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Publications - Stress and Develop Biology

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Publications

Cotrim, C. A.; Weidner, A.; Strehmel, N.; Bisol, T. B.; Meyer, D.; Brandt, W.; Wessjohann, L. A.; Stubbs, M. T. A Distinct Aromatic Prenyltransferase Associated with the Futalosine Pathway ChemistrySelect 2, 9319-9325, (2017) DOI: 10.1002/slct.201702151

Menaquinone (MK) is an electron carrier molecule essential for respiration in most Gram positive bacteria. A crucial step in MK biosynthesis involves the prenylation of an aromatic molecule, catalyzed by integral membrane prenyltransferases of the UbiA (4‐hydroxybenzoate oligoprenyltransferase) superfamily. In the classical MK biosynthetic pathway, the prenyltransferase responsible is MenA (1,4‐dihydroxy‐2‐naphthoate octaprenyltransferase). Recently, an alternative pathway for formation of MK, the so‐called futalosine pathway, has been described in certain micro‐organisms. Until now, five soluble enzymes (MqnA‐MqnE) have been identified in the first steps. In this study, the genes annotated as ubiA from T. thermophilus and S. lividans were cloned, expressed and investigated for prenylation activity. The integral membrane proteins possess neither UbiA nor MenA activity and represent a distinct class of prenyltransferases associated with the futalosine pathway that we term MqnP. We identify a critical residue within a highly conserved Asp‐rich motif that serves to distinguish between members of the UbiA superfamily.
Publications

Brömme, T.; Schmitz, C.; Moszner, N.; Burtscher, P.; Strehmel, N.; Strehmel, B. Photochemical Oxidation of NIR Photosensitizers in the Presence of Radical Initiators and Their Prospective Use in Dental Applications ChemistrySelect 1, 524–532, (2016) DOI: 10.1002/slct.201600048

Photochemical oxidation of near infrared (NIR) photosensitizers in the presence of diaryl iodonium salts bearing either bis(trifluoromethylsulfonyl)imide or hexafluorophosphate was investigated by exposure with NIR LEDs emitting either at 790 nm, 830 nm, 850 nm or 870 nm. Four different cyanines with barbituryl group at the meso position exhibit similar absorption in the NIR. These photosensitizers initiate in combination with diaryliodonium salts radical photopolymerization of dental composites with the focus to cure large thicknesses. Furthermore, the mixture comprising the cyanine and the iodonium salt was used to generate brown color in dental composites on demand. This required to understand the mechanism of dye decomposition in more detail applying exposure kinetics and a coupling of Ultra Performance Liquid Chromatography (UPLC) with mass spectrometry (MS) to analyze the photoproducts formed. Data showed cleavage of the polymethine chain at typical positions in case of the oxidized species. These were formed as result of electron transfer between the excited state of the photosensitizer and the iodonium salt. UPLC-MS experiments additionally indicated a certain sensitivity of the system upon adding of acids and radicals generated by thermal treatment of azobisisobutyronitrile (AIBN). Thus, treatment of the photoinitiator composition led almost to the same products no matter the system was either exposed with NIR light or treated with acids or radicals generated by thermal decomposition of AIBN. These findings helped to understand the large curing depth of 14 mm upon NIR exposure at 850 nm and the brown color formed.
Books and chapters

Hummel, J.; Strehmel, N.; Bölling, C.; Schmidt, S.; Walther D.; Kopka, J. Mass spectral search and analysis using the Golm metabolome. (Weckwerth, W.; Kahl, G.). 321-343, (2013) ISBN: 978-3-527-32777-5 DOI: 10.1002/9783527669882.ch18

The novel “omics” technologies of the postgenomic era generate large multiplexed phenotyping datasets, which can only inadequately be published in the traditional journal and supplemental formats. For this reason, public databases have been developed that utilize the efficient communication of knowledge through the World Wide Web. This trend also applies to the metabolomics field, which is, after genomics, transcriptomics, and proteomics, the fourth major systems-level phenotyping platform. Each different analytical technology used in metabolomics studies requires specific reference data for metabolite identification and optimal data formats for reporting the complex metabolite profiling data features. Therefore, we envision that every technology platform or even each high-throughput metabolomic laboratory will establish dedicated databases, which will communicate between each other and will be integrated by meta-databases and web services. The Golm Metabolome Database (GMD) (http://gmd.mpimp-golm.mpg.de/) is a metabolomic database, maintained by the Max Planck Institute of Molecular Plant Physiology, that was initiated around a nucleus of reference data from gas chromatography–mass spectrometry metabolite profiling data and is now developing toward a general mass spectrometry-based repository of reference metabolite profiles for essential plant tissues and typical variations of growth conditions. This chapter describes the mass spectral searches and analyses currently supported by the GMD. We specifically address the searches for the different chemical entities within GMD, namely the metabolites, reference substances, and the chemically derivatized analytes. We report the diverse options for mass spectral analyses and highlight the decision tree-supported prediction of chemical substructures, a feature of GMD that currently appears to be a unique among the many tools for the analysis of gas chromatography–electron ionization mass spectra.
Publications

Rasche, F.; Svatoš, A.; Maddula, R. K.; Böttcher, C.; Böcker, S. Computing Fragmentation Trees from Tandem Mass Spectrometry Data Anal Chem 83, 1243-1251, (2011) DOI: 10.1021/ac101825k

The structural elucidation of organic compounds in complex biofluids and tissues remains a significant analytical challenge. For mass spectrometry, the manual interpretation of collision-induced dissociation (CID) mass spectra is cumbersome and requires expert knowledge, as the fragmentation mechanisms of ions formed from small molecules are not completely understood. The automated identification of compounds is generally limited to searching in spectral libraries. Here, we present a method for interpreting the CID spectra of the organic compound’s protonated ions by computing fragmentation trees that establish not only the molecular formula of the compound and all fragment ions but also the dependencies between fragment ions. This is an important step toward the automated identification of unknowns from the CID spectra of compounds that are not in any database.
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