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Citation
Louie, A., Song, K.H., Hotson, A., Thomas Tate, A., Schneider, D.S. (2016). How Many Parameters Does It Take to Describe Disease Tolerance?  PLoS Biol. 14(4): e1002435.
FlyBase ID
FBrf0232043
Publication Type
Research paper
Abstract

The study of infectious disease has been aided by model organisms, which have helped to elucidate molecular mechanisms and contributed to the development of new treatments; however, the lack of a conceptual framework for unifying findings across models, combined with host variability, has impeded progress and translation. Here, we fill this gap with a simple graphical and mathematical framework to study disease tolerance, the dose response curve relating health to microbe load; this approach helped uncover parameters that were previously overlooked. Using a model experimental system in which we challenged Drosophila melanogaster with the pathogen Listeria monocytogenes, we tested this framework, finding that microbe growth, the immune response, and disease tolerance were all well represented by sigmoid models. As we altered the system by varying host or pathogen genetics, disease tolerance varied, as we would expect if it was indeed governed by parameters controlling the sensitivity of the system (the number of bacteria required to trigger a response) and maximal effect size according to a logistic equation. Though either the pathogen or host immune response or both together could theoretically be the proximal cause of pathology that killed the flies, we found that the pathogen, but not the immune response, drove damage in this model. With this new understanding of the circuitry controlling disease tolerance, we can now propose better ways of choosing, combining, and developing treatments.

PubMed ID
PubMed Central ID
PMC4835111 (PMC) (EuropePMC)
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Secondary IDs
    Language of Publication
    English
    Additional Languages of Abstract
    Parent Publication
    Publication Type
    Journal
    Abbreviation
    PLoS Biol.
    Title
    PLoS Biology
    Publication Year
    2003-
    ISBN/ISSN
    1545-7885 1544-9173
    Data From Reference
    Alleles (4)
    Genes (11)