive drug actions will yield validated targets for CNS drug discovery. This review article focuses on an unbiased, discovery-based approach aimed at uncovering the molecular targets responsible for psychoactive drug actions wherein the main active ingredients of psychoactive plants are screened at the "receptorome" (that portion of the proteome encoding receptors). An overview of the receptorome is given and various in silico, public-domain resources are described. Newly developed tools for the in silico mining of data derived from the National Institute of Mental Health Psychoactive Drug Screening Program's (NIMH-PDSP) K(i) Database (K(i) DB) are described in detail. Additionally, three case studies aimed at discovering the molecular targets responsible for Hypericum perforatum, Salvia divinorum, and Ephedra sinica actions are presented. Finally, recommendations are made for future studies.

Identification of MOSPD2, a novel scaffold for endoplasmic reticulum membrane contact sites.

PubMed

Di Mattia, Thomas; Wilhelm, Léa P; Ikhlef, Souade; Wendling, Corinne; Spehner, Danièle; Nominé, Yves; Giordano, Francesca; Mathelin, Carole; Drin, Guillaume; Tomasetto, Catherine; Alpy, Fabien

2018-06-01

Membrane contact sites are cellular structures that mediate interorganelle exchange and communication. The two major tether proteins of the endoplasmic reticulum (ER), VAP-A and VAP-B, interact with proteins from other organelles that possess a small VAP-interacting motif, named FFAT [two phenylalanines (FF) in an acidic track (AT)]. In this study, using an unbiased proteomic approach, we identify a novel ER tether named motile sperm domain-containing protein 2 (MOSPD2). We show that MOSPD2 possesses a Major Sperm Protein (MSP) domain which binds FFAT motifs and consequently allows membrane tethering in vitro MOSPD2 is an ER-anchored protein, and it interacts with several FFAT-containing tether proteins from endosomes, mitochondria, or Golgi. Consequently, MOSPD2 and these organelle-bound proteins mediate the formation of contact sites between the ER and endosomes, mitochondria, or Golgi. Thus, we characterized here MOSPD2, a novel tethering component related to VAP proteins, bridging the ER with a variety of distinct organelles. © 2018 The Authors. Published under the terms of the CC BY NC ND 4.0 license.

Survey of large protein complexes D. vulgaris reveals great structural diversity

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

Han, B.-G.; Dong, M.; Liu, H.

2009-08-15

An unbiased survey has been made of the stable, most abundant multi-protein complexes in Desulfovibrio vulgaris Hildenborough (DvH) that are larger than Mr {approx} 400 k. The quaternary structures for 8 of the 16 complexes purified during this work were determined by single-particle reconstruction of negatively stained specimens, a success rate {approx}10 times greater than that of previous 'proteomic' screens. In addition, the subunit compositions and stoichiometries of the remaining complexes were determined by biochemical methods. Our data show that the structures of only two of these large complexes, out of the 13 in this set that have recognizable functions,more » can be modeled with confidence based on the structures of known homologs. These results indicate that there is significantly greater variability in the way that homologous prokaryotic macromolecular complexes are assembled than has generally been appreciated. As a consequence, we suggest that relying solely on previously determined quaternary structures for homologous proteins may not be sufficient to properly understand their role in another cell of interest.« less

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.

Empirical Likelihood in Nonignorable Covariate-Missing Data Problems.

PubMed

Xie, Yanmei; Zhang, Biao

2017-04-20

Missing covariate data occurs often in regression analysis, which frequently arises in the health and social sciences as well as in survey sampling. We study methods for the analysis of a nonignorable covariate-missing data problem in an assumed conditional mean function when some covariates are completely observed but other covariates are missing for some subjects. We adopt the semiparametric perspective of Bartlett et al. (Improving upon the efficiency of complete case analysis when covariates are MNAR. Biostatistics 2014;15:719-30) on regression analyses with nonignorable missing covariates, in which they have introduced the use of two working models, the working probability model of missingness and the working conditional score model. In this paper, we study an empirical likelihood approach to nonignorable covariate-missing data problems with the objective of effectively utilizing the two working models in the analysis of covariate-missing data. We propose a unified approach to constructing a system of unbiased estimating equations, where there are more equations than unknown parameters of interest. One useful feature of these unbiased estimating equations is that they naturally incorporate the incomplete data into the data analysis, making it possible to seek efficient estimation of the parameter of interest even when the working regression function is not specified to be the optimal regression function. We apply the general methodology of empirical likelihood to optimally combine these unbiased estimating equations. We propose three maximum empirical likelihood estimators of the underlying regression parameters and compare their efficiencies with other existing competitors. We present a simulation study to compare the finite-sample performance of various methods with respect to bias, efficiency, and robustness to model misspecification. The proposed empirical likelihood method is also illustrated by an analysis of a data set from the US National Health and Nutrition Examination Survey (NHANES).

Identification of Bicarbonate as a Trigger and Genes Involved with Extracellular DNA Export in Mycobacterial Biofilms

PubMed Central

Rose, Sasha J.

2016-01-01

ABSTRACT Extracellular DNA (eDNA) is an integral biofilm matrix component of numerous pathogens, including nontuberculous mycobacteria (NTM). Cell lysis is the source of eDNA in certain bacteria, but the source of eDNA remains unidentified for NTM, as well as for other eDNA-containing bacterial species. In this study, conditions affecting eDNA export were examined, and genes involved with the eDNA export mechanism were identified. After a method for monitoring eDNA in real time in undisturbed biofilms was established, different conditions affecting eDNA were investigated. Bicarbonate positively influenced eDNA export in a pH-independent manner in Mycobacterium avium, M. abscessus, and M. chelonae. The surface-exposed proteome of M. avium in eDNA-containing biofilms revealed abundant carbonic anhydrases. Chemical inhibition of carbonic anhydrases with ethoxzolamide significantly reduced eDNA export. An unbiased transposon mutant library screen for eDNA export in M. avium identified many severely eDNA-attenuated mutants, including one not expressing a unique FtsK/SpoIIIE-like DNA-transporting pore, two with inactivation of carbonic anhydrases, and nine with inactivation of genes belonging to a unique genomic region, as well as numerous mutants involved in metabolism and energy production. Complementation of nine mutants that included the FtsK/SpoIIIE and carbonic anhydrase significantly restored eDNA export. Interestingly, several attenuated eDNA mutants have mutations in genes encoding proteins that were found with the surface proteomics, and many more mutations are localized in operons potentially encoding surface proteins. Collectively, our data strengthen the evidence of eDNA export being an active mechanism that is activated by the bacterium responding to bicarbonate. PMID:27923918

Instant Integrated Ultradeep Quantitative-structural Membrane Proteomics Discovered Post-translational Modification Signatures for Human Cys-loop Receptor Subunit Bias.

PubMed

Zhang, Xi

2016-12-01

Neurotransmitter ligand-gated ion channels (LGICs) are widespread and pivotal in brain functions. Unveiling their structure-function mechanisms is crucial to drive drug discovery, and demands robust proteomic quantitation of expression, post-translational modifications (PTMs) and dynamic structures. Yet unbiased digestion of these modified transmembrane proteins-at high efficiency and peptide reproducibility-poses the obstacle. Targeting both enzyme-substrate contacts and PTMs for peptide formation and detection, we devised flow-and-detergent-facilitated protease and de-PTM digestions for deep sequencing (FDD) method that combined omni-compatible detergent, tandem immobilized protease/PNGase columns, and Cys-selective reduction/alkylation, to achieve streamlined ultradeep peptide preparation within minutes not days, at high peptide reproducibility and low abundance-bias. FDD transformed enzyme-protein contacts into equal catalytic travel paths through enzyme-excessive columns regardless of protein abundance, removed products instantly preventing inhibition, tackled intricate structures via sequential multiple micro-digestions along the flow, and precisely controlled peptide formation by flow rate. Peptide-stage reactions reduced steric bias; low contamination deepened MS/MS scan; distinguishing disulfide from M oxidation and avoiding gain/loss artifacts unmasked protein-endogenous oxidation states. Using a recent interactome of 285-kDa human GABA type A receptor, this pilot study validated FDD platform's applicability to deep sequencing (up to 99% coverage), H/D-exchange and TMT-based structural mapping. FDD discovered novel subunit-specific PTM signatures, including unusual nontop-surface N-glycosylations, that may drive subunit biases in human Cys-loop LGIC assembly and pharmacology, by redefining subunit/ligand interfaces and connecting function domains. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Proteome-wide muscle protein fractional synthesis rates predict muscle mass gain in response to a selective androgen receptor modulator in rats.

PubMed

Shankaran, Mahalakshmi; Shearer, Todd W; Stimpson, Stephen A; Turner, Scott M; King, Chelsea; Wong, Po-Yin Anne; Shen, Ying; Turnbull, Philip S; Kramer, Fritz; Clifton, Lisa; Russell, Alan; Hellerstein, Marc K; Evans, William J

2016-03-15

Biomarkers of muscle protein synthesis rate could provide early data demonstrating anabolic efficacy for treating muscle-wasting conditions. Androgenic therapies have been shown to increase muscle mass primarily by increasing the rate of muscle protein synthesis. We hypothesized that the synthesis rate of large numbers of individual muscle proteins could serve as early response biomarkers and potentially treatment-specific signaling for predicting the effect of anabolic treatments on muscle mass. Utilizing selective androgen receptor modulator (SARM) treatment in the ovariectomized (OVX) rat, we applied an unbiased, dynamic proteomics approach to measure the fractional synthesis rates (FSR) of 167-201 individual skeletal muscle proteins in triceps, EDL, and soleus. OVX rats treated with a SARM molecule (GSK212A at 0.1, 0.3, or 1 mg/kg) for 10 or 28 days showed significant, dose-related increases in body weight, lean body mass, and individual triceps but not EDL or soleus weights. Thirty-four out of the 94 proteins measured from the triceps of all rats exhibited a significant, dose-related increase in FSR after 10 days of SARM treatment. For several cytoplasmic proteins, including carbonic anhydrase 3, creatine kinase M-type (CK-M), pyruvate kinase, and aldolase-A, a change in 10-day FSR was strongly correlated (r(2) = 0.90-0.99) to the 28-day change in lean body mass and triceps weight gains, suggesting a noninvasive measurement of SARM effects. In summary, FSR of multiple muscle proteins measured by dynamics of moderate- to high-abundance proteins provides early biomarkers of the anabolic response of skeletal muscle to SARM. Copyright © 2016 the American Physiological Society.

Systematic Analysis of Cell-Type Differences in the Epithelial Secretome Reveals Insights into the Pathogenesis of RSV-Induced Lower Respiratory Tract Infections

PubMed Central

Zhao, Yingxin; Jamaluddin, Mohammad; Zhang, Yueqing; Sun, Hong; Ivanciuc, Teodora; Garofalo, Roberto P.; Brasier, Allan R.

2017-01-01

Lower respiratory tract infections (LRTIs) from Respiratory Syncytial Virus (RSV) are due, in part, to secreted signals from lower airway cells that modify immune response and trigger airway remodeling. To understand this process, we applied an unbiased quantitative proteomics analysis of the RSV-induced epithelial secretory response in cells representative of the trachea (hBECs) vs small airway bronchiolar cells (hSAECs). A workflow was established using telomerase- immortalized human epithelial cells that revealed highly reproducible cell type-specific differences in both secreted proteins and nanoparticles (exosomes). Approximately one-third of secretome proteins are exosomal, with the remainder from lysosomal and vacuolar compartments. We applied this workflow to three independently derived primary human cultures from trachea (phBECs) vs bronchioles (phSAECs). 577 differentially expressed proteins from control supernatants and 966 differentially expressed proteins from RSV-infected cell supernatants were identified at a 1% false discovery rate (FDR). Fifteen proteins unique to RSV-infected phBECs were regulated by epithelial-specific ets homology factor (EHF). 106 proteins unique to RSV-infected hSAECs were regulated by the transcription factor NFκB. In this latter group, we validated the differential expression of Chemokine (C-C Motif) Ligand 20 (CCL20)/macrophage-inducible protein (MIP)3α, thymic stromal lymphopoietin (TSLP) and chemokine (CC) ligand 3-like 1(CCL3-L1) because of their roles in Th2 polarization. CCL20/MIP3α was the most active mucin-inducing factor in the RSV-infected hSAEC secretome, and was differentially expressed in smaller airways in a mouse model of RSV infection. These studies provide insights into the complexity of innate responses, and regional differences in epithelial secretome participating in RSV LRTI-induced airway remodeling. PMID:28258195

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.

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.

Proteomic Analysis of the Arabidopsis Nucleolus Suggests Novel Nucleolar FunctionsD⃞

PubMed Central

Pendle, Alison F.; Clark, Gillian P.; Boon, Reinier; Lewandowska, Dominika; Lam, Yun Wah; Andersen, Jens; Mann, Matthias; Lamond, Angus I.; Brown, John W. S.; Shaw, Peter J.

2005-01-01

The eukaryotic nucleolus is involved in ribosome biogenesis and a wide range of other RNA metabolism and cellular functions. An important step in the functional analysis of the nucleolus is to determine the complement of proteins of this nuclear compartment. Here, we describe the first proteomic analysis of plant (Arabidopsis thaliana) nucleoli, in which we have identified 217 proteins. This allows a direct comparison of the proteomes of an important nuclear structure between two widely divergent species: human and Arabidopsis. The comparison identified many common proteins, plant-specific proteins, proteins of unknown function found in both proteomes, and proteins that were nucleolar in plants but nonnucleolar in human. Seventy-two proteins were expressed as GFP fusions and 87% showed nucleolar or nucleolar-associated localization. In a striking and unexpected finding, we have identified six components of the postsplicing exon-junction complex (EJC) involved in mRNA export and nonsense-mediated decay (NMD)/mRNA surveillance. This association was confirmed by GFP-fusion protein localization. These results raise the possibility that in plants, nucleoli may have additional functions in mRNA export or surveillance. PMID:15496452

Comparative Proteomic and Transcriptomic Analysis of Follistatin-Induced Skeletal Muscle Hypertrophy.

PubMed

Barbé, Caroline; Bray, Fabrice; Gueugneau, Marine; Devassine, Stéphanie; Lause, Pascale; Tokarski, Caroline; Rolando, Christian; Thissen, Jean-Paul

2017-10-06

Skeletal muscle, the most abundant body tissue, plays vital roles in locomotion and metabolism. Myostatin is a negative regulator of skeletal muscle mass. In addition to increasing muscle mass, Myostatin inhibition impacts muscle contractility and energy metabolism. To decipher the mechanisms of action of the Myostatin inhibitors, we used proteomic and transcriptomic approaches to investigate the changes induced in skeletal muscles of transgenic mice overexpressing Follistatin, a physiological Myostatin inhibitor. Our proteomic workflow included a fractionation step to identify weakly expressed proteins and a comparison of fast versus slow muscles. Functional annotation of altered proteins supports the phenotypic changes induced by Myostatin inhibition, including modifications in energy metabolism, fiber type, insulin and calcium signaling, as well as membrane repair and regeneration. Less than 10% of the differentially expressed proteins were found to be also regulated at the mRNA level but the Biological Process annotation, and the KEGG pathways analysis of transcriptomic results shows a great concordance with the proteomic data. Thus this study describes the most extensive omics analysis of muscle overexpressing Follistatin, providing molecular-level insights to explain the observed muscle phenotypic changes.

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.

Proteome alteration induced by hTERT transfection of human fibroblast cells.

PubMed

Mazzucchelli, Gabriel D; Gabelica, Valérie; Smargiasso, Nicolas; Fléron, Maximilien; Ashimwe, Wilson; Rosu, Frédéric; De Pauw-Gillet, Marie-Claire; Riou, Jean-François; De Pauw, Edwin

2008-04-17

Telomerase confers cellular immortality by elongating telomeres, thereby circumventing the Hayflick limit. Extended-life-span cells have been generated by transfection with the human telomerase reverse transcriptase (hTERT) gene. hTERT transfected cell lines may be of outstanding interest to monitor the effect of drugs targeting the telomerase activity. The incidence of hTERT gene transfection at the proteome level is a prerequisite to that purpose. The effect of the transfection has been studied on the proteome of human fibroblast (WI38). Cytosolic and nuclear fractions of WI38 cells, empty vector transfected WI38 (WI38-HPV) and hTERT WI38 cells were submitted to a 2D-DIGE (Two-Dimensional Differential In-Gel Electrophoresis) analysis. Only spots that had a similar abundance in WI38 and WI38-HPV, but were differentially expressed in WI38 hTERT were selected for MS identification. This method directly points to the proteins linked with the hTERT expression. Number of false positive differentially expressed proteins has been excluded by using control WI38-HPV cells. The proteome alteration induced by hTERT WI38 transfection should be taken into account in subsequent use of the cell line for anti-telomerase drugs evaluation. 2D-DIGE experiment shows that 57 spots out of 2246 are significantly differentially expressed in the cytosolic fraction due to hTERT transfection, and 38 were confidently identified. In the nuclear fraction, 44 spots out of 2172 were selected in the differential proteome analysis, and 14 were identified. The results show that, in addition to elongating telomeres, hTERT gene transfection has other physiological roles, among which an enhanced ER capacity and a potent cell protection against apoptosis. We show that the methodology reduces the complexity of the proteome analysis and highlights proteins implicated in other processes than telomere elongation. hTERT induced proteome changes suggest that telomerase expression enhances natural cell repair mechanisms and stress resistance probably required for long term resistance of immortalized cells. Thus, hTERT transfected cells can not be only consider as an immortal equivalent to parental cells but also as cells which are over-resistant to stresses. These findings are the prerequisite for any larger proteomics aiming to evaluate anti-telomerase drugs proteome alteration and thus therapeutics induced cell reactions.

PubMed Central

Castagnola, M.; Scarano, E.; Messana, I.; Cabras, T.; Iavarone, F.; Di Cintio, G.; Fiorita, A.; De Corso, E.; Paludetti, G.

2017-01-01

SUMMARY Saliva testing is a non-invasive and inexpensive test that can serve as a source of information useful for diagnosis of disease. As we enter the era of genomic technologies and –omic research, collection of saliva has increased. Recent proteomic platforms have analysed the human salivary proteome and characterised about 3000 differentially expressed proteins and peptides: in saliva, more than 90% of proteins in weight are derived from the secretion of three couples of "major" glands; all the other components are derived from minor glands, gingival crevicular fluid, mucosal exudates and oral microflora. The most common aim of proteomic analysis is to discriminate between physiological and pathological conditions. A proteomic protocol to analyze the whole saliva proteome is not currently available. It is possible distinguish two type of proteomic platforms: top-down proteomics investigates intact naturally-occurring structure of a protein under examination; bottom-up proteomics analyses peptide fragments after pre-digestion (typically with trypsin). Because of this heterogeneity, many different biomarkers may be proposed for the same pathology. The salivary proteome has been characterised in several diseases: oral squamous cell carcinoma and oral leukoplakia, chronic graft-versus-host disease Sjögren's syndrome and other autoimmune disorders such as SAPHO, schizophrenia and bipolar disorder, and genetic diseases like Down's Syndrome and Wilson disease. The results of research reported herein suggest that in the near future human saliva will be a relevant diagnostic fluid for clinical diagnosis and prognosis. PMID:28516971

The State of the Human Proteome in 2013 as viewed through PeptideAtlas: Comparing the Kidney, Urine, and Plasma Proteomes for the Biology and Disease-driven Human Proteome Project

PubMed Central

Farrah, Terry; Deutsch, Eric W.; Omenn, Gilbert S.; Sun, Zhi; Watts, Julian D.; Yamamoto, Tadashi; Shteynberg, David; Harris, Micheleen M.; Moritz, Robert L.

2014-01-01

The kidney, urine, and plasma proteomes are intimately related: proteins and metabolic waste products are filtered from the plasma by the kidney and excreted via the urine, while kidney proteins may be secreted into the circulation or released into the urine. Shotgun proteomics datasets derived from human kidney, urine, and plasma samples were collated and processed using a uniform software pipeline, and relative protein abundances were estimated by spectral counting. The resulting PeptideAtlas builds yielded 4005, 2491, and 3553 nonredundant proteins at 1% FDR for the kidney, urine, and plasma proteomes, respectively—for kidney and plasma, the largest high-confidence protein sets to date. The same pipeline applied to all available human data yielded a 2013 Human PeptideAtlas build containing 12,644 nonredundant proteins and at least one peptide for each of ~14,000 Swiss-Prot entries, an increase over 2012 of ~7.5% of the predicted human proteome. We demonstrate that abundances are correlated between plasma and urine, examine the most abundant urine proteins not derived from either plasma or kidney, and consider the biomarker potential of proteins associated with renal decline. This analysis forms part of the Biology and Disease-driven Human Proteome Project (B/D-HPP) and a contribution to the Chromosome-centric Human Proteome Project (C-HPP) special issue. PMID:24261998

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

PubMed Central

Casadonte, Rita; Caprioli, Richard M

2012-01-01

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

Exploring the Arabidopsis proteome: influence of protein solubilization buffers on proteome coverage.

PubMed

Marondedze, Claudius; Wong, Aloysius; Groen, Arnoud; Serrano, Natalia; Jankovic, Boris; Lilley, Kathryn; Gehring, Christoph; Thomas, Ludivine

2014-12-31

The study of proteomes provides new insights into stimulus-specific responses of protein synthesis and turnover, and the role of post-translational modifications at the systems level. Due to the diverse chemical nature of proteins and shortcomings in the analytical techniques used in their study, only a partial display of the proteome is achieved in any study, and this holds particularly true for plant proteomes. Here we show that different solubilization and separation methods have profound effects on the resulting proteome. In particular, we observed that the type of detergents employed in the solubilization buffer preferentially enriches proteins in different functional categories. These include proteins with a role in signaling, transport, response to temperature stimuli and metabolism. This data may offer a functional bias on comparative analysis studies. In order to obtain a broader coverage, we propose a two-step solubilization protocol with first a detergent-free buffer and then a second step utilizing a combination of two detergents to solubilize proteins.

Exploring the Arabidopsis Proteome: Influence of Protein Solubilization Buffers on Proteome Coverage

PubMed Central

Marondedze, Claudius; Wong, Aloysius; Groen, Arnoud; Serrano, Natalia; Jankovic, Boris; Lilley, Kathryn; Gehring, Christoph; Thomas, Ludivine

2014-01-01

The study of proteomes provides new insights into stimulus-specific responses of protein synthesis and turnover, and the role of post-translational modifications at the systems level. Due to the diverse chemical nature of proteins and shortcomings in the analytical techniques used in their study, only a partial display of the proteome is achieved in any study, and this holds particularly true for plant proteomes. Here we show that different solubilization and separation methods have profound effects on the resulting proteome. In particular, we observed that the type of detergents employed in the solubilization buffer preferentially enriches proteins in different functional categories. These include proteins with a role in signaling, transport, response to temperature stimuli and metabolism. This data may offer a functional bias on comparative analysis studies. In order to obtain a broader coverage, we propose a two-step solubilization protocol with first a detergent-free buffer and then a second step utilizing a combination of two detergents to solubilize proteins. PMID:25561235

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

Methodologies and Perspectives of Proteomics Applied to Filamentous Fungi: From Sample Preparation to Secretome Analysis

PubMed Central

Bianco, Linda; Perrotta, Gaetano

2015-01-01

Filamentous fungi possess the extraordinary ability to digest complex biomasses and mineralize numerous xenobiotics, as consequence of their aptitude to sensing the environment and regulating their intra and extra cellular proteins, producing drastic changes in proteome and secretome composition. Recent advancement in proteomic technologies offers an exciting opportunity to reveal the fluctuations of fungal proteins and enzymes, responsible for their metabolic adaptation to a large variety of environmental conditions. Here, an overview of the most commonly used proteomic strategies will be provided; this paper will range from sample preparation to gel-free and gel-based proteomics, discussing pros and cons of each mentioned state-of-the-art technique. The main focus will be kept on filamentous fungi. Due to the biotechnological relevance of lignocellulose degrading fungi, special attention will be finally given to their extracellular proteome, or secretome. Secreted proteins and enzymes will be discussed in relation to their involvement in bio-based processes, such as biomass deconstruction and mycoremediation. PMID:25775160

Methodologies and perspectives of proteomics applied to filamentous fungi: from sample preparation to secretome analysis.

PubMed

Bianco, Linda; Perrotta, Gaetano

2015-03-12

Filamentous fungi possess the extraordinary ability to digest complex biomasses and mineralize numerous xenobiotics, as consequence of their aptitude to sensing the environment and regulating their intra and extra cellular proteins, producing drastic changes in proteome and secretome composition. Recent advancement in proteomic technologies offers an exciting opportunity to reveal the fluctuations of fungal proteins and enzymes, responsible for their metabolic adaptation to a large variety of environmental conditions. Here, an overview of the most commonly used proteomic strategies will be provided; this paper will range from sample preparation to gel-free and gel-based proteomics, discussing pros and cons of each mentioned state-of-the-art technique. The main focus will be kept on filamentous fungi. Due to the biotechnological relevance of lignocellulose degrading fungi, special attention will be finally given to their extracellular proteome, or secretome. Secreted proteins and enzymes will be discussed in relation to their involvement in bio-based processes, such as biomass deconstruction and mycoremediation.

NCI's Clinical Proteomic Tumor Analysis Consortium 1st Annual Scientific Symposium | Office of Cancer Clinical Proteomics Research

Cancer.gov

On behalf of the National Cancer Institute and the Office of Cancer Clinical Proteomics Research, you are invited to the First Annual CPTAC Scientific Symposium on Wednesday, November 13, 2013. The purpose of this symposium, which consists of plenary and poster sessions, is for investigators from CPTAC community and beyond to share and discuss novel biological discoveries, analytical methods, and translational approaches using CPTAC data.

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.

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.

Recent advances and opportunities in proteomic analyses of tumour heterogeneity.

PubMed

Bateman, Nicholas W; Conrads, Thomas P

2018-04-01

Solid tumour malignancies comprise a highly variable admixture of tumour and non-tumour cellular populations, forming a complex cellular ecosystem and tumour microenvironment. This tumour heterogeneity is not incidental, and is known to correlate with poor patient prognosis for many cancer types. Indeed, non-malignant cell populations, such as vascular endothelial and immune cells, are known to play key roles supporting and, in some cases, driving aggressive tumour biology, and represent targets of emerging therapeutics, such as antiangiogenesis and immune checkpoint inhibitors. The biochemical interplay between these cellular populations and how they contribute to molecular tumour heterogeneity remains enigmatic, particularly from the perspective of the tumour proteome. This review focuses on recent advances in proteomic methods, namely imaging mass spectrometry, single-cell proteomic techniques, and preanalytical sample processing, that are uniquely positioned to enable detailed analysis of discrete cellular populations within tumours to improve our understanding of tumour proteomic heterogeneity. This review further emphasizes the opportunity afforded by the application of these techniques to the analysis of tumour heterogeneity in formalin-fixed paraffin-embedded archival tumour tissues, as these represent an invaluable resource for retrospective analyses that is now routinely accessible, owing to recent technological and methodological advances in tumour tissue proteomics. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Leaf proteome alterations in the context of physiological and morphological responses to drought and heat stress in barley (Hordeum vulgare L.)

PubMed Central

von Korff, M.

2013-01-01

The objective of this study was to identify barley leaf proteins differentially regulated in response to drought and heat and the combined stresses in context of the morphological and physiological changes that also occur. The Syrian landrace Arta and the Australian cultivar Keel were subjected to drought, high temperature, or a combination of both treatments starting at heading. Changes in the leaf proteome were identified using differential gel electrophoresis and mass spectrometry. The drought treatment caused strong reductions of biomass and yield, while photosynthetic performance and the proteome were not significantly changed. In contrast, the heat treatment and the combination of heat and drought reduced photosynthetic performance and caused changes of the leaf proteome. The proteomic analysis identified 99 protein spots differentially regulated in response to heat treatment, 14 of which were regulated in a genotype-specific manner. Differentially regulated proteins predominantly had functions in photosynthesis, but also in detoxification, energy metabolism, and protein biosynthesis. The analysis indicated that de novo protein biosynthesis, protein quality control mediated by chaperones and proteases, and the use of alternative energy resources, i.e. glycolysis, play important roles in adaptation to heat stress. In addition, genetic variation identified in the proteome, in plant growth and photosynthetic performance in response to drought and heat represent stress adaption mechanisms to be exploited in future crop breeding efforts. PMID:23918963

Protein expression profiles of human lymph and plasma mapped by 2D-DIGE and 1D SDS–PAGE coupled with nanoLC–ESI–MS/MS bottom-up proteomics

PubMed Central

Clement, Cristina C.; Aphkhazava, David; Nieves, Edward; Callaway, Myrasol; Olszewski, Waldemar; Rotzschke, Olaf; Santambrogio, Laura

2013-01-01

In this study a proteomic approach was used to define the protein content of matched samples of afferent prenodal lymph and plasma derived from healthy volunteers. The analysis was performed using two analytical methodologies coupled with nanoliquid chromatography-tandem mass spectrometry: one-dimensional gel electrophoresis (1DEF nanoLC Orbitrap–ESI–MS/MS), and two-dimensional fluorescence difference-in-gel electrophoresis (2D-DIGE nanoLC–ESI–MS/MS). The 253 significantly identified proteins (p<0.05), obtained from the tandem mass spectrometry data, were further analyzed with pathway analysis (IPA) to define the functional signature of prenodal lymph and matched plasma. The 1DEF coupled with nanoLC–MS–MS revealed that the common proteome between the two biological fluids (144 out of 253 proteins) was dominated by complement activation and blood coagulation components, transporters and protease inhibitors. The enriched proteome of human lymph (72 proteins) consisted of products derived from the extracellular matrix, apoptosis and cellular catabolism. In contrast, the enriched proteome of human plasma (37 proteins) consisted of soluble molecules of the coagulation system and cell–cell signaling factors. The functional networks associated with both common and source-distinctive proteomes highlight the principal biological activity of these immunologically relevant body fluids. PMID:23202415

The Application of SILAC Mouse in Human Body Fluid Proteomics Analysis Reveals Protein Patterns Associated with IgA Nephropathy.

PubMed

Zhao, Shilin; Li, Rongxia; Cai, Xiaofan; Chen, Wanjia; Li, Qingrun; Xing, Tao; Zhu, Wenjie; Chen, Y Eugene; Zeng, Rong; Deng, Yueyi

2013-01-01

Body fluid proteome is the most informative proteome from a medical viewpoint. But the lack of accurate quantitation method for complicated body fluid limited its application in disease research and biomarker discovery. To address this problem, we introduced a novel strategy, in which SILAC-labeled mouse serum was used as internal standard for human serum and urine proteome analysis. The SILAC-labeled mouse serum was mixed with human serum and urine, and multidimensional separation coupled with tandem mass spectrometry (IEF-LC-MS/MS) analysis was performed. The shared peptides between two species were quantified by their SILAC pairs, and the human-only peptides were quantified by mouse peptides with coelution. The comparison for the results from two replicate experiments indicated the high repeatability of our strategy. Then the urine from Immunoglobulin A nephropathy patients treated and untreated was compared by this quantitation strategy. Fifty-three peptides were found to be significantly changed between two groups, including both known diagnostic markers for IgAN and novel candidates, such as Complement C3, Albumin, VDBP, ApoA,1 and IGFBP7. In conclusion, we have developed a practical and accurate quantitation strategy for comparison of complicated human body fluid proteome. The results from such strategy could provide potential disease-related biomarkers for evaluation of treatment.

Proteomics Analysis of Skeletal Muscle from Leptin-Deficient ob/ob Mice Reveals Adaptive Remodeling of Metabolic Characteristics and Fiber Type Composition.

PubMed

Schönke, Milena; Björnholm, Marie; Chibalin, Alexander V; Zierath, Juleen R; Deshmukh, Atul S

2018-03-01

Skeletal muscle insulin resistance, an early metabolic defect in the pathogenesis of type 2 diabetes (T2D), may be a cause or consequence of altered protein expression profiles. Proteomics technology offers enormous promise to investigate molecular mechanisms underlying pathologies, however, the analysis of skeletal muscle is challenging. Using state-of-the-art multienzyme digestion and filter-aided sample preparation (MED-FASP) and a mass spectrometry (MS)-based workflow, we performed a global proteomics analysis of skeletal muscle from leptin-deficient, obese, insulin resistant (ob/ob) and lean mice in mere two fractions in a short time (8 h per sample). We identified more than 6000 proteins with 118 proteins differentially regulated in obesity. This included protein kinases, phosphatases, and secreted and fiber type associated proteins. Enzymes involved in lipid metabolism in skeletal muscle from ob/ob mice were increased, providing evidence against reduced fatty acid oxidation in lipid-induced insulin resistance. Mitochondrial and peroxisomal proteins, as well as components of pyruvate and lactate metabolism, were increased. Finally, the skeletal muscle proteome from ob/ob mice displayed a shift toward the "slow fiber type." This detailed characterization of an obese rodent model of T2D demonstrates an efficient workflow for skeletal muscle proteomics, which may easily be adapted to other complex tissues. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Combined analysis of transcriptome and proteome data as a tool for the identification of candidate biomarkers in renal cell carcinoma

PubMed Central

Seliger, Barbara; Dressler, Sven P.; Wang, Ena; Kellner, Roland; Recktenwald, Christian V.; Lottspeich, Friedrich; Marincola, Francesco M.; Baumgärtner, Maja; Atkins, Derek; Lichtenfels, Rudolf

2012-01-01

Results obtained from expression profilings of renal cell carcinoma using different “ome”-based approaches and comprehensive data analysis demonstrated that proteome-based technologies and cDNA microarray analyses complement each other during the discovery phase for disease-related candidate biomarkers. The integration of the respective data revealed the uniqueness and complementarities of the different technologies. While comparative cDNA microarray analyses though restricted to upregulated targets largely revealed genes involved in controlling gene/protein expression (19%) and signal transduction processes (13%), proteomics/PROTEOMEX-defined candidate biomarkers include enzymes of the cellular metabolism (36%), transport proteins (12%) and cell motility/structural molecules (10%). Candidate biomarkers defined by proteomics and PROTEOMEX are frequently shared, whereas the sharing rate between cDNA microarray and proteome-based profilings is limited. Putative candidate biomarkers provide insights into their cellular (dys)function and their diagnostic/prognostic value but still warrant further validation in larger patient numbers. Based on the fact that merely 3 candidate biomarkers were shared by all applied technologies, namely annexin A4, tubulin alpha-1A chain and ubiquitin carboxyl-terminal hydrolase L1 the analysis at a single hierarchical level of biological regulation seems to provide only limited results thus emphasizing the importance and benefit of performing rather combinatorial screenings which can complement the standard clinical predictors. PMID:19235166

Combination of Bottom-up 2D-LC-MS and Semi-top-down GelFree-LC-MS Enhances Coverage of Proteome and Low Molecular Weight Short Open Reading Frame Encoded Peptides of the Archaeon Methanosarcina mazei.

PubMed

Cassidy, Liam; Prasse, Daniela; Linke, Dennis; Schmitz, Ruth A; Tholey, Andreas

2016-10-07

The recent discovery of an increasing number of small open reading frames (sORF) creates the need for suitable analytical technologies for the comprehensive identification of the corresponding gene products. For biological and functional studies the knowledge of the entire set of proteins and sORF gene products is essential. Consequently in the present study we evaluated analytical approaches that will allow for simultaneous analysis of widest parts of the proteome together with the predicted sORF. We performed a full proteome analysis of the methane producing archaeon Methanosarcina mazei strain Gö1 cytosolic proteome using a high/low pH reversed phase LC-MS bottom-up approach. The second analytical approach was based on semi-top-down strategy, encompassing a separation at intact protein level using a GelFree system, followed by digestion and LC-MS analysis. A high overlap in identified proteins was found for both approaches yielding the most comprehensive coverage of the cytosolic proteome of this organism achieved so far. The application of the second approach in combination with an adjustment of the search criteria for database searches further led to a significant increase of sORF peptide identifications, finally allowing to detect and identify 28 sORF gene products.

Global Analysis Reveals the Complexity of the Human Glomerular Extracellular Matrix

PubMed Central

Byron, Adam; Humphries, Jonathan D.; Randles, Michael J.; Carisey, Alex; Murphy, Stephanie; Knight, David; Brenchley, Paul E.; Zent, Roy; Humphries, Martin J.

2014-01-01

The glomerulus contains unique cellular and extracellular matrix (ECM) components, which are required for intact barrier function. Studies of the cellular components have helped to build understanding of glomerular disease; however, the full composition and regulation of glomerular ECM remains poorly understood. We used mass spectrometry-based proteomics of enriched ECM extracts for a global analysis of human glomerular ECM in vivo and identified a tissue-specific proteome of 144 structural and regulatory ECM proteins. This catalog includes all previously identified glomerular components plus many new and abundant components. Relative protein quantification showed a dominance of collagen IV, collagen I, and laminin isoforms in the glomerular ECM together with abundant collagen VI and TINAGL1. Protein network analysis enabled the creation of a glomerular ECM interactome, which revealed a core of highly connected structural components. More than one half of the glomerular ECM proteome was validated using colocalization studies and data from the Human Protein Atlas. This study yields the greatest number of ECM proteins relative to previous investigations of whole glomerular extracts, highlighting the importance of sample enrichment. It also shows that the composition of glomerular ECM is far more complex than previously appreciated and suggests that many more ECM components may contribute to glomerular development and disease processes. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the dataset identifier PXD000456. PMID:24436468

Proteomic Analysis of Pigeonpea (Cajanus cajan) Seeds Reveals the Accumulation of Numerous Stress-Related Proteins.

PubMed

Krishnan, Hari B; Natarajan, Savithiry S; Oehrle, Nathan W; Garrett, Wesley M; Darwish, Omar

2017-06-14

Pigeonpea is one of the major sources of dietary protein for more than a billion people living in South Asia. This hardy legume is often grown in low-input and risk-prone marginal environments. Considerable research effort has been devoted by a global research consortium to develop genomic resources for the improvement of this legume crop. These efforts have resulted in the elucidation of the complete genome sequence of pigeonpea. Despite these developments, little is known about the seed proteome of this important crop. Here, we report the proteome of pigeonpea seed. To enable the isolation of maximum number of seed proteins, including those that are present in very low amounts, three different protein fractions were obtained by employing different extraction media. High-resolution two-dimensional (2-D) electrophoresis followed by MALDI-TOF-TOF-MS/MS analysis of these protein fractions resulted in the identification of 373 pigeonpea seed proteins. Consistent with the reported high degree of synteny between the pigeonpea and soybean genomes, a large number of pigeonpea seed proteins exhibited significant amino acid homology with soybean seed proteins. Our proteomic analysis identified a large number of stress-related proteins, presumably due to its adaptation to drought-prone environments. The availability of a pigeonpea seed proteome reference map should shed light on the roles of these identified proteins in various biological processes and facilitate the improvement of seed composition.

LFQProfiler and RNP(xl): Open-Source Tools for Label-Free Quantification and Protein-RNA Cross-Linking Integrated into Proteome Discoverer.

PubMed

Veit, Johannes; Sachsenberg, Timo; Chernev, Aleksandar; Aicheler, Fabian; Urlaub, Henning; Kohlbacher, Oliver

2016-09-02

Modern mass spectrometry setups used in today's proteomics studies generate vast amounts of raw data, calling for highly efficient data processing and analysis tools. Software for analyzing these data is either monolithic (easy to use, but sometimes too rigid) or workflow-driven (easy to customize, but sometimes complex). Thermo Proteome Discoverer (PD) is a powerful software for workflow-driven data analysis in proteomics which, in our eyes, achieves a good trade-off between flexibility and usability. Here, we present two open-source plugins for PD providing additional functionality: LFQProfiler for label-free quantification of peptides and proteins, and RNP(xl) for UV-induced peptide-RNA cross-linking data analysis. LFQProfiler interacts with existing PD nodes for peptide identification and validation and takes care of the entire quantitative part of the workflow. We show that it performs at least on par with other state-of-the-art software solutions for label-free quantification in a recently published benchmark ( Ramus, C.; J. Proteomics 2016 , 132 , 51 - 62 ). The second workflow, RNP(xl), represents the first software solution to date for identification of peptide-RNA cross-links including automatic localization of the cross-links at amino acid resolution and localization scoring. It comes with a customized integrated cross-link fragment spectrum viewer for convenient manual inspection and validation of the results.

Proteomic identification of processes and pathways characteristic of osmoregulatory tissues in spiny dogfish shark (Squalus acanthias).

PubMed

Lee, Jinoo; Valkova, Nelly; White, Mark P; Kültz, Dietmar

2006-09-01

We used dogfish shark (Squalus acanthias) as a model for proteome analysis of six different tissues to evaluate tissue-specific protein expression on a global scale and to deduce specific functions and the relatedness of multiple tissues from their proteomes. Proteomes of heart, brain, kidney, intestine, gill, and rectal gland were separated by two-dimensional gel electrophoresis (2DGE), gel images were matched using Delta 2D software and then evaluated for tissue-specific proteins. Sixty-one proteins (4%) were found to be in only a single type of tissue and 535 proteins (36%) were equally abundant in all six tissues. Relatedness between tissues was assessed based on tissue-specific expression patterns of all 1465 consistently resolved protein spots. This analysis revealed that tissues with osmoregulatory function (kidney, intestine, gill, rectal gland) were more similar in their overall proteomes than non-osmoregulatory tissues (heart, brain). Sixty-one proteins were identified by MALDI-TOF/TOF mass spectrometry and biological functions characteristic of osmoregulatory tissues were derived from gene ontology and molecular pathway analysis. Our data demonstrate that the molecular machinery for energy and urea metabolism and the Rho-GTPase/cytoskeleton pathway are enriched in osmoregulatory tissues of sharks. Our work provides a strong rationale for further study of the contribution of these mechanisms to the osmoregulation of marine sharks.

Quantitative proteome analysis of plasma microparticles for the characterization of HCV-induced hepatic cirrhosis and hepatocellular carcinoma.

PubMed

Taleb, Raghda Saad Zaghloul; Moez, Pacint; Younan, Doreen; Eisenacher, Martin; Tenbusch, Matthias; Sitek, Barbara; Bracht, Thilo

2017-12-01

Hepatocellular carcinoma (HCC) is the most common primary malignant liver tumor and a leading cause of cancer-related deaths worldwide. Cirrhosis induced by hepatitis-C virus (HCV) infection is the most critical risk factor for HCC. However, the mechanism of HCV-induced carcinogenesis is not fully understood. Plasma microparticles (PMP) contribute to numerous physiological and pathological processes and contain proteins whose composition correlates to the respective pathophysiological conditions. We analyzed PMP from 22 HCV-induced cirrhosis patients, 16 HCV-positive HCC patients with underlying cirrhosis and 18 healthy controls. PMP were isolated using ultracentrifugation and analyzed via label-free LC-MS/MS. We identified 840 protein groups and quantified 507 proteins. 159 proteins were found differentially abundant between the three experimental groups. PMP in both disease entities displayed remarkable differences in the proteome composition compared to healthy controls. Conversely, the proteome difference between both diseases was minimal. GO analysis revealed that PMP isolated from both diseases were significantly enriched in proteins involved in complement activation, while endopeptidase activity was downregulated exclusively in HCC patients. This study reports for the first time a quantitative proteome analysis for PMP from patients with HCV-induced cirrhosis and HCC. Data are available via ProteomeXchange with identifier PXD005777. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Simplifying the human serum proteome for discriminating patients with bipolar disorder of other psychiatry conditions.

PubMed

de Jesus, Jemmyson Romário; Galazzi, Rodrigo Moretto; de Lima, Tatiani Brenelli; Banzato, Cláudio Eduardo Muller; de Almeida Lima E Silva, Luiz Fernando; de Rosalmeida Dantas, Clarissa; Gozzo, Fábio Cézar; Arruda, Marco Aurélio Zezzi

2017-12-01

An exploratory analysis using proteomic strategies in blood serum of patients with bipolar disorder (BD), and with other psychiatric conditions such as Schizophrenia (SCZ), can provide a better understanding of this disorder, as well as their discrimination based on their proteomic profile. The proteomic profile of blood serum samples obtained from patients with BD using lithium or other drugs (N=14), healthy controls, including non-family (HCNF; N=3) and family (HCF; N=9), patients with schizophrenia (SCZ; N=23), and patients using lithium for other psychiatric conditions (OD; N=4) were compared. Four methods for simplifying the serum samples proteome were evaluated for both removing the most abundant proteins and for enriching those of lower-abundance: protein depletion with acetonitrile (ACN), dithiothreitol (DTT), sequential depletion using DTT and ACN, and protein equalization using commercial ProteoMiner® kit (PM). For proteomic evaluation, 2-D DIGE and nanoLC-MS/MS analysis were employed. PM method was the best strategy for removing proteins of high abundance. Through 2-D DIGE gel image comparison, 37 protein spots were found differentially abundant (p<0.05, Student's t-test), which exhibited ≥2.0-fold change of the average value of normalized spot intensities in the serum of SCZ, BD and OD patients compared to subject controls (HCF and HCNF). From these spots detected, 13 different proteins were identified: ApoA1, ApoE, ApoC3, ApoA4, Samp, SerpinA1, TTR, IgK, Alb, VTN, TR, C4A and C4B. Proteomic analysis allowed the discrimination of patients with BD from patients with other mental disorders, such as SCZ. The findings in this exploratory study may also contribute for better understanding the pathophysiology of these disorders and finding potential serum biomarkers for these conditions. Copyright © 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

SELDI-TOF-based serum proteomic pattern diagnostics for early detection of cancer.

PubMed

Petricoin, Emanuel F; Liotta, Lance A

2004-02-01

Proteomics is more than just generating lists of proteins that increase or decrease in expression as a cause or consequence of pathology. The goal should be to characterize the information flow through the intercellular protein circuitry that communicates with the extracellular microenvironment and then ultimately to the serum/plasma macroenvironment. The nature of this information can be a cause, or a consequence, of disease and toxicity-based processes. Serum proteomic pattern diagnostics is a new type of proteomic platform in which patterns of proteomic signatures from high dimensional mass spectrometry data are used as a diagnostic classifier. This approach has recently shown tremendous promise in the detection of early-stage cancers. The biomarkers found by SELDI-TOF-based pattern recognition analysis are mostly low molecular weight fragments produced at the specific tumor microenvironment.

Unraveling snake venom complexity with 'omics' approaches: challenges and perspectives.

PubMed

Zelanis, André; Tashima, Alexandre Keiji

2014-09-01

The study of snake venom proteomes (venomics) has been experiencing a burst of reports, however the comprehensive knowledge of the dynamic range of proteins present within a single venom, the set of post-translational modifications (PTMs) as well as the lack of a comprehensive database related to venom proteins are among the main challenges in venomics research. The phenotypic plasticity in snake venom proteomes together with their inherent toxin proteoform diversity, points out to the use of integrative analysis in order to better understand their actual complexity. In this regard, such a systems venomics task should encompass the integration of data from transcriptomic and proteomic studies (specially the venom gland proteome), the identification of biological PTMs, and the estimation of artifactual proteomes and peptidomes generated by sample handling procedures. Copyright © 2014 Elsevier Ltd. All rights reserved.