RESUMEN
In a Dutch non-consanguineous patient having mitochondrial encephalomyopathy with complex I and complex IV deficiency, whole exome sequencing revealed two compound heterozygous variants in SLIRP. SLIRP gene encodes a stem-loop RNA-binding protein that regulates mitochondrial RNA expression and oxidative phosphorylation (OXPHOS). A frameshift and a deep-intronic splicing variant reduced the amount of functional wild-type SLIRP RNA to 5%. Consequently, in patient fibroblasts, MT-ND1, MT-ND6, and MT-CO1 expression was reduced. Lentiviral transduction of wild-type SLIRP cDNA in patient fibroblasts increased MT-ND1, MT-ND6, and MT-CO1 expression (2.5-7.2-fold), whereas mutant cDNAs did not. A fourfold decrease of citrate synthase versus total protein ratio in patient fibroblasts indicated that the resulting reduced mitochondrial mass caused the OXPHOS deficiency. Transduction with wild-type SLIRP cDNA led to a 2.4-fold increase of this ratio and partly restored OXPHOS activity. This confirmed causality of the SLIRP variants. In conclusion, we report SLIRP variants as a novel cause of mitochondrial encephalomyopathy with OXPHOS deficiency.
Asunto(s)
Encefalomiopatías Mitocondriales/genética , Proteínas de Unión al ARN/genética , Células Cultivadas , Niño , Complejo I de Transporte de Electrón/metabolismo , Complejo IV de Transporte de Electrones/metabolismo , Fibroblastos/metabolismo , Genes Recesivos , Humanos , Masculino , Encefalomiopatías Mitocondriales/patología , Mutación , Proteínas de Unión al ARN/metabolismoRESUMEN
The variety of available mitochondrial quantification tools makes it difficult to select the most reliable and accurate quantification tool. Here, we performed elaborate analyses on five open source ImageJ tools. Excessive clustering of mitochondrial structures was observed in four tools, caused by the global thresholding applied by these tools. The Mitochondrial Analyzer, which uses adaptive thresholding, outperformed the other examined tools, with accurate structural segregation and identification. Additionally, we showed that the Mitochondrial Analyzer successfully identifies mitochondrial morphology differences. Based on the observed performance, we consider the Mitochondrial Analyzer the best open source tool for mitochondrial network morphology quantification.