Worms and Bugs - Quantifying Infection Dynamics in Microcosms

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Despite continual progress in medicine, infectious diseases pose an unabated threat not only to humans but also to domestic and wild animals. Epidemiologists rely increasingly on mathematical models to analyse and predict the outcome of epidemic outbreaks. However, those models are still far from perfect and are based on many assumptions that cannot always be validated. One of the remaining black boxes in our understanding of infectious disease dynamics is transmission. On the one hand, new technologies have allowed microbiologists to gain increasingly detailed knowledge of the molecular interactions between pathogens and their hosts, informing on the within-host dynamics of infection. On the other hand, the roles of environment and host behaviour on the spread of epidemics is better understood, with the recent hindsight from SARS, pandemic influenza or foot-and-mouth disease outbreaks. But there remains a major gap between those two scales. In particular, we are still far from being able to predict the epidemic potential of a pathogen just based on measures of its growth and spread within an individual host. Reconciling those two levels is also an essential step to improve our understanding of pathogen evolution: because different factors may favour within-host growth and between-host transmission, we are likely to misjudge the selective pressures acting on the whole life-cycle of pathogens. This can have practical implications for the management of vaccination and drugs. In order to help fill those gaps, I propose to set up a new experimental host-pathogen system where individual-level and population dynamics can be measured and used to design and validate integrated mathematical models. Experiments on animals, while essential to gain specific knowledge on chosen pathogens, are limited in scope by technical and ethical issues. My project will use the free-living nematode worm Caenorhabditis elegans, which has been studied by biologists throughout the world for half a century. The worms can be infected in the lab with various microbes, either specific parasites of C. elegans or foodborne pathogens of humans and animals such as Salmonella. Using microscopes, it is possible to keep track of the numbers of infected and uninfected nematodes in a microcosm (an experimental population maintained in a large Petri dish), but also measure the development of infection and its effects in individual worms. Data from these experimental epidemics will be used to design and parameterise mathematical models that simulate population dynamics. The models can then be used to predict the outcomes of different experiments, which can then be carried out in the lab to validate the models. The aim is to establish the quantitative links between individual-level measurements and epidemic spread. For example, if we observe that variations in resources affect the ability of worms to resist or survive infection, can we predict how that will modify the circulation of the pathogen in the population? We will also assess the competitive abilities of different pathogen lines: some pathogens might have a higher growth rate within individual hosts but a lower transmission ability (for example if they kill their host too quickly). Which genotype 'wins' (i.e. spreads across a host population) will depend on a combination of factors, which can be measured and combined into a mathematical framework. These questions are important to understand the ecology and evolution of infectious diseases in natural populations. While they have been studied theoretically for many years, the application to real systems has remained difficult because of our lack of understanding of the detailed mechanisms of infection dynamics at the interface of individuals and populations. This project offers a unique opportunity to reconcile those different levels of investigation and test some fundamental assumptions of mathematical models that had not been validated before.