Rat model of MTLE: Animals with epilepsy vs animals without epilepsy (codelink)

Neither the molecular basis of the pathologic tendency of neuronal circuits to generate spontaneous seizures (epileptogenicity) nor anti-epileptogenic mechanisms that maintain a seizure-free state are well understood. Here, we performed transcriptomic analysis in the intrahippocampal kainate model of temporal lobe epilepsy in rats using both Agilent and Codelink microarray platforms to characterize the epileptic processes. The experimental design allowed subtraction of the confounding effects of the lesion, identification of expression changes associated with epileptogenicity, and genes upregulated by seizures with potential homeostatic anti-epileptogenic effects. Using differential expression analysis, we identified several hundred expression changes in chronic epilepsy, including candidate genes associated with epileptogenicity such as Bdnf and Kcnj13. To analyze these data from a systems perspective, we applied weighted gene co-expression network analysis (WGCNA) to identify groups of co-expressed genes (modules) and their central (hub) genes. One such module contained genes upregulated in the epileptogenic region, including multiple epileptogenicity candidate genes, and was found to be involved the protection of glial cells against oxidative stress, implicating glial oxidative stress in epileptogenicity. Another distinct module corresponded to the effects of chronic seizures and represented changes in neuronal synaptic vesicle trafficking. We found that the network structure and connectivity of one hub gene, Sv2a, showed significant changes between normal and epileptogenic tissue, becoming more highly connected in epileptic brain. Since Sv2a is a target of the antiepileptic levetiracetam, this module may be important in controlling seizure activity. Bioinformatic analysis of this module also revealed a potential mechanism for the observed transcriptional changes via generation of longer alternatively polyadenlyated transcripts through the upregulation of the RNA binding protein HuD. In summary, combining conventional statistical methods and network analysis allowed us to interpret the differentially regulated genes from a systems perspective, yielding new insight into several biological pathways underlying homeostatic anti-epileptogenic effects and epileptogenicity.目前，神经环路自发产生痫性发作的病理倾向（致痫性，epileptogenicity）的分子基础，以及维持无痫性发作状态的抗致痫机制，均尚未得到充分阐明。在此，我们针对大鼠颞叶癫痫的海马内红藻氨酸模型，采用安捷伦（Agilent）与Codelink两款微阵列平台开展转录组分析，以刻画癫痫发作相关的病理过程。本实验设计可排除病灶所致的混杂效应，鉴定与致痫性相关的基因表达变化，以及经痫性发作上调、具有潜在稳态抗致痫作用的基因。通过差异表达分析，我们在慢性癫痫样本中鉴定出数百个存在表达差异的基因，包括Bdnf与Kcnj13等与致痫性相关的候选基因。为从系统生物学视角解析这些数据，我们应用加权基因共表达网络分析（weighted gene co-expression network analysis, WGCNA），以鉴定共表达基因簇（模块）及其核心（枢纽）基因。其中一个模块包含在致痫脑区上调的基因，涵盖多个致痫性候选基因，且该模块参与神经胶质细胞对抗氧化应激的保护过程，提示胶质细胞氧化应激与致痫性密切相关。另一个独立模块对应慢性痫性发作的效应，反映神经元突触囊泡运输过程的表达变化。我们发现，枢纽基因Sv2a的网络结构与连接性在正常脑组织与致痫脑组织间存在显著差异，在癫痫脑内其连接性显著增强。由于Sv2a是抗癫痫药物左乙拉西坦（levetiracetam）的作用靶点，该模块可能在调控痫性发作活动中发挥关键作用。对该模块的生物信息学分析还揭示了一种潜在的转录调控机制：通过上调RNA结合蛋白HuD，生成更长的可变多聚腺苷酸化转录本。综上，结合传统统计方法与网络分析手段，我们得以从系统视角解析差异调控基因，为阐明稳态抗致痫效应与致痫性背后的多条生物学通路提供了全新见解。