Proteomics Standards Initiative Extended FASTA Format.

Mass-spectrometry-based proteomics enables the high-throughput identification and quantification of proteins, including sequence variants and post-translational modifications (PTMs) in biological samples. However, most workflows require that such variations be included in the search space used to analyze the data, and doing so remains challenging with most analysis tools. In order to facilitate the search for known sequence variants and PTMs, the Proteomics Standards Initiative (PSI) has designed and implemented the PSI extended FASTA format (PEFF). PEFF is based on the very popular FASTA format but adds a uniform mechanism for encoding substantially more metadata about the sequence collection as well as individual entries, including support for encoding known sequence variants, PTMs, and proteoforms. The format is very nearly backward compatible, and as such, existing FASTA parsers will require little or no changes to be able to read PEFF files as FASTA files, although without supporting any of the extra capabilities of PEFF. PEFF is defined by a full specification document, controlled vocabulary terms, a set of example files, software libraries, and a file validator. Popular software and resources are starting to support PEFF, including the sequence search engine Comet and the knowledge bases neXtProt and UniProtKB. Widespread implementation of PEFF is expected to further enable proteogenomics and top-down proteomics applications by providing a standardized mechanism for encoding protein sequences and their known variations. All the related documentation, including the detailed file format specification and example files, are available at http://www.psidev.info/peff .

A standardized framing for reporting protein identifications in mzIdentML 1.2.

Inferring which protein species have been detected in bottom-up proteomics experiments has been a challenging problem for which solutions have been maturing over the past decade. While many inference approaches now function well in isolation, comparing and reconciling the results generated across different tools remains difficult. It presently stands as one of the greatest barriers in collaborative efforts such as the Human Proteome Project and public repositories such as the PRoteomics IDEntifications (PRIDE) database. Here we present a framework for reporting protein identifications that seeks to improve capabilities for comparing results generated by different inference tools. This framework standardizes the terminology for describing protein identification results, associated with the HUPO-Proteomics Standards Initiative (PSI) mzIdentML standard, while still allowing for differing methodologies to reach that final state. It is proposed that developers of software for reporting identification results will adopt this terminology in their outputs. While the new terminology does not require any changes to the core mzIdentML model, it represents a significant change in practice, and, as such, the rules will be released via a new version of the mzIdentML specification (version 1.2) so that consumers of files are able to determine whether the new guidelines have been adopted by export software.

A two-step database search method improves sensitivity in peptide sequence matches for metaproteomics and proteogenomics studies.

Large databases (>10(6) sequences) used in metaproteomic and proteogenomic studies present challenges in matching peptide sequences to MS/MS data using database-search programs. Most notably, strict filtering to avoid false-positive matches leads to more false negatives, thus constraining the number of peptide matches. To address this challenge, we developed a two-step method wherein matches derived from a primary search against a large database were used to create a smaller subset database. The second search was performed against a target-decoy version of this subset database merged with a host database. High confidence peptide sequence matches were then used to infer protein identities. Applying our two-step method for both metaproteomic and proteogenomic analysis resulted in twice the number of high confidence peptide sequence matches in each case, as compared to the conventional one-step method. The two-step method captured almost all of the same peptides matched by the one-step method, with a majority of the additional matches being false negatives from the one-step method. Furthermore, the two-step method improved results regardless of the database search program used. Our results show that our two-step method maximizes the peptide matching sensitivity for applications requiring large databases, especially valuable for proteogenomics and metaproteomics studies.

Workflow for analysis of high mass accuracy salivary data set using MaxQuant and ProteinPilot search algorithm.

LTQ Orbitrap data analyzed with ProteinPilot can be further improved by MaxQuant raw data processing, which utilizes precursor-level high mass accuracy data for peak processing and MGF creation. In particular, ProteinPilot results from MaxQuant-processed peaklists for Orbitrap data sets resulted in improved spectral utilization due to an improved peaklist quality with higher precision and high precursor mass accuracy (HPMA). The output and postsearch analysis tools of both workflows were utilized for previously unexplored features of a three-dimensional fractionated and hexapeptide library (ProteoMiner) treated whole saliva data set comprising 200 fractions. ProteinPilot's ability to simultaneously predict multiple modifications showed an advantage from ProteoMiner treatment for modified peptide identification. We demonstrate that complementary approaches in the analysis pipeline provide comprehensive results for the whole saliva data set acquired on an LTQ Orbitrap. Overall our results establish a workflow for improved protein identification from high mass accuracy data.

The mzIdentML data standard for mass spectrometry-based proteomics results.

We report the release of mzIdentML, an exchange standard for peptide and protein identification data, designed by the Proteomics Standards Initiative. The format was developed by the Proteomics Standards Initiative in collaboration with instrument and software vendors, and the developers of the major open-source projects in proteomics. Software implementations have been developed to enable conversion from most popular proprietary and open-source formats, and mzIdentML will soon be supported by the major public repositories. These developments enable proteomics scientists to start working with the standard for exchanging and publishing data sets in support of publications and they provide a stable platform for bioinformatics groups and commercial software vendors to work with a single file format for identification data.

CysTRAQ - A combination of iTRAQ and enrichment of cysteinyl peptides for uncovering and quantifying hidden proteomes.

Shotgun proteomics is capable of characterizing differences in both protein quality and quantity, and has been applied in various biomedical applications. Unfortunately, the high complexity and dynamic range of proteins in studied samples, clinical in particular, often hinders the identification of relevant proteins. Indeed, information-rich, low abundance proteins often remain undetected, whereas repeatedly reported altered concentrations in high abundance proteins are often ambiguous and insignificant. Several techniques have therefore been developed to overcome this obstacle and provide a deeper insight into the proteome. Here we report a novel approach, which enables iTRAQ reagent quantitation of peptides fractionated based on presence of a cysteine residue (thus CysTRAQ). For the first time, we prove that iTRAQ quantitation is fully compatible with cysteinyl peptide enrichment and is not influenced by the fractionation process. Moreover, the employment of the method combined with high-resolution TripleTOF 5600 mass spectrometer for very fast MS/MS acquisition in human amniotic fluid analysis significantly increased the number of identified proteins, which were simultaneously quantified owing to the introduction of iTRAQ labeling. We herein show that CysTRAQ is a robust and straightforward method with potential application in quantitative proteomics experiments, i.e. as an alternative to the ICAT reagent approach.

Recommendations for mass spectrometry data quality metrics for open access data (corollary to the Amsterdam principles).

Policies supporting the rapid and open sharing of proteomic data are being implemented by the leading journals in the field. The proteomics community is taking steps to ensure that data are made publicly accessible and are of high quality, a challenging task that requires the development and deployment of methods for measuring and documenting data quality metrics. On September 18, 2010, the U.S. National Cancer Institute (NCI) convened the "International Workshop on Proteomic Data Quality Metrics" in Sydney, Australia, to identify and address issues facing the development and use of such methods for open access proteomics data. The stakeholders at the workshop enumerated the key principles underlying a framework for data quality assessment in mass spectrometry data that will meet the needs of the research community, journals, funding agencies, and data repositories. Attendees discussed and agreed upon two primary needs for the wide use of quality metrics: (i) an evolving list of comprehensive quality metrics and (ii) standards accompanied by software analytics. Attendees stressed the importance of increased education and training programs to promote reliable protocols in proteomics. This workshop report explores the historic precedents, key discussions, and necessary next steps to enhance the quality of open access data. By agreement, this article is published simultaneously in Proteomics, Proteomics Clinical Applications, Journal of Proteome Research, and Molecular and Cellular Proteomics, as a public service to the research community. The peer review process was a coordinated effort conducted by a panel of referees selected by the journals.

Recommendations for mass spectrometry data quality metrics for open access data (corollary to the Amsterdam Principles).

Policies supporting the rapid and open sharing of proteomic data are being implemented by the leading journals in the field. The proteomics community is taking steps to ensure that data are made publicly accessible and are of high quality, a challenging task that requires the development and deployment of methods for measuring and documenting data quality metrics. On September 18, 2010, the U.S. National Cancer Institute (NCI) convened the "International Workshop on Proteomic Data Quality Metrics" in Sydney, Australia, to identify and address issues facing the development and use of such methods for open access proteomics data. The stakeholders at the workshop enumerated the key principles underlying a framework for data quality assessment in mass spectrometry data that will meet the needs of the research community, journals, funding agencies, and data repositories. Attendees discussed and agreed up on two primary needs for the wide use of quality metrics: (1) an evolving list of comprehensive quality metrics and (2) standards accompanied by software analytics. Attendees stressed the importance of increased education and training programs to promote reliable protocols in proteomics. This workshop report explores the historic precedents, key discussions, and necessary next steps to enhance the quality of open access data. By agreement, this article is published simultaneously in the Journal of Proteome Research, Molecular and Cellular Proteomics, Proteomics, and Proteomics Clinical Applications as a public service to the research community. The peer review process was a coordinated effort conducted by a panel of referees selected by the journals.

Recommendations for mass spectrometry data quality metrics for open access data (corollary to the Amsterdam Principles).

Policies supporting the rapid and open sharing of proteomic data are being implemented by the leading journals in the field. The proteomics community is taking steps to ensure that data are made publicly accessible and are of high quality, a challenging task that requires the development and deployment of methods for measuring and documenting data quality metrics. On September 18, 2010, the United States National Cancer Institute convened the "International Workshop on Proteomic Data Quality Metrics" in Sydney, Australia, to identify and address issues facing the development and use of such methods for open access proteomics data. The stakeholders at the workshop enumerated the key principles underlying a framework for data quality assessment in mass spectrometry data that will meet the needs of the research community, journals, funding agencies, and data repositories. Attendees discussed and agreed up on two primary needs for the wide use of quality metrics: 1) an evolving list of comprehensive quality metrics and 2) standards accompanied by software analytics. Attendees stressed the importance of increased education and training programs to promote reliable protocols in proteomics. This workshop report explores the historic precedents, key discussions, and necessary next steps to enhance the quality of open access data. By agreement, this article is published simultaneously in the Journal of Proteome Research, Molecular and Cellular Proteomics, Proteomics, and Proteomics Clinical Applications as a public service to the research community. The peer review process was a coordinated effort conducted by a panel of referees selected by the journals.

A systems view of epithelial-mesenchymal transition signaling states.

Epithelial-mesenchymal transition (EMT) is an important contributor to the invasion and metastasis of epithelial-derived cancers. While considerable effort has focused in the regulators involved in the transition process, we have focused on consequences of EMT to prosurvival signaling. Changes in distinct metastable and 'epigentically-fixed' EMT states were measured by correlation of protein, phosphoprotein, phosphopeptide and RNA transcript abundance. The assembly of 1167 modulated components into functional systems or machines simplified biological understanding and increased prediction confidence highlighting four functional groups: cell adhesion and migration, metabolism, transcription nodes and proliferation/survival networks. A coordinate metabolic reduction in a cluster of 17 free-radical stress pathway components was observed and correlated with reduced glycolytic and increased oxidative phosphorylation enzyme capacity, consistent with reduced cell cycling and reduced need for macromolecular biosynthesis in the mesenchymal state. An attenuation of EGFR autophosphorylation and a switch from autocrine to paracrine-competent EGFR signaling was implicated in the enablement of tumor cell chemotaxis. A similar attenuation of IGF1R, MET and RON signaling with EMT was observed. In contrast, EMT increased prosurvival autocrine IL11/IL6-JAK2-STAT signaling, autocrine fibronectin-integrin α5ß1 activation, autocrine Axl/Tyro3/PDGFR/FGFR RTK signaling and autocrine TGFßR signaling. A relatively uniform loss of polarity and cell-cell junction linkages to actin cytoskeleton and intermediate filaments was measured at a systems level. A more heterogeneous gain of ECM remodeling and associated with invasion and migration was observed. Correlation to stem cell, EMT, invasion and metastasis datasets revealed the greatest similarity with normal and cancerous breast stem cell populations, CD49f(hi)/EpCAM(-/lo) and CD44(hi)/CD24(lo), respectively.

Recommendations for mass spectrometry data quality metrics for open access data (corollary to the Amsterdam principles).

Policies supporting the rapid and open sharing of proteomic data are being implemented by the leading journals in the field. The proteomics community is taking steps to ensure that data are made publicly accessible and are of high quality, a challenging task that requires the development and deployment of methods for measuring and documenting data quality metrics. On September 18, 2010, the U.S. National Cancer Institute (NCI) convened the "International Workshop on Proteomic Data Quality Metrics" in Sydney, Australia, to identify and address issues facing the development and use of such methods for open access proteomics data. The stakeholders at the workshop enumerated the key principles underlying a framework for data quality assessment in mass spectrometry data that will meet the needs of the research community, journals, funding agencies, and data repositories. Attendees discussed and agreed up on two primary needs for the wide use of quality metrics: (i) an evolving list of comprehensive quality metrics and (ii) standards accompanied by software analytics. Attendees stressed the importance of increased education and training programs to promote reliable protocols in proteomics. This workshop report explores the historic precedents, key discussions, and necessary next steps to enhance the quality of open access data. By agreement, this article is published simultaneously in Proteomics, Proteomics Clinical Applications, Journal of Proteome Research, and Molecular and Cellular Proteomics, as a public service to the research community. The peer review process was a coordinated effort conducted by a panel of referees selected by the journals.

Nonlinear fitting method for determining local false discovery rates from decoy database searches.

False discovery rate (FDR) analyses of protein and peptide identification results using decoy database searching conventionally report aggregate or global FDRs for a whole set of identifications, which are often not very informative about the error rates of individual members in the set. We describe a nonlinear curve fitting method for calculating the local FDR, which estimates the chance that an individual protein (or peptide) is incorrect, and present a simple tool that implements this analysis. The goal of this method is to offer a simple extension to the now commonplace decoy database searching, providing additional valuable information.

The minimum information about a proteomics experiment (MIAPE).

Both the generation and the analysis of proteomics data are now widespread, and high-throughput approaches are commonplace. Protocols continue to increase in complexity as methods and technologies evolve and diversify. To encourage the standardized collection, integration, storage and dissemination of proteomics data, the Human Proteome Organization's Proteomics Standards Initiative develops guidance modules for reporting the use of techniques such as gel electrophoresis and mass spectrometry. This paper describes the processes and principles underpinning the development of these modules; discusses the ramifications for various interest groups such as experimentalists, funders, publishers and the private sector; addresses the issue of overlap with other reporting guidelines; and highlights the criticality of appropriate tools and resources in enabling 'MIAPE-compliant' reporting.

The Paragon Algorithm, a next generation search engine that uses sequence temperature values and feature probabilities to identify peptides from tandem mass spectra.

The Paragon Algorithm, a novel database search engine for the identification of peptides from tandem mass spectrometry data, is presented. Sequence Temperature Values are computed using a sequence tag algorithm, allowing the degree of implication by an MS/MS spectrum of each region of a database to be determined on a continuum. Counter to conventional approaches, features such as modifications, substitutions, and cleavage events are modeled with probabilities rather than by discrete user-controlled settings to consider or not consider a feature. The use of feature probabilities in conjunction with Sequence Temperature Values allows for a very large increase in the effective search space with only a very small increase in the actual number of hypotheses that must be scored. The algorithm has a new kind of user interface that removes the user expertise requirement, presenting control settings in the language of the laboratory that are translated to optimal algorithmic settings. To validate this new algorithm, a comparison with Mascot is presented for a series of analogous searches to explore the relative impact of increasing search space probed with Mascot by relaxing the tryptic digestion conformance requirements from trypsin to semitrypsin to no enzyme and with the Paragon Algorithm using its Rapid mode and Thorough mode with and without tryptic specificity. Although they performed similarly for small search space, dramatic differences were observed in large search space. With the Paragon Algorithm, hundreds of biological and artifact modifications, all possible substitutions, and all levels of conformance to the expected digestion pattern can be searched in a single search step, yet the typical cost in search time is only 2-5 times that of conventional small search space. Despite this large increase in effective search space, there is no drastic loss of discrimination that typically accompanies the exploration of large search space.

Discovering known and unanticipated protein modifications using MS/MS database searching.

We present an MS/MS database search algorithm with the following novel features: (1) a novel protein database structure containing extensive preindexing and (2) zone modification searching, which enables the rapid discovery of protein modifications of known (i.e., user-specified) and unanticipated delta masses. All of these features are implemented in Interrogator, the search engine that runs behind the Pro ID, Pro ICAT, and Pro QUANT software products. Speed benchmarks demonstrate that our modification-tolerant database search algorithm is 100-fold faster than traditional database search algorithms when used for comprehensive searches for a broad variety of modification species. The ability to rapidly search for a large variety of known as well as unanticipated modifications allows a significantly greater percentage of MS/MS scans to be identified. We demonstrate this with an example in which, out of a total of 473 identified MS/MS scans, 315 of these scans correspond to unmodified peptides, while 158 scans correspond to a wide variety of modified peptides. In addition, we provide specific examples where the ability to search for unanticipated modifications allows the scientist to discover: unexpected modifications that have biological significance; amino acid mutations; salt-adducted peptides in a sample that has nominally been desalted; peptides arising from nontryptic cleavage in a sample that has nominally been digested using trypsin; other unintended consequences of sample handling procedures.

Comparison of rates and kinetic isotope effects using PEG-modified variants and glycoforms of glucose oxidase: the relationship of modification of the protein envelope to C-H activation and tunneling.

An earlier investigation of the temperature dependencies of rates and kinetic isotope effects (KIEs) in glucose oxidase (GO) used variants that differed in the extent of glycosylation at the surface of the protein. Kohen et al. [Kohen, A., Jonsson, T., and Klinman, J. P. (1997) Biochemistry 36, 2603-2611] presented evidence that the KIE on the Arrhenius prefactor varied as a function of protein modification, concluding that the degree of hydrogen tunneling at the active site was dependent on changes in mass at the surface. We now examine GO proteins containing polyethylene glycol (PEG) at their surface and a more extensively glycosylated form of GO, to distinguish simple mass effects from other sources of altered catalytic behavior. One PEG variant was created by modifying deglycosylated GO with short PEG chains (average of 350 Da each), while another contained a smaller number of long PEG chains (average of 5000 Da each). The light (146 kDa) and heavy (211 kDa) PEG variants and the hyperglycosylated variant display isotope effects on the Arrhenius prefactor that are similar (A(D)/A(T) = 0.55-0.62), while the unperturbed wild-type GO (WT-GO) is found to have an A(D)/A(T) that is reassessed as being close to unity. It appears that any modification of the protein surface away from that of the wild type gives rise to altered behavior for hydrogen transfer in the active site. We have also compared the effect of enthalpies of activation on both k(cat)/K(M) and k(cat) for the variants, introducing a new method to extract the k(cat)/K(M) rate constant and enthalpy of activation for the tritiated substrate from competitive KIE experiments. We find similar trends in Delta H(++) for both competitive and noncompetitive parameters and a smaller trend in k(cat) than reported earlier. Correlations are observed between A(D)/A(T) and both the enthalpies of activation and the thermal melt temperatures (T(M)) of the GO isoforms. In addition to the present study, there are now a number of examples where a perturbation of enzyme structure away from that of the wild type causes the observed KIE to become more temperature-dependent. The implications of these findings are discussed in the context of hydrogen tunneling and the relationship of protein structure and dynamics to this process.