In the Thompson laboratory, we are interested in the molecular mechanisms that influence and regulate the hypothalamus as well as those CNS regions implicated in the regulation of hypothalamic functions.  As the hypothalamus is a key integration center within the brain our research studies involve biological themes including eating/appetite, emotionality/psychiatric illness/stress and reproductive functions.  It is noteworthy that many of these same themes are dysregulated in a host of disorders including diabetes, obesity, several psychiatric disorders as well as polycystic ovarian syndrome (PCOS).  To examine these mechanisms, we utilize a host of molecular/anatomical/genomic approaches and model systems including in vitro culture systems, animal models and human postmortem brain samples.

In the past year or so, our laboratory has shifted considerable attention to the role of small RNAs (e.g. microRNAs) and their involvement in both neuronal development but also in adult CNS functions.  We have co-developed a molecular anatomical method to examine microRNAs in developing and adult CNS tissues (Thompson, et al. 2007 Methods 43: 153-161) and are applying this method to the anatomical examination of several microRNAs in the adult CNS.  To date, several microRNAs have demonstrated regional as well as cellular patterns of expression that could implicate them in unique or brain-region selective functions.  Beyond these neuroanatomical studies, we have developed and analyzed a host of microRNAs profiling methods to determine what microRNAs are expressed in the adult brain (including human) and whether these microRNAs expression patterns vary as a function of disease or treatment.  These studies allow us to pose broader research questions such as “what microRNAs are expressed in specific brain regions and due these patterns of microRNAs expression change due to disease or treatment?”  In recent studies in collaboration with the laboratory of Dr. David Turner, we have implemented deep sequencing approaches to examine the expression of microRNAs at an unparalleled level.  This methodology has multiple advantages over hybridization-based microRNAs analysis methods including the potential identification of novel microRNAs.

  

Imaging of differential expression of two microRNAs across hippocampal subfields via in situ hybridization

Other Ongoing Studies:

Cellular Plasticity and Hypothalamic-Pituitary-Adrenal (HPA) Dysfunction (NIH R01 MH069879; J. Tasker (PI)).   We are using laser capture microscopy (LCM) approaches to selectively isolate specific anatomical divisions of a nucleus within the hypothalamus (paraventricular nucleus (PVN) from control and chronically stressed rodents prior to microarray gene expression analyses.  These studies are designed to identify patterns of gene expression associated with the chronically stressed condition so as to better understand how cells respond and adapt to such stressors.  With such knowledge, we believe we will have better insight into how such systems are dysregulated in psychiatric disorders.  Parallel LCM and microarray studies are being conducted in human postmortem brains in major depressive disorder, bipolar disorder and control patients (collaboration with Drs. Watson and Akil, MBNI).

Functional Genomic Studies of Neuronal Differentiation (NIH R01 NS051472; M. Uhler (PI)).  In these studies, the Thompson lab is specifically charged with the task to use gene expression profiling methods to examine patterns of gene expression following the induction of neuronal differentiation.  We are using an in vitro model system (P19 cells) and induction of neuronal differentiation following the activation of two different helix-loop-helix (HLH) transcription factors.  These time course studies have already led to the identification of several very interesting gene candidates as novel regulators of neuronal differentiation.  The collaborative team is attempting to use additional molecular methods to identify conserved non-genic sequences shared across neuronal differentiation genes and hence, common transcription factors involved in this process.