Solving polymicrobial puzzles: evolutionary dynamics and future directions

Area of Science:

• Microbiology
• Evolutionary Biology
• Infectious Diseases

Background:

• Polymicrobial infections, involving multiple microorganisms, present unique challenges compared to monomicrobial infections.
• Understanding the complex interactions within these microbial communities, including virulence and antibiotic susceptibility, has long puzzled scientists.
• Existing literature on inter-bacterial interactions lacks synchronization, hindering comprehensive analysis.

Purpose of the Study:

• To synthesize the current understanding of inter-bacterial interactions in clinically relevant polymicrobial infections.
• To introduce and apply the concept of evolutionary dynamics (ED) as a unifying framework for analyzing these interactions.
• To explore innovative strategies incorporating ED for controlling polymicrobial infections.

Main Methods:

• Review of existing literature on polymicrobial infections and inter-bacterial interactions.
• Integration of game theory and eco-evolutionary dynamics to form evolutionary dynamics (ED).
• Application of ED to analyze niche colonization dynamics of specific bacteria, such as *S. aureus* and *P. aeruginosa*.

Main Results:

• Evolutionary dynamics (ED) offer a robust approach to analyze complex proteomic interactions like metabolic syntropy and niche segregation.
• ED can synchronize and mold raw data from inter-bacterial interactions.
• Analysis of clinically relevant polymicrobial infections (chronic wounds, CAUTI, otitis media, dental caries) through the lens of ED.

Conclusions:

• Evolutionary dynamics (ED) provide a crucial framework for understanding and managing polymicrobial infections.
• The integration of ED with existing data can reveal insights into bacterial competition and colonization.
• This approach paves the way for innovative strategies to combat polymicrobial infections.