TY - JOUR A1 - Arlt, Wiebke A1 - Biehl, Michael A1 - Taylor, Angela E. A1 - Hahner, Stefanie A1 - Libé, Rossella A1 - Hughes, Beverly A. A1 - Schneider, Petra A1 - Smith, David J. A1 - Stiekema, Han A1 - Krone, Nils A1 - Porfiri, Emilio A1 - Opocher, Giuseppe A1 - Bertherat, Jerôme A1 - Mantero, Franco A1 - Allolio, Bruno A1 - Terzolo, Massimo A1 - Nightingale, Peter A1 - Shackleton, Cedric H. L. A1 - Bertagna, Xavier A1 - Fassnacht, Martin A1 - Stewart, Paul M. T1 - Urine Steroid Metabolomics as a Biomarker Tool for Detecting Malignancy in Adrenal Tumors JF - The Journal of Clinical Endocrinology & Metabolism N2 - Context: Adrenal tumors have a prevalence of around 2% in the general population. Adrenocortical carcinoma (ACC) is rare but accounts for 2–11% of incidentally discovered adrenal masses. Differentiating ACC from adrenocortical adenoma (ACA) represents a diagnostic challenge in patients with adrenal incidentalomas, with tumor size, imaging, and even histology all providing unsatisfactory predictive values. Objective: Here we developed a novel steroid metabolomic approach, mass spectrometry-based steroid profiling followed by machine learning analysis, and examined its diagnostic value for the detection of adrenal malignancy. Design: Quantification of 32 distinct adrenal derived steroids was carried out by gas chromatography/mass spectrometry in 24-h urine samples from 102 ACA patients (age range 19–84 yr) and 45 ACC patients (20–80 yr). Underlying diagnosis was ascertained by histology and metastasis in ACC and by clinical follow-up [median duration 52 (range 26–201) months] without evidence of metastasis in ACA. Steroid excretion data were subjected to generalized matrix learning vector quantization (GMLVQ) to identify the most discriminative steroids. Results: Steroid profiling revealed a pattern of predominantly immature, early-stage steroidogenesis in ACC. GMLVQ analysis identified a subset of nine steroids that performed best in differentiating ACA from ACC. Receiver-operating characteristics analysis of GMLVQ results demonstrated sensitivity = specificity = 90% (area under the curve = 0.97) employing all 32 steroids and sensitivity = specificity = 88% (area under the curve = 0.96) when using only the nine most differentiating markers. Conclusions: Urine steroid metabolomics is a novel, highly sensitive, and specific biomarker tool for discriminating benign from malignant adrenal tumors, with obvious promise for the diagnostic work-up of patients with adrenal incidentalomas. KW - adrenal cortex hormones KW - urine KW - adrenal cortex neoplasms KW - mass spectrometry KW - metabolomics Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-154682 VL - 96 IS - 12 SP - 3775 EP - 3784 ER - TY - JOUR A1 - Reel, Smarti A1 - Reel, Parminder S. A1 - Erlic, Zoran A1 - Amar, Laurence A1 - Pecori, Alessio A1 - Larsen, Casper K. A1 - Tetti, Martina A1 - Pamporaki, Christina A1 - Prehn, Cornelia A1 - Adamski, Jerzy A1 - Prejbisz, Aleksander A1 - Ceccato, Filippo A1 - Scaroni, Carla A1 - Kroiss, Matthias A1 - Dennedy, Michael C. A1 - Deinum, Jaap A1 - Eisenhofer, Graeme A1 - Langton, Katharina A1 - Mulatero, Paolo A1 - Reincke, Martin A1 - Rossi, Gian Paolo A1 - Lenzini, Livia A1 - Davies, Eleanor A1 - Gimenez-Roqueplo, Anne-Paule A1 - Assié, Guillaume A1 - Blanchard, Anne A1 - Zennaro, Maria-Christina A1 - Beuschlein, Felix A1 - Jefferson, Emily R. T1 - Predicting hypertension subtypes with machine learning using targeted metabolites and their ratios JF - Metabolites N2 - Hypertension is a major global health problem with high prevalence and complex associated health risks. Primary hypertension (PHT) is most common and the reasons behind primary hypertension are largely unknown. Endocrine hypertension (EHT) is another complex form of hypertension with an estimated prevalence varying from 3 to 20% depending on the population studied. It occurs due to underlying conditions associated with hormonal excess mainly related to adrenal tumours and sub-categorised: primary aldosteronism (PA), Cushing’s syndrome (CS), pheochromocytoma or functional paraganglioma (PPGL). Endocrine hypertension is often misdiagnosed as primary hypertension, causing delays in treatment for the underlying condition, reduced quality of life, and costly antihypertensive treatment that is often ineffective. This study systematically used targeted metabolomics and high-throughput machine learning methods to predict the key biomarkers in classifying and distinguishing the various subtypes of endocrine and primary hypertension. The trained models successfully classified CS from PHT and EHT from PHT with 92% specificity on the test set. The most prominent targeted metabolites and metabolite ratios for hypertension identification for different disease comparisons were C18:1, C18:2, and Orn/Arg. Sex was identified as an important feature in CS vs. PHT classification. KW - metabolomics KW - machine learning KW - hypertension KW - primary aldosteronism KW - pheochromocytoma/paraganglioma KW - Cushing syndrome KW - biomarkers Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-286161 SN - 2218-1989 VL - 12 IS - 8 ER - TY - JOUR A1 - Bliziotis, Nikolaos G. A1 - Kluijtmans, Leo A. J. A1 - Tinnevelt, Gerjen H. A1 - Reel, Parminder A1 - Reel, Smarti A1 - Langton, Katharina A1 - Robledo, Mercedes A1 - Pamporaki, Christina A1 - Pecori, Alessio A1 - Van Kralingen, Josie A1 - Tetti, Martina A1 - Engelke, Udo F. H. A1 - Erlic, Zoran A1 - Engel, Jasper A1 - Deutschbein, Timo A1 - Nölting, Svenja A1 - Prejbisz, Aleksander A1 - Richter, Susan A1 - Adamski, Jerzy A1 - Januszewicz, Andrzej A1 - Ceccato, Filippo A1 - Scaroni, Carla A1 - Dennedy, Michael C. A1 - Williams, Tracy A. A1 - Lenzini, Livia A1 - Gimenez-Roqueplo, Anne-Paule A1 - Davies, Eleanor A1 - Fassnacht, Martin A1 - Remde, Hanna A1 - Eisenhofer, Graeme A1 - Beuschlein, Felix A1 - Kroiss, Matthias A1 - Jefferson, Emily A1 - Zennaro, Maria-Christina A1 - Wevers, Ron A. A1 - Jansen, Jeroen J. A1 - Deinum, Jaap A1 - Timmers, Henri J. L. M. T1 - Preanalytical pitfalls in untargeted plasma nuclear magnetic resonance metabolomics of endocrine hypertension JF - Metabolites N2 - Despite considerable morbidity and mortality, numerous cases of endocrine hypertension (EHT) forms, including primary aldosteronism (PA), pheochromocytoma and functional paraganglioma (PPGL), and Cushing’s syndrome (CS), remain undetected. We aimed to establish signatures for the different forms of EHT, investigate potentially confounding effects and establish unbiased disease biomarkers. Plasma samples were obtained from 13 biobanks across seven countries and analyzed using untargeted NMR metabolomics. We compared unstratified samples of 106 PHT patients to 231 EHT patients, including 104 PA, 94 PPGL and 33 CS patients. Spectra were subjected to a multivariate statistical comparison of PHT to EHT forms and the associated signatures were obtained. Three approaches were applied to investigate and correct confounding effects. Though we found signatures that could separate PHT from EHT forms, there were also key similarities with the signatures of sample center of origin and sample age. The study design restricted the applicability of the corrections employed. With the samples that were available, no biomarkers for PHT vs. EHT could be identified. The complexity of the confounding effects, evidenced by their robustness to correction approaches, highlighted the need for a consensus on how to deal with variabilities probably attributed to preanalytical factors in retrospective, multicenter metabolomics studies. KW - confounders KW - metabolomics KW - multicenter KW - plasma NMR KW - preanalytical conditions Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-282930 SN - 2218-1989 VL - 12 IS - 8 ER - TY - JOUR A1 - Bohnert, Simone A1 - Reinert, Christoph A1 - Trella, Stefanie A1 - Schmitz, Werner A1 - Ondruschka, Benjamin A1 - Bohnert, Michael T1 - Metabolomics in postmortem cerebrospinal fluid diagnostics: a state-of-the-art method to interpret central nervous system–related pathological processes JF - International Journal of Legal Medicine N2 - In the last few years, quantitative analysis of metabolites in body fluids using LC/MS has become an established method in laboratory medicine and toxicology. By preparing metabolite profiles in biological specimens, we are able to understand pathophysiological mechanisms at the biochemical and thus the functional level. An innovative investigative method, which has not yet been used widely in the forensic context, is to use the clinical application of metabolomics. In a metabolomic analysis of 41 samples of postmortem cerebrospinal fluid (CSF) samples divided into cohorts of four different causes of death, namely, cardiovascular fatalities, isoIated torso trauma, traumatic brain injury, and multi-organ failure, we were able to identify relevant differences in the metabolite profile between these individual groups. According to this preliminary assessment, we assume that information on biochemical processes is not gained by differences in the concentration of individual metabolites in CSF, but by a combination of differently distributed metabolites forming the perspective of a new generation of biomarkers for diagnosing (fatal) TBI and associated neuropathological changes in the CNS using CSF samples. KW - CSF KW - cerebrospinal fluid KW - forensic neuropathology KW - forensic neurotraumatology KW - biomarker KW - metabolomics Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-235724 SN - 0937-9827 VL - 135 ER - TY - JOUR A1 - Macintyre, Lynsey A1 - Zhang, Tong A1 - Viegelmann, Christina A1 - Martinez, Ignacio Juarez A1 - Cheng, Cheng A1 - Dowdells, Catherine A1 - Abdelmohsen, Usama Ramadan A1 - Gernert, Christine A1 - Hentschel, Ute A1 - Edrada-Ebel, RuAngelie T1 - Metabolomic Tools for Secondary Metabolite Discovery from Marine Microbial Symbionts JF - Marine Drugs N2 - Marine invertebrate-associated symbiotic bacteria produce a plethora of novel secondary metabolites which may be structurally unique with interesting pharmacological properties. Selection of strains usually relies on literature searching, genetic screening and bioactivity results, often without considering the chemical novelty and abundance of secondary metabolites being produced by the microorganism until the time-consuming bioassay-guided isolation stages. To fast track the selection process, metabolomic tools were used to aid strain selection by investigating differences in the chemical profiles of 77 bacterial extracts isolated from cold water marine invertebrates from Orkney, Scotland using liquid chromatography-high resolution mass spectrometry (LC-HRMS) and nuclear magnetic resonance (NMR) spectroscopy. Following mass spectrometric analysis and dereplication using an Excel macro developed in-house, principal component analysis (PCA) was employed to differentiate the bacterial strains based on their chemical profiles. NMR H-1 and correlation spectroscopy (COSY) were also employed to obtain a chemical fingerprint of each bacterial strain and to confirm the presence of functional groups and spin systems. These results were then combined with taxonomic identification and bioassay screening data to identify three bacterial strains, namely Bacillus sp. 4117, Rhodococcus sp. ZS402 and Vibrio splendidus strain LGP32, to prioritize for scale-up based on their chemically interesting secondary metabolomes, established through dereplication and interesting bioactivities, determined from bioassay screening. KW - multivariate analysis KW - metabolic profiling KW - metabolomics KW - dereplication KW - symbiotic bacteria KW - mass spectrometry KW - NMR KW - sponge holicolona-simulans KW - bryozoan bugula-neritina KW - polyketide synthase gene Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-116097 SN - 1660-3397 VL - 12 IS - 6 ER - TY - THES A1 - Rikanovic, Carina T1 - Metabolomanalytik antiinfektiv wirkender Isochinolinalkaloide T1 - Metabolome analysis of antiinfectiv isoquinoline alkaloids N2 - Die zunehmende Entstehung von Resistenzen macht die Entwicklung neuer potenter Wirkstoffe zur Therapie von Infektionskrankheiten immer wichtiger. Dieser Aufgabe stellt sich auch der interdisziplinär aufgebaute SFB 630, in den sich die vorliegende Arbeit eingliedert. Innerhalb des SFBs wurden Isochinolinalkaloid-Derivate (IQs) synthetisiert, die aktiv gegen verschiedene Mikroorganismen sind. Bioinformatische Modellierungen bilden die für den jeweiligen Mikroorganismus spezifischen Stoffwechselwege ab. In Netzwerkanalysen können Änderungen metabolischer Flüsse durch pharmakologisch aktive Substanzen vorhergesagt werden. Gemeinsam mit bioinformatischen Modellen liefern die Metabolommessungen Hinweise auf mögliche Wirkmechanismen. Im Rahmen der vorliegenden Arbeit wurden verschiedene analytische Methoden etabliert, um antiinfektive Wirkungen dieser verheißungsvollen Leitstrukturen auf das Metabolom verschiedener Mikroorganismen zu untersuchen. Die aus den Metabolommessungen erhaltenen Daten fließen in diese Modelle ein und tragen zu deren Optimierung bei. Die Mikroorganismen wurden für die Metabolomanalysen mit aktiven IQs (für S. aureus und C. albicans GB-AP-143, für L. major GB-AP-304) inkubiert. Bei C. albicans erfolgte die Probennahme zu unterschiedlichen Zeitpunkten (lag-, log-, stationäre Phase), um auch die Zeitabhängigkeit der Effekte zu untersuchen. Zusätzlich dienten bei C. albicans als Kontrollen neben parallel angesetzten Zellkulturen ohne Inhibitor, auch Zellkulturen, denen das Lösungsmittel DMSO zugegeben wurde. Es wurden Extraktionsmethoden für die betreffenden Metabolite der hier untersuchten Mikroorganismen (S. aureus, C. albicans, L. major) etabliert. Dabei lag der Fokus auf polaren Metaboliten, da bioinformatische Modellierungen für die Effekte der IQs Änderungen vor allem im Purin- und Pyrimidinstoffwechsel der Mikroorganismen vorhersagten. Zur Analyse des Nukleotidstoffwechsels wurde eine ionenpaarchromatographische HPLC-Methode entwickelt und optimiert. Mit dieser Methode konnten Nicotinamidderivate und Nukleotide des Purin- und Pyrimidinstoffwechsels in Zellextrakten von S. aureus, C. albicans und L. major quantifiziert werden. Für eine Analyse des Wirkmechanismus von GB-AP-143 wurde die Zusammensetzung des Metaboloms von C. albicans mittels einer GC/MS-Methode bestimmt. Nach einer Derivatisierung des Extrakts mit Methoxyamin-HCl und MSTFA konnten in einem Lauf zugleich Target- und Fingerprintanalytik durchgeführt werden. Die Auswertung der Targetanalytik fand unter Anwendung der NIST-Datenbank und Vermessung von Standards statt. Hierbei konnten vor allem Aminosäuren quantitativ erfasst werden. Der Fingerprint wurde durch Einsatz multivariater statistischer Verfahren ausgewertet. Die Daten für die mit GB AP 143 behandelten S. aureus und die mit GB AP 304 behandelten L. major-Promastigoten liefern Hinweise auf eine Wirkung der IQs auf den Komplex-I der mitochondrialen Atmungskette. Für die Behandlung der C. albicans-Kulturen mit GB-AP-143 konnten komplexe Änderungen im Nukleotid- und Aminosäurestoffwechsel gemessen werden. So beeinflusste bereits der Zeitpunkt der Probennahme (lag-, log- oder stationäre Wachstumsphase) die Zusammensetzung des Metaboloms und auch das Lösungsmittel, das für die IQs verwendet wurde, verursachte komplexe Änderungen im Metabolom von C. albicans. Zusätzlich wurden Nukleotid- und Aminosäurekonzentrationen Fluconazol-resistenter C. albicans-Mutanten (TAC, UPC und MRR) untersucht. Im Nukleotidstoffwechsel waren sowohl Konzentrationssteigerungen als auch ein Absinken der Konzentrationen im Vergleich zum Wildtyp zu verzeichnen. Der Aminosäurestoffwechsel zeigte insgesamt einen verminderten Gehalt an Aminosäuren der Mutanten gegenüber dem Wildtyp. Da GB-AP-143 auch Aktivität gegen diese Mutanten zeigte, wurde exemplarisch die MRR-Mutante mit GB-AP-143 inkubiert, um zu untersuchen, ob die durch GB-AP-143 hervorgerufenen Änderungen im Nukleotid- und Aminosäurestoffwechsel ähnlich zu denen des Wildtyps sind. Es konnten im Nukleotidstoffwechsel gegenläufige Effekte für die Inkubation von GB-AP-143 des Wildtyps und der Mutante verzeichnet werden. Die Daten aus den HPLC/UV- und GC/MS-Messungen werden von der Bioinformatik zur Optimierung der verwendeten Modelle genutzt, um auf diese Weise die Wirkmechanismen der IQs besser modellieren zu können. Da das Cytochrom-P-450-Enzymsystem am Metabolismus von etwa 95 % aller Arzneistoffe beteiligt ist, wurden die Effekte ausgewählter IQs auf die sechs wichtigsten arzneistoffmetabolisierenden Enzyme (CYP1A2, 2C8, 2C9, 2C19, 2D6 und 3A4) mit Hilfe eines bereits etablierten CYP-Assays analysiert und näher charakterisiert. Im CYP-Assay zeigte sich für drei IQs eine CYP2D6-Hemmung. Die ausgeprägte CYP2D6-selektive Hemmung von GB-AP-110 ergab einen IC50-Wert von nur 109 nM. Die Charakterisierung der Hemmung ergab einen reversiblen, kompetitiven Inhibitionsmechanismus. N2 - The increasing frequency of resistance towards antibiotics in the therapy of infectious diseases highlights the importance of the development of novel drugs against infectious diseases. This work is integrated in the Collaboration Research Center 630 (SFB 630), which has been formed to search for innovative solutions by joint interdisciplinary approaches. In the framework of this SFB, some new isoquinoline alkaloid derivatives (IQs) could be synthesized, which show distinct activities against various microorganisms. The present work focussed on the development of different analytical methods in order to determine the antiinfective properties of these promising lead structures on the level of the metabolome of different microorganisms. Metabolome measurements together with bioinformatic models provide information about the possible mode of action. By using bioinformatic models one can predict changes in metabolic fluxes caused by pharmacologically active substances. The integration of data from metabolic measurements can optimize the predictive power of these models. For these measurements the microorganisms were incubated with the active IQs (GB-AP-143 for S. aureus and C. albicans, GB-AP-304 for L. major). In the case of C. albicans sampling was carried out at different time points (lag-, log and stationary growth stage) in order to examine the time dependence. In addition cell cultures without inhibitor and with the addition of the solvent DMSO were used as controls for C. albicans. Initially, extraction methods for the respective metabolites of the microorganisms S. aureus, C. albicans and L. major were established. Since bioinformatic models predicted alterations especially in the purine and pyrimidine metabolism of these microorganisms as a consequence of treatment with IQs, priority was put on the extraction of polar compounds. To analyze the nucleotide metabolism an ion pair chromatography method was developed and optimized. By means of this method nicotinamide derivatives and nucleotides of the purine and pyrimidine metabolisms could be quantified in cell extracts of S. aureus, C. albicans and L. major. For a more holistic analysis of GB-AP-143´s effect on the composition of the C. albicans metabolome a GC/MS-method was developed. After a derivatisation step of the cell extract by using methoxyamine hydrochloride and MSTFA target and fingerprint analysis were conducted simultaneously. Target analysis was conducted by means of the NIST database and measuring reference standards. Particularly, amino acids could be quantified. Fingerprint analysis was interpreted using multivariate statistics. A detailed biological interpretation of metabolome data was not the focus of this study, because the main goal was the method development. However, data of S. aureus and L. major treated with the IQs gave hints towards an effect of the IQs on complex I of mitochondrial respiration. For the treatment of C. albicans with GB-AP-143 a complex alteration of the metabolites has been detected: already the time of sampling and the solvent, which was applied for GB-AP-143, have an impact on metabolome pattern of C. albicans. Additionally, the nucleotide and amino acid concentrations of fluconazol-resistant C. albicans mutants (TAC; UPC and MRR) have been investigated. Nucleotides showed increased as well as decreased concentrations compared to the C. albicans wild type. The overall concentration of amino acids was decreased in the mutants. Since GB-AP-143 also showed activity against these resistant mutants, exemplarily the MRR-mutant was incubated with this compound in order to determine, whether the effect of GB-AP-143 on the nucleotide and amino acid metabolism in the wild type also occurs in the mutant. Nucleotide metabolism showed antidromic effects for the incubation of wild type and mutant for GB-AP-143. This indicates that the metabolism of the mutant, which differs from the wild type already without treatment, also reacts differently on GB-AP-143-incubation. Data from HPLC/UV- and GC/MS-analysis are used by the bioinformatics to optimize the developed models in order to develop improved models for the mode of action of IQs. Since cytochrome-P-450-enzymes are involved in the metabolism of about 95 % of all drugs, the effects of selected IQs on the six main drug processing enzymes (CYP1A2, 2C8, 2C9, 2C19, 2D6 and 3A4) were investigated. Therefore, a previously developed and well-established in vitro test system was used. Three of the tested IQs showed an inhibition of CYP2D6. The distinct CYP2D6-selective inhibition of GB-AP-110 showed an IC50 value as low as 109 nM. The accurate characterization revealed a reversible and competitive mode of inhibition. KW - Metabolom KW - GC-MS KW - Isochinolinalkaloide KW - Ionenpaarchromatographie KW - Cytochrom P-450 KW - metabolomics KW - GC-MS KW - ion-pair chromatography KW - cytochrome-P-450 Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-56183 ER - TY - THES A1 - Cecil, Alexander [geb. Schmid] T1 - Metabolische Netzwerkanalysen für den Weg von xenobiotischen zu verträglichen antibiotischen Substanzen T1 - Metabolic network analysis for the path from xenobiotic to compliant antibiotic substances N2 - Durch das Auftreten neuer Stämme resistenter Krankheitserreger ist die Suche nach neuartigen Wirkstoffen gegen diese, sich ständig weiter ausbreitende Bedrohung, dringend notwendig. Der interdisziplinäre Sonderforschungsbereich 630 der Universität Würzburg stellt sich dieser Aufgabe, indem hier neuartige Xenobiotika synthetisiert und auf ihre Wirksamkeit getestet werden. Die hier vorgelegte Dissertation fügt sich hierbei nahtlos in die verschiedenen Fachbereiche des SFB630 ein: Sie stellt eine Schnittstelle zwischen Synthese und Analyse der Effekte der im Rahmen des SFB630 synthetisierten Isochinolinalkaloid-Derivaten. Mit den hier angewandten bioinformatischen Methoden wurden zunächst die wichtigsten Stoffwechselwege von S. epidermidis R62A, S. aureus USA300 und menschlicher Zellen in sogenannten metabolischen Netzwerkmodellen nachgestellt. Basierend auf diesen Modellen konnten Enzymaktivitäten für verschiedene Szenarien an zugesetzten Xenobiotika berechnet werden. Die hierfür benötigten Daten wurden direkt aus Genexpressionsanalysen gewonnen. Die Validierung dieser Methode erfolgte durch Metabolommessungen. Hierfür wurde S. aureus USA300 mit verschiedenen Konzentrationen von IQ-143 behandelt und gemäß dem in dieser Dissertation vorgelegten Ernteprotokoll aufgearbeitet. Die Ergebnisse hieraus lassen darauf schließen, dass IQ-143 starke Effekte auf den Komplex 1 der Atmungskette ausübt – diese Resultate decken sich mit denen der metabolischen Netzwerkanalyse. Für den Wirkstoff IQ-238 ergaben sich trotz der strukturellen Ähnlichkeiten zu IQ-143 deutlich verschiedene Wirkeffekte: Dieser Stoff verursacht einen direkten Abfall der Enzymaktivitäten in der Glykolyse. Dadurch konnte eine unspezifische Toxizität dieser Stoffe basierend auf ihrer chemischen Struktur ausgeschlossen werden. Weiterhin konnten die bereits für IQ-143 und IQ-238 auf Bakterien angewandten Methoden erfolgreich zur Modellierung der Effekte von Methylenblau auf verschiedene resistente Stämme von P. falciparum 3D7 angewandt werden. Dadurch konnte gezeigt werden, dass Methylenblau in einer Kombination mit anderen Präparaten gegen diesen Parasiten zum einen die Wirkung des Primärpräparates verstärkt, zum anderen aber auch in gewissem Maße vorhandene Resistenzen gegen das Primärpräparat zu verringern vermag. Somit konnte durch die vorgelegte Arbeit eine Pipeline zur Identifizierung der metabolischen Effekte verschiedener Wirkstoffe auf unterschiedliche Krankheitserreger erstellt werden. Diese Pipeline kann jederzeit auf andere Organismen ausgeweitet werden und stellt somit einen wichtigen Ansatz um Netzwerkeffekte verschiedener, potentieller Medikamente aufzuklären. N2 - With the emergence of new strains of resistant pathogens, the search for new compounds against this spreading threat is of utmost importance. The interdisciplinary special research field SFB630 of the University of Würzburg is ready to tackle this task by synthesizing and analysing the effects of xenobiotics. The presented dissertation is seamlessly integrated into the diverse range of special fields of the SFB630: it provides a gateway between synthesis and analysis of the effects of the newly synthesized isoquinoline alkaloid derivatives. The presented bioinformatic methods were used to build a so called metabolic network model of the most important pathways of S. epidermidis RP62A, S. aureus USA300 and human cells. Based on these models it was possible to calculate the enzyme activities for different scenarios of added xenobiotics. The data needed for these calculations were derived directly from gene expression analysis. Validation of this method was done by metabolomic measurements. In order to accomplish this, a strain of S. aureus USA300 was subjected to different concentrations of IQ-143 and processed according to the workflow also published in this dissertation. The results suggest that IQ-143 has very strong effects on the complex 1 of the oxidative phosphorylation – these results are consistent with the results obtained by the metabolic network analysis. Although IQ-238 is structurally a close relative to IQ-143, the effects of this compound are very different: it leads to a drop of the enzyme activities in the glycolysis. Therefore an unspecific toxicity of those compounds based on their chemical structure dould be ruled out. The methods used to model the effects of IQ-143 and IQ-238 on bacteria were furthermore successfully transferred to model the effects of methylene blue on several resistant strains of P. falciparum 3D7. It was shown that a combination of methylene blue and other malaria medications either enhances the effects of the primary medication, or – in the case of a resistant strain – methylene blue was able to mitigate the resistances against the primary medication. The presented dissertation was thus successfully able to build a pipeline to identify the metabolic effects of different compounds on various germs. This pipeline can be expanded to other organisms at any time and therefore yields an important approach to identify network effects of various potential drugs. KW - Stoffwechsel KW - Bioinformatik KW - Mathematisches Modell KW - Enzymaktivität KW - Xenobiotikum KW - Netzwerkanalyse KW - Bioinformatik KW - Metabolische Stoffwechselmodellierung KW - Metabolomik KW - Metabonomik KW - Network analysis KW - Bioinformatics KW - metabolic pathway modeling KW - metabolomics KW - metabonomics Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-71866 ER - TY - JOUR A1 - Koderer, Corinna A1 - Schmitz, Werner A1 - Wünsch, Anna Chiara A1 - Balint, Julia A1 - El-Mesery, Mohamed A1 - Volland, Julian Manuel A1 - Hartmann, Stefan A1 - Linz, Christian A1 - Kübler, Alexander Christian A1 - Seher, Axel T1 - Low energy status under methionine restriction is essentially independent of proliferation or cell contact inhibition JF - Cells N2 - Nonlimited proliferation is one of the most striking features of neoplastic cells. The basis of cell division is the sufficient presence of mass (amino acids) and energy (ATP and NADH). A sophisticated intracellular network permanently measures the mass and energy levels. Thus, in vivo restrictions in the form of amino acid, protein, or caloric restrictions strongly affect absolute lifespan and age-associated diseases such as cancer. The induction of permanent low energy metabolism (LEM) is essential in this process. The murine cell line L929 responds to methionine restriction (MetR) for a short time period with LEM at the metabolic level defined by a characteristic fingerprint consisting of the molecules acetoacetate, creatine, spermidine, GSSG, UDP-glucose, pantothenate, and ATP. Here, we used mass spectrometry (LC/MS) to investigate the influence of proliferation and contact inhibition on the energy status of cells. Interestingly, the energy status was essentially independent of proliferation or contact inhibition. LC/MS analyses showed that in full medium, the cells maintain active and energetic metabolism for optional proliferation. In contrast, MetR induced LEM independently of proliferation or contact inhibition. These results are important for cell behaviour under MetR and for the optional application of restrictions in cancer therapy. KW - methionine restriction KW - caloric restriction KW - mass spectrometry KW - LC/MS KW - liquid chromatography/mass spectrometry KW - metabolomics KW - L929 KW - amino acid KW - proliferation KW - contact inhibition Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-262329 SN - 2073-4409 VL - 11 IS - 3 ER - TY - JOUR A1 - Schäbler, Stefan A1 - Amatobi, Kelechi M. A1 - Horn, Melanie A1 - Rieger, Dirk A1 - Helfrich‑Förster, Charlotte A1 - Mueller, Martin J. A1 - Wegener, Christian A1 - Fekete, Agnes T1 - Loss of function in the Drosophila clock gene period results in altered intermediary lipid metabolism and increased susceptibility to starvation JF - Cellular and Molecular Life Sciences N2 - The fruit fly Drosophila is a prime model in circadian research, but still little is known about its circadian regulation of metabolism. Daily rhythmicity in levels of several metabolites has been found, but knowledge about hydrophobic metabolites is limited. We here compared metabolite levels including lipids between period\(^{01}\) (per\(^{01}\)) clock mutants and Canton-S wildtype (WT\(_{CS}\)) flies in an isogenic and non-isogenic background using LC–MS. In the non-isogenic background, metabo-lites with differing levels comprised essential amino acids, kynurenines, pterinates, glycero(phospho)lipids, and fatty acid esters. Notably, detectable diacylglycerols (DAG) and acylcarnitines (AC), involved in lipid metabolism, showed lower levels in per\(^{01}\) mutants. Most of these differences disappeared in the isogenic background, yet the level differences for AC as well as DAG were consistent for fly bodies. AC levels were dependent on the time of day in WTCS in phase with food consumption under LD conditions, while DAGs showed weak daily oscillations. Two short-chain ACs continued to cycle even in constant darkness. per\(^{01}\) mutants in LD showed no or very weak diel AC oscillations out of phase with feeding activity. The low levels of DAGs and ACs in per\(^{01}\) did not correlate with lower total food consumption, body mass or weight. Clock mutant flies showed higher sensitivity to starvation independent of their background-dependent activity level. Our results suggest that neither feeding, energy storage nor mobilisation is significantly affected in per\(^{01}\) mutants, but point towards impaired mitochondrial activity, supported by upregulation of the mitochondrial stress marker 4EBP in the clock mutants KW - circadian rhythms KW - metabolomics KW - mitochondrial activity KW - tryptophan KW - acylcarnitine KW - feeding Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-232432 SN - 1420-682X VL - 77 ER - TY - THES A1 - Wagner, Silvia T1 - Identifizierung von Biomarkern mittels LC-MS-basiertem Metabonomics - Merkaptursäuren als Indikatoren für die Bildung toxischer Intermediate T1 - Identification of biomarkers via LC-MS-based metabonomics – mercapturic acids as indicators for the formation of toxic intermediates N2 - Metabonomics bildet das Ende der Omics-Kaskade und stellt eine top-down-Strategie zur Erfassung und Interpretation des Metaboloms, d. h. der Gesamtheit aller niedermolekularen Metaboliten in einem intakten Organismus, dar. Ziel der Technik ist es, mittels geeigneter ungerichteter Screeningverfahren in nicht-invasiv zu gewinnenden biologischen Proben wie Urin oder Blut charakteristische Metabolitenprofile zu bestimmen. Im Kontext des Metabonomics wurde in Anlehnung an den Geno- bzw. Phänotyp hierfür der Begriff „Metabotyp“ geprägt. Durch biostatistische Methoden, die auf Mustererkennung (pattern recognition) basieren, können Signaturen gegenübergestellt und auf diesem Weg gruppenspezifische Metaboliten, d. h. Biomarker bzw. Metabolitenmuster, extrahiert werden. Metabonomics kann folglich als Fusion klassischer bioanalytischer und biostatistischer Verfahren aufgefasst werden. Seit der Einführung im Jahr 1999 hat sich das Konzept des Metabonomics in mehrere Richtungen weiterentwickelt. So gab es Bestrebungen, die Technik, die ursprünglich zur Prädiktion von toxischen Effekten bei der Arzneistoffentwicklung etabliert wurde, auf Fragestellungen zu übertragen, die den Menschen im Mittelpunkt haben. Neben präklinischen Anwendungen verfolgt man mit Metabonomics zunehmend das Ziel, einer personalisierten Medizin und Ernährung einen Schritt näher zu kommen. Da sich die ursprünglich eingesetzte NMR-Technik als zu unempfindlich und die resultierenden Metabolitenprofile als zu anfällig gegenüber biologischen und analytischen Einflussgrößen (Confoundern) erwiesen haben, wurde parallel auf sensitivere Verfahren wie die Massenspektrometrie gesetzt. Insbesondere die Kopplung mit der Hochdruckflüssigchromatographie erwies sich hierbei für das Metabolitenscreening als geeignet. Schnell wurde allerdings klar, dass aus den klassischen full scan/TOF-Methoden Datensätze resultierten, die häufig zu komplex waren, um mit nachgeschalteten chemometrischen Verfahren die „Spreu vom Weizen trennen“ zu können. Da sich Metabolitendatenbanken bisher noch im Aufbau befinden, ist die Identifizierung der Marker mit zusätzlichen Schwierigkeiten verbunden und bedarf aufwändiger analytischer Verfahren. Eine Strategie stellt daher die Beschränkung auf ein Metabolitensubset dar. Indem man sich auf Metabolitenklassen fokussiert, die einen Bezug zum untersuchten Mechanismus haben, können die Erfolgsaussichten bei der Identifizierung charakteristischer Biomarker deutlich erhöht werden. Aufgrund zahlreicher exogener und endogener Faktoren (Arzneistoffe, Industriechemikalien, Nahrungsbestandteile, Tabakrauchbestandteile, Produkte der Lipidperoxidation etc.) ist der menschliche Organismus stets einer Vielzahl an elektrophilen Verbindungen ausgesetzt. Oxidative Schädigungen an Strukturen wie der DNA, Proteinen und Lipiden werden mit einer Reihe von Krankheitsbildern in Zusammenhang gebracht, darunter Parkinson, Alzheimer, Krebs und Volkskrankheiten wie Arteriosklerose, Allergien und koronare Herzerkrankungen. Mit dem Glutathionsystem verfügt der Körper über einen wirksamen Detoxifizierungsmechanismus. Das Tripeptid Glutathion reagiert als Nukleophil mit den exogen oder endogen gebildeten elektrophilen Intermediaten. Endprodukte sind Merkaptursäuren (N-Acetyl-L-Cystein-Addukte) bzw. deren Sulfoxide, die in erster Linie mit dem Urin ausgeschieden werden. Folglich besteht zwischen diesen Merkaptursäurederivaten und der elektrophilen Belastung eines Organismus ein direkter Zusammenhang. Vor diesem Hintergrund war es das Ziel der Arbeit, einen nicht-invasiven Metabonomicsansatz zur Anwendung am Menschen zu entwickeln. Durch die Fokussierung des Metabolitenscreenings auf die Effekt-, Dosis- und Suszeptibilitätsmarkerklasse der Merkaptursäuren sollten hierbei die Erfolgsaussichten im Hinblick auf die Identifizierung potentieller Biomarker für diverse toxikologische sowie medizinische Endpunkte erhöht werden. N2 - Metabonomics forms the end of the omics-cascade and represents a top-down strategy for the interpretation of the metabolome, i. e. all the low molecular weight metabolites in an intact organism. The aim of the approach is to analyse characteristic metabolite profiles by suitable untargeted screening methods in biological samples like urine or blood that can be obtained in a non-invasive manner. In the context of metabonomics, the term “metabotype” was defined according to the geno- and phenotype, respectively. Biostatistical methods based on pattern recognition techniques allow comparing metabolic signatures and extracting group specific metabolites and biomarkers. Therefore, metabonomics can be regarded as the fusion of bioanalytical and biostatistical techniques. Since its introduction in 1999, the concept of metabonomics has permanently gained importance in many fields of scientific research. One aim was to transfer the methodology, which was originally established to predict toxic effects in drug development processes, to human issues. Apart from preclinical questions, metabonomics is increasingly applied in the area of personalised medicine and nutrition. As the NMR technique used by pioneers of the field was too insensitive and the resulting metabolite profiles were too susceptible to biological and analytical confounders, more sensitive techniques like mass spectrometry were more and more applied. Especially mass spectrometry in combination with high performance liquid chromatography showed great promise for the screening of metabolites. However, after a very short time, it was clear that the data sets resulting from full scan/TOF-methods were too complex to “separate the wheat from the chaff” with chemometric procedures. Metabolite databases are still under construction, and therefore marker identification is challenging and requires complex analytical techniques. Thus, one strategy is to concentrate on a certain metabolite subset. The focus on a metabolite class with a close relation to the mechanism under investigation can considerably increase the prospects of success in the biomarker identification process. Due to a variety of exogenous and endogenous factors (drugs, industrial chemicals, food ingredients, and tobacco smoke) the human organism is steadily confronted with a multitude of electrophilic compounds. Oxidative damage of the DNA, proteins, and lipids is associated with the development of diseases like Parkinson’s, Alzheimer’s, cancer and widespread diseases like arteriosclerosis, allergies and coronary heart diseases. With the glutathione system the human organism is equipped with an efficient detoxification mechanism. The tripeptide glutathione reacts as nucleophile with exogenously and endogenously formed electrophilic intermediates. End products are mercapturic acids (N-acetyl-L-cysteine-adducts) and respective sulfoxides that are predominantly excreted with urine. Therefore, there is a close relationship between these mercapturic acid patterns and the electrophilic burden of an organism. In this context, the aim of this thesis was to develop a non-invasive human metabonomics approach that focuses the metabolite screening on the effect, dose and susceptibility marker class of the mercapturic acids. Thus, the prospects of success regarding the identification of potential biomarkers for various toxicological and pathological endpoints should be increased. KW - Metabolom KW - Biomarker KW - Datenanalyse KW - Paracetamol KW - Validierung KW - Tetrachlormethan KW - Raucher KW - Tabakrauch KW - Zigarettenrauch KW - Biostatistik KW - Chemometrie KW - Hauptkomponentenanalyse KW - Methode der partiellen kleinsten Quadrate KW - Diskriminanzanalyse KW - Fl KW - Merkaptursäuren KW - Metabonomics KW - Metabolomics KW - Expositionsmarker KW - mercapturic acids KW - metabonomics KW - metabolomics KW - markers of exposure Y1 - 2008 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-35760 ER -