Spatially-resolved metabolic cooperativity within dense bacterial colonies.

Area of Science:

• Microbiology
• Systems Biology
• Computational Biology

Background:

• Cellular metabolism and metabolite exchange drive divergent behaviors in microbial colonies.
• Understanding cell subpopulation interactions requires advanced metabolic modeling and extracellular space description.

Purpose of the Study:

• To model and describe position-dependent metabolism and growth in Escherichia coli colonies.
• To investigate cooperative metabolic interactions within bacterial colonies.

Main Methods:

• Hybrid simulation integrating 3D reaction-diffusion modeling with genome-scale flux balance analysis (FBA).
• In silico modeling of Escherichia coli colonies grown on glucose minimal agar.
• Imaging experiments with fluorescently-labeled E. coli strains.

Main Results:

• Cell position within the colony dictates metabolism; outer cells grow rapidly, inner cells become dormant.
• A novel, cooperative acetate crossfeeding mechanism links spatially distinct subpopulations.
• Experimental fluorescence patterns confirm upregulated acetate crossfeeding genes, aligning with model predictions.
• Simulated and experimental colony height-to-width ratios show good agreement over 48 hours.

Conclusions:

• The developed modeling paradigm accurately reproduces known E. coli colony growth features and predicts a novel interaction.
• Identified acetate crossfeeding has analogues in cancer metabolism (lactate crossfeeding).
• The methodology is anticipated for future application in modeling tissues and tumors.