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

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.

Brucella proteomes--a review.

PubMed

DelVecchio, Vito G; Wagner, Mary Ann; Eschenbrenner, Michel; Horn, Troy A; Kraycer, Jo Ann; Estock, Frank; Elzer, Phil; Mujer, Cesar V

2002-12-20

The proteomes of selected Brucella spp. have been extensively analyzed by utilizing current proteomic technology involving 2-DE and MALDI-MS. In Brucella melitensis, more than 500 proteins were identified. The rapid and large-scale identification of proteins in this organism was accomplished by using the annotated B. melitensis genome which is now available in the GenBank. Coupled with new and powerful tools for data analysis, differentially expressed proteins were identified and categorized into several classes. A global overview of protein expression patterns emerged, thereby facilitating the simultaneous analysis of different metabolic pathways in B. melitensis. Such a global characterization would not have been possible by using time consuming and traditional biochemical approaches. The era of post-genomic technology offers new and exciting opportunities to understand the complete biology of different Brucella species.

A Systematic Analysis of a Deep Mouse Epididymal Sperm Proteome

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

Chauvin, Theodore; Xie, Fang; Liu, Tao

Spermatozoa are highly specialized cells that, when mature, are capable of navigating the female reproductive tract and fertilizing an oocyte. The sperm cell is thought to be largely quiescent in terms of transcriptional and translational activity. As a result, once it has left the male reproductive tract, the sperm cell is essentially operating with a static population of proteins. It is therefore theoretically possible to understand the protein networks contained in a sperm cell and to deduce its cellular function capabilities. To this end we have performed a proteomic analysis of mouse sperm isolated from the cauda epididymis and havemore » confidently identified 2,850 proteins, which is the most comprehensive sperm proteome for any species reported to date. These proteins comprise many complete cellular pathways, including those for energy production via glycolysis, β-oxidation and oxidative phosphorylation, protein folding and transport, and cell signaling systems. This proteome should prove a useful tool for assembly and testing of protein networks important for sperm function.« less

Comprehensive Analysis of Cancer-Proteogenome to Identify Biomarkers for the Early Diagnosis and Prognosis of Cancer.

PubMed

Shukla, Hem D

2017-10-25

During the past century, our understanding of cancer diagnosis and treatment has been based on a monogenic approach, and as a consequence our knowledge of the clinical genetic underpinnings of cancer is incomplete. Since the completion of the human genome in 2003, it has steered us into therapeutic target discovery, enabling us to mine the genome using cutting edge proteogenomics tools. A number of novel and promising cancer targets have emerged from the genome project for diagnostics, therapeutics, and prognostic markers, which are being used to monitor response to cancer treatment. The heterogeneous nature of cancer has hindered progress in understanding the underlying mechanisms that lead to abnormal cellular growth. Since, the start of The Cancer Genome Atlas (TCGA), and the International Genome consortium projects, there has been tremendous progress in genome sequencing and immense numbers of cancer genomes have been completed, and this approach has transformed our understanding of the diagnosis and treatment of different types of cancers. By employing Genomics and proteomics technologies, an immense amount of genomic data is being generated on clinical tumors, which has transformed the cancer landscape and has the potential to transform cancer diagnosis and prognosis. A complete molecular view of the cancer landscape is necessary for understanding the underlying mechanisms of cancer initiation to improve diagnosis and prognosis, which ultimately will lead to personalized treatment. Interestingly, cancer proteome analysis has also allowed us to identify biomarkers to monitor drug and radiation resistance in patients undergoing cancer treatment. Further, TCGA-funded studies have allowed for the genomic and transcriptomic characterization of targeted cancers, this analysis aiding the development of targeted therapies for highly lethal malignancy. High-throughput technologies, such as complete proteome, epigenome, protein-protein interaction, and pharmacogenomics data, are indispensable to glean into the cancer genome and proteome and these approaches have generated multidimensional universal studies of genes and proteins (OMICS) data which has the potential to facilitate precision medicine. However, due to slow progress in computational technologies, the translation of big omics data into their clinical aspects have been slow. In this review, attempts have been made to describe the role of high-throughput genomic and proteomic technologies in identifying a panel of biomarkers which could be used for the early diagnosis and prognosis of cancer.

The online Tabloid Proteome: an annotated database of protein associations

PubMed Central

Turan, Demet; Tavernier, Jan

2018-01-01

Abstract A complete knowledge of the proteome can only be attained by determining the associations between proteins, along with the nature of these associations (e.g. physical contact in protein–protein interactions, participation in complex formation or different roles in the same pathway). Despite extensive efforts in elucidating direct protein interactions, our knowledge on the complete spectrum of protein associations remains limited. We therefore developed a new approach that detects protein associations from identifications obtained after re-processing of large-scale, public mass spectrometry-based proteomics data. Our approach infers protein association based on the co-occurrence of proteins across many different proteomics experiments, and provides information that is almost completely complementary to traditional direct protein interaction studies. We here present a web interface to query and explore the associations derived from this method, called the online Tabloid Proteome. The online Tabloid Proteome also integrates biological knowledge from several existing resources to annotate our derived protein associations. The online Tabloid Proteome is freely available through a user-friendly web interface, which provides intuitive navigation and data exploration options for the user at http://iomics.ugent.be/tabloidproteome. PMID:29040688

Assembling proteomics data as a prerequisite for the analysis of large scale experiments

PubMed Central

Schmidt, Frank; Schmid, Monika; Thiede, Bernd; Pleißner, Klaus-Peter; Böhme, Martina; Jungblut, Peter R

2009-01-01

Background Despite the complete determination of the genome sequence of a huge number of bacteria, their proteomes remain relatively poorly defined. Beside new methods to increase the number of identified proteins new database applications are necessary to store and present results of large- scale proteomics experiments. Results In the present study, a database concept has been developed to address these issues and to offer complete information via a web interface. In our concept, the Oracle based data repository system SQL-LIMS plays the central role in the proteomics workflow and was applied to the proteomes of Mycobacterium tuberculosis, Helicobacter pylori, Salmonella typhimurium and protein complexes such as 20S proteasome. Technical operations of our proteomics labs were used as the standard for SQL-LIMS template creation. By means of a Java based data parser, post-processed data of different approaches, such as LC/ESI-MS, MALDI-MS and 2-D gel electrophoresis (2-DE), were stored in SQL-LIMS. A minimum set of the proteomics data were transferred in our public 2D-PAGE database using a Java based interface (Data Transfer Tool) with the requirements of the PEDRo standardization. Furthermore, the stored proteomics data were extractable out of SQL-LIMS via XML. Conclusion The Oracle based data repository system SQL-LIMS played the central role in the proteomics workflow concept. Technical operations of our proteomics labs were used as standards for SQL-LIMS templates. Using a Java based parser, post-processed data of different approaches such as LC/ESI-MS, MALDI-MS and 1-DE and 2-DE were stored in SQL-LIMS. Thus, unique data formats of different instruments were unified and stored in SQL-LIMS tables. Moreover, a unique submission identifier allowed fast access to all experimental data. This was the main advantage compared to multi software solutions, especially if personnel fluctuations are high. Moreover, large scale and high-throughput experiments must be managed in a comprehensive repository system such as SQL-LIMS, to query results in a systematic manner. On the other hand, these database systems are expensive and require at least one full time administrator and specialized lab manager. Moreover, the high technical dynamics in proteomics may cause problems to adjust new data formats. To summarize, SQL-LIMS met the requirements of proteomics data handling especially in skilled processes such as gel-electrophoresis or mass spectrometry and fulfilled the PSI standardization criteria. The data transfer into a public domain via DTT facilitated validation of proteomics data. Additionally, evaluation of mass spectra by post-processing using MS-Screener improved the reliability of mass analysis and prevented storage of data junk. PMID:19166578

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

PubMed Central

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

2014-01-01

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

A multi-protease, multi-dissociation, bottom-up-to-top-down proteomic view of the Loxosceles intermedia venom

PubMed Central

Trevisan-Silva, Dilza; Bednaski, Aline V.; Fischer, Juliana S.G.; Veiga, Silvio S.; Bandeira, Nuno; Guthals, Adrian; Marchini, Fabricio K.; Leprevost, Felipe V.; Barbosa, Valmir C.; Senff-Ribeiro, Andrea; Carvalho, Paulo C.

2017-01-01

Venoms are a rich source for the discovery of molecules with biotechnological applications, but their analysis is challenging even for state-of-the-art proteomics. Here we report on a large-scale proteomic assessment of the venom of Loxosceles intermedia, the so-called brown spider. Venom was extracted from 200 spiders and fractioned into two aliquots relative to a 10 kDa cutoff mass. Each of these was further fractioned and digested with trypsin (4 h), trypsin (18 h), pepsin (18 h), and chymotrypsin (18 h), then analyzed by MudPIT on an LTQ-Orbitrap XL ETD mass spectrometer fragmenting precursors by CID, HCD, and ETD. Aliquots of undigested samples were also analyzed. Our experimental design allowed us to apply spectral networks, thus enabling us to obtain meta-contig assemblies, and consequently de novo sequencing of practically complete proteins, culminating in a deep proteome assessment of the venom. Data are available via ProteomeXchange, with identifier PXD005523. PMID:28696408

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.

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

PubMed

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

2014-10-01

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

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

PubMed Central

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

2014-01-01

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

Combining Capillary Electrophoresis with Mass Spectrometry for Applications in Proteomics

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

Simpson, David C.; Smith, Richard D.

2005-04-01

Throughout the field of global proteomics, ranging from simple organism studies to human medical applications, the high sample complexity creates demands for improved separations and analysis techniques. Furthermore, with increased organism complexity, the correlation between proteome and genome becomes less certain due to extensive mRNA processing prior to translation. In this way, the same DNA sequence can potentially code for regions in a number of distinct proteins; quantitative differences in expression (or abundance) between these often-related species are of significant interest. Well-established proteomics techniques, which use genomic information to identify peptides that originate from protease digestion, often cannot easily distinguishmore » between such gene products; intact protein-level analyses are required to complete the picture, particularly for identifying post-translational modifications. While chromatographic techniques are currently better suited to peptide analysis, capillary electrophoresis (CE) in combination with mass spectrometry (MS) may become important for intact protein analysis. This review focuses on CE/MS instrumentation and techniques showing promise for such applications, highlighting those with greatest potential. Reference will also be made to developments relevant to peptide-level analyses for use in time- or sample-limited situations.« less

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.

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.

DOGMA: domain-based transcriptome and proteome quality assessment.

PubMed

Dohmen, Elias; Kremer, Lukas P M; Bornberg-Bauer, Erich; Kemena, Carsten

2016-09-01

Genome studies have become cheaper and easier than ever before, due to the decreased costs of high-throughput sequencing and the free availability of analysis software. However, the quality of genome or transcriptome assemblies can vary a lot. Therefore, quality assessment of assemblies and annotations are crucial aspects of genome analysis pipelines. We developed DOGMA, a program for fast and easy quality assessment of transcriptome and proteome data based on conserved protein domains. DOGMA measures the completeness of a given transcriptome or proteome and provides information about domain content for further analysis. DOGMA provides a very fast way to do quality assessment within seconds. DOGMA is implemented in Python and published under GNU GPL v.3 license. The source code is available on https://ebbgit.uni-muenster.de/domainWorld/DOGMA/ CONTACTS: e.dohmen@wwu.de or c.kemena@wwu.de Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A comprehensive proteomics study on platelet concentrates: Platelet proteome, storage time and Mirasol pathogen reduction technology.

PubMed

Salunkhe, Vishal; De Cuyper, Iris M; Papadopoulos, Petros; van der Meer, Pieter F; Daal, Brunette B; Villa-Fajardo, María; de Korte, Dirk; van den Berg, Timo K; Gutiérrez, Laura

2018-03-19

Platelet concentrates (PCs) represent a blood transfusion product with a major concern for safety as their storage temperature (20-24°C) allows bacterial growth, and their maximum storage time period (less than a week) precludes complete microbiological testing. Pathogen inactivation technologies (PITs) provide an additional layer of safety to the blood transfusion products from known and unknown pathogens such as bacteria, viruses, and parasites. In this context, PITs, such as Mirasol Pathogen Reduction Technology (PRT), have been developed and are implemented in many countries. However, several studies have shown in vitro that Mirasol PRT induces a certain level of platelet shape change, hyperactivation, basal degranulation, and increased oxidative damage during storage. It has been suggested that Mirasol PRT might accelerate what has been described as the platelet storage lesion (PSL), but supportive molecular signatures have not been obtained. We aimed at dissecting the influence of both variables, that is, Mirasol PRT and storage time, at the proteome level. We present comprehensive proteomics data analysis of Control PCs and PCs treated with Mirasol PRT at storage days 1, 2, 6, and 8. Our workflow was set to perform proteomics analysis using a gel-free and label-free quantification (LFQ) approach. Semi-quantification was based on LFQ signal intensities of identified proteins using MaxQuant/Perseus software platform. Data are available via ProteomeXchange with identifier PXD008119. We identified marginal differences between Mirasol PRT and Control PCs during storage. However, those significant changes at the proteome level were specifically related to the functional aspects previously described to affect platelets upon Mirasol PRT. In addition, the effect of Mirasol PRT on the platelet proteome appeared not to be exclusively due to an accelerated or enhanced PSL. In summary, semi-quantitative proteomics allows to discern between proteome changes due to Mirasol PRT or PSL, and proves to be a methodology suitable to phenotype platelets in an unbiased manner, in various physiological contexts.

HiQuant: Rapid Postquantification Analysis of Large-Scale MS-Generated Proteomics Data.

PubMed

Bryan, Kenneth; Jarboui, Mohamed-Ali; Raso, Cinzia; Bernal-Llinares, Manuel; McCann, Brendan; Rauch, Jens; Boldt, Karsten; Lynn, David J

2016-06-03

Recent advances in mass-spectrometry-based proteomics are now facilitating ambitious large-scale investigations of the spatial and temporal dynamics of the proteome; however, the increasing size and complexity of these data sets is overwhelming current downstream computational methods, specifically those that support the postquantification analysis pipeline. Here we present HiQuant, a novel application that enables the design and execution of a postquantification workflow, including common data-processing steps, such as assay normalization and grouping, and experimental replicate quality control and statistical analysis. HiQuant also enables the interpretation of results generated from large-scale data sets by supporting interactive heatmap analysis and also the direct export to Cytoscape and Gephi, two leading network analysis platforms. HiQuant may be run via a user-friendly graphical interface and also supports complete one-touch automation via a command-line mode. We evaluate HiQuant's performance by analyzing a large-scale, complex interactome mapping data set and demonstrate a 200-fold improvement in the execution time over current methods. We also demonstrate HiQuant's general utility by analyzing proteome-wide quantification data generated from both a large-scale public tyrosine kinase siRNA knock-down study and an in-house investigation into the temporal dynamics of the KSR1 and KSR2 interactomes. Download HiQuant, sample data sets, and supporting documentation at http://hiquant.primesdb.eu .

Proteomic Analysis of Lyme Disease: Global Protein Comparison of Three Strains of Borrelia burgdorferi

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

Jacobs, Jon M.; Yang, Xiaohua; Luft, Benjamin J.

2005-04-01

The Borrelia burgdorferi spirochete is the causative agent of Lyme disease, the most common tick-borne disease in the United States. It has been studied extensively to help understand its pathogenicity of infection and how it can persist in different mammalian hosts. We report the proteomic analysis of the archetype B. burgdorferi B31 strain and two other strains (ND40, and JD-1) having different Borrelia pathotypes using strong cation exchange fractionation of proteolytic peptides followed by high-resolution, reversed phase capillary liquid chromatography coupled with ion trap tandem mass spectrometric (LC-MS/MS) analysis. Protein identification was facilitated by the availability of the complete B31more » genome sequence. A total of 665 Borrelia proteins were identified representing ~38 % coverage of the theoretical B31 proteome. A significant overlap was observed between the identified proteins in direct comparisons between any two strains (>72%), but distinct differences were observed among identified hypothetical and outer membrane proteins of the three strains. Such a concurrent proteomic overview of three Borrelia strains based upon only the B31 genome sequence is shown to provide significant insights into the presence or absence of specific proteins and a broad overall comparison among strains.« less

Revisiting venom of the sea anemone Stichodactyla haddoni: Omics techniques reveal the complete toxin arsenal of a well-studied sea anemone genus.

PubMed

Madio, Bruno; Undheim, Eivind A B; King, Glenn F

2017-08-23

More than a century of research on sea anemone venoms has shown that they contain a diversity of biologically active proteins and peptides. However, recent omics studies have revealed that much of the venom proteome remains unexplored. We used, for the first time, a combination of proteomic and transcriptomic techniques to obtain a holistic overview of the venom arsenal of the well-studied sea anemone Stichodactyla haddoni. A purely search-based approach to identify putative toxins in a transcriptome from tentacles regenerating after venom extraction identified 508 unique toxin-like transcripts grouped into 63 families. However, proteomic analysis of venom revealed that 52 of these toxin families are likely false positives. In contrast, the combination of transcriptomic and proteomic data enabled positive identification of 23 families of putative toxins, 12 of which have no homology known proteins or peptides. Our data highlight the importance of using proteomics of milked venom to correctly identify venom proteins/peptides, both known and novel, while minimizing false positive identifications from non-toxin homologues identified in transcriptomes of venom-producing tissues. This work lays the foundation for uncovering the role of individual toxins in sea anemone venom and how they contribute to the envenomation of prey, predators, and competitors. Proteomic analysis of milked venom combined with analysis of a tentacle transcriptome revealed the full extent of the venom arsenal of the sea anemone Stichodactyla haddoni. This combined approach led to the discovery of 12 entirely new families of disulfide-rich peptides and proteins in a genus of anemones that have been studied for over a century. Copyright © 2017 Elsevier B.V. All rights reserved.

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

PubMed

Uddin, Reaz; Jamil, Faiza

2018-06-01

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

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.

Recognizing millions of consistently unidentified spectra across hundreds of shotgun proteomics datasets

PubMed Central

Griss, Johannes; Perez-Riverol, Yasset; Lewis, Steve; Tabb, David L.; Dianes, José A.; del-Toro, Noemi; Rurik, Marc; Walzer, Mathias W.; Kohlbacher, Oliver; Hermjakob, Henning; Wang, Rui; Vizcaíno, Juan Antonio

2016-01-01

Mass spectrometry (MS) is the main technology used in proteomics approaches. However, on average 75% of spectra analysed in an MS experiment remain unidentified. We propose to use spectrum clustering at a large-scale to shed a light on these unidentified spectra. PRoteomics IDEntifications database (PRIDE) Archive is one of the largest MS proteomics public data repositories worldwide. By clustering all tandem MS spectra publicly available in PRIDE Archive, coming from hundreds of datasets, we were able to consistently characterize three distinct groups of spectra: 1) incorrectly identified spectra, 2) spectra correctly identified but below the set scoring threshold, and 3) truly unidentified spectra. Using a multitude of complementary analysis approaches, we were able to identify less than 20% of the consistently unidentified spectra. The complete spectrum clustering results are available through the new version of the PRIDE Cluster resource (http://www.ebi.ac.uk/pride/cluster). This resource is intended, among other aims, to encourage and simplify further investigation into these unidentified spectra. PMID:27493588

Recognizing millions of consistently unidentified spectra across hundreds of shotgun proteomics datasets.

PubMed

Griss, Johannes; Perez-Riverol, Yasset; Lewis, Steve; Tabb, David L; Dianes, José A; Del-Toro, Noemi; Rurik, Marc; Walzer, Mathias W; Kohlbacher, Oliver; Hermjakob, Henning; Wang, Rui; Vizcaíno, Juan Antonio

2016-08-01

Mass spectrometry (MS) is the main technology used in proteomics approaches. However, on average 75% of spectra analysed in an MS experiment remain unidentified. We propose to use spectrum clustering at a large-scale to shed a light on these unidentified spectra. PRoteomics IDEntifications database (PRIDE) Archive is one of the largest MS proteomics public data repositories worldwide. By clustering all tandem MS spectra publicly available in PRIDE Archive, coming from hundreds of datasets, we were able to consistently characterize three distinct groups of spectra: 1) incorrectly identified spectra, 2) spectra correctly identified but below the set scoring threshold, and 3) truly unidentified spectra. Using a multitude of complementary analysis approaches, we were able to identify less than 20% of the consistently unidentified spectra. The complete spectrum clustering results are available through the new version of the PRIDE Cluster resource (http://www.ebi.ac.uk/pride/cluster). This resource is intended, among other aims, to encourage and simplify further investigation into these unidentified spectra.

The complete genome sequence and proteomics of Yersinia pestis phage Yep-phi.

PubMed

Zhao, Xiangna; Wu, Weili; Qi, Zhizhen; Cui, Yujun; Yan, Yanfeng; Guo, Zhaobiao; Wang, Zuyun; Wang, Hu; Deng, Haijun; Xue, Yan; Chen, Weijun; Wang, Xiaoyi; Yang, Ruifu

2011-01-01

Yep-phi, a lytic phage of Yersinia pestis, was isolated in China and is routinely used as a diagnostic phage for the identification of the plague pathogen. Yep-phi has an isometric hexagonal head containing dsDNA and a short non-contractile conical tail. In this study, we sequenced the Yep-phi genome (GenBank accession no. HQ333270) and performed proteomics analysis. The genome consists of 38 ,616 bp of DNA, including direct terminal repeats of 222 bp, and is predicted to contain 45 ORFs. Most structural proteins were identified by proteomics analysis. Compared with the three available genome sequences of lytic phages for Y. pestis, the phages could be divided into two subgroups. Yep-phi displays marked homology to the bacteriophages Berlin (GenBank accession no. AM183667) and Yepe2 (GenBank accession no. EU734170), and these comprise one subgroup. The other subgroup is represented by bacteriophage ΦA1122 (GenBank accession no. AY247822). Potential recombination was detected among the Yep-phi subgroup.

Proteomic Analysis Reveals Inflammation Modulation of κ/ι-Carrageenan Hexaoses in Lipopolysaccharide-Induced RAW264.7 Macrophages.

PubMed

Guo, Juanjuan; Chen, Jinghao; Lu, Xu; Guo, Zebin; Huang, Zhiwei; Zeng, Shaoxiao; Zhang, Yi; Zheng, Baodong

2018-05-09

κ/ι-Carrageenan hexaoses (κ/ι-neocarrahexaoses, KCO-4) are a type of carrageenan oligosaccharide that have a broad spectrum of bioactivities due to the presence of sulfate groups. However, the anti-inflammatory capacity of purified carrageenan oligosaccharides and the underlying mechanism has not been completely elucidated. The present study aimed to investigate inflammatory signaling modulation of KCO-4 in LPS-induced macrophages using a quantitative proteomic strategy. KCO-4 inhibited the oversecretion of inflammatory mediators (i.e., NO, TNF-α, IL-1β, IL-8, iNOS, and COX-2). KCO-4 treatment altered proteome profile, and metabolic processes in mitochondria were significantly disrupted. The IPA network analysis proposed that KCO-4 triggered the NF-κB signaling pathway-dependent anti-inflammation process through the inhibition of CD14/Rel@p50 in LPS-induced RAW264.7 macrophages. These data improve our understanding of the anti-inflammatory mechanism and contribute to exposure biomarker screening of κ-carrageenan oligosaccharides.

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

PubMed

Uddin, Reaz; Sufian, Muhammad

2016-01-01

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

QC-ART: A tool for real-time quality control assessment of mass spectrometry-based proteomics data.

PubMed

Stanfill, Bryan A; Nakayasu, Ernesto S; Bramer, Lisa M; Thompson, Allison M; Ansong, Charles K; Clauss, Therese; Gritsenko, Marina A; Monroe, Matthew E; Moore, Ronald J; Orton, Daniel J; Piehowski, Paul D; Schepmoes, Athena A; Smith, Richard D; Webb-Robertson, Bobbie-Jo; Metz, Thomas O

2018-04-17

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics studies of large sample cohorts can easily require from months to years to complete. Acquiring consistent, high-quality data in such large-scale studies is challenging because of normal variations in instrumentation performance over time, as well as artifacts introduced by the samples themselves, such as those due to collection, storage and processing. Existing quality control methods for proteomics data primarily focus on post-hoc analysis to remove low-quality data that would degrade downstream statistics; they are not designed to evaluate the data in near real-time, which would allow for interventions as soon as deviations in data quality are detected.  In addition to flagging analyses that demonstrate outlier behavior, evaluating how the data structure changes over time can aide in understanding typical instrument performance or identify issues such as a degradation in data quality due to the need for instrument cleaning and/or re-calibration.  To address this gap for proteomics, we developed Quality Control Analysis in Real-Time (QC-ART), a tool for evaluating data as they are acquired in order to dynamically flag potential issues with instrument performance or sample quality.  QC-ART has similar accuracy as standard post-hoc analysis methods with the additional benefit of real-time analysis.  We demonstrate the utility and performance of QC-ART in identifying deviations in data quality due to both instrument and sample issues in near real-time for LC-MS-based plasma proteomics analyses of a sample subset of The Environmental Determinants of Diabetes in the Young cohort. We also present a case where QC-ART facilitated the identification of oxidative modifications, which are often underappreciated in proteomic experiments. Published under license by The American Society for Biochemistry and Molecular Biology, Inc.

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

PubMed Central

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

2016-01-01

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

Proteogenomics | Office of Cancer Clinical Proteomics Research

Cancer.gov

Proteogenomics, or the integration of proteomics with genomics and transcriptomics, is an emerging approach that promises to advance basic, translational and clinical research.  By combining genomic and proteomic information, leading scientists are gaining new insights due to a more complete and unified understanding of complex biological processes.

NCI-CPTAC DREAM Proteogenomics Challenge (Registration Now Open) | Office of Cancer Clinical Proteomics Research

Cancer.gov

Proteogenomics, integration of proteomics, genomics, and transcriptomics, is an emerging approach that promises to advance basic, translational and clinical research.  By combining genomic and proteomic information, leading scientists are gaining new insights due to a more complete and unified understanding of complex biological processes.

Development of a Web-Enabled Informatics Platform for Manipulation of Gene Expression Data

DTIC Science & Technology

2004-12-01

genomic platforms such as metabolomics and proteomics , and to federated databases for knowledge management. A successful SBIR Phase I completed...measurements that require sophisticated bioinformatic platforms for data archival, management, integration, and analysis if researchers are to derive...web-enabled bioinformatic platform consisting of a Laboratory Information Management System (LIMS), an Analysis Information Management System (AIMS

Listeriomics: an Interactive Web Platform for Systems Biology of Listeria

PubMed Central

Koutero, Mikael; Tchitchek, Nicolas; Cerutti, Franck; Lechat, Pierre; Maillet, Nicolas; Hoede, Claire; Chiapello, Hélène; Gaspin, Christine

2017-01-01

ABSTRACT As for many model organisms, the amount of Listeria omics data produced has recently increased exponentially. There are now >80 published complete Listeria genomes, around 350 different transcriptomic data sets, and 25 proteomic data sets available. The analysis of these data sets through a systems biology approach and the generation of tools for biologists to browse these various data are a challenge for bioinformaticians. We have developed a web-based platform, named Listeriomics, that integrates different tools for omics data analyses, i.e., (i) an interactive genome viewer to display gene expression arrays, tiling arrays, and sequencing data sets along with proteomics and genomics data sets; (ii) an expression and protein atlas that connects every gene, small RNA, antisense RNA, or protein with the most relevant omics data; (iii) a specific tool for exploring protein conservation through the Listeria phylogenomic tree; and (iv) a coexpression network tool for the discovery of potential new regulations. Our platform integrates all the complete Listeria species genomes, transcriptomes, and proteomes published to date. This website allows navigation among all these data sets with enriched metadata in a user-friendly format and can be used as a central database for systems biology analysis. IMPORTANCE In the last decades, Listeria has become a key model organism for the study of host-pathogen interactions, noncoding RNA regulation, and bacterial adaptation to stress. To study these mechanisms, several genomics, transcriptomics, and proteomics data sets have been produced. We have developed Listeriomics, an interactive web platform to browse and correlate these heterogeneous sources of information. Our website will allow listeriologists and microbiologists to decipher key regulation mechanism by using a systems biology approach. PMID:28317029

Genome-wide screening and identification of antigens for rickettsial vaccine development

USDA-ARS?s Scientific Manuscript database

The capacity to identify immunogens for vaccine development by genome-wide screening has been markedly enhanced by the availability of complete microbial genome sequences coupled to rapid proteomic and bioinformatic analysis. Critical to this genome-wide screening is in vivo testing in the context o...

Proteomics research in India: an update.

PubMed

Reddy, Panga Jaipal; Atak, Apurva; Ghantasala, Saicharan; Kumar, Saurabh; Gupta, Shabarni; Prasad, T S Keshava; Zingde, Surekha M; Srivastava, Sanjeeva

2015-09-08

After a successful completion of the Human Genome Project, deciphering the mystery surrounding the human proteome posed a major challenge. Despite not being largely involved in the Human Genome Project, the Indian scientific community contributed towards proteomic research along with the global community. Currently, more than 76 research/academic institutes and nearly 145 research labs are involved in core proteomic research across India. The Indian researchers have been major contributors in drafting the "human proteome map" along with international efforts. In addition to this, virtual proteomics labs, proteomics courses and remote triggered proteomics labs have helped to overcome the limitations of proteomics education posed due to expensive lab infrastructure. The establishment of Proteomics Society, India (PSI) has created a platform for the Indian proteomic researchers to share ideas, research collaborations and conduct annual conferences and workshops. Indian proteomic research is really moving forward with the global proteomics community in a quest to solve the mysteries of proteomics. A draft map of the human proteome enhances the enthusiasm among intellectuals to promote proteomic research in India to the world.This article is part of a Special Issue entitled: Proteomics in India. Copyright © 2015 Elsevier B.V. All rights reserved.

Protannotator: a semiautomated pipeline for chromosome-wise functional annotation of the "missing" human proteome.

PubMed

Islam, Mohammad T; Garg, Gagan; Hancock, William S; Risk, Brian A; Baker, Mark S; Ranganathan, Shoba

2014-01-03

The chromosome-centric human proteome project (C-HPP) aims to define the complete set of proteins encoded in each human chromosome. The neXtProt database (September 2013) lists 20,128 proteins for the human proteome, of which 3831 human proteins (∼19%) are considered "missing" according to the standard metrics table (released September 27, 2013). In support of the C-HPP initiative, we have extended the annotation strategy developed for human chromosome 7 "missing" proteins into a semiautomated pipeline to functionally annotate the "missing" human proteome. This pipeline integrates a suite of bioinformatics analysis and annotation software tools to identify homologues and map putative functional signatures, gene ontology, and biochemical pathways. From sequential BLAST searches, we have primarily identified homologues from reviewed nonhuman mammalian proteins with protein evidence for 1271 (33.2%) "missing" proteins, followed by 703 (18.4%) homologues from reviewed nonhuman mammalian proteins and subsequently 564 (14.7%) homologues from reviewed human proteins. Functional annotations for 1945 (50.8%) "missing" proteins were also determined. To accelerate the identification of "missing" proteins from proteomics studies, we generated proteotypic peptides in silico. Matching these proteotypic peptides to ENCODE proteogenomic data resulted in proteomic evidence for 107 (2.8%) of the 3831 "missing proteins, while evidence from a recent membrane proteomic study supported the existence for another 15 "missing" proteins. The chromosome-wise functional annotation of all "missing" proteins is freely available to the scientific community through our web server (http://biolinfo.org/protannotator).

Proteomic analysis of Medulloblastoma reveals functional biology with translational potential.

PubMed

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

2018-06-07

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

The state of proteome profiling in the fungal genus Aspergillus.

PubMed

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

2008-03-01

Aspergilli are an important genus of filamentous fungi that contribute to a multibillion dollar industry. Since many fungal genome sequencing were recently completed, it would be advantageous to profile their proteome to better understand the fungal cell factory. Here, we review proteomic data generated for the Aspergilli in recent years. Thus far, a combined total of 28 cell surface, 102 secreted and 139 intracellular proteins have been identified based on 10 different studies on Aspergillus proteomics. A summary proteome map highlighting identified proteins in major metabolic pathway is presented.

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

PubMed Central

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

2016-01-01

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

Potential for proteomic approaches in determining efficacy biomarkers following administration of fish oils rich in omega-3 fatty acids: application in pancreatic cancers.

PubMed

Runau, Franscois; Arshad, Ali; Isherwood, John; Norris, Leonie; Howells, Lynne; Metcalfe, Matthew; Dennison, Ashley

2015-06-01

Pancreatic cancer is a disease with a significantly poor prognosis. Despite modern advances in other medical, surgical, and oncologic therapy, the outcome from pancreatic cancer has improved little over the last 40 years. To improve the management of this difficult disease, trials investigating the use of dietary and parenteral fish oils rich in omega-3 (ω-3) fatty acids, exhibiting proven anti-inflammatory and anticarcinogenic properties, have revealed favorable results in pancreatic cancers. Proteomics is the large-scale study of proteins that attempts to characterize the complete set of proteins encoded by the genome of an organism and that, with the use of sensitive mass spectrometric-based techniques, has allowed high-throughput analysis of the proteome to aid identification of putative biomarkers pertinent to given disease states. These biomarkers provide useful insight into potentially discovering new markers for early detection or elucidating the efficacy of treatment on pancreatic cancers. Here, our review identifies potential proteomic-based biomarkers in pancreatic cancer relating to apoptosis, cell proliferation, angiogenesis, and metabolic regulation in clinical studies. We also reviewed proteomic biomarkers from the administration of ω-3 fatty acids that act on similar anticarcinogenic pathways as above and reflect that proteomic studies on the effect of ω-3 fatty acids in pancreatic cancer will yield favorable results. © 2015 American Society for Parenteral and Enteral Nutrition.

Venomic Analysis of the Poorly Studied Desert Coral Snake, Micrurus tschudii tschudii, Supports the 3FTx/PLA2 Dichotomy across Micrurus Venoms

PubMed Central

Sanz, Libia; Pla, Davinia; Pérez, Alicia; Rodríguez, Yania; Zavaleta, Alfonso; Salas, Maria; Lomonte, Bruno; Calvete, Juan J.

2016-01-01

The venom proteome of the poorly studied desert coral snake Micrurus tschudii tschudii was unveiled using a venomic approach, which identified ≥38 proteins belonging to only four snake venom protein families. The three-finger toxins (3FTxs) constitute, both in number of isoforms (~30) and total abundance (93.6% of the venom proteome), the major protein family of the desert coral snake venom. Phospholipases A2 (PLA2s; seven isoforms, 4.1% of the venom proteome), 1–3 Kunitz-type proteins (1.6%), and 1–2 l-amino acid oxidases (LAO, 0.7%) complete the toxin arsenal of M. t. tschudii. Our results add to the growing evidence that the occurrence of two divergent venom phenotypes, i.e., 3FTx- and PLA2-predominant venom proteomes, may constitute a general trend across the cladogenesis of Micrurus. The occurrence of a similar pattern of venom phenotypic variability among true sea snake (Hydrophiinae) venoms suggests that the 3FTx/PLA2 dichotomy may be widely distributed among Elapidae venoms. PMID:27338473

Venomic Analysis of the Poorly Studied Desert Coral Snake, Micrurus tschudii tschudii, Supports the 3FTx/PLA₂ Dichotomy across Micrurus Venoms.

PubMed

Sanz, Libia; Pla, Davinia; Pérez, Alicia; Rodríguez, Yania; Zavaleta, Alfonso; Salas, Maria; Lomonte, Bruno; Calvete, Juan J

2016-06-07

The venom proteome of the poorly studied desert coral snake Micrurus tschudii tschudii was unveiled using a venomic approach, which identified ≥38 proteins belonging to only four snake venom protein families. The three-finger toxins (3FTxs) constitute, both in number of isoforms (~30) and total abundance (93.6% of the venom proteome), the major protein family of the desert coral snake venom. Phospholipases A₂ (PLA₂s; seven isoforms, 4.1% of the venom proteome), 1-3 Kunitz-type proteins (1.6%), and 1-2 l-amino acid oxidases (LAO, 0.7%) complete the toxin arsenal of M. t. tschudii. Our results add to the growing evidence that the occurrence of two divergent venom phenotypes, i.e., 3FTx- and PLA₂-predominant venom proteomes, may constitute a general trend across the cladogenesis of Micrurus. The occurrence of a similar pattern of venom phenotypic variability among true sea snake (Hydrophiinae) venoms suggests that the 3FTx/PLA₂ dichotomy may be widely distributed among Elapidae venoms.

The Perseus computational platform for comprehensive analysis of (prote)omics data.

PubMed

Tyanova, Stefka; Temu, Tikira; Sinitcyn, Pavel; Carlson, Arthur; Hein, Marco Y; Geiger, Tamar; Mann, Matthias; Cox, Jürgen

2016-09-01

A main bottleneck in proteomics is the downstream biological analysis of highly multivariate quantitative protein abundance data generated using mass-spectrometry-based analysis. We developed the Perseus software platform (http://www.perseus-framework.org) to support biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data. Perseus contains a comprehensive portfolio of statistical tools for high-dimensional omics data analysis covering normalization, pattern recognition, time-series analysis, cross-omics comparisons and multiple-hypothesis testing. A machine learning module supports the classification and validation of patient groups for diagnosis and prognosis, and it also detects predictive protein signatures. Central to Perseus is a user-friendly, interactive workflow environment that provides complete documentation of computational methods used in a publication. All activities in Perseus are realized as plugins, and users can extend the software by programming their own, which can be shared through a plugin store. We anticipate that Perseus's arsenal of algorithms and its intuitive usability will empower interdisciplinary analysis of complex large data sets.

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

PubMed

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

2018-03-01

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

BioInfra.Prot: A comprehensive proteomics workflow including data standardization, protein inference, expression analysis and data publication.

PubMed

Turewicz, Michael; Kohl, Michael; Ahrens, Maike; Mayer, Gerhard; Uszkoreit, Julian; Naboulsi, Wael; Bracht, Thilo; Megger, Dominik A; Sitek, Barbara; Marcus, Katrin; Eisenacher, Martin

2017-11-10

The analysis of high-throughput mass spectrometry-based proteomics data must address the specific challenges of this technology. To this end, the comprehensive proteomics workflow offered by the de.NBI service center BioInfra.Prot provides indispensable components for the computational and statistical analysis of this kind of data. These components include tools and methods for spectrum identification and protein inference, protein quantification, expression analysis as well as data standardization and data publication. All particular methods of the workflow which address these tasks are state-of-the-art or cutting edge. As has been shown in previous publications, each of these methods is adequate to solve its specific task and gives competitive results. However, the methods included in the workflow are continuously reviewed, updated and improved to adapt to new scientific developments. All of these particular components and methods are available as stand-alone BioInfra.Prot services or as a complete workflow. Since BioInfra.Prot provides manifold fast communication channels to get access to all components of the workflow (e.g., via the BioInfra.Prot ticket system: bioinfraprot@rub.de) users can easily benefit from this service and get support by experts. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Evolutionary conservation of the polyproline II conformation surrounding intrinsically disordered phosphorylation sites.

PubMed

Elam, W Austin; Schrank, Travis P; Campagnolo, Andrew J; Hilser, Vincent J

2013-04-01

Intrinsically disordered (ID) proteins function in the absence of a unique stable structure and appear to challenge the classic structure-function paradigm. The extent to which ID proteins take advantage of subtle conformational biases to perform functions, and whether signals for such mechanism can be identified in proteome-wide studies is not well understood. Of particular interest is the polyproline II (PII) conformation, suggested to be highly populated in unfolded proteins. We experimentally determine a complete calorimetric propensity scale for the PII conformation. Projection of the scale into representative eukaryotic proteomes reveals significant PII bias in regions coding for ID proteins. Importantly, enrichment of PII in ID proteins, or protein segments, is also captured by other PII scales, indicating that this enrichment is robustly encoded and universally detectable regardless of the method of PII propensity determination. Gene ontology (GO) terms obtained using our PII scale and other scales demonstrate a consensus for molecular functions performed by high PII proteins across the proteome. Perhaps the most striking result of the GO analysis is conserved enrichment (P < 10(-8) ) of phosphorylation sites in high PII regions found by all PII scales. Subsequent conformational analysis reveals a phosphorylation-dependent modulation of PII, suggestive of a conserved "tunability" within these regions. In summary, the application of an experimentally determined polyproline II (PII) propensity scale to proteome-wide sequence analysis and gene ontology reveals an enrichment of PII bias near disordered phosphorylation sites that is conserved throughout eukaryotes. Copyright © 2013 The Protein Society.

Development of Advanced Technologies for Complete Genomic and Proteomic Characterization of Quantized Human Tumor Cells

DTIC Science & Technology

2013-07-01

AVAILABILITY STATEMENT Approved for Public Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT With the establishment of GBM cell lines...and quantized cell populations form these GBM patients tumor samples we are able to complete some of our aims of our project. We will continue to...collect tumor samples with consent from families of GBM patients in preparation to perform the molecular analysis of these. Our efforts in the development

Protein profile of mouse ovarian follicles grown in vitro.

PubMed

Anastácio, Amandine; Rodriguez-Wallberg, Kenny A; Chardonnet, Solenne; Pionneau, Cédric; Fédérici, Christian; Almeida Santos, Teresa; Poirot, Catherine

2017-12-01

Could the follicle proteome be mapped by identifying specific proteins that are common or differ between three developmental stages from the secondary follicle (SF) to the antrum-like stage? From a total of 1401 proteins identified in the follicles, 609 were common to the three developmental stages investigated and 444 were found uniquely at one of the stages. The importance of the follicle as a functional structure has been recognized; however, up-to-date the proteome of the whole follicle has not been described. A few studies using proteomics have previously reported on either isolated fully-grown oocytes before or after meiosis resumption or cumulus cells. The experimental design included a validated mice model for isolation and individual culture of SFs. The system was chosen as it allows continuous evaluation of follicle growth and selection of follicles for analysis at pre-determined developmental stages: SF, complete Slavjanski membrane rupture (SMR) and antrum-like cavity (AF). The experiments were repeated 13 times independently to acquire the material that was analyzed by proteomics. SFs (n = 2166) were isolated from B6CBA/F1 female mice (n = 42), 12 days old, from 15 l. About half of the follicles isolated as SF were analyzed as such (n = 1143) and pooled to obtain 139 μg of extracted protein. Both SMR (n = 359) and AF (n = 124) were obtained after individual culture of 1023 follicles in a microdrop system under oil, selected for analysis and pooled, to obtain 339 μg and 170 μg of protein, respectively. The follicle proteome was analyzed combining isoelectric focusing (IEF) fractionation with 1D and 2D LC-MS/MS analysis to enhance protein identification. The three protein lists were submitted to the 'Compare gene list' tool in the PANTHER website to gain insights on the Gene Ontology Biological processes present and to Ingenuity Pathway Analysis to highlight protein networks. A label-free quantification was performed with 1D LC-MS/MS analyses to emphasize proteins with different expression profiles between the three follicular stages. Supplementary western blot analysis (using new biological replicates) was performed to confirm the expression variations of three proteins during follicle development in vitro. It was found that 609 out of 1401 identified proteins were common to the three follicle developmental stages investigated. Some proteins were identified uniquely at one stage: 71 of the 775 identified proteins in SF, 181 of 1092 in SMR and 192 of 1100 in AF. Additional qualitative and quantitative analysis highlighted 44 biological processes over-represented in our samples compared to the Mus musculus gene database. In particular, it was possible to identify proteins implicated in the cell cycle, calcium ion binding and glycolysis, with specific expressions and abundance, throughout in vitro follicle development. Data are available via ProteomeXchange with identifier PXD006227. The proteome analyses described in this study were performed after in vitro development. Despite fractionation of the samples before LC-MS/MS, proteomic approaches are not exhaustive, thus proteins that are not identified in a group are not necessarily absent from that group, although they are likely to be less abundant. This study allowed a general view of proteins implicated in follicle development in vitro and it represents the most complete catalog of the whole follicle proteome available so far. Not only were well known proteins of the oocyte identified but also proteins that are probably expressed only in granulosa cells. This study was supported by the Portuguese Foundation for Science and Technology, FCT (PhD fellowship SFRH/BD/65299/2009 to A.A.), the Swedish Childhood Cancer Foundation (PR 2014-0144 to K.A.R-.W.) and Stockholm County Council to K.A.R-.W. The authors of the study have no conflict of interest to report. © The Author 2017. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology.

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

PubMed

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

2015-09-04

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

Proteome-wide identification of predominant subcellular protein localizations in a bacterial model organism

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

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

2014-03-01

Proteomics data provide unique insights into biological systems, including the predominant subcellular localization (SCL) of proteins, which can reveal important clues about their functions. Here we analyzed data of a complete prokaryotic proteome expressed under two conditions mimicking interaction of the emerging pathogen Bartonella henselae with its mammalian host. Normalized spectral count data from cytoplasmic, total membrane, inner and outer membrane fractions allowed us to identify the predominant SCL for 82% of the identified proteins. The spectral count proportion of total membrane versus cytoplasmic fractions indicated the propensity of cytoplasmic proteins to co-fractionate with the inner membrane, and enabled usmore » to distinguish cytoplasmic, peripheral innermembrane and bona fide inner membrane proteins. Principal component analysis and k-nearest neighbor classification training on selected marker proteins or predominantly localized proteins, allowed us to determine an extensive catalog of at least 74 expressed outer membrane proteins, and to extend the SCL assignment to 94% of the identified proteins, including 18% where in silico methods gave no prediction. Suitable experimental proteomics data combined with straightforward computational approaches can thus identify the predominant SCL on a proteome-wide scale. Finally, we present a conceptual approach to identify proteins potentially changing their SCL in a condition-dependent fashion.« less

Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins

PubMed Central

Ma, Yue; Tuskan, Gerald A.

2018-01-01

The existence of complete genome sequences makes it important to develop different approaches for classification of large-scale data sets and to make extraction of biological insights easier. Here, we propose an approach for classification of complete proteomes/protein sets based on protein distributions on some basic attributes. We demonstrate the usefulness of this approach by determining protein distributions in terms of two attributes: protein lengths and protein intrinsic disorder contents (ID). The protein distributions based on L and ID are surveyed for representative proteome organisms and protein sets from the three domains of life. The two-dimensional maps (designated as fingerprints here) from the protein distribution densities in the LD space defined by ln(L) and ID are then constructed. The fingerprints for different organisms and protein sets are found to be distinct with each other, and they can therefore be used for comparative studies. As a test case, phylogenetic trees have been constructed based on the protein distribution densities in the fingerprints of proteomes of organisms without performing any protein sequence comparison and alignments. The phylogenetic trees generated are biologically meaningful, demonstrating that the protein distributions in the LD space may serve as unique phylogenetic signals of the organisms at the proteome level. PMID:29686995

Streptococcus iniae SF1: Complete Genome Sequence, Proteomic Profile, and Immunoprotective Antigens

PubMed Central

Zhang, Bao-cun; Zhang, Jian; Sun, Li

2014-01-01

Streptococcus iniae is a Gram-positive bacterium that is reckoned one of the most severe aquaculture pathogens. It has a broad host range among farmed marine and freshwater fish and can also cause zoonotic infection in humans. Here we report for the first time the complete genome sequence as well as the host factor-induced proteomic profile of a pathogenic S. iniae strain, SF1, a serotype I isolate from diseased fish. SF1 possesses a single chromosome of 2,149,844 base pairs, which contains 2,125 predicted protein coding sequences (CDS), 12 rRNA genes, and 45 tRNA genes. Among the protein-encoding CDS are genes involved in resource acquisition and utilization, signal sensing and transduction, carbohydrate metabolism, and defense against host immune response. Potential virulence genes include those encoding adhesins, autolysins, toxins, exoenzymes, and proteases. In addition, two putative prophages and a CRISPR-Cas system were found in the genome, the latter containing a CRISPR locus and four cas genes. Proteomic analysis detected 21 secreted proteins whose expressions were induced by host serum. Five of the serum-responsive proteins were subjected to immunoprotective analysis, which revealed that two of the proteins were highly protective against lethal S. iniae challenge when used as purified recombinant subunit vaccines. Taken together, these results provide an important molecular basis for future study of S. iniae in various aspects, in particular those related to pathogenesis and disease control. PMID:24621602

A proteome view of structural, functional, and taxonomic characteristics of major protein domain clusters.

PubMed

Sun, Chia-Tsen; Chiang, Austin W T; Hwang, Ming-Jing

2017-10-27

Proteome-scale bioinformatics research is increasingly conducted as the number of completely sequenced genomes increases, but analysis of protein domains (PDs) usually relies on similarity in their amino acid sequences and/or three-dimensional structures. Here, we present results from a bi-clustering analysis on presence/absence data for 6,580 unique PDs in 2,134 species with a sequenced genome, thus covering a complete set of proteins, for the three superkingdoms of life, Bacteria, Archaea, and Eukarya. Our analysis revealed eight distinctive PD clusters, which, following an analysis of enrichment of Gene Ontology functions and CATH classification of protein structures, were shown to exhibit structural and functional properties that are taxa-characteristic. For examples, the largest cluster is ubiquitous in all three superkingdoms, constituting a set of 1,472 persistent domains created early in evolution and retained in living organisms and characterized by basic cellular functions and ancient structural architectures, while an Archaea and Eukarya bi-superkingdom cluster suggests its PDs may have existed in the ancestor of the two superkingdoms, and others are single superkingdom- or taxa (e.g. Fungi)-specific. These results contribute to increase our appreciation of PD diversity and our knowledge of how PDs are used in species, yielding implications on species evolution.

The MaxQuant computational platform for mass spectrometry-based shotgun proteomics.

PubMed

Tyanova, Stefka; Temu, Tikira; Cox, Juergen

2016-12-01

MaxQuant is one of the most frequently used platforms for mass-spectrometry (MS)-based proteomics data analysis. Since its first release in 2008, it has grown substantially in functionality and can be used in conjunction with more MS platforms. Here we present an updated protocol covering the most important basic computational workflows, including those designed for quantitative label-free proteomics, MS1-level labeling and isobaric labeling techniques. This protocol presents a complete description of the parameters used in MaxQuant, as well as of the configuration options of its integrated search engine, Andromeda. This protocol update describes an adaptation of an existing protocol that substantially modifies the technique. Important concepts of shotgun proteomics and their implementation in MaxQuant are briefly reviewed, including different quantification strategies and the control of false-discovery rates (FDRs), as well as the analysis of post-translational modifications (PTMs). The MaxQuant output tables, which contain information about quantification of proteins and PTMs, are explained in detail. Furthermore, we provide a short version of the workflow that is applicable to data sets with simple and standard experimental designs. The MaxQuant algorithms are efficiently parallelized on multiple processors and scale well from desktop computers to servers with many cores. The software is written in C# and is freely available at http://www.maxquant.org.

Proteomic analysis of a decellularized human vocal fold mucosa scaffold using 2D electrophoresis and high-resolution mass spectrometry.

PubMed

Welham, Nathan V; Chang, Zhen; Smith, Lloyd M; Frey, Brian L

2013-01-01

Natural biologic scaffolds for tissue engineering are commonly generated by decellularization of tissues and organs. Despite some preclinical and clinical success, in vivo scaffold remodeling and functional outcomes remain variable, presumably due to the influence of unidentified bioactive molecules on the scaffold-host interaction. Here, we used 2D electrophoresis and high-resolution mass spectrometry-based proteomic analyses to evaluate decellularization effectiveness and identify potentially bioactive protein remnants in a human vocal fold mucosa model. We noted proteome, phosphoproteome and O-glycoproteome depletion post-decellularization, and identified >200 unique protein species within the decellularized scaffold. Gene ontology-based enrichment analysis revealed a dominant set of functionally-related ontology terms associated with extracellular matrix assembly, organization, morphology and patterning, consistent with preservation of a tissue-specific niche for later cell seeding and infiltration. We further identified a subset of ontology terms associated with bioactive (some of which are antigenic) cellular proteins, despite histological and immunohistochemical data indicating complete decellularization. These findings demonstrate the value of mass spectrometry-based proteomics in identifying agents potentially responsible for variation in host response to engineered tissues derived from decellularized scaffolds. This work has implications for the manufacturing of biologic scaffolds from any tissue or organ, as well as for prediction and monitoring of the scaffold-host interaction in vivo. Copyright © 2012 Elsevier Ltd. All rights reserved.

The developmental proteome of Drosophila melanogaster

PubMed Central

Casas-Vila, Nuria; Bluhm, Alina; Sayols, Sergi; Dinges, Nadja; Dejung, Mario; Altenhein, Tina; Kappei, Dennis; Altenhein, Benjamin; Roignant, Jean-Yves; Butter, Falk

2017-01-01

Drosophila melanogaster is a widely used genetic model organism in developmental biology. While this model organism has been intensively studied at the RNA level, a comprehensive proteomic study covering the complete life cycle is still missing. Here, we apply label-free quantitative proteomics to explore proteome remodeling across Drosophila’s life cycle, resulting in 7952 proteins, and provide a high temporal-resolved embryogenesis proteome of 5458 proteins. Our proteome data enabled us to monitor isoform-specific expression of 34 genes during development, to identify the pseudogene Cyp9f3Ψ as a protein-coding gene, and to obtain evidence of 268 small proteins. Moreover, the comparison with available transcriptomic data uncovered examples of poor correlation between mRNA and protein, underscoring the importance of proteomics to study developmental progression. Data integration of our embryogenesis proteome with tissue-specific data revealed spatial and temporal information for further functional studies of yet uncharacterized proteins. Overall, our high resolution proteomes provide a powerful resource and can be explored in detail in our interactive web interface. PMID:28381612

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)”.

Hormone regulation of rhizome development in tall fescue (Festuca arundinacea) associated with proteomic changes controlling respiratory and amino acid metabolism

PubMed Central

Ma, Xiqing; Xu, Qian; Meyer, William A.; Huang, Bingru

2016-01-01

Background and Aims Rhizomes are underground stems with meristematic tissues capable of generating shoots and roots. However, mechanisms controlling rhizome formation and growth are yet to be completely understood. The objectives of this study were to investigate whether rhizome development could be regulated by cytokinins (CKs) and gibberellic acids (GAs), and determine underlying mechanisms of regulation of rhizome formation and growth of tall fescue (Festuca arundinacea) by a CK or GA through proteomic and transcript analysis. Methods A rhizomatous genotype of tall fescue (‘BR’) plants were treated with 6-benzylaminopurine (BAP, a synthetic cytokinin) or GA3 in hydroponic culture in growth chambers. Furthermore, comparative proteomic analysis of two-dimensional electrophoresis and mass spectrometry were performed to investigate proteins and associated metabolic pathways imparting increased rhizome number by BAP and rhizome elongation by GA3. Key Results BAP stimulated rhizome formation while GA3 promoted rhizome elongation. Proteomic analysis identified 76 differentially expressed proteins (DEPs) due to BAP treatment and 37 DEPs due to GA3 treatment. Cytokinin-related genes and cell division-related genes were upregulated in the rhizome node by BAP and gibberellin-related and cell growth-related genes in the rhizome by GA3. Conclusions Most of the BAP- or GA-responsive DEPs were involved in respiratory metabolism and amino acid metabolism. Transcription analysis demonstrated that genes involved in hormone metabolism, signalling pathways, cell division and cell-wall loosening were upregulated by BAP or GA3. The CK and GA promoted rhizome formation and growth, respectively, by activating metabolic pathways that supply energy and amino acids to support cell division and expansion during rhizome initiation and elongation in tall fescue. PMID:27443301

Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins

DOE PAGES

Guo, Hao-Bo; Ma, Yue; Tuskan, Gerald A.; ...

2018-01-01

The existence of complete genome sequences makes it important to develop different approaches for classification of large-scale data sets and to make extraction of biological insights easier. Here, we propose an approach for classification of complete proteomes/protein sets based on protein distributions on some basic attributes. We demonstrate the usefulness of this approach by determining protein distributions in terms of two attributes: protein lengths and protein intrinsic disorder contents (ID). The protein distributions based on L and ID are surveyed for representative proteome organisms and protein sets from the three domains of life. The two-dimensional maps (designated as fingerprints here)more » from the protein distribution densities in the LD space defined by ln( L ) and ID are then constructed. The fingerprints for different organisms and protein sets are found to be distinct with each other, and they can therefore be used for comparative studies. As a test case, phylogenetic trees have been constructed based on the protein distribution densities in the fingerprints of proteomes of organisms without performing any protein sequence comparison and alignments. The phylogenetic trees generated are biologically meaningful, demonstrating that the protein distributions in the LD space may serve as unique phylogenetic signals of the organisms at the proteome level.« less

Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins

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

Guo, Hao-Bo; Ma, Yue; Tuskan, Gerald A.

The existence of complete genome sequences makes it important to develop different approaches for classification of large-scale data sets and to make extraction of biological insights easier. Here, we propose an approach for classification of complete proteomes/protein sets based on protein distributions on some basic attributes. We demonstrate the usefulness of this approach by determining protein distributions in terms of two attributes: protein lengths and protein intrinsic disorder contents (ID). The protein distributions based on L and ID are surveyed for representative proteome organisms and protein sets from the three domains of life. The two-dimensional maps (designated as fingerprints here)more » from the protein distribution densities in the LD space defined by ln( L ) and ID are then constructed. The fingerprints for different organisms and protein sets are found to be distinct with each other, and they can therefore be used for comparative studies. As a test case, phylogenetic trees have been constructed based on the protein distribution densities in the fingerprints of proteomes of organisms without performing any protein sequence comparison and alignments. The phylogenetic trees generated are biologically meaningful, demonstrating that the protein distributions in the LD space may serve as unique phylogenetic signals of the organisms at the proteome level.« less

Early Prediction of Lupus Nephritis Using Advanced Proteomics

DTIC Science & Technology

2010-06-01

SELDI-TOF-MS. Additional proteomic profiling studies using NMR- and MS-based metabonomics have been completed, and LC/MS based protein profiling using...Flight mass spectrometry (SELDI-TOF-MS). Changes in proteomic profiles will be confirmed and enhanced using NMR- and MS-based metabonomics , by Dr...performed using NMR- and MS-based metabonomics at Miami University, in the laboratory of Dr. Michael Kennedy. Initial spectra and profiles obtained show

Proteomic Changes in Rat Thyroarytenoid Muscle Induced by Botulinum Neurotoxin Injection

PubMed Central

Welham, Nathan V.; Marriott, Gerard; Tateya, Ichiro; Bless, Diane M.

2009-01-01

Botulinum neurotoxin (BoNT) injection into the thyroarytenoid (TA) muscle is a commonly performed medical intervention for adductor spasmodic dysphonia. The mechanism of action of BoNT at the neuromuscular junction is well understood, however, aside from reports focused on myosin heavy chain isoform abundance, there is a paucity of data addressing the effects of therapeutic BoNT injection on the TA muscle proteome. In this study, 12 adult Sprague Dawley rats underwent unilateral TA muscle BoNT serotype A injection followed by tissue harvest at 72 hrs, 7 days, 14 days, and 56 days post-injection. Three additional rats were reserved as controls. Proteomic analysis was performed using 2D SDS-PAGE followed by MALDI-MS. Vocal fold movement was significantly reduced by 72 hrs, with complete return of function by 56 days. Twenty-five protein spots demonstrated significant protein abundance changes following BoNT injection, and were associated with alterations in energy metabolism, muscle contractile function, cellular stress response, transcription, translation, and cell proliferation. A number of protein abundance changes persisted beyond the return of gross physiologic TA function. These findings represent the first report of BoNT induced changes in any skeletal muscle proteome, and reinforce the utility of applying proteomic tools to the study of system-wide biological processes in normal and perturbed TA muscle function. PMID:18442174

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

PubMed Central

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

2013-01-01

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

Comparative and quantitative proteomics reveal the adaptive strategies of oyster larvae to ocean acidification.

PubMed

Dineshram, R; Quan, Q; Sharma, Rakesh; Chandramouli, Kondethimmanahalli; Yalamanchili, Hari Krishna; Chu, Ivan; Thiyagarajan, Vengatesen

2015-12-01

Decreasing pH due to anthropogenic CO2 inputs, called ocean acidification (OA), can make coastal environments unfavorable for oysters. This is a serious socioeconomical issue for China which supplies >70% of the world's edible oysters. Here, we present an iTRAQ-based protein profiling approach for the detection and quantification of proteome changes under OA in the early life stage of a commercially important oyster, Crassostrea hongkongensis. Availability of complete genome sequence for the pacific oyster (Crassostrea gigas) enabled us to confidently quantify over 1500 proteins in larval oysters. Over 7% of the proteome was altered in response to OA at pHNBS 7.6. Analysis of differentially expressed proteins and their associated functional pathways showed an upregulation of proteins involved in calcification, metabolic processes, and oxidative stress, each of which may be important in physiological adaptation of this species to OA. The downregulation of cytoskeletal and signal transduction proteins, on the other hand, might have impaired cellular dynamics and organelle development under OA. However, there were no significant detrimental effects in developmental processes such as metamorphic success. Implications of the differentially expressed proteins and metabolic pathways in the development of OA resistance in oyster larvae are discussed. The MS proteomics data have been deposited to the ProteomeXchange with identifiers PXD002138 (http://proteomecentral.proteomexchange.org/dataset/PXD002138). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2015-03-01

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

Computational clustering for viral reference proteomes

PubMed Central

Chen, Chuming; Huang, Hongzhan; Mazumder, Raja; Natale, Darren A.; McGarvey, Peter B.; Zhang, Jian; Polson, Shawn W.; Wang, Yuqi; Wu, Cathy H.

2016-01-01

Motivation: The enormous number of redundant sequenced genomes has hindered efforts to analyze and functionally annotate proteins. As the taxonomy of viruses is not uniformly defined, viral proteomes pose special challenges in this regard. Grouping viruses based on the similarity of their proteins at proteome scale can normalize against potential taxonomic nomenclature anomalies. Results: We present Viral Reference Proteomes (Viral RPs), which are computed from complete virus proteomes within UniProtKB. Viral RPs based on 95, 75, 55, 35 and 15% co-membership in proteome similarity based clusters are provided. Comparison of our computational Viral RPs with UniProt’s curator-selected Reference Proteomes indicates that the two sets are consistent and complementary. Furthermore, each Viral RP represents a cluster of virus proteomes that was consistent with virus or host taxonomy. We provide BLASTP search and FTP download of Viral RP protein sequences, and a browser to facilitate the visualization of Viral RPs. Availability and implementation: http://proteininformationresource.org/rps/viruses/ Contact: chenc@udel.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153712

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.

Remodeling of skeletal muscle mitochondrial proteome with high-fat diet involves greater changes to β-oxidation than electron transfer proteins in mice.

PubMed

Dasari, Surendra; Newsom, Sean A; Ehrlicher, Sarah E; Stierwalt, Harrison D; Robinson, Matthew M

2018-05-29

Excess fat intake can increase lipid oxidation and expression of mitochondrial proteins, indicating remodeling of the mitochondrial proteome. Yet intermediates of lipid oxidation also accumulate and indicate a relative insufficiency to completely oxidize lipids. We investigated remodeling of the mitochondrial proteome to determine mechanisms of changes to lipid oxidation following high-fat feeding. C57BL/6J mice consumed either a high-fat diet (HFD, 60% fat from lard) or low fat diet (LFD, 10% fat) for 12 weeks. Mice were fasted 4 hours then anaesthetized by sodium pentobarbital for tissue collection. A mitochondrial-enriched fraction was prepared from gastrocnemius muscles and underwent proteomic analysis by high-resolution mass spectrometry. Mitochondrial respiratory efficiency was measured as ATP production per oxygen consumption (P:O). Intramuscular acyl-carnitines were measured by liquid-chromatography mass spectrometry. A total of 658 mitochondrial proteins were identified with 40 having higher and 14 having lower abundance in mice consuming a HFD compared to LFD. Individual proteins that changed with HFD were primarily related to β-oxidation with fewer changes to the electron transfer system. Gene set enrichment analysis identified HFD increased pathways of lipid metabolism and β-oxidation. Intramuscular concentrations of select acyl-carnitines (C18:0) were greater with HFD and reflected dietary lipid composition. Mitochondrial respiratory P:O for lipids was not different between LFD and HFD. Following the 60% fat diet, remodeling of the mitochondrial proteome revealed up-regulation of proteins regulating lipid oxidation that was not evident for all mitochondrial pathways. The accumulation of lipid metabolites with obesity may occur without intrinsic dysfunction to mitochondrial lipid oxidation.

Identification and Validation of Human Missing Proteins and Peptides in Public Proteome Databases: Data Mining Strategy.

PubMed

Elguoshy, Amr; Hirao, Yoshitoshi; Xu, Bo; Saito, Suguru; Quadery, Ali F; Yamamoto, Keiko; Mitsui, Toshiaki; Yamamoto, Tadashi

2017-12-01

In an attempt to complete human proteome project (HPP), Chromosome-Centric Human Proteome Project (C-HPP) launched the journey of missing protein (MP) investigation in 2012. However, 2579 and 572 protein entries in the neXtProt (2017-1) are still considered as missing and uncertain proteins, respectively. Thus, in this study, we proposed a pipeline to analyze, identify, and validate human missing and uncertain proteins in open-access transcriptomics and proteomics databases. Analysis of RNA expression pattern for missing proteins in Human protein Atlas showed that 28% of them, such as Olfactory receptor 1I1 ( O60431 ), had no RNA expression, suggesting the necessity to consider uncommon tissues for transcriptomic and proteomic studies. Interestingly, 21% had elevated expression level in a particular tissue (tissue-enriched proteins), indicating the importance of targeting such proteins in their elevated tissues. Additionally, the analysis of RNA expression level for missing proteins showed that 95% had no or low expression level (0-10 transcripts per million), indicating that low abundance is one of the major obstacles facing the detection of missing proteins. Moreover, missing proteins are predicted to generate fewer predicted unique tryptic peptides than the identified proteins. Searching for these predicted unique tryptic peptides that correspond to missing and uncertain proteins in the experimental peptide list of open-access MS-based databases (PA, GPM) resulted in the detection of 402 missing and 19 uncertain proteins with at least two unique peptides (≥9 aa) at <(5 × 10 -4 )% FDR. Finally, matching the native spectra for the experimentally detected peptides with their SRMAtlas synthetic counterparts at three transition sources (QQQ, QTOF, QTRAP) gave us an opportunity to validate 41 missing proteins by ≥2 proteotypic peptides.

Trends in genome dynamics among major orders of insects revealed through variations in protein families.

PubMed

Rappoport, Nadav; Linial, Michal

2015-08-07

Insects belong to a class that accounts for the majority of animals on earth. With over one million identified species, insects display a huge diversity and occupy extreme environments. At present, there are dozens of fully sequenced insect genomes that cover a range of habitats, social behavior and morphologies. In view of such diverse collection of genomes, revealing evolutionary trends and charting functional relationships of proteins remain challenging. We analyzed the relatedness of 17 complete proteomes representative of proteomes from insects including louse, bee, beetle, ants, flies and mosquitoes, as well as an out-group from the crustaceans. The analyzed proteomes mostly represented the orders of Hymenoptera and Diptera. The 287,405 protein sequences from the 18 proteomes were automatically clustered into 20,933 families, including 799 singletons. A comprehensive analysis based on statistical considerations identified the families that were significantly expanded or reduced in any of the studied organisms. Among all the tested species, ants are characterized by an exceptionally high rate of family gain and loss. By assigning annotations to hundreds of species-specific families, the functional diversity among species and between the major clades (Diptera and Hymenoptera) is revealed. We found that many species-specific families are associated with receptor signaling, stress-related functions and proteases. The highest variability among insects associates with the function of transposition and nucleic acids processes (collectively coined TNAP). Specifically, the wasp and ants have an order of magnitude more TNAP families and proteins relative to species that belong to Diptera (mosquitoes and flies). An unsupervised clustering methodology combined with a comparative functional analysis unveiled proteomic signatures in the major clades of winged insects. We propose that the expansion of TNAP families in Hymenoptera potentially contributes to the accelerated genome dynamics that characterize the wasp and ants.

Developmental distribution of the plasma membrane-enriched proteome in the maize primary root growth zone.

PubMed

Zhang, Zhe; Voothuluru, Priyamvada; Yamaguchi, Mineo; Sharp, Robert E; Peck, Scott C

2013-01-01

Within the growth zone of the maize primary root, there are well-defined patterns of spatial and temporal organization of cell division and elongation. However, the processes underlying this organization remain poorly understood. To gain additional insights into the differences amongst the defined regions, we performed a proteomic analysis focusing on fractions enriched for plasma membrane (PM) proteins. The PM is the interface between the plant cell and the apoplast and/or extracellular space. As such, it is a key structure involved in the exchange of nutrients and other molecules as well as in the integration of signals that regulate growth and development. Despite the important functions of PM-localized proteins in mediating these processes, a full understanding of dynamic changes in PM proteomes is often impeded by low relative concentrations relative to total proteins. Using a relatively simple strategy of treating microsomal fractions with Brij-58 detergent to enrich for PM proteins, we compared the developmental distribution of proteins within the root growth zone which revealed a number of previously known as well as novel proteins with interesting patterns of abundance. For instance, the quantitative proteomic analysis detected a gradient of PM aquaporin proteins similar to that previously reported using immunoblot analyses, confirming the veracity of this strategy. Cellulose synthases increased in abundance with increasing distance from the root apex, consistent with expected locations of cell wall deposition. The similar distribution pattern for Brittle-stalk-2-like protein implicates that this protein may also have cell wall related functions. These results show that the simplified PM enrichment method previously demonstrated in Arabidopsis can be successfully applied to completely unrelated plant tissues and provide insights into differences in the PM proteome throughout growth and development zones of the maize primary root.

Dynamic Response of Mycobacterium vanbaalenii PYR-1 to BP Deepwater Horizon Crude Oil

PubMed Central

Kim, Seong-Jae; Kweon, Ohgew; Sutherland, John B.; Kim, Hyun-Lee; Jones, Richard C.; Burback, Brian L.; Graves, Steven W.; Psurny, Edward

2015-01-01

We investigated the response of the hydrocarbon-degrading Mycobacterium vanbaalenii PYR-1 to crude oil from the BP Deepwater Horizon (DWH) spill, using substrate depletion, genomic, and proteome analyses. M. vanbaalenii PYR-1 cultures were incubated with BP DWH crude oil, and proteomes and degradation of alkanes and polycyclic aromatic hydrocarbons (PAHs) were analyzed at four time points over 30 days. Gas chromatography-mass spectrometry (GC-MS) analysis showed a chain length-dependent pattern of alkane degradation, with C12 and C13 being degraded at the highest rate, although alkanes up to C28 were degraded. Whereas phenanthrene and pyrene were completely degraded, a significantly smaller amount of fluoranthene was degraded. Proteome analysis identified 3,948 proteins, with 876 and 1,859 proteins up- and downregulated, respectively. We observed dynamic changes in protein expression during BP crude oil incubation, including transcriptional factors and transporters potentially involved in adaptation to crude oil. The proteome also provided a molecular basis for the metabolism of the aliphatic and aromatic hydrocarbon components in the BP DWH crude oil, which included upregulation of AlkB alkane hydroxylase and an expression pattern of PAH-metabolizing enzymes different from those in previous proteome expression studies of strain PYR-1 incubated with pure or mixed PAHs, particularly the ring-hydroxylating oxygenase (RHO) responsible for the initial oxidation of aromatic hydrocarbons. Based on these results, a comprehensive cellular response of M. vanbaalenii PYR-1 to BP crude oil was proposed. This study increases our fundamental understanding of the impact of crude oil on the cellular response of bacteria and provides data needed for development of practical bioremediation applications. PMID:25888169

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

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.

Proteomic analysis of grapevine resistance induced by Trichoderma harzianum T39 reveals specific defence pathways activated against downy mildew

PubMed Central

Perazzolli, Michele

2012-01-01

Downy mildew is caused by the oomycete Plasmopara viticola and is one of the most serious diseases of grapevine. The beneficial microorganism Trichoderma harzianum T39 (T39) has previously been shown to induce plant-mediated resistance and to reduce the severity of downy mildew in susceptible grapevines. In order to better understand the cellular processes associated with T39-induced resistance, the proteomic and histochemical changes activated by T39 in grapevine were investigated before and 1 day after P. viticola inoculation. A comprehensive proteomic analysis of T39-induced resistance in grapevine was performed using an eight-plex iTRAQ protocol, resulting in the identification and quantification of a total of 800 proteins. Most of the proteins directly affected by T39 were found to be involved in signal transduction, indicating activation of a complete microbial recognition machinery. Moreover, T39-induced resistance was associated with rapid accumulation of reactive oxygen species and callose at infection sites, as well as changes in abundance of proteins involved in response to stress and redox balance, indicating an active defence response to downy mildew. On the other hand, proteins affected by P. viticola in control plants mainly decreased in abundance, possibly reflecting the establishment of a compatible interaction. Finally, the high-throughput iTRAQ protocol allowed de novo peptide sequencing, which will be used to improve annotation of the Vitis vinifera cv. Pinot Noir proteome. PMID:23105132

In-depth Proteomics Characterization of Embryogenesis of the Honey Bee Worker (Apis mellifera ligustica) *

PubMed Central

Fang, Yu; Feng, Mao; Han, Bin; Lu, Xiaoshan; Ramadan, Haitham; Li, Jianke

2014-01-01

Identifying proteome changes of honey bee embryogenesis is of prime importance for unraveling the molecular mechanisms that they underlie. However, many proteomic changes during the embryonic period are not well characterized. We analyzed the proteomic alterations over the complete time course of honey bee worker embryogenesis at 24, 48, and 72 h of age, using mass spectrometry-based proteomics, label-free quantitation, and bioinformatics. Of the 1460 proteins identified the embryo of all three ages, the core proteome (proteins shared by the embryos of all three ages, accounting for 40%) was mainly involved in protein synthesis, metabolic energy, development, and molecular transporter, which indicates their centrality in driving embryogenesis. However, embryos at different developmental stages have their own specific proteome and pathway signatures to coordinate and modulate developmental events. The young embryos (<24 h) stronger expression of proteins related to nutrition storage and nucleic acid metabolism may correlate with the cell proliferation occurring at this stage. The middle aged embryos (24–48 h) enhanced expression of proteins associated with cell cycle control, transporters, antioxidant activity, and the cytoskeleton suggest their roles to support rudimentary organogenesis. Among these proteins, the biological pathways of aminoacyl-tRNA biosynthesis, β-alanine metabolism, and protein export are intensively activated in the embryos of middle age. The old embryos (48–72 h) elevated expression of proteins implicated in fatty acid metabolism and morphogenesis indicate their functionality for the formation and development of organs and dorsal closure, in which the biological pathways of fatty acid metabolism and RNA transport are highly activated. These findings add novel understanding to the molecular details of honey bee embryogenesis, in which the programmed activation of the proteome matches with the physiological transition observed during embryogenesis. The identified biological pathways and key node proteins allow for further functional analysis and genetic manipulation for both the honey bee embryos and other eusocial insects. PMID:24895377

In-depth proteomics characterization of embryogenesis of the honey bee worker (Apis mellifera ligustica).

PubMed

Fang, Yu; Feng, Mao; Han, Bin; Lu, Xiaoshan; Ramadan, Haitham; Li, Jianke

2014-09-01

Identifying proteome changes of honey bee embryogenesis is of prime importance for unraveling the molecular mechanisms that they underlie. However, many proteomic changes during the embryonic period are not well characterized. We analyzed the proteomic alterations over the complete time course of honey bee worker embryogenesis at 24, 48, and 72 h of age, using mass spectrometry-based proteomics, label-free quantitation, and bioinformatics. Of the 1460 proteins identified the embryo of all three ages, the core proteome (proteins shared by the embryos of all three ages, accounting for 40%) was mainly involved in protein synthesis, metabolic energy, development, and molecular transporter, which indicates their centrality in driving embryogenesis. However, embryos at different developmental stages have their own specific proteome and pathway signatures to coordinate and modulate developmental events. The young embryos (<24 h) stronger expression of proteins related to nutrition storage and nucleic acid metabolism may correlate with the cell proliferation occurring at this stage. The middle aged embryos (24-48 h) enhanced expression of proteins associated with cell cycle control, transporters, antioxidant activity, and the cytoskeleton suggest their roles to support rudimentary organogenesis. Among these proteins, the biological pathways of aminoacyl-tRNA biosynthesis, β-alanine metabolism, and protein export are intensively activated in the embryos of middle age. The old embryos (48-72 h) elevated expression of proteins implicated in fatty acid metabolism and morphogenesis indicate their functionality for the formation and development of organs and dorsal closure, in which the biological pathways of fatty acid metabolism and RNA transport are highly activated. These findings add novel understanding to the molecular details of honey bee embryogenesis, in which the programmed activation of the proteome matches with the physiological transition observed during embryogenesis. The identified biological pathways and key node proteins allow for further functional analysis and genetic manipulation for both the honey bee embryos and other eusocial insects. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

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

PubMed Central

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

2008-01-01

Background Quantitative proteomics holds great promise for identifying proteins that are differentially abundant between populations representing different physiological or disease states. A range of computational tools is now available for both isotopically labeled and label-free liquid chromatography mass spectrometry (LC-MS) based quantitative proteomics. However, they are generally not comparable to each other in terms of functionality, user interfaces, information input/output, and do not readily facilitate appropriate statistical data analysis. These limitations, along with the array of choices, present a daunting prospect for biologists, and other researchers not trained in bioinformatics, who wish to use LC-MS-based quantitative proteomics. Results We have developed Corra, a computational framework and tools for discovery-based LC-MS proteomics. Corra extends and adapts existing algorithms used for LC-MS-based proteomics, and statistical algorithms, originally developed for microarray data analyses, appropriate for LC-MS data analysis. Corra also adapts software engineering technologies (e.g. Google Web Toolkit, distributed processing) so that computationally intense data processing and statistical analyses can run on a remote server, while the user controls and manages the process from their own computer via a simple web interface. Corra also allows the user to output significantly differentially abundant LC-MS-detected peptide features in a form compatible with subsequent sequence identification via tandem mass spectrometry (MS/MS). We present two case studies to illustrate the application of Corra to commonly performed LC-MS-based biological workflows: a pilot biomarker discovery study of glycoproteins isolated from human plasma samples relevant to type 2 diabetes, and a study in yeast to identify in vivo targets of the protein kinase Ark1 via phosphopeptide profiling. Conclusion The Corra computational framework leverages computational innovation to enable biologists or other researchers to process, analyze and visualize LC-MS data with what would otherwise be a complex and not user-friendly suite of tools. Corra enables appropriate statistical analyses, with controlled false-discovery rates, ultimately to inform subsequent targeted identification of differentially abundant peptides by MS/MS. For the user not trained in bioinformatics, Corra represents a complete, customizable, free and open source computational platform enabling LC-MS-based proteomic workflows, and as such, addresses an unmet need in the LC-MS proteomics field. PMID:19087345

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.

Platelet proteome reveals novel pathways of platelet activation and platelet-mediated immunoregulation in dengue.

PubMed

Trugilho, Monique Ramos de Oliveira; Hottz, Eugenio Damaceno; Brunoro, Giselle Villa Flor; Teixeira-Ferreira, André; Carvalho, Paulo Costa; Salazar, Gustavo Adolfo; Zimmerman, Guy A; Bozza, Fernando A; Bozza, Patrícia T; Perales, Jonas

2017-05-01

Dengue is the most prevalent human arbovirus disease worldwide. Dengue virus (DENV) infection causes syndromes varying from self-limiting febrile illness to severe dengue. Although dengue pathophysiology is not completely understood, it is widely accepted that increased inflammation plays important roles in dengue pathogenesis. Platelets are blood cells classically known as effectors of hemostasis which have been increasingly recognized to have major immune and inflammatory activities. Nevertheless, the phenotype and effector functions of platelets in dengue pathogenesis are not completely understood. Here we used quantitative proteomics to investigate the protein content of platelets in clinical samples from patients with dengue compared to platelets from healthy donors. Our assays revealed a set of 252 differentially abundant proteins. In silico analyses associated these proteins with key molecular events including platelet activation and inflammatory responses, and with events not previously attributed to platelets during dengue infection including antigen processing and presentation, proteasome activity, and expression of histones. From these results, we conducted functional assays using samples from a larger cohort of patients and demonstrated evidence for platelet activation indicated by P-selectin (CD62P) translocation and secretion of granule-stored chemokines by platelets. In addition, we found evidence that DENV infection triggers HLA class I synthesis and surface expression by a mechanism depending on functional proteasome activity. Furthermore, we demonstrate that cell-free histone H2A released during dengue infection binds to platelets, increasing platelet activation. These findings are consistent with functional importance of HLA class I, proteasome subunits, and histones that we found exclusively in proteome analysis of platelets in samples from dengue patients. Our study provides the first in-depth characterization of the platelet proteome in dengue, and sheds light on new mechanisms of platelet activation and platelet-mediated immune and inflammatory responses.

Platelet proteome reveals novel pathways of platelet activation and platelet-mediated immunoregulation in dengue

PubMed Central

Teixeira-Ferreira, André; Carvalho, Paulo Costa; Salazar, Gustavo Adolfo; Zimmerman, Guy A.; Perales, Jonas

2017-01-01

Dengue is the most prevalent human arbovirus disease worldwide. Dengue virus (DENV) infection causes syndromes varying from self-limiting febrile illness to severe dengue. Although dengue pathophysiology is not completely understood, it is widely accepted that increased inflammation plays important roles in dengue pathogenesis. Platelets are blood cells classically known as effectors of hemostasis which have been increasingly recognized to have major immune and inflammatory activities. Nevertheless, the phenotype and effector functions of platelets in dengue pathogenesis are not completely understood. Here we used quantitative proteomics to investigate the protein content of platelets in clinical samples from patients with dengue compared to platelets from healthy donors. Our assays revealed a set of 252 differentially abundant proteins. In silico analyses associated these proteins with key molecular events including platelet activation and inflammatory responses, and with events not previously attributed to platelets during dengue infection including antigen processing and presentation, proteasome activity, and expression of histones. From these results, we conducted functional assays using samples from a larger cohort of patients and demonstrated evidence for platelet activation indicated by P-selectin (CD62P) translocation and secretion of granule-stored chemokines by platelets. In addition, we found evidence that DENV infection triggers HLA class I synthesis and surface expression by a mechanism depending on functional proteasome activity. Furthermore, we demonstrate that cell-free histone H2A released during dengue infection binds to platelets, increasing platelet activation. These findings are consistent with functional importance of HLA class I, proteasome subunits, and histones that we found exclusively in proteome analysis of platelets in samples from dengue patients. Our study provides the first in-depth characterization of the platelet proteome in dengue, and sheds light on new mechanisms of platelet activation and platelet-mediated immune and inflammatory responses. PMID:28542641

MPLEx: a Robust and Universal Protocol for Single-Sample Integrative Proteomic, Metabolomic, and Lipidomic Analyses

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

Nakayasu, Ernesto S.; Nicora, Carrie D.; Sims, Amy C.

2016-05-03

ABSTRACT Integrative multi-omics analyses can empower more effective investigation and complete understanding of complex biological systems. Despite recent advances in a range of omics analyses, multi-omic measurements of the same sample are still challenging and current methods have not been well evaluated in terms of reproducibility and broad applicability. Here we adapted a solvent-based method, widely applied for extracting lipids and metabolites, to add proteomics to mass spectrometry-based multi-omics measurements. Themetabolite,protein, andlipidextraction (MPLEx) protocol proved to be robust and applicable to a diverse set of sample types, including cell cultures, microbial communities, and tissues. To illustrate the utility of thismore » protocol, an integrative multi-omics analysis was performed using a lung epithelial cell line infected with Middle East respiratory syndrome coronavirus, which showed the impact of this virus on the host glycolytic pathway and also suggested a role for lipids during infection. The MPLEx method is a simple, fast, and robust protocol that can be applied for integrative multi-omic measurements from diverse sample types (e.g., environmental,in vitro, and clinical). IMPORTANCEIn systems biology studies, the integration of multiple omics measurements (i.e., genomics, transcriptomics, proteomics, metabolomics, and lipidomics) has been shown to provide a more complete and informative view of biological pathways. Thus, the prospect of extracting different types of molecules (e.g., DNAs, RNAs, proteins, and metabolites) and performing multiple omics measurements on single samples is very attractive, but such studies are challenging due to the fact that the extraction conditions differ according to the molecule type. Here, we adapted an organic solvent-based extraction method that demonstrated broad applicability and robustness, which enabled comprehensive proteomics, metabolomics, and lipidomics analyses from the same sample.« less

SILAC-based proteomics of human primary endothelial cell morphogenesis unveils tumor angiogenic markers.

PubMed

Zanivan, Sara; Maione, Federica; Hein, Marco Y; Hernández-Fernaud, Juan Ramon; Ostasiewicz, Pawel; Giraudo, Enrico; Mann, Matthias

2013-12-01

Proteomics has been successfully used for cell culture on dishes, but more complex cellular systems have proven to be challenging and so far poorly approached with proteomics. Because of the complexity of the angiogenic program, we still do not have a complete understanding of the molecular mechanisms involved in this process, and there have been no in depth quantitative proteomic studies. Plating endothelial cells on matrigel recapitulates aspects of vessel growth, and here we investigate this mechanism by using a spike-in SILAC quantitative proteomic approach. By comparing proteomic changes in primary human endothelial cells morphogenesis on matrigel to general adhesion mechanisms in cells spreading on culture dish, we pinpoint pathways and proteins modulated by endothelial cells. The cell-extracellular matrix adhesion proteome depends on the adhesion substrate, and a detailed proteomic profile of the extracellular matrix secreted by endothelial cells identified CLEC14A as a matrix component, which binds to MMRN2. We verify deregulated levels of these proteins during tumor angiogenesis in models of multistage carcinogenesis. This is the most in depth quantitative proteomic study of endothelial cell morphogenesis, which shows the potential of applying high accuracy quantitative proteomics to in vitro models of vessel growth to shed new light on mechanisms that accompany pathological angiogenesis. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD000359.

Megadalton Complexes in the Chloroplast Stroma of Arabidopsis thaliana Characterized by Size Exclusion Chromatography, Mass Spectrometry, and Hierarchical Clustering*

PubMed Central

Olinares, Paul Dominic B.; Ponnala, Lalit; van Wijk, Klaas J.

2010-01-01

To characterize MDa-sized macromolecular chloroplast stroma protein assemblies and to extend coverage of the chloroplast stroma proteome, we fractionated soluble chloroplast stroma in the non-denatured state by size exclusion chromatography with a size separation range up to ∼5 MDa. To maximize protein complex stability and resolution of megadalton complexes, ionic strength and composition were optimized. Subsequent high accuracy tandem mass spectrometry analysis (LTQ-Orbitrap) identified 1081 proteins across the complete native mass range. Protein complexes and assembly states above 0.8 MDa were resolved using hierarchical clustering, and protein heat maps were generated from normalized protein spectral counts for each of the size exclusion chromatography fractions; this complemented previous analysis of stromal complexes up to 0.8 MDa (Peltier, J. B., Cai, Y., Sun, Q., Zabrouskov, V., Giacomelli, L., Rudella, A., Ytterberg, A. J., Rutschow, H., and van Wijk, K. J. (2006) The oligomeric stromal proteome of Arabidopsis thaliana chloroplasts. Mol. Cell. Proteomics 5, 114–133). This combined experimental and bioinformatics analyses resolved chloroplast ribosomes in different assembly and functional states (e.g. 30, 50, and 70 S), which enabled the identification of plastid homologues of prokaryotic ribosome assembly factors as well as proteins involved in co-translational modifications, targeting, and folding. The roles of these ribosome-associating proteins will be discussed. Known RNA splice factors (e.g. CAF1/WTF1/RNC1) as well as uncharacterized proteins with RNA-binding domains (pentatricopeptide repeat, RNA recognition motif, and chloroplast ribosome maturation), RNases, and DEAD box helicases were found in various sized complexes. Chloroplast DNA (>3 MDa) was found in association with the complete heteromeric plastid-encoded DNA polymerase complex, and a dozen other DNA-binding proteins, e.g. DNA gyrase, topoisomerase, and various DNA repair enzymes. The heteromeric ≥5-MDa pyruvate dehydrogenase complex and the 0.8–1-MDa acetyl-CoA carboxylase complex associated with uncharacterized biotin carboxyl carrier domain proteins constitute the entry point to fatty acid metabolism in leaves; we suggest that their large size relates to the need for metabolic channeling. Protein annotations and identification data are available through the Plant Proteomics Database, and mass spectrometry data are available through Proteomics Identifications database. PMID:20423899

Proteogenomics: Integrating Next-Generation Sequencing and Mass Spectrometry to Characterize Human Proteomic Variation

NASA Astrophysics Data System (ADS)

Sheynkman, Gloria M.; Shortreed, Michael R.; Cesnik, Anthony J.; Smith, Lloyd M.

2016-06-01

Mass spectrometry-based proteomics has emerged as the leading method for detection, quantification, and characterization of proteins. Nearly all proteomic workflows rely on proteomic databases to identify peptides and proteins, but these databases typically contain a generic set of proteins that lack variations unique to a given sample, precluding their detection. Fortunately, proteogenomics enables the detection of such proteomic variations and can be defined, broadly, as the use of nucleotide sequences to generate candidate protein sequences for mass spectrometry database searching. Proteogenomics is experiencing heightened significance due to two developments: (a) advances in DNA sequencing technologies that have made complete sequencing of human genomes and transcriptomes routine, and (b) the unveiling of the tremendous complexity of the human proteome as expressed at the levels of genes, cells, tissues, individuals, and populations. We review here the field of human proteogenomics, with an emphasis on its history, current implementations, the types of proteomic variations it reveals, and several important applications.

Proteogenomics: Integrating Next-Generation Sequencing and Mass Spectrometry to Characterize Human Proteomic Variation

PubMed Central

Sheynkman, Gloria M.; Shortreed, Michael R.; Cesnik, Anthony J.; Smith, Lloyd M.

2016-01-01

Mass spectrometry–based proteomics has emerged as the leading method for detection, quantification, and characterization of proteins. Nearly all proteomic workflows rely on proteomic databases to identify peptides and proteins, but these databases typically contain a generic set of proteins that lack variations unique to a given sample, precluding their detection. Fortunately, proteogenomics enables the detection of such proteomic variations and can be defined, broadly, as the use of nucleotide sequences to generate candidate protein sequences for mass spectrometry database searching. Proteogenomics is experiencing heightened significance due to two developments: (a) advances in DNA sequencing technologies that have made complete sequencing of human genomes and transcriptomes routine, and (b) the unveiling of the tremendous complexity of the human proteome as expressed at the levels of genes, cells, tissues, individuals, and populations. We review here the field of human proteogenomics, with an emphasis on its history, current implementations, the types of proteomic variations it reveals, and several important applications. PMID:27049631

Detection of Missing Proteins Using the PRIDE Database as a Source of Mass Spectrometry Evidence.

PubMed

Garin-Muga, Alba; Odriozola, Leticia; Martínez-Val, Ana; Del Toro, Noemí; Martínez, Rocío; Molina, Manuela; Cantero, Laura; Rivera, Rocío; Garrido, Nicolás; Dominguez, Francisco; Sanchez Del Pino, Manuel M; Vizcaíno, Juan Antonio; Corrales, Fernando J; Segura, Victor

2016-11-04

The current catalogue of the human proteome is not yet complete, as experimental proteomics evidence is still elusive for a group of proteins known as the missing proteins. The Human Proteome Project (HPP) has been successfully using technology and bioinformatic resources to improve the characterization of such challenging proteins. In this manuscript, we propose a pipeline starting with the mining of the PRIDE database to select a group of data sets potentially enriched in missing proteins that are subsequently analyzed for protein identification with a method based on the statistical analysis of proteotypic peptides. Spermatozoa and the HEK293 cell line were found to be a promising source of missing proteins and clearly merit further attention in future studies. After the analysis of the selected samples, we found 342 PSMs, suggesting the presence of 97 missing proteins in human spermatozoa or the HEK293 cell line, while only 36 missing proteins were potentially detected in the retina, frontal cortex, aorta thoracica, or placenta. The functional analysis of the missing proteins detected confirmed their tissue specificity, and the validation of a selected set of peptides using targeted proteomics (SRM/MRM assays) further supports the utility of the proposed pipeline. As illustrative examples, DNAH3 and TEPP in spermatozoa, and UNCX and ATAD3C in HEK293 cells were some of the more robust and remarkable identifications in this study. We provide evidence indicating the relevance to carefully analyze the ever-increasing MS/MS data available from PRIDE and other repositories as sources for missing proteins detection in specific biological matrices as revealed for HEK293 cells.

Detection of Missing Proteins Using the PRIDE Database as a Source of Mass Spectrometry Evidence

PubMed Central

2016-01-01

The current catalogue of the human proteome is not yet complete, as experimental proteomics evidence is still elusive for a group of proteins known as the missing proteins. The Human Proteome Project (HPP) has been successfully using technology and bioinformatic resources to improve the characterization of such challenging proteins. In this manuscript, we propose a pipeline starting with the mining of the PRIDE database to select a group of data sets potentially enriched in missing proteins that are subsequently analyzed for protein identification with a method based on the statistical analysis of proteotypic peptides. Spermatozoa and the HEK293 cell line were found to be a promising source of missing proteins and clearly merit further attention in future studies. After the analysis of the selected samples, we found 342 PSMs, suggesting the presence of 97 missing proteins in human spermatozoa or the HEK293 cell line, while only 36 missing proteins were potentially detected in the retina, frontal cortex, aorta thoracica, or placenta. The functional analysis of the missing proteins detected confirmed their tissue specificity, and the validation of a selected set of peptides using targeted proteomics (SRM/MRM assays) further supports the utility of the proposed pipeline. As illustrative examples, DNAH3 and TEPP in spermatozoa, and UNCX and ATAD3C in HEK293 cells were some of the more robust and remarkable identifications in this study. We provide evidence indicating the relevance to carefully analyze the ever-increasing MS/MS data available from PRIDE and other repositories as sources for missing proteins detection in specific biological matrices as revealed for HEK293 cells. PMID:27581094

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.

Transcriptomic analysis of Arabidopsis developing stems: a close-up on cell wall genes

PubMed Central

Minic, Zoran; Jamet, Elisabeth; San-Clemente, Hélène; Pelletier, Sandra; Renou, Jean-Pierre; Rihouey, Christophe; Okinyo, Denis PO; Proux, Caroline; Lerouge, Patrice; Jouanin, Lise

2009-01-01

Background Different strategies (genetics, biochemistry, and proteomics) can be used to study proteins involved in cell biogenesis. The availability of the complete sequences of several plant genomes allowed the development of transcriptomic studies. Although the expression patterns of some Arabidopsis thaliana genes involved in cell wall biogenesis were identified at different physiological stages, detailed microarray analysis of plant cell wall genes has not been performed on any plant tissues. Using transcriptomic and bioinformatic tools, we studied the regulation of cell wall genes in Arabidopsis stems, i.e. genes encoding proteins involved in cell wall biogenesis and genes encoding secreted proteins. Results Transcriptomic analyses of stems were performed at three different developmental stages, i.e., young stems, intermediate stage, and mature stems. Many genes involved in the synthesis of cell wall components such as polysaccharides and monolignols were identified. A total of 345 genes encoding predicted secreted proteins with moderate or high level of transcripts were analyzed in details. The encoded proteins were distributed into 8 classes, based on the presence of predicted functional domains. Proteins acting on carbohydrates and proteins of unknown function constituted the two most abundant classes. Other proteins were proteases, oxido-reductases, proteins with interacting domains, proteins involved in signalling, and structural proteins. Particularly high levels of expression were established for genes encoding pectin methylesterases, germin-like proteins, arabinogalactan proteins, fasciclin-like arabinogalactan proteins, and structural proteins. Finally, the results of this transcriptomic analyses were compared with those obtained through a cell wall proteomic analysis from the same material. Only a small proportion of genes identified by previous proteomic analyses were identified by transcriptomics. Conversely, only a few proteins encoded by genes having moderate or high level of transcripts were identified by proteomics. Conclusion Analysis of the genes predicted to encode cell wall proteins revealed that about 345 genes had moderate or high levels of transcripts. Among them, we identified many new genes possibly involved in cell wall biogenesis. The discrepancies observed between results of this transcriptomic study and a previous proteomic study on the same material revealed post-transcriptional mechanisms of regulation of expression of genes encoding cell wall proteins. PMID:19149885

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

PubMed

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

2017-04-01

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

Proteomic profiling of epileptogenesis in a rat model: Focus on cell stress, extracellular matrix and angiogenesis.

PubMed

Keck, Michael; van Dijk, Roelof Maarten; Deeg, Cornelia A; Kistler, Katharina; Walker, Andreas; von Rüden, Eva-Lotta; Russmann, Vera; Hauck, Stefanie M; Potschka, Heidrun

2018-04-01

Information about epileptogenesis-associated changes in protein expression patterns is of particular interest for future selection of target and biomarker candidates. Bioinformatic analysis of proteomic data sets can increase our knowledge about molecular alterations characterizing the different phases of epilepsy development following an initial epileptogenic insult. Here, we report findings from a focused analysis of proteomic data obtained for the hippocampus and parahippocampal cortex samples collected during the early post-insult phase, latency phase, and chronic phase of a rat model of epileptogenesis. The study focused on proteins functionally associated with cell stress, cell death, extracellular matrix (ECM) remodeling, cell-ECM interaction, cell-cell interaction, angiogenesis, and blood-brain barrier function. The analysis revealed prominent pathway enrichment providing information about the complex expression alterations of the respective protein groups. In the hippocampus, the number of differentially expressed proteins declined over time during the course of epileptogenesis. In contrast, a peak in the regulation of proteins linked with cell stress and death as well as ECM and cell-cell interaction became evident at later phases during epileptogenesis in the parahippocampal cortex. The data sets provide valuable information about the time course of protein expression patterns during epileptogenesis for a series of proteins. Moreover, the findings provide comprehensive novel information about expression alterations of proteins that have not been discussed yet in the context of epileptogenesis. These for instance include different members of the lamin protein family as well as the fermitin family member 2 (FERMT2). Induction of FERMT2 and other selected proteins, CD18 (ITGB2), CD44 and Nucleolin were confirmed by immunohistochemistry. Taken together, focused bioinformatic analysis of the proteomic data sets completes our knowledge about molecular alterations linked with cell death and cellular plasticity during epileptogenesis. The analysis provided can guide future selection of target and biomarker candidates. Copyright © 2018 Elsevier Inc. All rights reserved.

Proteome-wide Adaptations of Mouse Skeletal Muscles during a Full Month in Space.

PubMed

Tascher, Georg; Brioche, Thomas; Maes, Pauline; Chopard, Angèle; O'Gorman, Donal; Gauquelin-Koch, Guillemette; Blanc, Stéphane; Bertile, Fabrice

2017-07-07

The safety of space flight is challenged by a severe loss of skeletal muscle mass, strength, and endurance that may compromise the health and performance of astronauts. The molecular mechanisms underpinning muscle atrophy and decreased performance have been studied mostly after short duration flights and are still not fully elucidated. By deciphering the muscle proteome changes elicited in mice after a full month aboard the BION-M1 biosatellite, we observed that the antigravity soleus incurred the greatest changes compared with locomotor muscles. Proteomics data notably suggested mitochondrial dysfunction, metabolic and fiber type switching toward glycolytic type II fibers, structural alterations, and calcium signaling-related defects to be the main causes for decreased muscle performance in flown mice. Alterations of the protein balance, mTOR pathway, myogenesis, and apoptosis were expected to contribute to muscle atrophy. Moreover, several signs reflecting alteration of telomere maintenance, oxidative stress, and insulin resistance were found as possible additional deleterious effects. Finally, 8 days of recovery post flight were not sufficient to restore completely flight-induced changes. Thus in-depth proteomics analysis unraveled the complex and multifactorial remodeling of skeletal muscle structure and function during long-term space flight, which should help define combined sets of countermeasures before, during, and after the flight.

The Proteomics Stock Market Project. A Cross-Disciplinary Collaboration in Biochemistry and Business Education

NASA Astrophysics Data System (ADS)

Keller, Heath; Cox, James R.

2004-04-01

Students taking courses in different disciplines can work together to add unique elements to their educational experience. A model for this type of pedagogical approach has been established in the Proteomics Stock Market Project, a collaborative effort between instructors and students in the Department of Chemistry and Department of Management, Marketing, and Business Administration at Murray State University. Stage I involved biochemistry students investigating the topic of proteomics and choosing companies for potential investment based only on scientific investigation. Marketing and management students completed Stage II and provided an investment analysis on the companies selected in Stage I. In Stage III, the biochemistry students focused on a particular company and investigated a protein-based therapeutic product. Blackboard software was utilized in each stage of the project to facilitate the exchange of information and electronic documents. This project was designed to give biochemistry students an appreciation for the emerging field of proteomics and the marketing and management students a flavor for real-world applications of business principles. During the project, students were exposed to ideas and concepts not typically covered in their courses. With this involvement, the students had the opportunity to gain a broader perspective of course content compared to a more traditional curriculum.

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

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

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

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

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.

Snake venomics of Lachesis muta rhombeata and genus-wide antivenomics assessment of the paraspecific immunoreactivity of two antivenoms evidence the high compositional and immunological conservation across Lachesis.

PubMed

Pla, Davinia; Sanz, Libia; Molina-Sánchez, Pedro; Zorita, Virginia; Madrigal, Marvin; Flores-Díaz, Marietta; Alape-Girón, Alberto; Núñez, Vitelbina; Andrés, Vicente; Gutiérrez, José María; Calvete, Juan J

2013-08-26

We report the proteomic analysis of the Atlantic bushmaster, Lachesis muta rhombeata, from Brazil. Along with previous characterization of the venom proteomes of L. stenophrys (Costa Rica), L. melanocephala (Costa Rica), L. acrochorda (Colombia), and L. muta muta (Bolivia), the present study provides the first overview of the composition and distribution of venom proteins across this wide-ranging genus, and highlights the remarkable similar compositional and pharmacological profiles across Lachesis venoms. The paraspecificity of two antivenoms, produced at Instituto Vital Brazil (Brazil) and Instituto Clodomiro Picado (Costa Rica) using different conspecific taxa in the immunization mixtures, was assessed using genus-wide comparative antivenomics. This study confirms that the proteomic similarity among Lachesis sp. venoms is mirrored in their high immunological conservation across the genus. The clinical and therapeutic consequences of genus-wide venomics and antivenomics investigations of Lachesis venoms are discussed. The proteomics characterization of L. m. rhombeata venom completes the overview of Lachesis venom proteomes and confirms the remarkable toxin profile conservation across the five clades of this wide-ranging genus. Genus-wide antivenomics showed that two antivenoms, produced against L. stenophrys or L. m. rhombeata, exhibit paraspecificity towards all other congeneric venoms. Our venomics study shows that, despite the broad geographic distribution of the genus, monospecific antivenoms may achieve clinical coverage for any Lachesis sp. envenoming. Copyright © 2013 Elsevier B.V. All rights reserved.

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.

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

Cancer.gov

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

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...

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.

Simple preparation of plant epidermal tissue for laser microdissection and downstream quantitative proteome and carbohydrate analysis

PubMed Central

Falter, Christian; Ellinger, Dorothea; von Hülsen, Behrend; Heim, René; Voigt, Christian A.

2015-01-01

The outwardly directed cell wall and associated plasma membrane of epidermal cells represent the first layers of plant defense against intruding pathogens. Cell wall modifications and the formation of defense structures at sites of attempted pathogen penetration are decisive for plant defense. A precise isolation of these stress-induced structures would allow a specific analysis of regulatory mechanism and cell wall adaption. However, methods for large-scale epidermal tissue preparation from the model plant Arabidopsis thaliana, which would allow proteome and cell wall analysis of complete, laser-microdissected epidermal defense structures, have not been provided. We developed the adhesive tape – liquid cover glass technique (ACT) for simple leaf epidermis preparation from A. thaliana, which is also applicable on grass leaves. This method is compatible with subsequent staining techniques to visualize stress-related cell wall structures, which were precisely isolated from the epidermal tissue layer by laser microdissection (LM) coupled to laser pressure catapulting. We successfully demonstrated that these specific epidermal tissue samples could be used for quantitative downstream proteome and cell wall analysis. The development of the ACT for simple leaf epidermis preparation and the compatibility to LM and downstream quantitative analysis opens new possibilities in the precise examination of stress- and pathogen-related cell wall structures in epidermal cells. Because the developed tissue processing is also applicable on A. thaliana, well-established, model pathosystems that include the interaction with powdery mildews can be studied to determine principal regulatory mechanisms in plant–microbe interaction with their potential outreach into crop breeding. PMID:25870605

Simple preparation of plant epidermal tissue for laser microdissection and downstream quantitative proteome and carbohydrate analysis.

PubMed

Falter, Christian; Ellinger, Dorothea; von Hülsen, Behrend; Heim, René; Voigt, Christian A

2015-01-01

The outwardly directed cell wall and associated plasma membrane of epidermal cells represent the first layers of plant defense against intruding pathogens. Cell wall modifications and the formation of defense structures at sites of attempted pathogen penetration are decisive for plant defense. A precise isolation of these stress-induced structures would allow a specific analysis of regulatory mechanism and cell wall adaption. However, methods for large-scale epidermal tissue preparation from the model plant Arabidopsis thaliana, which would allow proteome and cell wall analysis of complete, laser-microdissected epidermal defense structures, have not been provided. We developed the adhesive tape - liquid cover glass technique (ACT) for simple leaf epidermis preparation from A. thaliana, which is also applicable on grass leaves. This method is compatible with subsequent staining techniques to visualize stress-related cell wall structures, which were precisely isolated from the epidermal tissue layer by laser microdissection (LM) coupled to laser pressure catapulting. We successfully demonstrated that these specific epidermal tissue samples could be used for quantitative downstream proteome and cell wall analysis. The development of the ACT for simple leaf epidermis preparation and the compatibility to LM and downstream quantitative analysis opens new possibilities in the precise examination of stress- and pathogen-related cell wall structures in epidermal cells. Because the developed tissue processing is also applicable on A. thaliana, well-established, model pathosystems that include the interaction with powdery mildews can be studied to determine principal regulatory mechanisms in plant-microbe interaction with their potential outreach into crop breeding.

Variation among Staphylococcus aureus membrane vesicle proteomes affects cytotoxicity of host cells.

PubMed

Jeon, Hyejin; Oh, Man Hwan; Jun, So Hyun; Kim, Seung Il; Choi, Chi Won; Kwon, Hyo Il; Na, Seok Hyeon; Kim, Yoo Jeong; Nicholas, Asiimwe; Selasi, Gati Noble; Lee, Je Chul

2016-04-01

Staphylococcus aureus secretes membrane-derived vesicles (MVs), which can deliver virulence factors to host cells and induce cytopathology. However, the cytopathology of host cells induced by MVs derived from different S. aureus strains has not yet been characterized. In the present study, the cytotoxic activity of MVs from different S. aureus isolates on host cells was compared and the proteomes of S. aureus MVs were analyzed. The MVs purified from S. aureus M060 isolated from a patient with staphylococcal scalded skin syndrome showed higher cytotoxic activity toward host cells than that shown by MVs from three other clinical S. aureus isolates. S. aureus M060 MVs induced HEp-2 cell apoptosis in a dose-dependent manner, but the cytotoxic activity of MVs was completely abolished by treatment with proteinase K. In a proteomic analysis, the MVs from three S. aureus isolates not only carry 25 common proteins, but also carry ≥60 strain-specific proteins. All S. aureus MVs contained δ-hemolysin (Hld), γ-hemolysin, leukocidin D, and exfoliative toxin C, but exfoliative toxin A (ETA) was specifically identified in S. aureus M060 MVs. ETA was delivered to HEp-2 cells via S. aureus MVs. Both rETA and rHld induced cytotoxicity in HEp-2 cells. In conclusion, MVs from clinical S. aureus isolates differ with respect to cytotoxic activity in host cells, and these differences may result from differences in the MV proteomes. Further proteogenomic analysis or mutagenesis of specific genes is necessary to identify cytotoxic factors in S. aureus MVs. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Proteomic characterization and comparison of venoms from two elapid snakes (Bungarus multicinctus and Naja atra) from China.

PubMed

Shan, Lin-Lin; Gao, Jian-Fang; Zhang, Yan-Xia; Shen, Shan-Shan; He, Ying; Wang, Jin; Ma, Xiao-Mei; Ji, Xiang

2016-04-14

Bungarus multicinctus (many-banded krait) and Naja atra (Chinese cobra) are widely distributed and medically important venomous snakes in China; however, their venom proteomic profiles have not been fully compared. Here, we fractionated crude venoms and analyzed them using a combination of proteomic techniques. Three-finger toxins (3-FTx) and phospholipase A2 (PLA2) were most abundant in both species, respectively accounting for 32.6% and 66.4% of total B. multicinctus venom, and 84.3% and 12.2% of total N. atra venom. Venoms from these two species contained one common protein family and six less abundant species-specific protein families. The proteomic profiles of B. multicinctus and N. atra venoms and analysis of toxicological activity in mice suggested that 3-FTx and PLA2 are the major contributors to clinical symptoms caused by envenomation. The venoms differed in enzymatic activity, likely the result of inter-specific variation in the amount of related venom components. Antivenomics assessment revealed that a small number of venom components (3-FTxs and PLA2s in B. multicinctus, and 3-FTxs in N. atra) could not be immunocaptured completely, suggesting that we should pay attention to enhancing the immune response of these components in designing commercial antivenoms for B. multicinctus and N. atra. The proteomic profiles of venoms from two medically important snake species - B. multicinctus and N. atra - have been explored. Quantitative and qualitative differences are evident in both venoms when proteomic profiles and transcriptomic results are compared; this is a reminder that combined approaches are needed to explore the precise composition of snake venom. Two protein families (3-FTx and PLA2) of high abundance in these snake venoms are major players in the biochemical and pharmacological effects of envenomation. Elucidation of the proteomic profiles of these snake venoms is helpful in understanding composition-function relationships and will facilitate the clinical application of antivenoms. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Proteomics analysis of latex from Hevea brasiliensis (clone RRIM 600).

PubMed

Habib, Mohd Afiq Hazlami; Yuen, Gan Chee; Othman, Fazilah; Zainudin, Nurul Nabilah; Latiff, Aishah Abdul; Ismail, Mohd Nazri

2017-04-01

The natural rubber latex extracted from the bark of Hevea brasiliensis plays various important roles in today's modern society. Following ultracentrifugation, the latex can be separated into 3 layers: C-serum, lutoids, and rubber particles. Previous studies have shown that a large number of proteins are present in these 3 layers. However, a complete proteome for this important plant is still unavailable. Protein sequences have been recently translated from the completed draft genome database of H. brasiliensis, leading to the creation of annotated protein databases of the following H. brasiliensis biosynthetic pathways: photosynthesis, latex allergens, rubberwood formation, latex biosynthesis, and disease resistance. This research was conducted to identify the proteins contained within the latex by way of de novo sequencing from mass spectral data obtained from the 3 layers of the latex. Peptides from these proteins were fragmented using collision-induced dissociation, higher-energy collisional dissociation, and electron-transfer dissociation activation methods. A large percentage of proteins from the biosynthetic pathways (63% to 100%) were successfully identified. In addition, a total of 1839 unique proteins were identified from the whole translated draft genome database (AnnHBM).

Proteomic contributions to our understanding of vaccine and immune responses

PubMed Central

Galassie, Allison C.; Link, Andrew J.

2015-01-01

Vaccines are one of the greatest public health successes; yet, due to the empirical nature of vaccine design, we have an incomplete understanding of how the genes and proteins induced by vaccines contribute to the development of both protective innate and adaptive immune responses. While the advent of genomics has enabled new vaccine development and facilitated understanding of the immune response, proteomics identifies potentially new vaccine antigens with increasing speed and sensitivity. In addition, as proteomics is complementary to transcriptomic approaches, a combination of both approaches provides a more comprehensive view of the immune response after vaccination via systems vaccinology. This review details the advances that proteomic strategies have made in vaccine development and reviews how proteomics contributes to the development of a more complete understanding of human vaccines and immune responses. PMID:26172619

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

Effects of Hypertension and Exercise on Cardiac Proteome Remodelling

PubMed Central

Petriz, Bernardo A.; Franco, Octavio L.

2014-01-01

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

Hormone regulation of rhizome development in tall fescue (Festuca arundinacea) associated with proteomic changes controlling respiratory and amino acid metabolism.

PubMed

Ma, Xiqing; Xu, Qian; Meyer, William A; Huang, Bingru

2016-09-01

Rhizomes are underground stems with meristematic tissues capable of generating shoots and roots. However, mechanisms controlling rhizome formation and growth are yet to be completely understood. The objectives of this study were to investigate whether rhizome development could be regulated by cytokinins (CKs) and gibberellic acids (GAs), and determine underlying mechanisms of regulation of rhizome formation and growth of tall fescue (Festuca arundinacea) by a CK or GA through proteomic and transcript analysis. A rhizomatous genotype of tall fescue ('BR') plants were treated with 6-benzylaminopurine (BAP, a synthetic cytokinin) or GA3 in hydroponic culture in growth chambers. Furthermore, comparative proteomic analysis of two-dimensional electrophoresis and mass spectrometry were performed to investigate proteins and associated metabolic pathways imparting increased rhizome number by BAP and rhizome elongation by GA3 KEY RESULTS: BAP stimulated rhizome formation while GA3 promoted rhizome elongation. Proteomic analysis identified 76 differentially expressed proteins (DEPs) due to BAP treatment and 37 DEPs due to GA3 treatment. Cytokinin-related genes and cell division-related genes were upregulated in the rhizome node by BAP and gibberellin-related and cell growth-related genes in the rhizome by GA3 CONCLUSIONS: Most of the BAP- or GA-responsive DEPs were involved in respiratory metabolism and amino acid metabolism. Transcription analysis demonstrated that genes involved in hormone metabolism, signalling pathways, cell division and cell-wall loosening were upregulated by BAP or GA3 The CK and GA promoted rhizome formation and growth, respectively, by activating metabolic pathways that supply energy and amino acids to support cell division and expansion during rhizome initiation and elongation in tall fescue. © The Author 2016. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2012-08-01

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

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

PubMed Central

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

2012-01-01

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

FunRich proteomics software analysis, let the fun begin!

PubMed

Benito-Martin, Alberto; Peinado, Héctor

2015-08-01

Protein MS analysis is the preferred method for unbiased protein identification. It is normally applied to a large number of both small-scale and high-throughput studies. However, user-friendly computational tools for protein analysis are still needed. In this issue, Mathivanan and colleagues (Proteomics 2015, 15, 2597-2601) report the development of FunRich software, an open-access software that facilitates the analysis of proteomics data, providing tools for functional enrichment and interaction network analysis of genes and proteins. FunRich is a reinterpretation of proteomic software, a standalone tool combining ease of use with customizable databases, free access, and graphical representations. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

ATAQS: A computational software tool for high throughput transition optimization and validation for selected reaction monitoring mass spectrometry

PubMed Central

2011-01-01

Background Since its inception, proteomics has essentially operated in a discovery mode with the goal of identifying and quantifying the maximal number of proteins in a sample. Increasingly, proteomic measurements are also supporting hypothesis-driven studies, in which a predetermined set of proteins is consistently detected and quantified in multiple samples. Selected reaction monitoring (SRM) is a targeted mass spectrometric technique that supports the detection and quantification of specific proteins in complex samples at high sensitivity and reproducibility. Here, we describe ATAQS, an integrated software platform that supports all stages of targeted, SRM-based proteomics experiments including target selection, transition optimization and post acquisition data analysis. This software will significantly facilitate the use of targeted proteomic techniques and contribute to the generation of highly sensitive, reproducible and complete datasets that are particularly critical for the discovery and validation of targets in hypothesis-driven studies in systems biology. Result We introduce a new open source software pipeline, ATAQS (Automated and Targeted Analysis with Quantitative SRM), which consists of a number of modules that collectively support the SRM assay development workflow for targeted proteomic experiments (project management and generation of protein, peptide and transitions and the validation of peptide detection by SRM). ATAQS provides a flexible pipeline for end-users by allowing the workflow to start or end at any point of the pipeline, and for computational biologists, by enabling the easy extension of java algorithm classes for their own algorithm plug-in or connection via an external web site. This integrated system supports all steps in a SRM-based experiment and provides a user-friendly GUI that can be run by any operating system that allows the installation of the Mozilla Firefox web browser. Conclusions Targeted proteomics via SRM is a powerful new technique that enables the reproducible and accurate identification and quantification of sets of proteins of interest. ATAQS is the first open-source software that supports all steps of the targeted proteomics workflow. ATAQS also provides software API (Application Program Interface) documentation that enables the addition of new algorithms to each of the workflow steps. The software, installation guide and sample dataset can be found in http://tools.proteomecenter.org/ATAQS/ATAQS.html PMID:21414234

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.

Detailed proteomic analysis on DM: insight into its hypoallergenicity.

PubMed

Bertino, Enrico; Gastaldi, Daniela; Monti, Giovanna; Baro, Cristina; Fortunato, Donatella; Perono Garoffo, Lorenza; Coscia, Alessandra; Fabris, Claudio; Mussap, Michele; Conti, Amedeo

2010-01-01

Successful therapy in cow milk (CM) protein allergy rests upon completely eliminating CM proteins from the child's diet: it is thus necessary to provide a replacement food. Donkey milk (DM) has recently aroused scientific and clinical interest, above all among paediatric allergologists. A deeper knowledge of proteins in DM is necessary to evaluate the immunological and physiological properties of this natural substitute for cow's milk. The paper offers a detailed comparative analysis among the protein fractions of DM, CM and human milk, following an extensive proteomic study of the casein and whey proteins of DM performed by narrow pH range 2-DE. The detailed protein composition and structural features reported in this study provide insight into the molecular reasons for the hypoallergenicity of DM. Whole DM might constitute a valid substitute of CM in feeding children with CM protein allergy and it might also constitute the basis for formulas suitable for allergic subjects in the first year of life.

First evidence of a membrane-bound, tyramine and beta-phenylethylamine producing, tyrosine decarboxylase in Enterococcus faecalis: a two-dimensional electrophoresis proteomic study.

PubMed

Pessione, Enrica; Pessione, Alessandro; Lamberti, Cristina; Coïsson, Daniel Jean; Riedel, Kathrin; Mazzoli, Roberto; Bonetta, Silvia; Eberl, Leo; Giunta, Carlo

2009-05-01

The soluble and membrane proteome of a tyramine producing Enterococcus faecalis, isolated from an Italian goat cheese, was investigated. A detailed analysis revealed that this strain also produces small amounts of beta-phenylethylamine. Kinetics of tyramine and beta-phenylethylamine accumulation, evaluated in tyrosine plus phenylalanine-enriched cultures (stimulated condition), suggest that the same enzyme, the tyrosine decarboxylase (TDC), catalyzes both tyrosine and phenylalanine decarboxylation: tyrosine was recognized as the first substrate and completely converted into tyramine (100% yield) while phenylalanine was decarboxylated to beta-phenylethylamine (10% yield) only when tyrosine was completely depleted. The presence of an aspecific aromatic amino acid decarboxylase is a common feature in eukaryotes, but in bacteria only indirect evidences of a phenylalanine decarboxylating TDC have been presented so far. Comparative proteomic investigations, performed by 2-DE and MALDI-TOF/TOF MS, on bacteria grown in conditions stimulating tyramine and beta-phenylethylamine biosynthesis and in control conditions revealed 49 differentially expressed proteins. Except for aromatic amino acid biosynthetic enzymes, no significant down-regulation of the central metabolic pathways was observed in stimulated conditions, suggesting that tyrosine decarboxylation does not compete with the other energy-supplying routes. The most interesting finding is a membrane-bound TDC highly over-expressed during amine production. This is the first evidence of a true membrane-bound TDC, longly suspected in bacteria on the basis of the gene sequence.

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

PubMed

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

2017-03-03

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

Activity-based protein profiling: from enzyme chemistry to proteomic chemistry.

PubMed

Cravatt, Benjamin F; Wright, Aaron T; Kozarich, John W

2008-01-01

Genome sequencing projects have provided researchers with a complete inventory of the predicted proteins produced by eukaryotic and prokaryotic organisms. Assignment of functions to these proteins represents one of the principal challenges for the field of proteomics. Activity-based protein profiling (ABPP) has emerged as a powerful chemical proteomic strategy to characterize enzyme function directly in native biological systems on a global scale. Here, we review the basic technology of ABPP, the enzyme classes addressable by this method, and the biological discoveries attributable to its application.

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

PubMed Central

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

2013-01-01

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

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.

Concurrent Label-Free Mass Spectrometric Analysis of Dystrophin Isoform Dp427 and the Myofibrosis Marker Collagen in Crude Extracts from mdx-4cv Skeletal Muscles

PubMed Central

Murphy, Sandra; Zweyer, Margit; Mundegar, Rustam R.; Henry, Michael; Meleady, Paula; Swandulla, Dieter; Ohlendieck, Kay

2015-01-01

The full-length dystrophin protein isoform of 427 kDa (Dp427), the absence of which represents the principal abnormality in X-linked muscular dystrophy, is difficult to identify and characterize by routine proteomic screening approaches of crude tissue extracts. This is probably related to its large molecular size, its close association with the sarcolemmal membrane, and its existence within a heterogeneous glycoprotein complex. Here, we used a careful extraction procedure to isolate the total protein repertoire from normal versus dystrophic mdx-4cv skeletal muscles, in conjunction with label-free mass spectrometry, and successfully identified Dp427 by proteomic means. In contrast to a considerable number of previous comparative studies of the total skeletal muscle proteome, using whole tissue proteomics we show here for the first time that the reduced expression of this membrane cytoskeletal protein is the most significant alteration in dystrophinopathy. This agrees with the pathobiochemical concept that the almost complete absence of dystrophin is the main defect in Duchenne muscular dystrophy and that the mdx-4cv mouse model of dystrophinopathy exhibits only very few revertant fibers. Significant increases in collagens and associated fibrotic marker proteins, such as fibronectin, biglycan, asporin, decorin, prolargin, mimecan, and lumican were identified in dystrophin-deficient muscles. The up-regulation of collagen in mdx-4cv muscles was confirmed by immunofluorescence microscopy and immunoblotting. Thus, this is the first mass spectrometric study of crude tissue extracts that puts the proteomic identification of dystrophin in its proper pathophysiological context. PMID:28248273

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.

PSSMSearch: a server for modeling, visualization, proteome-wide discovery and annotation of protein motif specificity determinants.

PubMed

Krystkowiak, Izabella; Manguy, Jean; Davey, Norman E

2018-06-05

There is a pressing need for in silico tools that can aid in the identification of the complete repertoire of protein binding (SLiMs, MoRFs, miniMotifs) and modification (moiety attachment/removal, isomerization, cleavage) motifs. We have created PSSMSearch, an interactive web-based tool for rapid statistical modeling, visualization, discovery and annotation of protein motif specificity determinants to discover novel motifs in a proteome-wide manner. PSSMSearch analyses proteomes for regions with significant similarity to a motif specificity determinant model built from a set of aligned motif-containing peptides. Multiple scoring methods are available to build a position-specific scoring matrix (PSSM) describing the motif specificity determinant model. This model can then be modified by a user to add prior knowledge of specificity determinants through an interactive PSSM heatmap. PSSMSearch includes a statistical framework to calculate the significance of specificity determinant model matches against a proteome of interest. PSSMSearch also includes the SLiMSearch framework's annotation, motif functional analysis and filtering tools to highlight relevant discriminatory information. Additional tools to annotate statistically significant shared keywords and GO terms, or experimental evidence of interaction with a motif-recognizing protein have been added. Finally, PSSM-based conservation metrics have been created for taxonomic range analyses. The PSSMSearch web server is available at http://slim.ucd.ie/pssmsearch/.

Unraveling incompatibility between wheat and the fungal pathogen Zymoseptoria tritici through apoplastic proteomics.

PubMed

Yang, Fen; Li, Wanshun; Derbyshire, Mark; Larsen, Martin R; Rudd, Jason J; Palmisano, Giuseppe

2015-05-08

Hemibiotrophic fungal pathogen Zymoseptoria tritici causes severe foliar disease in wheat. However, current knowledge of molecular mechanisms involved in plant resistance to Z. tritici and Z. tritici virulence factors is far from being complete. The present work investigated the proteome of leaf apoplastic fluid with emphasis on both host wheat and Z. tritici during the compatible and incompatible interactions. The proteomics analysis revealed rapid host responses to the biotrophic growth, including enhanced carbohydrate metabolism, apoplastic defenses and stress, and cell wall reinforcement, might contribute to resistance. Compatibility between the host and the pathogen was associated with inactivated plant apoplastic responses as well as fungal defenses to oxidative stress and perturbation of plant cell wall during the initial biotrophic stage, followed by the strong induction of plant defenses during the necrotrophic stage. To study the role of anti-oxidative stress in Z. tritici pathogenicity in depth, a YAP1 transcription factor regulating antioxidant expression was deleted and showed the contribution to anti-oxidative stress in Z. tritici, but was not required for pathogenicity. This result suggests the functional redundancy of antioxidants in the fungus. The data demonstrate that incompatibility is probably resulted from the proteome-level activation of host apoplastic defenses as well as fungal incapability to adapt to stress and interfere with host cell at the biotrophic stage of the interaction.

Encapsulated in silica: genome, proteome and physiology of the thermophilic bacterium Anoxybacillus flavithermus WK1

PubMed Central

Saw, Jimmy H; Mountain, Bruce W; Feng, Lu; Omelchenko, Marina V; Hou, Shaobin; Saito, Jennifer A; Stott, Matthew B; Li, Dan; Zhao, Guang; Wu, Junli; Galperin, Michael Y; Koonin, Eugene V; Makarova, Kira S; Wolf, Yuri I; Rigden, Daniel J; Dunfield, Peter F; Wang, Lei; Alam, Maqsudul

2008-01-01

Background Gram-positive bacteria of the genus Anoxybacillus have been found in diverse thermophilic habitats, such as geothermal hot springs and manure, and in processed foods such as gelatin and milk powder. Anoxybacillus flavithermus is a facultatively anaerobic bacterium found in super-saturated silica solutions and in opaline silica sinter. The ability of A. flavithermus to grow in super-saturated silica solutions makes it an ideal subject to study the processes of sinter formation, which might be similar to the biomineralization processes that occurred at the dawn of life. Results We report here the complete genome sequence of A. flavithermus strain WK1, isolated from the waste water drain at the Wairakei geothermal power station in New Zealand. It consists of a single chromosome of 2,846,746 base pairs and is predicted to encode 2,863 proteins. In silico genome analysis identified several enzymes that could be involved in silica adaptation and biofilm formation, and their predicted functions were experimentally validated in vitro. Proteomic analysis confirmed the regulation of biofilm-related proteins and crucial enzymes for the synthesis of long-chain polyamines as constituents of silica nanospheres. Conclusions Microbial fossils preserved in silica and silica sinters are excellent objects for studying ancient life, a new paleobiological frontier. An integrated analysis of the A. flavithermus genome and proteome provides the first glimpse of metabolic adaptation during silicification and sinter formation. Comparative genome analysis suggests an extensive gene loss in the Anoxybacillus/Geobacillus branch after its divergence from other bacilli. PMID:19014707

Encapsulated in silica: genome, proteome and physiology of the thermophilic bacterium Anoxybacillus flavithermus

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

Saw, Jimmy H; Mountain, Bruce W; Feng, Lu

Gram-positive bacteria of the genus Anoxybacillus have been found in diverse thermophilic habitats, such as geothermal hot springs and manure, and in processed foods such as gelatin and milk powder. Anoxybacillus flavithermus is a facultatively anaerobic bacterium found in super-saturated silica solutions and in opaline silica sinter. The ability of A. flavithermus to grow in super-saturated silica solutions makes it an ideal subject to study the processes of sinter formation, which might be similar to the biomineralization processes that occurred at the dawn of life. We report here the complete genome sequence of A. flavithermus strain WK1, isolated from themore » waste water drain at the Wairakei geothermal power station in New Zealand. It consists of a single chromosome of 2,846,746 base pairs and is predicted to encode 2,863 proteins. In silico genome analysis identified several enzymes that could be involved in silica adaptation and biofilm formation, and their predicted functions were experimentally validated in vitro. Proteomic analysis confirmed the regulation of biofilm-related proteins and crucial enzymes for the synthesis of long-chain polyamines as constituents of silica nanospheres. Microbial fossils preserved in silica and silica sinters are excellent objects for studying ancient life, a new paleobiological frontier. An integrated analysis of the A. flavithermus genome and proteome provides the first glimpse of metabolic adaptation during silicification and sinter formation. Comparative genome analysis suggests an extensive gene loss in the Anoxybacillus/Geobacillus branch after its divergence from other bacilli.« less

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

[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.

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.

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.

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.

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

PubMed

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

2018-04-06

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

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.

Comparative genomic, proteomic and exoproteomic analyses of three Pseudomonas strains reveals novel insights into the phosphorus scavenging capabilities of soil bacteria

PubMed Central

Murphy, Andrew R. J.; Scanlan, David J.; Bending, Gary D.; Jones, Alexandra M. E.; Moore, Jonathan D.; Goodall, Andrew; Hammond, John P.; Wellington, Elizabeth M. H.

2016-01-01

Summary Bacteria that inhabit the rhizosphere of agricultural crops can have a beneficial effect on crop growth. One such mechanism is the microbial‐driven solubilization and remineralization of complex forms of phosphorus (P). It is known that bacteria secrete various phosphatases in response to low P conditions. However, our understanding of their global proteomic response to P stress is limited. Here, exoproteomic analysis of Pseudomonas putida BIRD‐1 (BIRD‐1), Pseudomonas fluorescens SBW25 and Pseudomonas stutzeri DSM4166 was performed in unison with whole‐cell proteomic analysis of BIRD‐1 grown under phosphate (Pi) replete and Pi deplete conditions. Comparative exoproteomics revealed marked heterogeneity in the exoproteomes of each Pseudomonas strain in response to Pi depletion. In addition to well‐characterized members of the PHO regulon such as alkaline phosphatases, several proteins, previously not associated with the response to Pi depletion, were also identified. These included putative nucleases, phosphotriesterases, putative phosphonate transporters and outer membrane proteins. Moreover, in BIRD‐1, mutagenesis of the master regulator, phoBR, led us to confirm the addition of several novel PHO‐dependent proteins. Our data expands knowledge of the Pseudomonas PHO regulon, including species that are frequently used as bioinoculants, opening up the potential for more efficient and complete use of soil complexed P. PMID:27233093

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.

Molecular phenotype of zebrafish ovarian follicle by serial analysis of gene expression and proteomic profiling, and comparison with the transcriptomes of other animals

PubMed Central

Knoll-Gellida, Anja; André, Michèle; Gattegno, Tamar; Forgue, Jean; Admon, Arie; Babin, Patrick J

2006-01-01

Background The ability of an oocyte to develop into a viable embryo depends on the accumulation of specific maternal information and molecules, such as RNAs and proteins. A serial analysis of gene expression (SAGE) was carried out in parallel with proteomic analysis on fully-grown ovarian follicles from zebrafish (Danio rerio). The data obtained were compared with ovary/follicle/egg molecular phenotypes of other animals, published or available in public sequence databases. Results Sequencing of 27,486 SAGE tags identified 11,399 different ones, including 3,329 tags with an occurrence superior to one. Fifty-eight genes were expressed at over 0.15% of the total population and represented 17.34% of the mRNA population identified. The three most expressed transcripts were a rhamnose-binding lectin, beta-actin 2, and a transcribed locus similar to the H2B histone family. Comparison with the large-scale expressed sequence tags sequencing approach revealed highly expressed transcripts that were not previously known to be expressed at high levels in fish ovaries, like the short-sized polarized metallothionein 2 transcript. A higher sensitivity for the detection of transcripts with a characterized maternal genetic contribution was also demonstrated compared to large-scale sequencing of cDNA libraries. Ferritin heavy polypeptide 1, heat shock protein 90-beta, lactate dehydrogenase B4, beta-actin isoforms, tubulin beta 2, ATP synthase subunit 9, together with 40 S ribosomal protein S27a, were common highly-expressed transcripts of vertebrate ovary/unfertilized egg. Comparison of transcriptome and proteome data revealed that transcript levels provide little predictive value with respect to the extent of protein abundance. All the proteins identified by proteomic analysis of fully-grown zebrafish follicles had at least one transcript counterpart, with two exceptions: eosinophil chemotactic cytokine and nothepsin. Conclusion This study provides a complete sequence data set of maternal mRNA stored in zebrafish germ cells at the end of oogenesis. This catalogue contains highly-expressed transcripts that are part of a vertebrate ovarian expressed gene signature. Comparison of transcriptome and proteome data identified downregulated transcripts or proteins potentially incorporated in the oocyte by endocytosis. The molecular phenotype described provides groundwork for future experimental approaches aimed at identifying functionally important stored maternal transcripts and proteins involved in oogenesis and early stages of embryo development. PMID:16526958

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

MPLEx: a Robust and Universal Protocol for Single-Sample Integrative Proteomic, Metabolomic, and Lipidomic Analyses

PubMed Central

Nakayasu, Ernesto S.; Nicora, Carrie D.; Sims, Amy C.; Burnum-Johnson, Kristin E.; Kim, Young-Mo; Kyle, Jennifer E.; Matzke, Melissa M.; Shukla, Anil K.; Chu, Rosalie K.; Schepmoes, Athena A.; Jacobs, Jon M.; Baric, Ralph S.; Webb-Robertson, Bobbie-Jo; Smith, Richard D.

2016-01-01

ABSTRACT Integrative multi-omics analyses can empower more effective investigation and complete understanding of complex biological systems. Despite recent advances in a range of omics analyses, multi-omic measurements of the same sample are still challenging and current methods have not been well evaluated in terms of reproducibility and broad applicability. Here we adapted a solvent-based method, widely applied for extracting lipids and metabolites, to add proteomics to mass spectrometry-based multi-omics measurements. The metabolite, protein, and lipid extraction (MPLEx) protocol proved to be robust and applicable to a diverse set of sample types, including cell cultures, microbial communities, and tissues. To illustrate the utility of this protocol, an integrative multi-omics analysis was performed using a lung epithelial cell line infected with Middle East respiratory syndrome coronavirus, which showed the impact of this virus on the host glycolytic pathway and also suggested a role for lipids during infection. The MPLEx method is a simple, fast, and robust protocol that can be applied for integrative multi-omic measurements from diverse sample types (e.g., environmental, in vitro, and clinical). IMPORTANCE In systems biology studies, the integration of multiple omics measurements (i.e., genomics, transcriptomics, proteomics, metabolomics, and lipidomics) has been shown to provide a more complete and informative view of biological pathways. Thus, the prospect of extracting different types of molecules (e.g., DNAs, RNAs, proteins, and metabolites) and performing multiple omics measurements on single samples is very attractive, but such studies are challenging due to the fact that the extraction conditions differ according to the molecule type. Here, we adapted an organic solvent-based extraction method that demonstrated broad applicability and robustness, which enabled comprehensive proteomics, metabolomics, and lipidomics analyses from the same sample. Author Video: An author video summary of this article is available. PMID:27822525

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.

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.

Draft de novo transcriptome assembly and proteome characterization of the electric lobe of Tetronarce californica: a molecular tool for the study of cholinergic neurotransmission in the electric organ.

PubMed

Stavrianakou, Maria; Perez, Ricardo; Wu, Cheng; Sachs, Matthew S; Aramayo, Rodolfo; Harlow, Mark

2017-08-14

The electric organ of Tetronarce californica (an electric ray formerly known as Torpedo californica) is a classic preparation for biochemical studies of cholinergic neurotransmission. To broaden the usefulness of this preparation, we have performed a transcriptome assembly of the presynaptic component of the electric organ (the electric lobe). We combined our assembled transcriptome with a previous transcriptome of the postsynaptic electric organ, to define a MetaProteome containing pre- and post-synaptic components of the electric organ. Sequencing yielded 102 million paired-end 100 bp reads. De novo Trinity assembly was performed at Kmer 25 (default) and Kmers 27, 29, and 31. Trinity, generated around 103,000 transcripts, and 78,000 genes per assembly. Assemblies were evaluated based on the number of bases/transcripts assembled, RSEM-EVAL scores and informational content and completeness. We found that different assemblies scored differently according to the evaluation criteria used, and that while each individual assembly contained unique information, much of the assembly information was shared by all assemblies. To generate the presynaptic transcriptome (electric lobe), while capturing all information, assemblies were first clustered and then combined with postsynaptic transcripts (electric organ) downloaded from NCBI. The completness of the resulting clustered predicted MetaProteome was rigorously evaluated by comparing its information against the predicted proteomes from Homo sapiens, Callorhinchus milli, and the Transporter Classification Database (TCDB). In summary, we obtained a MetaProteome containing 92%, 88.5%, and 66% of the expected set of ultra-conserved sequences (i.e., BUSCOs), expected to be found for Eukaryotes, Metazoa, and Vertebrata, respectively. We cross-annotated the conserved set of proteins shared between the T. californica MetaProteome and the proteomes of H. sapiens and C. milli, using the H. sapiens genome as a reference. This information was used to predict the position in human pathways of the conserved members of the T. californica MetaProteome. We found proteins not detected before in T. californica, corresponding to processes involved in synaptic vesicle biology. Finally, we identified 42 transporter proteins in TCDB that were detected by the T. californica MetaProteome (electric fish) and not selected by a control proteome consisting of the combined proteomes of 12 widely diverse non-electric fishes by Reverse-Blast-Hit Blast. Combined, the information provided here is not only a unique tool for the study of cholinergic neurotransmission, but it is also a starting point for understanding the evolution of early vertebrates.

Mitochondrial dysfunction, oxidative stress and apoptosis revealed by proteomic and transcriptomic analyses of the striata in two mouse models of Parkinson’s disease

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

Chin, Mark H.; Qian, Weijun; Wang, Haixing

2008-02-10

The molecular mechanisms underlying the changes in the nigrostriatal pathway in Parkinson disease (PD) are not completely understood. Here we use mass spectrometry and microarrays to study the proteomic and transcriptomic changes in the striatum of two mouse models of PD, induced by the distinct neurotoxins 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and methamphetamine (METH). Proteomic analyses resulted in the identification and relative quantification of 912 proteins with two or more unique peptides and 85 proteins with significant abundance changes following neurotoxin treatment. Similarly, microarray analyses revealed 181 genes with significant changes in mRNA following neurotoxin treatment. The combined protein and gene list providesmore » a clearer picture of the potential mechanisms underlying neurodegeneration observed in PD. Functional analysis of this combined list revealed a number of significant categories, including mitochondrial dysfunction, oxidative stress response and apoptosis. Additionally, codon usage and miRNAs may play an important role in translational control in the striatum. These results constitute one of the largest datasets integrating protein and transcript changes for these neurotoxin models with many similar endpoint phenotypes but distinct mechanisms.« less

2-DE analysis indicates that Acinetobacter baumannii displays a robust and versatile metabolism

PubMed Central

Soares, Nelson C; Cabral, Maria P; Parreira, José R; Gayoso, Carmen; Barba, Maria J; Bou, Germán

2009-01-01

Background Acinetobacter baumannii is a nosocomial pathogen that has been associated with outbreak infections in hospitals. Despite increasing awareness about this bacterium, its proteome remains poorly characterised, however recently the complete genome of A. baumannii reference strain ATCC 17978 has been sequenced. Here, we have used 2-DE and MALDI-TOF/TOF approach to characterise the proteome of this strain. Results The membrane and cytoplasmatic protein extracts were analysed separately, these analyses revealed the reproducible presence of 239 and 511 membrane and cytoplamatic protein spots, respectively. MALDI-TOF/TOF characterisation identified a total of 192 protein spots (37 membrane and 155 cytoplasmatic) and revealed that the identified membrane proteins were mainly transport-related proteins, whereas the cytoplasmatic proteins were of diverse nature, although mainly related to metabolic processes. Conclusion This work indicates that A. baumannii has a versatile and robust metabolism and also reveal a number of proteins that may play a key role in the mechanism of drug resistance and virulence. The data obtained complements earlier reports of A. baumannii proteome and provides new tools to increase our knowledge on the protein expression profile of this pathogen. PMID:19785748

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

PubMed

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

2016-10-01

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

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

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...

Development of Advanced Technologies for Complete Genomic and Proteomic Characterization of Quantized Human Tumor Cells

DTIC Science & Technology

2014-07-01

establishment of Glioblastoma ( GBM ) cell lines from GBM patient’s tumor samples and quantized cell populations of each of the parental GBM cell lines, we... GBM patients are now well established and from the basis of the molecular characterization of the tumor development and signatures presented by these...analysis of these quantized cell sub populations and have begun to assemble the protein signatures of GBM tumors underpinned by the comprehensive

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.

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

PubMed

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

2015-05-01

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

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

PubMed

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

2018-04-15

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

Identification of beta-Lactamases and beta-Lactam-Related Proteins in Human Pathogenic Bacteria using a Computational Search Approach.

PubMed

Brambila-Tapia, Aniel Jessica Leticia; Perez-Rueda, Ernesto; Barrios, Humberto; Dávalos-Rodríguez, Nory Omayra; Dávalos-Rodríguez, Ingrid Patricia; Cardona-Muñoz, Ernesto Germán; Salazar-Páramo, Mario

2017-08-01

A systematic analysis of beta-lactamases based on comparative proteomics has not been performed thus far. In this report, we searched for the presence of beta-lactam-related proteins in 591 bacterial proteomes belonging to 52 species that are pathogenic to humans. The amino acid sequences for 19 different types of beta-lactamases (ACT, CARB, CifA, CMY, CTX, FOX, GES, GOB, IMP, IND, KPC, LEN, OKP, OXA, OXY, SHV, TEM, NDM, and VIM) were obtained from the ARG-ANNOT database and were used to construct 19 HMM profiles, which were used to identify potential beta-lactamases in the completely sequenced bacterial proteomes. A total of 2877 matches that included the word "beta-lactamase" and/or "penicillin" in the functional annotation and/or in any of its regions were obtained. These enzymes were mainly described as "penicillin-binding proteins," "beta-lactamases," and "metallo-beta-lactamases" and were observed in 47 of the 52 species studied. In addition, proteins classified as "beta-lactamases" were observed in 39 of the species included. A positive correlation between the number of beta-lactam-related proteins per species and the proteome size was observed (R 0.78, P < 0.00001). This correlation partially explains the high presence of beta-lactam-related proteins in large proteomes, such as Nocardia brasiliensis, Bacillus anthracis, and Mycobacterium tuberculosis, along with their absence in small proteomes, such as Chlamydia spp. and Mycoplasma spp. We detected only five types of beta-lactamases (TEM, SHV, CTX, IMP, and OXA) and other related proteins in particular species that corresponded with those reported in the literature. We additionally detected other potential species-specific beta-lactamases that have not yet been reported. In the future, better results will be achieved due to more accurate sequence annotations and a greater number of sequenced genomes.

Complete Proteome of a Quinolone-Resistant Salmonella Typhimurium Phage Type DT104B Clinical Strain

PubMed Central

Correia, Susana; Nunes-Miranda, Júlio D.; Pinto, Luís; Santos, Hugo M.; de Toro, María; Sáenz, Yolanda; Torres, Carmen; Capelo, José Luis; Poeta, Patrícia; Igrejas, Gilberto

2014-01-01

Salmonellosis is one of the most common and widely distributed foodborne diseases. The emergence of Salmonella strains that are resistant to a variety of antimicrobials is a serious global public health concern. Salmonella enterica serovar Typhimurium definitive phage type 104 (DT104) is one of these emerging epidemic multidrug resistant strains. Here we collate information from the diverse and comprehensive range of experiments on Salmonella proteomes that have been published. We then present a new study of the proteome of the quinolone-resistant Se20 strain (phage type DT104B), recovered after ciprofloxacin treatment and compared it to the proteome of reference strain SL1344. A total of 186 and 219 protein spots were recovered from Se20 and SL1344 protein extracts, respectively, after two-dimensional gel electrophoresis. The signatures of 94% of the protein spots were successfully identified through matrix-assisted laser desorption/ionization mass spectrometry (MALDI-TOF MS). Three antimicrobial resistance related proteins, whose genes were previously detected by polymerase chain reaction (PCR), were identified in the clinical strain. The presence of these proteins, dihydropteroate synthase type-2 (sul2 gene), aminoglycoside resistance protein A (strA gene) and aminoglycoside 6'-N-acetyltransferase type Ib-cr4 (aac(6')-Ib-cr4 gene), was confirmed in the DT104B clinical strain. The aac(6')-Ib-cr4 gene is responsible for plasmid-mediated aminoglycoside and quinolone resistance. This is a preliminary analysis of the proteome of these two S. Typhimurium strains and further work is being developed to better understand how antimicrobial resistance is developing in this pathogen. PMID:25196519

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.

Experimental annotation of post-translational features and translated coding regions in the pathogen Salmonella Typhimurium

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

Ansong, Charles; Tolic, Nikola; Purvine, Samuel O.

Complete and accurate genome annotation is crucial for comprehensive and systematic studies of biological systems. For example systems biology-oriented genome scale modeling efforts greatly benefit from accurate annotation of protein-coding genes to develop proper functioning models. However, determining protein-coding genes for most new genomes is almost completely performed by inference, using computational predictions with significant documented error rates (> 15%). Furthermore, gene prediction programs provide no information on biologically important post-translational processing events critical for protein function. With the ability to directly measure peptides arising from expressed proteins, mass spectrometry-based proteomics approaches can be used to augment and verify codingmore » regions of a genomic sequence and importantly detect post-translational processing events. In this study we utilized “shotgun” proteomics to guide accurate primary genome annotation of the bacterial pathogen Salmonella Typhimurium 14028 to facilitate a systems-level understanding of Salmonella biology. The data provides protein-level experimental confirmation for 44% of predicted protein-coding genes, suggests revisions to 48 genes assigned incorrect translational start sites, and uncovers 13 non-annotated genes missed by gene prediction programs. We also present a comprehensive analysis of post-translational processing events in Salmonella, revealing a wide range of complex chemical modifications (70 distinct modifications) and confirming more than 130 signal peptide and N-terminal methionine cleavage events in Salmonella. This study highlights several ways in which proteomics data applied during the primary stages of annotation can improve the quality of genome annotations, especially with regards to the annotation of mature protein products.« less

Biological Entanglement-Like Effect After Communication of Fish Prior to X-Ray Exposure.

PubMed

Mothersill, Carmel; Smith, Richard; Wang, Jiaxi; Rusin, Andrej; Fernandez-Palomo, Cris; Fazzari, Jennifer; Seymour, Colin

2018-01-01

The phenomenon by which irradiated organisms including cells in vitro communicate with unirradiated neighbors is well established in biology as the radiation-induced bystander effect (RIBE). Generally, the purpose of this communication is thought to be protective and adaptive, reflecting a highly conserved evolutionary mechanism enabling rapid adjustment to stressors in the environment. Stressors known to induce the effect were recently shown to include chemicals and even pathological agents. The mechanism is unknown but our group has evidence that physical signals such as biophotons acting on cellular photoreceptors may be implicated. This raises the question of whether quantum biological processes may occur as have been demonstrated in plant photosynthesis. To test this hypothesis, we decided to see whether any form of entanglement was operational in the system. Fish from 2 completely separate locations were allowed to meet for 2 hours either before or after which fish from 1 location only (group A fish) were irradiated. The results confirm RIBE signal production in both skin and gill of fish, meeting both before and after irradiation of group A fish. The proteomic analysis revealed that direct irradiation resulted in pro-tumorigenic proteomic responses in rainbow trout. However, communication from these irradiated fish, both before and after they had been exposed to a 0.5 Gy X-ray dose, resulted in largely beneficial proteomic responses in completely nonirradiated trout. The results suggest that some form of anticipation of a stressor may occur leading to a preconditioning effect or temporally displaced awareness after the fish become entangled.

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

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.

Development of Advanced Technologies for Complete Genomic and Proteomic Characterization of Quantized Human Tumor Cells

DTIC Science & Technology

2015-09-01

glioblastoma . We have successfully established several patient-derived cell lines from glioblastoma tumors and further established a number of...and single-cell technologies. Although the focus of this research is glioblastoma , the proposed tools are generally applicable to all cancer-based...studies. 15. SUBJECT TERMS Human cohorts, Glioblastoma , Genomic, Proteomic, Single-cell technologies, Hypothesis-driven, integrative systems approach

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

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.

Conservation and variability of West Nile virus proteins.

PubMed

Koo, Qi Ying; Khan, Asif M; Jung, Keun-Ok; Ramdas, Shweta; Miotto, Olivo; Tan, Tin Wee; Brusic, Vladimir; Salmon, Jerome; August, J Thomas

2009-01-01

West Nile virus (WNV) has emerged globally as an increasingly important pathogen for humans and domestic animals. Studies of the evolutionary diversity of the virus over its known history will help to elucidate conserved sites, and characterize their correspondence to other pathogens and their relevance to the immune system. We describe a large-scale analysis of the entire WNV proteome, aimed at identifying and characterizing evolutionarily conserved amino acid sequences. This study, which used 2,746 WNV protein sequences collected from the NCBI GenPept database, focused on analysis of peptides of length 9 amino acids or more, which are immunologically relevant as potential T-cell epitopes. Entropy-based analysis of the diversity of WNV sequences, revealed the presence of numerous evolutionarily stable nonamer positions across the proteome (entropy value of < or = 1). The representation (frequency) of nonamers variant to the predominant peptide at these stable positions was, generally, low (< or = 10% of the WNV sequences analyzed). Eighty-eight fragments of length 9-29 amino acids, representing approximately 34% of the WNV polyprotein length, were identified to be identical and evolutionarily stable in all analyzed WNV sequences. Of the 88 completely conserved sequences, 67 are also present in other flaviviruses, and several have been associated with the functional and structural properties of viral proteins. Immunoinformatic analysis revealed that the majority (78/88) of conserved sequences are potentially immunogenic, while 44 contained experimentally confirmed human T-cell epitopes. This study identified a comprehensive catalogue of completely conserved WNV sequences, many of which are shared by other flaviviruses, and majority are potential epitopes. The complete conservation of these immunologically relevant sequences through the entire recorded WNV history suggests they will be valuable as components of peptide-specific vaccines or other therapeutic applications, for sequence-specific diagnosis of a wide-range of Flavivirus infections, and for studies of homologous sequences among other flaviviruses.

Insights into salicylic acid responses in cucumber (Cucumis sativus L.) cotyledons based on a comparative proteomic analysis.

PubMed

Hao, J H; Dong, C J; Zhang, Z G; Wang, X L; Shang, Q M

2012-05-01

To investigate the response of cucumber seedlings to exogenous salicylic acid (SA) and gain a better understanding of SA action mechanism, we generated a proteomic profile of cucumber (Cucumis sativus L.) cotyledons treated with exogenous SA. Analysis of 1500 protein spots from each gel revealed 63 differentially expressed proteins, 59 of which were identified successfully. Of the identified proteins, 97% matched cucumber proteins using a whole cucumber protein database based on the newly completed genome established by our laboratory. The identified proteins were involved in various cellular responses and metabolic processes, including antioxidative reactions, cell defense, photosynthesis, carbohydrate metabolism, respiration and energy homeostasis, protein folding and biosynthesis. The two largest functional categories included proteins involved in antioxidative reactions (23.7%) and photosynthesis (18.6%). Furthermore, the SA-responsive protein interaction network revealed 13 key proteins, suggesting that the expression changes of these proteins could be critical for SA-induced resistance. An analysis of these changes suggested that SA-induced resistance and seedling growth might be regulated in part through pathways involving antioxidative reactions and photosynthesis. © 2012 Elsevier Ireland Ltd. 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.

The complete genome and proteome of Laribacter hongkongensis reveal potential mechanisms for adaptations to different temperatures and habitats.

PubMed

Woo, Patrick C Y; Lau, Susanna K P; Tse, Herman; Teng, Jade L L; Curreem, Shirly O T; Tsang, Alan K L; Fan, Rachel Y Y; Wong, Gilman K M; Huang, Yi; Loman, Nicholas J; Snyder, Lori A S; Cai, James J; Huang, Jian-Dong; Mak, William; Pallen, Mark J; Lok, Si; Yuen, Kwok-Yung

2009-03-01

Laribacter hongkongensis is a newly discovered Gram-negative bacillus of the Neisseriaceae family associated with freshwater fish-borne gastroenteritis and traveler's diarrhea. The complete genome sequence of L. hongkongensis HLHK9, recovered from an immunocompetent patient with severe gastroenteritis, consists of a 3,169-kb chromosome with G+C content of 62.35%. Genome analysis reveals different mechanisms potentially important for its adaptation to diverse habitats of human and freshwater fish intestines and freshwater environments. The gene contents support its phenotypic properties and suggest that amino acids and fatty acids can be used as carbon sources. The extensive variety of transporters, including multidrug efflux and heavy metal transporters as well as genes involved in chemotaxis, may enable L. hongkongensis to survive in different environmental niches. Genes encoding urease, bile salts efflux pump, adhesin, catalase, superoxide dismutase, and other putative virulence factors-such as hemolysins, RTX toxins, patatin-like proteins, phospholipase A1, and collagenases-are present. Proteomes of L. hongkongensis HLHK9 cultured at 37 degrees C (human body temperature) and 20 degrees C (freshwater habitat temperature) showed differential gene expression, including two homologous copies of argB, argB-20, and argB-37, which encode two isoenzymes of N-acetyl-L-glutamate kinase (NAGK)-NAGK-20 and NAGK-37-in the arginine biosynthesis pathway. NAGK-20 showed higher expression at 20 degrees C, whereas NAGK-37 showed higher expression at 37 degrees C. NAGK-20 also had a lower optimal temperature for enzymatic activities and was inhibited by arginine probably as negative-feedback control. Similar duplicated copies of argB are also observed in bacteria from hot springs such as Thermus thermophilus, Deinococcus geothermalis, Deinococcus radiodurans, and Roseiflexus castenholzii, suggesting that similar mechanisms for temperature adaptation may be employed by other bacteria. Genome and proteome analysis of L. hongkongensis revealed novel mechanisms for adaptations to survival at different temperatures and habitats.

Proteomics Standards Initiative: Fifteen Years of Progress and Future Work

PubMed Central

2017-01-01

The Proteomics Standards Initiative (PSI) of the Human Proteome Organization (HUPO) has now been developing and promoting open community standards and software tools in the field of proteomics for 15 years. Under the guidance of the chair, cochairs, and other leadership positions, the PSI working groups are tasked with the development and maintenance of community standards via special workshops and ongoing work. Among the existing ratified standards, the PSI working groups continue to update PSI-MI XML, MITAB, mzML, mzIdentML, mzQuantML, mzTab, and the MIAPE (Minimum Information About a Proteomics Experiment) guidelines with the advance of new technologies and techniques. Furthermore, new standards are currently either in the final stages of completion (proBed and proBAM for proteogenomics results as well as PEFF) or in early stages of design (a spectral library standard format, a universal spectrum identifier, the qcML quality control format, and the Protein Expression Interface (PROXI) web services Application Programming Interface). In this work we review the current status of all of these aspects of the PSI, describe synergies with other efforts such as the ProteomeXchange Consortium, the Human Proteome Project, and the metabolomics community, and provide a look at future directions of the PSI. PMID:28849660

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

PubMed

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

2017-12-01

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

Proteomics Standards Initiative: Fifteen Years of Progress and Future Work.

PubMed

Deutsch, Eric W; Orchard, Sandra; Binz, Pierre-Alain; Bittremieux, Wout; Eisenacher, Martin; Hermjakob, Henning; Kawano, Shin; Lam, Henry; Mayer, Gerhard; Menschaert, Gerben; Perez-Riverol, Yasset; Salek, Reza M; Tabb, David L; Tenzer, Stefan; Vizcaíno, Juan Antonio; Walzer, Mathias; Jones, Andrew R

2017-12-01

The Proteomics Standards Initiative (PSI) of the Human Proteome Organization (HUPO) has now been developing and promoting open community standards and software tools in the field of proteomics for 15 years. Under the guidance of the chair, cochairs, and other leadership positions, the PSI working groups are tasked with the development and maintenance of community standards via special workshops and ongoing work. Among the existing ratified standards, the PSI working groups continue to update PSI-MI XML, MITAB, mzML, mzIdentML, mzQuantML, mzTab, and the MIAPE (Minimum Information About a Proteomics Experiment) guidelines with the advance of new technologies and techniques. Furthermore, new standards are currently either in the final stages of completion (proBed and proBAM for proteogenomics results as well as PEFF) or in early stages of design (a spectral library standard format, a universal spectrum identifier, the qcML quality control format, and the Protein Expression Interface (PROXI) web services Application Programming Interface). In this work we review the current status of all of these aspects of the PSI, describe synergies with other efforts such as the ProteomeXchange Consortium, the Human Proteome Project, and the metabolomics community, and provide a look at future directions of the PSI.

Hop (Humulus lupulus L.) response mechanisms in drought stress: Proteomic analysis with physiology.

PubMed

Kolenc, Zala; Vodnik, Dominik; Mandelc, Stanislav; Javornik, Branka; Kastelec, Damijana; Čerenak, Andreja

2016-08-01

Drought is one of the major environmental devastating stressors that impair the growth and productivity of crop plants. Despite the relevance of drought stress, changes in physiology and resistance mechanisms are not completely understood for certain crops, including hop (Humulus lupulus L.). In this research the drought response of hop was studied using a conventional physiological approach (gas exchange techniques, fluorescence, relative water content measurements) and proteomic analysis (2D-DIGE). Plants of two cultivars (Aurora and Savinjski golding) were exposed to progressive drought in a pot experiment and analysed at different stress stages (mild, moderate and severe). Measurements of relative water content revealed a hydrostable water balance of hop. Photosynthesis was decreased due to stomatal and non-stomatal limitation to the same extent in both cultivars. Of 28 identified differentially abundant proteins, the majority were down regulated and included in photosynthetic (41%) and sugar metabolism (33%). Fifteen % of identified proteins were classified into the nitrogen metabolism, 4% were related to a ROS related pathway and 7% to other functions. Copyright © 2016. Published by Elsevier Masson SAS.

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.

Differential proteomics analysis to identify proteins and pathways associated with male sterility of soybean using iTRAQ-based strategy.

PubMed

Li, Jiajia; Ding, Xianlong; Han, Shaohuai; He, Tingting; Zhang, Hao; Yang, Longshu; Yang, Shouping; Gai, Junyi

2016-04-14

To further elucidate the molecular mechanism of cytoplasmic male sterility (CMS) in soybean, a differential proteomic analysis was completed between the CMS line NJCMS1A and its maintainer NJCMS1B using iTRAQ-based strategy. As a result, 180 differential abundance proteins (DAPs) were identified, of which, 60 were down-regulated and 120 were up-regulated in NJCMS1A compared with NJCMS1B. Bioinformatic analysis showed that 167 DAPs were annotated in 41 Gene Ontology functional groups, 106 DAPs were classified into 20 clusters of orthologous groups of protein categories, and 128 DAPs were enrichment in 53 KEGG pathways. Fifteen differential level proteins/genes with the same expression pattern were identified in the further conjoint analysis of DAPs and the previously reported differential expression genes. Moreover, multiple reaction monitoring test, qRT-PCR analysis and enzyme activity assay validated that the iTRAQ results were reliable. Based on functional analysis of DAPs, we concluded that male sterility in NJCMS1A might be related to insufficiencies in energy supply, unbalance of protein synthesis and degradation, disruption of flavonoid synthesis, programmed cell death, abnormalities of substance metabolism, etc. These results might facilitate our understanding of the molecular mechanisms behind CMS in soybean. Soybean is an important global crop that provides protein and oil. Heterosis is a significantly potential approach to increase the yield of soybean. Cytoplasmic male sterility (CMS) plays a vital role in the production of hybrid seeds. However, the genetic and molecular mechanisms of male sterility in soybean still need to be further elucidated. In the present paper, a differential proteomic analysis was carried out and the results showed that several key proteins involved in key pathways were associated with male sterility in soybean. This work provides a new insight to understand the genetic and molecular mechanisms underlying CMS in soybean. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Functional Proteomic Analysis of Lipid Raft Kinase Complexes

DTIC Science & Technology

2009-08-01

Ribosomal protein SA Raft 12 46/300 + 16.0 8.0 2.0 18 8 2.3 14 6 2.3 712 + + IPI00023101 RQCD1 Homo sapiens protein involved in sexual development...KnownHuman 17-ODYA IPI00065486 ABCB6 CDNA FLJ32464 fis, clone SKNMC1000251, highly similar to Homo sapiens MT-ABCtransporter (MTABC) mRNA IPI00006675...3.7 : 0 + + IPI00023101 RQCD1 Homo sapiens protein involved in sexual development, complete cds + + IPI00021766 RTN4 Isoform 1 of Reticulon-4 12

The Reactome pathway knowledgebase

PubMed Central

Croft, David; Mundo, Antonio Fabregat; Haw, Robin; Milacic, Marija; Weiser, Joel; Wu, Guanming; Caudy, Michael; Garapati, Phani; Gillespie, Marc; Kamdar, Maulik R.; Jassal, Bijay; Jupe, Steven; Matthews, Lisa; May, Bruce; Palatnik, Stanislav; Rothfels, Karen; Shamovsky, Veronica; Song, Heeyeon; Williams, Mark; Birney, Ewan; Hermjakob, Henning; Stein, Lincoln; D'Eustachio, Peter

2014-01-01

Reactome (http://www.reactome.org) is a manually curated open-source open-data resource of human pathways and reactions. The current version 46 describes 7088 human proteins (34% of the predicted human proteome), participating in 6744 reactions based on data extracted from 15 107 research publications with PubMed links. The Reactome Web site and analysis tool set have been completely redesigned to increase speed, flexibility and user friendliness. The data model has been extended to support annotation of disease processes due to infectious agents and to mutation. PMID:24243840

The Reactome pathway knowledgebase.

PubMed

Croft, David; Mundo, Antonio Fabregat; Haw, Robin; Milacic, Marija; Weiser, Joel; Wu, Guanming; Caudy, Michael; Garapati, Phani; Gillespie, Marc; Kamdar, Maulik R; Jassal, Bijay; Jupe, Steven; Matthews, Lisa; May, Bruce; Palatnik, Stanislav; Rothfels, Karen; Shamovsky, Veronica; Song, Heeyeon; Williams, Mark; Birney, Ewan; Hermjakob, Henning; Stein, Lincoln; D'Eustachio, Peter

2014-01-01

Reactome (http://www.reactome.org) is a manually curated open-source open-data resource of human pathways and reactions. The current version 46 describes 7088 human proteins (34% of the predicted human proteome), participating in 6744 reactions based on data extracted from 15 107 research publications with PubMed links. The Reactome Web site and analysis tool set have been completely redesigned to increase speed, flexibility and user friendliness. The data model has been extended to support annotation of disease processes due to infectious agents and to mutation.

Mass spectrometry and renal calculi

PubMed Central

Purcarea, VL; Sisu, I; Sisu, E

2010-01-01

The present review represents a concise and complete survey of the literature covering 2004–2009, concerning the mass spectrometric techniques involved in the structural investigation of renal calculi. After a short presentation of the fundamental mass spectrometric techniques (MALDI–TOF, QTOF, MS–MS) as well as hyphenated methods (GC–MS, LC–MS, CE–MS), an extensive study of the urinary proteome analysis as well as the detection and quantification by mass spectrometry of toxins, drugs and metabolites from renal calculi is presented. PMID:20968197

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.

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

PubMed Central

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

2011-01-01

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

The Schistosoma mansoni phylome: using evolutionary genomics to gain insight into a parasite's biology.

PubMed

Silva, Larissa Lopes; Marcet-Houben, Marina; Nahum, Laila Alves; Zerlotini, Adhemar; Gabaldón, Toni; Oliveira, Guilherme

2012-11-13

Schistosoma mansoni is one of the causative agents of schistosomiasis, a neglected tropical disease that affects about 237 million people worldwide. Despite recent efforts, we still lack a general understanding of the relevant host-parasite interactions, and the possible treatments are limited by the emergence of resistant strains and the absence of a vaccine. The S. mansoni genome was completely sequenced and still under continuous annotation. Nevertheless, more than 45% of the encoded proteins remain without experimental characterization or even functional prediction. To improve our knowledge regarding the biology of this parasite, we conducted a proteome-wide evolutionary analysis to provide a broad view of the S. mansoni's proteome evolution and to improve its functional annotation. Using a phylogenomic approach, we reconstructed the S. mansoni phylome, which comprises the evolutionary histories of all parasite proteins and their homologs across 12 other organisms. The analysis of a total of 7,964 phylogenies allowed a deeper understanding of genomic complexity and evolutionary adaptations to a parasitic lifestyle. In particular, the identification of lineage-specific gene duplications pointed to the diversification of several protein families that are relevant for host-parasite interaction, including proteases, tetraspanins, fucosyltransferases, venom allergen-like proteins, and tegumental-allergen-like proteins. In addition to the evolutionary knowledge, the phylome data enabled us to automatically re-annotate 3,451 proteins through a phylogenetic-based approach rather than solely sequence similarity searches. To allow further exploitation of this valuable data, all information has been made available at PhylomeDB (http://www.phylomedb.org). In this study, we used an evolutionary approach to assess S. mansoni parasite biology, improve genome/proteome functional annotation, and provide insights into host-parasite interactions. Taking advantage of a proteome-wide perspective rather than focusing on individual proteins, we identified that this parasite has experienced specific gene duplication events, particularly affecting genes that are potentially related to the parasitic lifestyle. These innovations may be related to the mechanisms that protect S. mansoni against host immune responses being important adaptations for the parasite survival in a potentially hostile environment. Continuing this work, a comparative analysis involving genomic, transcriptomic, and proteomic data from other helminth parasites, other parasites, and vectors will supply more information regarding parasite's biology as well as host-parasite interactions.

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.

Development of an Efficient Protein Extraction Method Compatible with LC-MS/MS for Proteome Mapping in Two Australian Seagrasses Zostera muelleri and Posidonia australis

PubMed Central

Jiang, Zhijian; Kumar, Manoj; Padula, Matthew P.; Pernice, Mathieu; Kahlke, Tim; Kim, Mikael; Ralph, Peter J.

2017-01-01

The availability of the first complete genome sequence of the marine flowering plant Zostera marina (commonly known as seagrass) in early 2016, is expected to significantly raise the impact of seagrass proteomics. Seagrasses are marine ecosystem engineers that are currently declining worldwide at an alarming rate due to both natural and anthropogenic disturbances. Seagrasses (especially species of the genus Zostera) are compromised for proteomic studies primarily due to the lack of efficient protein extraction methods because of their recalcitrant cell wall which is rich in complex polysaccharides and a high abundance of secondary metabolites in their cells. In the present study, three protein extraction methods that are commonly used in plant proteomics i.e., phenol (P); trichloroacetic acid/acetone/SDS/phenol (TASP); and borax/polyvinyl-polypyrrolidone/phenol (BPP) extraction, were evaluated quantitatively and qualitatively based on two dimensional isoelectric focusing (2D-IEF) maps and LC-MS/MS analysis using the two most abundant Australian seagrass species, namely Zostera muelleri and Posidonia australis. All three tested methods produced high quality protein extracts with excellent 2D-IEF maps in P. australis. However, the BPP method produces better results in Z. muelleri compared to TASP and P. Therefore, we further modified the BPP method (M-BPP) by homogenizing the tissue in a modified protein extraction buffer containing both ionic and non-ionic detergents (0.5% SDS; 1.5% Triton X-100), 2% PVPP and protease inhibitors. Further, the extracted proteins were solubilized in 0.5% of zwitterionic detergent (C7BzO) instead of 4% CHAPS. This slight modification to the BPP method resulted in a higher protein yield, and good quality 2-DE maps with a higher number of protein spots in both the tested seagrasses. Further, the M-BPP method was successfully utilized in western-blot analysis of phosphoenolpyruvate carboxylase (PEPC—a key enzyme for carbon metabolism). This optimized protein extraction method will be a significant stride toward seagrass proteome mining and identifying the protein biomarkers to stress response of seagrasses under the scenario of global climate change and anthropogenic perturbations. PMID:28861098

Development of an Efficient Protein Extraction Method Compatible with LC-MS/MS for Proteome Mapping in Two Australian Seagrasses Zostera muelleri and Posidonia australis.

PubMed

Jiang, Zhijian; Kumar, Manoj; Padula, Matthew P; Pernice, Mathieu; Kahlke, Tim; Kim, Mikael; Ralph, Peter J

2017-01-01

The availability of the first complete genome sequence of the marine flowering plant Zostera marina (commonly known as seagrass) in early 2016, is expected to significantly raise the impact of seagrass proteomics. Seagrasses are marine ecosystem engineers that are currently declining worldwide at an alarming rate due to both natural and anthropogenic disturbances. Seagrasses (especially species of the genus Zostera ) are compromised for proteomic studies primarily due to the lack of efficient protein extraction methods because of their recalcitrant cell wall which is rich in complex polysaccharides and a high abundance of secondary metabolites in their cells. In the present study, three protein extraction methods that are commonly used in plant proteomics i.e., phenol (P); trichloroacetic acid/acetone/SDS/phenol (TASP); and borax/polyvinyl-polypyrrolidone/phenol (BPP) extraction, were evaluated quantitatively and qualitatively based on two dimensional isoelectric focusing (2D-IEF) maps and LC-MS/MS analysis using the two most abundant Australian seagrass species, namely Zostera muelleri and Posidonia australis . All three tested methods produced high quality protein extracts with excellent 2D-IEF maps in P. australis . However, the BPP method produces better results in Z. muelleri compared to TASP and P. Therefore, we further modified the BPP method (M-BPP) by homogenizing the tissue in a modified protein extraction buffer containing both ionic and non-ionic detergents (0.5% SDS; 1.5% Triton X-100), 2% PVPP and protease inhibitors. Further, the extracted proteins were solubilized in 0.5% of zwitterionic detergent (C7BzO) instead of 4% CHAPS. This slight modification to the BPP method resulted in a higher protein yield, and good quality 2-DE maps with a higher number of protein spots in both the tested seagrasses. Further, the M-BPP method was successfully utilized in western-blot analysis of phosphoenolpyruvate carboxylase (PEPC-a key enzyme for carbon metabolism). This optimized protein extraction method will be a significant stride toward seagrass proteome mining and identifying the protein biomarkers to stress response of seagrasses under the scenario of global climate change and anthropogenic perturbations.

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.

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

Comparison of analytical methods for profiling N- and O-linked glycans from cultured cell lines

PubMed Central

Togayachi, Akira; Azadi, Parastoo; Ishihara, Mayumi; Geyer, Rudolf; Galuska, Christina; Geyer, Hildegard; Kakehi, Kazuaki; Kinoshita, Mitsuhiro; Karlsson, Niclas G.; Jin, Chunsheng; Kato, Koichi; Yagi, Hirokazu; Kondo, Sachiko; Kawasaki, Nana; Hashii, Noritaka; Kolarich, Daniel; Stavenhagen, Kathrin; Packer, Nicolle H.; Thaysen-Andersen, Morten; Nakano, Miyako; Taniguchi, Naoyuki; Kurimoto, Ayako; Wada, Yoshinao; Tajiri, Michiko; Yang, Pengyuan; Cao, Weiqian; Li, Hong; Rudd, Pauline M.; Narimatsu, Hisashi

2016-01-01

The Human Disease Glycomics/Proteome Initiative (HGPI) is an activity in the Human Proteome Organization (HUPO) supported by leading researchers from international institutes and aims at development of disease-related glycomics/glycoproteomics analysis techniques. Since 2004, the initiative has conducted three pilot studies. The first two were N- and O-glycan analyses of purified transferrin and immunoglobulin-G and assessed the most appropriate analytical approach employed at the time. This paper describes the third study, which was conducted to compare different approaches for quantitation of N- and O-linked glycans attached to proteins in crude biological samples. The preliminary analysis on cell pellets resulted in wildly varied glycan profiles, which was probably the consequence of variations in the pre-processing sample preparation methodologies. However, the reproducibility of the data was not improved dramatically in the subsequent analysis on cell lysate fractions prepared in a specified method by one lab. The study demonstrated the difficulty of carrying out a complete analysis of the glycome in crude samples by any single technology and the importance of rigorous optimization of the course of analysis from preprocessing to data interpretation. It suggests that another collaborative study employing the latest technologies in this rapidly evolving field will help to realize the requirements of carrying out the large-scale analysis of glycoproteins in complex cell samples. PMID:26511985

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

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.

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

PubMed

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

2014-04-04

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

Plasma proteomics for biomarker discovery: a study in blue.

PubMed

Di Girolamo, Francesco; Righetti, Pier Giorgio

2011-12-01

The performance of Cibacron Blue dye (HiTrapBlue or Affigel Blue) in depleting albumin from plasma, as a pre-treatment for biomarker searching in the low-abundance proteome, is here assessed. It is shown that (i) co-depletion of non-albumin species is an ever-present hazard; (ii) the only proper eluant able to release quantitatively the proteins bound to the dye is boiling 4% SDS-25 mM DTT, an ion shock (2 M NaCl) being quite ineffective in releasing the low-abundance species tightly bound to the dye moiety; (iii) the mechanism of dye-protein interaction, after an initial ion-ion docking, is a robust hydrophobic interaction, which progressively augments at lower and lower pH values; (iv) at pH 2.2 in the presence of 0.1% TFA, the blue resin behaves, for all practical purposes, just as a reverse-phase chromatography column, since all residual proteins present in plasma are completely harvested. However Cibacron Blue technology should not necessarily be discarded: As long as also the plasma fraction adsorbed is properly released and analyzed, together with the flow through, one should be able to perform a viable analysis of the low-abundance proteome. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Covering complete proteomes with X-ray structures: A current snapshot

DOE PAGES

Mizianty, Marcin J.; Fan, Xiao; Yan, Jing; ...

2014-10-23

Structural genomics programs have developed and applied structure-determination pipelines to a wide range of protein targets, facilitating the visualization of macromolecular interactions and the understanding of their molecular and biochemical functions. The fundamental question of whether three-dimensional structures of all proteins and all functional annotations can be determined using X-ray crystallography is investigated. A first-of-its-kind large-scale analysis of crystallization propensity for all proteins encoded in 1953 fully sequenced genomes was performed. It is shown that current X-ray crystallographic knowhow combined with homology modeling can provide structures for 25% of modeling families (protein clusters for which structural models can be obtainedmore » through homology modeling), with at least one structural model produced for each Gene Ontology functional annotation. The coverage varies between superkingdoms, with 19% for eukaryotes, 35% for bacteria and 49% for archaea, and with those of viruses following the coverage values of their hosts. It is shown that the crystallization propensities of proteomes from the taxonomic superkingdoms are distinct. The use of knowledge-based target selection is shown to substantially increase the ability to produce X-ray structures. It is demonstrated that the human proteome has one of the highest attainable coverage values among eukaryotes, and GPCR membrane proteins suitable for X-ray structure determination were determined.« less

Proteomic analysis of human follicular fluid associated with successful in vitro fertilization.

PubMed

Shen, Xiaofang; Liu, Xin; Zhu, Peng; Zhang, Yuhua; Wang, Jiahui; Wang, Yanwei; Wang, Wenting; Liu, Juan; Li, Ning; Liu, Fujun

2017-07-27

Human follicular fluid (HFF) provides a key environment for follicle development and oocyte maturation, and contributes to oocyte quality and in vitro fertilization (IVF) outcome. To better understand folliculogenesis in the ovary, a proteomic strategy based on dual reverse phase high performance liquid chromatography (RP-HPLC) coupled to matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometry (LC-MALDI TOF/TOF MS) was used to investigate the protein profile of HFF from women undergoing successful IVF. A total of 219 unique high-confidence (False Discovery Rate (FDR) < 0.01) HFF proteins were identified by searching the reviewed Swiss-Prot human database (20,183 sequences), and MS data were further verified by western blot. PANTHER showed HFF proteins were involved in complement and coagulation cascade, growth factor and hormone, immunity, and transportation, KEGG indicated their pathway, and STRING demonstrated their interaction networks. In comparison, 32% and 50% of proteins have not been reported in previous human follicular fluid and plasma. Our HFF proteome research provided a new complementary high-confidence dataset of folliculogenesis and oocyte maturation environment. Those proteins associated with innate immunity, complement cascade, blood coagulation, and angiogenesis might serve as the biomarkers of female infertility and IVF outcome, and their pathways facilitated a complete exhibition of reproductive process.

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

Proteome-scale human interactomics

PubMed Central

Luck, Katja; Sheynkman, Gloria M.; Zhang, Ivy; Vidal, Marc

2017-01-01

Cellular functions are mediated by complex interactome networks of physical, biochemical, and functional interactions between DNA sequences, RNA molecules, proteins, lipids, and small metabolites. A thorough understanding of cellular organization requires accurate and relatively complete models of interactome networks at proteome-scale. The recent publication of four human protein-protein interaction (PPI) maps represents a technological breakthrough and an unprecedented resource for the scientific community, heralding a new era of proteome-scale human interactomics. Our knowledge gained from these and complementary studies provides fresh insights into the opportunities and challenges when analyzing systematically generated interactome data, defines a clear roadmap towards the generation of a first reference interactome, and reveals new perspectives on the organization of cellular life. PMID:28284537

Genomics, transcriptomics and proteomics to elucidate the pathogenesis of rheumatoid arthritis.

PubMed

Song, Xinqiang; Lin, Qingsong

2017-08-01

Rheumatoid arthritis is an autoimmune disease that affects several organs and tissues, predominantly the synovial joints. The pathogenesis of this disease is not completely understood, which maybe involved in the genomic variations, gene expression, protein translation and post-translational modifications. These system variations in genomics, transcriptomics and proteomics are dynamic in nature and their crosstalk is overwhelmingly complex, thus analyzing them separately may not be very informative. However, various '-omics' techniques developed in recent years have opened up new possibilities for clarifying disease pathways and thereby facilitating early diagnosis and specific therapies. This review examines how recent advances in the fields of genomics, transcriptomics and proteomics have contributed to our understanding of rheumatoid arthritis.

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

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.

The speciation of the proteome

PubMed Central

Jungblut, Peter R; Holzhütter, Hermann G; Apweiler, Rolf; Schlüter, Hartmut

2008-01-01

Introduction In proteomics a paradox situation developed in the last years. At one side it is basic knowledge that proteins are post-translationally modified and occur in different isoforms. At the other side the protein expression concept disclaims post-translational modifications by connecting protein names directly with function. Discussion Optimal proteome coverage is today reached by bottom-up liquid chromatography/mass spectrometry. But quantification at the peptide level in shotgun or bottom-up approaches by liquid chromatography and mass spectrometry is completely ignoring that a special peptide may exist in an unmodified form and in several-fold modified forms. The acceptance of the protein species concept is a basic prerequisite for meaningful quantitative analyses in functional proteomics. In discovery approaches only top-down analyses, separating the protein species before digestion, identification and quantification by two-dimensional gel electrophoresis or protein liquid chromatography, allow the correlation between changes of a biological situation and function. Conclusion To obtain biological relevant information kinetics and systems biology have to be performed at the protein species level, which is the major challenge in proteomics today. PMID:18638390

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.

Sma3s: A universal tool for easy functional annotation of proteomes and transcriptomes.

PubMed

Casimiro-Soriguer, Carlos S; Muñoz-Mérida, Antonio; Pérez-Pulido, Antonio J

2017-06-01

The current cheapening of next-generation sequencing has led to an enormous growth in the number of sequenced genomes and transcriptomes, allowing wet labs to get the sequences from their organisms of study. To make the most of these data, one of the first things that should be done is the functional annotation of the protein-coding genes. But it used to be a slow and tedious step that can involve the characterization of thousands of sequences. Sma3s is an accurate computational tool for annotating proteins in an unattended way. Now, we have developed a completely new version, which includes functionalities that will be of utility for fundamental and applied science. Currently, the results provide functional categories such as biological processes, which become useful for both characterizing particular sequence datasets and comparing results from different projects. But one of the most important implemented innovations is that it has now low computational requirements, and the complete annotation of a simple proteome or transcriptome usually takes around 24 hours in a personal computer. Sma3s has been tested with a large amount of complete proteomes and transcriptomes, and it has demonstrated its potential in health science and other specific projects. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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 Grape Berry Cell Cultures Reveals that Developmentally Regulated Ripening Related Processes Can Be Studied Using Cultured Cells

PubMed Central

Sharathchandra, Ramaschandra G.; Stander, Charmaine; Jacobson, Dan; Ndimba, Bongani; Vivier, Melané A.

2011-01-01

Background This work describes a proteomics profiling method, optimized and applied to berry cell suspensions to evaluate organ-specific cultures as a platform to study grape berry ripening. Variations in berry ripening within a cluster(s) on a vine and in a vineyard are a major impediment towards complete understanding of the functional processes that control ripening, specifically when a characterized and homogenous sample is required. Berry cell suspensions could overcome some of these problems, but their suitability as a model system for berry development and ripening needs to be established first. Methodology/Principal Findings In this study we report on the proteomic evaluation of the cytosolic proteins obtained from synchronized cell suspension cultures that were established from callus lines originating from green, véraison and ripe Vitis vinifera berry explants. The proteins were separated using liquid phase IEF in a Microrotofor cell and SDS PAGE. This method proved superior to gel-based 2DE. Principal component analysis confirmed that biological and technical repeats grouped tightly and importantly, showed that the proteomes of berry cultures originating from the different growth/ripening stages were distinct. A total of twenty six common bands were selected after band matching between different growth stages and twenty two of these bands were positively identified. Thirty two % of the identified proteins are currently annotated as hypothetical. The differential expression profile of the identified proteins, when compared with published literature on grape berry ripening, suggested common trends in terms of relative abundance in the different developmental stages between real berries and cell suspensions. Conclusions The advantages of having suspension cultures that accurately mimic specific developmental stages are profound and could significantly contribute to the study of the intricate regulatory and signaling networks responsible for berry development and ripening. PMID:21379583

Identification and Characterization of Soluble Factors Involved in Delayed Effects of Low Dose Radiation. Final report

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

Baulch, Janet

2013-09-11

This is a 'glue grant' that was part of a DOE Low Dose project entitled 'Identification and Characterization of Soluble Factors Involved in Delayed Effects of Low Dose Radiation'. This collaborative program has involved Drs. David L. Springer from Pacific Northwest National Laboratory (PNNL), John H. Miller from Washington State University, Tri-cities (WSU) and William F. Morgan then from the University of Maryland, Baltimore (UMB). In July 2008, Dr. Morgan moved to PNNL and Dr. Janet E. Baulch became PI for this project at University of Maryland. In November of 2008, a one year extension with no new funds wasmore » requested to complete the proteomic analyses. The project stemmed from studies in the Morgan laboratory demonstrating that genomically unstable cells secret a soluble factor or factors into the culture medium, that cause cytogenetic aberrations and apoptosis in normal parental GM10115 cells. The purpose of this project was to identify the death inducing effect (DIE) factor or factors, estimate their relative abundance, identify the cell signaling pathways involved and finally recapitulate DIE in normal cells by exogenous manipulation of putative DIE factors in culture medium. As reported in detail in the previous progress report, analysis of culture medium from the parental cell line, and stable and unstable clones demonstrated inconsistent proteomic profiles as relate to candidate DIE factors. While the proposed proteomic analyses did not provide information that would allow DIE factors to be identified, the analyses provided another important set of observations. Proteomic analysis suggested that proteins associated with the cellular response to oxidative stress and mitochondrial function were elevated in the medium from unstable clones in a manner consistent with mitochondrial dysfunction. These findings correlate with previous studies of these clones that demonstrated functional differences between the mitochondria of stable and unstable clones. These mitochondrial abnormalities in the unstable clones contributes to oxidative stress.« less

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.

Integrated transcriptomic and proteomic profiling of white spruce stems during the transition from active growth to dormancy.

PubMed

Galindo González, Leonardo M; El Kayal, Walid; Ju, Chelsea J-T; Allen, Carmen C G; King-Jones, Susanne; Cooke, Janice E K

2012-04-01

In the autumn, stems of woody perennials such as forest trees undergo a transition from active growth to dormancy. We used microarray transcriptomic profiling in combination with a proteomics analysis to elucidate processes that occur during this growth-to-dormancy transition in a conifer, white spruce (Picea glauca[Moench] Voss). Several differentially expressed genes were likely associated with the developmental transition that occurs during growth cessation in the cambial zone and the concomitant completion of cell maturation in vascular tissues. Genes encoding for cell wall and membrane biosynthetic enzymes showed transcript abundance patterns consistent with completion of cell maturation, and also of cell wall and membrane modifications potentially enabling cells to withstand the harsh conditions of winter. Several differentially expressed genes were identified that encoded putative regulators of cambial activity, cell development and of the photoperiodic pathway. Reconfiguration of carbon allocation figured centrally in the tree's overwintering preparations. For example, genes associated with carbon-based defences such as terpenoids were down-regulated, while many genes associated with protein-based defences and other stress mitigation mechanisms were up-regulated. Several of these correspond to proteins that were accumulated during the growth-to-dormancy transition, emphasizing the importance of stress protection in the tree's adaptive response to overwintering. © 2011 Blackwell Publishing Ltd.

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

Factors Affecting Cis-Dichloroethene and Vinyl Chloride Biological Transformation Under Anaerobic Conditions

DTIC Science & Technology

2006-05-01

410. 3. Baek, J-M, and C. M. Kenerley. 1998. Detection and enumeration of a genetically modified fungus in soil environments by quantitative...deduced proteome of D. ethenogenes using the complete sequence of the alcohol dehydrogenase with the most similar N-terminus (accession number ZP_00128696...chlorophenol respiration (3 1). Four orfs similru· to VcrC were also found in the deduced proteome of D. ethenogenes (38 - 47 % identity). Two of those are

Genome-wide identification of the subcellular localization of the Escherichia coli B proteome using experimental and computational methods.

PubMed

Han, Mee-Jung; Yun, Hongseok; Lee, Jeong Wook; Lee, Yu Hyun; Lee, Sang Yup; Yoo, Jong-Shin; Kim, Jin Young; Kim, Jihyun F; Hur, Cheol-Goo

2011-04-01

Escherichia coli K-12 and B strains have most widely been employed for scientific studies as well as industrial applications. Recently, the complete genome sequences of two representative descendants of E. coli B strains, REL606 and BL21(DE3), have been determined. Here, we report the subproteome reference maps of E. coli B REL606 by analyzing cytoplasmic, periplasmic, inner and outer membrane, and extracellular proteomes based on the genome information using experimental and computational approaches. Among the total of 3487 spots, 651 proteins including 410 non-redundant proteins were identified and characterized by 2-DE and LC-MS/MS; they include 440 cytoplasmic, 45 periplasmic, 50 inner membrane, 61 outer membrane, and 55 extracellular proteins. In addition, subcellular localizations of all 4205 ORFs of E. coli B were predicted by combined computational prediction methods. The subcellular localizations of 1812 (43.09%) proteins of currently unknown function were newly assigned. The results of computational prediction were also compared with the experimental results, showing that overall precision and recall were 92.16 and 92.16%, respectively. This work represents the most comprehensive analyses of the subproteomes of E. coli B, and will be useful as a reference for proteome profiling studies under various conditions. The complete proteome data are available online (http://ecolib.kaist.ac.kr). Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

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.

A curated gluten protein sequence database to support development of proteomics methods for determination of gluten in gluten-free foods.

PubMed

Bromilow, Sophie; Gethings, Lee A; Buckley, Mike; Bromley, Mike; Shewry, Peter R; Langridge, James I; Clare Mills, E N

2017-06-23

The unique physiochemical properties of wheat gluten enable a diverse range of food products to be manufactured. However, gluten triggers coeliac disease, a condition which is treated using a gluten-free diet. Analytical methods are required to confirm if foods are gluten-free, but current immunoassay-based methods can unreliable and proteomic methods offer an alternative but require comprehensive and well annotated sequence databases which are lacking for gluten. A manually a curated database (GluPro V1.0) of gluten proteins, comprising 630 discrete unique full length protein sequences has been compiled. It is representative of the different types of gliadin and glutenin components found in gluten. An in silico comparison of their coeliac toxicity was undertaken by analysing the distribution of coeliac toxic motifs. This demonstrated that whilst the α-gliadin proteins contained more toxic motifs, these were distributed across all gluten protein sub-types. Comparison of annotations observed using a discovery proteomics dataset acquired using ion mobility MS/MS showed that more reliable identifications were obtained using the GluPro V1.0 database compared to the complete reviewed Viridiplantae database. This highlights the value of a curated sequence database specifically designed to support the proteomic workflows and the development of methods to detect and quantify gluten. We have constructed the first manually curated open-source wheat gluten protein sequence database (GluPro V1.0) in a FASTA format to support the application of proteomic methods for gluten protein detection and quantification. We have also analysed the manually verified sequences to give the first comprehensive overview of the distribution of sequences able to elicit a reaction in coeliac disease, the prevalent form of gluten intolerance. Provision of this database will improve the reliability of gluten protein identification by proteomic analysis, and aid the development of targeted mass spectrometry methods in line with Codex Alimentarius Commission requirements for foods designed to meet the needs of gluten intolerant individuals. Copyright © 2017. Published by Elsevier B.V.

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...

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.

The Successful Diagnosis and Typing of Systemic Amyloidosis Using A Microwave-Assisted Filter-Aided Fast Sample Preparation Method and LC/MS/MS Analysis

PubMed Central

Zou, Lili; Shen, Kaini; Zhong, Dingrong; Zhou, Daobin; Sun, Wei; Li, Jian

2015-01-01

Laser microdissection followed by mass spectrometry has been successfully used for amyloid typing. However, sample contamination can interfere with proteomic analysis, and overnight digestion limits the analytical throughput. Moreover, current quantitative analysis methods are based on the spectrum count, which ignores differences in protein length and may lead to misdiagnoses. Here, we developed a microwave-assisted filter-aided sample preparation (maFASP) method that can efficiently remove contaminants with a 10-kDa cutoff ultrafiltration unit and can accelerate the digestion process with the assistance of a microwave. Additionally, two parameters (P- and D-scores) based on the exponentially modified protein abundance index were developed to define the existence of amyloid deposits and those causative proteins with the greatest abundance. Using our protocol, twenty cases of systemic amyloidosis that were well-typed according to clinical diagnostic standards (training group) and another twenty-four cases without subtype diagnoses (validation group) were analyzed. Using this approach, sample preparation could be completed within four hours. We successfully subtyped 100% of the cases in the training group, and the diagnostic success rate in the validation group was 91.7%. This maFASP-aided proteomic protocol represents an efficient approach for amyloid diagnosis and subtyping, particularly for serum-contaminated samples. PMID:25984759

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

Complete genome sequence and description of Lactococcus garvieae M14 isolated from Algerian fermented milk.

PubMed

Moumene, M; Drissi, F; Croce, O; Djebbari, B; Robert, C; Angelakis, E; Benouareth, D E; Raoult, D; Merhej, V

2016-03-01

We describe using a polyphasic approach that combines proteomic by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF) analysis, genomic data and phenotypic characterization the features of Lactococcus garvieae strain M14 newly isolated from the fermented milk (known as raib) of an Algerian cow. The 2 188 835 bp containing genome sequence displays a metabolic capacity to form acid fermentation that is very useful for industrial applications and encodes for two bacteriocins responsible for its eventual bioprotective properties.

Detailed analysis of the plasma extracellular vesicle proteome after separation from lipoproteins.

PubMed

Karimi, Nasibeh; Cvjetkovic, Aleksander; Jang, Su Chul; Crescitelli, Rossella; Hosseinpour Feizi, Mohammad Ali; Nieuwland, Rienk; Lötvall, Jan; Lässer, Cecilia

2018-02-13

The isolation of extracellular vesicles (EVs) from blood is of great importance to understand the biological role of circulating EVs and to develop EVs as biomarkers of disease. Due to the concurrent presence of lipoprotein particles, however, blood is one of the most difficult body fluids to isolate EVs from. The aim of this study was to develop a robust method to isolate and characterise EVs from blood with minimal contamination by plasma proteins and lipoprotein particles. Plasma and serum were collected from healthy subjects, and EVs were isolated by size-exclusion chromatography (SEC), with most particles being present in fractions 8-12, while the bulk of the plasma proteins was present in fractions 11-28. Vesicle markers peaked in fractions 7-11; however, the same fractions also contained lipoprotein particles. The purity of EVs was improved by combining a density cushion with SEC to further separate lipoprotein particles from the vesicles, which reduced the contamination of lipoprotein particles by 100-fold. Using this novel isolation procedure, a total of 1187 proteins were identified in plasma EVs by mass spectrometry, of which several proteins are known as EV-associated proteins but have hitherto not been identified in the previous proteomic studies of plasma EVs. This study shows that SEC alone is unable to completely separate plasma EVs from lipoprotein particles. However, combining SEC with a density cushion significantly improved the separation of EVs from lipoproteins and allowed for a detailed analysis of the proteome of plasma EVs, thus making blood a viable source for EV biomarker discovery.

Proteomic analysis reveals metabolic and regulatory systems involved in the syntrophic and axenic lifestyle of Syntrophomonas wolfei

DOE PAGES

Sieber, Jessica R.; Crable, Bryan R.; Sheik, Cody S.; ...

2015-02-11

We report that microbial syntrophy is a vital metabolic interaction necessary for the complete oxidation of organic biomass to methane in all-anaerobic ecosystems. However, this process is thermodynamically constrained and represents an ecosystem-level metabolic bottleneck. To gain insight into the physiology of this process, a shotgun proteomics approach was used to quantify the protein landscape of the model syntrophic metabolizer, Syntrophomonas wolfei, grown axenically and syntrophically with Methanospirillum hungatei. Remarkably, the abundance of most proteins as represented by normalized spectral abundance factor (NSAF) value changed very little between the pure and coculture growth conditions. Among the most abundant proteins detectedmore » were GroEL and GroES chaperonins, a small heat shock protein, and proteins involved in electron transfer, beta-oxidation, and ATP synthesis. Several putative energy conservation enzyme systems that utilize NADH and ferredoxin were present. The abundance of an EtfAB2 and the membrane-bound iron-sulfur oxidoreductase (Swol_0698 gene product) delineated a potential conduit for electron transfer between acyl-CoA dehydrogenases and membrane redox carriers. Proteins detected only when S. wolfei was grown with M. hungatei included a zinc-dependent dehydrogenase with a GroES domain, whose gene is present in genomes in many organisms capable of syntrophy, and transcriptional regulators responsive to environmental stimuli or the physiological status of the cell. In conclusion, the proteomic analysis revealed an emphasis on macromolecular stability and energy metabolism by S. wolfei and presence of regulatory mechanisms responsive to external stimuli and cellular physiological status.« less

Proteomic analysis reveals metabolic and regulatory systems involved in the syntrophic and axenic lifestyle of Syntrophomonas wolfei

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

Sieber, Jessica R.; Crable, Bryan R.; Sheik, Cody S.

We report that microbial syntrophy is a vital metabolic interaction necessary for the complete oxidation of organic biomass to methane in all-anaerobic ecosystems. However, this process is thermodynamically constrained and represents an ecosystem-level metabolic bottleneck. To gain insight into the physiology of this process, a shotgun proteomics approach was used to quantify the protein landscape of the model syntrophic metabolizer, Syntrophomonas wolfei, grown axenically and syntrophically with Methanospirillum hungatei. Remarkably, the abundance of most proteins as represented by normalized spectral abundance factor (NSAF) value changed very little between the pure and coculture growth conditions. Among the most abundant proteins detectedmore » were GroEL and GroES chaperonins, a small heat shock protein, and proteins involved in electron transfer, beta-oxidation, and ATP synthesis. Several putative energy conservation enzyme systems that utilize NADH and ferredoxin were present. The abundance of an EtfAB2 and the membrane-bound iron-sulfur oxidoreductase (Swol_0698 gene product) delineated a potential conduit for electron transfer between acyl-CoA dehydrogenases and membrane redox carriers. Proteins detected only when S. wolfei was grown with M. hungatei included a zinc-dependent dehydrogenase with a GroES domain, whose gene is present in genomes in many organisms capable of syntrophy, and transcriptional regulators responsive to environmental stimuli or the physiological status of the cell. In conclusion, the proteomic analysis revealed an emphasis on macromolecular stability and energy metabolism by S. wolfei and presence of regulatory mechanisms responsive to external stimuli and cellular physiological status.« less

Repeatability and Reproducibility in Proteomic Identifications by Liquid Chromatography—Tandem Mass Spectrometry

PubMed Central

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

2009-01-01

The complexity of proteomic instrumentation for LC-MS/MS introduces many possible sources of variability. Data-dependent sampling of peptides constitutes a stochastic element at the heart of discovery proteomics. Although this variation impacts the identification of peptides, proteomic identifications are far from completely random. In this study, we analyzed interlaboratory data sets from the NCI Clinical Proteomic Technology Assessment for Cancer to examine repeatability and reproducibility in peptide and protein identifications. Included data spanned 144 LC-MS/MS experiments on four Thermo LTQ and four Orbitrap instruments. Samples included yeast lysate, the NCI-20 defined dynamic range protein mix, and the Sigma UPS 1 defined equimolar protein mix. Some of our findings reinforced conventional wisdom, such as repeatability and reproducibility being higher for proteins than for peptides. Most lessons from the data, however, were more subtle. Orbitraps proved capable of higher repeatability and reproducibility, but aberrant performance occasionally erased these gains. Even the simplest protein digestions yielded more peptide ions than LC-MS/MS could identify during a single experiment. We observed that peptide lists from pairs of technical replicates overlapped by 35–60%, giving a range for peptide-level repeatability in these experiments. Sample complexity did not appear to affect peptide identification repeatability, even as numbers of identified spectra changed by an order of magnitude. Statistical analysis of protein spectral counts revealed greater stability across technical replicates for Orbitraps, making them superior to LTQ instruments for biomarker candidate discovery. The most repeatable peptides were those corresponding to conventional tryptic cleavage sites, those that produced intense MS signals, and those that resulted from proteins generating many distinct peptides. Reproducibility among different instruments of the same type lagged behind repeatability of technical replicates on a single instrument by several percent. These findings reinforce the importance of evaluating repeatability as a fundamental characteristic of analytical technologies. PMID:19921851

Proteome-Scale Human Interactomics.

PubMed

Luck, Katja; Sheynkman, Gloria M; Zhang, Ivy; Vidal, Marc

2017-05-01

Cellular functions are mediated by complex interactome networks of physical, biochemical, and functional interactions between DNA sequences, RNA molecules, proteins, lipids, and small metabolites. A thorough understanding of cellular organization requires accurate and relatively complete models of interactome networks at proteome scale. The recent publication of four human protein-protein interaction (PPI) maps represents a technological breakthrough and an unprecedented resource for the scientific community, heralding a new era of proteome-scale human interactomics. Our knowledge gained from these and complementary studies provides fresh insights into the opportunities and challenges when analyzing systematically generated interactome data, defines a clear roadmap towards the generation of a first reference interactome, and reveals new perspectives on the organization of cellular life. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2013-01-01

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

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.

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

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.

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.

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 .

Exploratory research into pathogen surface interactions.

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

Sinclair, Michael B.; Lane, Todd W.; Jones, Howland D. T.

2006-02-01

In this short-duration project the research team was able to achieve growth of both drinking water biofilms and monospecific biofilms of Legionella pneurnophila. Preliminary comparative proteomic analyses were carried out on planktonic and biofilm-associated Legionella. After delay for completion of permitting and review by the director of the National Institutes for Allergy and Infectious Disease, the Utah 112 strain of Francisella novicida was obtained and preliminary culture and comparative proteomic analyses were carried out. Comprehensive literature searches and data mining were carried out on all research topics.

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…

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.

Arbuscular mycorrhizal symbiosis affects the grain proteome of Zea mays: a field study

PubMed Central

Bona, Elisa; Scarafoni, Alessio; Marsano, Francesco; Boatti, Lara; Copetta, Andrea; Massa, Nadia; Gamalero, Elisa; D’Agostino, Giovanni; Cesaro, Patrizia; Cavaletto, Maria; Berta, Graziella

2016-01-01

Maize is one of the most important crops worldwide and is strongly dependent on arbuscular mycorrhiza (AM) fungi, organisms that form a mutualistic association with land plants. In maize, AM symbiosis enhances spike dry weight, spike length, spike circumference, and the dry weight and dimensions of the grain. Notwithstanding its ubiquitous nature, the detailed relationship between AM fungal colonization and plant development is not completely understood. To facilitate a better understanding of the effects of AM fungi on plants, the work reported here assessed the effects of a consortium of AM fungi on the kernel proteome of maize, cultivated in open-field conditions. To our knowledge, this is the first report of the modulation of a plant seed proteome following AM fungal inoculation in the field. Here, it was found that AM fungi modify the maize seed proteome by up-regulating enzymes involved in energetic metabolism, embryo development, nucleotide metabolism, seed storage and stress responses. PMID:27216714

Arbuscular mycorrhizal symbiosis affects the grain proteome of Zea mays: a field study.

PubMed

Bona, Elisa; Scarafoni, Alessio; Marsano, Francesco; Boatti, Lara; Copetta, Andrea; Massa, Nadia; Gamalero, Elisa; D'Agostino, Giovanni; Cesaro, Patrizia; Cavaletto, Maria; Berta, Graziella

2016-05-24

Maize is one of the most important crops worldwide and is strongly dependent on arbuscular mycorrhiza (AM) fungi, organisms that form a mutualistic association with land plants. In maize, AM symbiosis enhances spike dry weight, spike length, spike circumference, and the dry weight and dimensions of the grain. Notwithstanding its ubiquitous nature, the detailed relationship between AM fungal colonization and plant development is not completely understood. To facilitate a better understanding of the effects of AM fungi on plants, the work reported here assessed the effects of a consortium of AM fungi on the kernel proteome of maize, cultivated in open-field conditions. To our knowledge, this is the first report of the modulation of a plant seed proteome following AM fungal inoculation in the field. Here, it was found that AM fungi modify the maize seed proteome by up-regulating enzymes involved in energetic metabolism, embryo development, nucleotide metabolism, seed storage and stress responses.

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

PubMed Central

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

2014-01-01

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

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 unique peptidome: Taxon-specific tryptic peptides as biomarkers for targeted metaproteomics.

PubMed

Mesuere, Bart; Van der Jeugt, Felix; Devreese, Bart; Vandamme, Peter; Dawyndt, Peter

2016-09-01

The Unique Peptide Finder (http://unipept.ugent.be/peptidefinder) is an interactive web application to quickly hunt for tryptic peptides that are unique to a particular species, genus, or any other taxon. Biodiversity within the target taxon is represented by a set of proteomes selected from a monthly updated list of complete and nonredundant UniProt proteomes, supplemented with proprietary proteomes loaded into persistent local browser storage. The software computes and visualizes pan and core peptidomes as unions and intersections of tryptic peptides occurring in the selected proteomes. In addition, it also computes and displays unique peptidomes as the set of all tryptic peptides that occur in all selected proteomes but not in any UniProt record not assigned to the target taxon. As a result, the unique peptides can serve as robust biomarkers for the target taxon, for example, in targeted metaproteomics studies. Computations are extremely fast since they are underpinned by the Unipept database, the lowest common ancestor algorithm implemented in Unipept and modern web technologies that facilitate in-browser data storage and parallel processing. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

JVirGel 2.0: computational prediction of proteomes separated via two-dimensional gel electrophoresis under consideration of membrane and secreted proteins.

PubMed

Hiller, Karsten; Grote, Andreas; Maneck, Matthias; Münch, Richard; Jahn, Dieter

2006-10-01

After the publication of JVirGel 1.0 in 2003 we got many requests and suggestions from the proteomics community to further improve the performance of the software and to add additional useful new features. The integration of the PrediSi algorithm for the prediction of signal peptides for the Sec-dependent protein export into JVirGel 2.0 allows the exclusion of most exported preproteins from calculated proteomic maps and provides the basis for the calculation of Sec-based secretomes. A tool for the identification of transmembrane helices carrying proteins (JCaMelix) and the prediction of the corresponding membrane proteome was added. Finally, in order to directly compare experimental and calculated proteome data, a function to overlay and evaluate predicted and experimental two-dimensional gels was included. JVirGel 2.0 is freely available as precompiled package for the installation on Windows or Linux operating systems. Furthermore, there is a completely platform-independent Java version available for download. Additionally, we provide a Java Server Pages based version of JVirGel 2.0 which can be operated in nearly all web browsers. All versions are accessible at http://www.jvirgel.de

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

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

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

2009-12-01

In the past 10 years, we have witnessed remarkable advances in the field of plant molecular biology. The rapid development of proteomic technologies and the speed with which these techniques have been applied to the field have altered our perception of how we can analyze proteins in complex systems. At nearly the same time, the availability of the complete genome for the model plant Arabidopsis thaliana was released; this effort provides an unsurpassed resource for the identification of proteins when researchers use MS to analyze plant samples. Recognizing the growth in this area, the Multinational Arabidopsis Steering Committee (MASC) establishedmore » a subcommittee for A. thaliana proteomics in 2006 with the objective of consolidating databases, technique standards, and experimentally validated candidate genes and functions. Since the establishment of the Multinational Arabidopsis Steering Subcommittee for Proteomics (MASCP), many new approaches and resources have become available. Recently, the subcommittee established a webpage to consolidate this information (www.masc-proteomics.org). It includes links to plant proteomic databases, general information about proteomic techniques, meeting information, a summary of proteomic standards, and other relevant resources. Altogether, this website provides a useful resource for the Arabidopsis proteomics community. In the future, the website will host discussions and investigate the cross-linking of databases. The subcommittee members have extensive experience in arabidopsis proteomics and collectively have produced some of the most extensive proteomics data sets for this model plant (Table S1 in the Supporting Information has a list of resources). The largest collection of proteomics data from a single study in A. thaliana was assembled into an accessible database (AtProteome; http://fgcz-atproteome.unizh.ch/index.php) and was recently published by the Baginsky lab.1 The database provides links to major Arabidopsis online resources, and raw data have been deposited in PRIDE and PRIDE BioMart. Included in this database is an Arabidopsis proteome map that provides evidence for the expression of {approx}50% of all predicted gene models, including several alternative gene models that are not represented in The Arabidopsis Information Resource (TAIR) protein database. A set of organ-specific biomarkers is provided, as well as organ-specific proteotypic peptides for 4105 proteins that can be used to facilitate targeted quantitative proteomic surveys. In the future, the AtProteome database will be linked to additional existing resources developed by MASCP members, such as PPDB, ProMEX, and SUBA. The most comprehensive study on the Arabidopsis chloroplast proteome, which includes information on chloroplast sorting signals, posttranslational modifications (PTMs), and protein abundances (analyzed by high-accuracy MS [Orbitrap]), was recently published by the van Wijk lab.2 These and previous data are available via the plant proteome database (PPDB; http://ppdb.tc.cornell.edu) for A. thaliana and maize. PPDB provides genome-wide experimental and functional characterization of the A. thaliana and maize proteomes, including PTMs and subcellular localization information, with an emphasis on leaf and plastid proteins. Maize and Arabidopsis proteome entries are directly linked via internal BLAST alignments within PPDB. Direct links for each protein to TAIR, SUBA, ProMEX, and other resources are also provided.« less

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.

PRIDE Inspector Toolsuite: Moving Toward a Universal Visualization Tool for Proteomics Data Standard Formats and Quality Assessment of ProteomeXchange Datasets.

PubMed

Perez-Riverol, Yasset; Xu, Qing-Wei; Wang, Rui; Uszkoreit, Julian; Griss, Johannes; Sanchez, Aniel; Reisinger, Florian; Csordas, Attila; Ternent, Tobias; Del-Toro, Noemi; Dianes, Jose A; Eisenacher, Martin; Hermjakob, Henning; Vizcaíno, Juan Antonio

2016-01-01

The original PRIDE Inspector tool was developed as an open source standalone tool to enable the visualization and validation of mass-spectrometry (MS)-based proteomics data before data submission or already publicly available in the Proteomics Identifications (PRIDE) database. The initial implementation of the tool focused on visualizing PRIDE data by supporting the PRIDE XML format and a direct access to private (password protected) and public experiments in PRIDE.The ProteomeXchange (PX) Consortium has been set up to enable a better integration of existing public proteomics repositories, maximizing its benefit to the scientific community through the implementation of standard submission and dissemination pipelines. Within the Consortium, PRIDE is focused on supporting submissions of tandem MS data. The increasing use and popularity of the new Proteomics Standards Initiative (PSI) data standards such as mzIdentML and mzTab, and the diversity of workflows supported by the PX resources, prompted us to design and implement a new suite of algorithms and libraries that would build upon the success of the original PRIDE Inspector and would enable users to visualize and validate PX "complete" submissions. The PRIDE Inspector Toolsuite supports the handling and visualization of different experimental output files, ranging from spectra (mzML, mzXML, and the most popular peak lists formats) and peptide and protein identification results (mzIdentML, PRIDE XML, mzTab) to quantification data (mzTab, PRIDE XML), using a modular and extensible set of open-source, cross-platform libraries. We believe that the PRIDE Inspector Toolsuite represents a milestone in the visualization and quality assessment of proteomics data. It is freely available at http://github.com/PRIDE-Toolsuite/. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

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.

Immobilized monolithic enzymatic reactor and its application for analysis of in-vitro fertilization media samples.

PubMed

Chen, Wei-Qiang; Obermayr, Philipp; Černigoj, Urh; Vidič, Jana; Panić-Janković, Tanta; Mitulović, Goran

2017-11-01

Classical proteomics approaches involve enzymatic hydrolysis of proteins (either separated by polyacrylamide gels or in solution) followed by peptide identification using LC-MS/MS analysis. This method requires normally more than 16 h to complete. In the case of clinical analysis, it is of the utmost importance to provide fast and reproducible analysis with minimal manual sample handling. Herein we report the method development for online protein digestion on immobilized monolithic enzymatic reactors (IMER) to accelerate protein digestion, reduce manual sample handling, and provide reproducibility to the digestion process in clinical laboratory. An integrated online digestion and separation method using monolithic immobilized enzymatic reactor was developed and applied to digestion and separation of in-vitro-fertilization media. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Nipple aspirate fluid-A liquid biopsy for diagnosing breast health.

PubMed

Shaheed, Sadr-Ul; Tait, Catherine; Kyriacou, Kyriacos; Mullarkey, Joanne; Burrill, Wayne; Patterson, Laurence H; Linforth, Richard; Salhab, Mohamed; Sutton, Chris W

2017-09-01

Nipple secretions are protein-rich and a potential source of breast cancer biomarkers for breast cancer screening. Previous studies of specific proteins have shown limited correlation with clinicopathological features. Our aim, in this pilot study, was to investigate the intra- and interpatient protein composition of nipple secretions and the implications for their use as liquid biopsies. Matched pairs of nipple discharge/nipple aspirate fluid (NAF, n = 15) were characterized for physicochemical properties and SDS-PAGE. Four pairs were selected for semiquantitative proteomic profiling and trypsin-digested peptides analyzed using 2D-LC Orbitrap Fusion MS. The resulting data were subject to bioinformatics analysis and statistical evaluation for functional significance. A total of 1990 unique proteins were identified many of which are established cancer-associated markers. Matched pairs shared the greatest similarity (average Pearson correlation coefficient of 0.94), but significant variations between individuals were observed. This was the most complete proteomic study of nipple discharge/nipple aspirate fluid to date providing a valuable source for biomarker discovery. The high level of milk proteins in healthy volunteer samples compared to the cancer patients was associated with galactorrhoea. Using matched pairs increased confidence in patient-specific protein levels but changes relating to cancer stage require investigation of a larger cohort. © 2017 The Authors. PROTEOMICS-Clinical Applications published by WILEY-VCH Verlag GmbH & Co. KGaA.

Proteome analysis reveals differential expression of proteins involved in triacylglycerol accumulation by Rhodococcus jostii RHA1 after addition of methyl viologen.

PubMed

Dávila Costa, José Sebastián; Silva, Roxana A; Leichert, Lars; Alvarez, Héctor M

2017-03-01

Rhodococcus jostii RHA1 is able to degrade toxic compounds and accumulate high amounts of triacylglycerols (TAG) upon nitrogen starvation. These NADPH-dependent processes are essential for the adaptation of rhodococci to fluctuating environmental conditions. In this study, we used an MS-based, label-free and quantitative proteomic approach to better understand the integral response of R. jostii RHA1 to the presence of methyl viologen (MV) in relation to the synthesis and accumulation of TAG. The addition of MV promoted a decrease of TAG accumulation in comparison to cells cultivated under nitrogen-limiting conditions in the absence of this pro-oxidant. Proteomic analyses revealed that the abundance of key proteins of fatty acid biosynthesis, the Kennedy pathway, glyceroneogenesis and methylmalonyl-CoA pathway, among others, decreased in the presence of MV. In contrast, some proteins involved in lipolysis and β-oxidation of fatty acids were upregulated. Some metabolic pathways linked to the synthesis of NADPH remained activated during oxidative stress as well as under nitrogen starvation conditions. Additionally, exposure to MV resulted in the activation of complete antioxidant machinery comprising superoxide dismutases, catalases, mycothiol biosynthesis, mycothione reductase and alkyl hydroperoxide reductases, among others. Our study suggests that oxidative stress response affects TAG accumulation under nitrogen-limiting conditions through programmed molecular mechanisms when both stresses occur simultaneously.

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.

Antiandrogens act as selective androgen receptor modulators at the proteome level in prostate cancer cells.

PubMed

Brooke, Greg N; Gamble, Simon C; Hough, Michael A; Begum, Shajna; Dart, D Alwyn; Odontiadis, Michael; Powell, Sue M; Fioretti, Flavia M; Bryan, Rosie A; Waxman, Jonathan; Wait, Robin; Bevan, Charlotte L

2015-05-01

Current therapies for prostate cancer include antiandrogens, inhibitory ligands of the androgen receptor, which repress androgen-stimulated growth. These include the selective androgen receptor modulators cyproterone acetate and hydroxyflutamide and the complete antagonist bicalutamide. Their activity is partly dictated by the presence of androgen receptor mutations, which are commonly detected in patients who relapse while receiving antiandrogens, i.e. in castrate-resistant prostate cancer. To characterize the early proteomic response to these antiandrogens we used the LNCaP prostate cancer cell line, which harbors the androgen receptor mutation most commonly detected in castrate-resistant tumors (T877A), analyzing alterations in the proteome, and comparing these to the effect of these therapeutics upon androgen receptor activity and cell proliferation. The majority are regulated post-transcriptionally, possibly via nongenomic androgen receptor signaling. Differences detected between the exposure groups demonstrate subtle changes in the biological response to each specific ligand, suggesting a spectrum of agonistic and antagonistic effects dependent on the ligand used. Analysis of the crystal structures of the AR in the presence of cyproterone acetate, hydroxyflutamide, and DHT identified important differences in the orientation of key residues located in the AF-2 and BF-3 protein interaction surfaces. This further implies that although there is commonality in the growth responses between androgens and those antiandrogens that stimulate growth in the presence of a mutation, there may also be influential differences in the growth pathways stimulated by the different ligands. This therefore has implications for prostate cancer treatment because tumors may respond differently dependent upon which mutation is present and which ligand is activating growth, also for the design of selective androgen receptor modulators, which aim to elicit differential proteomic responses dependent upon cellular context. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Antiandrogens Act as Selective Androgen Receptor Modulators at the Proteome Level in Prostate Cancer Cells*

PubMed Central

Brooke, Greg N.; Gamble, Simon C.; Hough, Michael A.; Begum, Shajna; Dart, D. Alwyn; Odontiadis, Michael; Powell, Sue M.; Fioretti, Flavia M.; Bryan, Rosie A.; Waxman, Jonathan; Wait, Robin; Bevan, Charlotte L.

2015-01-01

Current therapies for prostate cancer include antiandrogens, inhibitory ligands of the androgen receptor, which repress androgen-stimulated growth. These include the selective androgen receptor modulators cyproterone acetate and hydroxyflutamide and the complete antagonist bicalutamide. Their activity is partly dictated by the presence of androgen receptor mutations, which are commonly detected in patients who relapse while receiving antiandrogens, i.e. in castrate-resistant prostate cancer. To characterize the early proteomic response to these antiandrogens we used the LNCaP prostate cancer cell line, which harbors the androgen receptor mutation most commonly detected in castrate-resistant tumors (T877A), analyzing alterations in the proteome, and comparing these to the effect of these therapeutics upon androgen receptor activity and cell proliferation. The majority are regulated post-transcriptionally, possibly via nongenomic androgen receptor signaling. Differences detected between the exposure groups demonstrate subtle changes in the biological response to each specific ligand, suggesting a spectrum of agonistic and antagonistic effects dependent on the ligand used. Analysis of the crystal structures of the AR in the presence of cyproterone acetate, hydroxyflutamide, and DHT identified important differences in the orientation of key residues located in the AF-2 and BF-3 protein interaction surfaces. This further implies that although there is commonality in the growth responses between androgens and those antiandrogens that stimulate growth in the presence of a mutation, there may also be influential differences in the growth pathways stimulated by the different ligands. This therefore has implications for prostate cancer treatment because tumors may respond differently dependent upon which mutation is present and which ligand is activating growth, also for the design of selective androgen receptor modulators, which aim to elicit differential proteomic responses dependent upon cellular context. PMID:25693800

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

2016 update of the PRIDE database and its related tools

PubMed Central

Vizcaíno, Juan Antonio; Csordas, Attila; del-Toro, Noemi; Dianes, José A.; Griss, Johannes; Lavidas, Ilias; Mayer, Gerhard; Perez-Riverol, Yasset; Reisinger, Florian; Ternent, Tobias; Xu, Qing-Wei; Wang, Rui; Hermjakob, Henning

2016-01-01

The PRoteomics IDEntifications (PRIDE) database is one of the world-leading data repositories of mass spectrometry (MS)-based proteomics data. Since the beginning of 2014, PRIDE Archive (http://www.ebi.ac.uk/pride/archive/) is the new PRIDE archival system, replacing the original PRIDE database. Here we summarize the developments in PRIDE resources and related tools since the previous update manuscript in the Database Issue in 2013. PRIDE Archive constitutes a complete redevelopment of the original PRIDE, comprising a new storage backend, data submission system and web interface, among other components. PRIDE Archive supports the most-widely used PSI (Proteomics Standards Initiative) data standard formats (mzML and mzIdentML) and implements the data requirements and guidelines of the ProteomeXchange Consortium. The wide adoption of ProteomeXchange within the community has triggered an unprecedented increase in the number of submitted data sets (around 150 data sets per month). We outline some statistics on the current PRIDE Archive data contents. We also report on the status of the PRIDE related stand-alone tools: PRIDE Inspector, PRIDE Converter 2 and the ProteomeXchange submission tool. Finally, we will give a brief update on the resources under development ‘PRIDE Cluster’ and ‘PRIDE Proteomes’, which provide a complementary view and quality-scored information of the peptide and protein identification data available in PRIDE Archive. PMID:26527722

Characterization of the rat cerebrospinal fluid proteome following acute cerebral ischemia using an aptamer-based proteomic technology.

PubMed

Simats, Alba; García-Berrocoso, Teresa; Ramiro, Laura; Giralt, Dolors; Gill, Natalia; Penalba, Anna; Bustamante, Alejandro; Rosell, Anna; Montaner, Joan

2018-05-21

The limited accessibility to the brain has turned the cerebrospinal fluid (CSF) into a valuable source that may contribute to the complete understanding of the stroke pathophysiology. Here we have described the CSF proteome in the hyper-acute phase of cerebral ischemia by performing an aptamer-based proteomic assay (SOMAscan) in CSF samples collected before and 30 min after male Wistar rats had undergone a 90 min Middle Cerebral Artery Occlusion (MCAO) or sham-surgery. Proteomic results indicated that cerebral ischemia acutely increased the CSF levels of 716 proteins, mostly overrepresented in leukocyte chemotaxis and neuronal death processes. Seven promising candidates were further evaluated in rat plasma and brain (CKB, CaMK2A, CaMK2B, CaMK2D, PDXP, AREG, CMPK). The 3 CaMK2 family-members and CMPK early decreased in the infarcted brain area and, together with AREG, co-localized with neurons. Conversely, CKB levels remained consistent after the insult and specifically matched with astrocytes. Further exploration of these candidates in human plasma revealed the potential of CKB and CMPK to diagnose stroke, while CaMK2B and CMPK resulted feasible biomarkers of functional stroke outcome. Our findings provided insights into the CSF proteome following cerebral ischemia and identified new outstanding proteins that might be further considered as potential biomarkers of stroke.

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.

Geena 2, improved automated analysis of MALDI/TOF mass spectra.

PubMed

Romano, Paolo; Profumo, Aldo; Rocco, Mattia; Mangerini, Rosa; Ferri, Fabio; Facchiano, Angelo

2016-03-02

Mass spectrometry (MS) is producing high volumes of data supporting oncological sciences, especially for translational research. Most of related elaborations can be carried out by combining existing tools at different levels, but little is currently available for the automation of the fundamental steps. For the analysis of MALDI/TOF spectra, a number of pre-processing steps are required, including joining of isotopic abundances for a given molecular species, normalization of signals against an internal standard, background noise removal, averaging multiple spectra from the same sample, and aligning spectra from different samples. In this paper, we present Geena 2, a public software tool for the automated execution of these pre-processing steps for MALDI/TOF spectra. Geena 2 has been developed in a Linux-Apache-MySQL-PHP web development environment, with scripts in PHP and Perl. Input and output are managed as simple formats that can be consumed by any database system and spreadsheet software. Input data may also be stored in a MySQL database. Processing methods are based on original heuristic algorithms which are introduced in the paper. Three simple and intuitive web interfaces are available: the Standard Search Interface, which allows a complete control over all parameters, the Bright Search Interface, which leaves to the user the possibility to tune parameters for alignment of spectra, and the Quick Search Interface, which limits the number of parameters to a minimum by using default values for the majority of parameters. Geena 2 has been utilized, in conjunction with a statistical analysis tool, in three published experimental works: a proteomic study on the effects of long-term cryopreservation on the low molecular weight fraction of serum proteome, and two retrospective serum proteomic studies, one on the risk of developing breat cancer in patients affected by gross cystic disease of the breast (GCDB) and the other for the identification of a predictor of breast cancer mortality following breast cancer surgery, whose results were validated by ELISA, a completely alternative method. Geena 2 is a public tool for the automated pre-processing of MS data originated by MALDI/TOF instruments, with a simple and intuitive web interface. It is now under active development for the inclusion of further filtering options and for the adoption of standard formats for MS spectra.

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

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.

Single-molecule protein sequencing through fingerprinting: computational assessment

NASA Astrophysics Data System (ADS)

Yao, Yao; Docter, Margreet; van Ginkel, Jetty; de Ridder, Dick; Joo, Chirlmin

2015-10-01

Proteins are vital in all biological systems as they constitute the main structural and functional components of cells. Recent advances in mass spectrometry have brought the promise of complete proteomics by helping draft the human proteome. Yet, this commonly used protein sequencing technique has fundamental limitations in sensitivity. Here we propose a method for single-molecule (SM) protein sequencing. A major challenge lies in the fact that proteins are composed of 20 different amino acids, which demands 20 molecular reporters. We computationally demonstrate that it suffices to measure only two types of amino acids to identify proteins and suggest an experimental scheme using SM fluorescence. When achieved, this highly sensitive approach will result in a paradigm shift in proteomics, with major impact in the biological and medical sciences.

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.

Phylogenetic Tracings of Proteome Size Support the Gradual Accretion of Protein Structural Domains and the Early Origin of Viruses from Primordial Cells

PubMed Central

Nasir, Arshan; Kim, Kyung Mo; Caetano-Anollés, Gustavo

2017-01-01

Untangling the origin and evolution of viruses remains a challenging proposition. We recently studied the global distribution of protein domain structures in thousands of completely sequenced viral and cellular proteomes with comparative genomics, phylogenomics, and multidimensional scaling methods. A tree of life describing the evolution of proteomes revealed viruses emerging from the base of the tree as a fourth supergroup of life. A tree of domains indicated an early origin of modern viral lineages from ancient cells that co-existed with the cellular ancestors. However, it was recently argued that the rooting of our trees and the basal placement of viruses was artifactually induced by small genome (proteome) size. Here we show that these claims arise from misunderstanding and misinterpretations of cladistic methodology. Trees are reconstructed unrooted, and thus, their topologies cannot be distorted a posteriori by the rooting methodology. Tracing proteome size in trees and multidimensional views of evolutionary relationships as well as tests of leaf stability and exclusion/inclusion of taxa demonstrated that the smallest proteomes were neither attracted toward the root nor caused any topological distortions of the trees. Simulations confirmed that taxa clustering patterns were independent of proteome size and were determined by the presence of known evolutionary relatives in data matrices, highlighting the need for broader taxon sampling in phylogeny reconstruction. Instead, phylogenetic tracings of proteome size revealed a slowdown in innovation of the structural domain vocabulary and four regimes of allometric scaling that reflected a Heaps law. These regimes explained increasing economies of scale in the evolutionary growth and accretion of kernel proteome repertoires of viruses and cellular organisms that resemble growth of human languages with limited vocabulary sizes. Results reconcile dynamic and static views of domain frequency distributions that are consistent with the axiom of spatiotemporal continuity that is tenet of evolutionary thinking. PMID:28690608

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.

Proteome-wide identification of predominant subcellular protein localizations in a bacterial model organism.

PubMed

Stekhoven, Daniel J; Omasits, Ulrich; Quebatte, Maxime; Dehio, Christoph; Ahrens, Christian H

2014-03-17

Proteomics data provide unique insights into biological systems, including the predominant subcellular localization (SCL) of proteins, which can reveal important clues about their functions. Here we analyzed data of a complete prokaryotic proteome expressed under two conditions mimicking interaction of the emerging pathogen Bartonella henselae with its mammalian host. Normalized spectral count data from cytoplasmic, total membrane, inner and outer membrane fractions allowed us to identify the predominant SCL for 82% of the identified proteins. The spectral count proportion of total membrane versus cytoplasmic fractions indicated the propensity of cytoplasmic proteins to co-fractionate with the inner membrane, and enabled us to distinguish cytoplasmic, peripheral inner membrane and bona fide inner membrane proteins. Principal component analysis and k-nearest neighbor classification training on selected marker proteins or predominantly localized proteins, allowed us to determine an extensive catalog of at least 74 expressed outer membrane proteins, and to extend the SCL assignment to 94% of the identified proteins, including 18% where in silico methods gave no prediction. Suitable experimental proteomics data combined with straightforward computational approaches can thus identify the predominant SCL on a proteome-wide scale. Finally, we present a conceptual approach to identify proteins potentially changing their SCL in a condition-dependent fashion. The work presented here describes the first prokaryotic proteome-wide subcellular localization (SCL) dataset for the emerging pathogen B. henselae (Bhen). The study indicates that suitable subcellular fractionation experiments combined with straight-forward computational analysis approaches assessing the proportion of spectral counts observed in different subcellular fractions are powerful for determining the predominant SCL of a large percentage of the experimentally observed proteins. This includes numerous cases where in silico prediction methods do not provide any prediction. Avoiding a treatment with harsh conditions, cytoplasmic proteins tend to co-fractionate with proteins of the inner membrane fraction, indicative of close functional interactions. The spectral count proportion (SCP) of total membrane versus cytoplasmic fractions allowed us to obtain a good indication about the relative proximity of individual protein complex members to the inner membrane. Using principal component analysis and k-nearest neighbor approaches, we were able to extend the percentage of proteins with a predominant experimental localization to over 90% of all expressed proteins and identified a set of at least 74 outer membrane (OM) proteins. In general, OM proteins represent a rich source of candidates for the development of urgently needed new therapeutics in combat of resurgence of infectious disease and multi-drug resistant bacteria. Finally, by comparing the data from two infection biology relevant conditions, we conceptually explore methods to identify and visualize potential candidates that may partially change their SCL in these different conditions. The data are made available to researchers as a SCL compendium for Bhen and as an assistance in further improving in silico SCL prediction algorithms. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

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.

Pse-Analysis: a python package for DNA/RNA and protein/ peptide sequence analysis based on pseudo components and kernel methods.

PubMed

Liu, Bin; Wu, Hao; Zhang, Deyuan; Wang, Xiaolong; Chou, Kuo-Chen

2017-02-21

To expedite the pace in conducting genome/proteome analysis, we have developed a Python package called Pse-Analysis. The powerful package can automatically complete the following five procedures: (1) sample feature extraction, (2) optimal parameter selection, (3) model training, (4) cross validation, and (5) evaluating prediction quality. All the work a user needs to do is to input a benchmark dataset along with the query biological sequences concerned. Based on the benchmark dataset, Pse-Analysis will automatically construct an ideal predictor, followed by yielding the predicted results for the submitted query samples. All the aforementioned tedious jobs can be automatically done by the computer. Moreover, the multiprocessing technique was adopted to enhance computational speed by about 6 folds. The Pse-Analysis Python package is freely accessible to the public at http://bioinformatics.hitsz.edu.cn/Pse-Analysis/, and can be directly run on Windows, Linux, and Unix.

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

Proteome analysis of the plant pathogen Xylella fastidiosa reveals major cellular and extracellular proteins and a peculiar codon bias distribution.

PubMed

Smolka, Marcus Bustamante; Martins-de-Souza, Daniel; Martins, Daniel; Winck, Flavia Vischi; Santoro, Carlos Eduardo; Castellari, Rafael Ramos; Ferrari, Fernanda; Brum, Itaraju Junior; Galembeck, Eduardo; Della Coletta Filho, Helvécio; Machado, Marcos Antonio; Marangoni, Sergio; Novello, Jose Camillo

2003-02-01

The bacteria Xylella fastidiosa is the causative agent of a number of economically important crop diseases, including citrus variegated chlorosis. Although its complete genome is already sequenced, X. fastidiosa is very poorly characterized by biochemical approaches at the protein level. In an initial effort to characterize protein expression in X. fastidiosa we used one- and two-dimensional gel electrophoresis and mass spectrometry to identify the products of 142 genes present in a whole cell extract and in an extracellular fraction of the citrus isolated strain 9a5c. Of particular interest for the study of pathogenesis are adhesion and secreted proteins. Homologs to proteins from three different adhesion systems (type IV fimbriae, mrk pili and hsf surface fibrils) were found to be coexpressed, the last two being detected only as multimeric complexes in the high molecular weight region of one-dimensional electrophoresis gels. Using a procedure to extract secreted proteins as well as proteins weakly attached to the cell surface we identified 30 different proteins including toxins, adhesion related proteins, antioxidant enzymes, different types of proteases and 16 hypothetical proteins. These data suggest that the intercellular space of X. fastidiosa colonies is a multifunctional microenvironment containing proteins related to in vivo bacterial survival and pathogenesis. A codon usage analysis of the most expressed proteins from the whole cell extract revealed a low biased distribution, which we propose is related to the slow growing nature of X. fastidiosa. A database of the X. fastidiosa proteome was developed and can be accessed via the internet (URL: www.proteome.ibi.unicamp.br).

Genome-, Transcriptome- and Proteome-Wide Analyses of the Gliadin Gene Families in Triticum urartu

PubMed Central

Wang, Dongzhi; Yang, Wenlong; Sun, Jiazhu; Zhang, Aimin; Zhan, Kehui

2015-01-01

Gliadins are the major components of storage proteins in wheat grains, and they play an essential role in the dough extensibility and nutritional quality of flour. Because of the large number of the gliadin family members, the high level of sequence identity, and the lack of abundant genomic data for Triticum species, identifying the full complement of gliadin family genes in hexaploid wheat remains challenging. Triticum urartu is a wild diploid wheat species and considered the A-genome donor of polyploid wheat species. The accession PI428198 (G1812) was chosen to determine the complete composition of the gliadin gene families in the wheat A-genome using the available draft genome. Using a PCR-based cloning strategy for genomic DNA and mRNA as well as a bioinformatics analysis of genomic sequence data, 28 gliadin genes were characterized. Of these genes, 23 were α-gliadin genes, three were γ-gliadin genes and two were ω-gliadin genes. An RNA sequencing (RNA-Seq) survey of the dynamic expression patterns of gliadin genes revealed that their synthesis in immature grains began prior to 10 days post-anthesis (DPA), peaked at 15 DPA and gradually decreased at 20 DPA. The accumulation of proteins encoded by 16 of the expressed gliadin genes was further verified and quantified using proteomic methods. The phylogenetic analysis demonstrated that the homologs of these α-gliadin genes were present in tetraploid and hexaploid wheat, which was consistent with T. urartu being the A-genome progenitor species. This study presents a systematic investigation of the gliadin gene families in T. urartu that spans the genome, transcriptome and proteome, and it provides new information to better understand the molecular structure, expression profiles and evolution of the gliadin genes in T. urartu and common wheat. PMID:26132381

Genome-, Transcriptome- and Proteome-Wide Analyses of the Gliadin Gene Families in Triticum urartu.

PubMed

Zhang, Yanlin; Luo, Guangbin; Liu, Dongcheng; Wang, Dongzhi; Yang, Wenlong; Sun, Jiazhu; Zhang, Aimin; Zhan, Kehui

2015-01-01

Gliadins are the major components of storage proteins in wheat grains, and they play an essential role in the dough extensibility and nutritional quality of flour. Because of the large number of the gliadin family members, the high level of sequence identity, and the lack of abundant genomic data for Triticum species, identifying the full complement of gliadin family genes in hexaploid wheat remains challenging. Triticum urartu is a wild diploid wheat species and considered the A-genome donor of polyploid wheat species. The accession PI428198 (G1812) was chosen to determine the complete composition of the gliadin gene families in the wheat A-genome using the available draft genome. Using a PCR-based cloning strategy for genomic DNA and mRNA as well as a bioinformatics analysis of genomic sequence data, 28 gliadin genes were characterized. Of these genes, 23 were α-gliadin genes, three were γ-gliadin genes and two were ω-gliadin genes. An RNA sequencing (RNA-Seq) survey of the dynamic expression patterns of gliadin genes revealed that their synthesis in immature grains began prior to 10 days post-anthesis (DPA), peaked at 15 DPA and gradually decreased at 20 DPA. The accumulation of proteins encoded by 16 of the expressed gliadin genes was further verified and quantified using proteomic methods. The phylogenetic analysis demonstrated that the homologs of these α-gliadin genes were present in tetraploid and hexaploid wheat, which was consistent with T. urartu being the A-genome progenitor species. This study presents a systematic investigation of the gliadin gene families in T. urartu that spans the genome, transcriptome and proteome, and it provides new information to better understand the molecular structure, expression profiles and evolution of the gliadin genes in T. urartu and common wheat.

Identification and characterization of insect-specific proteins by genome data analysis

PubMed Central

Zhang, Guojie; Wang, Hongsheng; Shi, Junjie; Wang, Xiaoling; Zheng, Hongkun; Wong, Gane Ka-Shu; Clark, Terry; Wang, Wen; Wang, Jun; Kang, Le

2007-01-01

Background Insects constitute the vast majority of known species with their importance including biodiversity, agricultural, and human health concerns. It is likely that the successful adaptation of the Insecta clade depends on specific components in its proteome that give rise to specialized features. However, proteome determination is an intensive undertaking. Here we present results from a computational method that uses genome analysis to characterize insect and eukaryote proteomes as an approximation complementary to experimental approaches. Results Homologs in common to Drosophila melanogaster, Anopheles gambiae, Bombyx mori, Tribolium castaneum, and Apis mellifera were compared to the complete genomes of three non-insect eukaryotes (opisthokonts) Homo sapiens, Caenorhabditis elegans and Saccharomyces cerevisiae. This operation yielded 154 groups of orthologous proteins in Drosophila to be insect-specific homologs; 466 groups were determined to be common to eukaryotes (represented by three opisthokonts). ESTs from the hemimetabolous insect Locust migratoria were also considered in order to approximate their corresponding genes in the insect-specific homologs. Stress and stimulus response proteins were found to constitute a higher fraction in the insect-specific homologs than in the homologs common to eukaryotes. Conclusion The significant representation of stress response and stimulus response proteins in proteins determined to be insect-specific, along with specific cuticle and pheromone/odorant binding proteins, suggest that communication and adaptation to environments may distinguish insect evolution relative to other eukaryotes. The tendency for low Ka/Ks ratios in the insect-specific protein set suggests purifying selection pressure. The generally larger number of paralogs in the insect-specific proteins may indicate adaptation to environment changes. Instances in our insect-specific protein set have been arrived at through experiments reported in the literature, supporting the accuracy of our approach. PMID:17407609

Excess copper induces anoxygenic photosynthesis in Anabaena doliolum: a homology based proteomic assessment of its survival strategy.

PubMed

Bhargava, Poonam; Mishra, Yogesh; Srivastava, Ashish Kumar; Narayan, Om Prakash; Rai, Lal Chand

2008-04-01

This study is the first to demonstrate operation of anoxygenic photosynthesis in copper acclimated Anabaena doliolum and to offer proteomic comparison with the control cells. The Cu-treated control strain showed a negative correlation in growth and intracellular Cu, partial inhibition of O(2)-evolution, PS II, PS I, whole chain, chlorophyll absorption, and nitrogenase activity. However, the acclimated strain growing in 250-fold excess Cu exhibited near normal growth, ATP content, PS I activity, carbon fixation, and almost complete inhibition of O(2)-evolution, PS II and chlorophyll absorption, but increased nitrogenase activity as compared to control. Proteomic decoding of the survival strategy of Cu-treated control and the acclimated strain using two-dimensional gel electrophoresis and MALDI-TOF MS analysis of proteins displaying significant and reproducible changes demonstrated involvement of transketolase, phycoerythrocyanin alpha-chain, iron superoxide dismutase (Fe-SOD), hypothetical protein alr 0803, manganese superoxide dismutase (Mn-SOD), phosphoribulokinase, and plastocyanin (PLC). Expression pattern of these proteins was attested at the transcriptional level using RT-PCR. Time course analysis of proteins of Cu-treated control strain revealed almost no change in PLC level, and a minor accumulation of transketolase, phycoerythrocyanin alpha-chain and both isoforms of SOD after 7 and recovery after 10 days. Acclimated strain under excess Cu, however, exhibited significant accumulation of both isoforms of SOD, plastocyanin, phosphoribulokinase and transketolase, which seem to counteract oxidative damage, serve as an alternate electron carrier from cytochrome b6/f complex to photosystem I and meet the NADPH and ATP requirements, respectively, under anoxygenic photosynthesis. In view of the kinetics of the hypothetical protein alr0803 (no change in expression level for 7, maximum after 10 and decline after 15 days) its involvement in metal homeostasis is suggested.

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.

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

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.

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

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...

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

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

PubMed Central

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

2015-01-01

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

GO Explorer: A gene-ontology tool to aid in the interpretation of shotgun proteomics data.

PubMed

Carvalho, Paulo C; Fischer, Juliana Sg; Chen, Emily I; Domont, Gilberto B; Carvalho, Maria Gc; Degrave, Wim M; Yates, John R; Barbosa, Valmir C

2009-02-24

Spectral counting is a shotgun proteomics approach comprising the identification and relative quantitation of thousands of proteins in complex mixtures. However, this strategy generates bewildering amounts of data whose biological interpretation is a challenge. Here we present a new algorithm, termed GO Explorer (GOEx), that leverages the gene ontology (GO) to aid in the interpretation of proteomic data. GOEx stands out because it combines data from protein fold changes with GO over-representation statistics to help draw conclusions. Moreover, it is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. Its usefulness is demonstrated by applying it to help interpret the effects of perillyl alcohol, a natural chemotherapeutic agent, on glioblastoma multiform cell lines (A172). We used a new multi-surfactant shotgun proteomic strategy and identified more than 2600 proteins; GOEx pinpointed key sets of differentially expressed proteins related to cell cycle, alcohol catabolism, the Ras pathway, apoptosis, and stress response, to name a few. GOEx facilitates organism-specific studies by leveraging GO and providing a rich graphical user interface. It is a simple to use tool, specialized for biologists who wish to analyze spectral counting data from shotgun proteomics. GOEx is available at http://pcarvalho.com/patternlab.

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.

Whole-proteome phylogeny of large dsDNA viruses and parvoviruses through a composition vector method related to dynamical language model

PubMed Central

2010-01-01

Background The vast sequence divergence among different virus groups has presented a great challenge to alignment-based analysis of virus phylogeny. Due to the problems caused by the uncertainty in alignment, existing tools for phylogenetic analysis based on multiple alignment could not be directly applied to the whole-genome comparison and phylogenomic studies of viruses. There has been a growing interest in alignment-free methods for phylogenetic analysis using complete genome data. Among the alignment-free methods, a dynamical language (DL) method proposed by our group has successfully been applied to the phylogenetic analysis of bacteria and chloroplast genomes. Results In this paper, the DL method is used to analyze the whole-proteome phylogeny of 124 large dsDNA viruses and 30 parvoviruses, two data sets with large difference in genome size. The trees from our analyses are in good agreement to the latest classification of large dsDNA viruses and parvoviruses by the International Committee on Taxonomy of Viruses (ICTV). Conclusions The present method provides a new way for recovering the phylogeny of large dsDNA viruses and parvoviruses, and also some insights on the affiliation of a number of unclassified viruses. In comparison, some alignment-free methods such as the CV Tree method can be used for recovering the phylogeny of large dsDNA viruses, but they are not suitable for resolving the phylogeny of parvoviruses with a much smaller genome size. PMID:20565983

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

Quantitative Proteomics Reveals Fundamental Regulatory Differences in Oncogenic HRAS and Isocitrate Dehydrogenase (IDH1) Driven Astrocytoma.

PubMed

Doll, Sophia; Urisman, Anatoly; Oses-Prieto, Juan A; Arnott, David; Burlingame, Alma L

2017-01-01

Glioblastoma multiformes (GBMs) are high-grade astrocytomas and the most common brain malignancies. Primary GBMs are often associated with disturbed RAS signaling, and expression of oncogenic HRAS results in a malignant phenotype in glioma cell lines. Secondary GBMs arise from lower-grade astrocytomas, have slower progression than primary tumors, and contain IDH1 mutations in over 70% of cases. Despite significant amount of accumulating genomic and transcriptomic data, the fundamental mechanistic differences of gliomagenesis in these two types of high-grade astrocytoma remain poorly understood. Only a few studies have attempted to investigate the proteome, phosphorylation signaling, and epigenetic regulation in astrocytoma. In the present study, we applied quantitative phosphoproteomics to identify the main signaling differences between oncogenic HRAS and mutant IDH1-driven glioma cells as models of primary and secondary GBM, respectively. Our analysis confirms the driving roles of the MAPK and PI3K/mTOR signaling pathways in HRAS driven cells and additionally uncovers dysregulation of other signaling pathways. Although a subset of the signaling changes mediated by HRAS could be reversed by a MEK inhibitor, dual inhibition of MEK and PI3K resulted in more complete reversal of the phosphorylation patterns produced by HRAS expression. In contrast, cells expressing mutant IDH1 did not show significant activation of MAPK or PI3K/mTOR pathways. Instead, global downregulation of protein expression was observed. Targeted proteomic analysis of histone modifications identified significant histone methylation, acetylation, and butyrylation changes in the mutant IDH1 expressing cells, consistent with a global transcriptional repressive state. Our findings offer novel mechanistic insight linking mutant IDH1 associated inhibition of histone demethylases with specific histone modification changes to produce global transcriptional repression in secondary glioblastoma. Our proteomic datasets are available for download and provide a comprehensive catalogue of alterations in protein abundance, phosphorylation, and histone modifications in oncogenic HRAS and IDH1 driven astrocytoma cells beyond the transcriptomic level. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Review of software tools for design and analysis of large scale MRM proteomic datasets.

PubMed

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

2013-06-15

Selective or Multiple Reaction monitoring (SRM/MRM) is a liquid-chromatography (LC)/tandem-mass spectrometry (MS/MS) method that enables the quantitation of specific proteins in a sample by analyzing precursor ions and the fragment ions of their selected tryptic peptides. Instrumentation software has advanced to the point that thousands of transitions (pairs of primary and secondary m/z values) can be measured in a triple quadrupole instrument coupled to an LC, by a well-designed scheduling and selection of m/z windows. The design of a good MRM assay relies on the availability of peptide spectra from previous discovery-phase LC-MS/MS studies. The tedious aspect of manually developing and processing MRM assays involving thousands of transitions has spurred to development of software tools to automate this process. Software packages have been developed for project management, assay development, assay validation, data export, peak integration, quality assessment, and biostatistical analysis. No single tool provides a complete end-to-end solution, thus this article reviews the current state and discusses future directions of these software tools in order to enable researchers to combine these tools for a comprehensive targeted proteomics workflow. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

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

PubMed

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

2018-04-26

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

Qualitative ubiquitome unveils the potential significances of protein lysine ubiquitination in hyphal growth of Aspergillus nidulans.

PubMed

Chu, Xin-Ling; Feng, Ming-Guang; Ying, Sheng-Hua

2016-02-01

Protein ubiquitination is an evolutionarily conserved post-translational modification process in eukaryotes, and it plays an important role in many biological processes. Aspergillus nidulans, a model filamentous fungus, contributes to our understanding of cellular physiology, metabolism and genetics, but its ubiquitination is not completely revealed. In this study, the ubiquitination sites in the proteome of A. nidulans were identified using a highly sensitive mass spectrometry combined with immuno-affinity enrichment of the ubiquitinated peptides. The 4816 ubiquitination sites were identified in 1913 ubiquitinated proteins, accounting for 18.1% of total proteins in A. nidulans. Bioinformatic analysis suggested that the ubiquitinated proteins associated with a number of biological functions and displayed various sub-cellular localisations. Meanwhile, seven motifs were revealed from the ubiquitinated peptides, and significantly over-presented in the different pathways. Comparison of the enriched functional catalogues indicated that the ubiquitination functions divergently during growth of A. nidulans and Saccharomyces cerevisiae. Additionally, the proteins in A. nidulans-specific sub-category (cell growth/morphogenesis) were subjected to the protein interaction analysis which demonstrated that ubiquitination is involved in the comprehensive protein interactions. This study presents a first proteomic view of ubiquitination in the filamentous fungus, and provides an initial framework for exploring the physiological roles of ubiquitination in A. nidulans.

Probing the Proteome on Earth and Beyond

NASA Astrophysics Data System (ADS)

Ostrom, P.

2008-12-01

Less than a decade ago, protein sequencing was the bane of paleobiology. Since that time researchers have completely sequenced proteins in >50 Ka fossils, been dazzled by reports of collagen peptides in dinosaur bones, and witnessed the development of phylogenetic trees from ancient protein sequences. Enlisting proteomics as biosignature is now in our grasp. In this talk the pitfalls and challenges of mass spectrometric approaches to protein sequencing will be illustrated and phylogenetic applications will be discussed. Work on extinct organisms at Michigan State University, University of Michigan and York University will provide a vantage point to assess methodologies, explore diagenetic alterations, evaluate mass spectra and illustrate issues associated with data base searching. Challenges encountered in the study of paleoproteomics, such as the absence of sequences for extinct organisms in commercially available databases, protein diagenesis and low concentrations of target are parallel to those that will be encountered when protein sequencing is extended to extreme and extraterrestrial environments. Thus, lessons learned from interrogating the ancient proteome are important and necessary step in developing proteomics as a biosignature tools.

Efficient Exploitation of Separation Space in Two-Dimensional Liquid Chromatography System for Comprehensive and Efficient Proteomic Analyses.

PubMed

Lee, Hangyeore; Mun, Dong-Gi; So, Jeong Eun; Bae, Jingi; Kim, Hokeun; Masselon, Christophe; Lee, Sang-Won

2016-12-06

Proteomics aims to achieve complete profiling of the protein content and protein modifications in cells, tissues, and biofluids and to quantitatively determine changes in their abundances. This information serves to elucidate cellular processes and signaling pathways and to identify candidate protein biomarkers and/or therapeutic targets. Analyses must therefore be both comprehensive and efficient. Here, we present a novel online two-dimensional reverse-phase/reverse-phase liquid chromatography separation platform, which is based on a newly developed online noncontiguous fractionating and concatenating device (NCFC fractionator). In bottom-up proteomics analyses of a complex proteome, this system provided significantly improved exploitation of the separation space of the two RPs, considerably increasing the numbers of peptides identified compared to a contiguous 2D-RP/RPLC method. The fully automated online 2D-NCFC-RP/RPLC system bypassed a number of labor-intensive manual processes required with the previously described offline 2D-NCFC RP/RPLC method, and thus, it offers minimal sample loss in a context of highly reproducible 2D-RP/RPLC experiments.

A systematic proteomic analysis of NaCl-stressed germinating maize seeds.

PubMed

Meng, Ling-Bo; Chen, Yi-Bo; Lu, Tian-Cong; Wang, Yue-Feng; Qian, Chun-Rong; Yu, Yang; Ge, Xuan-Liang; Li, Xiao-Hui; Wang, Bai-Chen

2014-05-01

Salt (NaCl) is a common physiological stressor of plants. To better understand how germinating seeds respond to salt stress, we examined the changes that occurred in the proteome of maize seeds during NaCl-treated germination. Phenotypically, salt concentrations less than 0.2 M appear to delay germination, while higher concentrations disrupt development completely, leading to seed death. The identities of 96 proteins with expression levels altered by NaCl-incubation were established using 2-DE-MALDI-TOF-MS and 2-DE-MALDI-TOF-MS/MS. Of these 96 proteins, 79 were altered greater than twofold when incubated with a 0.2 M salt solution, while 51 were altered when incubated with a 0.1 M salt solution. According to their functional annotations in the Swiss-Prot protein-sequence databases, these proteins are mainly involved in seed storage, energy metabolism, stress response, and protein metabolism. Notably, the expression of proteins that respond to abscisic acid signals increased in response to salt stress. The results of this study provide important clues as to how NaCl stresses the physiology of germinating maize seeds.

Protein expression profiling in head fragments during planarian regeneration after amputation.

PubMed

Chen, Xiaoguang; Xu, Cunshuan

2015-04-01

Following amputation, a planarian tail fragment can regrow into a complete organism including a well-organized brain within about 2-3 weeks, thus restoring the structure and function to presurgical levels. Despite the enormous potential of these animals for regenerative medicine, our understanding of the exact mechanism of planarian regeneration is incomplete. To better understand the molecular nature of planarian head regeneration, we applied two-dimensional electrophoresis (2-DE)/matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF)/time-of-flight mass spectrometry (TOF MS) technique to analyze the dynamic proteomic expression profiles over the course of 6 to 168 h post-decapitation. This approach identified a total of 141 differentially expressed proteins, 47 of which exhibited exceptionally high fold changes (≥3-fold change). Of these, Rx protein, an important regulator of head and brain development, was considered to be closely related to planarian head regeneration because of its exceptional high expression almost throughout the time course of regeneration process. Functional annotation analysis classified the 141 proteins into eight categories: (1) signaling, (2) Ca(2+) binding and translocation, (3) transcription and translation, (4) cytoskeleton, (5) metabolism, (6) cell protection, (7) tissue differentiation, and (8) cell cycle. Signaling pathway analysis indicated that Wnt1/Ca(2+) signaling pathway was activated during head regeneration. Integrating the analyses of proteome expression profiling, functional annotation, and signaling pathway, amputation-induced head reformation requires some mechanisms to promote cell proliferation and differentiation, including differential regulation of proapoptotic and antiapoptotic proteins, and the regulation of proliferation and differentiation-related proteins. Importantly, Wnt1/Ca(2+) signaling pathway upregulates Rx expression, finally facilitating the differentiation of neoblasts into various cell types. Taken together, our study demonstrated that proteomic analysis approach used by us is a powerful tool in understanding molecular process related to head regeneration of planarian.

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

A systems biology-led insight into the role of the proteome in neurodegenerative diseases.

PubMed

Fasano, Mauro; Monti, Chiara; Alberio, Tiziana

2016-09-01

Multifactorial disorders are the result of nonlinear interactions of several factors; therefore, a reductionist approach does not appear to be appropriate. Proteomics is a global approach that can be efficiently used to investigate pathogenetic mechanisms of neurodegenerative diseases. Here, we report a general introduction about the systems biology approach and mechanistic insights recently obtained by over-representation analysis of proteomics data of cellular and animal models of Alzheimer's disease, Parkinson's disease and other neurodegenerative disorders, as well as of affected human tissues. Expert commentary: As an inductive method, proteomics is based on unbiased observations that further require validation of generated hypotheses. Pathway databases and over-representation analysis tools allow researchers to assign an expectation value to pathogenetic mechanisms linked to neurodegenerative diseases. The systems biology approach based on omics data may be the key to unravel the complex mechanisms underlying neurodegeneration.

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.

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

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

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

PubMed

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

2012-01-01

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

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

PubMed Central

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

2012-01-01

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