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Objectives Liquid chromatography-tandem mass spectrometry (LC-MS/MS) panels that include glucocorticoid-related steroids are increasingly used to characterize and diagnose adrenal cortical diseases. Limited information is currently available about reproducibility of these measurements among laboratories. The aim of the study was to compare LC-MS/MS measurements of corticosterone, 11-deoxycortisol and cortisone at eight European centers and assess the performance after unification of calibration. Methods Seventy-eight patient samples and commercial calibrators were measured twice by laboratory-specific procedures. Results were obtained according to in-house and external calibration. We evaluated intra-laboratory and inter-laboratory imprecision, regression and agreement against performance specifications derived from 11-deoxycortisol biological variation. Results Intra-laboratory CVs ranged between 3.3 and 7.7%, 3.3 and 11.8% and 2.7 and 12.8% for corticosterone, 11-deoxycortisol and cortisone, with 1, 4 and 3 laboratories often exceeding the maximum allowable imprecision (MAI), respectively. Median inter-laboratory CVs were 10.0, 10.7 and 6.2%, with 38.5, 50.7 and 2.6% cases exceeding the MAI for corticosterone, 11-deoxycortisol and cortisone, respectively. Median laboratory bias vs. all laboratory-medians ranged from −5.6 to 12.3% for corticosterone, −14.6 to 12.4% for 11-deoxycortisol and −4.0 to 6.5% for cortisone, with few cases exceeding the total allowable error. Modest deviations were found in regression equations among most laboratories. External calibration did not improve 11-deoxycortisol and worsened corticosterone and cortisone inter-laboratory comparability. Conclusions Method imprecision was variable. Inter-laboratory performance was reasonably good. However, cases with imprecision and total error above the acceptable limits were apparent for corticosterone and 11-deoxycortisol. Variability did not depend on calibration but apparently on imprecision, accuracy and specificity of individual methods. Tools for improving selectivity and accuracy are required to improve harmonization.

The dysregulation of the hormone cortisol is related to several pathological states, and its monitoring could help prevent severe stress, fatigue, and mental diseases. While wearable antibody-based biosensors could allow real-time and simple monitoring of antigens, an accurate and low-cost antibody-based cortisol detection through electro-chemical methods is considerably challenging due to its low concentration and the high ionic strength of real biofluids. Here, a label-free and fast sensor for cortisol detection is proposed based on antibody-coated organic electrochemical transistors. The developed devices show unprecedented high sensitivities of 50 mu A/dec for cortisol sensing in high-ionic-strength solutions with effective cortisol detection demonstrated with real human sweat. The sensing mechanism is analyzed through impedance spectroscopy and confirmed with electrical models. Compared to existing methods requiring bulky and expensive laboratory equipment, these wearable devices enable point-of-care cortisol detection in 5 min with direct sweat collection for personalized well-being monitoring.

The Human Proteome Organization (HUPO) Proteomics Standards Initiative (PSI) has been successfully developing guidelines, data formats, and controlled vocabularies (CVs) for the proteomics community and other fields supported by mass spectrometry since its inception 20 years ago. Here we describe the general operation of the PSI, including its leadership, working groups, yearly workshops, and the document process by which proposals are thoroughly and publicly reviewed in order to be ratified as PSI standards. We briefly describe the current state of the many existing PSI standards, some of which remain the same as when originally developed, some of which have undergone subsequent revisions, and some of which have become obsolete. Then the set of proposals currently being developed are described, with an open call to the community for participation in the forging of the next generation of standards. Finally, we describe some synergies and collaborations with other organizations and look to the future in how the PSI will continue to promote the open sharing of data and thus accelerate the progress of the field of proteomics.

The Human Proteome Organization (HUPO) Proteomics Standards Initiative (PSI) has been successfully developing guidelines, data formats, and controlled vocabularies (CVs) for the proteomics community and other fields supported by mass spectrometry since its inception twenty years ago. Here we describe the general operation of the PSI, including its leadership, working groups, yearly workshops, and the document process by which proposals are thoroughly and publicly reviewed in order to be ratified as PSI standards. We briefly describe the current state of the many existing PSI standards, some of which remain the same as when originally developed, some of which have undergone subsequent revisions, and some of which have become obsolete. Then the set of proposals currently being developed are described, with an open call to the community for participation in the forging of the next generation of standards. Finally, we describe some synergies and collaborations with other organizations and look to the future in how the PSI will continue to promote the open sharing of data and thus accelerate the progress of the field of proteomics.

Objectives Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is recommended for measuring circulating steroids. However, assays display technical heterogeneity. So far, reproducibility of corticosteroid LC-MS/MS measurements has received scant attention. The aim of the study was to compare LC-MS/MS measurements of cortisol, 17OH-progesterone and aldosterone from nine European centers and assess performance according to external quality assessment (EQA) materials and calibration. Methods Seventy-eight patient samples, EQA materials and two commercial calibration sets were measured twice by laboratory-specific procedures. Results were obtained by in-house (CAL1) and external calibrations (CAL2 and CAL3). We evaluated intra and inter-laboratory imprecision, correlation and agreement in patient samples, and trueness, bias and commutability in EQA materials. Results Using CAL1, intra-laboratory CVs ranged between 2.8–7.4%, 4.4–18.0% and 5.2–22.2%, for cortisol, 17OH-progesterone and aldosterone, respectively. Trueness and bias in EQA materials were mostly acceptable, however, inappropriate commutability and target value assignment were highlighted in some cases. CAL2 showed suboptimal accuracy. Median inter-laboratory CVs for cortisol, 17OH-progesterone and aldosterone were 4.9, 11.8 and 13.8% with CAL1 and 3.6, 10.3 and 8.6% with CAL3 (all p Conclusions Intra-laboratory imprecision and performance with EQA materials were variable. Inter-laboratory performance was mostly within specifications. Although residual variability persists, adopting common traceable calibrators and RMP-determined EQA materials is beneficial for standardization of LC-MS/MS steroid measurements.

There is the need to represent in a standard manner all the possible variations of a protein or peptide primary sequence, including both artefactual and post-translational modifications of peptides and proteins. With that overall aim, here, the Human Proteome Organization (HUPO) Proteomics Standards Initiative (PSI) has developed a notation, called ProForma 2.0, which is a substantial extension of the original ProForma notation, developed by the Consortium for Top-Down Proteomics (CTDP). ProForma 2.0 aims to unify the representation of proteoforms and peptidoforms. Therefore, this notation supports use cases needed for bottom-up and middle/topdown proteomics approaches and allows the encoding of highly modified proteins and peptides using a human and machine-readable string. ProForma 2.0 covers encoding protein modification names and accessions, cross-linking reagents including disulfides, glycans, modifications encoded using mass shifts and/or via chemical formulas, labile and C or N-terminal modifications, ambiguity in the modification position and representation of atomic isotopes, among other use cases. Notational conventions are based on public controlled vocabularies and ontologies. Detailed information about the notation and existing implementations are available at http://www.psidev.info/proforma and at the corresponding GitHub repository (https://github.com/HUPO-PSI/proforma).

Creatine (Cr) is a nitrogenous organic acid and plays roles such as fast phosphate energy buffer to replenish ATP, osmolyte, antioxidant, neuromodulator, and as a compound with anabolic and ergogenic properties in muscle. Cr is taken from the diet or endogenously synthetized by the enzymes arginine:glycine amidinotransferase and guanidinoacetate methyltransferase, and specifically taken up by the transporter SLC6A8. Loss-of-function mutations in the genes encoding for the enzymes or the transporter cause creatine deficiency syndromes (CDS). CDS are characterized by brain Cr deficiency, intellectual disability with severe speech delay, behavioral troubles, epilepsy, and motor dysfunction. Among CDS, the X-linked Cr transporter deficiency (CTD) is the most prevalent with no efficient treatment so far. Different animal models of CTD show reduced brain Cr levels, cognitive deficiencies, and together they cover other traits similar to those of patients. However, motor function was poorly explored in CTD models, and some controversies in the phenotype exist in comparison with CTD patients. Our recently described Slc6a8^(Y389C) knock-in rat model of CTD showed mild impaired motor function, morphological alterations in cerebellum, reduced muscular mass, Cr deficiency, and increased guanidinoacetate content in muscle, although no consistent signs of muscle atrophy. Our results indicate that such motor dysfunction co-occurred with both nervous and muscle dysfunctions, suggesting that muscle strength and performance as well as neuronal connectivity might be affected by this Cr deficiency in muscle and brain., Journal of Inherited Metabolic Disease, 45 (2), ISSN:1573-2665, ISSN:0141-8955

Universal Spectrum Identifier (USI) provides a standardized mechanism for encoding a virtual path to mass spectra deposited to public repositories or contained in public spectral libraries. Mass spectra provide the ultimate evidence to support the findings of mass spectrometry proteomics studies in publications, and it is therefore crucial to be able to trace the conclusions back to the spectra. The Universal Spectrum Identifier (USI) provides a standardized mechanism for encoding a virtual path to any mass spectrum contained in datasets deposited to public proteomics repositories. USI enables greater transparency of spectral evidence, with more than 1 billion USI identifications from over 3 billion spectra already available through ProteomeXchange repositories.

Creatine (Cr) is a nitrogenous organic acid and plays roles as fast phosphate energy buffer to replenish ATP, osmolyte, antioxidant, neuromodulator, and as a compound with anabolic and ergogenic properties in muscle. Cr is taken from the diet or endogenously synthetized by the enzymes AGAT and GAMT, and specifically taken up by the transporter SLC6A8. Loss-of-function mutations in the genes encoding for the enzymes or the transporter cause Cerebral Creatine Deficiency Syndromes (CCDS). CCDS are characterized by brain Cr deficiency, intellectual disability with severe speech delay, behavioral troubles, epilepsy and motor dysfunction. Among CCDS, the X-linked Cr transporter deficiency (CTD) is the most prevalent with no efficient treatment so far. Different animal models of CTD show reduced brain Cr levels, cognitive deficiencies and together they cover other traits similar to those of patients. However, motor function was poorly explored in CTD models and some controversies in the phenotype exist in comparison with CTD patients. Our recently described Slc6a8Y389C knock-in (KI) rat model of CTD showed mild impaired motor function, morphological alterations in cerebellum, reduced muscular mass, Cr deficiency and increased guanidinoacetate content in muscle, although no consistent signs of muscle atrophy. Our results indicate that such motor dysfunction co-occurred with both nervous and muscle dysfunction, suggesting that muscle strength and performance as well as neuronal connectivity might be affected by this Cr deficiency in muscle and brain.

Background Burn patients characteristically have increased energy, glucose and protein requirements. Glutamine supplementation is strongly recommended during early phase treatment and is associated with improved immunity, wound healing, and reduced mortality. This study evaluated if early burn exudative losses might contribute to higher supplementation needs. Methods Patients admitted to the burn intensive care unit (ICU) had exudate collection from tight bandages applied to arms or legs during the first week (exudate aliquot twice daily). Seven amino acids (alanine, arginine, cystine, glutamine, leucine, lysine, methionine) were quantified by liquid chromatography-mass spectrometry. Descriptive analysis of all results is provided as in medians and interquartile ranges or in value ranges. Results Eleven patients aged 19 to 77 years, presenting with burns on 18 to 70% of body surface, with a median SAPSII 33 (range 16 to 56) were included during the study period. The highest amino acid losses were observed during the first 3 days with an important inter- and intra-patient variability. Glutamine and alanine losses were highest, followed by leucine and lysine in all patients: amino acid exudate concentrations were in the range of normal plasma concentrations and stable over time. Total glutamine losses were correlated to burned surface (r2 = 0.552, p = 0.012), but not to enteral glutamine supplements. Conclusions The study shows significant exudative losses during early stage burn recovery and particularly for glutamine and alanine. Glutamine loss generally decreased with wound closure and subsequent decline of exudation and evolving size of burn surfaces. This article is protected by copyright. All rights reserved.

Creatine is an organic compound used as fast phosphate energy buffer to recycle ATP, important in tissues with high energy demand such as muscle or brain. Creatine is taken from the diet or endogenously synthetized by the enzymes AGAT and GAMT, and specifically taken up by the transporter SLC6A8. Deficit in the endogenous synthesis or in the transport leads to Cerebral Creatine Deficiency Syndromes (CCDS). CCDS are characterized by brain creatine deficiency, intellectual disability with severe speech delay, behavioral troubles such as attention deficits and/or autistic features, and epilepsy. Among CCDS, the X-linked creatine transporter deficiency (CTD) is the most prevalent with no efficient treatment so far. Different mouse models of CTD were generated by doing long deletions in theSlc6a8gene showing reduced brain creatine and cognitive deficiencies or impaired motor function. We present a new knock-in (KI) rat model of CTD holding an identical point mutation found in patients with reported lack of transporter activity. KI males showed brain creatine deficiency, increased urinary creatine/creatinine ratio, cognitive deficiency and autistic features.Slc6a8xY389CKI rat fairly enriches the spectrum of CTD models and provides new data about the pathology, being the first animal model of CTD carrying a point mutation.

A protein designed to sense metabolites Many diseases cause characteristic changes in blood metabolites. Yu et al. describe a paper-based assay in which a chosen metabolite can be oxidized to generate reduced nicotinamide adenine dinucleotide phosphate (NADPH). Color changes in a designed NADPH sensor protein are then quantified by a digital camera. The sensor system successfully generated point-of-care measurements of phenylalanine, glucose, and glutamate. Concentrations of phenylalanine in the blood of phenylketonuria patients were analyzed within minutes with only half a microliter of blood. Science , this issue p. 1122

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 backwards 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 athttp://www.psidev.info/peff.

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. acceptedVersion

The 2017 Dagstuhl Seminar on Computational Proteomics provided an opportunity for a broad discussion on the current state and future directions of the generation and use of peptide tandem mass spectrometry spectral libraries. Their use in proteomics is growing slowly, but there are multiple challenges in the field that must be addressed to further increase the adoption of spectral libraries and related techniques. The primary bottlenecks are the paucity of high quality and comprehensive libraries and the general difficulty of adopting spectral library searching into existing workflows. There are several existing spectral library formats, but none captures a satisfactory level of metadata; therefore, a logical next improvement is to design a more advanced, Proteomics Standards Initiative-approved spectral library format that can encode all of the desired metadata. The group discussed a series of metadata requirements organized into three designations of completeness or quality, tentatively dubbed bronze, silver, and gold. The metadata can be organized at four different levels of granularity: at the collection (library) level, at the individual entry (peptide ion) level, at the peak (fragment ion) level, and at the peak annotation level. Strategies for encoding mass modifications in a consistent manner and the requirement for encoding high-quality and commonly seen but as-yet-unidentified spectra were discussed. The group also discussed related topics, including strategies for comparing two spectra, techniques for generating representative spectra for a library, approaches for selection of optimal signature ions for targeted workflows, and issues surrounding the merging of two or more libraries into one. We present here a review of this field and the challenges that the community must address in order to accelerate the adoption of spectral libraries in routine analysis of proteomics datasets.

Objective To describe the goals of the Proteomics Standards Initiative (PSI) of the Human Proteome Organization, the methods that the PSI has employed to create data standards, the resulting output of the PSI, lessons learned from the PSI’s evolution, and future directions and synergies for the group.Materials and Methods The PSI has 5 categories of deliverables that have guided the group. These are minimum information guidelines, data formats, controlled vocabularies, resources and software tools, and dissemination activities. These deliverables are produced via the leadership and working group organization of the initiative, driven by frequent workshops and ongoing communication within the working groups. Official standards are subjected to a rigorous document process that includes several levels of peer review prior to release.Results We have produced and published minimum information guidelines describing what information should be provided when making data public, either via public repositories or other means. The PSI has produced a series of standard formats covering mass spectrometer input, mass spectrometer output, results of informatics analysis (both qualitative and quantitative analyses), reports of molecular interaction data, and gel electrophoresis analyses. We have produced controlled vocabularies that ensure that concepts are uniformly annotated in the formats and engaged in extensive software development and dissemination efforts so that the standards can efficiently be used by the community.Conclusion In its first dozen years of operation, the PSI has produced many standards that have accelerated the field of proteomics by facilitating data exchange and deposition to data repositories. We look to the future to continue developing standards for new proteomics technologies and workflows and mechanisms for integration with other omics data types. Our products facilitate the translation of genomics and proteomics findings to clinical and biological phenotypes. The PSI website can be accessed at http://www.psidev.info.

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, co-chairs, 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. Further, 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 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.

The Annual 2014 Spring Workshop of the Proteomics Standards Initiative (PSI) of the Human Proteome Organization (HUPO) was held this year jointly with the metabolomics COordination of Standards in MetabOlomicS (COSMOS) group. The range of existing MS standards (mzML, mzIdentML, mzQuantML, mzTab, TraML) was reviewed and updated in the light of new methodologies and advances in technologies. Adaptations to meet the needs of the metabolomics community were incorporated and a new data format for NMR, nmrML, was presented. The molecular interactions workgroup began work on a new version of the existing XML data interchange format. PSI-MI XML3.0 will enable the capture of more abstract data types such as protein complex topology derived from experimental data, allosteric binding, and dynamic interactions. Further information about the work of the HUPO-PSI can be found at http://www.psidev.info.

This paper focuses on the use of controlled vocabularies (CVs) and ontologies especially in the area of proteomics, primarily related to the work of the Proteomics Standards Initiative (PSI). It describes the relevant proteomics standard formats and the ontologies used within them. Software and tools for working with these ontology files are also discussed. The article also examines the “mapping files” used to ensure correct controlled vocabulary terms that are placed within PSI standards and the fulfillment of the MIAPE (Minimum Information about a Proteomics Experiment) requirements. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan., Highlights ► The semantic annotation using ontologies is a prerequisite for the semantic web. ► The HUPO-PSI defined a set of XML-based standard formats for proteomics. ► These standard formats allow the referencing of CV terms defined in obo files. ► The CV terms can be used to enforce MIAPE compliance of the data files. ► The mass spectrometry CV is constantly maintained in a community process.

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.

This article belongs to a special issue Special Issue: Standardization and Quality Control in Proteomics: Technical note.-- et al., Mass spectrometry is already a well-established protein identification tool and recent methodological and technological developments have also made possible the extraction of quantitative data of protein abundance in large-scale studies. Several strategies for absolute and relative quantitative proteomics and the statistical assessment of quantifications are possible, each having specific measurements and therefore, different data analysis workflows. The guidelines for Mass Spectrometry Quantification allow the description of a wide range of quantitative approaches, including labeled and label-free techniques and also targeted approaches such as Selected Reaction Monitoring (SRM).

The Human Proteome Organisation Proteomics Standards Initiative (HUPO-PSI) was established in 2002 with the aim of defining community standards for data representation in proteomics and facilitating data comparison, exchange and verification. The 2013 annual spring workshop was hosted by the University of Liverpool, UK and concentrated on updating and refining the existing standards in the light of new methodologies and technologies. To control the inflation of file sizes, strategies for file compression, particularly for mzML files, were explored. Best practices for encoding information such as protein grouping and PTM localisation were refined and documented. Additional example files for the mzQuantML format were designed to provide support for selected reaction monitoring techniques. Enhancements to the PSI Common Query Interface (PSICQUIC) and PSI-MI XML were discussed. Finally, the group engaged in discussion on how the existing work of the HUPO-PSI can be leveraged by the Metabolomics Standards Initiative to improve the capture of metabolite data.

Type 2 diabetes is a worldwide disease reaching epidemic dimensions. The rapid progression of the disease urgently calls for both a broader and deeper understanding of its pathophysiology. In line with this statement, the Human Diabetes Proteome Project (HDPP) was officially launched at the 11th HUPO meeting in Boston, 2012. A special session was dedicated to this new initiative, gathering experts in the main topics related to diabetes and its associated complications. Key issues were debated with a focus on how deranged circulating glucose and free fatty acids induce dysfunction. It has been decided that HDPP will therefore focus on studying the early stages of diabetes that lead to abnormal glucose and lipid levels. The initiative will initially focused on islets of Langerhans, insulin-producing cell lines, and blood human samples from diabetes-related cohorts. In subsequent stages HDPP will investigate target tissues in which glucose and lipids could promote protein dysfunctions. Omics-rooted systems approaches enhanced by bioinformatics will be deployed to unravel effects of lipids and glucose triggering diabetes initiation and progression. A first milestone has been defined for the 12th HUPO meeting in Yokohama, 2013: the 1000 diabetes-associated protein (the 1000-HDPP) database, i.e. a freely available internet resource ( www.HDPP.info ) of more than 1000 proteins with links to their corresponding proteotypic peptides, affinity reagents and protein-specific biological/biomedical information.

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 non-redundant 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/.

The Human Proteome Organisation Proteomics Standards Initiative (HUPO-PSI) was established in 2002 with the aim of defining community standards for data representation in proteomics and facilitating data comparison, exchange and verification. Over the last 10 years significant advances have been made, with common data standards now published and implemented in the field of both mass spectrometry and molecular interactions. The 2012 meeting further advanced this work, with the mass spectrometry groups finalising approaches to capturing the output from recent developments in the field, such as quantitative proteomics and SRM. The molecular interaction group focused on improving the integration of data from multiple resources. Both groups united with a guest work track, organized by the HUPO Technology/Standards Committee, to formulate proposals for data submissions from the HUPO Human Proteome Project and to start an initiative to collect standard experimental protocols.

Human Proteome Organisation (HUPO) Highlights.-- El pdf es la versión post-print.-- et al., The plenary session of the Proteomics Standards Initiative (PSI) of the Human Proteome Organization at the Tenth annual HUPO World Congress updated the delegates on the ongoing activities of this group. The Molecular Interactions workgroup described the success of the PSICQUIC web service, which enables users to access multiple interaction resources with a single query. One user instance is the IMEx Consortium, which uses the service to enable users to access a non-redundant set of protein-protein interaction records. The mass spectrometry data formats, mzML for mass spectrometer output files and mzIdentML for the output of search engines, are now successfully established with increasing numbers of implementations. A format for the output of quantitative proteomics data, mzQuantML, and also TraML, for SRM/MRM transition lists, are both currently nearing completion. The corresponding MIAPE documents are being updated in line with advances in the field, as is the shared controlled vocabulary PSI-MS. In addition, the mzTab format was introduced, as a simpler way to report MS proteomics and metabolomics results. Finally, the ProteomeXchange Consortium, which will supply a single entry point for the submission of MS proteomics data to multiple data resources including PRIDE and PeptideAtlas, is currently being established., Much of this work has been funded by the European Commission FP7 programme, under PSIMEx (contract number FP7-HEALTH-2007-223411) and Proteome- Xchange (grant number 260558).

The plenary session of the Proteomics Standards Initiative of the Human Proteome Organisation at the 8th Annual HUPO World Congress updated the delegates on the current status of the ongoing work of this group. The mass spectrometry group reviewed the progress of mzML since its release last year and detailed new work on providing a common format for SRM/MRM transition lists (TraML). The implementation of mzIdentML, for describing the output of proteomics search engines, was outlined and the release of a new web service PSICQUIC, which allows users to simultaneously search multiple interaction databases, was announced. Finally, the audience participated in a lively debate, discussing both the benefits of these standard formats and issues with their adoption and use in a research environment.

In proteomics, rapid developments in instrumentation led to the acquisition of increasingly large data sets. Correspondingly, ProDaC was founded in 2006 as a Coordination Action project within the 6th European Union Framework Programme to support data sharing and community-wide data collection. The objectives of ProDaC were the development of documentation and storage standards, setup of a standardized data submission pipeline and collection of data. Ending in March 2009, ProDaC has delivered a comprehensive toolbox of standards and computer programs to achieve these goals.

Searching a spectral library for the identification of protein MS/MS data has proven to be a fast and accurate method, while yielding a high identification rate. We investigated the potential to increase peptide discovery rate, with little increase in computational time, by constructing a workflow based on a sequence search with Phenyx followed by a library search with SpectraST. Searching a consensus library compiled from the search results of the prior Phenyx search increased the number of confidently matched spectra by up to 156%. Additionally matched spectra by SpectraST included noisy spectra, spectra representing missed cleaved peptides as well as spectra from post-translationally modified peptides.

The Human Proteome Organization Proteomics Standards Initiative has produced reporting requirements and data interchange formats for the proteomics community. The implementation of these increasingly mature formats was the main focus of this meeting, with extensions being made to many schema to enable encoding of new data types. The endorsement of the proteomics standards initiative standards by an increasing number of journals is a main driving force behind tool development and a recognized need to ease the process of data deposition into the public domain for the bench scientist.

The role of the Human Proteome Organisation Proteomics Standards Initiative (HUPO-PSI) is to produce and release community-accepted reporting requirements, interchange formats and controlled vocabularies for mass spectrometry proteomics and related technologies such as gel electrophoresis, column chromatography and molecular interactions. A number of significant advances were made at this workshop, with the new MS standard, mzML, being finalised prior to release on 1(st) June 2008 and analysisXML, which will allow protein and peptide identifications and post-translational modifications to be captured, being prepared to enter the review process this summer. The accompanying controlled vocabularies are continuing to evolve and a number of standards papers are now being finalised prior to publication.

The autumn workshop of the Proteomics Standards Initiative of the Human Proteomics Organisation met to further advance the development of the existing standards in the fields of molecular interactions and mass spectrometry. In addition, new areas were addressed, in particular developing standards for the description and exchange of data from gel electrophoresis experiments. The General Proteomics Standards group is now working closely with the FuGE (Functional Genomics Experiment) efforts to define a general standard in which to encode data that will enable a systems biology approach to data analysis. Common to all these efforts is the field of protein modifications, and work has been initiated to establish an ontology in this field that can be used by both workers in the field of proteomics and the wider scientific community.

Acquisition of tandem mass spectra from peptides or other analytes deposited on non-conductive membranes is inhibited on instruments combining matrix-assisted laser desorption/ionization with tandem time-of-flight analyzers (MALDI-TOF/TOF) due to a charging effect. A thin layer of gold renders the membrane conductive. This allows adequate data acquisition on MALDI-TOF/TOF systems. Therefore, this methodology extends the capacity of the molecular scanner concept to tandem mass spectrometry.

Rapid advances in mass spectrometry have positioned it as a prime tool for diagnosis and biomarker discovery. Distilling a handful of accurate disease markers from the thousands of mass-to-charge ratios that comprise a mass spectrum raises non-trivial data analytic challenges. Thus, mass-spectral analysis is turning more and more to data mining, a technology that lies at the crossroads of artificial intelligence and statistical data analysis. This review describes recent attempts at applying data mining techniques to extract diagnostic biomarkers for cancer from SELDI-TOF and MALDI-TOF mass spectra.

The development of high throughput utilities to identify proteins is a major challenge in present research in the field of proteomics. One such utility, the molecular scanner, uses proteins separated by two-dimensional polyacrylamide gel electrophoresis that are digested in the gel and during transfer onto a collecting membrane. After adding a matrix, the membrane is inserted into a matrix-assisted laser desorption/ionization-time of flight mass spectrometer and a peptide mass fingerprint (PMF) is measured for every scanned site. Since the spacing between scanned sites is much smaller than the size of the most abundant protein spots, there is a certain redundancy in the data that was used in an earlier experiment with Escherichia coli [1] to improve mass calibration and PMF identification results. It was observed that the signal intensity of a peptide mass as a function of the position on the membrane showed similar patterns if peptides stemmed from the same protein. Taking account of these similarities a clustering algorithm was used to find lists of experimental masses with similar intensity distributions, which provided clearer identification of the corresponding proteins. Here, these methods are applied to a human plasma scan, where proteins were highly modified and less separated. The presence of very abundant proteins like albumin and immunoglobulins added another difficulty. The calibration of the initial PMFs was not satisfactory and masses had to be recalibrated. After discarding chemical noise, the membrane was partitioned into regions and for each region protein identification was carried out separately. A new scoring method was used, where the PMF score was multiplied by a factor that measures the similarity of matching peptides. This method proved to be more robust than the method developed in [1] if the region where a protein was found had an extended, nonspherical shape and strong overlap with regions of other proteins. Many proteins annotated on the SWISS-2D PAGE human plasma master gel could be clearly identified and many interesting properties were observed.

Matrix-assisted laser desorption/ionization-time of flight mass spectrometry has become a valuable tool in proteomics. With the increasing acquisition rate of mass spectrometers, one of the major issues is the development of accurate, efficient and automatic peptide mass fingerprinting (PMF) identification tools. Current tools are mostly based on counting the number of experimental peptide masses matching with theoretical masses. Almost all of them use additional criteria such as isoelectric point, molecular weight, PTMs, taxonomy or enzymatic cleavage rules to enhance prediction performance. However, these identification tools seldom use peak intensities as parameter as there is currently no model predicting the intensities based on the physicochemical properties of peptides. In this work, we used standard datamining methods such as classification and regression methods to find correlations between peak intensities and the properties of the peptides composing a PMF spectrum. These methods were applied on a dataset comprising a series of PMF experiments involving 157 proteins. We found that the C4.5 method gave the more informative results for the classification task (prediction of the presence or absence of a peptide in a spectra) and M5' for the regression methods (prediction of the normalized intensity of a peptide peak). The C4.5 result correctly classified 88% of the theoretical peaks; whereas the M5' peak intensities had a correlation coefficient of 0.6743 with the experimental peak intensities. These methods enabled us to obtain decision and model trees that can be directly used for prediction and identification of PMF results. The work performed permitted to lay the foundations of a method to analyze factors influencing the peak intensity of PMF spectra. A simple extension of this analysis could lead to improve the accuracy of the results by using a larger dataset. Additional peptide characteristics or even PMF experimental parameters can also be taken into account in the datamining process to analyze their influence on the peak intensity. Furthermore, this datamining approach can certainly be extended to the tandem mass spectrometry domain or other mass spectrometry derived methods.

Beyond an analysis of gene function at the genome level, the ultimate goal of functional genomics is to understand the organisation and coordinated operation of the cell. Integration of data and information is an essential feature of all the steps leading from the production of experimental results to the modelling of a complete cell. The Geneva workshop, organised within the framework of the European Science Foundation (ESF) Programme on Integrated Approaches for Functional Genomics (http://www.functionalgenomics.org.uk), provided an excellent opportunity to review the issue of data integration from various perspectives. It brought together scientists with different backgrounds (biologists, bioinformaticians), who currently participate in consortia involving or requiring the integration of heterogeneous biological data. The workshop dedicated equal time to presentations and discussions in order to optimise knowledge distribution and sharing. The first session was devoted to existing functional genomics projects, where diverse sets of experimental approaches are applied to a model organism or given project. For these, both the scientific objectives and data management strategies were described. Another set of presentations focused on ‘data integration requirements’ in proteomics. In this rapidly evolving area, data integration is a key issue for technological developments that are being carried out in both academic and industrial contexts. Data integration approaches were then presented by scientists involved in the design and maintenance of public database resources. The last session was devoted to bioinformatics and gave an overview of state of the art approaches for building up information systems with good capabilities with respect to data integration. The workshop concluded with an open discussion on bottlenecks and perspectives that emerged from the presentations. As a number of speakers have submitted reviews based on their presentations that are appearing in this issue of CFG and in the next one, in this report Comparative and Functional Genomics Comp Funct Genom 2002; 3: 16–21. DOI: 10.1002 / cfg.134

UniProtKB/Swiss-Prot provides expert curation with information extracted from literature and curator-evaluated computational analysis. As knowledgebases continue to play an increasingly important role in scientific research, a number of studies have evaluated their accuracy and revealed various errors. While some are curation errors, others are the result of incorrect information published in the scientific literature. By taking the example of sirtuin-5, a complex annotation case, we will describe the curation procedure of UniProtKB/Swiss-Prot and detail how we report conflicting information in the database. We will demonstrate the importance of collaboration between resources to ensure curation consistency and the value of contributions from the user community in helping maintain error-free resources. Database URL: www.uniprot.org

Escherichia coli is a model organism for biochemical and biological studies as it is one of the best characterised prokaryote. Two-dimensional polyacrylamide gel electrophoresis, computer image analysis and different protein identification techniques gave rise, in 1995, to the Escherichia coli SWISS-2D PAGE database (http://www.expasy.ch/ch2d/). In the E. coli 3.5-10 SWISS-2D PAGE map, 40% of the E. coli proteome was displayed. The present study demonstrated that the use of narrow range pH gradients is able to potentially display up to a few copies of protein per E. coli cell. Moreover, the six new E. coli SWISS-2D PAGE maps (pH 4-5, 4.5-5.5, 5-6, 5.5-6.7, 6-9 and 6-11) presented here displayed altogether more than 70% of the entire E. coli proteome.

A number of two-dimensional electrophoresis (2-DE) reference maps from mouse samples have been established and could be accessed through the internet. An up-to-date list can be found in WORLD-2D PAGE (http://www.expasy.ch/ch2d/2d- index.html), an index of 2-DE databases and services. None of them were established from mouse white and brown adipose tissues, pancreatic islets, liver nuclei and skeletal muscle. This publication describes the mouse SWISS-2D PAGE database. Proteins present in samples of mouse (C57BI/6J) liver, liver nuclei, muscle, white and brown adipose tissue and pancreatic islets are assembled and described in an accessible uniform format. SWISS-2D PAGE can be accessed through the World Wide Web (WWW) network on the ExPASy molecular biology server (http://www.expasy.ch/ ch2d/).

The heat shock proteins (hsp) are ubiquitous molecules induced in cells exposed to sublethal heat shock, present in all living cells, and highly conserved during evolution. Their function is to protect cells from environmental stress damage by binding to partially denatured proteins, dissociating protein aggregates, to regulate the correct folding, and to cooperate in transporting newly synthesized polypeptides to the target organelles. The molecular chaperones are involved in numerous diseases, including cancer, revealing changes of expression. In this review, we mainly describe the relationship of hsp expression with human cancer, and discuss what is known about their post-translational modifications according to malignancies.

The plenary session of the Proteomics Standards Initiative (PSI) of the Human Proteome Organisation at the 7(th) annual HUPO world congress updated the delegates on the current status of the ongoing work of this group. The release of the new MS interchange format, mzML, was formally announced and delegates were also updated on the advances in the area of molecular interactions, protein separations, proteomics informatics and also on PEFF, a common sequence database format currently under review in the PSI documentation process. Community input on this initiative was requested. Finally, the impact these new data standards are having on the data submission process, which increasingly is an integral part of the publication process, was reviewed and discussed.

We have developed a new algorithm to identify proteins by means of peptide mass fingerprinting. Starting from the matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) spectra and environmental data such as species, isoelectric point and molecular weight, as well as chemical modifications or number of missed cleavages of a protein, the program performs a fully automated identification of the protein. The first step is a peak detection algorithm, which allows precise and fast determination of peptide masses, even if the peaks are of low intensity or they overlap. In the second step the masses and environmental data are used by the identification algorithm to search in protein sequence databases (SWISS-PROT and/or TrEMBL) for protein entries that match the input data. Consequently, a list of candidate proteins is selected from the database, and a score calculation provides a ranking according to the quality of the match. To define the most discriminating scoring calculation we analyzed the respective role of each parameter in two directions. The first one is based on filtering and exploratory effects, while the second direction focuses on the levels where the parameters intervene in the identification process. Thus, according to our analysis, all input parameters contribute to the score, however with different weights. Since it is difficult to estimate the weights in advance, they have been computed with a generic algorithm, using a training set of 91 protein spectra with their environmental data. We tested the resulting scoring calculation on a test set of ten proteins and compared the identification results with those of other peptide mass fingerprinting programs.