Single cell transcriptomics identifies a dentate granule cell type switch in epilepsy

University Of Wisconsin-Madison, Madison WI

Investigators

Abstract

PROJECT SUMMARY After exposure to an epileptogenic insult, there may be a progressive reduction in seizure threshold that ultimately results in spontaneous seizures; this gradual process is called epileptogenesis. There are no drugs that modify the course of epileptogenesis; anticonvulsant drugs that suppress seizures do not work to modify disease progression7,8. Thus, there is a pressing need to identify molecules and pathways that are at the heart of epileptogenesis. This proposal addresses this unmet need. Combining our powerful novel algorithm, MAGIC9, with a unique, statistically powered single cell dataset from 2 rodent epilepsy models, we have identified those nuclear proteins that control the transcriptomes in every major cell type in the brain. This has allowed us to generate a regulatory hierarchy controlling large scale gene changes after status epilepticus. We now have insight into all the major drivers of gene changes in epilepsy across brain cell types. We find that DGs are the most transcriptionally altered neuronal cell type after SE and undergo a subtype switch from ‘quiet’ to ‘active’ DGs. The transcription factor STAT3 hijacks the DG gene network to become the hub, or apex factor that controls in excess of 90% of all information flow in the DG gene regulatory network. The major impact of this study will be the answering of the question ‘is the DG cell type switch in epilepsy sufficient and/or necessary for disease progression?’. The major gaps in our understanding of the role of this pathway are 1) in which cell types does STAT3 activation occur? 2). Is STAT3 activation sufficient to drive disease? The premise of this project is three-fold: Firstly, our recent work (in review at time of submission) and that of others, implicates STAT3 as a central factor in acquired epilepsy. Secondly, our preliminary data shows that many cell type are altered in epilepsy with DG cells the most perturbed. Molecular alterations in neurons are coordinated by activation of the transcription factor STAT3. Thirdly, pharmacological inhibition of the STAT3 upstream kinase JAK1 with the orally available, FDA approved drug CP690550 (Tofacitinib) profoundly suppresses spontaneous seizures in our WT model. Thus, we will test whether STAT3 induction in DGs is sufficient and/or necessary for disease progression. The innovations of this project are: 1) We are the first to apply MAGIC to snSeq data and identify drivers of transcriptional programs across cell types in epilepsy. 2) To our knowledge, our snSeq data is the most statistically powered and deeply annotated epilepsy and control dataset in existence with 150,000 cells and nearly a billion datapoints. Successful outcome of this risky and exploratory R21 proposal will be: 1) The first exploration of the sufficiency and necessity of the DG cell switch in epilepsy. 2) A suite of data to support a full, well-premised RO1 application.