Fifteen years SIB Swiss Institute of Bioinformatics: life science databases, tools and support.

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) was created in 1998 as an institution to foster excellence in bioinformatics. It is renowned worldwide for its databases and software tools, such as UniProtKB/Swiss-Prot, PROSITE, SWISS-MODEL, STRING, etc, that are all accessible on ExPASy.org, SIB's Bioinformatics Resource Portal. This article provides an overview of the scientific and training resources SIB has consistently been offering to the life science community for more than 15 years.

SwissPIT: An workflow-based platform for analyzing tandem-MS spectra using the Grid.

The identification and characterization of peptides from MS/MS data represents a critical aspect of proteomics. It has been the subject of extensive research in bioinformatics resulting in the generation of a fair number of identification software tools. Most often, only one program with a specific and unvarying set of parameters is selected for identifying proteins. Hence, a significant proportion of the experimental spectra do not match the peptide sequences in the screened database due to inappropriate parameters or scoring schemes. The Swiss protein identification toolbox (swissPIT) project provides the scientific community with an expandable multitool platform for automated in-depth analysis of MS data also able to handle data from high-throughput experiments. With swissPIT many problems have been solved: The missing standards for input and output formats (A), creation of analysis workflows (B), unified result visualization (C), and simplicity of the user interface (D). Currently, swissPIT supports four different programs implementing two different search strategies to identify MS/MS spectra. Conceived to handle the calculation-intensive needs of each of the programs, swissPIT uses the distributed resources of a Swiss-wide computer Grid (http://www.swing-grid.ch).

swissPIT: a novel approach for pipelined analysis of mass spectrometry data.

The identification and characterization of peptides from tandem mass spectrometry (MS/MS) data represents a critical aspect of proteomics. Today, tandem MS analysis is often performed by only using a single identification program achieving identification rates between 10-50% (Elias and Gygi, 2007). Beside the development of new analysis tools, recent publications describe also the pipelining of different search programs to increase the identification rate (Hartler et al., 2007; Keller et al., 2005). The Swiss Protein Identification Toolbox (swissPIT) follows this approach, but goes a step further by providing the user an expandable multi-tool platform capable of executing workflows to analyze tandem MS-based data. One of the major problems in proteomics is the absent of standardized workflows to analyze the produced data. This includes the pre-processing part as well as the final identification of peptides and proteins. The main idea of swissPIT is not only the usage of different identification tool in parallel, but also the meaningful concatenation of different identification strategies at the same time. The swissPIT is open source software but we also provide a user-friendly web platform, which demonstrates the capabilities of our software and which is available at http://swisspit.cscs.ch upon request for account.

Creating 2DE databases for the World Wide Web.

With the development of the Internet, a growing number of two-dimensional electrophoresis (2DE) databases have become available (60 in 2009, for a total of 425 image maps). By linking the two components constituting 2DE databases, gel images and protein information, the active hypertext links provide a powerful tool for data integration, in addition to navigation from one database to another.This chapter shows how to prepare the necessary files to build a federated 2DE database in order to make it available over the Internet and how to further update it.

Database interrogation algorithms for identification of proteins in proteomic separations.

Protein identification is a key aspect in the investigation of proteomes. Typically, in a 2-DE gel-based proteomics analysis, the spots are enzymatically digested and the resulting peptide masses are measured, producing mass spectra. Peptides can also be isolated and fragmented within the mass spectrometer, leading to tandem mass spectra. For protein and peptide identification, an algorithm matches the mass spectra and other empirical information against a protein database to define if a protein is already known or novel. A variety of different programs for protein identification with database interrogation has been developed. This chapter focuses on the use of the software Aldente and Phenyx, for MS and tandem MS identification, respectively.

A suite of tools to analyse and publish 2-DE data.

Bioinformatics tools may assist scientists in all steps of a typical 2-DE gel analysis workflow, that is, from the description of the sample preparation protocols, going through the gel image analysis and protein identification, to the publication of Internet-ready 2-DE gel databases. This short communication highlights in a single and summarised view, this workflow and the current bioinformatics solutions developed by the Proteome Informatics Group at the Swiss Institute of Bioinformatics.

Characterization of protein cross-links via mass spectrometry and an open-modification search strategy.

Protein-protein interactions are key to function and regulation of many biological pathways. To facilitate characterization of protein-protein interactions using mass spectrometry, a new data acquisition/analysis pipeline was designed. The goal for this pipeline was to provide a generic strategy for identifying cross-linked peptides from single LC/MS/MS data sets, without using specialized cross-linkers or custom-written software. To achieve this, each peptide in the pair of cross-linked peptides was considered to be "post-translationally" modified with an unknown mass at an unknown amino acid. This allowed use of an open-modification search engine, Popitam, to interpret the tandem mass spectra of cross-linked peptides. False positives were reduced and database selectivity increased by acquiring precursors and fragments at high mass accuracy. Additionally, a high-charge-state-driven data acquisition scheme was utilized to enrich data sets for cross-linked peptides. This open-modification search based pipeline was shown to be useful for characterizing both chemical as well as native cross-links in proteins. The pipeline was validated by characterizing the known interactions in the chemically cross-linked CYP2E1-b5 complex. Utility of this method in identifying native cross-links was demonstrated by mapping disulfide bridges in RcsF, an outer membrane lipoprotein involved in Rcs phosphorelay.

On the benefits of acquiring peptide fragment ions at high measured mass accuracy.

The advantages and disadvantages of acquiring tandem mass spectra by collision-induced dissociation (CID) of peptides in linear ion trap Fourier-transform hybrid instruments are described. These instruments offer the possibility to transfer fragment ions from the linear ion trap to the FT-based analyzer for analysis with both high resolution and high mass accuracy. In addition, performing CID during the transfer of ions from the linear ion trap (LTQ) to the FT analyzer is also possible in instruments containing an additional collision cell (i.e., the "C-trap" in the LTQ-Orbitrap), resulting in tandem mass spectra over the full m/z range and not limited by the ejection q value of the LTQ. Our results show that these scan modes have lower duty cycles than tandem mass spectra acquired in the LTQ with nominal mass resolution, and typically result in fewer peptide identifications during data-dependent analysis of complex samples. However, the higher measured mass accuracy and resolution provides more specificity and hence provides a lower false positive ratio for the same number of true positives during database search of peptide tandem mass spectra. In addition, the search for modified and unexpected peptides is greatly facilitated with this data acquisition mode. It is therefore concluded that acquisition of tandem mass spectral data with high measured mass accuracy and resolution is a competitive alternative to "classical" data acquisition strategies, especially in situations of complex searches from large databases, searches for modified peptides, or for peptides resulting from unspecific cleavages.

Grid-based analysis of tandem mass spectrometry data in clinical proteomics.

Biomarker detection is one of the greatest challenges in Clinical Proteomics. Today, great hopes are placed into tandem mass spectrometry (MS/MS) to discover potential biomarkers. MS/MS is a technique that allows large scale data analysis, including the identification, characterization, and quantification of molecules. Especially the identification process, that implies to compare experimental spectra with theoretical amino acid sequences stored in specialized databases, has been subject for extensive research in bioinformatics since many years. Dozens of identification programs have been developed addressing different aspects of the identification process but in general, clinicians are only using a single tools for their data analysis along with a single set of specific parameters. Hence, a significant proportion of the experimental spectra do not lead to a confident identification score due to inappropriate parameters or scoring schemes of the applied analysis software. The swissPIT (Swiss Protein Identification Toolbox) project was initiated to provide the scientific community with an expandable multi-tool platform for automated and in-depth analysis of mass spectrometry data. The swissPIT uses multiple identification tools to automatic analyze mass spectra. The tools are concatenated as analysis workflows. In order to realize these calculation-intensive workflows we are using the Swiss Bio Grid infrastructure. A first version of the web-based front-end is available (http://www.swisspit.cscs.ch) and can be freely accessed after requesting an account. The source code of the project will be also made available in near future.

Accessing Reliable Health Information on the Web: A Review of the HON Approach.

Accessing online health content of high quality and reliability presents challenges. Laypersons cannot easily differentiate trustworthy content from misinformed or manipulated content. This article describes complementary approaches for members of the general public and health professionals to find trustworthy content with as little bias as possible. These include the Khresmoi health search engine (K4E), the Health On the Net Code of Conduct (HONcode) and health trust indicator Web browser extensions.

ExPASy: The proteomics server for in-depth protein knowledge and analysis.

The ExPASy (the Expert Protein Analysis System) World Wide Web server (http://www.expasy.org), is provided as a service to the life science community by a multidisciplinary team at the Swiss Institute of Bioinformatics (SIB). It provides access to a variety of databases and analytical tools dedicated to proteins and proteomics. ExPASy databases include SWISS-PROT and TrEMBL, SWISS-2DPAGE, PROSITE, ENZYME and the SWISS-MODEL repository. Analysis tools are available for specific tasks relevant to proteomics, similarity searches, pattern and profile searches, post-translational modification prediction, topology prediction, primary, secondary and tertiary structure analysis and sequence alignment. These databases and tools are tightly interlinked: a special emphasis is placed on integration of database entries with related resources developed at the SIB and elsewhere, and the proteomics tools have been designed to read the annotations in SWISS-PROT in order to enhance their predictions. ExPASy started to operate in 1993, as the first WWW server in the field of life sciences. In addition to the main site in Switzerland, seven mirror sites in different continents currently serve the user community.

Health On the Net's 20 Years of Transparent and Reliable Health Information.

The Health On the Net Foundation (HON) was born in 1996, during the beginning of the World Wide Web, from a collective decision by health specialists, led by the late Jean-Raoul Scherrer, who anticipated the need for online trustworthy health information. Because the Internet is a free space that everyone shares, a search for quality information is like a shot in the dark: neither will reliably hit their target. Thus, HON was created to promote deployment of useful and reliable online health information, and to enable its appropriate and efficient use. Two decades on, HON is the oldest and most valued quality marker for online health information. The organization has maintained its reputation through dynamic measures, innovative endeavors and dedication to upholding key values and goals. This paper provides an overview of the HON Foundation, and its activities, challenges, and achievements over the years.

The molecular scanner: concept and developments.

Approaches aimed at deciphering the proteome have illustrated the need for relatively complex and highly sensitive methodologies. The major elements of proteome analysis, such as powerful protein separation and enzymatic processing, mass spectrometry and dedicated bioinformatics have been assembled in the development of the molecular scanner. This highly flexible and data-rich approach has combined the power of electrophoretic protein separation, the simultaneous digestion and transfer of proteins through an enzymatic membrane, the immediate use of the MALDI mass spectrometer to scan a collecting membrane, and the development of dedicated bioinformatics tools to perform protein identification and molecular imaging of the proteome. Clinical applications of the molecular scanner have also started to be developed for disease diagnosis in biological material.

Correlation of proteomic and transcriptomic profiles of Staphylococcus aureus during the post-exponential phase of growth.

A combined proteomic and transcriptomic analysis of Staphylococcus aureus strain N315 was performed to study a sequenced strain at the system level. Total protein and membrane protein extracts were prepared and analyzed using various proteomic workflows including: 2-DE, SDS-PAGE combined with microcapillary LC-MALDI-MS/MS, and multidimensional liquid chromatography. The presence of a protein was then correlated with its respective transcript level from S. aureus cells grown under the same conditions. Gene-expression data revealed that 97% of the 2'596 ORFs were detected during the post-exponential phase. At the protein level, 23% of these ORFs (591 proteins) were identified. Correlation of the two datasets revealed that 42% of the identified proteins (248 proteins) were amongst the top 25% of genes with highest mRNA signal intensities, and 69% of the identified proteins (406 proteins) were amongst the top 50% with the highest mRNA signal intensities. The fact that the remaining 31% of proteins were not strongly expressed at the RNA level indicates either that some low-abundance proteins were identified or that some transcripts or proteins showed extended half-lives. The most abundant classes identified with the combined proteomic and transcriptomic approach involved energy production, translational activities and nucleotide transport, reflecting an active metabolism. The simultaneous large-scale analysis of transcriptomes and proteomes enables a global and holistic view of the S. aureus biology, allowing the parallel study of multiple active events in an organism.

Visualization and analysis of molecular scanner peptide mass spectra.

The molecular scanner combines protein separation using gel electrophoresis with peptide mass fingerprinting (PMF) techniques to identify proteins in a highly automated manner. Proteins separated in a 2-dimensional polyacrylamide gel (2-D PAGE) are digested in parallel and transferred onto a membrane keeping their relative positions. The membrane is then sprayed with a matrix and inserted into a matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometer, which measures a peptide mass fingerprint at each site on the scanned grid. First, visualization of PMF data allows surveying all fingerprints at once and provides very useful information on the presence of chemical noise. Chemical noise is shown to be a potential source for erroneous identifications and is therefore purged from the mass fingerprints. Then, the correlation between neighboring spectra is used to recalibrate the peptide masses. Finally, a method that clusters peptide masses according to the similarity of the spatial distributions of their signal intensities is presented. This method allows discarding many of the false positives that usually go along with PMF identifications and allows identifying many weakly expressed proteins present in the gel.

MIAPEGelDB, a web-based submission tool and public repository for MIAPE gel electrophoresis documents.

The HUPO Proteomics Standards Initiative (PSI) defines standards for data representation in proteomics to facilitate data exchange and comparison, and quality assessment. A set of minimum reporting requirements, called MIAPE (for Minimum Information About a Proteomics Experiment) is provided to ensure consistency of data set annotation. Like the MIAME reporting requirements for transcriptomics, it is anticipated that journal editors will soon require such annotation for published data sets, simplifying further mining of data. Therefore, tools for data entry and public repositories for long-term storage will be needed. MIAPEGelDB is a public repository and a web-based data entry tool for documents conforming to the MIAPE gel electrophoresis guidelines. It aims to guide authors through the publication of the minimal set of information for their proteomics experiments using a clear, sequential interface. After publication by their author, documents in MIAPEGelDB can be viewed in HTML or plain text formats, and further used through stable URL links from remote resources. MIAPEGelDB is accessible at: http://miapegeldb.expasy.org/.

The World-2DPAGE Constellation to promote and publish gel-based proteomics data through the ExPASy server.

Since it was launched in 1993, the ExPASy server has been and is still a reference in the proteomics world. ExPASy users access various databases, many dedicated tools, and lists of resources, among other services. A significant part of resources available is devoted to two-dimensional electrophoresis data. Our latest contribution to the expansion of the pool of on-line proteomics data is the World-2DPAGE Constellation, accessible at http://world-2dpage.expasy.org/. It is composed of the established WORLD-2DPAGE List of 2-D PAGE database servers, the World-2DPAGE Portal that queries simultaneously world-wide proteomics databases, and the recently created World-2DPAGE Repository. The latter component is a public standards-compliant repository for gel-based proteomics data linked to protein identifications published in the literature. It has been set up using the Make2D-DB package, a software tool that helps building SWISS-2DPAGE-like databases on one's own Web site. The lack of necessary informatics infrastructure to build and run a dedicated website is no longer an obstacle to make proteomics data publicly accessible on the Internet.

Labeling of Bifidobacterium longum cells with 13C-substituted leucine for quantitative proteomic analyses.

Stable isotope labeling of amino acids in cell culture was used for Bifidobacterium longum. A comprehensive proteomic strategy was developed and validated by designing an appropriate semidefined medium that allows stable replacement of natural leucine by [(13)C6]leucine. Using this strategy, proteins having variations of at least 50% in their expression rates can be quantified with great confidence.

Using bioinformatic resources in the proteomic analysis of biological fluids.

On-line databases targeted towards protein contents in biological fluids are scarce. Consequently, the investigation of proteins identified in a biological fluid most importantly depends on crosschecking information gathered from less specific resources. This review summarises the key databases and tools for collecting information on tissue specificity or expression profiles. It also emphasises the high connectivity between databases fruitfully used to corroborate and piece information together. Finally, selected issues related to appropriate bioinformatics tools in the context of clinical applications are succinctly discussed.

Analysis of proteomes using the molecular scanner.

INTRODUCTIONThe molecular scanner offers a flexible and powerful visualization tool that can create a fully annotated 2D gel electrophoresis map. Proteins separated by 2D gel electrophoresis are simultaneously digested while undergoing electrotransfer from the gel to a membrane. The peptides are subjected to peptide mass fingerprint (PMF) analysis to identify proteins directly from the PVDF membranes by MALDI-TOF-MS scanning. An ensemble of dedicated tools is then used to create, analyze, and visualize a proteome as a multidimensional image. The molecular scanner method reduces to a minimum the sample handling prior to mass analysis and decreases the sample size to a few tens of micrometers, that is, the size of the MALDI-TOF-MS laser beam impact. The process can be divided into four parts: separation and digestion of proteins, acquisition of PMF data, processing of the MS data and protein identification, and creation of multidimensional proteome maps.