The <i>E. coli</i> running speed <i>vs</i> the chemoattractant concentrations.

<p>As in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004974#pcbi.1004974.g002" target="_blank">Fig 2</a>, the three curves refer to serine (red), aspartate (blue) or aspartate with a background of 30<i>μ</i>M of serine (green). The mean value is calculated by averaging over the population of bacteria and error bars represent the standard deviation of the velocity distribution over the population.</p

The progression of bacteria in the lateral channels.

<p>The graphs show at different times the so-called progression function, i.e. the distribution function of the number of bacteria cumulated from the position indicated on the abscissae up to the end of the channels on the side of the reservoirs. Curves were obtained using five different experiments. Panels A, B and C show the progression function for a gradient of aspartate, of serine, of aspartate with a background of serine, respectively. All the gradients go from 0 (at the entry of the channel) to 1mM.</p

Variation of the bacterial running time with respect to the chemoattractant concentrations.

<p>The curves refer to different concentrations of serine (red), aspartate (blue) or aspartate with a background of 30<i>μ</i>M of serine (green). Times are normalized to the average running time (whence a non-dimensional quantity on the <i>y</i>-axis) in the absence of any chemoattractant, whose average over the bacterial population is ≃1.15s. Run times are calculated by averaging over at least three different experiments and error bars represent the error on the mean. The loss of precise adaptation for the green and the red curves is clearly visible. Note also that the value of the green curve at the lowest aspartate concentration is consistent with the value of the red curve at 30<i>μ</i>M, as expected by the fact that the serine background becomes dominant.</p

The experimental setup and raw images of bacteria running in the channels.

<p><b>A.</b> Illustration of the microfluidic setup where bacterial speed races take place. Reservoirs were filled with the appropriate concentration of chemoattractants and let diffuse through the lateral channels so as to establish linear gradients of chemoattractants in equilibrium with the flow of motility medium applied in the injection channel. Bacteria were then inserted into the injection channel and a fraction of them climb gradients of chemoattractants in the lateral channels. <b>B.</b> A typical stitched fluorescence image of a channel. A sequence of 20 images (exposure time of 200ms) were superimposed and then stitched together. On the extreme left, it is shown the injection channels, where the density of bacteria is the highest, while successive positions along the lateral channel are presented moving from the left to the right of the panel. <b>C.</b> A zoom of the images in panel B at diverse positions along the lateral channels.</p

A sketch of the motor response curve and the dependence of the up-gradient chemotactic velocity on the running time.

<p>The curve represented in the main panel is a cartoon version of the clockwise (CW) bias <i>vs</i> the concentration of the second messenger CheYp of the chemotaxis pathway. Having the system set at the inflection point of the curve (blue point) would maximize the slope, i.e. the absolute sensitivity of the motor. However, the bacterial up-gradient velocity is not simply proportional to the absolute sensitivity, as discussed in the text. In particular, extending the duration of the runs can speed up the velocity as shown in the inset: the running time is reported in seconds on the abscissae while the solid line is <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004974#pcbi.1004974.e006" target="_blank">Eq (4)</a> with <i>λ</i> = 1 and the dashed line is again <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004974#pcbi.1004974.e006" target="_blank">Eq (4)</a> but <i>λ</i> changes now with <i>τ</i>_<i>r</i> so as to maximize the chemotactic velocity. The upshot is that points on the motor curve which do not maximize the absolute sensitivity, like the red one, can actually yield larger up-gradient speeds.</p

The bacterial forefronts <i>vs</i> time.

<p>We show the position of the (A) 10^<i>th</i>, (B) 20^<i>th</i> and (C) 40^<i>th</i> most advanced bacteria for a gradient of serine (red), a gradient of aspartate (blue) and a gradient of aspartate with a 30<i>μ</i>M background of serine (green). Curves represent the mean of five experiments and error bars represent the error on the estimation of the mean.</p

The Histograms of Lengths of the Known Operons for B. subtilis and E. coli K12

<p>Blue boxes are for <i>B. subtilis,</i> and red boxes are for E. coli K12.</p

Average Posterior Probabilities of Usage for the Codons of Phenylalanine, Threonine, and Valine in the Clusters Identified for E. coli K12 and B. subtilis

<p>E. coli K12, left column; <i>B. subtilis,</i> right column.</p> <p>Clusters are identified by a roman number on the <i>x</i>-axis. The corresponding standard deviations are on the order of a few percent of the average values.</p

The Correlation Function (1) of Cluster Memberships versus the Distance among Genes for B. subtilis and <i>E.coli</i> K12

<p>Blue dashed lines are for <i>B. subtilis,</i> and red solid lines are for <i>E. coli.</i></p

The Posterior Probability Distributions for Three Representative Codons: TTC (Phenylalanine), ACC (Threonine), and GTC (Valine) in the Clusters That We Identified for E. coli K12 and B. subtilis

<p>E. coli K12, left column; <i>B. subtilis,</i> right column.</p> <p>The curves are meant to show that the clusters are well separated by the combined information on the various codons.</p