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- ItemMetabolic Profiling of Thymic Epithelial Tumors Hints to a Strong Warburg Effect, Glutaminolysis and Precarious Redox Homeostasis as Potential Therapeutic Targets(Basel : MDPI, 2022) Alwahsh, Mohammad; Knitsch, Robert; Marchan, Rosemarie; Lambert, Jörg; Hoerner, Christian; Zhang, Xiaonan; Schalke, Berthold; Lee, De-Hyung; Bulut, Elena; Graeter, Thomas; Ott, German; Kurz, Katrin S.; Preissler, Gerhard; Schölch, Sebastian; Farhat, Joviana; Yao, Zhihan; Sticht, Carsten; Ströbel, Philipp; Hergenröder, Roland; Marx, Alexander; Belharazem, DjedaThymomas and thymic carcinomas (TC) are malignant thymic epithelial tumors (TETs) with poor outcome, if non-resectable. Metabolic signatures of TETs have not yet been studied and may offer new therapeutic options. Metabolic profiles of snap-frozen thymomas (WHO types A, AB, B1, B2, B3, n = 12) and TCs (n = 3) were determined by high resolution magic angle spinning 1H nuclear magnetic resonance (HRMAS 1H-NMR) spectroscopy. Metabolite-based prediction of active KEGG metabolic pathways was achieved with MetPA. In relation to metabolite-based metabolic pathways, gene expression signatures of TETs (n = 115) were investigated in the public “The Cancer Genome Atlas” (TCGA) dataset using gene set enrichment analysis. Overall, thirty-seven metabolites were quantified in TETs, including acetylcholine that was not previously detected in other nonendocrine cancers. Metabolite-based cluster analysis distinguished clinically indolent (A, AB, B1) and aggressive TETs (B2, B3, TCs). Using MetPA, six KEGG metabolic pathways were predicted to be activated, including proline/arginine, glycolysis and glutathione pathways. The activated pathways as predicted by metabolite-profiling were generally enriched transcriptionally in the independent TCGA dataset. Shared high lactic acid and glutamine levels, together with associated gene expression signatures suggested a strong “Warburg effect”, glutaminolysis and redox homeostasis as potential vulnerabilities that need validation in a large, independent cohort of aggressive TETs. If confirmed, targeting metabolic pathways may eventually prove as adjunct therapeutic options in TETs, since the metabolic features identified here are known to confer resistance to cisplatin-based chemotherapy, kinase inhibitors and immune checkpoint blockers, i.e., currently used therapies for non-resectable TETs.
- ItemCharacterization and prediction of the mechanism of action of antibiotics through NMR metabolomics(London : BioMed Central, 2016) Hoerr, Verena; Duggan, Gavin E.; Zbytnuik, Lori; Poon, Karen K.H.; Große, Christina; Neugebauer, Ute; Methling, Karen; Löffler, Bettina; Vogel, Hans J.Background: The emergence of antibiotic resistant pathogenic bacteria has reduced our ability to combat infectious diseases. At the same time the numbers of new antibiotics reaching the market have decreased. This situation has created an urgent need to discover novel antibiotic scaffolds. Recently, the application of pattern recognition techniques to identify molecular fingerprints in ‘omics’ studies, has emerged as an important tool in biomedical research and laboratory medicine to identify pathogens, to monitor therapeutic treatments or to develop drugs with improved metabolic stability, toxicological profile and efficacy. Here, we hypothesize that a combination of metabolic intracellular fingerprints and extracellular footprints would provide a more comprehensive picture about the mechanism of action of novel antibiotics in drug discovery programs. Results: In an attempt to integrate the metabolomics approach as a classification tool in the drug discovery processes, we have used quantitative 1H NMR spectroscopy to study the metabolic response of Escherichia coli cultures to different antibiotics. Within the frame of our study the effects of five different and well-known antibiotic classes on the bacterial metabolome were investigated both by intracellular fingerprint and extracellular footprint analysis. The metabolic fingerprints and footprints of bacterial cultures were affected in a distinct manner and provided complementary information regarding intracellular and extracellular targets such as protein synthesis, DNA and cell wall. While cell cultures affected by antibiotics that act on intracellular targets showed class-specific fingerprints, the metabolic footprints differed significantly only when antibiotics that target the cell wall were applied. In addition, using a training set of E. coli fingerprints extracted after treatment with different antibiotic classes, the mode of action of streptomycin, tetracycline and carbenicillin could be correctly predicted. Conclusion: The metabolic profiles of E. coli treated with antibiotics with intracellular and extracellular targets could be separated in fingerprint and footprint analysis, respectively and provided complementary information. Based on the specific fingerprints obtained for different classes of antibiotics, the mode of action of several antibiotics could be predicted. The same classification approach should be applicable to studies of other pathogenic bacteria.
- ItemChemical fingerprints of cold physical plasmas – an experimental and computational study using cysteine as tracer compound([London] : Macmillan Publishers Limited, part of Springer Nature, 2018-5-16) Lackmann, J.-W.; Wende, K.; Verlackt, C.; Golda, J.; Volzke, J.; Kogelheide, F.; Held, J.; Bekeschus, S.; Bogaerts, A.; Schulz-von der Gathen, V.; Stapelmann, K.Reactive oxygen and nitrogen species released by cold physical plasma are being proposed as effectors in various clinical conditions connected to inflammatory processes. As these plasmas can be tailored in a wide range, models to compare and control their biochemical footprint are desired to infer on the molecular mechanisms underlying the observed effects and to enable the discrimination between different plasma sources. Here, an improved model to trace short-lived reactive species is presented. Using FTIR, high-resolution mass spectrometry, and molecular dynamics computational simulation, covalent modifications of cysteine treated with different plasmas were deciphered and the respective product pattern used to generate a fingerprint of each plasma source. Such, our experimental model allows a fast and reliable grading of the chemical potential of plasmas used for medical purposes. Major reaction products were identified to be cysteine sulfonic acid, cystine, and cysteine fragments. Less-abundant products, such as oxidized cystine derivatives or S-nitrosylated cysteines, were unique to different plasma sources or operating conditions. The data collected point at hydroxyl radicals, atomic O, and singlet oxygen as major contributing species that enable an impact on cellular thiol groups when applying cold plasma in vitro or in vivo.