Exclusive neuronal expression of SUCLA2 in the human brain

SUCLA2 encodes the ATP-forming subunit (A-SUCL-) of succinyl-CoA ligase, an enzyme of the citric acid cycle. Mutations in SUCLA2 lead to a mitochondrial disorder manifesting as encephalomyopathy with dystonia, deafness and lesions in the basal ganglia. Despite the distinct brain pathology associated with SUCLA2 mutations, the precise localization of SUCLA2 protein has never been investigated. Here we show that immunoreactivity of A-SUCL- in surgical human cortical tissue samples was present exclusively in neurons, identified by their morphology and visualized by double labeling with a fluorescent Nissl dye. A-SUCL- immunoreactivity co-localized >99% with that of the d subunit of the mitochondrial F0-F1 ATP synthase. Specificity of the anti-A-SUCL- antiserum was verified by the absence of labeling in fibroblasts from a patient with a complete deletion of SUCLA2. A-SUCL- immunoreactivity was absent in glial cells, identified by antibodies directed against the glial markers GFAP and S100. Furthermore, in situ hybridization histochemistry demonstrated that SUCLA2 mRNA was present in Nissl-labeled neurons but not glial cells labeled with S100. Immunoreactivity of the GTP-forming subunit (G-SUCL-) encoded by SUCLG2, or in situ hybridization histochemistry for SUCLG2 mRNA could not be demonstrated in either neurons or astrocytes. Western blotting of post mortem brain samples revealed minor G-SUCL- immunoreactivity that was however, not upregulated in samples obtained from diabetic versus non-diabetic patients, as has been described for murine brain. Our work establishes that SUCLA2 is expressed exclusively in neurons in the human cerebral cortex

Improving the iMM904 S. cerevisiae metabolic model using essentiality and synthetic lethality data

<p>Abstract</p> <p>Background</p> <p><it>Saccharomyces cerevisiae </it>is the first eukaryotic organism for which a multi-compartment genome-scale metabolic model was constructed. Since then a sequence of improved metabolic reconstructions for yeast has been introduced. These metabolic models have been extensively used to elucidate the organizational principles of yeast metabolism and drive yeast strain engineering strategies for targeted overproductions. They have also served as a starting point and a benchmark for the reconstruction of genome-scale metabolic models for other eukaryotic organisms. In spite of the successive improvements in the details of the described metabolic processes, even the recent yeast model (i.e., <it>i</it>MM904) remains significantly less predictive than the latest <it>E. coli </it>model (i.e., <it>i</it>AF1260). This is manifested by its significantly lower specificity in predicting the outcome of grow/no grow experiments in comparison to the <it>E. coli </it>model.</p> <p>Results</p> <p>In this paper we make use of the automated GrowMatch procedure for restoring consistency with single gene deletion experiments in yeast and extend the procedure to make use of synthetic lethality data using the genome-scale model <it>i</it>MM904 as a basis. We identified and vetted using literature sources 120 distinct model modifications including various regulatory constraints for minimal and YP media. The incorporation of the suggested modifications led to a substantial increase in the fraction of correctly predicted lethal knockouts (i.e., specificity) from 38.84% (87 out of 224) to 53.57% (120 out of 224) for the minimal medium and from 24.73% (45 out of 182) to 40.11% (73 out of 182) for the YP medium. Synthetic lethality predictions improved from 12.03% (16 out of 133) to 23.31% (31 out of 133) for the minimal medium and from 6.96% (8 out of 115) to 13.04% (15 out of 115) for the YP medium.</p> <p>Conclusions</p> <p>Overall, this study provides a roadmap for the computationally driven correction of multi-compartment genome-scale metabolic models and demonstrates the value of synthetic lethals as curation agents.</p

Global Transcription Analysis of Krebs Tricarboxylic Acid Cycle Mutants Reveals an Alternating Pattern of Gene Expression and Effects on Hypoxic and Oxidative Genes

To understand the many roles of the Krebs tricarboxylic acid (TCA) cycle in cell function, we used DNA microarrays to examine gene expression in response to TCA cycle dysfunction. mRNA was analyzed from yeast strains harboring defects in each of 15 genes that encode subunits of the eight TCA cycle enzymes. The expression of >400 genes changed at least threefold in response to TCA cycle dysfunction. Many genes displayed a common response to TCA cycle dysfunction indicative of a shift away from oxidative metabolism. Another set of genes displayed a pairwise, alternating pattern of expression in response to contiguous TCA cycle enzyme defects: expression was elevated in aconitase and isocitrate dehydrogenase mutants, diminished in α-ketoglutarate dehydrogenase and succinyl-CoA ligase mutants, elevated again in succinate dehydrogenase and fumarase mutants, and diminished again in malate dehydrogenase and citrate synthase mutants. This pattern correlated with previously defined TCA cycle growth–enhancing mutations and suggested a novel metabolic signaling pathway monitoring TCA cycle function. Expression of hypoxic/anaerobic genes was elevated in α-ketoglutarate dehydrogenase mutants, whereas expression of oxidative genes was diminished, consistent with a heme signaling defect caused by inadequate levels of the heme precursor, succinyl-CoA. These studies have revealed extensive responses to changes in TCA cycle function and have uncovered new and unexpected metabolic networks that are wired into the TCA cycle