Cross-feeding Monod model and fit to linear frequency dependence

Monod model of a cross-feeding interaction, including dynamics of daily resource use and growth. Fits post-growth cycle relative frequencies to a linear parameterization of frequency dependent fitness

Black Queen Monod model and fit to linear frequency dependence

Monod model of a black queen interaction, including dynamics of daily resource use, toxin reduction, and growth. Fits post-growth cycle relative frequencies to a linear parameterization of frequency dependent fitness

nuoM competition data

Colony count data from 6-day competitions between admixtures of nuoM+ and nuoM- clones

Fit competition data to linear frequency dependence

Mathematica notebook that fits competition data to a linear paramaterization of frequency-dependent fitness

Methods.Means

This file has the precalculated means for each method at each time point. All of this can be calculated from the raw data file, but this makes things more convenient

Fit competition data to quadratic frequency dependence

Mathematica notebook that fits competition data to a quadratic paramaterization of frequency-dependent fitness

S and L competition data

Colony count data from 6-day and 12-day competitions between S and L clones

Methods.3.Forms

This file contains all the raw data for this manuscrip

Selected evolution experiments.

<p>* Mean calculated from four replicate populations</p><p>** Value estimated from figure</p><p>W_f is the fitness at the end of the evolution experiment.</p><p>W_i is the fitness at the start of the evolution experiment.</p><p>Selected evolution experiments.</p

A Comparison of Methods to Measure Fitness in <i>Escherichia coli</i>

<div><p>In order to characterize the dynamics of adaptation, it is important to be able to quantify how a population’s mean fitness changes over time. Such measurements are especially important in experimental studies of evolution using microbes. The Long-Term Evolution Experiment (LTEE) with <i>Escherichia coli</i> provides one such system in which mean fitness has been measured by competing derived and ancestral populations. The traditional method used to measure fitness in the LTEE and many similar experiments, though, is subject to a potential limitation. As the relative fitness of the two competitors diverges, the measurement error increases because the less-fit population becomes increasingly small and cannot be enumerated as precisely. Here, we present and employ two alternatives to the traditional method. One is based on reducing the fitness differential between the competitors by using a common reference competitor from an intermediate generation that has intermediate fitness; the other alternative increases the initial population size of the less-fit, ancestral competitor. We performed a total of 480 competitions to compare the statistical properties of estimates obtained using these alternative methods with those obtained using the traditional method for samples taken over 50,000 generations from one of the LTEE populations. On balance, neither alternative method yielded measurements that were more precise than the traditional method.</p></div