Fig 2: In Vivo Dual RNA-Seq Pipeline for the Enrichment of Bacterial RNA from Flow-Sorted Lung Macrophages(A) Flow gating strategy used to identify the two different lung macrophages lineages. CD64+ and MerTk+ macrophages were separated from the rest of the immune population and the AM and IM lineages identified by the level of expression of Siglecf. IM- and AM-infected macrophages constituted ~9% and ~2%, respectively, of the total macrophage population. The experimental infection and cellular isolation was repeated three times independently (n = 3), each time pooling and processing lung tissue from three infected mice.(B) Diagram of the RNA extraction process. Samples were sorted in Trizol to release host RNA and pelleted, and the supernatant (containing most of the host RNA) was removed and placed aside. Fresh Trizol was added to the tube containing the bacterial pellet, and the bacteria were disrupted through mechanical lysis. A percentage of the host RNA (nominally 50%) was then transferred back to the tube containing the lysed bacteria and the resulting total RNA, now enriched for bacterial transcripts, processed following the Trizol protocol.(C) Example of an Agilent Bioanalyzer 2100 plot shows how physical separation of the host RNA from the bacterial pellet prior Mtb homogenization preserves RNA quality and integrity, as evidenced by the intact rRNA peaks and higher quality score (RNA quality number [RQN] 7.5 versus 4.8).(D) Bar chart illustrating the percentage of total reads that map to the Mtb Erdman genome for the test and in vivo samples.(E) Venn diagram showing the overlap of the genes (abs[log2 FC > 1], false discovery rate [FDR] < 0.05) detected as differentially expressed on the full reference datasets by DESeq2, IHW, edgeR, and limma-voom. We nominally defined this set of genes as “true DE.”(F) Percentage of false positives (genes detected as differentially expressed; abs[log2 FC > 1], FDR < 0.05) in the subset of 1 M reads but not part of “true DE”) for the most common used statistical approaches in RNA-seq analysis. APEGLM outperformed all other methods, with a false-positive rate of <3.5%. p values were calculated using one-way ANOVA followed by Tukey’s post hoc test.

Fig 3: CLEC5A is critical for P. aeruginosa–induced cell infiltration and inflammation in the lung.WT and Clec5a–/– mice were intratracheally inoculated with median lethal dose (LD50) of P. aeruginosa (Xen41, PAO1 strain); WT mice were injected with DNase I (4 U/mouse) via i.p. route for comparison. (A) Lung tissue was collected at 24 hours after infection for H&E staining. Scale bar: 200 µm. (B) Lung tissue was harvested at 8 hours after infection for measurement of cytokine and chemokine mRNA levels. Data are mean ± SEM (mock: WT, n = 6; WT + DNase 1, n = 5; Clec5a–/–, n = 5; Xen41LD50: WT, n = 4; WT + DNase 1, n = 3; Clec5a–/–, n = 5). (C) BALF was collected at 15 hours after infection, and cytokines and chemokines were quantified by ELISA. Data are mean ± SEM (mock: WT, n = 3; WT + DNase 1, n = 3; Clec5a–/–, n = 3; Xen41LD50: WT, n = 5; WT + DNase 1, n = 5; Clec5a–/–, n = 7). (D) Lung cell suspensions from WT and Clec5a–/– mice were stained with PE/Cy7-conjugated anti-CD45 Ab, PerCP/Cy5.5-conjugated anti-CD64 Ab, APC/Cy7-conjugated anti-IA/IE Ab, BV421-conjugated anti–Siglec-F Ab, BV510-conjugated anti–TNF-a Ab, PE-conjugated anti–pro–IL1ß Ab, APC-conjugated anti–IL-6 Ab, PE-conjugated anti-RANTES Ab to measure intracellular TNF-a, IL-6, pro–IL-1ß, and RANTES in alveolar macrophage (AM?: CD45+CD64+IA/IE+Siglec-F+). Cytokine/chemokine MFIs were normalized to mock for WT and Clec5a–/– mice, and the data (fold change of MFI) are presented as mean ± SEM (mock: WT, n = 3; Clec5a–/–, n = 3; Xen41LD50: WT, n = 4; Clec5a–/–, n = 4). Statistical calculations were performed with 2-way ANOVA. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

Fig 4: CLEC5A is a potential therapeutic target in P. aeruginosa–induced cell infiltration and lethality.WT mice were intratracheally injected with a sublethal dose (LD90) of P. aeruginosa Xen41 (1 × 106 PFU) and injected with isotype control (mIgG1, 100 µg per mouse, i.v.), anti-mCLEC5A mAb (clone 4A12D5, 100 µg per mouse, i.v.), ciprofloxacin (Cip, 4 mg/kg, i.p.), or anti-mCLEC5A mAb (i.v.) combined with ciprofloxacin (i.p.) at 15 hours after infection. Ciprofloxacin was further administered every 12 hours. (A) Survival rate was monitored up to 120 hours after infection. (B) Lung tissues were collected, and formalin-fixed paraffin-embedded sections were prepared. Cellular infiltration was visualized by H&E staining. Scale bar: 200 m. (C) Tissue sections were stained with anti-CD64 Ab (green), anti-CD11b Ab (red), anti–Siglec-F Ab (yellow), and anti-F4/80 Ab (light blue); fluorescence images were captured using a Leica confocal microscope with white light laser system (TCS-SP8-MP-SMD) and analyzed using Leica Application Suite X software. Scale bar: 200 µm. (D and E) The cell population was analyzed with MetaMorph software to determine the percentages of interstitial macrophages (interstitial M?, CD64+CD11b+Siglec-F–F4/80+), alveolar macrophages (AM?, CD64+CD11b–Siglec-F+F4/80+), eosinophils (Eos, CD64–CD11b+Siglec-F+F4/80+), and neutrophils/DCs (PMN/DC, CD11b+Siglec-F–F4/80–CD64–) (ciprofloxacin, n = 11; ciprofloxacin + anti-mCLEC5A mAb, n = 10, from 4 independent experiments) (F) Lung cell suspensions were incubated with BV650-conjugated anti-Ly6G Ab, BUV805-conjugated anti-CD45 Ab, BUV395-conjugated anti-CD11b Ab, BV480-conjugated anti-CD11c Ab, BV605-conjugated anti-CD64 Ab, PE-Cy5-conjugated anti-CD25 Ab, and BUV496-conjugated anti-IA/IE Ab to analyze the percentage of neutrophil (PMN), alveolar macrophage (AM?), interstitial macrophage (IM?), and eosinophils after P. aeruginosa inoculation (ciprofloxacin, n = 4; ciprofloxacin + anti-mCLEC5A mAb, n = 4, from 3 independent experiments). Survival rate was assessed using the log-rank (Mantel-Cox) test with GraphPad Prism software. ***P < 0.005. Statistical analysis for D and E was calculated with unpaired and nonparametric Student’s t test with Mann-Whitney U test. *P < 0.05.

Fig 5: Gating strategy and absolute numbers from FACS.(A) Gating strategy and representative contour plots used for the identification of immune cells using flow cytometry in half brain of 9.5-mo-old PS19 and WT littermate mice. PBMs were sorted as TCRb− CD11b+ Ly6g− CD45high F4/80+ CD64+ CD206+. PBM phenotypes were identified by the expression of MHCII and/or CD38. (B) Absolute numbers of CD206+ cells, and subtypes of CD38+MHCII+CD206+, CD38-MHCII+CD206+, and CD38+MHCII-CD206+ cells. n = 9–10 mice/group. Data are presented as mean ± SEM. Significance was determined using two-tailed Mann–Whitney test. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001. Males and females are represented with blue dots and orange dots, respectively.