Geschmack ist vorhersagbar: Mit FlavorMiner. FlavorMiner heißt das Tool, das IPB-Chemiker und Partner aus Kolumbien jüngst entwickelt haben. Das Programm kann, basierend auf maschinellem Lernen (KI), anhand der…
Seit Februar 2021 bietet Wolfgang Brandt, ehemaliger Leiter der Arbeitsgruppe Computerchemie am IPB, sein Citizen Science-Projekt zur Pilzbestimmung an. Dafür hat er in regelmäßigen Abständen öffentliche Vorträge zur Vielfalt…
Hashemi Haeri, H.; Schneegans, N.; Eisenschmidt-Bönn, D.; Brandt, W.; Wittstock, U.; Hinderberger, D.;Characterization of the active site in the thiocyanate-forming protein from Thlaspi arvense (TaTFP) using EPR spectroscopyBiol. Chem.405105-118(2024)DOI: 10.1515/hsz-2023-0187
Glucosinolates are plant thioglucosides, which act as chemical defenses. Upon tissue damage, their myrosinase-catalyzed hydrolysis yields aglucones that rearrange to toxic isothiocyanates. Specifier proteins such as thiocyanate-forming protein from Thlaspi arvense (TaTFP) are non-heme iron proteins, which capture the aglucone to form alternative products, e.g. nitriles or thiocyanates. To resolve the electronic state of the bound iron cofactor in TaTFP, we applied continuous wave electron paramagnetic resonance (CW EPR) spectroscopy at X-and Q-band frequencies (∼9.4 and ∼34 GHz). We found characteristic features of high spin and low spin states of a d5 electronic configuration and local rhombic symmetry during catalysis. We monitored the oxidation states of bound iron during conversion of allylglucosinolate by myrosinase and TaTFP in presence and absence of supplemented Fe2+. Without added Fe2+, most high spin features of bound Fe3+ were preserved, while different g’-values of the low spin part indicated slight rearrangements in the coordination sphere and/or structural geometry. We also examined involvement of the redox pair Fe3+/Fe2 in samples with supplemented Fe2+. The absence of any EPR signal related to Fe3+ or Fe2+ using an iron-binding deficient TaTFP variant allowed us to conclude that recorded EPR signals originated from the bound iron cofactor.
Publikation
Tahara, K.; Nishiguchi, M.; Funke, E.; Miyazawa, S.-I.; Miyama, T.; Milkowski, C.;Dehydroquinate dehydratase/shikimate dehydrogenases involved in gallate biosynthesis of the aluminum-tolerant tree species Eucalyptus camaldulensisPlanta2533(2021)DOI: 10.1007/s00425-020-03516-w
The tree species Eucalyptus camaldulensis shows exceptionally high tolerance against aluminum, a widespread toxic metal in acidic soils. In the roots of E. camaldulensis, aluminum is detoxified via the complexation with oenothein B, a hydrolyzable tannin. In our approach to elucidate the biosynthesis of oenothein B, we here report on the identification of E. camaldulensis enzymes that catalyze the formation of gallate, which is the phenolic constituent of hydrolyzable tannins. By systematical screening of E. camaldulensis dehydroquinate dehydratase/shikimate dehydrogenases (EcDQD/SDHs), we found two enzymes, EcDQD/SDH2 and 3, catalyzing the NADP+-dependent oxidation of 3-dehydroshikimate to produce gallate. Based on extensive in vitro assays using recombinant EcDQD/SDH2 and 3 enzymes, we present for the first time a detailed characterization of the enzymatic gallate formation activity, including the cofactor preferences, pH optima, and kinetic constants. Sequence analyses and structure modeling suggest the gallate formation activity of EcDQD/SDHs is based on the reorientation of 3-dehydroshikimate in the catalytic center, which facilitates the proton abstraction from the C5 position. Additionally, EcDQD/SDH2 and 3 maintain DQD and SDH activities, resulting in a 3-dehydroshikimate supply for gallate formation. In E. camaldulensis, EcDQD/SDH2 and 3 are co-expressed with UGT84A25a/b and UGT84A26a/b involved in hydrolyzable tannin biosynthesis. We further identified EcDQD/SDH1 as a “classical” bifunctional plant shikimate pathway enzyme and EcDQD/SDH4a/b as functional quinate dehydrogenases of the NAD+/NADH-dependent clade. Our data indicate that in E. camaldulensis the enzymes EcDQD/SDH2 and 3 provide the essential gallate for the biosynthesis of the aluminum-detoxifying metabolite oenothein B.
Publikation
Ruttkies, C.; Schymanski, E. L.; Strehmel, N.; Hollender, J.; Neumann, S.; Williams, A. J.; Krauss, M.;Supporting non-target identification by adding hydrogen deuterium exchange MS/MS capabilities to MetFragAnal. Bioanal. Chem.4114683-4700(2019)DOI: 10.1007/s00216-019-01885-0
Liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) is increasingly popular for the non-targeted exploration of complex samples, where tandem mass spectrometry (MS/MS) is used to characterize the structure of unknown compounds. However, mass spectra do not always contain sufficient information to unequivocally identify the correct structure. This study investigated how much additional information can be gained using hydrogen deuterium exchange (HDX) experiments. The exchange of “easily exchangeable” hydrogen atoms (connected to heteroatoms), with predominantly [M+D]+ ions in positive mode and [M-D]− in negative mode was observed. To enable high-throughput processing, new scoring terms were incorporated into the in silico fragmenter MetFrag. These were initially developed on small datasets and then tested on 762 compounds of environmental interest. Pairs of spectra (normal and deuterated) were found for 593 of these substances (506 positive mode, 155 negative mode spectra). The new scoring terms resulted in 29 additional correct identifications (78 vs 49) for positive mode and an increase in top 10 rankings from 80 to 106 in negative mode. Compounds with dual functionality (polar head group, long apolar tail) exhibited dramatic retention time (RT) shifts of up to several minutes, compared with an average 0.04 min RT shift. For a smaller dataset of 80 metabolites, top 10 rankings improved from 13 to 24 (positive mode, 57 spectra) and from 14 to 31 (negative mode, 63 spectra) when including HDX information. The results of standard measurements were confirmed using targets and tentatively identified surfactant species in an environmental sample collected from the river Danube near Novi Sad (Serbia). The changes to MetFrag have been integrated into the command line version available at http://c-ruttkies.github.io/MetFrag and all resulting spectra and compounds are available in online resources and in the Electronic Supplementary Material (ESM).
Publikation
Hu, M.; Müller, E.; Schymanski, E. L.; Ruttkies, C.; Schulze, T.; Brack, W.; Krauss, M.;Performance of combined fragmentation and retention prediction for the identification of organic micropollutants by LC-HRMSAnal. Bioanal. Chem.4101931-1941(2018)DOI: 10.1007/s00216-018-0857-5
In nontarget screening, structure elucidation of small molecules from high resolution mass spectrometry (HRMS) data is challenging, particularly the selection of the most likely candidate structure among the many retrieved from compound databases. Several fragmentation and retention prediction methods have been developed to improve this candidate selection. In order to evaluate their performance, we compared two in silico fragmenters (MetFrag and CFM-ID) and two retention time prediction models (based on the chromatographic hydrophobicity index (CHI) and on log D). A set of 78 known organic micropollutants was analyzed by liquid chromatography coupled to a LTQ Orbitrap HRMS with electrospray ionization (ESI) in positive and negative mode using two fragmentation techniques with different collision energies. Both fragmenters (MetFrag and CFM-ID) performed well for most compounds, with average ranking the correct candidate structure within the top 25% and 22 to 37% for ESI+ and ESI− mode, respectively. The rank of the correct candidate structure slightly improved when MetFrag and CFM-ID were combined. For unknown compounds detected in both ESI+ and ESI−, generally positive mode mass spectra were better for further structure elucidation. Both retention prediction models performed reasonably well for more hydrophobic compounds but not for early eluting hydrophilic substances. The log D prediction showed a better accuracy than the CHI model. Although the two fragmentation prediction methods are more diagnostic and sensitive for candidate selection, the inclusion of retention prediction by calculating a consensus score with optimized weighting can improve the ranking of correct candidates as compared to the individual methods.