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Inducible gene expression is an important tool in molecular biology research to study protein function. Most frequently, the antibiotic doxycycline is used for regulation of so-called tetracycline (Tet)-inducible systems. In contrast to stable gene overexpression, these systems allow investigation of acute and reversible effects of cellular protein induction. Recent reports have already called for caution when using Tet-inducible systems as the employed antibiotics can disturb mitochondrial function and alter cellular metabolism by interfering with mitochondrial translation. Reprogramming of energy metabolism has lately been recognized as an important emerging hallmark of cancer and is a central focus of cancer research. Therefore, the scope of this study was to systematically analyze dose-dependent metabolic effects of doxycycline on a panel of glioma cell lines with concomitant monitoring of gene expression from Tet-inducible systems. We report that doxycycline doses commonly used with inducible expression systems (0.01–1 µg/mL) substantially alter cellular metabolism: Mitochondrial protein synthesis was inhibited accompanied by reduced oxygen and increased glucose consumption. Furthermore, doxycycline protected human glioma cells from hypoxia-induced cell death. An impairment of cell growth was only detectable with higher doxycycline doses (10 µg/mL). Our findings describe settings where doxycycline exerts effects on eukaryotic cellular metabolism, limiting the employment of Tet-inducible systems.
Linking epigenetic signature and metabolic phenotype in IDH mutant and IDH wildtype diffuse glioma
(2020)
Aims: Changes in metabolism are known to contribute to tumour phenotypes. If and how metabolic alterations in brain tumours contribute to patient outcome is still poorly understood. Epigenetics impact metabolism and mitochondrial function. The aim of this study is a characterisation of metabolic features in molecular subgroups of isocitrate dehydrogenase mutant (IDHmut) and isocitrate dehydrogenase wildtype (IDHwt) gliomas. Methods: We employed DNA methylation pattern analyses with a special focus on metabolic genes, large-scale metabolism panel immunohistochemistry (IHC), qPCR-based determination of mitochondrial DNA copy number and immune cell content using IHC and deconvolution of DNA methylation data. We analysed molecularly characterised gliomas (n = 57) for in depth DNA methylation, a cohort of primary and recurrent gliomas (n = 22) for mitochondrial copy number and validated these results in a large glioma cohort (n = 293). Finally, we investigated the potential of metabolic markers in Bevacizumab (Bev)-treated gliomas (n = 29). Results: DNA methylation patterns of metabolic genes successfully distinguished the molecular subtypes of IDHmut and IDHwt gliomas. Promoter methylation of lactate dehydrogenase A negatively correlated with protein expression and was associated with IDHmut gliomas. Mitochondrial DNA copy number was increased in IDHmut tumours and did not change in recurrent tumours. Hierarchical clustering based on metabolism panel IHC revealed distinct subclasses of IDHmut and IDHwt gliomas with an impact on patient outcome. Further quantification of these markers allowed for the prediction of survival under anti-angiogenic therapy. Conclusion: A mitochondrial signature was associated with increased survival in all analyses, which could indicate tumour subgroups with specific metabolic vulnerabilities.