Gene networks involved in hypothalamic plasticity in response to dehydration; assessing the in vivo functions of candidate nodal genes.

The driving force behind this project is the need to rapidly exploit genomic information in order to obtain physiological understanding. We now know that mammals have approximately 30,000 genes. These data prompt two questions, firstly, where and when are these genes expressed, and secondly, what do these genes do? We have addressed these questions in a robust model system, namely the physiologically challenged vasopressin (VP) neurones of the hypothalamus. When an animal is dehydrated, the peptide hormone VP is released and travels through the blood stream to specific receptor targets located in the kidney, where it reduces the excretion of water, thus promoting water conservation. This is accompanied by a plethora of changes in the morphology, electrophysiological properties and biosynthetic and secretory activity of VP neurones. We wish to understand this functional plasticity and its physiological consequences in terms of the differential expression of genes. We have used microarray techniques that allow us to look at the expression of tens of thousands of genes in a single assay. We have thus compiled catalogues that represent comprehensive descriptions of the RNA populations expressed in different regions of the hypothalamus and pituitary. Further, we have identified transcripts that are either up- or down-regulated as a consequence of chronic dehydration. These catalogues are an important resource for researchers working on all aspects of VP physiology, particularly the central neuro-humoral control of cardiovascular homeostasis. Based on unbiased mathematical criteria, we have selected 4 genes for further study on the basis that they are key hubs, or nodes, in a gene network that, we hypothesise, might be involved in regulating and mediating hypothalamic functional plasticity. In order to test this hypothesis, we will: 1. check that the array data are correct using independent methods; 2. use gene transfer into the whole organism, coupled with the latest non-invasive monitoring technologies to determine the functional consequences of the increased or decreased activity of target gene products in terms of integrated cardiovascular control. This will be the first time that, based on a microarray output, a gene network will be studied functionally in the context of a whole animal physiological system. The data will undoubtedly lead to a better understanding of gene networks involved in the plasticity of a physiological system in health and disease states.

We have used array technology to comprehensively describe the pattern of gene expression in the hypothalamus, and how this changes following the physiological challenge of dehydration. We now wish to study the functions of key differentially expressed genes in vivo. We have employed a rational and unbiased approach to gene selection. We have utilised machine-learning algorithms to describe a gene network that, we hypothesise, might be involved in regulating and mediating hypothalamic plasticity. Of particular interest are those genes with many connections. Such genes may represent crucial functional hubs, or nodes. We will now test this hypothesis in vivo, focusing on 4 genes with 4 or more connections. We will now determine the functional and regulatory roles of these four key signalling nodes within a hypothetical gene network activated in the SON as a consequence of dehydration. To test this hypothesis we will: - validate the transcriptome data by determining the expression patterns of our candidate genes in the brain, hypothalamus and HNS at both the RNA and protein levels in terms of both specific brain cell-types and responses to dehydration - assess the functions of these genes in basal hypothalamic activity and stress-induced remodelling using in vivo gene manipulation techniques. Three systems will be exploited - knockout' transgenic mice, transgenic rats and somatic gene delivery using viral vectors. Gene activity will be manipulated by over-expression of wild-type proteins, or inhibition using RNAi. This will be followed by expression analysis of putative interacting genes, and by robust, but wherever possible, non-invasive, quantification of water balance, vasopressin release, the electrical activity of hypothalamic neurons, and hypothalamic morphology.