Fredrik Levander

mzML—a Community Standard for Mass Spectrometry Data

Mass spectrometry is a fundamental tool for discovery and analysis in the life sciences. With the rapid advances in mass spectrometry technology and methods, it has become imperative to provide a standard output format for mass spectrometry data that will facilitate data sharing and analysis. Initially, the efforts to develop a standard format for mass spectrometry data resulted in multiple formats, each designed with a different underlying philosophy. To resolve the issues associated with having multiple formats, vendors, researchers, and software developers convened under the banner of the HUPO PSI to develop a single standard. The new data format incorporated many of the desirable technical attributes from the previous data formats, while adding a number of improvements, including features such as a controlled vocabulary with validation tools to ensure consistent usage of the format, improved support for selected reaction monitoring data, and immediately available implementations to facilitate rapid adoption by the community. The resulting standard data format, mzML, is a well tested open-source format for mass spectrometer output files that can be readily utilized by the community and easily adapted for incremental advances in mass spectrometry technology.

Enhanced Exopolysaccharide Production by Metabolic Engineering of Streptococcus thermophilus

ABSTRACT It is possible that the low levels of production of exopolysaccharides (EPSs) by lactic acid bacteria could be improved by altering the levels of enzymes in the central metabolism that influence the production of precursor nucleotide sugars. To test this hypothesis, we identified and cloned the galU gene, which codes for UDP glucose pyrophosphorylase (GalU) in Streptococcus thermophilus LY03. Homologous overexpression of the gene led to a 10-fold increase in GalU activity but did not have any effect on the EPS yield when lactose was the carbon source. However, when galU was overexpressed in combination with pgmA, which encodes phosphoglucomutase (PGM), the EPS yield increased from 0.17 to 0.31 g/mol of carbon from lactose. A galactose-fermenting LY03 mutant (Gal+) with increased activities of the Leloir enzymes was also found to have a higher EPS yield (0.24 g/mol of carbon) than the parent strain. The EPS yield was further improved to 0.27 g/mol of carbon by overexpressing galU in this strain. However, the highest EPS yield, 0.36 g/mol of carbon, was obtained when pgmA was knocked out in the Gal+ strain. Measurements of the levels of intracellular metabolites in the cultures revealed that the Gal+ strains had considerably higher glucose 1-phosphate levels than the other strains, and the strain lacking PGM activity had threefold-higher levels of glucose 1-phosphate than the other Gal+ strains. These results show that it is possible to increase EPS production by altering the levels of enzymes in the central carbohydrate metabolism.

TraML—A Standard Format for Exchange of Selected Reaction Monitoring Transition Lists

Targeted proteomics via selected reaction monitoring is a powerful mass spectrometric technique affording higher dynamic range, increased specificity and lower limits of detection than other shotgun mass spectrometry methods when applied to proteome analyses. However, it involves selective measurement of predetermined analytes, which requires more preparation in the form of selecting appropriate signatures for the proteins and peptides that are to be targeted. There is a growing number of software programs and resources for selecting optimal transitions and the instrument settings used for the detection and quantification of the targeted peptides, but the exchange of this information is hindered by a lack of a standard format. We have developed a new standardized format, called TraML, for encoding transition lists and associated metadata. In addition to introducing the TraML format, we demonstrate several implementations across the community, and provide semantic validators, extensive documentation, and multiple example instances to demonstrate correctly written documents. Widespread use of TraML will facilitate the exchange of transitions, reduce time spent handling incompatible list formats, increase the reusability of previously optimized transitions, and thus accelerate the widespread adoption of targeted proteomics via selected reaction monitoring.

Requirement for Phosphoglucomutase in Exopolysaccharide Biosynthesis in Glucose- and Lactose-Utilizing Streptococcus thermophilus

ABSTRACT To study the influence of phosphoglucomutase (PGM) activity on exopolysaccharide (EPS) synthesis in glucose- and lactose-growingStreptococcus thermophilus, a knockout PGM mutant and a strain with elevated PGM activity were constructed. ThepgmA gene, encoding PGM in S. thermophilusLY03, was identified and cloned. The gene was functional inEscherichia coli and was shown to be expressed from its own promoter. The pgmA-deficient mutant was unable to grow on glucose, while the mutation did not affect growth on lactose. Overexpression of pgmA had no significant effect on EPS production in glucose-growing cells. Neither deletion nor overexpression of pgmA changed the growth or EPS production on lactose. Thus, the EPS precursors in lactose-utilizing S. thermophilus are most probably formed from the galactose moiety of lactose via the Leloir pathway, which circumvents the need for a functional PGM.

The Proteios Software Environment: an extensible multiuser platform for management and analysis of proteomics data

Proteome analysis involves many steps that generate large quantities of data in different formats. This creates a need for automatic data merging and extraction of important features from data. Furthermore, metadata need to be collected and reported to enable critical evaluation of results. Many data analysis tools are developed locally in research laboratories and are nontrivial to adapt for other laboratories, preventing optimal exploitation of generated data. The proteomics field would benefit from user-friendly analysis and data management platforms in which method developers can make their analysis tools available for the community. Here, we describe the Proteios Software Environment (ProSE) that is built around a Web-based local data repository for proteomics experiments. The application features sample tracking, project sharing between multiple users, and automated data merging and analysis. ProSE has built-in support for several quantitative proteomics workflows, and integrates searching in several search engines, automated combination of the search results with predetermined false discovery rates, annotation of proteins and submission of results to public repositories. ProSE also provides a programming interface to enable local extensions, as well as database access using Web services. ProSE provides an analysis platform for proteomics research and is targeted for multiuser projects with needs to share data, sample tracking, and analysis result. ProSE is open source software available at http://www.proteios.org .

Starch-hydrolyzing bacteria from Ethiopian soda lakes

Abstract. Alkaliphilic bacteria were isolated from soil and water samples obtained from Ethiopian soda lakes in the Rift Valley area – Lake Shala, Lake Abijata, and Lake Arenguadi. Starch-hydrolyzing isolates were selected on the basis of their activity on starch agar plate assay. Sixteen isolates were chosen, characterized, and subjected to 16S rRNA gene sequence analysis. All the isolates were gram positive and catalase- and β-galactosidase positive. All isolates except one were motile endospore-forming rods and were found to be closely related to the Bacillus cluster, being grouped with Bacillus pseudofirmus, Bacillus cohnii, Bacillus vedderi, and Bacillus agaradhaerens. The one exception had nonmotile coccoid cells and was closely related to Nesterenkonia halobia. The majority of the isolates showed optimal growth at 37°C and tolerated salinity up to 10% (w/v) NaCl. Both extracellular and cell-bound amylase activity was detected among the isolates. The amylase activity of two isolates, related to B. vedderi and B. cohnii, was stimulated by ethylenediaminetetraacetic acid (EDTA) and inhibited in the presence of calcium ions. Pullulanase activity was expressed by isolates grouped with B. vedderi and also most of the isolates clustered with B. cohnii; cyclodextrin glycosyltransferase was expressed by most of the B. agaradhaerens-related strains. Minor levels of α-glucosidase activity were detected in all the strains.

Modular, scriptable and automated analysis tools for high-throughput peptide mass fingerprinting

UNLABELLED A set of new algorithms and software tools for automatic protein identification using peptide mass fingerprinting is presented. The software is automatic, fast and modular to suit different laboratory needs, and it can be operated either via a Java user interface or called from within scripts. The software modules do peak extraction, peak filtering and protein database matching, and communicate via XML. Individual modules can therefore easily be replaced with other software if desired, and all intermediate results are available to the user. The algorithms are designed to operate without human intervention and contain several novel approaches. The performance and capabilities of the software is illustrated on spectra from different mass spectrometer manufacturers, and the factors influencing successful identification are discussed and quantified. MOTIVATION Protein identification with mass spectrometric methods is a key step in modern proteomics studies. Some tools are available today for doing different steps in the analysis. Only a few commercial systems integrate all the steps in the analysis, often for only one vendors hardware, and the details of these systems are not public. RESULTS A complete system for doing protein identification with peptide mass fingerprints is presented, including everything from peak picking to matching the database protein. The details of the different algorithms are disclosed so that academic researchers can have full control of their tools. AVAILABILITY The described software tools are available from the Halmstad University website www.hh.se/staff/bioinf/ SUPPLEMENTARY INFORMATION Details of the algorithms are described in supporting information available from the Halmstad University website www.hh.se/staff/bioinf/

Trehalose-6-phosphate phosphorylase is part of a novel metabolic pathway for trehalose utilization in Lactococcus lactis.

Lactococcus lactis splits phosphorylated trehalose by the action of inorganic phosphate-dependent trehalose-6-phosphate phosphorylase (TrePP) in a novel catabolic pathway. TrePP was found to catalyze the reversible conversion of trehalose 6-phosphate into β-glucose 1-phosphate and glucose 6-phosphate by measuring intermediate sugar phosphates in cell extracts from trehalose-cultivated lactococci. According to native PAGE and SDS-PAGE, TrePP was shown to be a monomeric enzyme with a molecular mass of 94 kDa. Reaction kinetics suggested that the enzyme follows a ternary complex mechanism with optimal phosphorolysis at 35 °C and pH 6.3. The equilibrium constants were found to be 0.026 and 0.032 at pH 6.3 and 7.0, respectively, favoring the formation of trehalose 6-phosphate. The Michaelis-Menten constants of TrePP for trehalose 6-phosphate, inorganic phosphate, β-glucose 1-phosphate, and glucose 6-phosphate were determined to be 6, 32, 0.9, and 4 mm, respectively. The TrePP-encoding gene, designated trePP, was localized in a putative trehalose operon of L. lactis. This operon includes the gene encoding β-phosphoglucomutase in addition to three open reading frames believed to encode a transcriptional regulator and two trehalose-specific phosphotransferase system components. The identity of trePP was confirmed by determining the N-terminal amino acid sequence of TrePP and by its overexpression inEscherichia coli and L. lactis, as well as the construction of a lactococcal trePP knockout mutant. Furthermore, both TrePP and β-phosphoglucomutase activity were detected in Enterococcus faecalis cell extract, indicating that this bacterium exhibits the same trehalose assimilation route asL. lactis.

Data processing methods and quality control strategies for label-free LC-MS protein quantification.

Protein quantification using different LC-MS techniques is becoming a standard practice. However, with a multitude of experimental setups to choose from, as well as a wide array of software solutions for subsequent data processing, it is non-trivial to select the most appropriate workflow for a given biological question. In this review, we highlight different issues that need to be addressed by software for quantitative LC-MS experiments and describe different approaches that are available. With focus on label-free quantification, examples are discussed both for LC-MS/MS and LC-SRM data processing. We further elaborate on current quality control methodology for performing accurate protein quantification experiments. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.

The HUPO proteomics standards initiative-mass spectrometry controlled vocabulary

Controlled vocabularies (CVs), i.e. a collection of predefined terms describing a modeling domain, used for the semantic annotation of data, and ontologies are used in structured data formats and databases to avoid inconsistencies in annotation, to have a unique (and preferably short) accession number and to give researchers and computer algorithms the possibility for more expressive semantic annotation of data. The Human Proteome Organization (HUPO)–Proteomics Standards Initiative (PSI) makes extensive use of ontologies/CVs in their data formats. The PSI-Mass Spectrometry (MS) CV contains all the terms used in the PSI MS–related data standards. The CV contains a logical hierarchical structure to ensure ease of maintenance and the development of software that makes use of complex semantics. The CV contains terms required for a complete description of an MS analysis pipeline used in proteomics, including sample labeling, digestion enzymes, instrumentation parts and parameters, software used for identification and quantification of peptides/proteins and the parameters and scores used to determine their significance. Owing to the range of topics covered by the CV, collaborative development across several PSI working groups, including proteomics research groups, instrument manufacturers and software vendors, was necessary. In this article, we describe the overall structure of the CV, the process by which it has been developed and is maintained and the dependencies on other ontologies. Database URL: http://psidev.cvs.sourceforge.net/viewvc/psidev/psi/psi-ms/mzML/controlledVocabulary/psi-ms.obo