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Host Pathogen interactions as a Resource - Competition Problem

Project: Research


Malnutrition and obesity are two of the most prevalent nutritional conditions affecting humans around the world today. As well as their obvious pathological effects on body condition and general well-being, sufferers may also have a reduced capacity to resist infections. In light of this, there has been a growth in the use of nutritional supplements aimed at boosting immunity, practiced both by the medical establishment (e.g. iron and vitamin supplements) and on the medical fringes. Whilst there is little doubt that certain key nutrients can play an important role in fighting infections, many of the studies to date have been conducted on single nutrients in isolation, without considering how they interact with other components of the diet, and without a robust framework for assessing their efficacy or mechanisms of action. The aim of the current proposal is to combine the theories provided by nutritional biology, ecological immunology and community ecology to develop a new framework that will allow us to test ideas about the importance of nutrition in determining the outcome of infections.
Insects and their pathogens can provide useful models for understanding human diseases. This is because the insect's relatively simple immune system shows striking parallels with the human innate immune system. Moreover, insects are often easier to work with than humans, yet exhibit many of the same nutritional behaviours, such as obesity, anorexia and self-medication. We will use the caterpillar, Spodoptera littoralis, and the bacterium, Bacillus subtilis, as a model system for exploring the effects of macronutrients on innate immunity and pathogen resistance. Our previous studies have shown that healthy insects perform best on a diet that is roughly balanced in terms the relative amounts of protein (P) and carbohydrate (C), the two most important macronutrients for insects. If the insect eats too much or too little P or C, then it performs less well, indicating that this is the 'optimal' diet when uninfected. In contrast, insects that have been infected with pathogens, like B. subtilis, have much higher survival rates if they eat a diet extremely rich in protein. Moreover, if they are given a choice, infected insects will feed on a diet with a high protein content to aid their survival.
We will use a step-wise experimental approach to determine whether we can predict the outcome of pathogen infections by understanding how the host and pathogen fare when grown in isolation. In particular, we will test the null hypothesis that the outcome of the infection (e.g. whether the insect lives or dies) is determined solely by the nutritional requirements of the host and pathogen. We will use 20 different artificial diets that vary in their P:C composition, so that we force the insects to ingest different amounts of P and C. 1. We will start by establishing how the diet of the insect affects the nutritional composition of its blood, which is where the bacteria will feed. 2. We will then grow the bacteria in a range of broths that have the same nutritional composition as the insect blood on each diet, but without blood cells and other immune defences. This will show us the nutritional requirements of the bacterium in the absence of the host. 3. We will then determine how the insect host's immune defences perform in the absence of the pathogen by injecting the insect with dead bacteria to stimulate the immune response, which we will be quantified using genetic and other methods. These first three experiments will allow us to determine how the performance of the host (insect) and pathogen (bacteria) differs on different diets and to make predictions about winners and losers based on assumptions about who controls nutrient use. 4. Finally, we will inject caterpillars with live bacteria and quantify the outcome in terms of bacterial growth rates and insect growth/survival, allowing us to test these predictions.
AcronymHost Pathogen interactions as a Resource - Competition Problem
Effective start/end date7/11/116/03/15


  • BBSRC: £473,915.00


Research outputs