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Data from: Nonlinear disease tolerance curves reveal distinct components of host responses to viral infection

Citation

Gupta, Vanika; Vale, Pedro F. (2017), Data from: Nonlinear disease tolerance curves reveal distinct components of host responses to viral infection, Dryad, Dataset, https://doi.org/10.5061/dryad.7b2p6

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.

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