The goal of this hypothesis-generating research proposal is to investigate the molecular mechanisms involved in the central nervous system (CNS) response to systemic inflammation. The central response to systemic inflammation will be monitored by DNA microarray technology, which allows the simultaneous monitoring of the expression of thousands of genes. Our proposed studies will systematically assess several parameters that will provide guidance for the use of microarrays in the study of dissected discrete regions of whole CNS tissue and will include extensive validation of the findings by real-time PCR. We will assess parameters such as coefficients of intraassay (interslide) and interassay variation, and the inclusion of brain region specific and inflammation cDNA controls. We will evaluate data obtained using: (1) three methods of tissue dissection, (2) two brain regions (hypothalamus and hippocampus), and (3) a specific transgenic model that shows meaningful biological outcome with our chosen paradigm. The validation of these parameters and the implications of our data analyses will be useful in the evaluation of microarray as a technique for comprehensive surveys of CNS transcriptional changes that will be likely to occur upon the completion of current genomic projects. To study CNS gene transcription we will use a rodent model of systemic inflammation response syndrome (SIRS or Sepsis) caused by peripheral (intraperitoneal) lipopolysaccharide (LPS) administration. This is a clinically relevant model of inflammation that induces acute transcription of multiple genes in the CNS. The areas to be studied, hypothalamus and hippocampus, are the sites for the regulation of clinically relevant neuroendocrine responses to inflammation. In addition, the proposed studies will result in new and valuable data related to transcription regulation that are important in defining signaling pathway mechanisms in the CNS during states of inflammation. The proposed studies will result in new data that will be needed for us to generate novel testable hypotheses, which will provide the framework for future R0l applications.
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