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Publications - Stress and Develop Biology

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Publications

Schober, D., Jacob, D., Wilson, M., Cruz, J. A., Marcu, A., Grant, J. R., Moing, A., Deborde, C., de Figueiredo, L. F., Haug, K., Rocca-Serra, P., Easton, J., Ebbels, T. M. D., Hao, J., Ludwig, C., Günther, U. L., Rosato, A., Klein, M. S., Lewis, I. A., Luchinat, C., Jones, A. R., Grauslys, A., Larralde, M., Yokochi, M., Kobayashi, N., Porzel, A., Griffin, J. L., Viant, M. R., Wishart, D. S., Steinbeck, C., Salek, R. M. & Neumann, S. nmrML: A community supported open data standard for the description, storage, and exchange of NMR data. Anal Chem. 90 , 649–656, (2018) DOI: 10.1021/acs.analchem.7b02795

NMR is a widely used analytical technique with a growing number of repositories available. As a result, demands for a vendor-agnostic, open data format for long-term archiving of NMR data have emerged with the aim to ease and encourage sharing, comparison, and reuse of NMR data. Here we present nmrML, an open XML-based exchange and storage format for NMR spectral data. The nmrML format is intended to be fully compatible with existing NMR data for chemical, biochemical, and metabolomics experiments. nmrML can capture raw NMR data, spectral data acquisition parameters, and where available spectral metadata, such as chemical structures associated with spectral assignments. The nmrML format is compatible with pure-compound NMR data for reference spectral libraries as well as NMR data from complex biomixtures, i.e., metabolomics experiments. To facilitate format conversions, we provide nmrML converters for Bruker, JEOL and Agilent/Varian vendor formats. In addition, easy-to-use Web-based spectral viewing, processing, and spectral assignment tools that read and write nmrML have been developed. Software libraries and Web services for data validation are available for tool developers and end-users. The nmrML format has already been adopted for capturing and disseminating NMR data for small molecules by several open source data processing tools and metabolomics reference spectral libraries, e.g., serving as storage format for the MetaboLights data repository. The nmrML open access data standard has been endorsed by the Metabolomics Standards Initiative (MSI), and we here encourage user participation and feedback to increase usability and make it a successful standard.
Printed publications

Döll, S., Kuhlmann, M., Rutten, T., Mette, M. F., Scharfenberg, S., Petridis, A., Berreth, D.-C. & & Mock, H.-P.  Accumulation of the coumarin scopolin under abiotic stress conditions is mediated by the Arabidopsis thaliana THO/TREX complex. Plant J. (2018) DOI: 10.1111/tpj.13797

Secondary metabolites are involved in the plant stress response. Among these are scopolin and its active form scopoletin, which are coumarin derivatives associated with reactive oxygen species scavenging and pathogen defence. Here we show that scopolin accumulation can be induced in the root by osmotic stress and in the leaf by low-temperature stress in Arabidopsis thaliana. A genetic screen for altered scopolin levels in A. thaliana revealed a mutant compromised in scopolin accumulation in response to stress; the lesion was present in a homologue of THO1 coding for a subunit of the THO/TREX complex. The THO/TREX complex contributes to RNA silencing, supposedly by trafficking precursors of small RNAs. Mutants defective in THO, AGO1, SDS3 and RDR6 were impaired with respect to scopolin accumulation in response to stress, suggesting a mechanism based on RNA silencing such as the trans-acting small interfering RNA pathway, which requires THO/TREX function.
Publications

Strehmel, N., Hoehenwarter, W., Mönchgesang, S., Majovsky, P., Krüger, S., Scheel, D. & Lee, J. Stress-reated mitogen-activated protein kinases stimulate the accumulation of small molecules and proteins in Arabidopsis thaliana root exudates. Front Plant Sci 8 , 1292, (2017) DOI: 10.3389/fpls.2017.01292

A delicate balance in cellular signaling is required for plants to respond to microorganisms or to changes in their environment. Mitogen-activated protein kinase (MAPK) cascades are one of the signaling modules that mediate transduction of extracellular microbial signals into appropriate cellular responses. Here, we employ a transgenic system that simulates activation of two pathogen/stress-responsive MAPKs to study release of metabolites and proteins into root exudates. The premise is based on our previous proteomics study that suggests upregulation of secretory processes in this transgenic system. An advantage of this experimental set-up is the direct focus on MAPK-regulated processes without the confounding complications of other signaling pathways activated by exposure to microbes or microbial molecules. Using non-targeted metabolomics and proteomics studies, we show that MAPK activation can indeed drive the appearance of dipeptides, defense-related metabolites and proteins in root apoplastic fluid. However, the relative levels of other compounds in the exudates were decreased. This points to a bidirectional control of metabolite and protein release into the apoplast. The putative roles for some of the identified apoplastic metabolites and proteins are discussed with respect to possible antimicrobial/defense or allelopathic properties. Overall, our findings demonstrate that sustained activation of MAPKs alters the composition of apoplastic root metabolites and proteins, presumably to influence the plant-microbe interactions in the rhizosphere. The reported metabolomics and proteomics data are available via Metabolights (Identifier: MTBLS441) and ProteomeXchange (Identifier: PXD006328), respectively.
Printed publications

Al Shweiki, M. H. D. R., Mönchgesang, S., Majovsky, P., Thieme, D., Trutschel, D. & Hoehenwarter, W. Assessment of Label-Free quantification in discovery proteomics and impact of technological factors and natural variability of protein abundance. J Proteome Res. 16 , 1410–1424, (2017) DOI: 10.1021/acs.jproteome.6b00645

We evaluated the state of label-free discovery proteomics focusing especially on technological contributions and contributions of naturally occurring differences in protein abundance to the intersample variability in protein abundance estimates in this highly peptide-centric technology. First, the performance of popular quantitative proteomics software, Proteome Discoverer, Scaffold, MaxQuant, and Progenesis QIP, was benchmarked using their default parameters and some modified settings. Beyond this, the intersample variability in protein abundance estimates was decomposed into variability introduced by the entire technology itself and variable protein amounts inherent to individual plants of the Arabidopsis thaliana Col-0 accession. The technical component was considerably higher than the biological intersample variability, suggesting an effect on the degree and validity of reported biological changes in protein abundance. Surprisingly, the biological variability, protein abundance estimates, and protein fold changes were recorded differently by the software used to quantify the proteins, warranting caution in the comparison of discovery proteomics results. As expected, ∼99% of the proteome was invariant in the isogenic plants in the absence of environmental factors; however, few proteins showed substantial quantitative variability. This naturally occurring variation between individual organisms can have an impact on the causality of reported protein fold changes.

Publications

Meier, R., Ruttkies, C., Treutler, H. & Neumann, S. Bioinformatics can boost metabolomics research.  J. Biotechnol. 261 , 137-141, (2017) DOI: 10.1016/j.jbiotec.2017.05.018

Metabolomics is the modern term for the field of small molecule research in biology and biochemistry. Currently, metabolomics is undergoing a transition where the classic analytical chemistry is combined with modern cheminformatics and bioinformatics methods, paving the way for large-scale data analysis. We give some background on past developments, highlight current state-of-the-art approaches, and give a perspective on future requirements.
Publications

Furlan, G., Nakagami, H., Eschen-Lippold, L., Jiang, X., Majovsky, P., Kowarschik, K., Hoehenwarter, W., Lee, J. & Trujillo, M. Changes in PUB22 ubiquitination modes triggered by MITOGEN-ACTIVATED PROTEIN KINASE3 dampen the immune response Plant Cell 29, 726-745, (2017) DOI: 10.1105/tpc.16.00654

Crosstalk between post-translational modifications such as ubiquitination and phosphorylation play key roles in controlling the duration and intensity of signalling events to ensure cellular homeostasis. However, the molecular mechanisms underlying the regulation of negative feedback loops remain poorly understood. Here we uncover a pathway in Arabidopsis thaliana by which a negative feedback loop involving the E3 ubiquitin ligase PUB22 that dampens the immune response is triggered by MITOGEN-ACTIVATED PROTEIN KINASE3 (MPK3), best known for its function in the activation of signalling. PUB22's stability is controlled by MPK3-mediated phosphorylation of residues localized in and adjacent to the E2 docking domain. We show that phosphorylation is critical for stabilization by inhibiting PUB22 oligomerization and thus autoubiquitination. The activity switch allows PUB22 to dampen the immune response. This regulatory mechanism also suggests that autoubiquitination, which is inherent to most single unit E3s in vitro, can function as a self-regulatory mechanism in vivo. 
Publications

Ziegler, J., Schmidt, S., Strehmel, N., Scheel, D. & Abel, S. Arabidopsis transporter ABCG37/PDR9 contributes primarily highly oxygenated coumarins to root exudation.  Scientific Rep 7, 3704, (2017) DOI: 10.1038/s41598-017-03250-6

The chemical composition of root exudates strongly impacts the interactions of plants with microorganisms in the rhizosphere and the efficiency of nutrient acquisition. Exudation of metabolites is in part mediated by ATP-binding cassette (ABC) transporters. In order to assess the contribution of individual ABC transporters to root exudation, we performed an LC-MS based non-targeted metabolite profiling of semi-polar metabolites accumulating in root exudates of Arabidopsis thaliana plants and mutants deficient in the expression of ABCG36 (PDR8/PEN3), ABCG37 (PDR9) or both transporters. Comparison of the metabolite profiles indicated distinct roles for each ABC transporter in root exudation. Thymidine exudation could be attributed to ABCG36 function, whereas coumarin exudation was strongly reduced only in ABCG37 deficient plants. However, coumarin exudation was compromised in abcg37 mutants only with respect to certain metabolites of this substance class. The specificity of ABCG37 for individual coumarins was further verified by a targeted LC-MS based coumarin profiling method. The response to iron deficiency, which is known to strongly induce coumarin exudation, was also investigated. In either treatment, the distribution of individual coumarins between roots and exudates in the investigated genotypes suggested the involvement of ABCG37 in the exudation specifically of highly oxygenated rather than monohydroxylated coumarins.
Publications

Witting, M., Ruttkies, C., Neumann, S. & Schmitt-Kopplin, P. LipidFrag: Improving reliability of in silico fragmentation of lipids and application to the Caenorhabditis elegans lipidome.  PLoS ONE 12, e0172311, (2017) DOI: 10.1371/journal.pone.0172311

Lipid identification is a major bottleneck in high-throughput lipidomics studies. However, tools for the analysis of lipid tandem MS spectra are rather limited. While the comparison against spectra in reference libraries is one of the preferred methods, these libraries are far from being complete. In order to improve identification rates, the in silico fragmentation tool MetFrag was combined with Lipid Maps and lipid-class specific classifiers which calculate probabilities for lipid class assignments. The resulting LipidFrag workflow was trained and evaluated on different commercially available lipid standard materials, measured with data dependent UPLC-Q-ToF-MS/MS acquisition. The automatic analysis was compared against manual MS/MS spectra interpretation. With the lipid class specific models, identification of the true positives was improved especially for cases where candidate lipids from different lipid classes had similar MetFrag scores by removing up to 56% of false positive results. This LipidFrag approach was then applied to MS/MS spectra of lipid extracts of the nematode Caenorhabditis elegans. Fragments explained by LipidFrag match known fragmentation pathways, e.g., neutral losses of lipid headgroups and fatty acid side chain fragments. Based on prediction models trained on standard lipid materials, high probabilities for correct annotations were achieved, which makes LipidFrag a good choice for automated lipid data analysis and reliability testing of lipid identifications.
Publications

Schymanski, E. L., Ruttkies, C., Krauss, M., Brouard, C., Kind, T., Dührkop, K., Allen, F., Vaniya, A., Verdegem, D., Böcker, S., Rousu, J., Shen, H., Tsugawa, H., Sajed, T., Fiehn, O., Ghesquière, B. & Neumann, S. Critical assessment of small molecule identification 2016: automated methods. J. Cheminformatics 9, 22, (2017) DOI: 10.1186/s13321-017-0207-1

Background
The fourth round of the Critical Assessment of Small Molecule Identification (CASMI) Contest (www.casmi-contest.org) was held in 2016, with two new categories for automated methods. This article covers the 208 challenges in Categories 2 and 3, without and with metadata, from organization, participation, results and post-contest evaluation of CASMI 2016 through to perspectives for future contests and small molecule annotation/identification.

Results
The Input Output Kernel Regression (CSI:IOKR) machine learning approach performed best in “Category 2: Best Automatic Structural Identification—In Silico Fragmentation Only”, won by Team Brouard with 41% challenge wins. The winner of “Category 3: Best Automatic Structural Identification—Full Information” was Team Kind (MS-FINDER), with 76% challenge wins. The best methods were able to achieve over 30% Top 1 ranks in Category 2, with all methods ranking the correct candidate in the Top 10 in around 50% of challenges. This success rate rose to 70% Top 1 ranks in Category 3, with candidates in the Top 10 in over 80% of the challenges. The machine learning and chemistry-based approaches are shown to perform in complementary ways.

Conclusions
The improvement in (semi-)automated fragmentation methods for small molecule identification has been substantial. The achieved high rates of correct candidates in the Top 1 and Top 10, despite large candidate numbers, open up great possibilities for high-throughput annotation of untargeted analysis for “known unknowns”. As more high quality training data becomes available, the improvements in machine learning methods will likely continue, but the alternative approaches still provide valuable complementary information. Improved integration of experimental context will also improve identification success further for “real life” annotations. The true “unknown unknowns” remain to be evaluated in future CASMI contests.
Publications

Blüher, D., Laha, D., Thieme, S., Hofer, A., Eschen-Lippold, L., Masch, A., Balcke, G., Pavlovic, I., Nagel, O., Schonsky, A., Hinkelmann, R., Wörner, J., Parvin, N., Greiner, R., Weber, S., Tissier, A., Schutkowski, M., Lee, J., Jessen, H., Schaaf, G. & Bonas, U. A 1-phytase type III effector interferes with plant hormone signaling. Nature Commun. 8(1), 2159, (2017) DOI: 10.1038/s41467-017-02195-8

Most Gram-negative phytopathogenic bacteria inject type III effector (T3E) proteins into plant cells to manipulate signaling pathways to the pathogen’s benefit. In resistant plants, specialized immune receptors recognize single T3Es or their biochemical activities, thus halting pathogen ingress. However, molecular function and mode of recognition for most T3Es remains elusive. Here, we show that the Xanthomonas T3E XopH possesses phytase activity, i.e., dephosphorylates phytate (myo-inositol-hexakisphosphate, InsP6), the major phosphate storage compound in plants, which is also involved in pathogen defense. A combination of biochemical approaches, including a new NMR-based method to discriminate inositol polyphosphate enantiomers, identifies XopH as a naturally occurring 1-phytase that dephosphorylates InsP6 at C1. Infection of Nicotiana benthamiana and pepper by Xanthomonas results in a XopH-dependent conversion of InsP6 to InsP5. 1-phytase activity is required for XopH-mediated immunity of plants carrying the Bs7 resistance gene, and for induction of jasmonate- and ethylene-responsive genes in N. benthamiana.
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