Leigh Syndrome (LS) is the most common form of mitochondrial disease in children. It affects 1 in every 40,000 births and is characterized by ataxia, seizures, failure to thrive and premature death. There are more than 75 gene mutations that have been associated with LS. Among them is NDUFS4, the gene that codes for a subunit of the protein complex I of the mitochondria. Mice carrying a whole-body knockout (KO) of this gene greatly model this illness; they recapitulate multiple phenotypes of LS in patients. Prior studies in the lab have shown that the KO of Ndufs4 in GABAergic neurons, not in excitatory neurons, across all brain regions, reproduce the epilepsy phenotype seen in the global KO mice. Moreover, GABAergic neurons in a specific brain region such as the brainstem are sufficient to lead to epilepsy in mice. Mice with Ndufs4 KO in brainstem and cerebellum interneurons, mediated by GlycineCre, have epilepsy. However, it is still unclear as to what brain regions housed neurons involved in seizure activity in these mice. In this study, brain regions experiencing neuronal hyperactivity and hypersynchrony during seizures in this new model of LS were examined. A thermal seizure was induced in the Ndufs4 GlycineCre KO mice. Forty-five minutes after the seizures, the mice were anaesthetized, the brains were fixed, and harvested. Brain slices were prepared and stained with a c-Fos antibody and finally imaged on the confocal microscope. Surprisingly, high c-Fos immunoactivity was observed in the cerebellum alone and not in other brain regions generally known to be involved in seizure generation. These findings indicate the participation of the cerebellum in seizure generation in Leigh Syndrome epilepsy. In future studies, we will repeat this experiment to increase the sample size and confirm these findings.

The Ndufs4 gene codes for a subunit of complex 1 in the mitochondrial respiratory chain. Mutations causing a loss-of-function of the Ndufs4 gene are linked to Leigh syndrome(LS), a progressive neurodegenerative disorder. LS is characterized by progressive loss of mental, and movement abilities, respiratory distress, and epilepsy, leading to premature death within 2 to 3 years. It is the most common clinical pediatric presentation of mitochondrial disease. Mice with global Ndufs4 knockout(KO) are a good model of LS, exhibiting seizures and other phenotypes of LS. Previous work has shown that epileptic seizures arise from the impact of Ndufs4(KO) in GABAergic interneurons. The objective of my project is to further our understanding of the mechanism of LS-related epilepsy. I assessed the impact of the Ndufs4(KO) on interneuron morphology as a possible contributing factor to the development of seizures. The LS mouse model was generated using the Cre/LoxP mechanism. Two mice with floxed Ndufs4, one is Dlx12cre positive and the other is homozygous Ai14, were crossed creating mutant mice. Control mice were generated similarly, but parents are Wild-Type (WT) for Ndufs4. Mice were perfused with phosphate-buffered saline (PBS) and fixed with 4% paraformaldehyde (PFA). I made 50-um coronal brain slices using the Leica VT1000S Vibratome. Then, I mounted the slices and used the Olympus slide scanner to collect fluorescent images. We found scattered labeling of GABAergic neurons in both the control and mutant forebrains. Our results show that the Dlx12cre+ mouse can label a dispersed population of GABAergic neurons across multiple brain regions. Neural dendrites are visible in our images of control and mutant mice. Optimizations are needed to improve the image resolution for optimal Scholl analysis. This study elucidates the impact of Ndufs4 on interneuron morphology and the contribution of this neuronal characteristic in the mechanism of epilepsy in LS.

 Dravet syndrome (DS) is a genetic form of epilepsy characterized by febrile seizures in infancy, developmental delays, and sudden unexpected death in epilepsy (SUDEP) as a result of being drug-resistant. Finding new and innovative treatments is essential to reducing the risk of SUDEP and other symptoms in DS patients. Using a mouse model of DS (SCN1a+/- mouse), I showed that a machine learning-based detection algorithm could be used to detect interictal spikes (IS), which are abnormal neuronal discharges typical of epilepsy. The goal of the current experiment is to see whether the prior findings can be generalized to a larger dataset and whether the detected IS can be used to predict seizures before their onset. Data is collected by implanting two electrocorticographic electrodes and one electromyography electrode, as well as a wireless body temperature sensor in DS mice. Ambient temperature is controlled so that the animal’s core body temperature is initially maintained at 37°C and then is gradually increased by 0.5 °C every 2 min until a seizure is observed or the core body temperature reaches 42.5 °C. A machine learning model previously trained using manually scored data from the de la Iglesia lab is used to autonomously detect IS in the collected data. My results so far showed a moderate yet significant positive correlation between ambient temperature increases and IS frequency and points to a positive correlation between IS frequency and seizure onset. However, these results did not include the continuous recordings of body temperature. In the current experiment, I test if these correlations hold using a larger sample size and including continuously recorded body temperature, which may have more predictive power than ambient temperature. Our long-term plan is to design a closed-loop experiment that uses the algorithm to predict and stop seizures before their onset.