Screening for Active Small Molecules in Mitochondrial Complex I Deficient Patient's Fibroblasts, Reveals AICAR as the Most Beneficial Compound

Congenital deficiency of the mitochondrial respiratory chain complex I (CI) is a common defect of oxidative phosphorylation (OXPHOS). Despite major advances in the biochemical and molecular diagnostics and the deciphering of CI structure, function assembly and pathomechanism, there is currently no satisfactory cure for patients with mitochondrial complex I defects. Small molecules provide one feasible therapeutic option, however their use has not been systematically evaluated using a standardized experimental system. In order to evaluate potentially therapeutic compounds, we set up a relatively simple system measuring different parameters using only a small amount of patient's fibroblasts, in glucose free medium, where growth is highly OXPOS dependent. Ten different compounds were screened using fibroblasts derived from seven CI patients, harboring different mutations

Genetic Networks of Liver Metabolism Revealed by Integration of Metabolic and Transcriptional Profiling

Although numerous quantitative trait loci (QTL) influencing disease-related phenotypes have been detected through gene mapping and positional cloning, identification of the individual gene(s) and molecular pathways leading to those phenotypes is often elusive. One way to improve understanding of genetic architecture is to classify phenotypes in greater depth by including transcriptional and metabolic profiling. In the current study, we have generated and analyzed mRNA expression and metabolic profiles in liver samples obtained in an F2 intercross between the diabetes-resistant C57BL/6 leptinob/ob and the diabetes-susceptible BTBR leptinob/ob mouse strains. This cross, which segregates for genotype and physiological traits, was previously used to identify several diabetes-related QTL. Our current investigation includes microarray analysis of over 40,000 probe sets, plus quantitative mass spectrometry-based measurements of sixty-seven intermediary metabolites in three different classes (amino acids, organic acids, and acyl-carnitines). We show that liver metabolites map to distinct genetic regions, thereby indicating that tissue metabolites are heritable. We also demonstrate that genomic analysis can be integrated with liver mRNA expression and metabolite profiling data to construct causal networks for control of specific metabolic processes in liver. As a proof of principle of the practical significance of this integrative approach, we illustrate the construction of a specific causal network that links gene expression and metabolic changes in the context of glutamate metabolism, and demonstrate its validity by showing that genes in the network respond to changes in glutamine and glutamate availability. Thus, the methods described here have the potential to reveal regulatory networks that contribute to chronic, complex, and highly prevalent diseases and conditions such as obesity and diabetes