Understanding Lactobacillus paracasei and Streptococcus oralis Biofilm Interactions through Agent-Based Modeling

Area of Science:

• Microbiology
• Computational Biology
• Biofilm Research

Background:

• Commensal Lactobacillus species promote health, while some Streptococcus species can enhance pathogenicity.
• Streptococcus oralis acts as an accessory pathogen, increasing Candida albicans virulence and promoting tissue-damaging biofilms.
• Lactobacillus species are known to inhibit the biofilm formation of various microbes, including Streptococcus species.

Purpose of the Study:

• To explore the in vitro biofilm interactions between Streptococcus oralis and Lactobacillus paracasei using computational modeling and live imaging.
• To investigate the mechanisms by which Lactobacillus paracasei influences Streptococcus oralis growth in biofilms.
• To leverage agent-based modeling and experimental data to understand multi-species biofilm dynamics relevant to mucosal health and disease.

Main Methods:

• Developed a computational agent-based model simulating space, oxygen, and glucose competition between S. oralis and L. paracasei.
• Created subsequent models incorporating L. paracasei secreted surfactant or growth inhibitor.
• Quantified bacterial growth in live biofilms and compared experimental results with model predictions.

Main Results:

• Initial models predicted higher S. oralis biomass than observed experimentally.
• Both simulated surfactant secretion and inhibitor secretion by L. paracasei affected S. oralis growth.
• Experimental data supported the hypothesis that L. paracasei secretes an inhibitor of S. oralis growth, though a surfactant mechanism was not entirely excluded.

Conclusions:

• Agent-based modeling and experimental synergy can effectively address complex multi-species biofilm interactions.
• Lactobacillus paracasei exhibits inhibitory effects on Streptococcus oralis within biofilms, potentially via secreted compounds.
• Understanding these interactions may lead to strategies for preventing or mitigating mucosal fungal infections.