Game theoretical modelling of survival strategies of Candida albicans inside macrophages

S Hummert1, C Hummert, A Schröter

  • 1Friedrich-Schiller University, School of Biology and Pharmaceutics, Ernst-Abbe-Platz 2, D-07743 Jena, Germany. sabine.hummert@uni-jena.de

Insights

This study models Candida albicans strategies within macrophages. Depending on costs, the fungus either pierces macrophages or a mix of strategies emerges, aligning with experimental data.

Area of Science:

  • Mycology
  • Immunology
  • Mathematical Biology

Background:

  • Candida albicans is a polymorphic fungus and opportunistic human pathogen.
  • Phagocytes, such as neutrophils and macrophages, are key in host defense against C. albicans infections.
  • Understanding pathogen-host interactions at a cellular level is crucial for developing effective treatments.

Purpose of the Study:

  • To develop game theoretical models simulating the behavior of Candida albicans within macrophages.
  • To analyze the strategies of C. albicans: 'silencing' to avoid lysis and 'piercing' to escape by forming hyphae.
  • To investigate the influence of the SAP gene family and secreted proteinases on these strategies.

Main Methods:

  • Development of two game theoretical models to represent C. albicans interactions within macrophages.
  • Analysis of two distinct strategies: 'silencing' (avoiding lysis) and 'piercing' (hyphal escape).
  • Integration of existing research on the SAP gene family and Sap proteins into the model.

Main Results:

  • Model outcomes depend on the relative costs of the two strategies.
  • Low cost differences lead to a 'piercing' strategy dominance.
  • High cost differences result in a stable mixed population of 'piercing' and 'silencing' cells.
  • The role of SAP genes and proteins is linked to the cost parameters.

Conclusions:

  • The game theoretical models provide insights into C. albicans survival strategies within macrophages.
  • Model predictions align with experimental findings from other research groups.
  • The study suggests that model parameters can be estimated from experimental data, facilitating further research.