Insights into the Mechanism of Human Deiodinase 1.

The three isoenzymes of iodothyronine deiodinases (DIO1-3) are membrane-anchored homo-dimeric selenoproteins which share the thioredoxin-fold structure. Several questions regarding their catalytic mechanisms still remain open. Here, we addressed the roles of several cysteines which are conserved among deiodinase isoenzymes and asked whether they may contribute to dimerization and reduction of the oxidized enzyme with physiological reductants. We also asked whether amino acids previously identified in DIO3 play the same role in DIO1. Human DIO1 and 2 were recombinantly expressed in insect cells with selenocysteine replaced with cysteine (DIO1U126C) or in COS7 cells as selenoprotein. Enzyme activities were studied by radioactive deiodination assays with physiological reducing agents and recombinant proteins were characterized by mass spectrometry. Mutation of Cys124 in DIO1 prevented reduction by glutathione, while 20 mM dithiothreitol still regenerated the enzyme. Protein thiol reductants, thioredoxin and glutaredoxin, did not reduce DIO1U126C. Mass spectrometry demonstrated the formation of an intracellular disulfide between the side-chains of Cys124 and Cys(Sec)126. We conclude that the proximal Cys124 forms a selenenyl-sulfide with the catalytic Sec126 during catalysis, which is the substrate of the physiological reductant glutathione. Mutagenesis studies support the idea of a proton-relay pathway from solvent to substrate that is shared between DIO1 and DIO3.

Association between MGMT Enhancer Methylation and MGMT Promoter Methylation, MGMT Protein Expression, and Overall Survival in Glioblastoma.

The repair protein O6-methylguanine-DNA methyltransferase (MGMT) is regulated epigenetically, mainly by the methylation of the MGMT promoter. MGMT promoter methylation status has emerged as a prognostic and predictive biomarker for patients with newly diagnosed glioblastoma (GBM). However, a strong negative correlation between MGMT promoter methylation and MGMT protein expression cannot be applied as a rule for all GBM patients. In order to investigate if the DNA methylation status of MGMT enhancers is associated with MGMT promoter methylation, MGMT expression, and the overall survival (OS) of GBM patients, we established assays based on high-resolution melting analysis and pyrosequencing for one intragenic and three intergenic MGMT enhancers. For CpGs in an enhancer located 560 kb upstream of the MGMT promoter, we found a significant negative correlation between the methylation status and MGMT protein levels of GBM samples expressing MGMT. The methylation status of CpGs in the intragenic enhancer (hs696) was strongly negatively correlated with MGMT promoter methylation and was significantly higher in MGMT-expressing GBM samples than in MGMT-non-expressing GBM samples. Moreover, low methylation of CpGs 01-03 and CpGs 09-13 was associated with the longer OS of the GBM patients. Our findings indicate an association between MGMT enhancer methylation and MGMT promoter methylation, MGMT protein expression, and/or OS.

Association of MGMT Promoter and Enhancer Methylation with Genetic Variants, Clinical Parameters, and Demographic Characteristics in Glioblastoma.

The response of glioblastoma (GBM) patients to the alkylating agent temozolomide (TMZ) vitally depends on the expression level of the repair protein O6-methylguanine-DNA methyltransferase (MGMT). Since MGMT is strongly regulated by promoter methylation, the methylation status of the MGMT promoter has emerged as a prognostic and predictive biomarker for GBM patients. By determining the methylation levels of the four enhancers located within or close to the MGMT gene, we recently found that enhancer methylation contributes to MGMT regulation. In this study, we investigated if methylation of the four enhancers is associated with SNP rs16906252, TERT promoter mutations C228T and C250T, TERT SNP rs2853669, proliferation index Ki-67, overall survival (OS), age, and sex of the patients. In general, associations with genetic variants, clinical parameters, and demographic characteristics were caused by a complex interplay of multiple CpGs in the MGMT promoter and of multiple CpGs in enhancer regions. The observed associations for intragenic enhancer 4, located in intron 2 of MGMT, differed from associations observed for the three intergenic enhancers. Some findings were restricted to subgroups of samples with either methylated or unmethylated MGMT promoters, underpinning the relevance of the MGMT promoter status in GBMs.

Development of a fed-batch process for the production of the cytochrome P450 monooxygenase CYP102A1 from Bacillus megaterium in E. coli.

A fed-batch process utilizing a pET-based expression system (pET28a+ derivative) and E. coli BL21(DE3) as production strain for the heterologous expression of recombinant cytochrome P450 monooxygenase CYP102A1 from Bacillus megaterium was developed. In a first step the expression was optimized during a series of flask experiments testing several parameters for their influence on the expression level, activity and solubility of the recombinant protein. The optimal process parameters found in the flask experiments were transferred to a cultivation process in a 5l (operating volume) bioreactor with a special focus on the feeding strategy and the aeration during expression. Glycerol feeding proved to be superior over glucose as carbon source since the formation of larger amounts of acetate was prevented. Expression levels exceeding 12,500nmoll(-1), corresponding to approximately 1.5gl(-1) of product in culture medium ( approximately 11% of CDW) could be demonstrated. The P450 enzyme showed high activity and high solubility. The findings now can be transferred to other enzyme variants and different P450 monooxygenases to increase production of recombinant proteins.

Metabolomics: current state and evolving methodologies and tools.

In recent years, metabolomics developed to an accepted and valuable tool in life sciences. Substantial improvements of analytical hardware allow metabolomics to run routinely now. Data are successfully used to investigate genotype-phenotype relations of strains and mutants. Metabolomics facilitates metabolic engineering to optimise mircoorganisms for white biotechnology and spreads to the investigation of biotransformations and cell culture. Metabolomics serves not only as a source of qualitative but also quantitative data of intra-cellular metabolites essential for the model-based description of the metabolic network operating under in vivo conditions. To collect reliable metabolome data sets, culture and sampling conditions, as well as the cells' metabolic state, are crucial. Hence, application of biochemical engineering principles and method standardisation efforts become important. Together with the other more established omics technologies, metabolomics will strengthen its claim to contribute to the detailed understanding of the in vivo function of gene products, biochemical and regulatory networks and, even more ambitious, the mathematical description and simulation of the whole cell in the systems biology approach. This knowledge will allow the construction of designer organisms for process application using biotransformation and fermentative approaches making effective use of single enzymes, whole microbial and even higher cells.