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A within-host infection model to explore tolerance and resistance

Pierre D. M. Lafont, Christine Lauzeral, Nathalie Parthuisot, Christian Faucher, View ORCID ProfileDavid Duneau, Jean-Baptiste Ferdy
doi: https://doi.org/10.1101/2021.10.19.464998
Pierre D. M. Lafont
1Évolution et Diversité Biologique UMR 5174 CNRS-UPS, Université Paul Sabatier, F-31062 Toulouse cedex 9, France
2Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3FL, United Kingdom
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Christine Lauzeral
1Évolution et Diversité Biologique UMR 5174 CNRS-UPS, Université Paul Sabatier, F-31062 Toulouse cedex 9, France
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Nathalie Parthuisot
1Évolution et Diversité Biologique UMR 5174 CNRS-UPS, Université Paul Sabatier, F-31062 Toulouse cedex 9, France
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Christian Faucher
1Évolution et Diversité Biologique UMR 5174 CNRS-UPS, Université Paul Sabatier, F-31062 Toulouse cedex 9, France
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David Duneau
1Évolution et Diversité Biologique UMR 5174 CNRS-UPS, Université Paul Sabatier, F-31062 Toulouse cedex 9, France
3Instituto Gulbenkian de Ciência, Oeiras, Portugal
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  • For correspondence: david.duneau@gmail.com
Jean-Baptiste Ferdy
1Évolution et Diversité Biologique UMR 5174 CNRS-UPS, Université Paul Sabatier, F-31062 Toulouse cedex 9, France
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Abstract

How are some individuals surviving infections while others die? The answer lies in how infected individuals invest into controlling pathogen proliferation and mitigating damage, two strategies respectively called resistance and disease tolerance. Pathogen within-host dynamics (WHD), influenced by resistance, and its connection to host survival, determined by tolerance, decide the infection outcome. To grasp these intricate effects of resistance and tolerance, we used a deterministic theoretical model where pathogens interact with the immune system of a host. The model describes the positive and negative regulation of the immune response, consider the way damage accumulate during the infection and predicts WHD. When chronic, infections stabilize at a Set-Point Pathogen Load (SPPL). Our model predicts that this situation can be transient, the SPPL being then a predictor of life span which depends on initial condition (e.g. inoculum). When stable, the SPPL is rather diagnostic of non lethal chronic infections. In lethal infections, hosts die at a Pathogen Load Upon Death (PLUD) which is almost independent from the initial conditions. As the SPPL, the PLUD is affected by both resistance and tolerance but we demonstrate that it can be used in conjunction with mortality measurement to distinguish the effect of disease tolerance from that of resistance. We validate empirically this new approach, using Drosophila, melanogaster and the pathogen Providencia rettgeri.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • ↵† david.duneau{at}gmail.com

  • ↵§ jean-baptiste.ferdy{at}univ-tlse3.fr

  • We updated the text.

  • https://plafont.shinyapps.io/WHD_app/

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted January 25, 2022.
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A within-host infection model to explore tolerance and resistance
Pierre D. M. Lafont, Christine Lauzeral, Nathalie Parthuisot, Christian Faucher, David Duneau, Jean-Baptiste Ferdy
bioRxiv 2021.10.19.464998; doi: https://doi.org/10.1101/2021.10.19.464998
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A within-host infection model to explore tolerance and resistance
Pierre D. M. Lafont, Christine Lauzeral, Nathalie Parthuisot, Christian Faucher, David Duneau, Jean-Baptiste Ferdy
bioRxiv 2021.10.19.464998; doi: https://doi.org/10.1101/2021.10.19.464998

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