Improved Cross-Linking Mass Spectrometry Algorithms for Probing Protein Structures and Interactions

Proteins are the most active molecules in living bodies. They catalyze chemical reactions, provide structural support for cells and allow organisms to move. Their function is intrinsically linked to their folded structure. Resolving the structures of proteins and protein complexes is crucial for our understanding of basic biological processes and diseases. Cross-Linking Mass Spectrometry (XL-MS) is a method to gain structural insights into protein complexes. The field of XL-MS data analysis software is not yet as established as many other methods in proteomics. XL-MS analysis software has significant room for improvement in terms of sensitivity, efficiency and standardization of file formats and workflows to facilitate interoperability and reproducibility. In this thesis we present a new XL-MS search engine, OpenPepXL. We develop an algorithm that scores all candidate cross-linked peptide pairs and is efficient enough to be used on a standard desktop PC for most applications. OpenPepXL supports the standardized XL-MS identification file format defined as a part of the MzIdentML 1.2 specifications that were developed in collaboration with the Proteomics Standards Initiative. We benchmark OpenPepXL against other state-of-the-art XL-MS identification tools on multiple datasets that allow cross-link validation through structures or other means. We show that our exhaustive approach, although not the quickest one, is superior in sensitivity to other tools. We suggest this is due to some tools improving their processing time by discarding too many candidates in early steps of the data analysis. We apply XL-MS analysis with OpenPepXL to multiple protein complexes related to meiosis and the type III secretion system. The first project involved several proteins with unknown structures, some of which are expected to be at least partially intrinsically disordered and therefore difficult to investigate using most traditional structural research methods. Unfortunately, we could not find cross-links between the interaction sites we were interested in the most, but we were able to identify many others in these complexes and gained some structural insights. In the second project we used the photo-cross-linking amino acid pBpa to test very specific hypotheses about interactions within the type III secretion system. We were not able to gain any new structural information yet. However, we could confirm that this is a viable approach. It is possible to identify cross-links between a pBpa residue incorporated into a protein sequence and a residue it cross-links to on a residue level resolution

JSBML 1.0: providing a smorgasbord of options to encode systems biology models

JSBML, the official pure Java programming library for the SBML format, has evolved with the advent of different modeling formalisms in systems biology and their ability to be exchanged and represented via extensions of SBML. JSBML has matured into a major, active open-source project with contributions from a growing, international team of developers who not only maintain compatibility with SBML, but also drive steady improvements to the Java interface and promote ease-of-use with end users

The mzIdentML Data Standard Version 1.2, Supporting Advances in Proteome Informatics

The first stable version of the Proteomics Standards Initiative mzIdentML open data standard (version 1.1) was published in 2012—capturing the outputs of peptide and protein identification software. In the intervening years, the standard has become well-supported in both commercial and open software, as well as a submission and download format for public repositories. Here we report a new release of mzIdentML (version 1.2) that is required to keep pace with emerging practice in proteome informatics. New features have been added to support: (1) scores associated with localization of modifications on peptides; (2) statistics performed at the level of peptides; (3) identification of cross-linked peptides; and (4) support for proteogenomics approaches. In addition, there is now improved support for the encoding of de novo sequencing of peptides, spectral library searches, and protein inference. As a key point, the underlying XML schema has only undergone very minor modifications to simplify as much as possible the transition from version 1.1 to version 1.2 for implementers, but there have been several notable updates to the format specification, implementation guidelines, controlled vocabularies and validation software. mzIdentML 1.2 can be described as backwards compatible, in that reading software designed for mzIdentML 1.1 should function in most cases without adaptation. We anticipate that these developments will provide a continued stable base for software teams working to implement the standard.ISSN:1535-9476ISSN:1535-948

JSBML

JSBML is a community-driven project to create a free, open-source, pure Java™ library for reading, writing, and manipulating SBML files (the Systems Biology Markup Language) and data streams. It is an alternative to the mixed Java/native code-based interface provided in libSBML.Related Publication:</p> JSBML 1.0: providing a smorgasbord of options to encode systems biology models</p> Nicolas Rodriguez Babraham Institute, Babraham Research Campus, Cambridge, UK</p> Alex Thomas University of California, San Diego, La Jolla, CA, USA</p> Leandro Watanabe The University of Utah, Salt Lake City, UT, USA</p> Ibrahim Y. Vazirabad Marquette University, Milwaukee, WI, USA</p> Victor Kofia Princess Margaret Cancer Centre</p> Harold Gómez Boston University, Boston, MA, USA</p> Florian Mittag Center for Bioinformatics Tübingen</p> Jakob Matthes Center for Bioinformatics Tübingen</p> Jan Rudolph Center for Bioinformatics Tübingen</p> Finja Wrzodek Center for Bioinformatics Tübingen</p> Eugen Netz Center for Bioinformatics Tübingen</p> Alexander Diamantikos Center for Bioinformatics Tübingen</p> Johannes Eichner Center for Bioinformatics Tübingen</p> Roland Keller Center for Bioinformatics Tübingen</p> Clemens Wrzodek Center for Bioinformatics Tübingen</p> Sebastian Fröhlich Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany</p> Nathan E. Lewis University of California, San Diego, La Jolla, CA, USA</p> Chris J. Myers The University of Utah, Salt Lake City, UT, USA</p> Nicolas Le Novère Babraham Institute, Babraham Research Campus, Cambridge, UK</p> Bernhard Ø. Pallson University of California, San Diego, La Jolla, CA, USA</p> Michael Hucka Caltech</p> Andreas Dräger Center for Bioinformatics Tübingen</p> Bioinformatics</p> 2015-10-15</p> https://doi.org/10.1093/bioinformatics/btv341</p>en