Wound healing rate in FOXO3 and FOXO3 LysM-cre knockout mice compared to control.

<p>A) Quantitative RT-PCR using mRNA from non-wounded and <i>in vivo</i> wounded mouse skin was performed. All data was normalized to GAPDH expression (Glyceraldehyde 3-phosphate dehydrogenase) that was used as housekeeping gene. A one-way analysis of variance was performed. Significant differences were found day 1 after wounding for FOXO3 and FOXO4 when performing a Dunnett's Multiple Comparison Test against non-wounded control. (*<i>P</i><0.05, **<i>P</i><0.01). Error bar denotes mean ±SD (n = 3). B) Graph displays wound size in mm² over time. Values from each mouse represent an average of 4 wounds induced by 6 mm punches through folded dorsal skin. A two-way ANOVA was performed to detect differences over time between FOXO3 knock out mice and C57bl/6 control mice using Bonferroni post-testing to detect differences at each time point. An overall difference was detected over time <i>P</i><0.023 and post-testing generated significant results for day 1 to day 4. (*<i>P</i><0.05, **<i>P</i><0.01, ***<i>P</i><0.001) (n = 4) C) Bacterial loads in the wound beds day 10 after wounding. D) Wound healing rate in FOXO3 LysM-cre mice and control mice over time. E) Group A streptococcal (GAS) survival in neutrophil killing assays using neutrophils isolated from either FOXO3 LysM-cre mice or C57bl/6 control mice. Percent survival is expressed relative to GAS survival with no neutrophils present.</p

Significantly differentially expressed regulators of FOXO3.

<p>List of significantly differentially expressed genes involved in regulation of FOXO3 expression/activity in the Roupé et al 2009 data set comparing human <i>in vivo</i> wounded skin with control.</p><p>*Change in expression is consistent with a decrease in FOXO3 activity/expression.</p><p>** Change in expression is not consistent with a decrease in FOXO3 activity/expression.</p

Re-analysis of a microarray data set from [14] on non wounded and <i>in vivo</i> wounded human skin samples.

<p>A) The promoter sequences for the 100 most differentially expressed genes between wounded and non-wounded skin were probed for transcription factor binding sites and co-occurring transcription factor binding sites. The presence of co-occurring transcription factor binding sites of FOXO1, FOXO3 and FOXO4 found by the SMART software to be within 50 base pairs of each other is depicted in the promoter regions of the 70 genes out of 100 were they were found. The presence of co-occurring transcription factor binding sites of either FOXO1, FOXO3 or FOXO4 in these promoter regions are also depicted. Some of these sites are partially overlapping. Genes with a Pavlidis template matching correlation coefficient of 0.9 to FOXO3 expression are highlighted; yellow equals positive correlation and green negative correlation B) Hierarchical clustering and heat map of the 70 genes containing co-occurring FOXO1-FOXO3-FOXO4 transcription factor binding sites. C) Schematic of currently known and annotated interactions between the 70 genes containing co-occurring FOXO1-FOXO3-FOXO4 binding sites generated by ingenuity pathway analysis software. FOXO1, FOXO3 and FOXO4 were also added to visualize how they interact with the selected genes. Only genes with at least one known connection to FOXO1, FOXO3, FOXO4, or one of the other 70 genes were included. D) PCA plots of the 100 selected genes depicting the remaining variance between the samples on the left and a synchronized PCA plot of the variables (gene expression) giving rise to the variance on the right. Genes were selected by first removing all genes having a q-value>0.05 based on a two group comparison analysis between wounded and non-wounded samples. Remaining genes were then filtered by variance till the top 100 genes remained with a p-value≤0.008. The selected genes stood for 23% of the total amount of variance in the data set. E) The normalized hybridization levels of FOXO transcription factor transcripts from the micro array data set from Roupé et. al. 2010 are depicted. A two-tailed Student's t-test confirmed a differential expression of FOXO1, FOXO3 and FOXO6 when comparing non-wounded and <i>in vivo</i> wounded human skin (*<i>P</i><0.05, **<i>P</i><0.01, ***<i>P</i><0.001). Error bar denotes mean ±SD (n = 3). F) Flowchart giving an overview over the analysis approach (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0089274#s2" target="_blank">methods</a> section for more details.)</p

Significantly differentially expressed target genes of FOXO3.

<p>List of significantly differentially expressed known, potential and indirect target genes of FOXO3 in Roupé et al 2009 data set comparing human <i>in vivo</i> wounded skin with control. Genes known to be direct target genes of FOXO3 are <b>in bold</b>.</p><p>*Change in expression is consistent with a decrease in FOXO3 transcriptional activity.</p><p>**Change in expression not consistent with a decrease in FOXO3 transcriptional activity.</p

Population dynamics of bacterial communities.

<p>(<b>a</b>) Simulated growth trajectories for Cm^R and Cm^S populations subject to antibiotic stress and resource competition. (<b>b</b>) Dynamic of intracellular Cm (<i>y</i>_r and <i>y</i>_s) and growth-limiting resource (<i>z</i>). Simulation time is scaled relative to the mean residence time of cells in a chemostat, which is equal to the generation time at steady state. At low population densities, the Cm^R strain can grow, whereas Cm^S cannot, due to a high concentration of Cm. However, the invasion of Cm^R lowers antibiotic stress, generating permissive conditions for the growth of Cm^S cells. The chemostat is then rapidly colonized by both strains (shortly after <i>t</i> = 180) until the resource becomes limiting. From that moment onwards, total cell density changes little, while the relative frequencies of the two strains continue to shift. Eventually, a stable equilibrium is reached, at which the cost and benefit of CAT expression (i.e., reduced growth rate efficiency for Cm^R cells versus their lower intracellular Cm concentration) balance out. Inset (<b>c</b>), The dark-red dot pinpoints the parameter set used in the simulation shown in <b>a</b> and <b>b</b>: <i>r</i> = 20.0, <i>η</i> = 0.9, <i>k</i>_z = 4.0, <i>c</i> = 1.0, <i>p</i> = 50.0, <i>h</i>_Y = 0.25/<i>Y</i>₀, <i>k</i>_Y = 2.5/<i>Y</i>₀, <i>d</i> = 30.0/<i>Y</i>₀ and <i>Y</i>₀ = 0.8. These parameters were selected to lie in a restricted area of parameter space (highlighted in red) where stable coexistence between Cm^S and Cm^R cells is observed Alternative model outcomes, which were identified by a numerical bifurcation analysis (see <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2000631#pbio.2000631.s007" target="_blank">S1 Text</a> and <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2000631#pbio.2000631.s004" target="_blank">S4 Fig</a>), include establishment of Cm^S only (area S), establishment of Cm^R only (area R), no bacterial growth (area N), and competition-induced extinction (area E, where Cm^S bacteria first outcompete Cm^R bacteria and subsequently are cleared by the antibiotic; see <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2000631#pbio.2000631.s005" target="_blank">S5 Fig</a>).</p

Experimental setup to determine passive resistance.

<p>Antibiotic-susceptible cells (Ab^S) constitutively expressing <i>luc</i> are grown together with antibiotic-resistant cells (Ab^R, which do not express <i>luc</i>). Only when the concentration of the antibiotic in the medium is reduced by enzymatic deactivation of resistant cells will the genetically antibiotic-susceptible cells be able to grow and produce light.</p

BlaI contributes to survival in human whole blood and virulence <i>in vivo</i>.

<p>(A) <i>S</i>. <i>aureus</i> Newman WT with empty complementation vector pDC123, the <i>blaI</i> mutant with pDC123, and the complemented <i>blaI</i> mutant strain were incubated for 1 h in human whole blood and CFU numbers enumerated. Samples were run in triplicate and data were plotted as the average percentage ± SD for each strain as compared to the initial inocula. A representative experiment of three performed is shown. **, <i>p</i><0.01. (B) CD-1 mice (<i>n</i> = 8) were injected subcutaneously on one flank with <i>S</i>. <i>aureus</i> Newman WT and on the opposite flank with <i>blaI</i> mutant bacteria, and lesion sizes were monitored for 7 days. The lesions for each individual mouse at Day 7 are plotted and the average value indicated. Overall, the <i>blaI</i> mutant lesions were significantly smaller compared to the WT (<i>p</i><0.04; paired t-test). (C-D) Survival of CD-1 mice (<i>n</i> = 10) after intraperitoneal infection with (C) 1 x 10⁶ CFU of <i>S</i>. <i>aureus</i> Newman WT or Newman <i>blaI</i> mutant or (D) 6 x 10⁸ CFU of MRSA252 or MRSA252 <i>blaI</i> mutant. Survival was monitored for 3 days. The survival for Newman or MRSA252 <i>blaI</i> mutant strain infected mice was significantly higher than for the WT infected strains as assessed by log-rank (Mantel Cox) test; the <i>p</i> values are shown in the respective graphs.</p

Skewed cytokine responses in Siglec-E KO mice challenged in a GBS intranasal pneumonia model.

<p>Mice were infected intranasally with 5×10⁷ CFU WT GBS and cytokine levels in cell-free BAL fluid or lung homogenates collected 6 h post infection. (A) Bacterial load in lung tissue was calculated by dilution plating for CFU enumeration. (B) Cells from BAL were counted and stained with mAb to F4/80 and Gr-1 to quantitate infiltrating cell populations. IL-1β (C) and IL-6 (D) in the BAL and IL-10 in lung homogenates (E) were examined by ELISA analysis. Data shown are means ± SEM and each circle denotes 1 mouse (n = 8 for WT and n = 7 for mSiglec-E KO mice). The difference between different groups was calculated by Mann-Whitney test.</p

Reduced brain dissemination and enhanced bactericidal responses in Siglec-E deficient mice upon sublethal GBS challenge.

<p>Comparison of bacterial counts (expressed in CFU) recovered from the kidney (A) and brain (B) of WT mice and Siglec-E KO mice 48 h after intravenous challenge with 1×10⁸ CFU of WT GBS. (C) Brain bacterial counts were corrected for blood contamination (brain/blood ratio) using a conservative estimate of the mouse cerebral blood volume (2.5 ml per 100 g tissue). mRNA expression of IL-1β (D) and IL-12 (E) in lung and IL-10 in spleen (F) was examined by quantitative real time RT-PCR analysis. Results pooled the data from two independent experiment with final numbers of <i>n</i> = 14 for each group. Each circle denotes 1 mouse (A–F). Siglec-E KO microglia cells showed greater bactericidal ability (G) and produced higher levels of TNF-α (H) after GBS challenge. Statistical analysis was performed by Mann-Whitney test (A–F), two-way ANOVA with Bonferroni posttest (G) and one-way ANOVA with Tukey's multiple comparison test (H). *<i>P</i><0.05.</p