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An optimised GAS-pharyngeal cell biofilm model.

Heema K N Vyas1,2, Jason D McArthur2, Martina L Sanderson-Smith3,4

  • 1Illawarra Health and Medical Research Institute, Wollongong, NSW, Australia.

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Group A Streptococcus (GAS) infections cause millions of deaths annually. This study developed a novel host cell model to effectively study GAS biofilm formation in a simulated host environment.

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Area of Science:

  • Microbiology
  • Pathogen Biology
  • Infectious Diseases

Background:

  • Group A Streptococcus (GAS) is a significant human pathogen responsible for millions of infections and deaths globally.
  • Biofilm formation by GAS is linked to pharyngeal and dermal infections, but previous in vitro studies often used abiotic surfaces, failing to mimic host conditions.
  • Understanding GAS biofilm development on host tissues is crucial for developing effective treatments.

Purpose of the Study:

  • To optimize a host cell-GAS model for studying biofilm formation in a relevant physiological environment.
  • To refine biofilm quantification methods for detecting delicate GAS biofilms.
  • To characterize the structure of GAS biofilms formed in the host cell model.

Main Methods:

  • Development and optimization of a host cell-GAS co-culture model.
  • Adaptation of the crystal violet biofilm biomass assay for enhanced sensitivity and reproducibility.
  • Application of Scanning Electron Microscopy (SEM) for visualizing biofilm structure.
  • Determination of optimal GAS biofilm growth period (72 hours).

Main Results:

  • The optimized host cell-GAS model successfully supports the growth of GAS biofilms from various M-types.
  • Modified crystal violet assay with methanol fixation allows reproducible detection of robust and durable GAS biofilms.
  • SEM imaging revealed three-dimensional aggregated structures of GAS cocci chains embedded in an EPS matrix.
  • A 72-hour incubation period was identified as optimal for detectable biofilm biomass.

Conclusions:

  • An effective GAS pharyngeal cell model was established for studying long-term biofilm formation.
  • The model generates biofilms that closely resemble in vivo structures, providing a more accurate representation of infection dynamics.
  • This model offers a valuable tool for investigating GAS pathogenesis and evaluating anti-biofilm strategies.