Research

The overall aim of our research is to understand how individual-level host heterogeneity scales up to population level disease outcomes. Using the fruit fly Drosophila melanogaster as an established model of infection, immunity and behaviour, we take an experimental approach to investigate the causes and the consequences of individual variation in immune responses, life-history traits and social behaviours. Currently our work focuses on the following broad questions:

What are the causes of individual heterogeneity in the response to infection?     

Which factors generate extreme host heterogeneity in pathogen transmission?

How does individual-level host heterogeneity scale up to population-level disease dynamics?

How will pathogens evolve in response to heterogeneity in host health?

 


 

 

What are the causes of individual heterogeneity in the response to infection? 

 

Natural genetic variation in disease tolerance

Our work has focused on tolerance of Drosophila C Virus, a horizontally transmitted viral pathogen of Drosophila. We have described natural genetic variation in tolerance of DCV, and found that females were generally more tolerant than males. We have taken this work further and found that flies tolerated not by decreasing the severity of disease, but instead by delaying the onset of severe disease beyond a higher threshold of viral titer. These effects were shown to be driven in part by negative regulators of the JAK-STAT pathway, a damage signalling pathway that is conserved between insects and mammals.

 

 

 

 

Innate immune regulation of disease tolerance 

In contrast to genetic variation in mechanisms that eliminate pathogens, we currently know less about mechanisms that prevent or repair tissue damage arising from infection, and how they vary among individuals of different genotypes and sexes.  Following our work on DCV, we wanted to better understand if  - similar to viral infection - negative regulators of immune responses are also important mediators of tolerance during bacterial infection. This has led to some work to associate disease tolerance phenotypes to specific immune or damage repair mechanisms. The major insights to derive from this work include that negative regulators of the Immune Deficiency (IMD) pathway, caudal and pirk, are important regulators not only of pathogen clearance, but also of the ability to tolerate septic bacterial infection. During enteric or gut infections, we instead find important roles of mechanisms that either prevent, repair or renew gut epithelia following infection-induced damage.

 

 

 

 

Mitochondrial genetic effects on innate immunity

Most work on natural variation in immunity tends to focus on polymorphism in the nuclear genomes. Mitochondria are intracellular organelles with their own DNA (mtDNA) and are increasingly recognized as important mediators of immune responses. However, it is currently unclear how naturally occurring variation in mtDNA contributes to the widespread heterogeneity in infection outcomes.  We are using phenotypic, physiological and genomic approaches to test the effect of specific mitochondrial polymorphisms on cellular and humoral responses to infection in Drosophila melanogaster

 

 

 

 

 

 


 

Which factors generate extreme host heterogeneity in pathogen transmission?

 

Host heterogeneity in pathogen transmission presents a major hurdle to predicting and minimizing the spread of infectious agents. For example, superspreaders are individuals that contribute disproportionately to disease spread, making outbreak prediction unreliable when we lack information on host heterogeneity and have to rely on modelling the average transmission.

Part of the difficulty in linking individual variation to population-scale outcomes is that hosts can vary on multiple axes (e.g., behavioural, physiological, immunological) that affect their transmission potential. Moreover, we lack well-characterized empirical systems that account for multiple facets of individual variation. Therefore, the population-level epidemic outcomes of such variation remain unclear.

To address this gap, we combine the strengths of Drosophila as genetically tractable model of infection, immunity and behaviour to develop it as a model system for experimental epidemiology. Our approach is to identify the individual host traits that drive pathogen transmission, identify genetic and environmental drivers of variation for trait, and put this all back together as a more useful predictive framework of pathogen spread. Using a combination of experimental and modeling approaches, we're currently working on the following related questions:

 

How does infection change social group behaviours that impact disease spread?

Host behavioural changes following infection are common and could be important determinants of host behavioural competence to transmit pathogens. Identifying potential sources of variation in sickness behaviours is therefore central to our understanding of disease transmission. Using the Drosophila C virus (DCV) system, we found genetic-based variation in both locomotor activity and social aggregation. DCV infection caused sex-specific effects on social aggregation, as male flies in most genetic backgrounds increased the distance to their nearest neighbour when infected. We have now expanded this work on social interactions to study the effect of bacterial infection on social network structure.

 

The genetic determinants of pathogen acquisition and spread
Following all the work with DCV, our focus has shifted almost entirely to bacterial infections, as these offer a more tractable system to explore epidemiology experimentally. We have developed methodology to precisely measure bacterial shedding and actual spread within mesocosm epidemic setups. Acquiring and spreading infection involves multiple behavioural and physiological host traits, in addition to immunity. The contribution of host genetics to variation in these traits is largely unknown for most infectious diseases.  

We have previously carried out experimental infections with the bacterial pathogen Pseudomonas aeruginosa on males and females of at least 120 lines from the Drosophila Genetic Reference Panel (DGRP), and measured host traits such as bacterial shedding and behavioural avoidance of infectious food.

 In another project, we're investigating the role of gut damage prevention and repair mechanisms of the ability to shed and transmit bacterial pathogens.


 

 

How does individual-level host heterogeneity scale up to population-level disease dynamics?

Continuing with the Drosophila C Virus system, we dissected the genetic and sex-specific sources of variation in multiple host traits that are central to pathogen transmission. We found complex interactions between genetic background, sex, and female mating status accounting for a substantial proportion of variance in lifespan following infection, viral load, virus shedding, and viral load at death. Two notable findings include the interaction between genetic background and sex accounting for nearly 20% of the variance in viral load, and genetic background alone accounting for ~10% of the variance in viral shedding and in lifespan following infection.

To understand how variation in these traits could generate heterogeneity in individual pathogen transmission potential, we combined measures lifespan following infection, virus shedding, and previously published data on fly social aggregation. We found that the interaction between genetic background and sex explained ~12% of the variance in individual transmission potential

We then used this individual-level data to inform a stochastic contact network model. Our major finding was that individual host variation in host infectiousness, social aggregation, and infection duration – as measured experimentally – is sufficient to drive striking differences in the likelihood, severity, and duration of disease outbreaks. We were further able to identify the sources of host heterogeneity (i.e., genetic background, sex) and the specific host traits (i.e., social aggregation, infectiousness, infection duration) that are most important in determining disease dynamics.

 


 

 

How will pathogens evolve in response to variation in host health?

 

Understanding pathogen evolution is key to predicting and managing disease emergence. Theory predicts that strong immune responses will generally select for increased pathogen growth rates, which may be associated with higher virulence. However, there are currently few experimental tests of changes in pathogen growth and virulence resulting from selection in hosts with weakened immune responses resulting in either reduced ability to clear or to tolerate pathogens. We are starting to test the role of immune-compromised hosts on the evolution of pathogen traits by carrying out experimental evolution of bacterial pathogens in hosts with known deficiencies in disease tolerance. 

 

 

 
 
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