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Die Identifizierung von Genen ist heute durch die Kombination von Hochdurchsatz-Sequenziermethoden wie Deep Sequencing und den Einsatz natürlicher Variationen sehr viel effizienter. Allein in Arabidopsis konnten hunderte Genloci identifiziert werden, die ein breites Spektrum biologischer Vorgänge beeinflussen. Unser Ziel ist es, über die vorhandenen Gene, Proteinprodukte zu charakterisieren. Dabei nutzen wir Ansätze, die es uns erlauben, das umfangreiche Metabolom der Pflanze „als Gesamtbild“ zu erfassen.

Am IPB werden derzeit eine Vielzahl von NMR-Geräten und Massenspektrometern betrieben. Sie werden in allen vier wissenschaftlichen Abteilungen für die Bearbeitung von Fragestellungen innerhalb der Metabolom-Forschung eingesetzt, die damit gleichzeitig auch Teil unserer Metabolomics-Plattform sind.

Die experimentelle Arbeit wird ergänzt durch umfangreiche chemo- und bioinformatische Ansätze, um die großen Datenmengen zu bearbeiten und auszuwerten. Das IPB betreibt den ersten European MassBank Server sowie zahlreiche Online-Tools zur Identifizierung von Metaboliten.

Ansprechpartner für alle Belange innerhalb der Metabolomics-Plattform ist Dr. Steffen Neumann.

Publikationen nach Tag: Metabolomics

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Moreno, P.; Beisken, S.; Harsha, B.; Muthukrishnan, V.; Tudose, I.; Dekker, A.; Dornfeldt, S.; Taruttis, F.; Grosse, I.; Hastings, J.; Neumann, S.; Steinbeck, C. BiNChE: A web tool and library for chemical enrichment analysis based on the ChEBI ontology BMC Bioinformatics 16, 56, (2015) DOI: 10.1186/s12859-015-0486-3

Background: Ontology-based enrichment analysis aids in the interpretation and understanding of large-scale biological data. Ontologies are hierarchies of biologically relevant groupings. Using ontology annotations, which link ontology classes to biological entities, enrichment analysis methods assess whether there is a significant over or under representation of entities for ontology classes. While many tools exist that run enrichment analysis for protein setsannotated with the Gene Ontology, there are only a few that can be used for small molecules enrichment analysis.Results: We describe BiNChE, an enrichment analysis tool for small molecules based on the ChEBI Ontology. BiNChE displays an interactive graph that can be exported as a high-resolution image or in network formats. The tool provides plain, weighted and fragment analysis based on either the ChEBI Role Ontology or the ChEBI Structural Ontology.Conclusions: BiNChE aids in the exploration of large sets of small molecules produced within Metabolomics or other Systems Biology research contexts. The open-source tool provides easy and highly interactive web access to enrichment analysis with the ChEBI ontology tool and is additionally available as a standalone library.

Brack, W.; Altenburger, R.; Schüürmann, G.; Krauss, M.; López Herráez, D.; van Gils, J.; Slobodnik, J.; Munthe, J.; Gawlik, B. M.; van Wezel, A.; Schriks, M.; Hollender, J.; Tollefsen, K. E.; Mekenyan, O.; Dimitrov, S.; Bunke, D.; Cousins, I.; Posthuma, L.; van den Brink, P. J.; López de Alda, M.; Barceló, D.; Faust, M.; Kortenkamp, A.; Scrimshaw, M.; Ignatova, S.; Engelen, G.; Massmann, G.; Lemkine, G.; Teodorovic, I.; Walz, K.-H.; Dulio, V.; Jonker, M. T.O.; Jäger, F.; Chipman, K.; Falciani, F.; Liska, I.; Rooke, D.; Zhang, X.; Hollert, H.; Vrana, B.; Hilscherova, K.; Kramer, K.; Neumann, S.; Hammerbacher, R.; Backhaus, T.; Mack, J.; Segner, H.; Escher, B.; de Aragão Umbuzeiro, G. The SOLUTIONS project: Challenges and responses for present and future emerging pollutants in land and water resources management Science total Environ 503-504, 22-31, (2015) DOI: 10.1016/j.scitotenv.2014.05.143

SOLUTIONS (2013 to 2018) is a European Union Seventh Framework Programme Project (EU-FP7). The project aims to deliver a conceptual framework to support the evidence-based development of environmental policies with regard to water quality. SOLUTIONS will develop the tools for the identification, prioritisation and assessment of those water contaminants that may pose a risk to ecosystems and human health. To this end, a new generation of chemical and effect-based monitoring tools is developed and integrated with a full set of exposure, effect and risk assessment models. SOLUTIONS attempts to address legacy, present and future contamination by integrating monitoring and modelling based approaches with scenarios on future developments in society, economy and technology and thus in contamination. The project follows a solutions-oriented approach by addressing major problems of water and chemicals management and by assessing abatement options. SOLUTIONS takes advantage of the access to the infrastructure necessary to investigate the large basins of the Danube and Rhine as well as relevant Mediterranean basins as case studies, and puts major efforts on stakeholder dialogue and support. Particularly, the EU Water Framework Directive (WFD) Common Implementation Strategy (CIS) working groups, International River Commissions, and water works associations are directly supported with consistent guidance for the early detection, identification, prioritisation, and abatement of chemicals in the water cycle. SOLUTIONS will give a specific emphasis on concepts and tools for the impact and risk assessment of complex mixtures of emerging pollutants, their metabolites and transformation products. Analytical and effect-based screening tools will be applied together with ecological assessment tools for the identification of toxicants and their impacts. The SOLUTIONS approach is expected to provide transparent and evidence-based candidates or River Basin Specific Pollutants in the case study basins and to assist future review of priority pollutants under the WFD as well as potential abatement options.

Libiseller, G.; Dvorzak, M.; Kleb, U.; Gander, E.; Eisenberg, T.; Madeo, F.; Neumann, S.; Trausinger, G.; Sinner, F.; Pieber, T.; Magnes, C. IPO: a tool for automated optimization of XCMS parameters BMC Bioinformatics 16, 118, (2015) DOI: 10.1186/s12859-015-0562-8

Background: Untargeted metabolomics generates a huge amount of data. Software packages for automated data processing are crucial to successfully process these data. A variety of such software packages exist, but the outcome of data processing strongly depends on algorithm parameter settings. If they are not carefully chosen, suboptimal parameter settings can easily lead to biased results. Therefore, parameter settings also require optimization. Severalparameter optimization approaches have already been proposed, but a software package for parameter optimization which is free of intricate experimental labeling steps, fast and widely applicable is still missing.Results: We implemented the software package IPO (‘Isotopologue Parameter Optimization’) which is fast and free of labeling steps, and applicable to data from different kinds of samples and data from different methods of liquid chromatography - high resolution mass spectrometry and data from different instruments. IPO optimizes XCMS peak picking parameters by using natural, stable 13C isotopic peaks to calculate a peak picking score. Retention time correction is optimized by minimizing relative retention time differences within peak groups. Grouping parameters are optimized by maximizing the number of peak groups that show one peak from each injection of a pooled sample. The different parameter settings are achieved by design of experiments, and the resulting scores are evaluated using response surface models. IPO was tested on three different data sets, each consisting of a training set and test set. IPO resulted in an increase of reliable groups (146% - 361%), a decrease of non-reliable groups (3% - 8%) and a decrease of the retention time deviation to one third.Conclusions: IPO was successfully applied to data derived from liquid chromatography coupled to high resolution mass spectrometry from three studies with different sample type s and different chromatographic methods and devices. We were also able to show the potential of IPO to increase the reliability of metabolomics data. The source code is implemented in R, tested on Linux and Windows and it is freely available for download at https://github.com/glibiseller/IPO. The training sets and test sets can be downloaded from https://health.joanneum.at/IPO.

Altenburger, R.; Ait-Aissa, S.; Antczak, P.; Backhaus, T.; Barceló, D.; Seiler, T.-B.; Brion, F.; Busch, W.; Chipman, K.; López de Alda, M.; de Aragão Umbuzeiro, G.; Escher, B. I.; Falciani, F.; Faust, M.; Focks, A.; Hilscherova, K.; Hollender, J.; Hollert, H.; Jäger, F.; Jahnke, A.; Kortenkamp, A.; Krauss, M.; Lemkine, G. F.; Munthe, J.; Neumann, S.; Schymanski, E. L.; Scrimshaw, M.; Segner, H.; Slobodnik, J.; Smedes, F.; Kughathas, S.; Teodorovic, I.; Tindall, A. J.; Tollefsen, K. E.; Walz, K.-H.; Williams, T. D.; Van den Brink, P. J.; van Gils, J.; Vrana, B.; Zhang, X.; Brack, W. Future water quality monitoring — Adapting tools to deal with mixtures of pollutants in water resource management Sci Total Environ 512–513, 540–551, (2015) DOI: 10.1016/j.scitotenv.2014.12.057

Environmental quality monitoringofwaterresourcesis challenged with providing the basisfor safe guarding the environment against adverse biological effects of anthropogenic chemical contamination from diffuse and point sources. While current regulatory efforts focus on monitoring and assessing a few legacy chemicals, many more anthropogenic chemicals can be detected simultaneously in our aquatic resources. However, exposure to chemical mixtures does not necessarily translate into adverse biological effects nor clearly shows whether mitigationmeasures are needed. Thus, the question which mixtures are present and which have associated combined effects becomes central for defining adequate monitoring and assessment strategies. Here we describe the vision of the international, EU-funded project SOLUTIONS, where three routes are explored to link the occurrence of chemical mixtures at specific sites to the assessment of adverse biological combination effects. First of all, multi-residue target and non-target screening techniques covering a broader range of anticipated chemicalsco-occurring in the environment are being developed. By improving sensitivity and detection limits for known bioactive compounds of concern, new analytical chemistry data for multiple components can be obtained and used to characterise priority mixtures. This information on chemical occurrence will be used to predict mixture toxicity and toderive combined effecte stimatessuitable for advancing environmental quality standards. Secondly, bioanalytical tools will be explored to provide aggregate bioactivity measuresintegrating all components that produce common (adverse) outcomes even for mixtures of varying compositions. The ambition is to provide comprehensive arrays of effect-based tools and trait-based field observations that link multiple chemical exposures to various environmental protection goals more directly and to provide improved in situ observations for impact assessment of mixtures. Thirdly, effect-directed analysis (EDA) will be applied to identify major drivers of mixture toxicity. Refinements of EDA include the use of statistical approaches with monitoring information for guidance of experimental EDA studies. These three approaches will be explored using case studies at theDanube and Rhine river basins as well as rivers of the Iberian Peninsula. The synthesis offindings will be organised toprovide guidance for futuresolution-oriented environmenta lmonitoring and exploremore systematic ways to assess mixture exposures and combination effects in future water quality monitoring.

Horai, H.; Arita, M.; Kanaya, S.; Nihei, Y.; Ikeda, T.; Suwa, K.; Ojima, Y.; Tanaka, K.; Tanaka, S.; Aoshima, K.; Oda, Y.; Kakazu, Y.; Kusano, M.; Tohege, T.; Matsuda, F.; Sawada, Y.; Hirai, M.Y.; Nakanishi, H.; Ikeda, K.; Akimoto, N.; Maoko, T.; Takahashi, H.; Ara, T.; Sakurai, N.; Suzuki, H.; Shibata, D.; Neumann, S.; Iida, T.; Tanaka, K.; Funatsu, K.; Matsuura, F.; Soga, T.; Taguchi, R.; Saito, K.; Nishioka, T. MassBank: a public repository for sharing mass spectral data for life sciences Journal of Mass Spectrometrie 45(7), 703-714, (2010) DOI: 10.1002/jms.1777

MassBank is the first public repository of mass spectra of small chemical compounds for life sciences (<3000 Da). The database contains 605 electron-ionization mass spectrometry (EI-MS), 137 fast atom bombardment MS and 9276 electrospray ionization (ESI)-MS(n) data of 2337 authentic compounds of metabolites, 11 545 EI-MS and 834 other-MS data of 10,286 volatile natural and synthetic compounds, and 3045 ESI-MS(2) data of 679 synthetic drugs contributed by 16 research groups (January 2010). ESI-MS(2) data were analyzed under nonstandardized, independent experimental conditions. MassBank is a distributed database. Each research group provides data from its own MassBank data servers distributed on the Internet. MassBank users can access either all of the MassBank data or a subset of the data by specifying one or more experimental conditions. In a spectral search to retrieve mass spectra similar to a query mass spectrum, the similarity score is calculated by a weighted cosine correlation in which weighting exponents on peak intensity and the mass-to-charge ratio are optimized to the ESI-MS(2) data. MassBank also provides a merged spectrum for each compound prepared by merging the analyzed ESI-MS(2) data on an identical compound under different collision-induced dissociation conditions. Data merging has significantly improved the precision of the identification of a chemical compound by 21-23% at a similarity score of 0.6. Thus, MassBank is useful for the identification of chemical compounds and the publication of experimental data.

Böttcher, C.; Centeno, D.; Freitag, J.; Höfgen, R.; Köhl, K.; Kopka, J.; Kroymann, J.; Matros, A.; Mock, H.P.; Neumann, S.; Pfalz, M.; von Roepenack-Lahaye, E.; Schauer, N.; Trenkamp, S.; Zubriggen, M.; Fernie, A.R. Teaching (and learning from) metabolomics: the 2006 PlantMetaNet ETNA Metabolomics Research School Physiol Plant 132, 136-49, (2008) DOI: 10.1111/j.1399-3054.2007.00990.x

Under the auspices of the European Training and Networking Activity programme of the European Union, a 'Metabolic Profiling and Data Analysis' Plant Genomics and Bioinformatics Summer School was hosted in Potsdam, Germany between 20 and 29 September 2006. Sixteen early career researchers were invited from the European Union partner nations and the so-called developing nations (Appendix). Lectures from invited leading European researchers provided an overview of the state of the art of these fields and seeded discussion regarding major challenges for their future advancement. Hands-on experience was provided by an example experiment - that of defining the metabolic response of Arabidopsis to treatment of a commercial herbicide of defined mode of action. This experiment was performed throughout the duration of the course in order to teach the concepts underlying extraction and machine handling as well as to provide a rich data set with which the required computation and statistical skills could be illustrated. Here we review the state of the field by describing both key lectures given at and practical aspects taught at the summer school. In addition, we disclose results that were obtained using the four distinct technical platforms at the different participating institutes. While the effects of the chosen herbicide are well documented, this study looks at a broader number of metabolites than in previous investigations. This allowed, on the one hand, not only to characterise further effects of the herbicide than previously observed but also to detect molecules other than the herbicide that were obviously present in the commercial formulation. These data and the workshop in general are all discussed in the context of the teaching of metabolomics.

Böttcher, C.; von Roepenack-Lahaye, E.; Schmidt, J.; Schmotz, C.; Neumann, S.; Scheel, D.; Clemens, S. Metabolome analysis of biosynthetic mutants reveals diversity of metabolomic changes and allows identification of a large number of new compounds in <span>Arabidopsis thaliana</span> Plant Physiol 147, 2107-2120, (2008) DOI: 10.1104/pp.108.117754

Metabolomics is facing a major challenge: the lack of knowledge about metabolites present in a given biological system. Thus, large-scale discovery of metabolites is considered an essential step toward a better understanding of plant metabolism. We show here that the application of a metabolomics approach generating structural information for the analysis of Arabidopsis (Arabidopsis thaliana) mutants allows the efficient cataloging of metabolites. Fifty-six percent of the features that showed significant differences in abundance between seeds of wild-type, transparent testa4, and transparent testa5 plants could be annotated. Seventy-five compounds were structurally characterized, 21 of which could be identified. About 40 compounds had not been known from Arabidopsis before. Also, the high-resolution analysis revealed an unanticipated expansion of metabolic conversions upstream of biosynthetic blocks. Deficiency in chalcone synthase results in the increased seed-specific biosynthesis of a range of phenolic choline esters. Similarly, a lack of chalcone isomerase activity leads to the accumulation of various naringenin chalcone derivatives. Furthermore, our data provide insight into the connection between p-coumaroyl-coenzyme A-dependent pathways. Lack of flavonoid biosynthesis results in elevated synthesis not only of p-coumarate-derived choline esters but also of sinapate-derived metabolites. However, sinapoylcholine is not the only accumulating end product. Instead, we observed specific and sophisticated changes in the complex pattern of sinapate derivatives.

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