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Understanding host-pathogen interactions using a new synthetic theoretical framework for organismal nutrition

ReferenceBB/V01661X/1
Principal Investigator / Supervisor Professor Thomas Anderson
Co-Investigators /
Co-Supervisors
Institution National Oceanography Centre
DepartmentScience and Technology
Funding typeResearch
Value (£) 42,296
StatusCurrent
TypeResearch Grant
Start date 01/02/2022
End date 31/01/2025
Duration36 months

Abstract

Many factors can impact the outcome of infections, but the role of host nutrition is one of the most widely recognised, with both over- and under-nutrition affecting the susceptibility to infectious disease. However, whilst many studies have now demonstrated nutrition-driven effects on host-parasite interactions, we have only a limited understanding of the mechanisms underpinning them. Here, we propose to address this issue by using a novel combination of in vivo, in vitro and in silico approaches and a model host-pathogen system comprising an insect crop pest and 4 entomopathogenic bacteria. We will use the new Geometric Stoichiometry (GS) framework (Anderson 2020) to model the dynamic interaction between the nutritional requirements, and consequences for growth and mortality, of the host and pathogen. This will be underpinned by data from experiments that will quantify host utilisation of different nutrients and the time-varying metabolic budgets of both the host and its pathogens (singly and in combination). We will first construct a metabolic budget for the host by quantifying intake, growth, respiration and excretion of the host, from which we can understand the impact on the host, at a physiological level, of diets varying in their amounts and ratios of protein and carbohydrate. We will also quantify the consequences for this budget of mobilising an immune response against non-lethal infections with four bacteria. We have recently developed synthetic bloods with the same nutritional properties as the bloods of insects feeding on these different diets (Wilson et al. 2020). We will use these to help construct metabolic budgets for the four bacteria growing in vitro in the absence of any host immune response. Finally, we will use these host and pathogen metabolic budgets developed using GS to make a priori predictions about the outcome of the host-pathogen interactions, which will then be tested empirically using infection experiments.

Summary

A healthy diet is vital for many reasons, but one that has come to be appreciated more recently is how diet impacts the ability to fight off infectious diseases. This is true for humans and other animals but we currently don't really understand how this works. In other words we don't understand exactly how the food an animal eats changes its ability to either fight off a pathogen with its immune system, cope with the negative effects of infection on its body or indeed, how it directly affects the ability of the pathogen to grow in the animal's body. This last effect is particularly interesting as it has been considered much less by researchers than the first two options, but of course, the food an animal eats becomes the food the pathogen 'eats' in order for it to grow. This leads to the intriguing possibility that by changing a diet, an animal can manipulate how suitable its body is for a pathogen to grow in it. In this study we will carefully unpick the dietary requirements of 4 bacterial pathogens and 1 host, the cotton leafworm a caterpillar crop pest that causes devastation to agriculture across Europe and Africa. As well as being an important animal in its own right, this caterpillar is easy to rear in the lab and can be used as a model to understand the responses of other animals. We will rear the host on diets that differ in their calorie content and the ratio of proteins to carbohydrates. We will measure growth, protein turnover, respiration and the excretion of carbon and nitrogen in the faeces, telling us exactly how the animal uses the nutrients in the diet to build its body and those that are expelled. We will also measure immune responses and other biochemical properties of the blood. In a previous study we analysed the blood nutrients of caterpillars reared on these diets and created 'NutriBloods' that mimic the nutritional properties of caterpillar blood, but without any immune molecules. We will use these NutriBloods to grow the bacteria, and as for the host, measure their growth, protein turnover, respiration and the excretion of carbon and nitrogen. This information will allow us to create metabolic budgets for the host and the 4 pathogens. We will then use a modelling system called 'Geometric Stoichiometry' (GS) to predict how the pathogens should grow in the host, given that we understand how both host and pathogens use and excrete nutrients. This is exciting as we can model how the host's nutritional state will change during infection, what impact this will have on the growth of the pathogen and in turn what effects the growth of the pathogen will have on the host's nutritional state, as we expect constant feedback between the two systems. We can then test the predictions from the GS models by carrying out infections with the 4 pathogens in turn and measuring how the host and bacteria change over time. If GS predicts closely what happens during infection this will tell us that the nutritional requirements of the host and pathogen are the most important element in determining who will win the race for survival. If GS does not completely explain the outcome of the interaction we can use other information from our experiments (immune response and other blood properties) to determine how important these other elements are in controlling infection. The information from this study could be valuable for controlling crop pests, or more widely, it could help us, for example, to understand how livestock diet impacts infections, or indeed how our own diet impacts our risk of infectious disease.
Committee Research Committee A (Animal disease, health and welfare)
Research TopicsImmunology, Microbiology, Systems Biology
Research PriorityX – Research Priority information not available
Research Initiative X - not in an Initiative
Funding SchemeX – not Funded via a specific Funding Scheme
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