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Modeling and quantifying frequency-dependent fitness in microbial populations with cross-feeding interactions

Noah Ribeck, Richard E. Lenski
doi: https://doi.org/10.1101/012807
Noah Ribeck
1Department of Microbiology and Molecular Genetics
2BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, Michigan 48824
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Richard E. Lenski
1Department of Microbiology and Molecular Genetics
2BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, Michigan 48824
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Abstract

Coexistence of multiple populations by frequency-dependent selection is common in nature, and it often arises even in well-mixed experiments with microbes. If ecology is to be incorporated into models of population genetics, then it is important to represent accurately the functional form of frequency-dependent interactions. However, measuring this functional form is problematic for traditional fitness assays, which assume a constant fitness difference between competitors over the course of an assay. Here, we present a theoretical framework for measuring the functional form of frequency-dependent fitness by accounting for changes in abundance and relative fitness during a competition assay. Using two examples of ecological coexistence that arose in a long-term evolution experiment with Escherichia coli, we illustrate accurate quantification of the functional form of frequency-dependent relative fitness. Using a Monod-type model of growth dynamics, we show that two ecotypes in a typical cross-feeding interaction—such as when one bacterial population uses a byproduct generated by another—yields relative fitness that is linear with relative frequency.

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Posted December 16, 2014.
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Modeling and quantifying frequency-dependent fitness in microbial populations with cross-feeding interactions
Noah Ribeck, Richard E. Lenski
bioRxiv 012807; doi: https://doi.org/10.1101/012807
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Modeling and quantifying frequency-dependent fitness in microbial populations with cross-feeding interactions
Noah Ribeck, Richard E. Lenski
bioRxiv 012807; doi: https://doi.org/10.1101/012807

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