A within-host infection model to explore tolerance and resistance

  1. David Duneau  Is a corresponding author
  2. Pierre DM Lafont
  3. Christine Lauzeral
  4. Nathalie Parthuisot
  5. Christian Faucher
  6. Xuerong Jin
  7. Nicolas Buchon
  8. Jean-Baptiste Ferdy  Is a corresponding author
  1. University of Edinburgh, United Kingdom
  2. University of Toulouse 3, France
  3. Cornell University, United States

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. We found that, as predicted by the model, hosts that were wounded or deficient of key antimicrobial peptides had a higher PLUD, while Catalase mutant hosts, likely to have a default in disease tolerance, had a lower PLUD.

Data availability

Details of the shiny application can be found on Zenodo at P. Lafont. (2024). Sydag/WHD\_shiny: Shiny\_WHD\_model (Main\_release). Zenodo. \href{https://doi.org/10.5281/zenodo.13309654}{https://doi.org/10.5281/zenodo.13309654}. Scripts and analyses are available via a Rmarkdown HTML file provided as supplementary file. Data are available as supplementary files.

The following data sets were generated

Article and author information

Author details

  1. David Duneau

    The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom
    For correspondence
    david.duneau@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8323-1511
  2. Pierre DM Lafont

    Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  3. Christine Lauzeral

    University of Toulouse 3, Toulouse, France
    Competing interests
    The authors declare that no competing interests exist.
  4. Nathalie Parthuisot

    University of Toulouse 3, Toulouse, France
    Competing interests
    The authors declare that no competing interests exist.
  5. Christian Faucher

    University of Toulouse 3, Toulouse, France
    Competing interests
    The authors declare that no competing interests exist.
  6. Xuerong Jin

    Department of Entomology, Cornell University, Ithaca, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0009-0000-2862-4075
  7. Nicolas Buchon

    Department of Entomology, Cornell University, Ithaca, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3636-8387
  8. Jean-Baptiste Ferdy

    University of Toulouse 3, Toulouse, France
    For correspondence
    jean-baptiste.ferdy@univ-tlse3.fr
    Competing interests
    The authors declare that no competing interests exist.

Funding

Agence Nationale de la Recherche (ANR- 10-LABX-41)

  • David Duneau

Agence Nationale de la Recherche (ANR-11-IDEX-0002-02)

  • Jean-Baptiste Ferdy

Agence Nationale de la Recherche (LIA BEEG-B)

  • David Duneau

National Institutes of Health (5R01AI148541-05)

  • Nicolas Buchon

National Science Foundation (IOS 1398682)

  • Nicolas Buchon

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2025, Duneau et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 252
    views
  • 60
    downloads
  • 1
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. David Duneau
  2. Pierre DM Lafont
  3. Christine Lauzeral
  4. Nathalie Parthuisot
  5. Christian Faucher
  6. Xuerong Jin
  7. Nicolas Buchon
  8. Jean-Baptiste Ferdy
(2025)
A within-host infection model to explore tolerance and resistance
eLife 14:e104052.
https://doi.org/10.7554/eLife.104052

Share this article

https://doi.org/10.7554/eLife.104052

Further reading

    1. Computational and Systems Biology
    2. Microbiology and Infectious Disease
    Saugat Poudel, Jason Hyun ... Bernhard O Palsson
    Research Article

    The Staphylococcus aureus clonal complex 8 (CC8) is made up of several subtypes with varying levels of clinical burden; from community-associated methicillin-resistant S. aureus USA300 strains to hospital-associated (HA-MRSA) USA500 strains and ancestral methicillin-susceptible (MSSA) strains. This phenotypic distribution within a single clonal complex makes CC8 an ideal clade to study the emergence of mutations important for antibiotic resistance and community spread. Gene-level analysis comparing USA300 against MSSA and HA-MRSA strains have revealed key horizontally acquired genes important for its rapid spread in the community. However, efforts to define the contributions of point mutations and indels have been confounded by strong linkage disequilibrium resulting from clonal propagation. To break down this confounding effect, we combined genetic association testing with a model of the transcriptional regulatory network (TRN) to find candidate mutations that may have led to changes in gene regulation. First, we used a De Bruijn graph genome-wide association study to enrich mutations unique to the USA300 lineages within CC8. Next, we reconstructed the TRN by using independent component analysis on 670 RNA-sequencing samples from USA300 and non-USA300 CC8 strains which predicted several genes with strain-specific altered expression patterns. Examination of the regulatory region of one of the genes enriched by both approaches, isdH, revealed a 38-bp deletion containing a Fur-binding site and a conserved single-nucleotide polymorphism which likely led to the altered expression levels in USA300 strains. Taken together, our results demonstrate the utility of reconstructed TRNs to address the limits of genetic approaches when studying emerging pathogenic strains.

    1. Immunology and Inflammation
    2. Microbiology and Infectious Disease
    Malika Hale, Kennidy K Takehara ... Marion Pepper
    Research Article

    Pseudomonas aeruginosa (PA) is an opportunistic, frequently multidrug-resistant pathogen that can cause severe infections in hospitalized patients. Antibodies against the PA virulence factor, PcrV, protect from death and disease in a variety of animal models. However, clinical trials of PcrV-binding antibody-based products have thus far failed to demonstrate benefit. Prior candidates were derivations of antibodies identified using protein-immunized animal systems and required extensive engineering to optimize binding and/or reduce immunogenicity. Of note, PA infections are common in people with cystic fibrosis (pwCF), who are generally believed to mount normal adaptive immune responses. Here, we utilized a tetramer reagent to detect and isolate PcrV-specific B cells in pwCF and, via single-cell sorting and paired-chain sequencing, identified the B cell receptor (BCR) variable region sequences that confer PcrV-specificity. We derived multiple high affinity anti-PcrV monoclonal antibodies (mAbs) from PcrV-specific B cells across three donors, including mAbs that exhibit potent anti-PA activity in a murine pneumonia model. This robust strategy for mAb discovery expands what is known about PA-specific B cells in pwCF and yields novel mAbs with potential for future clinical use.