FRAP image acquisition.

<p>The schematic at the top shows the fluorescence intensity (<i>green shaded area</i>) changes in a fluorescent cell during the course of a FRAP experiment. The cell is bleached at 8 s at the bottom pole by the bleach beam (<i>yellow star</i>), and exhibits fluorescence recovery dynamics afterwards as shown at 10 s and 20 s. Corresponding bright-field images are shown below. In this example, the <i>E</i>. <i>coli</i> cells contain the MtlA-YFP membrane fluorescence-protein fusion (strain VS116::MtlA-YFP). Notice that the cell's outline is brighter than at its center, indicating the membrane localization of the fluorescent protein. During bleaching at 8 s, the bleach intensity is so high that photons spill over into the other acquisition channels of the CCD camera, creating the illusion of fluorescence beyond the cell borders. Scale bar 1 μm.</p

Extraction of a one-dimensional intensity profile from a two-dimensional fluorescent image.

<p>A two-dimensional fluorescent image of an <i>E</i>. <i>coli</i> cell expressing the MtlA-YFP fluorescent fusion protein is shown at the top. The image has been rotated to make the cell’s long-axis horizontal. The one-dimensional intensity profile (arbitrary units; A.U.) for the image is shown in the middle. It is scaled to match the length of the cell. The intensity profile is calculated using the average intensity of each vertical stripe (column) of pixels in the image at each position along the cell’s long axis. Black vertical lines indicate the calculated ends of the cell, where the intensity profile is at half of its maximum value. In each frame, the intensity profile was normalized to eliminate effects of uniform photobleaching over the course of imaging. This results in similar, uniform intensity profiles in the first pre-bleach (<i>red curve</i>) and last post-bleach (<i>blue curve</i>) intensity profiles. The intensity profile immediately after photo-bleaching (<i>green curve</i>) shows reduced fluorescence at the left pole, where the cell was photobleached. The plot at the bottom shows the calculated amplitudes of the first (non-constant) Fourier cosine modes of intensity profiles after photobleaching (<i>green squares</i>). The fit of these data to an exponential decay function (<i>black curve</i>) is used to estimate the apparent diffusion coefficient of the fluorescent protein. The post-bleach values of first Fourier cosine mode amplitude approach that of images before photobleaching (<i>red dashed horizontal line</i>). Pre, pre-bleach; post, post-bleach; t = ∞, last image in the time series. Scale bar 0.5 μm.</p

The effect of antibiotics on protein diffusion in the <i>Escherichia coli</i> cytoplasmic membrane

<div><p>Accumulating evidence suggests that molecular motors contribute to the apparent diffusion of molecules in cells. However, current literature lacks evidence for an active process that drives diffusive-like motion in the bacterial membrane. One possible mechanism is cell wall synthesis, which involves the movement of protein complexes in the cell membrane circumferentially around the cell envelope and may generate currents in the lipid bilayer that advectively transport other transmembrane proteins. We test this hypothesis in <i>Escherichia coli</i> using drug treatments that slow cell wall synthesis and measure their effect on the diffusion of the transmembrane protein mannitol permease using fluorescence recovery after photobleaching. We found no clear decrease in diffusion in response to vancomycin and no decrease in response to mecillinam treatment. These results suggest that cell wall synthesis is not an active contributor to mobility in the cytoplasmic membrane.</p></div

FRAP measurements of MtlA apparent diffusion in <i>E</i>. <i>coli</i> cells treated with mecillinam, A22, and cefsulodin.

<p>(A) The apparent diffusion coefficient of MtlA was measured in cells treated with (<i>red</i>) and without mecillinam treatment (<i>blue</i>). (B) Apparent diffusion coefficient of MtlA in cells with (<i>red</i>) and without A22 treatment (<i>blue</i>). (C) Apparent diffusion coefficient of MtlA in cells with (<i>red</i>) and without cefsulodin treatment (<i>blue</i>).</p

SpoIIE-GFP is preferentially localized to the forespore in <i>B. subtilis</i>.

<p>(A) Schematic showing the displacement of SpoIIE-GFP (green) from FM4-64 (red), and the displacement measured by PSICIC (arrow). (B) A typical <i>B. subtilis</i> image, showing the GFP channel (top), FM4-64 channel (bottom), and merged image (middle). Highlighted are a SpoIIE-GFP peak (arrow) and an FM4-64 peak (arrowhead). (C) Histogram showing the magnitude and direction of SpoIIE-GFP displacement towards (positive) or away from (negative) the forespore.</p

Schematic view of the implementation of PSICIC.

<p>(A) The original image, prior to analysis. (B) The set of points (red dots) at which the image intensity crosses a given threshold is calculated, defining a contour for that cell. The given points are unevenly distributed. (C) The pair of points (stars) on the contour that are the greatest Euclidean distance apart are chosen as a first approximation of the poles. The choice of poles divides the contour into two curves (called “left” and “right” for simplicity). (D) An equal number of points (blue triangles) are evenly distributed along the left and the right curves, such that the distances between points on the left curve are all equal, but not necessarily equal to the distances between points on the right curve. (E) Each point on the left curve is paired with the corresponding point on the right curve, and a straight line, called a “width line” (blue lines) is drawn connecting the pair. (F) The midline (dotted green line) is drawn through the midpoint of each of the width lines. (G) Each pole is moved stepwise and the process described above iterated until the longest midline is identified (solid green line). (H) Using the resulting internal coordinate system of midline and width lines, measurements, such as cell width (dashed line) or fluorescence intensity (solid line), can be quantified.</p

<i>In silico</i> tests of PSICIC precision.

<p>(A) Symmetrical cell shapes were generated (first cell from left), rotated to different angles (not shown), blurred to simulate the point-spread function of our microscope (second cell), pixilated at a spatial density similar to that of the microscope (third cell), and measured by PSICIC (fourth cell). (B) Distribution of the difference between actual “cell” length and length measured by PSICIC, measured in pixels. The dashed line shows the mean deviation (+0.049 pixels, equivalent to 6.3 nm for the imaging apparatus used for the subsequent <i>E. coli</i> division experiments) and the two dotted lines show plus and minus one standard deviation (±0.094 pixels, equivalent to 12.2 nm). (C) The deviation of measured division-site location from midcell in symmetrically pinched “cell” images, as a percentage of cell length. Colored bars represent different pinch depths, measured by the thickness at the pinch as a fraction of cell thickness away from the pinch. Inset shows detailed data for the 5% of cell length closest to midcell.</p

Pinch position measurements in <i>E. coli</i>.

<p>(A) Schematic showing an asymmetrically dividing cell, indicating the geometric midpoint of the cell (solid line), the pinch position and width, the distance of the pinch position from midcell (double-headed solid arrow), and the maximal cell width. (B) Distribution of the distance of the pinch position from midcell, as a percentage of cell length, shown for wild-type (black line) and Δ<i>minC</i> (gray shading) strains. (C) Scatter plot of pinch position versus the depth of the pinch for wild type (green dots) and Δ<i>minC</i> (blue circles). Standard deviation is shown for wild type (solid green curve), Δ<i>minC</i> (solid blue curve), and the theoretical limits of PSICIC (dashed black curve, see also <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000233#pcbi-1000233-g002" target="_blank">Figure 2C</a>).</p

Measurement of beads of known size.

<p>(A) Phase contrast image of 1 µm diameter beads (100× magnification) with PSICIC identification of outlines overlaid (blue lines). (B) Comparison of the size in microns of: a pixel in these images, mean bead size measured by PSICIC, mean bead size measured by electron microscopy, typical <i>E. coli</i> width, and typical <i>E. coli</i> length. (C) The distribution of bead sizes as measured by PSICIC (gray bars) compared to the expected distribution obtained from electron microscopy data (dashed curve).</p

Inhibition of <i>Escherichia coli</i> CTP Synthetase by NADH and Other Nicotinamides and Their Mutual Interactions with CTP and GTP

CTP synthetases catalyze the last step of pyrimidine biosynthesis and provide the sole <i>de novo</i> source of cytosine-containing nucleotides. As a central regulatory hub, they are regulated by ribonucleotide and enzyme concentration through ATP and UTP substrate availability, CTP product inhibition, GTP allosteric modification, and quaternary structural changes including the formation of CTP-inhibited linear polymers (filaments). Here, we demonstrate that nicotinamide redox cofactors are moderate inhibitors of <i>Escherichia coli</i> CTP synthetase (<i>Ec</i>CTPS). NADH and NADPH are the most potent, and the primary inhibitory determinant is the reduced nicotinamide ring. Although nicotinamide inhibition is noncompetitive with substrates, it apparently enhances CTP product feedback inhibition and GTP allosteric regulation. Further, CTP and GTP also enhance each other’s effects, consistent with the idea that NADH, CTP, and GTP interact with a common intermediate enzyme state. A filament-blocking mutation that reduces CTP inhibitory effects also reduced inhibition by GTP but not NADH. Protein-concentration effects on GTP inhibition suggest that, like CTP, GTP preferentially binds to the filament. All three compounds display nearly linear dose-dependent inhibition, indicating a complex pattern of cooperative interactions between binding sites. The apparent synergy between inhibitors, in consideration with physiological nucleotide concentrations, points to metabolically relevant inhibition by nicotinamides, and implicates cellular redox state as a regulator of pyrimidine biosynthesis