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. 2022 Feb 3;11:e72071. doi: 10.7554/eLife.72071

Figure 1. Neutrophil response is delayed in infected diabetic wound tissue.

Normal (C57BL/6) and diabetic (db/db) wounds were infected with PA103 (1000 CFU/wound). (a–b) Wound tissues were harvested at indicated timepoints post-infection and assessed for neutrophil contents by histological analysis using anti-Ly6G antibody. (a) Representative regions from underneath the wounds extending in the dermis are shown at ×40 and ×400 magnification (top and bottom, respectively). A representative magnified region is also inserted in the ×400 magnification images. Black scale bar = 500 µm for ×40 magnification and red scale bar = 50 µm for ×400 magnification. (b) The corresponding data were plotted as the Mean ± SEM. (c) Wounds at indicated timepoints were assessed for their MPO contents by ELISA and the tabulated data are shown as the Mean ± SEM. (d) Day 1 infected wound tissues of C57BL/6 and db/db were evaluated for their neutrophil contents by flow cytometry. Corresponding data were plotted as the Mean ± SEM. (N = 4; ns = not significant, *p < 0.05; **p < 0.01; ***p < 0.001 – are comparisons made between C57BL/6 and db/db at indicated timepoints; or #p < 0.05; ##p < 0.01; ###p < 0.001 are comparisons made within each group to day one values, respectively. Statistical analyses between groups were conducted by One-way ANOVA with additional post hoc testing, and pair-wise comparisons between groups were performed or by unpaired Student’s t-test).

Figure 1—source data 1. Related to Figure 1b.
Figure 1—source data 2. Related to Figure 1c.
Figure 1—source data 3. Related to Figure 1d.

Figure 1.

Figure 1—figure supplement 1. Diabetic wound is vulnerable to increased infection with Pseudomonas aeruginosa.

Figure 1—figure supplement 1.

Normal and diabetic wounds were infected with 103 of P. aeruginosa (PA103). Bacterial burden in wounds was determined by serial dilution and plating at indicated times after infection and is shown as the Mean ± SEM. (N = 4 mice/group, 2 wounds/mouse. (*) Represents significance with p < 0.01. Statistical analyses between groups were conducted by One-way ANOVA with additional post hoc testing, and pair-wise comparisons between groups were performed or by unpaired Student’s t-test).
Figure 1—figure supplement 1—source data 1. Related to Figure 1—figure supplement 1.
Figure 1—figure supplement 2. Gating strategy for flow cytometric analysis.

Figure 1—figure supplement 2.

Spleen (a) and skin tissues (b) were harvested from C57BL/6 mice. For the gating strategy, Live singlet lymphocytes were identified by gating on forward scatter (FSC)-area (A) versus (vs) side scatter (SSC)-A, then LIVE/DEAD staining vs SSC-A, FSC-A vs FSC-height (H), SSC-A vs SSC-H, FSC-width (W) vs SSC-W, and CD45 vs SSC-A. T cells, B cells, and NK cells were excluded using antibodies against CD3, CD19, and NK1.1, respectively, all on one channel as a dump gate. Neutrophils were then identified using CD11b vs Ly6G staining, with neutrophils being CD11b high and Ly6G high. Macrophages were identified as CD11b positive and Ly6G low/negative, followed by F4/80-positive staining.