bioRxivMicrobiology
Understanding Lactobacillus paracasei and Streptococcus oralis biofilm interactions through agent-based modeling
L. Archambault, S. Koshy-Chenthittayil, A. Thompson, A. Dongari-Bagtzoglou, R. Laubenbacher, P. Mendes
Abstract
As common commensals residing on mucosal tissues, Lactobacillus species are known to encourage health, while recent findings highlight the pathogenic roles of Streptococcus species in these environments. In this study we used a combination of in vivo imaging experiments and computational modeling to explore biofilm interactions between Streptococcus oralis, an accessory pathogen in oral Candidiasis, and Lactobacillus paracasei, an organism with known probiotic properties. A computational agent-based model was created where the two species only interact by competing for space and nutrients. Quantification of bacterial growth in live biofilms indicated that S. oralis biomass and cell numbers were much lower than predicted by the model. Two subsequent models were then created to examine more complex interactions between these species, one where L. paracasei secretes a surfactant, and another where L. paracasei secretes an inhibitor of S. oralis growth. Further biofilm experiments support the hypothesis that L. paracasei may secrete an inhibitor of S. oralis growth, although they do not exclude that a surfactant could also be involved. This contribution shows how agent-based modeling and experiments can be used in synergy to address multiple species biofilm interactions, with important roles in mucosal health and disease. IMPORTANCEWe previously discovered a role of the oral commensal Streptococcus oralis as an accessory pathogen. S. oralis increases the virulence of Candida albicans infections in murine oral candidiasis and epithelial cell models through mechanisms which promote the formation of tissue-damaging biofilms. Lactobacillus species have known inhibitory effects on biofilm formation of many microbes, including Streptococcus species. Agent-based modeling has great advantages as a means of exploring multifaceted relationships between organisms in complex environments such as biofilms. Here we used an iterative collaborative process between experimentation and modeling to reveal aspects of the mostly unexplored relationship between S. oralis and L. paracasei in biofilm growth. The inhibitory nature of L. paracasei on S. oralis in biofilms may be exploited as a means of preventing or alleviating mucosal fungal infections.
- organism: human
- assay: imaging
- research focus: cell-cell communication
- approach: deep learning
- approach: statistical model
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