Abstract
The ability to tolerate infection is a key component of host defence and offers potential novel therapeutic approaches for infectious diseases. To yield successful targets for therapeutic intervention, it is important that the analytical tools employed to measure disease tolerance are able to capture distinct host responses to infection. Here, we show that commonly used methods that estimate tolerance as a linear relationship should be complemented with more flexible, nonlinear estimates of this relationship which may reveal variation in distinct components such as host vigour, sensitivity to increases in pathogen loads, and the severity of the infection. To illustrate this, we measured the survival of Drosophila melanogaster carrying either a functional or non-functional regulator of the JAK-STAT immune pathway (G9a) when challenged with a range of concentrations of Drosophila C virus (DCV). While classical linear model analyses indicated that G9a affected tolerance only in females, a more powerful nonlinear logistic model showed that G9a mediates viral tolerance to different extents in both sexes. This analysis also revealed that G9a acts by changing the sensitivity to increasing pathogen burdens, but does not reduce the ultimate severity of disease. These results indicate that fitting nonlinear models to host health–pathogen burden relationships may offer better and more detailed estimates of disease tolerance.
Highlights
Disease tolerance is broadly defined as the host’s ability to limit damage and maintain health when faced with increasing pathogen burdens, and is a general feature of host responses to infection [1,2,3,4,5]
The key to understanding tolerance is that it cannot be measured by considering host health or pathogen growth separately, but is instead defined by their relationship. This idea is embedded in the original statistical framework of tolerance [13], where it is analysed as a linear reaction norm of host health measured over a range of increasing infectious doses or pathogen burdens
A recent study of disease tolerance fitted a 4-parameter logistic model to the median survival of Drosophila infected with the bacterial pathogen Listeria monocytogenes, and this allowed to disentangle changes in fly health during infection that arose due to bacterial pathogenesis and host immunopathology [15], which would not have been possible using classical linear analyses
Summary
Disease tolerance is broadly defined as the host’s ability to limit damage and maintain health when faced with increasing pathogen burdens, and is a general feature of host responses to infection [1,2,3,4,5]. A recent study of disease tolerance fitted a 4-parameter logistic model to the median survival of Drosophila infected with the bacterial pathogen Listeria monocytogenes, and this allowed to disentangle changes in fly health during infection that arose due to bacterial pathogenesis and host immunopathology [15], which would not have been possible using classical linear analyses Despite these analytical advances, many studies continue to infer tolerance phenotypes from separate measures of host health and pathogen burdens measured at a single infectious dose (for example, [11,12,17]). We employed systemic infections in both males and females of two Drosophila lines with identical genetic backgrounds, differing only in having a functional or non-functional G9a (G9a+/+ and G9−/−) We challenged these flies with a range of DCV doses and quantified their tolerance responses using both the slope of linear reaction norm and a nonlinear sigmoid model. This allowed us to measure infection tolerance in the most comprehensive way, identifying which components of infection tolerance are affected by a single regulator of fly immunity (G9a), while providing a useful comparison of current methodology to estimate components of infection tolerance
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
