TY  - JOUR
A1  - Kotthoff, Lisa
A1  - Lisec, Jan
A1  - Schwerdtle, Tanja
A1  - Koch, Matthias
T1  - Prediction of transformation products of monensin by electrochemistry compared to microsomal assay and hydrolysis
JF  - Molecules
N2  - The knowledge of transformation pathways and identification of transformation products (TPs) of veterinary drugs is important for animal health, food, and environmental matters. The active agent Monensin (MON) belongs to the ionophore antibiotics and is widely used as a veterinary drug against coccidiosis in broiler farming. However, no electrochemically (EC) generated TPs of MON have been described so far. In this study, the online coupling of EC and mass spectrometry (MS) was used for the generation of oxidative TPs. EC-conditions were optimized with respect to working electrode material, solvent, modifier, and potential polarity. Subsequent LC/HRMS (liquid chromatography/high resolution mass spectrometry) and MS/MS experiments were performed to identify the structures of derived TPs by a suspected target analysis. The obtained EC-results were compared to TPs observed in metabolism tests with microsomes and hydrolysis experiments of MON. Five previously undescribed TPs of MON were identified in our EC/MS based study and one TP, which was already known from literature and found by a microsomal assay, could be confirmed. Two and three further TPs were found as products in microsomal tests and following hydrolysis, respectively. We found decarboxylation, O-demethylation and acid-catalyzed ring-opening reactions to be the major mechanisms of MON transformation.
KW  - transformation products
KW  - monensin
KW  - veterinary drugs
KW  - electrochemistry
KW  - hydrolysis
KW  - LC/HRMS
Y1  - 2019
U6  - https://doi.org/10.3390/molecules24152732
SN  - 1420-3049
VL  - 24
IS  - 15
PB  - MDPI
CY  - Basel
ER  - 
TY  - JOUR
A1  - Steinfath, Matthias
A1  - Gärtner, Tanja
A1  - Lisec, Jan
A1  - Meyer, Rhonda Christiane
A1  - Altmann, Thomas
A1  - Willmitzer, Lothar
A1  - Selbig, Joachim
T1  - Prediction of hybrid biomass in Arabidopsis thaliana by selected parental SNP and metabolic markers
JF  - Theoretical and applied genetics : TAG ; international journal of plant breeding research
N2  - A recombinant inbred line (RIL) population, derived from two Arabidopsis thaliana accessions, and the corresponding testcrosses with these two original accessions were used for the development and validation of machine learning models to predict the biomass of hybrids. Genetic and metabolic information of the RILs served as predictors. Feature selection reduced the number of variables (genetic and metabolic markers) in the models by more than 80% without impairing the predictive power. Thus, potential biomarkers have been revealed. Metabolites were shown to bear information on inherited macroscopic phenotypes. This proof of concept could be interesting for breeders. The example population exhibits substantial mid-parent biomass heterosis. The results of feature selection could therefore be used to shed light on the origin of heterosis. In this respect, mainly dominance effects were detected.
KW  - Quantitative Trait Locus
KW  - feature selection
KW  - Partial Little Square
KW  - recombinant inbred line
KW  - Quantitative Trait Locus analysis
Y1  - 2009
U6  - https://doi.org/10.1007/s00122-009-1191-2
SN  - 0040-5752
SN  - 1432-2242
VL  - 120
SP  - 239
EP  - 247
PB  - Springer
CY  - Berlin
ER  -