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Rethinking the Choice Behavior of Sugar Metabolism in Bacteria
1R.F. Smith School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY 14853.
Microbial growth is modeled as an economic decision, where cells allocate resources to enzymes like a consumer choosing products. This explains why microbes often consume one food source before another, a phenomenon called diauxic growth.
Area of Science:
- Microbial Physiology
- Biochemical Engineering
- Systems Biology
Background:
- The cybernetic model explains microbial growth by resource allocation for enzyme synthesis.
- Previous models lacked an explicit economic framework for the cell's decision-making process.
- The optimality of the matching rule was established, but the precise objective and constraints were undefined.
Purpose of the Study:
- To formulate the cybernetic enzyme-synthesis control as an explicit economic decision problem.
- To recast microbial resource allocation as a linear programming problem from microeconomic theory.
- To elucidate the economic basis for sequential versus simultaneous substrate utilization.
Main Methods:
- The cell's proteome budget is treated as a constraint in a linear program (LP).
- Growth utility is maximized subject to the proteome budget, modeled as a linear function.
- LP solutions are analyzed geometrically to determine optimal enzyme allocation strategies.
Main Results:
- The linear programming approach reveals that cells allocate their entire proteome to the most profitable substrate (corner solution), leading to diauxic growth.
- Simultaneous substrate use occurs only in a degenerate case where substrate profitability is equal.
- The LP-derived cybernetic variables accurately predicted the diauxic and triauxic batch growth of *Klebsiella oxytoca*.
Conclusions:
- Sequential substrate use is the standard outcome of growth maximization when resources are perfectly substitutable.
- Simultaneous substrate utilization is a special case arising from equal substrate profitability.
- The economic decision framework provides a robust explanation for observed microbial growth patterns.
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