The role of chain length in fatty acid uptake in both health and disease: a combined experimental-theoretical modelling approach

Heart disease, type 2 diabetes and obesity (collectively known as metabolic syndrome) are three of the most serious health conditions facing the UK today. They affect one in four adults in the UK, costing the NHS over £10 billion annually. These figures are rising rapidly, with 1 in 2 people predicted to be affected by 2050, with an associated cost of £50 billion. Sadly, we do not know the basic mechanisms of how type 2 diabetes (and many other obesity-related conditions) occur. Establishing the mechanics and role of fats is critical since too many entering our cells can contribute to the development of diabetes. This then poses the question: how do fats enter cells? At present, we know very little. Identifying how fats enter cells will pave the way for the development of new diets and drug treatments to reduce fat uptake. In the long term, this will help to slow and potentially halt the development of type 2 diabetes, obesity and heart disease.

I will use imaging techniques to measure how much fat crosses into cells, how quickly this happens, and how this changes with different types of fats. I will then use this information to build mathematical models that explain the mechanisms behind fat uptake. Although it may seem surprising that mathematics can be used to answer questions in biology, recent progress has shown that combining these two areas can lead to great advances in physiology and medicine. In this project, I will take advantage of my mathematical model to make predictions about the ways in which fats enter cells. I can then confirm or reject these predictions through experiments in the lab. With a good understanding of fat uptake, I will be able to start testing drug treatments and diets in rodents to prevent the progression of type 2 diabetes and obesity.

Metabolic syndrome refers to a range of conditions including obesity, diabetes and high blood pressure, which increases an individual's risk of developing cardiovascular disease. These conditions are typically preceded by elevated levels of circulatory free fatty acids (FFAs), which are taken up by cells, subsequently leading to cellular dysfunction and death. This work will identify the mechanisms by which FFAs cross the plasma membrane (PM) and how FFA size alters the rate and mode of transport. This is important as it is often the longer chained FFAs that exert a toxic phenotype. By identifying such mechanisms, therapies can ultimately be developed to regulate cellular FFA entry, thus providing potential targeted therapies for metabolic syndrome. Raman spectroscopy will be used to image FFAs crossing the PM of cells. These experiments will determine the FFA flux and rate constants, which will then be incorporated into a biophysical model of FFA uptake, based on reaction-diffusion equations. The mathematical model will describe the movement of FFAs both outside and inside the cell, and FFA transport across the PM by both passive diffusion and facilitated transport. By fitting the mathematical model to the data, it will be determined: a) if FFA uptake is facilitated, passive or some combination of the two, b) how FFA size and concentration affect the mode of uptake, and c) how this mechanism is altered in metabolic syndrome. The mathematical modelling predictions will then be validated in a human hepatocyte cell line, a cell that contributes towards insulin resistance, a central characteristic of metabolic syndrome. Hepatocytes will be genetically engineered to over- or under-express components of FFA transport, and then exposed to FFAs of increasing chain length for different durations and at different concentrations. These experimental results will then be used to refine the mathematical model, generating fresh predictions and suggesting further experiments.

N/A. Not completed as advised by Dr Anke Davis, Programme Manager for non-clinical careers at the MRC.