Dock2^−/− mice and wild-type (WT) C57BL/6J mice were purchased from GemPharmatech Co., Ltd. (China). Sex-matched Dock2^−/− mice and WT littermate controls were used at 8–12 weeks old (body weight, 20–25 g). All mice were maintained under specific pathogen–free conditions with restricted 12-h day/night cycle at a temperature 18°C–22°C and humidity 50%–60%. Protocols for animal experiments were approved by the Institutional Animal Care and Use Committees of the Southern Medical University. For body weights assays, mice that lost ≥ 20% of initial weight were euthanized.

Dock2^−/− and WT mice were intraperitoneally (i.p.) injected with E. coli LPS (5 mg/kg or 25 mg/kg body weight, O55:B5, Sigma), diluted in pyrogen-free phosphate-buffered solution (PBS) or PBS as control. The survival, weight, and eye exudate formation of the mice were monitored over the next 72 h. Mice were euthanized, and the peripheral blood and the organs (spleen, lung and liver) were harvested at 72 h after LPS challenge and used in the assays described below.

The E. coli strain (American Type Culture Collection (ATCC) 25922) was stored at −80°C in 50% glycerol. E. coli stock solution (10 μL) was incubated in 10 mL of Luria-Bertani (LB; Sangon Biotech) medium at 37°C and 200 Revolutions Per Minute (rpm) shaking for 12 h and washed twice with cold PBS. The optical density 600nm (OD₆₀₀) (optical density 600nm) value was measured in a spectrophotometer to estimate the number of E. coli [OD₆₀₀ = 1 = 2 × 10⁹ colony-forming units (CFU)/mL]. The bacterial density was adjusted to 1 × 10⁹ CFU/mL. Dock2^−/− and WT mice were i.p. injected 2 × 10⁸ CFU of E. coli in 200 μL of PBS. Survival rates were monitored for 72 h.

To determine the bacterial burden in mice, blood and peritoneal lavage fluid (PLF) of mice were obtained 72 h after E. coli injection. Blood and PLF were serially diluted with sterile PBS. Serial dilutions (50 μL) were seeded on LB agar plates and incubated at 37°C for 12–18 h to determine the CFU of E. coli. The data were log-transformed for statistical analysis.

For the neutralization of IFN-γ experiments, mice were i.p. treated with 300 μg of anti–IFN-γ–InVivo (XMG1.2, Selleck) as well as isotype controls (rat IgG2b isotype control–InVivo, Selleck) 4 h after LPS injection and then monitored survival for 72 h. For the CD4⁺ T-cell depletion experiments, mice were received anti–CD4-InVivo (GK1.5, Selleck) (i.p., 200 μg per mouse every 2 days) at the day before LPS injection.

After anesthetizing mice with isoflurane, the peripheral blood of the mice was collected into a heparin anticoagulant tube, then euthanized, and perfused with cold PBS through the right ventricle of the heart before removal of tissues. For lung and liver, tissues were weighed, and dissected tissues were cut into small pieces and digested for 45 min at 37°C with collagenase type D (1 mg/mL; Worthington) and deoxyribonuclease (DNase) I(25 μg/mL; Roche) in Roswell Park Memorial Institute 1640 medium (RPMI 1640) medium supplemented with 10% Fetal Bovine Serum (FBS) (Biological Industries) and 1% penicillin/streptomycin (Life Technologies). Digested samples were passed through 70-μm cell strainers (BD Falcon) and washed with flow staining (Fluorescence-activated cell sorting (FACS)) buffer [PBS containing 1% FBS and 2 mM Ethylene Diamine Tetraacetic Acid (EDTA) (pH 8.0)]. Mononuclear leukocytes were fractionated by a 40%–80% (lung) or 30%–70% (liver) Percoll (GE Healthcare) density gradient centrifugation and washed in FACS buffer. Then, red blood cells (RBCs) were lysed in 1× ammonium-chloride-potassium (ACK) buffer. Single-cell suspensions were used for subsequent flow cytometry staining. Suspensions of spleen cells were obtained by mashing the spleen through a 70-mm nylon cell strainer, and RBCs were lysed in 1× ACK buffer. For peripheral blood serum isolation, peripheral blood was left to settle at 4°C until serum precipitation occurred and centrifugated at 1,200g for 7 min at 4°C to obtain serum for cytokine concentration detection.

Single-cell suspensions were blocked with anti-Fc receptor blocking antibody (anti-CD16/CD32, BioLegend, clone 93) in FACS buffer for 10 min to avoid false-positive staining.

For surface protein of cells staining, single-cell suspensions were counted and diluted into proper concentrations and incubated for 30 min in the dark at 4°C with the following fluorescently conjugated antibodies: CD3 (eBioscience, clone 17A2), CD4 (eBioscience, clone GK1.5), CD45 (BioLegend, clone 30-F11), NK1.1 (eBioscience, clone PK136), CD11c (eBioscience, clone N418), CD11b (eBioscience, clone M1/70), F4/80 (eBioscience, clone BM8), CD8a (eBioscience, clone 53-6.7), Ly6C (eBioscience, clone HK1.4), and Ly6G (eBioscience, clone RB6-8C5). The stained cells were then washed with FACS buffer and further stained with Fixable Viability Stain 700 (BD Biosciences) at 4°C under darkness for 30 min.

For detection of intracellular cytokine expression, the stained cells were suspended and stimulated in complete RPMI 1640 medium + 10% FBS with Phorbol 12-myristate 13-acetate (PMA) (50 ng/mL; Sigma-Aldrich), ionomycin (1 μg/mL; Sigma-Aldrich), and brefeldin A (1 μg/mL; eBioscience) for 4 h at 37°C and 5% CO₂. Cells were subsequently surface protein-stained, fixed (intracellular fixation buffer, eBioscience), permeabilized (10× permeabilization buffer, eBioscience), and stained with indicated cytokine antibodies: IFN-γ (BioLegend, clone XMG1.2), and tumor necrosis factor–α (TNF-α; BioLegend, clone MP6-X722). Ki-67 (BioLegend, clone 16A8) staining was performed with the Foxp3/Transcription Factor Staining Buffer Set (Thermo Fisher Scientific) according to the manufacturer’s instructions. Various immune cells of mouse lung, liver, spleen, and Peripheral blood (PB) were gated as Th1 cells (Live&Dead⁻CD3⁺CD4⁺IFN-γ⁺), CD8⁺ T cells (Live&Dead⁻ CD8⁺), and macrophage cells (Live&Dead⁻CD11b⁺ F4/80⁺). All stained cells were acquired on an LSRFortessa flow cytometer (BD Biosciences) and analyzed by FlowJo V10.0.7.

For flow cytometric sorting, CD4⁺ T cells of spleen were sorted from Dock2^−/− and WT mice at sepsis state for RNA sequencing (RNA-seq). Firstly, debris and doublets were excluded for cell types using forward scatter (FSC) and side scatter (SSC). Then, CD4⁺ T cell was gated as follow: CD44⁺CD4⁺ T cells (Live&Dead⁻CD4⁺CD44⁺). BD FACSAria III Cell Sorter (BD Biosciences) was used. The gating strategies and sorting purity of flow cytometry were included in the supplemental information.

The spleen, lung, and liver tissues were perfused with cold PBS to reduce blood cell-induced background and then were harvested and fixed in 4% phosphate-buffered formaldehyde solution for at least 24 h. Fixed and paraffin-embedded tissues were cut into 5-μm-thick sections, followed by hematoxylin and eosin (H&E) staining, and tissue injury severity analysis was measured under a microscope (Olympus BX63).

The levels of mouse IFN-γ, TNF-α, interleukin-6 (IL-6), and IL-1β in serum were measured by enzyme-linked immunosorbent assay (ELISA) according to the manufacturer’s protocol (R&D). Serum was prepared from blood collected from the eye socket after LPS treatment. After centrifugation, the supernatants were used for cytokine measurement.

Five thousand activated CD4⁺ T cells (Live&Dead⁻CD3⁺CD4⁺CD44^hi) from the spleen of LPS challenged mice were lysed in 10 μL of TCL buffer plus 1% 2-mercaptoethanol. Libraries were processed with SMARTSeq2 (15) with three biological replicates per condition and paired-end sequenced (150 bp × 2) with a 75-cycle NextSeq 500 high-output V2 kit. Obtained RNA-seq reads were aligned to the mouse genome and transcriptome (GENCODE GRCm38 vM25, mm10) using Spliced Transcripts Alignment to a Reference (STAR) (version 2.7.5c) (16) with “twopassMode Basic,” expression abundances were estimated using RSEM (version 1.3.3) (17). The count matrices’ outputs from gene results were processed with the R package (version 3.32.0) to analyze differential gene expression (18) with default parameters. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment was performed using custom script with clusterProfiler (version 3.16.1) (19) and hierarchical file from “http://rest.kegg.jp” and visualized using ggplot2 (version 3.3.3) (20). Gene set enrichment analysis (GSEA) was run with the official tool (GSEA version 4.2.1, MsigDB hallmark v7.3) and replot in R. Overall expression was computed as previously described (21, 22).

Data analysis and representation were performed with Prism (GraphPad version 10.0). The p-values were calculated using an unpaired two-tailed Student’s t-test or two-way ANOVA. A p-value < 0.05 was considered statistically significant and are displayed as follows: *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001; and not significant (ns), p > 0.05. Data in all figures are displayed as mean ± SEM.

To investigate the involvement of DOCK2 in the sensitivity to bacterial pathogen, we i.p. injected various doses of E. coli LPS into age- and sex-matched Dock2^−/− mice and WT cohorts ( Figures 1A, C ). Almost all Dock2^−/− mice but not WT littermates died within 72 h after challenge with 25 mg/kg body weight LPS ( Figure 1B ). Then, we narrowed down LPS dose to 5 mg/kg body weight as shown in Figure 1C and found that nearly half of Dock2^−/− mice still died within 72 h after LPS administration, whereas it does not cause mortality in the WT littermates ( Figure 1D ). These data led to the notion that DOCK2 plays a protective role in LPS-induced sepsis.

The weight loss and eye exudate formation of mice in sepsis induced by systemic inflammation can provide references for sickness progression and recovery. Thus, we tracked weight loss and eye exudates in septic mice administrated with LPS (5 mg/kg of body weight). The weight loss in Dock2^−/− mice and WT littermate controls was comparable within 36 h. As time went on, the weight of WT mice but not Dock2^−/− ones began to recover. At 72 h after LPS injection, Dock2^−/− mice showed lower body weight when compared to WT littermates ( Figure 2A ). In addition, DOCK2 deficiency led to more eye exudate formation and blunted recovery of eye exudates ( Figure 2B ). As sepsis is closely associated with multiple-organ injury and dysfunction, we next evaluated histopathology changes in the spleen, lung, and liver of the Dock2^−/− and WT mice by H&E staining. The Dock2^−/− mice exhibited structural disorganization in the spleen, severe injury and inflammation in the lung, thicken alveolar wall and inflammatory cell infiltration increasing in the lung, and widespread hemorrhaging in the liver, whereas the WT ones had much slighter organ damage after LPS treatment ( Figure 2C ). Increased serum aspartate aminotransferase (AST) also indicated more severe sepsis-induced liver injury in Dock2^−/− mice ( Supplementary Figure 2 ). As sepsis is characterized by “cytokine storm” which subsequently leads to overwhelming organ damage and mortality (4). We next focused on proinflammatory cytokines that play a major role in sepsis, including IFN-γ, TNFα, IL-6, and IL-1β. Serum cytokine levels were determined at 72 h after LPS treatment. As the data shown, the production of major proinflammatory cytokines, including IFN-γ and TNF-α, were significantly evaluated in Dock2^−/− mice compared with WT ones ( Figure 2D ). Together, these data suggest that DOCK2-deficiency lead to more susceptible to LPS-induced sepsis.

Sepsis is characterized by concurrent unbalanced hyperinflammation and aberrant immune responses. To explore the immune mechanisms by which Dock2^−/− mice exhibited much higher level of IFN-γ in the LPS-induced sepsis, we next profiled the major potential immune cells closely associated with sepsis, including macrophages (23), nature killer (NK) cells (24), and T cells (25). Flow cytometry analyzes that the loss of DOCK2 had increased frequencies and numbers of IFN-γ–producing CD4⁺ T cells (also named Th1) in the spleen, lung, and liver compared with those in control mice ( Figure 3A ). Consistently, we found that Dock2^−/− mice exhibited higher frequencies of Ki-67–expressing Th1 cells than WT littermate controls ( Figure 3B ). However, DOCK2 deficiency had minor role in regulating macrophages as well as IFN-γ–producing CD8⁺ T and NK cells in the above tissues from LPS-induced septic mice ( Supplementary Figures 3A–C ). Given that IL-12 was the major driver of IFN-γ production and Th1 polarization, we observed markedly increased serum IL-12 in Dock2 ^−/− mice at 12 h after LPS injection ( Supplementary Figure 4A ). Consistently, Th1 cells also elevated in in Dock2 ^−/− mice at 12 h after LPS treatment ( Supplementary Figure 4B ). Moreover, we also investigated the expression profile of DOCK2 in Th1 cells at different time points. The data revealed a downward expression of DOCK2 after LPS treatment and a much lower DOCK2 expression at 72 h after LPS injection, indicating that DOCK2 has an important role in the host immune response to septic inflammation ( Supplementary Figure 4C ). Thereafter, we mainly focus on 72 h after sepsis induction. Further analysis showed that Dock2^−/− and WT control mice also manifested comparable frequencies of TNF-α–producing CD4⁺ T, CD8⁺ T, and NK cells and macrophages ( Supplementary Figures 5A–D ). Collectively, hyperresponsive IFN-γ–producing CD4⁺ T cells in septic Dock2^−/− mice might contribute to the severe inflammation and organ injury.

Although DOCK2 protected against LPS-induced shock via blunting the cytokine storm, especially IFN-γ response, the role of DOCK2 in resisting live bacterial infections remains largely unknown. To address this issue, we studied E. coli sepsis. Namely, Dock2^−/− mice and WT littermates were i.p. injected with E. coli ATCC25922 ( Figure 4A ). Expectedly, we observed impaired survival of Dock2^−/− mice when compared to with WT animals within 72 h of E. coli infection ( Figure 4B ). This was paralleled by a substantial increase in the bacterial burden in PLF and peripheral blood of Dock2^−/− mice ( Figure 4C ). In addition, we found that the deficiency of DOCK2 significantly augmented the frequencies and numbers of CD4⁺IFN-γ⁺ inflammatory Th1 cells in the spleens, lungs, and livers in response to E. coli infection ( Figure 4D ), resembling the phenotypes of LPS challenge. Taken together, these data indicated that DOCK2 provides robust protection against live bacterial infection, other than LPS-induced sepsis.

To further explore whether DOCK2 regulates IFN-γ–producing CD4⁺ T cells that trigger LPS-induced sepsis or not, firstly, we detected the role of IFN-γ in DOCK2-deficient mice when they suffered from endotoxin-induced septic shock. Dock2^−/− mice were i.p. administered anti–IFN-γ or PBS 4 h after LPS injection and then monitored survival for 72 h. Data show that blocking IFN-γ efficiently prolonged the survival of LPS-treated Dock2^−/− mice ( Supplementary Figures 6A, B ). These data suggested IFN-γ played a critical role in process of endotoxin-induced septic shock in Dock2^−/− mice. Furthermore, we i.p. treated Dock2^−/− mice and WT littermates with depleting anti-CD4 antibody (26, 27) ahead of LPS administration and strengthen depletion at on the third day, and survival was monitored ( Figure 5A ). As shown in Figure 5B , the depletion of CD4⁺ T cells significantly increased the survival rate of Dock2^−/− mice within 72 h after LPS injection, and there was basically no death. At day 3 after LPS treatment, we confirmed the depletion efficiency of anti-CD4 antibody by flow cytometric analysis of CD4⁺ T cells. As expected, anti-CD4 antibody treatment resulted in the clearance of CD4⁺ T cells from the spleen, lung, and liver ( Supplementary Figures 6C, D ). Moreover, histomorphologic analysis of the spleen, lung, and liver showed that, compared with WT littermate controls, Dock2^−/− mice had no obvious structural disorganization in the spleen and no obvious infiltration of inflammatory cell in liver and lung tissue ( Figure 5C ). Consistently, CD4⁺ T cell–depleting Dock2^−/− mice manifested comparable serum IFN-γ, when compared with CD4⁺ T cell–depleting WT controls ( Figure 5D ). All these results together suggested that IFN-γ–producing CD4⁺ T cells are critical for systemic inflammation and multiple-organ injury in LPS-induced septic DOCK2-null mice.

To investigate the mechanisms underlying DOCK2-mediated suppression of Th1 responses in the septic mouse, we performed bulk RNA-seq analysis on CD3⁺CD4⁺ CD44⁺ T cells sorted from WT and Dock2^−/− mice treated with LPS. Principal component analysis clearly segregated the activated CD4⁺ T-cell transcriptome profile of Dock2^−/− mice from that of WT controls, suggesting the populations to be transcriptionally distinct ( Figure 6A ). Differentially expressed gene (DEG) analysis revealed that Dock2^−/− CD4⁺ T cells expressed higher levels of cell cycle genes (Cdk6) (28), proliferation genes (Mki67), IFN-induced genes (Ifitm2) (29), cytokine receptor genes (Il1r2, Il18r1, Il7r, and Il18rap) (30), gene associated with migration and adhesion (Ccr6) (31), T-cell migration gene (Itga4) (32), immune cell homing gene (Ccl5) (33), and immunoregulatory gene (Lilrb4a, Zfp36l2, Penk, and Cish) (34, 35) compared to Dock2^+/+ CD4⁺ T cells ( Figure 6B ). More significantly, DOCK2 deficiency resulted in upregulated TLR and IFN-γ signaling genes, including Tlr4, Nfkbi2, Il12rb2, Ifngr1, and Mapk14 ( Figure 6C ). Further weighted gene co-expression network analysis was performed on the DEGs to identify co expression modules ( Figures 6D, E ). Gene Ontology analysis demonstrated that the DEGs were mainly linked to lymphocyte differentiation and regulation of T-cell activation ( Figure 6F ). In addition, GSEA revealed that the cell cycle and cytokine-cytokine receptor interaction gene sets were differentially enriched between WT and Dock2^−/− CD4⁺ T cells ( Figure 6G ). Thus, DOCK2 directly regulated the expression of its target genes involved in mitotic cell cycle and effector cytokine expression associated with the CD4⁺ T cells to control overwhelming Th1 responses.