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Publications

Westphal, L.; Strehmel, N.; Eschen-Lippold, L.; Bauer, N.; Westermann, B.; Rosahl, S.; Scheel, D.; Lee, J. pH effects on plant calcium fluxes: lessons from acidification-mediated calcium elevation induced by the γ-glutamyl-leucine dipeptide identified from Phytophthora infestans Sci Rep 9, 4733, (2019) DOI: 10.1038/s41598-019-41276-0

Cytosolic Ca2+ ([Ca2+]cyt) elevation is an early signaling response upon exposure to pathogen-derived molecules (so-called microbe-associated molecular patterns, MAMPs) and has been successfully used as a quantitative read-out in genetic screens to identify MAMP receptors or their associated components. Here, we isolated and identified by mass spectrometry the dipeptide γ-Glu-Leu as a component of a Phytophthora infestans mycelium extract that induces [Ca2+]cyt elevation. Treatment of Arabidopsis seedlings with synthetic γ-Glu-Leu revealed stimulatory effects on defense signaling, including a weak enhancement of the expression of some MAMP-inducible genes or affecting the refractory period to a second MAMP elicitation. However, γ-Glu-Leu is not a classical MAMP since pH adjustment abolished these activities and importantly, the observed effects of γ-Glu-Leu could be recapitulated by mimicking extracellular acidification. Thus, although γ-Glu-Leu can act as a direct agonist of calcium sensing receptors in animal systems, the Ca2+-mobilizing activity in plants reported here is due to acidification. Low pH also shapes the Ca2+ signature of well-studied MAMPs (e.g. flg22) or excitatory amino acids such as glutamate. Overall, this work serves as a cautionary reminder that in defense signaling studies where Ca2+ flux measurements are concerned, it is important to monitor and consider the effects of pH.
Publications

Hoffmann, N.; Rein, J.; Sachsenberg, T.; Hartler, J.; Haug, K.; Mayer, G.; Alka, O.; Dayalan, S.; Pearce, J. T. M.; Rocca-Serra, P.; Qi, D.; Eisenacher, M.; Perez-Riverol, Y.; Vizcaíno, J. A.; Salek, R. M.; Neumann, S.; Jones, A. R. mzTab-M: A Data Standard for Sharing Quantitative Results in Mass Spectrometry Metabolomics Anal Chem 91, 3302-3310, (2019) DOI: 10.1021/acs.analchem.8b04310

Mass spectrometry (MS) is one of the primary techniques used for large-scale analysis of small molecules in metabolomics studies. To date, there has been little data format standardization in this field, as different software packages export results in different formats represented in XML or plain text, making data sharing, database deposition, and reanalysis highly challenging. Working within the consortia of the Metabolomics Standards Initiative, Proteomics Standards Initiative, and the Metabolomics Society, we have created mzTab-M to act as a common output format from analytical approaches using MS on small molecules. The format has been developed over several years, with input from a wide range of stakeholders. mzTab-M is a simple tab-separated text format, but importantly, the structure is highly standardized through the design of a detailed specification document, tightly coupled to validation software, and a mandatory controlled vocabulary of terms to populate it. The format is able to represent final quantification values from analyses, as well as the evidence trail in terms of features measured directly from MS (e.g., LC-MS, GC-MS, DIMS, etc.) and different types of approaches used to identify molecules. mzTab-M allows for ambiguity in the identification of molecules to be communicated clearly to readers of the files (both people and software). There are several implementations of the format available, and we anticipate widespread adoption in the field.
Publications

Peters, K.; Bradbury, J.; Bergmann, S.; Capuccini, M.; Cascante, M.; de Atauri, P.; Ebbels, T. M. D.; Foguet, C.; Glen, R.; Gonzalez-Beltran, A.; Günther, U. L.; Handakas, E.; Hankemeier, T.; Haug, K.; Herman, S.; Holub, P.; Izzo, M.; Jacob, D.; Johnson, D.; Jourdan, F.; Kale, N.; Karaman, I.; Khalili, B.; Emami Khonsari, P.; Kultima, K.; Lampa, S.; Larsson, A.; Ludwig, C.; Moreno, P.; Neumann, S.; Novella, J. A.; O'Donovan, C.; Pearce, J. T. M.; Peluso, A.; Piras, M. E.; Pireddu, L.; Reed, M. A. C.; Rocca-Serra, P.; Roger, P.; Rosato, A.; Rueedi, R.; Ruttkies, C.; Sadawi, N.; Salek, R. M.; Sansone, S.-A.; Selivanov, V.; Spjuth, O.; Schober, D.; Thévenot, E. A.; Tomasoni, M.; van Rijswijk, M.; van Vliet, M.; Viant, M. R.; Weber, R. J. M.; Zanetti, G.; Steinbeck, C. PhenoMeNal: processing and analysis of metabolomics data in the cloud GigaScience 8, giy149, (2019) DOI: 10.1093/gigascience/giy149

BackgroundMetabolomics is the comprehensive study of a multitude of small molecules to gain insight into an organism's metabolism. The research field is dynamic and expanding with applications across biomedical, biotechnological, and many other applied biological domains. Its computationally intensive nature has driven requirements for open data formats, data repositories, and data analysis tools. However, the rapid progress has resulted in a mosaic of independent, and sometimes incompatible, analysis methods that are difficult to connect into a useful and complete data analysis solution.FindingsPhenoMeNal (Phenome and Metabolome aNalysis) is an advanced and complete solution to set up Infrastructure-as-a-Service (IaaS) that brings workflow-oriented, interoperable metabolomics data analysis platforms into the cloud. PhenoMeNal seamlessly integrates a wide array of existing open-source tools that are tested and packaged as Docker containers through the project's continuous integration process and deployed based on a kubernetes orchestration framework. It also provides a number of standardized, automated, and published analysis workflows in the user interfaces Galaxy, Jupyter, Luigi, and Pachyderm.ConclusionsPhenoMeNal constitutes a keystone solution in cloud e-infrastructures available for metabolomics. PhenoMeNal is a unique and complete solution for setting up cloud e-infrastructures through easy-to-use web interfaces that can be scaled to any custom public and private cloud environment. By harmonizing and automating software installation and configuration and through ready-to-use scientific workflow user interfaces, PhenoMeNal has succeeded in providing scientists with workflow-driven, reproducible, and shareable metabolomics data analysis platforms that are interfaced through standard data formats, representative datasets, versioned, and have been tested for reproducibility and interoperability. The elastic implementation of PhenoMeNal further allows easy adaptation of the infrastructure to other application areas and ‘omics research domains.
Printed publications

Emami Khoonsari, P.; Moreno, P.; Bergmann, S.; Burman, J.; Capuccini, M.; Carone, M.; Cascante, M.; de Atauri, P.; Foguet, C.; Gonzalez-Beltran, A.; Hankemeier, T.; Haug, K.; He, S.; Herman, S.; Johnson, D.; Kale, N.; Larsson, A.; Neumann, S.; Peters, K.; Pireddu, L.; Rocca-Serra, P.; Roger, P.; Rueedi, R.; Ruttkies, C.; Sadawi, N.; Salek, R. M.; Sansone, S.-A.; Schober, D.; Selivanov, V.; Thévenot, E. A.; van Vliet, M.; Zanetti, G.; Steinbeck, C.; Kultima, K.; Spjuth, O. Interoperable and scalable data analysis with microservices: Applications in Metabolomics Bioinformatics (2019) DOI: 10.1093/bioinformatics/btz160

MotivationDeveloping a robust and performant data analysis workflow that integrates all necessary components whilst still being able to scale over multiple compute nodes is a challenging task. We introduce a generic method based on the microservice architecture, where software tools are encapsulated as Docker containers that can be connected into scientific workflows and executed using the Kubernetes container orchestrator.ResultsWe developed a virtual research environment which facilitates rapid integration of new tools and developing scalable and interoperable workflows for performing metabolomics data analysis. The environment can be launched on-demand on cloud resources and desktop computers. IT-expertise requirements on the user side are kept to a minimum, and workflows can be re-used effortlessly by any novice user. We validate our method in the field of metabolomics on two mass spectrometry, one nuclear magnetic resonance spectroscopy and one fluxomics study. We showed that the method scales dynamically with increasing availability of computational resources. We demonstrated that the method facilitates interoperability using integration of the major software suites resulting in a turn-key workflow encompassing all steps for mass-spectrometry-based metabolomics including preprocessing, statistics, and identification. Microservices is a generic methodology that can serve any scientific discipline and opens up for new types of large-scale integrative science.Availability and ImplementationThe PhenoMeNal consortium maintains a web portal (https://portal.phenomenal-h2020.eu) providing a GUI for launching the virtual research environment. The GitHub repository https://github.com/phnmnl/ hosts the source code of all projects.
Publications

Matern, A.; Böttcher, C.; Eschen-Lippold, L.; Westermann, B.; Smolka, U.; Döll, S.; Trempel, F.; Aryal, B.; Scheel, D.; Geisler, M.; Rosahl, S. A substrate of the ABC transporter PEN3 stimulates bacterial flagellin (flg22)-induced callose deposition in Arabidopsis thaliana J Biol Chem 294, 6857-6870, (2019) DOI: 10.1074/jbc.RA119.007676

Nonhost resistance of Arabidopsis thaliana against Phytophthora infestans, a filamentous eukaryotic microbe and the causal agent of potato late blight, is based on a multilayered defense system. Arabidopsis thaliana controls pathogen entry through the penetration-resistance genes PEN2 and PEN3, encoding an atypical myrosinase and an ABC transporter, respectively, required for synthesis and export of unknown indole compounds. To identify pathogen-elicited leaf surface metabolites and further unravel nonhost resistance in Arabidopsis, we performed untargeted metabolite profiling by incubating a P. infestans zoospore suspension on leaves of WT or pen3 mutant Arabidopsis plants. Among the plant-secreted metabolites, 4-methoxyindol-3-yl-methanol and S-(4-methoxy-indol-3-yl-methyl) cysteine were detected in spore suspensions recollected from WT plants, but at reduced levels from the pen3 mutant plants. In both whole-cell and microsome-based assays, 4-methoxyindol-3-yl-methanol was transported in a PEN3-dependent manner, suggesting that this compound is a PEN3 substrate. The syntheses of both compounds were dependent on functional PEN2 and phytochelatin synthase 1. None of these compounds inhibited mycelial growth of P. infestans in vitro. Of note, exogenous application of 4-methoxyindol-3-yl methanol slightly elevated cytosolic Ca2+ levels and enhanced callose deposition in hydathodes of seedlings treated with a bacterial pathogen-associated molecular pattern (PAMP), flagellin (flg22). Loss of flg22-induced callose deposition in leaves of pen3 seedlings was partially reverted by the addition of 4-methoxyindol-3-yl methanol. In conclusion, we have identified a specific indole compound that is a substrate for PEN3 and contributes to the plant defense response against microbial pathogens.
Books and chapters

Knogge, W. Diseases affecting barley: scald (Ed. Oliver R). Burleigh Dodds Series in Agricultural Science 183-215, (2018) ISBN: 9781786762160 DOI: 10.19103/as.2018.0039.10

Scald (leaf blotch), caused by the hemibiotrophic pathogen Rhynchosporium commune, is one of the major diseases of barley worldwide. Typical disease symptoms consist of necrotic areas on the leaf blades. Yield losses are manifested as reduced kernel quality, size and number per ear. This chapter reviews the origins, epidemiology and other characteristic features of scald, and considers the agricultural consequences of the pathogen’s biology. It then considers resistance breeding programmes in which more than a dozen major resistance genes as well as quantitative trait loci have been identified, and discusses strategies to minimize the damage caused by the disease comprising agricultural practices and different fungicides.
Printed publications

Moreno, P.; Pireddu, L.; Roger, P.; Goonasekera, N.; Afgan, E.; van den Beek, M.; He, S.; Larsson, A.; Ruttkies, C.; Schober, D.; Johnson, D.; Rocca-Serra, P.; Weber, R. J. M.; Gruening, B.; Salek, R.; Kale, N.; Perez-Riverol, Y.; Papatheodorou, I.; Spjuth, O.; Neumann, S. Galaxy-Kubernetes integration: scaling bioinformatics workflows in the cloud bioRxiv (2018) DOI: 10.1101/488643

Summary: Making reproducible, auditable and scalable data-processing analysis workflows is an important challenge in the field of bioinformatics. Recently, software containers and cloud computing introduced a novel solution to address these challenges. They simplify software installation, management and reproducibility by packaging tools and their dependencies. In this work we implemented a cloud provider agnostic and scalable container orchestration setup for the popular Galaxy workflow environment. This solution enables Galaxy to run on and offload jobs to most cloud providers (e.g. Amazon Web Services, Google Cloud or OpenStack, among others) through the Kubernetes container orchestrator. Availability: All code has been contributed to the Galaxy Project and is available (since Galaxy 17.05) at https://github.com/galaxyproject/ in the galaxy and galaxy-kubernetes repositories. https://public.phenomenal-h2020.eu/ is an example deployment.
Publications

McEachran, A. D.; Mansouri, K.; Grulke, C.; Schymanski, E. L.; Ruttkies, C.; Williams, A. J. “MS-Ready” structures for non-targeted high-resolution mass spectrometry screening studies J Cheminformatics 10, 45, (2018) DOI: 10.1186/s13321-018-0299-2

Chemical database searching has become a fixture in many non-targeted identification workflows based on high-resolution mass spectrometry (HRMS). However, the form of a chemical structure observed in HRMS does not always match the form stored in a database (e.g., the neutral form versus a salt; one component of a mixture rather than the mixture form used in a consumer product). Linking the form of a structure observed via HRMS to its related form(s) within a database will enable the return of all relevant variants of a structure, as well as the related metadata, in a single query. A Konstanz Information Miner (KNIME) workflow has been developed to produce structural representations observed using HRMS (“MS-Ready structures”) and links them to those stored in a database. These MS-Ready structures, and associated mappings to the full chemical representations, are surfaced via the US EPA’s Chemistry Dashboard (https://comptox.epa.gov/dashboard/). This article describes the workflow for the generation and linking of ~ 700,000 MS-Ready structures (derived from ~ 760,000 original structures) as well as download, search and export capabilities to serve structure identification using HRMS. The importance of this form of structural representation for HRMS is demonstrated with several examples, including integration with the in silico fragmentation software application MetFrag. The structures, search, download and export functionality are all available through the CompTox Chemistry Dashboard, while the MetFrag implementation can be viewed at https://msbi.ipb-halle.de/MetFragBeta/.
Publications

Herz, K.; Dietz, S.; Gorzolka, K.; Haider, S.; Jandt, U.; Scheel, D.; Bruelheide, H. Linking root exudates to functional plant traits PLOS ONE 13, e0204128, (2018) DOI: 10.1371/journal.pone.0204128

Primary and secondary metabolites exuded by plant roots have mainly been studied under laboratory conditions, while knowledge of root exudate patterns of plants growing in natural communities is very limited. Focusing on ten common European grassland plant species, we asked to which degree exuded metabolite compositions are specific to species or growth forms (forbs and grasses), depend on environments and local neighbourhoods, and reflect traditional plant functional traits. Root exudates were collected under field conditions and analysed using a non-targeted gas chromatography coupled mass spectrometry (GC-MS) approach. In total, we annotated 153 compounds of which 36 were identified by structure and name as metabolites mainly derived from the primary metabolism. Here we show by using variance partitioning, that the composition of exuded polar metabolites was mostly explained by plot identity, followed by plant species identity while plant species composition of the local neighbourhood played no role. Total and root dry biomass explained the largest proportion of variance in exudate composition, with additional variance explained by traditional plant traits. Although the exudate composition was quite similar between the two growth forms, we found some metabolites that occurred only in one of the two growth forms. Our study demonstrated the feasibility of measuring polar exudates under non-sterile field conditions by mass spectrometry, which opens new avenues of research for functional plant ecology.
Publications

Schüler, J.-A.; Neumann, S.; Müller-Hannemann, M.; Brandt, W. ChemFrag: Chemically meaningful annotation of fragment ion mass spectra J Mass Spectrom 53, 1104-1115, (2018) DOI: 10.1002/jms.4278

Identification and structural determination of small molecules by mass spectrometry is an important step in chemistry and biochemistry. However, the chemically realistic annotation of a fragment ion spectrum can be a difficult challenge. We developed ChemFrag, for the detection of fragmentation pathways and the annotation of fragment ions with chemically reasonable structures. ChemFrag combines a quantum chemical with a rule‐based approach. For different doping substances as test instances, ChemFrag correctly annotates fragment ions. In most cases, the predicted fragments are chemically more realistic than those from purely combinatorial approaches, or approaches based on machine learning. The annotation generated by ChemFrag often coincides with spectra that have been manually annotated by experts. This is a major advance in peak annotation and allows a more precise automatic interpretation of mass spectra.
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