Functional Inactivation of Drosophila GCK Orthologs Causes Genomic Instability and Oxidative Stress in a Fly Model of MODY-2

Maturity-onset diabetes of the young (MODY) type 2 is caused by heterozygous inactivating mutations in the gene encoding glucokinase (GCK), a pivotal enzyme for glucose homeostasis. In the pancreas GCK regulates insulin secretion, while in the liver it promotes glucose utilization and storage. We showed that silencing the Drosophila GCK orthologs Hex-A and Hex-C results in a MODY-2-like hyperglycemia. Targeted knock-down revealed that Hex-A is expressed in insulin producing cells (IPCs) whereas Hex-C is specifically expressed in the fat body. We showed that Hex-A is essential for insulin secretion and it is required for Hex-C expression. Reduced levels of either Hex-A or Hex-C resulted in chromosome aberrations (CABs), together with an increased production of advanced glycation end-products (AGEs) and reactive oxygen species (ROS). This result suggests that CABs, in GCK depleted cells, are likely due to hyperglycemia, which produces oxidative stress through AGE metabolism. In agreement with this hypothesis, treating GCK-depleted larvae with the antioxidant vitamin B6 rescued CABs, whereas the treatment with a B6 inhibitor enhanced genomic instability. Although MODY-2 rarely produces complications, our data revealed the possibility that MODY-2 impacts genome integrity.     

Evolution on neutral networks accelerates the ticking rate of the molecular clock

Large sets of genotypes give rise to the same phenotype, because phenotypic expression is highly redundant. Accordingly, a population can accept mutations without altering its phenotype, as long as the genotype mutates into another one on the same set. By linking every pair of genotypes that are mutually accessible through mutation, genotypes organize themselves into neutral networks (NNs). These networks are known to be heterogeneous and assortative, and these properties affect the evolutionary dynamics of the population. By studying the dynamics of populations on NNs with arbitrary topology, we analyse the effect of assortativity, of NN (phenotype) fitness and of network size. We find that the probability that the population leaves the network is smaller the longer the time spent on it. This progressive ‘phenotypic entrapment’ entails a systematic increase in the overdispersion of the process with time and an acceleration in the fixation rate of neutral mutations. We also quantify the variation of these effects with the size of the phenotype and with its fitness relative to that of neighbouring alternatives.     

Generation of Rho Zero Cells: Visualization and Quantification of the mtDNA Depletion Process

Human mitochondrial DNA (mtDNA) is located in discrete DNA-protein complexes, so called nucleoids. These structures can be easily visualized in living cells by utilizing the fluorescent stain PicoGreen^®. In contrary, cells devoid of endogenous mitochondrial genomes (ρ⁰ cells) display no mitochondrial staining in the cytoplasm. A modified restriction enzyme can be targeted to mitochondria to cleave the mtDNA molecules in more than two fragments, thereby activating endogenous nucleases. By applying this novel enzymatic approach to generate mtDNA-depleted cells the destruction of mitochondrial nucleoids in cultured cells could be detected in a time course. It is clear from these experiments that mtDNA-depleted cells can be seen as early as 48 h post-transfection using the depletion system. To prove that mtDNA is degraded during this process, mtDNA of transfected cells was quantified by real-time PCR. A significant decline could be observed 24 h post-transfection. Combination of both results showed that mtDNA of transfected cells is completely degraded and, therefore, ρ⁰ cells were generated within 48 h. Thus, the application of a mitochondrially-targeted restriction endonuclease proves to be a first and fast, but essential step towards a therapy for mtDNA disorders.     

Metabolomic Profiling of Plasma from Melioidosis Patients Using UHPLC-QTOF MS Reveals Novel Biomarkers for Diagnosis

To identify potential biomarkers for improving diagnosis of melioidosis, we compared plasma metabolome profiles of melioidosis patients compared to patients with other bacteremia and controls without active infection, using ultra-high-performance liquid chromatography-electrospray ionization-quadruple time-of-flight mass spectrometry. Principal component analysis (PCA) showed that the metabolomic profiles of melioidosis patients are distinguishable from bacteremia patients and controls. Using multivariate and univariate analysis, 12 significant metabolites from four lipid classes, acylcarnitine (n = 6), lysophosphatidylethanolamine (LysoPE) (n = 3), sphingomyelins (SM) (n = 2) and phosphatidylcholine (PC) (n = 1), with significantly higher levels in melioidosis patients than bacteremia patients and controls, were identified. Ten of the 12 metabolites showed area-under-receiver operating characteristic curve (AUC) >0.80 when compared both between melioidosis and bacteremia patients, and between melioidosis patients and controls. SM(d18:2/16:0) possessed the largest AUC when compared, both between melioidosis and bacteremia patients (AUC 0.998, sensitivity 100% and specificity 91.7%), and between melioidosis patients and controls (AUC 1.000, sensitivity 96.7% and specificity 100%). Our results indicate that metabolome profiling might serve as a promising approach for diagnosis of melioidosis using patient plasma, with SM(d18:2/16:0) representing a potential biomarker. Since the 12 metabolites were related to various pathways for energy and lipid metabolism, further studies may reveal their possible role in the pathogenesis and host response in melioidosis.