PRIDE: The proteomics identifications database

Martens, Lennart; Hermjakob, Henning; Jones, Philip; Adamski, Marcin; Taylor, Chris; States, David J.; Gevaert, Kris; Vandekerckhove, Joël; Apweiler, Rolf

doi:10.1002/pmic.200401303

Cited by 546 publications

(448 citation statements)

References 16 publications

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“…For determining the proportion of proteins within the exoproteome, replicate cultures ( n = 3) were averaged. The proteomics data has been deposited in the Pr oteomics Ide ntification (PRIDE) database (Martens et al , 2005) with the following accession numbers: PXD004065, PXD004064, PXD003830, PXD003829, PXD003828, PXD003827, PXD003826.…”

Section: Methodsmentioning

confidence: 99%

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

Lidbury

Murphy

Scanlan

et al. 2016

Environmental Microbiology

137

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SummaryBacteria 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.

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Section: Methodsmentioning

confidence: 99%

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

Lidbury

Murphy

Scanlan

et al. 2016

Environmental Microbiology

137

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“…In addition, since scientific journals in the field often request the submission of proteomics data used in publications to public data repositories such as PRIDE [11], the ms_lims database is also coupled directly to the Pride Converter tool [12], greatly facilitating the submission process of data to PRIDE. Finally, the manual validation of peptide quantification results can be carried out via the inhouse developed Rover application (http://genesis.ugent.be/ rover) that is developed to streamline this process.…”

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confidence: 99%

ms_lims, a simple yet powerful open source laboratory information management system for MS‐driven proteomics

et al. 2010

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MS-based proteomics produces large amounts of mass spectra that require processing, identification and possibly quantification before interpretation can be undertaken. Highthroughput studies require automation of these various steps, and management of the data in association with the results obtained. We here present ms_lims (http://genesis.UGent.be/ ms_lims), a freely available, open-source system based on a central database to automate data management and processing in MS-driven proteomics analyses. Keywords:Bioinformatics / Data management / Laboratory information management system / Mascot / MS Proteomics labs nowadays often acquire hundreds of thousands to millions of MS/MS spectra per proteome analysis to make large-scale (comprehensive) proteome maps [1]. They rely on contemporary mass spectrometers with rapid duty cycles that increase the amount of produced data by a full order of magnitude compared to older instruments [2]. Automating the processing of these data, and managing their provenance has correspondingly become an important postanalysis task. The automation of these tasks requires the implementation of a start-to-end workflow around a central database management system that is designed for proteomics experiments, with some of the most prominent commercial and academic systems recently reviewed in [3]. Typical actions include collecting and warehousing MS/MS peak lists (often acquired on multiple, different instruments), assigning the accumulated MS/MS data to peptide identifications, quantifying peptides and proteins from MS or MS/MS data, and organizing both data and analysis results in a navigable project structure. In most high-throughput environments, these diverse actions are typically undertaken by different individuals, which further necessitates a role-based implementation of the software interfaces [4].To tackle and manage these problems associated with MSdriven proteomics, we developed ms_lims, an open source and instrument vendor-independent system for proteomics data management. In contrast to existing web-based tools such as MASPECTRAS [4] or CPAS [5], ms_lims embraces a client-server architecture, which allows for more dynamic interaction. Additionally, ms_lims also differs from libraries Abbreviations: LIMS, laboratory information management system; MGF, Mascot generic file; SQL, Structured Query Language Ã These authors contributed equally to this work.

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“…The first of these challenges was the need for central and long‐term public repositories to store the generated data. Several such generic repositories are now available, for example PRIDE 4, GPMDB 5, PeptideAtlas 6, and MassIVE (http://massive.ucsd.edu/ProteoSAFe) for shotgun results; and PASSEL 7, SRMAtlas (http://www.srmatlas.org), and Panorama 8 for targeted proteomics quantification data. More specific databases have also been established, related to: diseases, for example TBDB for tuberculosis 9; organisms, for example ProteomicsDB 10 and the Human Proteome Map 11 for the human proteome, and pep2pro for Arabidopsis 12; or subproteomes, for example CSF‐PR 13 for cerebrospinal fluid or TOPPR 14 and TopFIND 15 for in vivo cleaved proteins.…”

Section: Introductionmentioning

confidence: 99%

Exploring the potential of public proteomics data

et al. 2015

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In a global effort for scientific transparency, it has become feasible and good practice to share experimental data supporting novel findings. Consequently, the amount of publicly available MS‐based proteomics data has grown substantially in recent years. With some notable exceptions, this extensive material has however largely been left untouched. The time has now come for the proteomics community to utilize this potential gold mine for new discoveries, and uncover its untapped potential. In this review, we provide a brief history of the sharing of proteomics data, showing ways in which publicly available proteomics data are already being (re‐)used, and outline potential future opportunities based on four different usage types: use, reuse, reprocess, and repurpose. We thus aim to assist the proteomics community in stepping up to the challenge, and to make the most of the rapidly increasing amount of public proteomics data.

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PRIDE: The proteomics identifications database

Cited by 546 publications

References 16 publications

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

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

ms_lims, a simple yet powerful open source laboratory information management system for MS‐driven proteomics

Exploring the potential of public proteomics data

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