The overall aim of this project is to combine experimental studies with mathematical modeling to understand the interactions between the hypothalamus and the pituitary gland that lead to rhythmic secretion of the hormone prolactin. This work will be done in close collaboration between an experimental lab and a mathematical modeling lab; both labs reside at the same university, facilitating daily interactions. The primary goal of this research is to understand how neurosecretory cells within the hypothalamus interact with the pituitary gland to produce daily rhythms of prolactin secretion in the rat during pregnancy. Prolactin is one of the most versatile hormones of mammalian organisms, with over 300 separate biological activities. The prolactin secreted following the mating stimulus has many targets, including other endocrine glands, and is important for maintaining a normal pregnancy in the rat. Prolactin is secreted by pituitary lactotrophs. Secretion from these cells is tightly regulated by the hypothalamus, a region of the brain that transmits time-of-day information to the rest of the body. The interaction between hypothalamic neurons and lactotrophs is complex; the neurons influence each other as well as the lactotrophs, and prolactin from lactotrophs feeds back onto and influences the hypothalamic neurons. Such a complex system is ideal for mathematical modeling, which can provide insight into the influence of the various network interactions, and can be used as a tool for integrating information. In this project, mathematical modeling is combined with experimental studies. The model will be calibrated by experimental data, and will make predictions that will be tested in the laboratory. This joint experimental-computational approach is well suited for understanding the complex hypothalamus-pituitary network. Student training is an important element of this project. It is anticipated that graduate students and postdoctoral fellows will play very active roles in the research described herein. This participation will provide multi-disciplinary training that will be invaluable for an increasingly multi-disciplinary workplace. There are four specific aims in this proposal. First, a mathematical model will be developed for pituitary lactotrophs. This model, based largely on experimental data on cultured lactotrophs from our lab, will provide a mechanistic understanding of the activity patterns of these cells. It will also be used to understand how the activity is modified by hormones such as dopamine and oxytocin. Second, mathematical models will be developed of hypothalamic dopamine- and oxytocin-secreting neurons, using hypothalamus slice data from our lab. These neurosecretory cells regulate prolactin secretion from lactotrophs, and are themselves under the influence of neurons within the suprachiasmatic nucleus (SCN). The third specific aim is to develop a mathematical model of the network interactions among the various hypothalamic neurons and pituitary lactotrophs. This model will be minimal, focusing on the network interactions between cells rather than the detailed biophysical processes that take place within cells (the goal of the first two aims). Fourth, the role of rhythmic clock gene expression in dopamine- and oxytocin-secreting neurons will be investigated. If the expression patterns are shown to be rhythmic, then this suggests that these cells provide circadian input to the pituitary that is separate from, but may be entrained by, neurons within the SCN. These studies will support the mission of NIDA by establishing the way the normal brain functions in the absence of drugs of abuse to support the pituitary gland. It will then lead to studies of effects of drugs of abuse on brain-pituitary function. ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Research Project (R01)
Project #
5R01DA019356-04
Application #
7265297
Study Section
Special Emphasis Panel (ZRG1-MDCN-C (50))
Program Officer
Volman, Susan
Project Start
2004-07-01
Project End
2009-06-30
Budget Start
2007-07-01
Budget End
2008-06-30
Support Year
4
Fiscal Year
2007
Total Cost
$341,047
Indirect Cost
Name
Florida State University
Department
Type
DUNS #
790877419
City
Tallahassee
State
FL
Country
United States
Zip Code
32306
Kennett, J E; McKee, D T (2012) Oxytocin: an emerging regulator of prolactin secretion in the female rat. J Neuroendocrinol 24:403-12
Watts, Margaret; Tabak, Joel; Zimliki, Charles et al. (2011) Slow variable dominance and phase resetting in phantom bursting. J Theor Biol 276:218-28
Helena, Cleyde V; Cristancho-Gordo, Ruth; Gonzalez-Iglesias, Arturo E et al. (2011) Systemic oxytocin induces a prolactin secretory rhythm via the pelvic nerve in ovariectomized rats. Am J Physiol Regul Integr Comp Physiol 301:R676-81
Teka, Wondimu; Tsaneva-Atanasova, Krasimira; Bertram, Richard et al. (2011) From plateau to pseudo-plateau bursting: making the transition. Bull Math Biol 73:1292-311
Sirzen-Zelenskaya, A; Gonzalez-Iglesias, A E; Boutet de Monvel, J et al. (2011) Prolactin induces a hyperpolarising current in rat paraventricular oxytocinergic neurones. J Neuroendocrinol 23:883-93
Sethi, Sumit; Tsutsui, Kazuyoshi; Chaturvedi, Chandra Mohini (2010) Temporal phase relation of circadian neural oscillations alters RFamide-related peptide-3 and testicular function in the mouse. Neuroendocrinology 91:189-99
Tsaneva-Atanasova, Krasimira; Osinga, Hinke M; Tabak, Joel et al. (2010) Modeling mechanisms of cell secretion. Acta Biotheor 58:315-27
Tomaiuolo, M; Bertram, R; Gonzalez-Iglesias, A E et al. (2010) Investigating heterogeneity of intracellular calcium dynamics in anterior pituitary lactotrophs using a combined modelling/experimental approach. J Neuroendocrinol 22:1279-89
Tabak, Joel; Gonzalez-Iglesias, Arturo E; Toporikova, Natalia et al. (2010) Variations in the response of pituitary lactotrophs to oxytocin during the rat estrous cycle. Endocrinology 151:1806-13
Tabak, Joel; Mascagni, Michael; Bertram, Richard (2010) Mechanism for the universal pattern of activity in developing neuronal networks. J Neurophysiol 103:2208-21

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