Spearman Rank Correlations between the RAAA of organisms and environments.

<p>Asterisks represent significance at <i>p</i><0.01 (**) and <i>p</i><0.001 (***).</p

Characterization of different environments by their relative amino acid composition.

<p>A) scatter plot by Principal Component Analysis according to the type of environment; B) Hierarchical clustering analysis. The length of branches represents the degree of dissimilarity between clusters. The x-axis of the heat map represents the 20 amino acids by alphabetical order of the three-letter code name. Determinations of Asp/Asn and Glu/Gln were considered together for the analysis, because environmental measurements did not distinguish between the two amino acids in the pairs. The y- axis of the heatmap represents the individual environments where amino acid abundance was determined. Over- and under-representation of amino acid residues in each environment are represented in green and red colored squares, respectively.</p

Relative amino acid composition, weighted by δ index, of each organism plotted against average GC content.

<p>Relative amino acid composition, weighted by δ index, of each organism plotted against average GC content.</p

Characterization of the relative amino acid composition of the proteomes from different organisms.

<p>A) scatter plot by Principal Component Analysis according to the type of environment; B) Hierarchical clustering analysis. The length of branches represents the degree of dissimilarity between clusters. The x-axis of the heat map represents the 20 amino acids by alphabetical order of the three-letter code name. The y- axis of the heatmap represents the individual organisms where amino acid abundance was estimated. Over- and under-representation of amino acid residues in each organism are represented in green and red colored squares, respectively.</p

Linear regression models for the effect of GC content, Phylogeny and Habitat on the relative cellular amino acid abundance.

1<p>*** <i>p</i><0.001; n.s., not significant.</p

Average environmental relative amino acid abundance (eRAAA) across habitats calculated from the literature.

<p>Environmental determinations of Asp/Asn and Glu/Gln did not distinguish between the two amino acids in the pairs, therefore they were considered together for the analysis.</p

Spearman rank correlation coefficients between estimated amino acid compositions (based on CAI and δ predictors) and experimentally-determined amino acid abundances.

<p>Values in bold indicate the strongest correlation.</p>1<p>ƒaa indicates unweighted amino acid frequency in the complete predicted proteome of an organism.</p>2<p>*** <i>p</i><0.001.</p

Percentage of parameter space where bistable responses are possible^a.

a<p>Some bidimensional sections of the multidimensional parameter space of bistability are shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031095#pone.0031095.s002" target="_blank">Figure S2</a>. The results show that in TCS with a bifunctional SK, both a TC_SK and a TC_RR cause a decrease in the size of the parametric region of bistability, with one exception: Model C has a larger parametric region of bistability when the signaling target is SK autophosphorylation (k₁). However, in systems with a monofunctional SK, a TCSK causes an increase and a TCRR causes a decrease in the size of the parametric region of bistability if the environment modulates the SK dephosphorylation (k₂). A|B stands for Model A controlled for Model B. A|C stands for Model A controlled for Model C.</p

Steady state signal-response curves for the various TCS modules.

<p>Each plot shows the steady state levels of the phosphorylated RR in the y axis at different values of the signal k₁ (SK autophosphorylation rate constant) or k₂ (SKP dephosphorylation rate constant) in the x axis. When the signal modulates SK dephosphorylation (changes in k₂), the system behaves symmetrically to when SK phosphorylation (changes in k₁) is modulated. In the first case, increases in signal intensity cause the fraction of RRP to decrease, while in the latter, increases in signal intensity cause the fraction of RRP to increase. A, C, E: Response curves of TCS modules with monofunctional sensor. B, D, F: Response curves of TCS modules with bifunctional sensor. A, B, Response curves of Model A. C, D: Mathematically controlled comparison between the response curves of Model B and those of Model A. E, F: Mathematically controlled comparison between the response curves of Model C and those of Model A. Mathematical controls are implemented to make sure that the differences in response between the alternative modules are due to the presence of third component and not to other spurious differences.</p

Percentage of parameter space where a bistable response is possible for Models A, B, and C^a.

a<p>A|B stands for Model A controlled for Model B. A|C stands for Model A controlled for Model C.</p><p>k_i: kinetic constants for the reactions in the systems shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031095#pone-0031095-g001" target="_blank">Figure 1</a>. SKt: total concentration of SK. RRt: total concentration of RR. TCt: total concentration of third component protein. The parameter space for k_i,k_j, and k_k was scanned between absolute values of 10⁻⁶ and 10 for each of the parameters. Sampling was uniform in logarithmic space.</p>b<p>Percentage of the parameter space of k_i, k_j and k_k where bistability is found for Models A, B, and C respectively.</p>c<p>Percentage of the parameter space where bistability is found in Model A controlled for B and for C, respectively.</p><p>NA Non Applicable. Mono functional systems have k₈ = 0. The concentration of TC = 0 in Model A. Model A can not be scanned with respect to the concentration of SK in the controlled comparisons, because SK is independently fixed to make the dynamical response of Model A more similar to those of Models B and C.</p