| 1. |
- Sandbaumhüter, Friederike A., et al.
(author)
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Enantioselective CE–MS analysis of ketamine metabolites in urine
- 2023
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In: Electrophoresis. - : Wiley-VCH Verlagsgesellschaft. - 0173-0835 .- 1522-2683. ; 44:1-2, s. 125-134
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Journal article (peer-reviewed)abstract
- The chiral drug ketamine has long-lasting antidepressant effects with a fast onset and is also suitable to treat patients with therapy-resistant depression. The metabolite hydroxynorketamine (HNK) plays an important role in the antidepressant mechanism of action. Hydroxylation at the cyclohexanone ring occurs at positions 4, 5, and 6 and produces a total of 12 stereoisomers. Among those, the four 6HNK stereoisomers have the strongest antidepressant effects. Capillary electrophoresis with highly sulfated γ-cyclodextrin (CD) as a chiral selector in combination with mass spectrometry (MS) was used to develop a method for the enantioselective analysis of HNK stereoisomers with a special focus on the 6HNK stereoisomers. The partial filling approach was applied in order to avoid contamination of the MS with the chiral selector. Concentration of the chiral selector and the length of the separation zone were optimized. With 5% highly sulfated γ-CD in 20 mM ammonium formate with 10% formic acid and a 75% filling the four 6HNK stereoisomers could be separated with a resolution between 0.79 and 3.17. The method was applied to analyze fractionated equine urine collected after a ketamine infusion and to screen the fractions as well as unfractionated urine for the parent drug ketamine and other metabolites, including norketamine and dehydronorketamine.
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| 2. |
- Sandbaumhuter, Friederike A., et al.
(author)
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Label-Free Quantitative Thermal Proteome Profiling Reveals Target Transcription Factors with Activities Modulated by MC3R Signaling
- 2023
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In: Analytical Chemistry. - : American Chemical Society (ACS). - 0003-2700 .- 1520-6882. ; 95:41, s. 15400-15408
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Journal article (peer-reviewed)abstract
- Thermal proteome profiling with label-free quantitation using ion-mobility-enhanced LC-MS offers versatile data sets, providing information on protein differential expression, thermal stability, and the activities of transcription factors. We developed a multidimensional data analysis workflow for label-free quantitative thermal proteome profiling (TPP) experiments that incorporates the aspects of gene set enrichment analysis, differential protein expression analysis, and inference of transcription factor activities from LC-MS data. We applied it to study the signaling processes downstream of melanocortin 3 receptor (MC3R) activation by endogenous agonists derived from the proopiomelanocortin prohormone: ACTH, alpha-MSH, and gamma-MSH. The obtained information was used to map signaling pathways downstream of MC3R and to deduce transcription factors responsible for cellular response to ligand treatment. Using our workflow, we identified differentially expressed proteins and investigated their thermal stability. We found in total 298 proteins with altered thermal stability, resulting from MC3R activation. Out of these, several proteins were transcription factors, indicating them as being downstream target regulators that take part in the MC3R signaling cascade. We found transcription factors CCAR2, DDX21, HMGB2, SRSF7, and TET2 to have altered thermal stability. These apparent target transcription factors within the MC3R signaling cascade play important roles in immune responses. Additionally, we inferred the activities of the transcription factors identified in our data set. This was done with Bayesian statistics using the differential expression data we obtained with label-free quantitative LC-MS. The inferred transcription factor activities were validated in our bioinformatic pipeline by the phosphorylated peptide abundances that we observed, highlighting the importance of post-translational modifications in transcription factor regulation. Our multidimensional data analysis workflow allows for a comprehensive characterization of the signaling processes downstream of MC3R activation. It provides insights into protein differential expression, thermal stability, and activities of key transcription factors. All proteomic data generated in this study are publicly available at DOI: 10.6019/PXD039945.
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