Toward resolving the human neocortex epileptic proteome

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Montana State University - Bozeman, College of Letters & Science


Epilepsy is a common and often devastating neurological disorder, which is not well understood at the molecular level. Exactly why some brain regions produce epileptic discharges and others do not is not known. Patients who fail to respond to antiseizure medication can benefit from surgical removal of brain regions that produce epileptic activities. The tissue removed in these surgeries offers an invaluable resource to uncover the molecular and cellular basis of human epilepsy. Here, we report a proteomic study, as part of a Systems Biology of Epilepsy Project, which utilizes in vivo electrophysiologically-characterized human brain samples from the neocortex of 6 patients with refractory epilepsy, to determine whether there are common proteomic patterns in human brain regions that produce epileptic discharges. This study is unique in that comparison of protein expression was made within same patient, between nearby epileptic and non-epileptic (or less epileptic) brain regions, as defined by their interictal (between seizure) spike frequencies. Protein spots were resolved from three subcellular fractions, using two-dimensional differential-in-gel-electrophoresis, revealing 31 spots that changed significantly and were identified by liquid-chromatography tandem mass-spectrometry. Interestingly, glial fibrillary acidic protein was found to be consistently down regulated in high spiking brain tissue and glial fibrillary acidic protein levels showed strong negative correlation with spiking frequency. We next developed a two-step analysis method to select for frequently changing spots among the patients and identified 397 of those proteins. Spots of interest were clustered by protein expression patterns across all samples. This analysis predicted proteomic changes due to both histological differences and molecular pathways by examination of gene ontology clusters. Our experimental design and proteomic data analysis predicts novel glial and vascular changes and changes in cytoskeleton and neuronal projections that provide new insights into the structural and functional basis of neocortical epilepsy.




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