The advantage of cross-feeding changes with initial densities of the bacteria (based on simulations of (<i>1.1</i>)).

<p>As in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0004115#pone-0004115-g001" target="_blank">fig. 1</a>, the cross-feeding X' genotype outgrows the non-cross-feeding X at intermediate densities. However, the times at which X' exceeds X and the magnitude of the excess depend on starting density. Curves are labeled according to the starting densities, the same for all genotypes, X, X' and Y, within a trial. The advantage of X' is diminished at high and low initial densities. In contrast to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0004115#pone-0004115-g001" target="_blank">fig. 1</a>, the curves here depict only the excess of X' over X during a run (showing <i>X'</i>–<i>X</i>, where ever that value exceeds zero). The curve for an initial density of 0.0001 reveals a slight advantage of cross-feeding for only 100 time units. The curve for an initial density of 1 reveals both the largest advantage of cross-feeding and the longest benefit (425 time units). The curve for an initial density of 10 reveals a modest advantage of cross-feeding spanning 275 time units. Parameters for Y were r_y = 0.011, and b_yx = 0.01; for X' were r_x = 0, and b_xy = 0.01; for X were r_x = 0.008, and b_xy = 0. K = 10,000 for all runs.</p

Simulations of two-species populations reveal the three phases of selection (based on equations <i>1.1</i>).

<p>The top level shows the dynamical trajectories of isolated populations of two (X,Y) genotype pairs differing in the level of cross-feeding provided by the X genotype; X does not cross-feed but X' does cross-feed to Y. Y cross feeds to X at the same level in both pairs, so the parameters of Y are the same in both simulations. The X and X' types are both represented by the curves marked by symbols (filled squares for <i>X</i>, open circles for <i>X'</i>), whereas the curves for type Y have no symbols (top level). The middle panel compares in the same graph the densities achieved by X and X', revealing that the cross-feeding X' outgrows X only at intermediate densities; the zone in which <i>X'</i> exceeds <i>X</i> is indicated by the vertical bars. The lower panel shows on an expanded vertical scale that X outgrows X' at low densities despite its later disadvantage. Densities of X and Y were both started at 0.01, with and . In the simulation illustrated on the left and . On the right and . Carrying capacity (<i>K</i>) was set at 10,000.</p

Ethionine resistant <i>metJ</i> and evolved methionine producing <i>metA</i> alleles are sufficient to recapitulate cooperative behavior in <i>S</i>. <i>enterica</i>.

<p>Error bars represent standard error of three biological replicates. Gray indicates either the original strain, or the reconstructed strain containing the <i>metA</i> and <i>metJ</i> alleles, such that the rest of their genome is the wild-type background. Differences in wild-type growth rates represent day-to-day variation in growth conditions.</p

<i>S</i>. <i>enterica</i> producers evolved from ethionine-resistant strains that feature mutations in <i>metJ</i>.

<p>a) <i>S</i>. <i>enterica</i> ethionine resistant strains (R strains) were evolved from wild-type LT2 and 14028s strains, and then co-cultured with <i>E</i>. <i>coli</i> methionine auxotrophs on lactose minimal media. Adaptive methionine excretion by evolved cooperators enabled growth of <i>E</i>. <i>coli</i> Δ<i>metB</i>. Sequencing revealed parallel mutational targets in each strain during both selection steps: <i>metJ</i> during selection for ethionine resistance (detailed in 1b) and <i>metA</i> during selection for cooperative methionine production (detailed in [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0174345#pone.0174345.ref014" target="_blank">14</a>]). b) A diagram of <i>metJ</i> shows the mutations in R1 (IS insertion), R2 (G^-54➙A mutation in promoter), and R3 (P11S residue substitution) that arose during selection for resistance to ethionine.</p

Individual and consortia growth rates for wild-type, ethionine resistant, and evolved strains.

<p>Individual growth of <i>S</i>. <i>enterica</i> strains was measured in galactose minimal media, while consortia growth rates represents <i>S</i>. <i>enterica</i> strains co-cultured with <i>E</i>. <i>coli</i> Δ<i>metB</i> in lactose minimal media. <i>S</i>. <i>enterica</i> LT2 is the wild-type ancestor of R1, which evolved into R1P1. <i>S</i>. <i>enterica</i> 14028s is the wild-type ancestor of R2 and R3, which each evolved into R2P4 and R3P5, respectively. Error bars represent standard error of three biological replicates.</p

The effect of <i>metJ</i> alleles on cooperation in different <i>S</i>. <i>enterica</i> genetic backgrounds.

<p>Mean growth rate of each cooperator with no <i>metJ</i> substitution was subtracted from measured consortia growth rates with substituted <i>metJ</i>. Error bars represent standard error of three biological replicates.</p

Measures of optimality and predictability after adaptation of gene knockouts on glucose for ∼600–800 generations.

<p>A,B) The % optimality of the ancestor (black) and evolved isolates (grey); C,D) distance to optimal flux distribution for FBA-predictions based upon BM/S (A,C) or ATP/S (B,D).</p

Evolutionary change in % optimality versus initial % optimality of the ancestor across data sets for BM/S.

<p>Error bars represent standard errors between evolved populations.</p

Evolution of metabolic fluxes and measures of optimality and predictability.

<p>We consider three ways to analyze changes in metabolism that relate an ancestor (Anc, blue) to an evolved isolate (E_i, green) in regard to an FBA-predicted optimum (Opt, red). A) Evolution of metabolic fluxes can be evaluated from the perspective of changes in proximity to the theoretical maximum for a given optimality criterion (Δ% Optimality). B) A vector of flux ratios defines a position in multi-dimensional flux space. One can then consider the relative Euclidian distance of a given evolved population in this space from its optimum (D_EO) compared to that of an ancestor from its optimum (D_AO; plotted as log(D_EO/D_AO)). C) At the most detailed level, one can compare the FBA-predicted value for a given flux ratio versus that observed via ¹³C labeling.</p

Evolved changes in central carbon metabolism for the LTEE populations after 50,000 generations of adaptation on glucose.

<p>A) The flux pathways measured for the LTEE lines are denoted with numbers and red arrows. The genes knocked out in the knockout data set and the entry point of lactate into the network are both indicated. B) A heat map of the difference between evolved and ancestral flux ratios from the LTEE populations. The right side indicates flux ratios predicted for the ancestral line according to each optimality criterion. The number of the flux ratio corresponds to the numbered pathways in A. Single asterisks denote significant changes as calculated by ANOVA, double asterisks are also significant by Tukey-HD.</p