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Organ-specific immune microenvironment determines the fitness landscape of the ΔqorA mutant in vivo (A) Bacteria survival in whole blood. (B) Murine rapid blood clearance model: mice were infected with WT, Δ qorA , and pOS1_ qorA via tail vein injection. Bacterial enumerations were performed at time zero and at 2, 5, 10, 20, and 30 min after infection. (C) WT and Δ qorA strains were mixed at a 1:1 ratio for an in vivo competition assay in mice. Following intravenous infection via the tail vein, mouse organs were harvested, and the respective proportions of the WT and Δ qorA strains were determined by PCR. (D) Representative immunofluorescence images of infected tissues. <t>Ly6G-positive</t> neutrophils, green fluorescence; F4/80-positive macrophages, red fluorescence; cell nuclei stained with DAPI, blue fluorescence. Scale bar, 10 μm. (E) Quantitative analysis of immune cell infiltration in infected tissues. (Ⅰ) Percentage of Ly6G-positive area, (Ⅱ) percentage of F4/80-positive area, (Ⅲ) comparative analysis of Ly6G-positive and F4/80-positive areas, and (Ⅳ) ratio of Ly6G-positive area to F4/80-positive area. Data are presented as mean ± SEM, n = 5 mice per group, 3–5 fields of view per organ. (F) Distribution of bacterial colonies in various mouse organs at 24 h post-bloodstream infection with the WT, Δ qorA , and pOS1- qorA strains. (G) Bacterial loads in skin abscesses following subcutaneous infection. Each experiment was repeated independently three times with at least five technical replicates per sample. Comparisons were made using one-way ANOVA with Tukey’s post hoc test for multiple comparisons; data are shown as mean ± SEM. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001; ns, not significant ( p ≥ 0.05).
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Organ-specific immune microenvironment determines the fitness landscape of the ΔqorA mutant in vivo (A) Bacteria survival in whole blood. (B) Murine rapid blood clearance model: mice were infected with WT, Δ qorA , and pOS1_ qorA via tail vein injection. Bacterial enumerations were performed at time zero and at 2, 5, 10, 20, and 30 min after infection. (C) WT and Δ qorA strains were mixed at a 1:1 ratio for an in vivo competition assay in mice. Following intravenous infection via the tail vein, mouse organs were harvested, and the respective proportions of the WT and Δ qorA strains were determined by PCR. (D) Representative immunofluorescence images of infected tissues. <t>Ly6G-positive</t> neutrophils, green fluorescence; F4/80-positive macrophages, red fluorescence; cell nuclei stained with DAPI, blue fluorescence. Scale bar, 10 μm. (E) Quantitative analysis of immune cell infiltration in infected tissues. (Ⅰ) Percentage of Ly6G-positive area, (Ⅱ) percentage of F4/80-positive area, (Ⅲ) comparative analysis of Ly6G-positive and F4/80-positive areas, and (Ⅳ) ratio of Ly6G-positive area to F4/80-positive area. Data are presented as mean ± SEM, n = 5 mice per group, 3–5 fields of view per organ. (F) Distribution of bacterial colonies in various mouse organs at 24 h post-bloodstream infection with the WT, Δ qorA , and pOS1- qorA strains. (G) Bacterial loads in skin abscesses following subcutaneous infection. Each experiment was repeated independently three times with at least five technical replicates per sample. Comparisons were made using one-way ANOVA with Tukey’s post hoc test for multiple comparisons; data are shown as mean ± SEM. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001; ns, not significant ( p ≥ 0.05).
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Organ-specific immune microenvironment determines the fitness landscape of the ΔqorA mutant in vivo (A) Bacteria survival in whole blood. (B) Murine rapid blood clearance model: mice were infected with WT, Δ qorA , and pOS1_ qorA via tail vein injection. Bacterial enumerations were performed at time zero and at 2, 5, 10, 20, and 30 min after infection. (C) WT and Δ qorA strains were mixed at a 1:1 ratio for an in vivo competition assay in mice. Following intravenous infection via the tail vein, mouse organs were harvested, and the respective proportions of the WT and Δ qorA strains were determined by PCR. (D) Representative immunofluorescence images of infected tissues. <t>Ly6G-positive</t> neutrophils, green fluorescence; F4/80-positive macrophages, red fluorescence; cell nuclei stained with DAPI, blue fluorescence. Scale bar, 10 μm. (E) Quantitative analysis of immune cell infiltration in infected tissues. (Ⅰ) Percentage of Ly6G-positive area, (Ⅱ) percentage of F4/80-positive area, (Ⅲ) comparative analysis of Ly6G-positive and F4/80-positive areas, and (Ⅳ) ratio of Ly6G-positive area to F4/80-positive area. Data are presented as mean ± SEM, n = 5 mice per group, 3–5 fields of view per organ. (F) Distribution of bacterial colonies in various mouse organs at 24 h post-bloodstream infection with the WT, Δ qorA , and pOS1- qorA strains. (G) Bacterial loads in skin abscesses following subcutaneous infection. Each experiment was repeated independently three times with at least five technical replicates per sample. Comparisons were made using one-way ANOVA with Tukey’s post hoc test for multiple comparisons; data are shown as mean ± SEM. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001; ns, not significant ( p ≥ 0.05).
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Organ-specific immune microenvironment determines the fitness landscape of the ΔqorA mutant in vivo (A) Bacteria survival in whole blood. (B) Murine rapid blood clearance model: mice were infected with WT, Δ qorA , and pOS1_ qorA via tail vein injection. Bacterial enumerations were performed at time zero and at 2, 5, 10, 20, and 30 min after infection. (C) WT and Δ qorA strains were mixed at a 1:1 ratio for an in vivo competition assay in mice. Following intravenous infection via the tail vein, mouse organs were harvested, and the respective proportions of the WT and Δ qorA strains were determined by PCR. (D) Representative immunofluorescence images of infected tissues. <t>Ly6G-positive</t> neutrophils, green fluorescence; F4/80-positive macrophages, red fluorescence; cell nuclei stained with DAPI, blue fluorescence. Scale bar, 10 μm. (E) Quantitative analysis of immune cell infiltration in infected tissues. (Ⅰ) Percentage of Ly6G-positive area, (Ⅱ) percentage of F4/80-positive area, (Ⅲ) comparative analysis of Ly6G-positive and F4/80-positive areas, and (Ⅳ) ratio of Ly6G-positive area to F4/80-positive area. Data are presented as mean ± SEM, n = 5 mice per group, 3–5 fields of view per organ. (F) Distribution of bacterial colonies in various mouse organs at 24 h post-bloodstream infection with the WT, Δ qorA , and pOS1- qorA strains. (G) Bacterial loads in skin abscesses following subcutaneous infection. Each experiment was repeated independently three times with at least five technical replicates per sample. Comparisons were made using one-way ANOVA with Tukey’s post hoc test for multiple comparisons; data are shown as mean ± SEM. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001; ns, not significant ( p ≥ 0.05).
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Organ-specific immune microenvironment determines the fitness landscape of the ΔqorA mutant in vivo (A) Bacteria survival in whole blood. (B) Murine rapid blood clearance model: mice were infected with WT, Δ qorA , and pOS1_ qorA via tail vein injection. Bacterial enumerations were performed at time zero and at 2, 5, 10, 20, and 30 min after infection. (C) WT and Δ qorA strains were mixed at a 1:1 ratio for an in vivo competition assay in mice. Following intravenous infection via the tail vein, mouse organs were harvested, and the respective proportions of the WT and Δ qorA strains were determined by PCR. (D) Representative immunofluorescence images of infected tissues. <t>Ly6G-positive</t> neutrophils, green fluorescence; F4/80-positive macrophages, red fluorescence; cell nuclei stained with DAPI, blue fluorescence. Scale bar, 10 μm. (E) Quantitative analysis of immune cell infiltration in infected tissues. (Ⅰ) Percentage of Ly6G-positive area, (Ⅱ) percentage of F4/80-positive area, (Ⅲ) comparative analysis of Ly6G-positive and F4/80-positive areas, and (Ⅳ) ratio of Ly6G-positive area to F4/80-positive area. Data are presented as mean ± SEM, n = 5 mice per group, 3–5 fields of view per organ. (F) Distribution of bacterial colonies in various mouse organs at 24 h post-bloodstream infection with the WT, Δ qorA , and pOS1- qorA strains. (G) Bacterial loads in skin abscesses following subcutaneous infection. Each experiment was repeated independently three times with at least five technical replicates per sample. Comparisons were made using one-way ANOVA with Tukey’s post hoc test for multiple comparisons; data are shown as mean ± SEM. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001; ns, not significant ( p ≥ 0.05).
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Organ-specific immune microenvironment determines the fitness landscape of the ΔqorA mutant in vivo (A) Bacteria survival in whole blood. (B) Murine rapid blood clearance model: mice were infected with WT, Δ qorA , and pOS1_ qorA via tail vein injection. Bacterial enumerations were performed at time zero and at 2, 5, 10, 20, and 30 min after infection. (C) WT and Δ qorA strains were mixed at a 1:1 ratio for an in vivo competition assay in mice. Following intravenous infection via the tail vein, mouse organs were harvested, and the respective proportions of the WT and Δ qorA strains were determined by PCR. (D) Representative immunofluorescence images of infected tissues. <t>Ly6G-positive</t> neutrophils, green fluorescence; F4/80-positive macrophages, red fluorescence; cell nuclei stained with DAPI, blue fluorescence. Scale bar, 10 μm. (E) Quantitative analysis of immune cell infiltration in infected tissues. (Ⅰ) Percentage of Ly6G-positive area, (Ⅱ) percentage of F4/80-positive area, (Ⅲ) comparative analysis of Ly6G-positive and F4/80-positive areas, and (Ⅳ) ratio of Ly6G-positive area to F4/80-positive area. Data are presented as mean ± SEM, n = 5 mice per group, 3–5 fields of view per organ. (F) Distribution of bacterial colonies in various mouse organs at 24 h post-bloodstream infection with the WT, Δ qorA , and pOS1- qorA strains. (G) Bacterial loads in skin abscesses following subcutaneous infection. Each experiment was repeated independently three times with at least five technical replicates per sample. Comparisons were made using one-way ANOVA with Tukey’s post hoc test for multiple comparisons; data are shown as mean ± SEM. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001; ns, not significant ( p ≥ 0.05).
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Organ-specific immune microenvironment determines the fitness landscape of the ΔqorA mutant in vivo (A) Bacteria survival in whole blood. (B) Murine rapid blood clearance model: mice were infected with WT, Δ qorA , and pOS1_ qorA via tail vein injection. Bacterial enumerations were performed at time zero and at 2, 5, 10, 20, and 30 min after infection. (C) WT and Δ qorA strains were mixed at a 1:1 ratio for an in vivo competition assay in mice. Following intravenous infection via the tail vein, mouse organs were harvested, and the respective proportions of the WT and Δ qorA strains were determined by PCR. (D) Representative immunofluorescence images of infected tissues. <t>Ly6G-positive</t> neutrophils, green fluorescence; F4/80-positive macrophages, red fluorescence; cell nuclei stained with DAPI, blue fluorescence. Scale bar, 10 μm. (E) Quantitative analysis of immune cell infiltration in infected tissues. (Ⅰ) Percentage of Ly6G-positive area, (Ⅱ) percentage of F4/80-positive area, (Ⅲ) comparative analysis of Ly6G-positive and F4/80-positive areas, and (Ⅳ) ratio of Ly6G-positive area to F4/80-positive area. Data are presented as mean ± SEM, n = 5 mice per group, 3–5 fields of view per organ. (F) Distribution of bacterial colonies in various mouse organs at 24 h post-bloodstream infection with the WT, Δ qorA , and pOS1- qorA strains. (G) Bacterial loads in skin abscesses following subcutaneous infection. Each experiment was repeated independently three times with at least five technical replicates per sample. Comparisons were made using one-way ANOVA with Tukey’s post hoc test for multiple comparisons; data are shown as mean ± SEM. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001; ns, not significant ( p ≥ 0.05).
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Organ-specific immune microenvironment determines the fitness landscape of the ΔqorA mutant in vivo (A) Bacteria survival in whole blood. (B) Murine rapid blood clearance model: mice were infected with WT, Δ qorA , and pOS1_ qorA via tail vein injection. Bacterial enumerations were performed at time zero and at 2, 5, 10, 20, and 30 min after infection. (C) WT and Δ qorA strains were mixed at a 1:1 ratio for an in vivo competition assay in mice. Following intravenous infection via the tail vein, mouse organs were harvested, and the respective proportions of the WT and Δ qorA strains were determined by PCR. (D) Representative immunofluorescence images of infected tissues. <t>Ly6G-positive</t> neutrophils, green fluorescence; F4/80-positive macrophages, red fluorescence; cell nuclei stained with DAPI, blue fluorescence. Scale bar, 10 μm. (E) Quantitative analysis of immune cell infiltration in infected tissues. (Ⅰ) Percentage of Ly6G-positive area, (Ⅱ) percentage of F4/80-positive area, (Ⅲ) comparative analysis of Ly6G-positive and F4/80-positive areas, and (Ⅳ) ratio of Ly6G-positive area to F4/80-positive area. Data are presented as mean ± SEM, n = 5 mice per group, 3–5 fields of view per organ. (F) Distribution of bacterial colonies in various mouse organs at 24 h post-bloodstream infection with the WT, Δ qorA , and pOS1- qorA strains. (G) Bacterial loads in skin abscesses following subcutaneous infection. Each experiment was repeated independently three times with at least five technical replicates per sample. Comparisons were made using one-way ANOVA with Tukey’s post hoc test for multiple comparisons; data are shown as mean ± SEM. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001; ns, not significant ( p ≥ 0.05).
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Organ-specific immune microenvironment determines the fitness landscape of the ΔqorA mutant in vivo (A) Bacteria survival in whole blood. (B) Murine rapid blood clearance model: mice were infected with WT, Δ qorA , and pOS1_ qorA via tail vein injection. Bacterial enumerations were performed at time zero and at 2, 5, 10, 20, and 30 min after infection. (C) WT and Δ qorA strains were mixed at a 1:1 ratio for an in vivo competition assay in mice. Following intravenous infection via the tail vein, mouse organs were harvested, and the respective proportions of the WT and Δ qorA strains were determined by PCR. (D) Representative immunofluorescence images of infected tissues. Ly6G-positive neutrophils, green fluorescence; F4/80-positive macrophages, red fluorescence; cell nuclei stained with DAPI, blue fluorescence. Scale bar, 10 μm. (E) Quantitative analysis of immune cell infiltration in infected tissues. (Ⅰ) Percentage of Ly6G-positive area, (Ⅱ) percentage of F4/80-positive area, (Ⅲ) comparative analysis of Ly6G-positive and F4/80-positive areas, and (Ⅳ) ratio of Ly6G-positive area to F4/80-positive area. Data are presented as mean ± SEM, n = 5 mice per group, 3–5 fields of view per organ. (F) Distribution of bacterial colonies in various mouse organs at 24 h post-bloodstream infection with the WT, Δ qorA , and pOS1- qorA strains. (G) Bacterial loads in skin abscesses following subcutaneous infection. Each experiment was repeated independently three times with at least five technical replicates per sample. Comparisons were made using one-way ANOVA with Tukey’s post hoc test for multiple comparisons; data are shown as mean ± SEM. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001; ns, not significant ( p ≥ 0.05).

Journal: iScience

Article Title: q orA shapes organ-specific adaptation of ST59-MRSA via balancing immune evasion and metabolic trade-off

doi: 10.1016/j.isci.2026.116272

Figure Lengend Snippet: Organ-specific immune microenvironment determines the fitness landscape of the ΔqorA mutant in vivo (A) Bacteria survival in whole blood. (B) Murine rapid blood clearance model: mice were infected with WT, Δ qorA , and pOS1_ qorA via tail vein injection. Bacterial enumerations were performed at time zero and at 2, 5, 10, 20, and 30 min after infection. (C) WT and Δ qorA strains were mixed at a 1:1 ratio for an in vivo competition assay in mice. Following intravenous infection via the tail vein, mouse organs were harvested, and the respective proportions of the WT and Δ qorA strains were determined by PCR. (D) Representative immunofluorescence images of infected tissues. Ly6G-positive neutrophils, green fluorescence; F4/80-positive macrophages, red fluorescence; cell nuclei stained with DAPI, blue fluorescence. Scale bar, 10 μm. (E) Quantitative analysis of immune cell infiltration in infected tissues. (Ⅰ) Percentage of Ly6G-positive area, (Ⅱ) percentage of F4/80-positive area, (Ⅲ) comparative analysis of Ly6G-positive and F4/80-positive areas, and (Ⅳ) ratio of Ly6G-positive area to F4/80-positive area. Data are presented as mean ± SEM, n = 5 mice per group, 3–5 fields of view per organ. (F) Distribution of bacterial colonies in various mouse organs at 24 h post-bloodstream infection with the WT, Δ qorA , and pOS1- qorA strains. (G) Bacterial loads in skin abscesses following subcutaneous infection. Each experiment was repeated independently three times with at least five technical replicates per sample. Comparisons were made using one-way ANOVA with Tukey’s post hoc test for multiple comparisons; data are shown as mean ± SEM. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001; ns, not significant ( p ≥ 0.05).

Article Snippet: Rabbit anti-Ly6G antibody , Servicebio , Cat#GB11229;RRID:AB_2814689.

Techniques: Mutagenesis, In Vivo, Bacteria, Infection, Injection, Competitive Binding Assay, Immunofluorescence, Fluorescence, Staining