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Using a Bacterial Pathogen to Probe for Cellular and Organismic-level Host Responses
08:38

Using a Bacterial Pathogen to Probe for Cellular and Organismic-level Host Responses

Published on: February 22, 2019

Pathogen interactions, population cycles, and phase shifts

Joanne Lello1, Rachel A Norman, Brian Boag

  • 1School of Biosciences, Cardiff University, Cardiff CF10 3TL, Wales, UK. lelloj@cardiff.ac.uk

The American Naturalist
|January 17, 2008
PubMed

Insights

Host immune memory can sustain pathogen interactions, even when pathogen levels are low. This immune memory can paradoxically strengthen interactions between out-of-phase pathogens, altering disease cycles.

Area of Science:

  • Ecology
  • Epidemiology
  • Immunology

Background:

  • Interspecific pathogen interactions significantly influence pathogen dynamics and control strategies.
  • Cyclic pathogen abundance patterns (e.g., seasonality) can lead to temporal asynchrony, potentially reducing interaction impacts.

Purpose of the Study:

  • To investigate the effects of cyclic abundance patterns on interspecific pathogen interactions using an extended mathematical model.
  • To explore the role of host immune memory in modulating these interactions.

Main Methods:

  • Extension of a previously published mathematical model to incorporate cyclic pathogen dynamics.
  • Analysis of model outputs to identify conditions under which interactions are maintained or altered.
  • Consideration of analogous predator-prey system dynamics.

Main Results:

  • Host immune memory can maintain the impact of pathogen interactions, irrespective of effector pathogen abundance.
  • Immune memory can paradoxically intensify interactions between temporally asynchronous pathogens.
  • Interspecific interactions can alter the temporal patterns of the affected pathogen species.

Conclusions:

  • Host immune memory is a critical factor in sustaining interspecific pathogen interactions, even under asynchronous conditions.
  • The findings have implications for understanding disease dynamics in natural systems and managing coinfections.
  • The model provides a framework for investigating ecological interactions analogous to predator-prey systems.

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