Given the multifactorial pathophysiological cascades involved in traumatic brain injury (TBI), it is difficult if not impossible to have a thorough view of the molecular mechanisms underlying the complexity of this pathology based on limited information derived from conventional approaches that examine isolated molecular events. This complexity becomes a larger limiting factor for the design of strategies to diagnose and predict the outcome of mild TBI (mTBI) which has a less defined symptomatology. Genomic profiling is emerging as a powerful tool to retrieve fundamental information about gene regulatory mechanisms that govern the mTBI pathology and its diversion towards other neurological disorders. However, genomic studies of mTBI have been primarily based on the use of whole brain regions comprised of heterogeneous cell types that mask information from the most vulnerable cell types which are crucial drivers of the pathogenesis. The unique aspect of our approach is to determine the genomic signatures of mTBI at single-cell resolution as cells are the basic units of biological structure and function. We will use state-of-the-art Drop-seq technology that empowers us to capture the transcriptome of thousands of individual brain cells in parallel to accurately define cell types based on aggregate genomic features and, more importantly, to identify cell-type specific gene markers of mTBI, which are generally hidden to the eyes of conventional approaches. We propose experiments to classify all the cell types in the hippocampus (one of the main action sites of TBI) in an unbiased manner and to assess the vulnerability of each cell type to mTBI using single-cell transcriptome profiles (Aim 1). In addition, we will define cell-type specific signatures of genes that could characterize main events involved in our rodent model of mTBI with varying severity at different time points post-TBI (Aim 2). We expect to retrieve novel cell types defined by the effects of mTBI, and their associated deterministic gene markers in the hippocampus. In doing so, we expect to unravel the fundamental, cell specific gene signatures that can be used as biomarkers of mTBI in a data-driven, unbiased manner. Our findings will derive clues to the underlying molecular events and pathways driving the cellular and functional remodeling. This proposal offers the unique opportunity to synergize efforts by combining the expertise of Dr. Fernando Gomez-Pinilla in TBI and the expertise of Dr. Xia Yang in genomics, bioinformatics, and systems biology of complex disorders. The overall goal of the proposal is to elaborate on an innovative research strategy that can provide a comprehensive understanding of the mTBI pathology at single cell resolution, which can be used to empower patient diagnosis, and to design a new line of strategies to redirect the courses of TBI and overcome subsequent neurological disorders.
We hypothesize that cell-type specific genomic variability determines the functions of individual cell types in the brain and is a critical determinant of TBI pathology and clinical outcomes. We propose to use this property to develop cell-type specific biomarkers of TBI that can be used to predict clinical outcomes by employing the cutting-edge Drop-seq technology to objectively evaluate the genomic variability of thousands of single cells in parallel. We expect to derive fundamental understandings of TBI at the level of gene regulation and the cell, the basic units of biological structure and function.
| Arneson, Douglas; Zhang, Guanglin; Ying, Zhe et al. (2018) Single cell molecular alterations reveal target cells and pathways of concussive brain injury. Nat Commun 9:3894 |
| Hui, Simon T; Kurt, Zeyneb; Tuominen, Iina et al. (2018) The Genetic Architecture of Diet-Induced Hepatic Fibrosis in Mice. Hepatology 68:2182-2196 |
| Gomez-Pinilla, Fernando; Yang, Xia (2018) System biology approach intersecting diet and cell metabolism with pathogenesis of brain disorders. Prog Neurobiol 169:76-90 |
| Arneson, Douglas; Zhang, Yong; Yang, Xia et al. (2018) Shared mechanisms among neurodegenerative diseases: from genetic factors to gene networks. J Genet 97:795-806 |
| Camacho, Jessica; Truong, Lisa; Kurt, Zeyneb et al. (2018) The Memory of Environmental Chemical Exposure in C. elegans Is Dependent on the Jumonji Demethylases jmjd-2 and jmjd-3/utx-1. Cell Rep 23:2392-2404 |
