Observation of Virions by Electron Microscopy after 8 D of Incubation at 37 °C

<p>The table gives the relative variation in the proportion of broken virions, as measured by electron microscopy, of more than a hundred particles, as well as the variation in the number of viable phages measured by plating on a susceptible host. Both observations have been made on the same samples. For each type of phage, the proportion of broken virions is significantly higher after incubation, and the variation in broken-virion particles measured by electron microscopy is similar to the variation in the number of infectious phages.</p

Actual Mortality Rate against Predicted Decay Rate by a Model of Multiple Regression Using the Decay Rate, <i>ρ _pack, </i> and the Capsid Surfacic mass

<p>The estimates were identified by a stepwise regression among all parameters used. The order of entrance of parameters is an increasing function of <i>p</i>-values. The model explains 91% of the variance of the mortality rate. </p

Correlations between Phage Life History Traits and Phage Particle Characteristics

<div><p>(A) Positive correlation between mortality rate and <i>ρ_pack, </i> the volumic density of the packaged DNA (Linear regression, <i>R²</i> = 0.67 and <i>p</i> = 0.001). <i>ρ_pack</i> has been calculated only for phages with a double-stranded DNA genome, because the volumes of single-strand DNA and double-strand RNA are different than the volume of double-stranded DNA. <i>ρ_pack</i> is calculated by dividing the volume of the genome by the internal volume of the capsid. </p> <p>(B) Negative correlation between mortality rate and the surfacic mass of the capsid, calculated by dividing the capsid molecular weight by capsid surface (linear regression, <i>R²</i> = 0.35 and <i>p</i> = 0.031). Because the surfacic mass is an estimation of the thickness of the capsid, it should be related to its strength. Some phages are not represented because data are not available, or in the case of M13, because it possesses a helical geometry, and thus the constraints on the capsid are very different than for icosahedral phages. </p> <p>(C) Negative correlation between the multiplication rate and the surfacic mass of the capsid (linear regression, <i>R²</i> = 0.46 and <i>p</i> = 0.011). </p> <p>(D) Positive correlation between the mortality rate and the multiplication rate. The log–log scale is for a better visualization of the results and does not modify the significance of the correlation. The line shows a linear regression characterized by <i>R²</i> = 0.73 and <i>p</i> < 0.0001. Each measure was repeated at least three times independently for the determination of the multiplication and mortality rates. </p></div

Representation of Various Phage Parameters in a PCA

<p>We can notice two groups of parameters: virion structural characteristics (green) and life history traits of phages (red). Within each group, parameters correlate highly with a nonparametric Spearman Rho test. For others correlations, see text and <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0040193#pbio-0040193-g004" target="_blank">Figure 4</a>. </p

Potential Relations between Phage Survival, Multiplication Rate, and Capsid Characteristics

<p>Evolutionary theory predicts that a high decay rate is associated with an elevated multiplication rate. Forces exerted on the capsid might lead to the rupture of the head of phages, leading to their inactivation. The multiplication rate of phages is possibly associated with properties of phage particles as a consequence of kinetic and energetic considerations involved in the assembly of the capsid and/or the encapsidation of the genome.</p

Mortality Rates of Phage Particles

<div><p>(A) Representative survival curves of phage particles maintained in LB at 37 °C, in the absence of host cells. Phage stocks are obtained by infecting growing E. coli host culture followed by cell elimination. Lines show exponential regressions, with <i>R²</i> values ranging from 0.87 for P2 to 0.99 for MS2. The mortality rate is not influenced by the initial concentration of the phage populations (unpublished data). Each experiment was repeated at least three times independently. </p> <p>(B) Relation between mortality rate and temperature. Symbols are the same as in (A). Lines show exponential fits between the mortality rate and 1/T. <i>R²</i> values range from 0.937 for Mu to 0.999 for P2. </p></div

Cheater invasion dynamics in phenotypically similar starting populations.

<p>In the main figure each line represents the average secretion, over time, of replicate populations started from the same ancestor. For clarity, we did not include the standard error of each group of replicate populations. The insert figure shows all replicate populations for the two most extreme population groups, zoomed in on the time period of interest for our analyses. Specifically, of all the population groups sharing a common ancestor, the blue populations had the highest and red the lowest average secretion between generation and generation . Note that average secretion in the inset represents the average secretion within each population, whilst in the main figure it is the average of the secretion of all the individuals from the replicate populations that share the same ancestor.</p

Genetic architecture associations after generation of <i>de novo</i> evolution of cooperation, at (A) high, c = and (B) low, c = secretion cost.

<p>In both cases, we quantified the presence of operons or overlaps between secretion genes and metabolic genes (S vs M) as well as between metabolic genes and other metabolic genes (M vs M). Genes were partitioned in four categories, labeled as in the <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003339#pcbi-1003339-g004" target="_blank">Fig. 4</a>: sharing a promoter (an operon) without overlapping with a metabolic gene (dark blue), overlapping and sharing an operon with a metabolic gene (light blue), overlapping without sharing an operon with a metabolic gene (green), not sharing an operon nor overlapping with any metabolic gene (red). Error bars represent plus and minus one standard error of the mean for the fifty replicate populations and their color corresponds to the genetic architecture category they relate to.</p

Secretion genes at generation and at generation partitioned between four categories:

<p>(a) sharing a promoter ( being on the same operon) without overlapping with a metabolic gene (dark blue), (b) overlapping and sharing an operon with a metabolic gene (light blue), (c) overlapping without sharing an operon with a metabolic gene (green), (d) neither sharing an operon nor overlapping with a metabolic gene (red). Error bars represent one standard error of the mean (fifty original cooperators). The color of the error bars corresponds to the genetic architecture category which they relate to.</p

Aevol genetic code.

<p>Here we use an example of a functioning gene from an Aevol individual to explain the transcription and the translation processes. The gene is flanked by a promoter and terminator regions and preceded by a ribosome binding site (RBS). The codons for mean position, the width, and the height of the protein are identified, transformed into Gray code using the Genetic code table (box on the right), and finally scaled and normalized, as we summarize in the box on the left and describe in more detail in the Methods. Note that a gene with re-shuffled codons, for example H1 H1 M1 M1 M0 W1 W0 W1, would encode exactly the same protein. START codon may occasionally be found inside a gene, in which case it is interpreted as H0. The promoter differs from the consensus sequence by base out of the maximal differences allowed, giving it a efficiency.</p