Modelling the vasopressin system

"Fundamental bioscience is vital to revealing the mechanisms underlying normal physiology and homeostatic control during early development and across the lifespan into old age. The Bioscience for Health priority aims to achieve a deep, integrated understanding of the 'healthy system' at multiple levels, and of the factors that maintain health and wellness under stress and biological or environmental challenge." (BBSRC Priorities 2018)

Healthy aging depends on the ability of physiological systems to sustain bodily functions throughout (and despite) the succession of acute and chronic challenges and insults that a normal life entails. One key system operates through the regulated secretion of the hormone vasopressin. This hormone has an essential role in maintaining a constant blood volume with a constant composition (especially of sodium).
Vasopressin is made by a small population of neurons in the hypothalamus and is secreted from their nerve terminals in the pituitary gland: it regulates blood volume by its actions on blood vessels and it regulates water retention by its actions at the kidney. The "appropriate" level of secretion is thus a function of blood volume and sodium concentration. During dehydration a healthy system can maintain an appropriately elevated secretion for long periods, despite progressive depletion of the pituitary stores of vasopressin. However, disorders of this system commonly arise during aging, with a substantial impact on quality of life and mortality.

Our aim is to understand (i) how the vasopressin system functions during chronic challenge, and (ii) how insults to this system can lead to disturbed function. We will develop computational models of the vasopressin system using experimental data from laboratory rats. The vasopressin system in the rat is very like that of the human - this is an important system that has been closely conserved throughout mammalian evolution - and studies in rats are possible that cannot be performed in people. These studies will involve recording the electrical activity of vasopressin cells in different chronic conditions and studying their responses to acute challenge.

With a detailed and accurate computational model of the vasopressin system we will be able to assess how simulated insults to the system affect its functionality. For example, many neurons are vulnerable to damage when they are strongly activated for prolonged periods. In the vasopressin system, this is likely to mean that the cells that are most sensitive to sodium levels are the cells most likely to die during prolonged periods without drinking or with excessive salt intake. As they die, the surviving cells will be under greater demand - so become more active - leading to further loss of cells. In extreme cases this vicious cycle can escalate, leading to a sudden collapse of the vasopressin system.

We think that the system has a number of mechanisms built into it to reduce the danger of this happening. In particular, the cells communicate with each other, and by doing so they can 'share the load' equitably. We will build a model of this system of intercommunication as part of our complete model of the vasopressin system, and test it experimentally.

With a complete model we will be able to systematically explore the points of vulnerability of the vasopressin system that can lead to long term problems. We expect also, that a better understanding of exactly how the system can become dysfunctional will help to identify early warning signs of chronic dysfunction.

Systems biology is an approach by which biological questions are addressed through integrating data collection activities with computational/ mathematical modelling activities to produce a better understanding of biological systems. This project will develop a computational model of the vasopressin system, including a combination of mathematical, statistical and computational modelling, visualisation tools and network inference. Model development and validation will proceed iteratively, using quantitative data from electrophysiological studies and studies of secretion in rats. The final model will include a model of the vasopressin cell populations and of dendro-dendritic interactions between them. The model will fully incorporate cell heterogeneity, and cell fitted, integrate-and-fire based spiking models will be linked to quantitative ordinary differential equation (ODE) models of stimulus-secretion coupling and to an ODE model of stimulus-synthesis coupling. Data will be obtained from rats in three physiological states: eunatremia, chronic hypernatremia, and recovery from chronic hypernatremia. Cell behaviour and secretion in each state will be characterised by measuring responses to acute osmotic, hypovolemic, baroreceptor challenges and to direct chemogenetic activation using a novel transgenic rat line with DREADDS expressed specifically in the vasopressin cells. Each of these challenges will themselves be modelled to build the complete systems model. The goal is for the model to be able to account for all biological challenges experienced by this system. We will then explore the model systematically to identify points of vulnerability in the system architecture that might lead to system dysfunction of the types observed commonly in our aging population, and to identify early warning signs of system dysfunction.

This project addresses BBSRC Bioscience for Health priority, which aims to achieve a deep, integrated understanding of the 'healthy system' at multiple levels, and of the factors that maintain health and wellness under stress and biological or environmental challenge. The project involves computational modeling integrated with experimental studies of the vasopressin system. The aim is to achieve a predictive, quantitative systems model of this important homeostatic system that can be used to identify system vulnerabilities that lead to chronic dysfunction.

The main groups of potential beneficiaries are:

1) The computational neuroscience community. This will benefit from the free availability of software and code - including the powerful genetic algorithm software for matching high dimensional models to neuronal data, and the novel software for modeling neuronal networks linked dendro-dendritically. These will be made freely available both in conjunction with publications and on the project website. They will also benefit from the open availability of large electrophysiological data sets for modeling (we will be uploading >400 time series of spiking activity of vasopressin neurons each comprising up to 60,000 spikes, with full metadata annotation). Impact on this community will be engaged by interaction with the INCF (The International Neuroinformatics Coordinating Facility https://www.incf.org/about).

2) Clinical academic communities within Endocrinology, Cardiovascular Sciences and Urology will benefit from a better understanding of the etiology of chronic disorders of the vasopressin system. These include conditions of chronic hypersecretion (SIADH, vasopressin-dependent hypertension), and hyposecretion or disordered secretion (nocturia, and sequela of septic shock). Developing a comprehensive and quantitative systems model may lead to early identification of warning signs and a rational approach to developing new therapies. This interest will be engaged primarily by the publication of cross-disciplinary topical reviews in relevant journals, and by engagement with the Physiome Project (http://physiomeproject.org/).

3) Academic communities within Neuroscience and Neuroendocrinology will benefit from insight into the functional role of paracrine interactions amongst neurons in general and dendro-dendritic interactions in particular, as reported in primary research publications arising from this project.

3. Pharmaceutical industry have invested heavily in the development of vasopressin agonists and antagonists and will be interested in the potential of the systems model for supporting the identification of targets and new therapeutic applications by a 'rational design' approach. Their awareness of the project will be facilitated by the involvement of Edinburgh Innovations (https://edinburgh-innovations.ed.ac.uk/)

5. Capacity in UK Life Sciences. New technologies in the life sciences have made in vivo skills and skills in integrating modeling and experimental approaches a priority. We will train new PhD students in these skills in the course of this project, and undertake to freely disseminate tools and expertise.

6. The interest of the general public will be engaged, and this will enhance public recognition of the importance of investment in basic science, and attract school students into Biomedical Sciences.