Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 33
Filtrar
Mais filtros










Base de dados
Intervalo de ano de publicação
1.
Sci Data ; 10(1): 697, 2023 10 13.
Artigo em Inglês | MEDLINE | ID: mdl-37833331

RESUMO

Data-Independent Acquisition (DIA) is a mass spectrometry-based method to reliably identify and reproducibly quantify large fractions of a target proteome. The peptide-centric data analysis strategy employed in DIA requires a priori generated spectral assay libraries. Such assay libraries allow to extract quantitative data in a targeted approach and have been generated for human, mouse, zebrafish, E. coli and few other organisms. However, a spectral assay library for the extreme halophilic archaeon Halobacterium salinarum NRC-1, a model organism that contributed to several notable discoveries, is not publicly available yet. Here, we report a comprehensive spectral assay library to measure 2,563 of 2,646 annotated H. salinarum NRC-1 proteins. We demonstrate the utility of this library by measuring global protein abundances over time under standard growth conditions. The H. salinarum NRC-1 library includes 21,074 distinct peptides representing 97% of the predicted proteome and provides a new, valuable resource to confidently measure and quantify any protein of this archaeon. Data and spectral assay libraries are available via ProteomeXchange (PXD042770, PXD042774) and SWATHAtlas (SAL00312-SAL00319).


Assuntos
Halobacterium salinarum , Proteoma , Halobacterium salinarum/metabolismo , Peptídeos/análise , Proteoma/análise , Proteômica/métodos
2.
bioRxiv ; 2023 Jun 16.
Artigo em Inglês | MEDLINE | ID: mdl-37398146

RESUMO

Lyme disease, caused by an infection with the spirochete Borrelia burgdorferi, is the most common vector-borne disease in North America. B. burgdorferi strains harbor extensive genomic and proteomic variability and further comparison is key to understanding the spirochetes infectivity and biological impacts of identified sequence variants. To achieve this goal, both transcript and mass spectrometry (MS)-based proteomics was applied to assemble peptide datasets of laboratory strains B31, MM1, B31-ML23, infective isolates B31-5A4, B31-A3, and 297, and other public datasets, to provide a publicly available Borrelia PeptideAtlas http://www.peptideatlas.org/builds/borrelia/. Included is information on total proteome, secretome, and membrane proteome of these B. burgdorferi strains. Proteomic data collected from 35 different experiment datasets, with a total of 855 mass spectrometry runs, identified 76,936 distinct peptides at a 0.1% peptide false-discovery-rate, which map to 1,221 canonical proteins (924 core canonical and 297 noncore canonical) and covers 86% of the total base B31 proteome. The diverse proteomic information from multiple isolates with credible data presented by the Borrelia PeptideAtlas can be useful to pinpoint potential protein targets which are common to infective isolates and may be key in the infection process.

3.
J Proteome Res ; 22(2): 647-655, 2023 02 03.
Artigo em Inglês | MEDLINE | ID: mdl-36629399

RESUMO

Fragmentation ion spectral analysis of chemically cross-linked proteins is an established technology in the proteomics research repertoire for determining protein interactions, spatial orientation, and structure. Here we present Kojak version 2.0, a major update to the original Kojak algorithm, which was developed to identify cross-linked peptides from fragment ion spectra using a database search approach. A substantially improved algorithm with updated scoring metrics, support for cleavable cross-linkers, and identification of cross-links between 15N-labeled homomultimers are among the newest features of Kojak 2.0 presented here. Kojak 2.0 is now integrated into the Trans-Proteomic Pipeline, enabling access to dozens of additional tools within that suite. In particular, the PeptideProphet and iProphet tools for validation of cross-links improve the sensitivity and accuracy of correct cross-link identifications at user-defined thresholds. These new features improve the versatility of the algorithm, enabling its use in a wider range of experimental designs and analysis pipelines. Kojak 2.0 remains open-source and multiplatform.


Assuntos
Proteômica , Espectrometria de Massas em Tandem , Proteômica/métodos , Espectrometria de Massas em Tandem/métodos , Peptídeos/análise , Proteínas/química , Software , Reagentes de Ligações Cruzadas/química
4.
J Proteome Res ; 22(2): 615-624, 2023 02 03.
Artigo em Inglês | MEDLINE | ID: mdl-36648445

RESUMO

The Trans-Proteomic Pipeline (TPP) mass spectrometry data analysis suite has been in continual development and refinement since its first tools, PeptideProphet and ProteinProphet, were published 20 years ago. The current release provides a large complement of tools for spectrum processing, spectrum searching, search validation, abundance computation, protein inference, and more. Many of the tools include machine-learning modeling to extract the most information from data sets and build robust statistical models to compute the probabilities that derived information is correct. Here we present the latest information on the many TPP tools, and how TPP can be deployed on various platforms from personal Windows laptops to Linux clusters and expansive cloud computing environments. We describe tutorials on how to use TPP in a variety of ways and describe synergistic projects that leverage TPP. We conclude with plans for continued development of TPP.


Assuntos
Proteômica , Software , Proteômica/métodos , Espectrometria de Massas , Probabilidade , Análise de Dados
5.
Sci Data ; 7(1): 389, 2020 11 12.
Artigo em Inglês | MEDLINE | ID: mdl-33184295

RESUMO

Data-Independent Acquisition (DIA) is a method to improve consistent identification and precise quantitation of peptides and proteins by mass spectrometry (MS). The targeted data analysis strategy in DIA relies on spectral assay libraries that are generally derived from a priori measurements of peptides for each species. Although Escherichia coli (E. coli) is among the best studied model organisms, so far there is no spectral assay library for the bacterium publicly available. Here, we generated a spectral assay library for 4,014 of the 4,389 annotated E. coli proteins using one- and two-dimensional fractionated samples, and ion mobility separation enabling deep proteome coverage. We demonstrate the utility of this high-quality library with robustness in quantitation of the E. coli proteome and with rapid-chromatography to enhance throughput by targeted DIA-MS. The spectral assay library supports the detection and quantification of 91.5% of all E. coli proteins at high-confidence with 56,182 proteotypic peptides, making it a valuable resource for the scientific community. Data and spectral libraries are available via ProteomeXchange (PXD020761, PXD020785) and SWATHAtlas (SAL00222-28).


Assuntos
Proteínas de Escherichia coli/análise , Escherichia coli/metabolismo , Espectrometria de Massas , Proteoma/análise , Biblioteca de Peptídeos , Peptídeos/análise
6.
J Proteome Res ; 19(12): 4754-4765, 2020 12 04.
Artigo em Inglês | MEDLINE | ID: mdl-33166149

RESUMO

Mass spectrometry has greatly improved the analysis of phosphorylation events in complex biological systems and on a large scale. Despite considerable progress, the correct identification of phosphorylated sites, their quantification, and their interpretation regarding physiological relevance remain challenging. The MS Resource Pillar of the Human Proteome Organization (HUPO) Human Proteome Project (HPP) initiated the Phosphopeptide Challenge as a resource to help the community evaluate methods, learn procedures and data analysis routines, and establish their own workflows by comparing results obtained from a standard set of 94 phosphopeptides (serine, threonine, tyrosine) and their nonphosphorylated counterparts mixed at different ratios in a neat sample and a yeast background. Participants analyzed both samples with their method(s) of choice to report the identification and site localization of these peptides, determine their relative abundances, and enrich for the phosphorylated peptides in the yeast background. We discuss the results from 22 laboratories that used a range of different methods, instruments, and analysis software. We reanalyzed submitted data with a single software pipeline and highlight the successes and challenges in correct phosphosite localization. All of the data from this collaborative endeavor are shared as a resource to encourage the development of even better methods and tools for diverse phosphoproteomic applications. All submitted data and search results were uploaded to MassIVE (https://massive.ucsd.edu/) as data set MSV000085932 with ProteomeXchange identifier PXD020801.


Assuntos
Fosfopeptídeos , Proteoma , Humanos , Espectrometria de Massas , Fosforilação , Proteômica
7.
J Proteome Res ; 18(12): 4262-4272, 2019 12 06.
Artigo em Inglês | MEDLINE | ID: mdl-31290668

RESUMO

Spectral matching sequence database search engines commonly used on mass spectrometry-based proteomics experiments excel at identifying peptide sequence ions, and in addition, possible sequence ions carrying post-translational modifications (PTMs), but most do not provide confidence metrics for the exact localization of those PTMs when several possible sites are available. Localization is absolutely required for downstream molecular cell biology analysis of PTM function in vitro and in vivo. Therefore, we developed PTMProphet, a free and open-source software tool integrated into the Trans-Proteomic Pipeline, which reanalyzes identified spectra from any search engine for which pepXML output is available to provide localization confidence to enable appropriate further characterization of biologic events. Localization of any type of mass modification (e.g., phosphorylation) is supported. PTMProphet applies Bayesian mixture models to compute probabilities for each site/peptide spectrum match where a PTM has been identified. These probabilities can be combined to compute a global false localization rate at any threshold to guide downstream analysis. We describe the PTMProphet tool, its underlying algorithms, and demonstrate its performance on ground-truth synthetic peptide reference data sets, one previously published small data set, one new larger data set, and also on a previously published phosphoenriched data set where the correct sites of modification are unknown. Data have been deposited to ProteomeXchange with identifier PXD013210.


Assuntos
Processamento de Proteína Pós-Traducional , Proteômica/métodos , Software , Algoritmos , Teorema de Bayes , Bases de Dados de Proteínas , Humanos , Fosfopeptídeos/metabolismo , Interface Usuário-Computador
8.
J Proteome Res ; 18(2): 652-663, 2019 02 01.
Artigo em Inglês | MEDLINE | ID: mdl-30523691

RESUMO

Thrombospondin type 1 repeats (TSRs), small adhesive protein domains with a wide range of functions, are usually modified with O-linked fucose, which may be extended to O-fucose-ß1,3-glucose. Collision-induced dissociation (CID) spectra of O-fucosylated peptides cannot be sequenced by standard tandem mass spectrometry (MS/MS) sequence database search engines because O-linked glycans are highly labile in the gas phase and are effectively absent from the CID peptide fragment spectra, resulting in a large mass error. Electron transfer dissociation (ETD) preserves O-linked glycans on peptide fragments, but only a subset of tryptic peptides with low m/ z can be reliably sequenced from ETD spectra compared to CID. Accordingly, studies to date that have used MS to identify O-fucosylated TSRs have required manual interpretation of CID mass spectra even when ETD was also employed. In order to facilitate high-throughput, automatic identification of O-fucosylated peptides from CID spectra, we re-engineered the MS/MS sequence database search engine Comet and the MS data analysis suite Trans-Proteomic Pipeline to enable automated sequencing of peptides exhibiting the neutral losses characteristic of labile O-linked glycans. We used our approach to reanalyze published proteomics data from Plasmodium parasites and identified multiple glycoforms of TSR-containing proteins.


Assuntos
Fucose/química , Proteômica/métodos , Ferramenta de Busca/métodos , Espectrometria de Massas em Tandem/métodos , Bases de Dados de Proteínas , Glicosilação , Peptídeos/análise , Plasmodium/química
9.
J Proteome Res ; 17(12): 4337-4344, 2018 12 07.
Artigo em Inglês | MEDLINE | ID: mdl-30230343

RESUMO

Bottom-up proteomics relies on the proteolytic or chemical cleavage of proteins into peptides, the identification of those peptides via mass spectrometry, and the mapping of the identified peptides back to the reference proteome to infer which possible proteins are identified. Reliable mapping of peptides to proteins still poses substantial challenges when considering similar proteins, protein families, splice isoforms, sequence variation, and possible residue mass modifications, combined with an imperfect and incomplete understanding of the proteome. The ProteoMapper tool enables a comprehensive and rapid mapping of peptides to a reference proteome. The indexer component creates a segmented index for an input proteome from a FASTA or PEFF file. The ProMaST component provides ultrafast mapping of one or more input peptides against the index. ProteoMapper allows searches that take into account known sequence variation encoded in PEFF files. It also enables fuzzy searches to find highly similar peptides with residue order changes or other isobaric or near-isobaric substitutions within a specified mass tolerance. We demonstrate an example of a one-hit-wonder identification in PeptideAtlas that may be better explained by a combination of catalogued and uncatalogued sequence variation in another highly observed protein. ProteoMapper is a free and open source, available for local use after downloading, embedding in other applications, as an online web tool at http://www.peptideatlas.org/map , and as a web service.


Assuntos
Mapeamento de Peptídeos/métodos , Proteoma , Software , Sequência de Aminoácidos , Animais , Variação Genética , Humanos , Espectrometria de Massas , Proteínas
10.
J Proteome Res ; 15(11): 4091-4100, 2016 11 04.
Artigo em Inglês | MEDLINE | ID: mdl-27577934

RESUMO

The results of analysis of shotgun proteomics mass spectrometry data can be greatly affected by the selection of the reference protein sequence database against which the spectra are matched. For many species there are multiple sources from which somewhat different sequence sets can be obtained. This can lead to confusion about which database is best in which circumstances-a problem especially acute in human sample analysis. All sequence databases are genome-based, with sequences for the predicted gene and their protein translation products compiled. Our goal is to create a set of primary sequence databases that comprise the union of sequences from many of the different available sources and make the result easily available to the community. We have compiled a set of four sequence databases of varying sizes, from a small database consisting of only the ∼20,000 primary isoforms plus contaminants to a very large database that includes almost all nonredundant protein sequences from several sources. This set of tiered, increasingly complete human protein sequence databases suitable for mass spectrometry proteomics sequence database searching is called the Tiered Human Integrated Search Proteome set. In order to evaluate the utility of these databases, we have analyzed two different data sets, one from the HeLa cell line and the other from normal human liver tissue, with each of the four tiers of database complexity. The result is that approximately 0.8%, 1.1%, and 1.5% additional peptides can be identified for Tiers 2, 3, and 4, respectively, as compared with the Tier 1 database, at substantially increasing computational cost. This increase in computational cost may be worth bearing if the identification of sequence variants or the discovery of sequences that are not present in the reviewed knowledge base entries is an important goal of the study. We find that it is useful to search a data set against a simpler database, and then check the uniqueness of the discovered peptides against a more complex database. We have set up an automated system that downloads all the source databases on the first of each month and automatically generates a new set of search databases and makes them available for download at http://www.peptideatlas.org/thisp/ .


Assuntos
Bases de Dados de Proteínas/tendências , Proteômica/métodos , Biologia Computacional/métodos , Células HeLa , Humanos , Fígado/química , Fígado/citologia , Espectrometria de Massas , Isoformas de Proteínas/análise , Proteínas/análise
11.
Cell ; 166(3): 766-778, 2016 Jul 28.
Artigo em Inglês | MEDLINE | ID: mdl-27453469

RESUMO

The ability to reliably and reproducibly measure any protein of the human proteome in any tissue or cell type would be transformative for understanding systems-level properties as well as specific pathways in physiology and disease. Here, we describe the generation and verification of a compendium of highly specific assays that enable quantification of 99.7% of the 20,277 annotated human proteins by the widely accessible, sensitive, and robust targeted mass spectrometric method selected reaction monitoring, SRM. This human SRMAtlas provides definitive coordinates that conclusively identify the respective peptide in biological samples. We report data on 166,174 proteotypic peptides providing multiple, independent assays to quantify any human protein and numerous spliced variants, non-synonymous mutations, and post-translational modifications. The data are freely accessible as a resource at http://www.srmatlas.org/, and we demonstrate its utility by examining the network response to inhibition of cholesterol synthesis in liver cells and to docetaxel in prostate cancer lines.


Assuntos
Bases de Dados de Proteínas , Proteoma , Acesso à Informação , Antineoplásicos/uso terapêutico , Linhagem Celular Tumoral , Colesterol/biossíntese , Docetaxel , Feminino , Humanos , Internet , Fígado/efeitos dos fármacos , Masculino , Mutação , Neoplasias da Próstata/tratamento farmacológico , Splicing de RNA , Taxoides/uso terapêutico
12.
J Am Soc Mass Spectrom ; 27(11): 1728-1734, 2016 11.
Artigo em Inglês | MEDLINE | ID: mdl-27469004

RESUMO

Protein-protein interactions are an important element in the understanding of protein function, and chemical cross-linking shotgun mass spectrometry is rapidly becoming a routine approach to identify these specific interfaces and topographical interactions. Protein cross-link data analysis is aided by dozens of algorithm choices, but hindered by a lack of a common format for representing results. Consequently, interoperability between algorithms and pipelines utilizing chemical cross-linking remains a challenge. pepXML is an open, widely-used format for representing spectral search algorithm results that has facilitated information exchange and pipeline development for typical shotgun mass spectrometry analyses. We describe an extension of this format to incorporate cross-linking spectral search results. We demonstrate application of the extension by representing results of multiple cross-linking search algorithms. In addition, we demonstrate adapting existing pepXML-supporting software pipelines to analyze protein cross-linking results formatted in pepXML. Graphical Abstract ᅟ.


Assuntos
Algoritmos , Espectrometria de Massas , Proteínas , Software , Computadores , Reagentes de Ligações Cruzadas , Proteínas/química , Proteínas/fisiologia , Estatística como Assunto
13.
Mol Cell Proteomics ; 15(3): 1151-63, 2016 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-26704149

RESUMO

Posttranslational modifications of proteins play an important role in biology. For example, phosphorylation is a key component in signal transduction in all three domains of life, and histones can be modified in such a variety of ways that a histone code for gene regulation has been proposed. Shotgun proteomics is commonly used to identify posttranslational modifications as well as chemical modifications from sample processing. However, it favors the detection of abundant peptides over the repertoire presented, and the data analysis usually requires advance specification of modification masses and target amino acids, their number constrained by available computational resources. Recent advances in data independent acquisition mass spectrometry technologies such as SWATH-MS enable a deeper recording of the peptide contents of samples, including peptides with modifications. Here, we present a novel approach that applies the power of SWATH-MS analysis to the automated pursuit of modified peptides. With the new SWATHProphet(PTM) functionality added to the open source SWATHProphet software, precursor ions consistent with a modification are identified along with the mass and localization of the modification in the peptide sequence in a sensitive and unrestricted manner without the need to anticipate the modifications in advance. Using this method, we demonstrate the detection of a wide assortment of modified peptides, many unanticipated, in samples containing unpurified synthetic peptides and human urine, as well as in phospho-enriched human tissue culture cell samples.


Assuntos
Peptídeos/química , Processamento de Proteína Pós-Traducional , Proteômica/métodos , Espectrometria de Massas em Tandem/métodos , Linhagem Celular Tumoral , Biologia Computacional/métodos , Histonas/química , Humanos , Peptídeos/urina , Fosforilação , Proteínas/metabolismo , Software
14.
J Am Soc Mass Spectrom ; 26(11): 1837-47, 2015 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-26419769

RESUMO

Most shotgun proteomics data analysis workflows are based on the assumption that each fragment ion spectrum is explained by a single species of peptide ion isolated by the mass spectrometer; however, in reality mass spectrometers often isolate more than one peptide ion within the window of isolation that contribute to additional peptide fragment peaks in many spectra. We present a new tool called reSpect, implemented in the Trans-Proteomic Pipeline (TPP), which enables an iterative workflow whereby fragment ion peaks explained by a peptide ion identified in one round of sequence searching or spectral library search are attenuated based on the confidence of the identification, and then the altered spectrum is subjected to further rounds of searching. The reSpect tool is not implemented as a search engine, but rather as a post-search engine processing step where only fragment ion intensities are altered. This enables the application of any search engine combination in the iterations that follow. Thus, reSpect is compatible with all other protein sequence database search engines as well as peptide spectral library search engines that are supported by the TPP. We show that while some datasets are highly amenable to chimeric spectrum identification and lead to additional peptide identification boosts of over 30% with as many as four different peptide ions identified per spectrum, datasets with narrow precursor ion selection only benefit from such processing at the level of a few percent. We demonstrate a technique that facilitates the determination of the degree to which a dataset would benefit from chimeric spectrum analysis. The reSpect tool is free and open source, provided within the TPP and available at the TPP website. Graphical Abstract ᅟ.


Assuntos
Proteômica/métodos , Software , Espectrometria de Massas em Tandem/métodos , Íons , Mapeamento de Peptídeos
15.
J Proteome Res ; 14(9): 3461-73, 2015 Sep 04.
Artigo em Inglês | MEDLINE | ID: mdl-26139527

RESUMO

The Human PeptideAtlas is a compendium of the highest quality peptide identifications from over 1000 shotgun mass spectrometry proteomics experiments collected from many different laboratories, all reanalyzed through a uniform processing pipeline. The latest 2015-03 build contains substantially more input data than past releases, is mapped to a recent version of our merged reference proteome, and uses improved informatics processing and the development of the AtlasProphet to provide the highest quality results. Within the set of ∼20,000 neXtProt primary entries, 14,070 (70%) are confidently detected in the latest build, 5% are ambiguous, 9% are redundant, leaving the total percentage of proteins for which there are no mapping detections at just 16% (3166), all derived from over 133 million peptide-spectrum matches identifying more than 1 million distinct peptides using AtlasProphet to characterize and classify the protein matches. Improved handling for detection and presentation of single amino-acid variants (SAAVs) reveals the detection of 5326 uniquely mapping SAAVs across 2794 proteins. With such a large amount of data, the control of false positives is a challenge. We present the methodology and results for maintaining rigorous quality along with a discussion of the implications of the remaining sources of errors in the build.


Assuntos
Bases de Dados de Proteínas , Proteínas/química , Proteômica , Sequência de Aminoácidos , Substituição de Aminoácidos , Humanos , Dados de Sequência Molecular , Homologia de Sequência de Aminoácidos
16.
Mol Cell Proteomics ; 14(5): 1411-8, 2015 May.
Artigo em Inglês | MEDLINE | ID: mdl-25713123

RESUMO

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


Assuntos
Peptídeos/análise , Proteínas/análise , Proteinúria/urina , Software , Espectrometria de Massas em Tandem/estatística & dados numéricos , Humanos , Biblioteca de Peptídeos , Proteínas/química , Proteólise , Proteômica/métodos , Reprodutibilidade dos Testes , Tripsina/química
17.
Proteomics Clin Appl ; 9(7-8): 745-54, 2015 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-25631240

RESUMO

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.


Assuntos
Biologia Computacional/métodos , Proteômica/métodos , Estatística como Assunto , Humanos , Proteoma/metabolismo , Reprodutibilidade dos Testes , Software
18.
Mol Cell Proteomics ; 14(2): 399-404, 2015 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-25418363

RESUMO

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.


Assuntos
Internet , Proteômica/métodos , Software , Estatística como Assunto , Computadores , Interface Usuário-Computador
19.
Front Microbiol ; 5: 392, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-25136337

RESUMO

Staphylococcus aureus is a human pathogen that can cause a wide range of diseases. Although formerly regarded as extracellular pathogen, it has been shown that S. aureus can also be internalized by host cells and persist within these cells. In the present study, we comparatively analyzed survival and physiological adaptation of S. aureus HG001 after internalization by two human lung epithelial cell lines (S9 and A549), and human embryonic kidney cells (HEK 293). Combining enrichment of bacteria from host-pathogen assays by cell sorting and quantitation of the pathogen's proteome by mass spectrometry we characterized S. aureus adaptation during the initial phase between 2.5 h and 6.5 h post-infection. Starting with about 2 × 10(6) bacteria, roughly 1450 S. aureus proteins, including virulence factors and metabolic enzymes were identified by spectral comparison and classical database searches. Most of the bacterial adaptation reactions, such as decreased levels of ribosomal proteins and metabolic enzymes or increased amounts of proteins involved in arginine and lysine biosynthesis, enzymes coding for terminal oxidases and stress responsive proteins or activation of the sigma factor SigB were observed after internalization into any of the three cell lines studied. However, differences were noted in central carbon metabolism including regulation of fermentation and threonine degradation. Since these differences coincided with different intracellular growth behavior, complementary profiling of the metabolome of the different non-infected host cell types was performed. This revealed similar levels of intracellular glucose but host cell specific differences in the amounts of amino acids such as glycine, threonine or glutamate. With this comparative study we provide an impression of the common and specific features of the adaptation of S. aureus HG001 to specific host cell environments as a starting point for follow-up studies with different strain isolates and regulatory mutants.

20.
J Proteome Res ; 13(1): 60-75, 2014 Jan 03.
Artigo em Inglês | MEDLINE | ID: mdl-24261998

RESUMO

The kidney, urine, and plasma proteomes are intimately related: proteins and metabolic waste products are filtered from the plasma by the kidney and excreted via the urine, while kidney proteins may be secreted into the circulation or released into the urine. Shotgun proteomics data sets derived from human kidney, urine, and plasma samples were collated and processed using a uniform software pipeline, and relative protein abundances were estimated by spectral counting. The resulting PeptideAtlas builds yielded 4005, 2491, and 3553 nonredundant proteins at 1% FDR for the kidney, urine, and plasma proteomes, respectively - for kidney and plasma, the largest high-confidence protein sets to date. The same pipeline applied to all available human data yielded a 2013 Human PeptideAtlas build containing 12,644 nonredundant proteins and at least one peptide for each of ∼14,000 Swiss-Prot entries, an increase over 2012 of ∼7.5% of the predicted human proteome. We demonstrate that abundances are correlated between plasma and urine, examine the most abundant urine proteins not derived from either plasma or kidney, and consider the biomarker potential of proteins associated with renal decline. This analysis forms part of the Biology and Disease-driven Human Proteome Project (B/D-HPP) and is a contribution to the Chromosome-centric Human Proteome Project (C-HPP) special issue.


Assuntos
Proteínas/metabolismo , Proteoma , Cromatografia Líquida , Humanos , Espectrometria de Massas em Tandem
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA
...