Xwalk: computing and visualizing distances in cross-linking experiments

Motivation: Chemical cross-linking of proteins or protein complexes and the mass spectrometry-based localization of the cross-linked amino acids in peptide sequences is a powerful method for generating distance restraints on the substrate's topology. Results: Here, we introduce the algorithm Xwalk for predicting and validating these cross-links on existing protein structures. Xwalk calculates and displays non-linear distances between chemically cross-linked amino acids on protein surfaces, while mimicking the flexibility and non-linearity of cross-linker molecules. It returns a ‘solvent accessible surface distance', which corresponds to the length of the shortest path between two amino acids, where the path leads through solvent occupied space without penetrating the protein surface. Availability: Xwalk is freely available as a web server or stand-alone JAVA application at http://www.xwalk.org. Contact: [email protected]; [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

2DDB – a bioinformatics solution for analysis of quantitative proteomics data

BACKGROUND: We present 2DDB, a bioinformatics solution for storage, integration and analysis of quantitative proteomics data. As the data complexity and the rate with which it is produced increases in the proteomics field, the need for flexible analysis software increases. RESULTS: 2DDB is based on a core data model describing fundamentals such as experiment description and identified proteins. The extended data models are built on top of the core data model to capture more specific aspects of the data. A number of public databases and bioinformatical tools have been integrated giving the user access to large amounts of relevant data. A statistical and graphical package, R, is used for statistical and graphical analysis. The current implementation handles quantitative data from 2D gel electrophoresis and multidimensional liquid chromatography/mass spectrometry experiments. CONCLUSION: The software has successfully been employed in a number of projects ranging from quantitative liquid-chromatography-mass spectrometry based analysis of transforming growth factor-beta stimulated fi-broblasts to 2D gel electrophoresis/mass spectrometry analysis of biopsies from human cervix. The software is available for download at SourceForge

Greedy de novo motif discovery to construct motif repositories for bacterial proteomes

BACKGROUND Bacterial surfaces are complex systems, constructed from membranes, peptidoglycan and, importantly, proteins. The proteins play crucial roles as critical regulators of how the bacterium interacts with and survive in its environment. A full catalog of the motifs in protein families and their relative conservation grade is a prerequisite to target the protein-protein interaction that bacterial surface protein makes to host proteins. RESULTS In this paper, we propose a greedy approach to identify conserved motifs in large sequence families iteratively. Each iteration discovers a motif de novo and masks all occurrences of that motif. Remaining unmasked sequences are subjected to the next round of motif detection until no more significant motifs can be found. We demonstrate the utility of the method through the construction of a proteome-wide motif repository for Group A Streptococcus (GAS), a significant human pathogen. GAS produce numerous surface proteins that interact with over 100 human plasma proteins, helping the bacteria to evade the host immune response. We used the repository to find that proteins part of the bacterial surface has motif architectures that differ from intracellular proteins. CONCLUSIONS We elucidate that the M protein, a coiled-coil homodimer that extends over 500 A from the cell wall, has a motif architecture that differs between various GAS strains. As the M protein is known to bind a variety of different plasma proteins, the results indicate that the different motif architectures are responsible for the quantitative differences of plasma proteins that various strains bind. The speed and applicability of the method enable its application to all major human pathogens

The Yeast Resource Center Public Data Repository

The Yeast Resource Center Public Data Repository (YRC PDR) serves as a single point of access for the experimental data produced from many collaborations typically studying Saccharomyces cerevisiae (baker's yeast). The experimental data include large amounts of mass spectrometry results from protein co-purification experiments, yeast two-hybrid interaction experiments, fluorescence microscopy images and protein structure predictions. All of the data are accessible via searching by gene or protein name, and are available on the Web at http://www.yeastrc.org/pdr/

DIANA—algorithmic improvements for analysis of data-independent acquisition MS data

Motivation: Data independent acquisition mass spectrometry has emerged as a reproducible and sensitive alternative in quantitative proteomics, where parsing the highly complex tandem mass spectra requires dedicated algorithms. Recently, targeted data extraction was proposed as a novel analysis strategy for this type of data, but it is important to further develop these concepts to provide quality-controlled, interference-adjusted and sensitive peptide quantification. Results: We here present the algorithm DIANA and the classifier PyProphet, which are based on new probabilistic sub-scores to classify the chromatographic peaks in targeted data-independent acquisition data analysis. The algorithm is capable of providing accurate quantitative values and increased recall at a controlled false discovery rate, in a complex gold standard dataset. Importantly, we further demonstrate increased confidence gained by the use of two complementary data-independent acquisition targeted analysis algorithms, as well as increased numbers of quantified peptide precursors in complex biological samples. Availability and implementation: DIANA is implemented in scala and python and available as open source (Apache 2.0 license) or pre-compiled binaries from http://quantitativeproteomics.org/diana. PyProphet can be installed from PyPi (https://pypi.python.org/pypi/pyprophet). Supplementary information: Supplementary data are available at Bioinformatics onlin

Efficient visualization of high-throughput targeted proteomics experiments: TAPIR

Motivation: Targeted mass spectrometry comprises a set of powerful methods to obtain accurate and consistent protein quantification in complex samples. To fully exploit these techniques, a cross-platform and open-source software stack based on standardized data exchange formats is required. Results: We present TAPIR, a fast and efficient Python visualization software for chromatograms and peaks identified in targeted proteomics experiments. The input formats are open, community-driven standardized data formats (mzML for raw data storage and TraML encoding the hierarchical relationships between transitions, peptides and proteins). TAPIR is scalable to proteome-wide targeted proteomics studies (as enabled by SWATH-MS), allowing researchers to visualize high-throughput datasets. The framework integrates well with existing automated analysis pipelines and can be extended beyond targeted proteomics to other types of analyses. Availability and implementation: TAPIR is available for all computing platforms under the 3-clause BSD license at https://github.com/msproteomicstools/msproteomicstools. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

aLFQ: an R-package for estimating absolute protein quantities from label-free LC-MS/MS proteomics data

Motivation: The determination of absolute quantities of proteins in biological samples is necessary for multiple types of scientific inquiry. While relative quantification has been commonly used in proteomics, few proteomic datasets measuring absolute protein quantities have been reported to date. Various technologies have been applied using different types of input data, e.g. ion intensities or spectral counts, as well as different absolute normalization strategies. To date, a user-friendly and transparent software supporting large-scale absolute protein quantification has been lacking. Results: We present a bioinformatics tool, termed aLFQ, which supports the commonly used absolute label-free protein abundance estimation methods (TopN, iBAQ, APEX, NSAF and SCAMPI) for LC-MS/MS proteomics data, together with validation algorithms enabling automated data analysis and error estimation. Availability and implementation: aLFQ is written in R and freely available under the GPLv3 from CRAN (http://www.cran.r-project.org). Instructions and example data are provided in the R-package. The raw data can be obtained from the PeptideAtlas raw data repository (PASS00321). Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

CD25(bright)CD4(+ )regulatory T cells are enriched in inflamed joints of patients with chronic rheumatic disease

CD25(+)CD4(+ )regulatory T cells participate in the regulation of immune responses. We recently demonstrated the presence of CD25(bright)CD4(+ )regulatory T cells with a capacity to control T cell proliferation in the joints of patients with rheumatoid arthritis. Here, we investigate a possible accumulation of these regulatory T cells in the inflamed joint of different rheumatic diseases including rheumatoid arthritis. The studies are also extended to analyze whether cytokine production can be suppressed by the regulatory T cells. Synovial fluid and peripheral blood samples were obtained during relapse from 36 patients with spondyloarthropathies, 21 adults with juvenile idiopathic arthritis and 135 patients with rheumatoid arthritis, and the frequency of CD25(bright)CD4(+ )T cells was determined. Of 192 patients, 182 demonstrated a higher frequency of CD25(bright)CD4(+ )T cells in synovial fluid than in peripheral blood. In comparison with healthy subjects, the patients had significantly fewer CD25(bright)CD4(+ )T cells in peripheral blood. For functional studies, synovial fluid cells from eight patients were sorted by flow cytometry, and the suppressive capacity of the CD25(bright)CD4(+ )T cells was determined in in vitro cocultures. The CD25(bright)CD4(+ )T cells suppressed the production of both type 1 and 2 cytokines including interleukin-17, as well as proliferation, independently of diagnosis. Thus, irrespective of the inflammatory joint disease investigated, CD25(bright)CD4(+ )T cells were reduced in peripheral blood and enriched in the joint, suggesting an active recruitment of regulatory T cells to the affected joint. Their capacity to suppress both proliferation and cytokine secretion might contribute to a dampening of local inflammatory processes

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