Activation of the endoplasmic reticulum stress regulator IRE1α compromises pulmonary host defenses

SUMMARY

The endoplasmic reticulum (ER) stress sensor inositol-requiring enzyme 1α (IRE1α) is associated with lung infections where innate immune cells are drivers for progression and resolution of inflammation. Yet, the role of IRE1α in pulmonary innate immune host defense during acute respiratory infection remains unexplored. Here, we found that activation of IRE1α in infected lungs compromises immunity against methicillin-resistant Staphylococcus aureus (MRSA)-induced primary and secondary pneumonia. Moreover, activation of IRE1α in MRSA-infected lungs and alveolar macrophages (AMs) leads to exacerbated production of inflammatory mediators followed by cell death. Ablation of myeloid IRE1α or global IRE1α inhibition confers protection against MRSA-induced pneumonia with improved survival, bacterial clearance, cytokine reduction, and lung injury. In addition, loss of myeloid IRE1α protects mice against MRSA-induced secondary to influenza pneumonia by promoting AM survival. Thus, activation of IRE1α is detrimental to pneumonia, and therefore, it shows potential as a target to control excessive unresolved lung inflammation.

In brief

Sharma et al. show that the endoplasmic reticulum stress sensor IRE1ɑ is activated in infected lungs, where myeloid IRE1ɑ exacerbates inflammation, cell death, and lung injury. Ablation of myeloid IRE1ɑ or global IRE1ɑ inhibition augments type II interferon response and protects mice against MRSA primary and secondary to influenza pneumonia.

Graphical Abstract

INTRODUCTION

The endoplasmic reticulum (ER) stress response has been associated with many inflammatory lung diseases, including respiratory infections. ¹ The ER serves as an essential organelle where biosynthesis and sorting of lipids and proteins, especially secreted molecules, take place. ² During infection, cells are exposed to environmental stressors, such as hypoxia and nutrient deprivation, ^3,4 and produce inflammatory mediators important for immune defense. However, these events often lead to overload and impair proper functioning of the ER. ⁵ Halting ER functions causes stress that leads to the activation of an adaptive response termed the unfolded protein response (UPR). ^6,7 The UPR is a signaling network that aims to restore cellular homeostasis by increasing protein folding and degradation of misfolded proteins. Many respiratory pathogens reportedly activate the UPR in the lungs. ^8–12 The majority of previous studies focused on understanding the contribution of UPR signaling to viral pathogenesis. Viruses such as influenza and severe acute respiratory syndrome coronavirus 2 exploit UPR activity to enhance their pathogenesis, while pathogenesis of respiratory syncytial virus is impaired by UPR activation. ^9–11,13 However, it remains unclear whether the UPR aids or impedes immune defenses against the acute phase of bacterial respiratory infection.

In mammals, the UPR is controlled by three resident ER sensors, of which inositol-requiring enzyme 1α (IRE1α) is most associated with downstream activation of immune cells.^{14, 15} IRE1α has a sensor domain that recognizes unfolded proteins in the ER lumen and enzymatic domains (kinase and endoribonuclease) that initiate UPR signaling in the cytosol.⁷ Once cells encounter stressors, the sensor domain of IRE1α initiates its oligomerization and autophosphorylation and activation of cytoplasmic enzymatic domains. The endoribonuclease of IRE1α then splices Xbp1 mRNA to allow translation of the transcription factor X box binding protein 1 (Xbp1),^16–18 which induces expression of many genes that improve ER protein folding and degradation.^19,20 The IRE1α endoribonuclease also regulates the expression of many UPR targets through post-transcriptional modifications via a process termed regulated IRE1α-dependent decay to restore ER homeostasis.^21,22 Further, in addition to self-phosphorylation, the kinase domain of IRE1α can directly phosphorylate other host factors, such as TRAF-2, which activates mitogen-activated protein kinase signaling, including activation of c-Jun N-terminal kinase.²³ Our previous work and that of others suggest that infection of innate immune cells by bacterial pathogens engages the IRE1α pathway through Toll-like receptor (TLR)/MyD88 signaling. ^15,24 Importantly, activation of IRE1α by TLR ligation promotes expression of inflammatory genes, including pro-inflammatory cytokines (tumor necrosis factor alpha [TNF-α], interleukin-1β [IL-1β], and IL-6).^15,25–27 Since inflammation is both necessary for immunity as well as pathogenic when occurring in excess or at inappropriate times, defining the role of innate immune IRE1α in respiratory infections is essential.

Methicillin-resistant Staphylococcus aureus (MRSA) infection is a leading hospital-borne infection that causes a wide spectrum of diseases ranging from localized skin infection to severe pneumonia and sepsis. ²⁸ Our previous studies have demonstrated that IRE1α is required for immunity against localized MRSA skin infection. ^24,27 Further, we found that bacterial infection stimulates IRE1α activation in peritoneal and bone marrow-derived macrophages to increase production of pro-inflammatory cytokines. ^24,26 A recent study demonstrated that macrophage IRE1α is essential for production of prostaglandin E₂ (PGE₂) during inflammation to promote chronic pain. ²⁹ However, macrophages from different tissues mount inflammatory responses with variable magnitudes to promote host defense without disrupting tissue-specific functions. ³⁰ In the lungs, PGE₂ specifically acts as an anti-inflammatory molecule promoting tissue repair, ³¹ suggesting that IRE1α may differentially control the tissue-specific function of lung macrophages.

Here, we investigated the direct contribution of IRE1α to the inflammatory responses of alveolar macrophages (AMs) in vitro during MRSA infection and of myeloid IRE1α to MRSA-induced primary and secondary pneumonia in vivo. Our results demonstrate that signaling by the IRE1α-Xbp1 pathway of the UPR imparts excessive AM inflammatory responses, which compromises immunity against MRSA-induced primary and secondary pneumonia. Moreover, the findings in this study suggest potential for modulation of IRE1α signaling to promote the resolution of acute inflammation in the lungs.

RESULTS

Activation of the IRE1α-Xbp1 pathway in AMs during MRSA infection promotes production of inflammatory mediators

Activation of IRE1α occurs in many lung inflammatory diseases where AM functions are critical for disease progression and resolution. ¹ To define the role of IRE1α in the AM inflammatory response, we first assessed IRE1α activation during bacterial infections. We chose MRSA as an infectious microbe, since MRSA is a common causative agent of hospital-acquired pneumonia. ³² Murine AM-like cells (MH-S) were infected with MRSA, and IRE1α activation was assessed by quantifying the spliced form of Xbp1. MRSA-infected macrophages increased the level of spliced Xbp1 by 6 h post infection (hpi), which was completely abolished when cells were treated with the IRE1α endoribonuclease inhibitor 4μ8C (Figures 1A and S1A). These data indicate that IRE1α is activated in AM-like cells during MRSA infection.

Figure 1. The IRE1α-Xbp1 pathway is activated in AM-like cells and enhances production of pro-inflammatory mediators.

(A) The expression level of spliced Xbp1 was quantified by RT-qPCR normalized relative to glyceraldehyde-3-phosphate dehydrogenase (Gapdh). The ΔΔCt was calculated relative to the average ΔCt of uninfected cells.

(B) The TNF-α level in culture media of macrophages was quantified by ELISA.

(C) Immunoblot analysis of pro-IL-1β and GAPDH from cell lysates. Levels of protein expression were quantified by analyzing the band intensity of pro-IL-1β relative to GAPDH using ImageJ software.

(D–F) Levels of the eicosanoids PGE₂ (D), TXB₂ (E), and 15(s)HETE (F) in culture media of macrophages were quantified by ELISA.

(G) Immunoblot analysis of COX-2 protein expression of macrophages. COX-2 expression was quantified relative to actin as in (C).

(H) Representative immunoblots of Xbp1 protein expression from NT-control and Xbp1 KD macrophages when cells were treated with DMSO (control) or stimulated with the ER stressor thapsigargin (TG; 1 μM) for 6 h.

(I) Levels of TNF-α and PGE₂ in culture media of NT-control and Xbp1 KD macrophages.

(J) Representative immunoblots of pro-IL-1β and GAPDH from cell lysates of NT-control and Xbp1 KD macrophages when cells were left untreated (mock) or infected with MRSA for 6 h. Levels of protein expression were quantified as in (C).

Graphs indicate the mean of ≥3 independent experiments ± SD. Statistical analysis was performed by one-way ANOVA with Tukey’s multiple-comparisons test (A–G) or two-way ANOVA with Holm-Sidak’s multiple-comparisons test (I and J). *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

To define the functional consequences of IRE1α activation on AM inflammatory responses, we first monitored the production of inflammatory cytokines (TNF-α and pro-IL-1β) and lipid mediators (PGE₂, TXB₂, and 15(S)-hydroxyeicosatetraenoic acid; 15(s)-HETE) when macrophages were infected with MRSA in the presence or absence of IRE1α inhibitor (Figures 1B–1F). MRSA infection triggered a robust immune response by inducing the production of each of these inflammatory mediators, and inhibition of IRE1α reduced the production of TNF-α, pro-IL-1β, PGE₂, and TXB₂. IRE1α control of the production of inflammatory lipid mediators was not applicable for all eicosanoids, as 15(s)-HETE was induced during infection but was not affected by inhibition of IRE1α (Figure 1F). In addition, the levels of lipoxygenase-dependent eicosanoids (LTB₄ and LTC₄) were neither increased during infection nor changed in the presence of 4μ8C (Figure S1B). Because PGE₂ and TXB₂ are produced via the cyclooxygenase-2 (COX-2)-dependent pathway, while 15(s)-HETE, LTB₄, and LTC₄ are all downstream of lipoxygenase, ³³ we monitored COX-2 expression in MRSA-infected macrophages. Expression of COX-2 protein was increased during MRSA infection relative to uninfected cells, and IRE1α inhibition reduced COX-2 expression by infected macrophages (Figure 1G). IRE1-α-mediated activation of the cyclooxygenase pathway occurred by increasing transcription levels of Ptgs2 (Cox-2) and Ptges but not Ptgs1 (Cox-1) (Figure S1C). By contrast, MRSA infection reduced expression of lipoxygenases (Alox15, Alox5, and Alox5ap) independent of IRE1α inhibition (Figure S1D), indicating that IRE1α controlled the production of PGE₂ and TXB₂ by reducing the expression of selected genes in the cyclooxygenase pathway. We next investigated whether IRE1α enhances cytokine production via activation of the main downstream target, Xbp1. We generated stable Xbp1 knockdown (Xbp1 KD) and non-target control (NT-control) MH-S cell lines via RNAi technology. Stimulating these cells with the potent ER stressor thapsigargin (TG) induced Xbp1 protein expression in NT-control macrophages but not in Xbp1 KD macrophages, indicating that Xbp1 expression is silenced (Figure 1H). Importantly, silencing Xbp1 phenocopied IRE1α inhibition and resulted in impairment of cytokine (TNF-α and pro-IL-1β) production and COX-2-dependent inflammatory mediators (PGE₂) when compared to MRSA-infected NT-control macrophages (Figures 1I and 1J). Collectively, our data suggest that the IRE1α-Xbp1 pathway is activated in MRSA-infected AM-like cells and promotes production of inflammatory mediators, including COX-2-dependent eicosanoids.

AMs and neutrophils are essential in immunity against MRSA-induced pneumonia

To investigate the role of IRE1α in pulmonary innate immune host defense, we first established a MRSA-induced pneumonia infection model by inoculating wild-type C57BL/6J mice with 10⁸ colony-forming units (CFUs) of MRSA via the oropharyngeal route to introduce the bacteria into the lungs.³⁴ IRE1α activation and lung tissue damage were assessed at 48 hpi, a time point when infected mice are considered most severely sick. Mice infected with MRSA exhibited increased Xbp1 splicing, indicating that IRE1α is activated in MRSA-infected lungs (Figure 2A). MRSA infection induced robust lung edema, which was quantified based on the accumulation of protein and DNA in the bronchoalveolar lavage fluid (BALF) (Figure 2B), and increased lung cell death, which was detected by terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) (Figure 2C). Induction of edema and lung cell death was accompanied by disruption of alveolar structure. This was apparent by the loss of type I epithelial cells in lung histology sections when labeled with anti-T1-α, a marker of alveolar surface/type I epithelial cells (Figure 2C),³⁵ and by staining lung histology sections with hematoxylin and eosin (H&E) (Figure S2A). These results indicate that MRSA infection induces IRE1α activation and acute lung injury. Previous study had established that mice become more susceptible to S. aureus infection when innate immune cells were depleted by anti-Ly6C/G.³⁶ Therefore, we sought to define the contribution of innate immune cells (AMs, neutrophils, or monocytes) to pulmonary host defense against MRSA. Mice were inoculated with clodronate liposomes via the oropharyngeal route to deplete AMs or anti-Ly6G antibodies intravenously to deplete neutrophils. Mice that received clodronate liposomes had a lower number of AMs in their BALF and lungs (Figure 2D). AM depletion rendered mice highly susceptible to a sub-lethal dosage (10⁷ CFUs) of MRSA, as these mice exhibited a reduced survival rate and had higher bacterial counts in the BALF and lungs when compared to mice that received control liposomes (Figures 2E and 2F). Profoundly, neutrophil depletion rendered mice more susceptible to MRSA than AM depletion, which could be due to the efficiency of a specific immune cell depletion. Mice that received anti-Ly6G antibodies had lower neutrophil infiltration, also known as polymorphonuclear leukocytes (PMNs), in MRSA-infected lungs, reduced survival during MRSA challenges, and higher bacterial counts in the lungs (Figures 2G–2I). Interestingly, neutrophil depletion provoked a compensatory increase in inflammatory monocyte recruitment to the infected lungs (Figure 2G). However, this increase in recruited inflammatory monocytes was insufficient to protect mice against MRSA challenges.

Figure 2. AMs and neutrophils are essential for immunity against MRSA-induced lung injury.

(A) The levels of spliced Xbp1 in lungs were assessed by RT-qPCR relative to Gapdh in uninfected mice (n = 6) or in mice infected with MRSA for 48 h (n = 6). The ΔΔCt was calculated relative to the average ΔCt of uninfected mice.

(B) The levels of protein and extracellular DNA in BALF of uninfected mice (n = 6) and MRSA-infected mice (n = 7).

(C) Representative confocal microscopy images of lung histology sections from uninfected and MRSA-infected mice. Histology sections were stained with TUNEL to label dead cells (green), anti-CD169 (red) to label macrophages, anti-T1α (magenta) to label type I epithelial cells, and DAPI (gray) to label DNA. The scale bar represents 20 μm.

(D) Flow cytometry analysis of AMs in BALF and lungs of mice receiving control liposomes (n = 6) or clodronate liposomes (n = 6) via oropharyngeal aspiration. Cells were stained with anti-CD45, anti-CD11c, and anti-CD170.

(E) Survival of MRSA-infected mice after aspiration of control liposomes (n = 10) or clodronate liposomes (n = 11).

(F) Bacterial burden in BALF and lungs of MRSA-infected mice after aspiration of control liposomes (n ≥ 7) or clodronate liposomes (n ≥ 5).

(G) Immunophenotyping of leukocytes in the lungs of mice when injected with control immunoglobulin G (IgG) (n = 8) or anti-Ly6G (n = 9) intravenously for two consecutive days prior to MRSA lung infection. Cells were stained for AM markers (anti-CD11c and anti-CD170), neutrophil (PMN) markers (anti-Ly6G and anti-CD11b), and monocyte (MONO) markers (anti-Ly6C and anti-CD11b) and analyzed by flow cytometry.

(H and I) Survival (H) and bacterial burden (I) when mice were injected with control IgG (n ≥ 8) or anti-Ly6G (n ≥ 9) intravenously for 2 consecutive days prior to MRSA lung infection.

(J) Bacterial burden in lungs of wild-type (WT; n = 16) and CCR2 knockout (CCR2 KO; n = 11) mice infected with MRSA via oropharyngeal aspiration for 48 h. Survival rates were graphed using a Kaplan-Meier survival plot, and p-values were calculated by log rank (Mantel-Cox) test. Other graphs represent the mean ± SD from at least two independent experiments. Statistical analysis was performed by Student’s t test (A, B, D, F, I, and J) or two-way ANOVA with Holm-Sidak’s multiple-comparisons test (G). *p < 0.05, **p < 0.01, ****p < 0.0001; ns, not statistically significant.

Alternatively, to measure the requirement of inflammatory monocytes in pulmonary immunity against MRSA, we assessed the susceptibility of CCR2-deficient mice to MRSA-induced pneumonia. CCR2 signaling is required for monocyte recruitment during immune responses. ³⁷ CCR2-deficient mice exhibited a moderate increase in susceptibility to MRSA-induced pneumonia relative to wild-type mice only when mice were infected with a lethal dose (10⁸ CFUs) of MRSA. Moreover, CCR2-deficient mice exhibited reduced inflammatory monocyte recruitment to MRSA-infected lungs relative to wild-type mice (Figure S2B) and a subtle decrease in survival with an increase in lung MRSA burden (Figures 2J and S2C). Together, our data establish that MRSA infection activates lung IRE1α and causes severe respiratory damage, which may lead to death when there is ineffective cooperative pulmonary host defense by AMs, neutrophils, and monocytes.

Ablation of myeloid IRE1α protects mice from MRSA-induced pneumonia

IRE1α is essential for placental development, and, thus, conventional IRE1α whole-body knockout is lethal. ³⁸ Therefore, to define the role of IRE1α in pulmonary innate immune response in vivo, we generated myeloid-specific IRE1α knockout mice by breeding Ire1α^flox/flox mice with Lyz2-Cre mice that express Cre recombinase in myeloid cells. ³⁹ Analysis of IRE1α protein expression in isolated BALF AMs from mice showed that IRE1α expression is restricted to AMs from control mice (IRE1α^f/f ) but not in myeloid-IRE1α deficient mice (IRE1α^ΔMyeloid) (Figure 3A). To address the role of IRE1α in pulmonary innate immune defense, we infected IRE1α^ΔMyeloid and control littermates (IRE1α^f/f) with a lethal dosage of MRSA via the oropharyngeal route and assessed survival, bacterial burden, leukocyte infiltration, and lung injury. After MRSA challenges, IRE1α^ΔMyeloid mice showed an enhanced survival rate over 48 h when compared to IRE1α^f/f mice (Figure 3B), suggesting that deletion of myeloid IRE1α protects mice from MRSA-induced pneumonia. In line with the survival rate, we observed lower bacterial counts in BALF and lungs of IRE1α^ΔMyeloid mice relative to IRE1α^f/f mice and reduced edema, which is indicated by the lower amounts of extracellular protein and DNA in BALF (Figures 3C and 3D). Immunophenotype analysis showed similar levels of neutrophils and monocytes recruited to BALF and lungs of MRSA-infected IRE1α^ΔMyeloid and IRE1α^f/f mice (Figure 3E). However, we observed higher AM counts, both relative leukocyte numbers and absolute numbers, in BALF of infected IRE1α^ΔMyeloid mice (Figures 3E and S3A). The presence of higher AM counts was also evident when BALF cells were immobilized by cytospin and visualized using Diff-Quik staining (Figure 3F). The increase in AM counts in infected IRE1α^ΔMyeloid mice was not due to the difference in baseline AM counts in naive mice, since there were comparable AM counts in uninfected IRE1α^ΔMyeloid and IRE1α^f/f mice (Figure S3B). These data suggest that deletion of myeloid IRE1α increases AM resilience to MRSA-induced cell death.

Figure 3. Silencing myeloid IRE1α protects mice from MRSA-induced pneumonia by inhibiting lung cell death.

(A) Immunoblot analysis of IRE1α and GAPDH from AMs isolated from uninfected myeloid IRE1α-deficient (IRE1α^ΔMyeloid ) mice and control littermates (IRE1α^f/f ).

(B) Survival curves of IRE1α^ΔMyeloid (n = 29) and IRE1α^f/f mice (n = 33) infected with MRSA for 48 h.

(C) Bacterial burden in BALF and lungs of MRSA-infected IRE1α^ΔMyeloid (n ≥ 11) and IRE1α^f/f (n ≥ 10) mice.

(D) Protein and DNA levels in BALF of MRSA-infected IRE1α^ΔMyeloid (n = 6) and IRE1α^f/f (n = 6) mice.

(E) Immunophenotyping analysis of leukocytes in BALF and lungs of IRE1α^ΔMyeloid (n ≥ 12) and IRE1α^f/f (n ≥ 11) mice infected via oropharyngeal aspiration for 48 h as in Figure 2G.

(F) Representative images of BALF cells from MRSA-infected IRE1α^ΔMyeloid and IRE1α^f/f mice. The scale bar represents 50 μm.

(G) Representative confocal microscopy images of lung histology sections from IRE1α^ΔMyeloid and IRE1α^f/f mice when infected with MRSA for 24 h. Sections were stained with TUNEL to label dead cells (green), anti-CD169 (red) to label macrophages, anti-T1α (magenta) to label type I epithelial cells, and DAPI (gray) to label DNA. The scale bar represents 20 μm.

(H) Percentage of TUNEL-positive cells in lung sections from IRE1α^ΔMyeloid (n = 3) and IRE1α^f/f (n = 3) mice. The percentage of TUNEL-positive cells was quantified relative to at least 450 total cells from each lung based on DAPI staining by using ImageJ software.

(I) Percentage of AM-positive cells in lungs from IRE1α^ΔMyeloid (n = 3) and IRE1α^f/f (n = 3) mice was quantified by flow cytometry.

Graphs represent the mean ± SD from at least two independent experiments. Statistical analysis was performed by Student’s t test (C, H, and I), one-way ANOVA with Tukey’s multiple-comparisons test (D), or two-way ANOVA with Holm-Sidak’s multiple-comparisons test (E). *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

To further characterize lung injury and cell death during MRSA-induced pneumonia, we evaluated lung histology sections of MRSA-infected mice at 24 hpi. Myeloid IRE1α-deficient mice did not exhibit severe lung injury, based on H&E staining and semiquantitative histopathology scoring (Figures S3C and S3D), and these mice only had mildly damaged alveoli in some of the lung lobes when assessed by TUNEL and anti-T1-α immunofluorescence staining (Figures 3G and 3H). In contrast, control wild-type mice exhibited severe lung injury, indicated by the presence of dense pockets of bacterial overgrowth and loss of type I epithelial cells lining numerous alveoli (Figures 3G and S3C). In addition, quantification of TUNEL staining showed more total dead cells and dead AMs in the lungs of MRSA-infected control mice relative to myeloid IRE1α-deficient mice (Figures 3G–3I). Together, our data suggest that myeloid IRE1α deficiency protects mice from MRSA-induced pneumonia by preventing excessive lung cell death.

Innate immune IRE1α exacerbates pulmonary inflammation in response to MRSA

We next sought to characterize the contribution of myeloid IRE1α to the production of inflammatory mediators in MRSA-infected lungs. We used a bead-based multiplex assay to quantify the levels of cytokines and chemokines produced in MRSA-infected lungs at 48 hpi. We observed lower levels of several nuclear factor κB-dependent cytokines (TNF-α, IL-1β, and IL-6) and chemokines (MCP-1, keratinocyte chemoattractant; KC, and MIP-1α) in MRSA-infected lungs of IRE1α^ΔMyeloid compared to lungs from IRE1α^f/f mice (Figures 4A and 4B). To define whether IRE1α promotes the early inflammatory responses, we monitored bacterial burden, leukocyte infiltration, and production of pro-inflammatory mediators at 6 hpi. There were similar bacterial burden and leukocyte infiltration in lungs of IRE1α^ΔMyeloid and IRE1α^f/f mice (Figures S4A and S4B). Although there were reduced transcript levels of several cytokines (Tnf-α, Il-6, and Il-1β) in the lungs of IRE1α^ΔMyeloid mice (Figure S4C), only selected cytokine proteins (granulocyte-macrophage colony-stimulating factor; GM-CSF, IL-1β, and IL-17α) were produced in significantly lower quantities in lungs of IRE1α^ΔMyeloid mice compared to IRE1α^f/f mice (Figure S4D). This indicates that IRE1α only enhanced production of selective cytokine proteins at an early stage of MRSA infection. Also, it should be noted that a general reduction in all inflammatory mediators at a late stage during infection (48 h) did not occur, as several cytokines and chemokines were produced in similar amounts in the lungs of both types of mice (Figure S4E). Interestingly, we also observed a higher level of interferon γ (IFN-γ) in the lungs of IRE1α^ΔMyeloid mice (Figure 4C), which may contribute to the observed protective response against MRSA infection.

Figure 4. Myeloid IRE1α modulates pulmonary inflammatory responses during MRSA-induced pneumonia.

(A–D) Levels of pro-inflammatory cytokines (A), chemokines (B), IFN-γ (C), and eicosanoids (D) in supernatants of lung single-cell suspensions from uninfected mice (n ≥ 5) and MRSA-infected IRE1α^ΔMyeloid (n ≥ 6) and control littermate IRE1α^f/f (n ≥ 6) mice at 48 h.

(E) Number of significantly changed genes in MRSA-infected lungs of IRE1α^ΔMyeloid (n = 4) and IRE1α^f/f (n = 3) mice relative to uninfected mice (n = 3). Upregulated (dark gray) or downregulated (light gray) genes were identified based on the log₁₀ ratio of infected normalized counts to uninfected normalized counts. Significant genes were determined based on p < 0.05.

(F) Volcano plot of differentially expressed genes in MRSA-infected lungs from IRE1α^f/f mice (n = 3) over MRSA-infected lungs from IRE1α^ΔMyeloid mice (n = 4). Red dots indicate genes that were significantly changed.

(G) Quantification of IFN-inducible GTPase (Gbp2, Gbp3, and Gbp5) transcripts in lungs of uninfected mice (n = 3), MRSA-infected IRE1α^f/f mice (n = 3), and MRSA-infected IRE1α^ΔMyeloid mice (n = 4) from NanoString data.

(H) RT-qPCR of Gbp2 and spliced Xbp1 transcript levels of NT-control and IRE1α KO macrophages when left untreated (mock) or infected with MRSA for 6 h. The expression level of spliced Xbp1 was quantified by RT-qPCR normalized relative to Gapdh. The ΔΔCt was calculated relative to the average ΔCt of uninfected cells.

Graphs represent the mean of ≥3 biological replicates ± SD. Statistical analysis was performed by one-way ANOVA with Holm-Sidak’s multiple-comparisons test (A–C and G), Student’s t test (D), or two-way ANOVA with Holm-Sidak’s multiple-comparisons test (H). *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

To identify the contribution of myeloid IRE1α to the production of lipid immune mediators during MRSA challenge, we extracted lipids from the acellular fraction of dissociated lung single-cell suspensions and analyzed these by mass spectrometry. The levels of inflammatory lipids produced in MRSA-infected lungs were normalized relative to the levels in the lungs of uninfected mice (Figure 4D). Although prostaglandins were detected at lower levels in infected lungs at 48 h relative to uninfected controls, we observed reduced levels of PGE₁, TXB₂, and 15-keto-PGF_2a in lungs of MRSA-infected IRE1α^ΔMyeloid mice compared to IRE1α^f/f mice. In addition, there were lower levels of other lipid mediators, including leukotrienes (LTB₄ and LTB₅), HETEs (5-HETE and 19-HETE), and 7-HDHA produced in MRSA-infected lungs of IRE1α^ΔMyeloid compared to IRE1α^f/f mice. The generally lower levels of lipid mediators produced in the lungs of MRSA-infected IRE1α^ΔMyeloid mice could be attributed to the lower levels of inflammation. These data suggest that myeloid IRE1α exacerbates lung inflammation during MRSA-induced pneumonia.

We next sought to characterize the contribution of myeloid IRE1α to the global pulmonary inflammatory response in MRSA-induced pneumonia. We used NanoString technology to quantify 785 transcripts of mouse inflammatory response genes in MRSA-infected lungs of IRE1α^ΔMyeloid and IRE1α^f/f mice as we performed previously.⁴⁰ We found that the number of inflammatory genes with expression that changed significantly in response to MRSA was higher in the lungs of IRE1α^ΔMyeloid mice than in those of IRE1α^f/f mice (Figure 4E). This was true for both the number of upregulated and downregulated genes. To define genes that are regulated by myeloid IRE1α during infection, we analyzed genes that differentially change in MRSA-infected IRE1α^f/f compared to MRSA-infected IRE1α^ΔMyeloid mice and identified 359 genes (Figure 4F; Table S1). This gene set contained the IL-20-subfamily cytokines Il19 and Il24, which were both increased in infected IRE1α^f/f relative to infected IRE1α^ΔMyeloid mice, indicating that myeloid IRE1α signaling is required for their induction in response to infection. In contrast, the antioxidant master regulator nuclear factor erythroid 2-related factor 2 (NRF2), the immunometabolism regulator hexokinase 3 (HK3), cluster of differentiation 68 (CD68), and macrophage receptor with collagenous structure (Marco) were among the genes increased in the absence of myeloid IRE1α. These data suggest that myeloid IRE1α signalling negatively regulates pulmonary oxidative stress by decreasing NRF-2 expression, immunometabolism by decreasing HK3 expression, and macrophage plasticity by decreasing M2 macrophage markers (CD68 and Marco). We then sorted the top 30 upregulated genes in infected IRE1α^f/f mice compared to infected IRE1α^ΔMyeloid mice. This set represents genes regulated by myeloid IRE1α during MRSA infection. This analysis revealed several inflammatory cytokines and chemokines (Csf2, Csf3, Ccl20, Cxcl2, Cxcl5, Il17a, Il12a, and others) that were increased in IRE1α^f/f and, to a lesser extent, in IRE1α^ΔMyeloid mice (Figure S4F). In this category, we also observed neutrophil-specific genes, such as Lcn2 and Elane, with differentially increased expression in MRSA-infected IRE1α^f/f relative to IRE1α^ΔMyeloid mice. These results indicate that activation of myeloid IRE1α positively promotes MRSA-induced lung hyperinflammation. We next analyzed genes with increased expression in MRSA-infected IRE1α^ΔMyeloid relative to IRE1α^f/f, which represent genes negatively regulated by IRE1α. This analysis identified several IFN-γ-dependent inflammatory genes, including Gbp2, Gbp5, Ifi203, Isg15, Oas1a, Oas2, Irf1, Irf7, Fcgr1, Fcgr4, and Stat-1, which concurred with the increased IFN-γ production in MRSA-infected IRE1α^ΔMyeloid mice (Figure 4C). Importantly, several genes with expression increased in MRSA-infected IRE1α^ΔMyeloid relative to IRE1α^f/f are reported to have antimicrobial properties. Examples of such genes include Gbp2, Gbp5, Ctsz, Ctss, and Psap (Figures 4G and S4F; Table S1), which may contribute to the protection from MRSA-induced pneumonia observed in IRE1α^ΔMyeloid mice. To directly assess the contribution of loss of IRE1α signaling to the ability of AMs to induce the antimicrobial IFN-induced guanylate-binding proteins, we quantified the expression of Gbp2 in the CRISPR-Cas9-generated IRE1α knockout (KO) MH-S cells relative to NT-control (Figure 4H). MRSA-infected IRE1α KO macrophages failed to splice Xbp1 transcripts, which validates deletion of IRE1α. Importantly, IRE1α KO macrophages induced higher expression of Gbp2 in response to MRSA when compared to NT-control macrophages. Thus, the lack of IRE1α signaling increases expression of macrophage antimicrobial genes like Gbp2 to promote MRSA clearance.

Last, we analyzed genes differentially downregulated during MRSA infection in IRE1α^f/f relative to IRE1α^ΔMyeloid, aiming to identify IRE1α-dependent gene suppression during infection (Figure S4G). Genes downregulated in MRSA-infected IRE1α^f/f, but not in IRE1α^ΔMyeloid, include Ace, Cxcl15, Map3k1, Lrrk2, and Prcp. This analysis also highlighted Mcoln1, Hsp90b1, NRF2, Ctsa, Gusb, and Ikbkg, which were suppressed in MRSA-infected IRE1α^f/f and upregulated in MRSA-infected IRE1α^ΔMyeloid. The contributions of these genes to protecting mice against MRSA-induced pneumonia will be investigated in our future studies. Collectively, our data suggest that ablation of myeloid IRE1α alters pulmonary inflammation into a protective response against MRSA.

Global IRE1α inhibition dampens MRSA-induced pneumonia

To leverage our findings into a potential therapeutic approach, we sought to define whether inhibition of IRE1α with the small-molecule inhibitor 4μ8C would protect mice from MRSA-induced pneumonia. Mice were treated with 4μ8C or vehicle control via intraperitoneal injections 24 h prior to MRSA lung infection and then every 24 h throughout the duration of the experiment. Infected mice treated with 4μ8C exhibited attenuated Xbp1 splicing in the lungs (Figure 5A). Importantly, IRE1α inhibition resulted in increased survival, like what was seen with myeloid IRE1α-deficient mice, which was accompanied by reduced bacterial counts in BALF and lungs (Figures 5B and 5C). Mice treated with 4μ8C had similar levels of protein and DNA in BALF and similar recruitment of neutrophils and monocytes to the BALF and lungs when compared to the vehicle control (Figures 5D and 5E); thus, IRE1α inhibition did not alter vascular permeability in response to MRSA infection. Instead, the increased immune protection was associated with an increase in the relative abundance of AMs (Figure 5E). To further visualize BALF cells from MRSA-infected mice treated with the IRE1α inhibitor, BALF cells were extracted, immobilized on microscopy slides, and Diff-Quik stained (Figure 5F). Like MRSA-infected IRE1α^ΔMyeloid mice, mice treated with 4μ8C showed an increase in the relative abundance of macrophages in BALF during MRSA infection compared to BALF of infected control mice. This may suggest that inhibition of IRE1α increases AM resilience in response to MRSA.

Figure 5. IRE1α inhibition confers protection against MRSA-induced pneumonia.

(A) The levels of spliced Xbp1 in lungs was assessed by RT-qPCR relative to Actin in uninfected mice (n = 5) or in mice treated with 4μ8C (n = 5) or control solvent (DMSO, n = 5) via the intraperitoneal route and infected with MRSA. The ΔΔCt was calculated relative to the average ΔCt of uninfected mice.

(B) Survival of MRSA-infected mice when mice were treated with 4μ8C (n = 14) or DMSO (n = 17). The p value was calculated by the log rank (Mantel-Cox) test.

(C–E) Bacterial burden (C), protein and DNA levels (D), and immunophenotyping analysis of leukocytes (E) in BALF and lungs of MRSA-infected mice when injected with 4μ8C (n ≥ 7) or DMSO (n ≥ 6).

(F) Representative cytospin image of BALF cells from MRSA-infected mice treated with 4μ8C or DMSO. The scale bar represents 50 μm.

(G) Heatmaps depicting expression of cytokines and chemokines in lungs of MRSA-infected mice treated with 4μ8C (n = 6) or DMSO (n = 6) relative to uninfected mice (n = 5).

Graphs indicate the mean ± SD from two independent experiments. Statistical analysis was performed by one-way ANOVA with Holm-Sidak’s multiple-comparisons test (A), Student’s t test (C, D, and G), or two-way ANOVA with Holm-Sidak’s multiple-comparisons test (E). *p < 0.05, **p < 0.01, ***p < 0.001.

We next sought to determine whether IRE1α inhibition impacts production of inflammatory mediators in infected lungs. The lungs from infected mice treated with 4μ8C or vehicle control were dissociated into cell suspensions in phosphate-buffered saline (PBS), and acellular supernatants were analyzed using bead-based flow cytometric immunoassay panels for cytokines and chemokines (Figure 5G). Mice treated with 4μ8C had lower amounts of cytokines (TNF-α, IL-6, and IL-1β) and chemokines (MIP-1β, KC, IP10, and MCP-1) than controls. In contrast, IRE1α inhibition increased IFN-γ levels compared to vehicle control-treated mice, which phenocopies the ablation of myeloid IRE1α. Together, our data suggest that pharmacologically blocking IRE1α signaling protects mice from MRSA-induced pneumonia by reprogramming pulmonary inflammatory responses.

Ablation of myeloid IRE1α protects mice against secondary MRSA pneumonia

Viral infections such as influenza and coronavirus substantially worsen secondary bacterium-induced pneumonia. ^41,42 A recent study showed that IRE1α signaling is among the most induced pathways in mice coinfected with influenza and MRSA. ⁴³ However, it is not clear whether ablation of myeloid IRE1α is as protective against influenza/MRSA coinfection as it is to primary MRSA infection. To establish influenza/MRSA coinfection, we first aimed to identify a viral dose and then a time point to introduce MRSA secondary to influenza. Mice were inoculated with 10 or 100 plaque-forming units (PFUs) of murine-adapted influenza A (PR8) via the oropharyngeal route. Survival and body weight were monitored over 12 days (Figures 6A and 6B). All mice started to lose weight by day 5; however, only the mice infected with 100 PFUs of PR8 exhibited mortality on day 8, while mice infected with 10 PFUs eventually recovered. These data provide us with study conditions including an inoculum size of 100 PFUs and a time point of day 6 post influenza infection to induce lung damage sufficient for introduction of secondary MRSA infection without lethality. Interestingly, this time point is consistent with human clinical data, as secondary bacterium-induced pneumonia is typically observed within the first 6 days of influenza infection. ⁴⁴ When mice were challenged with a sub-lethal dose of MRSA on day 6 post influenza infection, all mice succumbed within 24 hpi, while all mice infected with MRSA alone survived (Figures 6C and 6D). These data highlight that mice infected with influenza become highly susceptible to a sub-lethal dosage of MRSA and establish a model for MRSA-induced secondary pneumonia.

Figure 6. Myeloid IRE1α exacerbates influenza/MRSA coinfection.

(A and B) Change in body weight (A) and survival (B) of mice infected with 10 PFUs (n = 6) or 100 PFUs (n = 7) of PR8. Percentages were calculated relative to the starting bodyweight.

(C) Schematic of MRSA-induced secondary pneumonia.

(D) Survival curves of MRSA-induced primary (n = 5) and secondary (n = 6) pneumonia.

(E) Body weight changes of IRE1α^ΔMyeloid (n = 13) and IRE1α^f/f (n = 12) mice infected with 100 PFUs of PR8.

(F–H) Survival (F), bacterial burden in the lungs (G), and immunophenotyping of leukocytes in the lungs (H) of MRSA-induced secondary pneumonia in IRE1α^ΔMyeloid (n ≥ 11) and IRE1α^f/f (n ≥ 9) mice at 24 h.

Survival rates were graphed using a Kaplan-Meier survival plot, and p-values were calculated by log rank (Mantel-Cox) test. Other graphs indicate the mean ± SD from at least two independent experiments. Statistical analysis was performed by Student’s t test. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001; nd, not a discovery..

To investigate the role of myeloid IRE1α in MRSA-induced secondary pneumonia, IRE1α^ΔMyeloid mice and control littermates (IRE1α^f/f) were infected with 100 PFUs of PR8 for 6 days and then challenged with a sub-lethal dose of MRSA (Figure 6C). Both IRE1α^ΔMyeloid and IRE1α^f/f mice lost a similar percentage of body weight in the first 6 days post influenza infection, suggesting that a similar extent of lung injury occurred (Figure 6E). However, IRE1α^ΔMyeloid mice exhibited a higher survival rate post MRSA challenge when compared to IRE1α^f/f mice (Figure 6F). The higher survival rate of IRE1α^ΔMyeloid mice coincided with greater MRSA clearance, as there were lower bacterial counts in the lungs of IRE1α^ΔMyeloid mice relative to lungs of IRE1α^f/f mice (Figure 6G). To further characterize the role of myeloid IRE1α in controlling the clinical outcomes of MRSA-induced secondary pneumonia, we analyzed the relative abundance of immune cells and production of inflammatory cytokines and chemokines. Like primary MRSA infection, there were higher levels of AMs in influenza/MRSA-coinfected IRE1α^ΔMyeloid mice relative to those in coinfected IRE1α^f/f mice (Figure 6H). This suggests that the lack of myeloid IRE1α also preserves AMs during coinfection. Remarkably, we also observed an altered relative abundance of lymphocytes in infected myeloid IRE1α-deficient mice. There were fewer B cells and a trend of more T and natural killer cells in the lungs of influenza/MRSA-coinfected-IRE1α^ΔMyeloid mice relative to lungs of coinfected-IRE1α^f/f mice. The mechanism by which myeloid IRE1α regulates adaptive immune cell recruitment and function will be investigated in future studies. Last, we observed a similar level of inflammatory mediators produced in the lungs of IRE1α^ΔMyeloid and IRE1α ^f/f mice during coinfection (Figure S5). This could indicate that the loss of myeloid IRE1α is insufficient to modulate lung inflammation during influenza/MRSA coinfection. Collectively, our data highlight that blocking the activity of myeloid IRE1α could be beneficial in protecting against bacterium-induced secondary pneumonia.

DISCUSSION

Acute respiratory infections are often associated with ER stress and exuberant inflammation that can result in permanent lung damage and death. However, whether the ER stress regulator IRE1α counteracts or supports the pathogenesis of pneumonia is unknown. Here, we found that ablation of myeloid IRE1α or global inhibition IRE1α activity protects mice from MRSA-induced primary pneumonia and pneumonia secondary to influenza. These data highlight the potential benefits of modulating IRE1α activity as a novel therapeutic intervention to dampen lung inflammation and injury during acute respiratory infections.

Our findings support a model in which activation of innate immune IRE1α induces lung cell death that contributes to the severity of pneumonia. A number of studies have shown that different mechanisms of programmed cell death, including inflammasome-mediated pyroptosis and receptor-interacting serine/threonine-protein kinase 1 (RIPK1)-dependent necroptosis, contribute significantly to the pathology of S. aureus-induced pneumonia. ^45–48 While IRE1α can promote survival and cell fate, depending on the tissue and cell type, magnitude of stress, and type of the stress, if ER stress is unresolved, then IRE1α acts as an executioner. ⁴⁹ Our work and that of others have shown that IRE1α activation induces and preserves thioredoxin-interacting protein, which, in turn, activates inflammasome-dependent pyroptosis. ^26,50 In addition, when ER stress is sustained, RIPK1 can directly interact with IRE1α to induce necroptosis. ⁵¹ Therefore, our data suggest that IRE1α potentiates MRSA-induced pneumonia by enhancing pathways that lead to cell death, perhaps via pyroptosis and/or necroptosis.

Silencing myeloid IRE1α signaling permits activation of type II IFN-mediated host defense to promote immunity against respiratory pathogens. We found that IFN-γ and IFN-γ-dependent antimicrobial genes were among the upregulated genes when IRE1α signaling is inhibited. This indicates that myeloid IRE1α signaling can negatively control induction of the type II IFN response. Stimulation of immune cells with IFN-γ increased MRSA killing in vitro, which suggests that increased levels of IFN-γ in the lungs would enhance the ability of immune cells to kill respiratory pathogens like MRSA. ⁵² However, in contrast to this, a recent study suggests that increasing levels of IFN-γ in response to influenza infection contributes to the extreme pathology of MRSA-induced secondary pneumonia by producing excessive TNF-α. ⁵³ In addition, mice lacking IFN-γ signaling (Ifngr1-deficient mice) exhibit a similar susceptibility to primary MRSA-induced pneumonia, as seen in WT mice. ⁵⁴ A possible explanation for this discrepancy is that primary MRSA infection does not produce sustained IFN-γ in WT and Ifngr1-deficient mice to drive IFN-γ-dependent host defense in the lungs. Both WT and Ifngr1-deficient mice should trigger myeloid IRE1α signaling to repress production of IFN-γ in MRSA-infected lungs. Thus, the presence and absence of Ifngr1 is negligible to primary MRSA lung infection, since the ligand (IFN-γ) is not sufficiently made. In the context of MRSA-induced secondary pneumonia, the lack of myeloid IRE1α signaling could still reduce the negative impact of excessively produced TNF-α despite the high levels of IFN-γ. Another observation that remains unsettled is the source of IFN-γ produced in MRSA-infected lungs of myeloid IRE1α-deficient mice. IRE1α could suppress IFN-γ production in myeloid cells like AMs autonomously or indirectly through crosstalk between myeloid and other immune cells. We and others have reported previously that activated macrophages can produce IFN-γ by an unknown mechanism. ^40,55,56 This implies that suppression of IRE1α signaling could be a mechanism by which AMs contribute to IFN-γ production in infected lungs. Alternatively, in the absence of IRE1α signaling, AMs could signal to other immune cells to stimulate and release IFN-γ. In our future studies, we will explore mechanisms by which myeloid IRE1α limits IFN-γ production and the practical significance to progression and resolution of different inflammatory diseases.

Tuning down production of lipid mediator PGE ₂ by inactivating myeloid IRE1α signaling promotes survival and may reduce chest pain associated with pneumonia. We observed that the IRE1α-Xbp1 axis selectively controls prostanoids through upregulation of COX-2 in AM-like cells and lungs upon MRSA infection. PGE₂ can exhibit pro- and anti-inflammatory roles depending on which receptors it engages on target cells. ⁵⁷ In some contexts, PGE ₂ can suppress macrophage host defense by reducing phagocytosis and/or production of antimicrobial molecules like nitric oxide. ^58,59 In addition, inhibition of COX-2 has a beneficial suppressive effect in hyperinflammatory lung diseases, ⁶⁰ inferring that modulation of PGE ₂ by inhibition of IRE1α signaling could mitigate disease severity. Interestingly, a recent study suggests that activation of IRE1α-Xbp1 promotes pain sensation by increasing production of PGE₂. ²⁹ One of the main complications in patients with bacterium-induced pneumonia is severe chest pain, which could be driven in part by IRE1α-dependent production of PGE₂. Therefore, we speculate that inhibition of IRE1α could have a dual advantage by reducing lung inflammation and relieving chest discomfort associated with pneumonia.

Limitations of the study

IRE1ɑ is globally expressed by every cell in the body. In our investigation of the role of myeloid IRE1ɑ in immunity against pneumonia, the role of IRE1ɑ in nonhematopoietic cells remained largely undefined. Our findings indicate that myeloid IRE1ɑ exacerbates inflammation, cell death, and lung injury during MRSA infection. However, we did not explore whether these responses occur in a cell-autonomous manner or via corroborated interaction with various lung cell lineages. We acknowledge that the in vitro AM responses using MH-S cells could be different from responses of primary AMs. Expression of inflammatory genes was performed in whole lungs, which did not allow us to discriminate whether IRE1ɑ acts on innate immune cells to promote their expression or indirectly influence other nonhematopoietic cells, such as type I and II epithelial cells, to express these genes. Single-cell RNA sequencing could provide some insights into which cell type is responsible for expressing specific genes. However, the results from single-cell RNA sequencing are still insufficient to tease apart their contributions to pneumonia outcomes but may serve as the initial step to do so.

RESOURCE AVAILABILITY

Lead contact

Data, materials, and information can be obtained by directing requests to the lead contact, Basel H. Abuaita (babuaita@lsu.edu).

Materials availability

Reagents and resources can be shared upon request.

Data and code availability

• All data reported in this paper will be shared by the lead contact upon request.

• This paper does not report any new code.

• Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

STAR★METHODS

EXPERIMENTAL MODELS AND STUDY PARTICIPANT DETAILS

Mice

Wild-type C57BL/6J and CCR2 KO mice were purchased from the Jackson Laboratory. Generation of IRE1α floxed (IRE1α^f/f) and Myeloid IRE1α deficient (IRE1α^ΔMyeloid ) mice has been described previously. ³⁹ All mice were maintained in the Division of Laboratory Animal Medicine (DLAM) and all animal procedures were approved by the Institutional Animal Care and Use Committee at the School of Veterinary Medicine, Louisiana State University and A&M College-Baton Rouge. Mice were in-house genotyped using Direct mouse genotyping kit (Cat #K1025, APExBIO).

Bacteria

A community associated methicillin-resistant Staphylococcus aureus (MRSA) strain USA300 LAC was used in the study. Bacteria were maintained at − 70^◦C in Luria-Bertani (LB) medium (Cat# 244610, Becton Dickinson) containing 20% glycerol. Bacteria were streaked onto tryptic soy medium (Cat# 211825, Becton Dickinson) plates and grown overnight at 37^◦C. Selected colonies were cultured overnight in tryptic soy broth (TSB) at 37^◦C with shaking (220 rpm). Bacteria were pelleted, washed, and resuspended in phosphate buffer saline (PBS). The bacterial inoculum was estimated based on OD₆₀₀, and verified by plating serial dilutions onto the TSB plates to determine colony forming units (CFU).

Mouse lung infection

Male and female mice between the age of 8–12 weeks were used for the in vivo infection. Mice were anesthetized by isoflurane inhalation (3% isoflurane, 2 L/min oxygen). Anesthetized mice were placed on a surgical rack and inoculated with 10⁷ bacteria in 50 μL of PBS (sub-lethal dose) or 10⁸ bacteria in 75 μL of PBS (lethal dose ) via oropharyngeal aspiration. For the influenza/MRSA coinfection, mice were inoculated with 100 plaque-forming units (PFU) of influenza A virus (strain A/Puerto Rico/8/1934 H1N1, PR8) in 50 μL of PBS via oropharyngeal aspiration. PR8 was kindly provided by Dr. Huang Lab at Louisiana State University School of Veterinary Medicine. Viral infection was allowed to develop for 6 days and subsequently mice were challenged with non-lethal MRSA infection. All experimental mice were monitored at least every 6 h for the progression of the infections. Mice were sacrificed at 6, 24, or 48h post-infection, BALF and lungs were collected in PBS. Lungs were mechanically dissociated into single cell suspension as previously described, ^27,61 and further analyzed for host responses and lung damage including bacterial count enumeration, immune cell infiltration, protein and DNA accumulation in BALF, and inflammatory mediator quantification.

METHOD DETAILS

Macrophage and neutrophil depletion

AM depletion was achieved by administering 50 μL of Control or Clodronate coated liposomes (Cat# CP-005–005, Liposoma BV) to mice lung via oropharyngeal aspiration in two consecutive days. The efficiency of AM depletion was determined by measuring the number of AM in the BALF on day 3 post depletion. To deplete neutrophils, mice were injected intravenously with 200 μL (0.2 mg) of rat IgG2a isotype control (Cat# BE0089, BioXCell) or an anti-mouse Ly6G monoclonal antibody (Cat# BE0075–1, BioXCell) in two consecutive days. Mice were infected with MRSA on day 3 post neutrophil depletion and the efficiency of depletion was monitored by measuring the reduction of recruited neutrophils to MRSA-infected lungs.

Pharmacological IRE1α inhibition in vivo

IRE1α small molecule inhibitor, 4μ8C (Cat# HY-19707, MedChemExpress) was dissolved in Dimethylsulfoxide (DMSO) (25 mg/mL) and then prepared for in vivo administration by adding the following solvent, in order: 10% DMSO +40% PEG 400 (Cat# HY-Y0873A, MedChemExpress) + 5% Tween-80 (Cat# HY-Y1891, MedChemExpress) + 45% PBS. Mice were injected 10 mg/kg of 4μ8C or vehicle control intraperitoneally 24h prior to MRSA lung infection and then every 24 h throughout the duration of the experiment.

Macrophage infection

Murine alveolar macrophage cells (MH-S-CRL-2019, ATCC) were used for in vitro infection with MRSA. MH-S cells were cultured in Roswell Park Memorial Institute (RPMI) 1640 media containing 2 mM L-glutamine and 10% heat-inactivated fetal bovine serum (FBS). Cells were incubated at 37^◦C in 5% CO₂. Macrophages were seeded in either 24- or 6-well tissue culture treated plate at a density of 2 X 10⁵ or 8 X 10⁵ cells/well respectively. The next day, cells were infected with MRSA at multiplicity of infection (MOI) of 20. Macrophages were incubated with Gentamicin (50 μg/mL) (Cat# 120–098-661, Quality Biological) to kill extracellular bacteria at 1.5hpi and was maintained throughout the experiment. Wherever indicated, macrophages were incubated with 4μ8C (25 μM) or DMSO at 1.5hpi and incubated for 4.5h for a total of 6hpi. Cell culture supernatants were collected and stored at − 20^◦C for quantification of inflammatory mediators. TNF-α was analyzed by the Biolegend ELISA kit. Eicosanoids including PGE₂, TXB₂, LTB₄, LTC₄, and 15s-HETE were analyzed by Cayman Chemical ELISA kits. Cell lysates were also collected in Triton X-100 lysis buffer (50 mM Tris +150 mM NaCl+ 1% Triton X-100) for immunoblotting analysis or in Lysis/Binding buffer (Cat# AM1561, ThermoFisher) for mRNA quantification.

Generation of IRE1α and Xbp1 deficient MH-S cells

HEK293T cells were used to generate the lentivirus for CRISPR-Cas9 knockout and shRNA knockdown. HEK293T cells were grown in Dulbecco’s Modified Eagle Medium (DMEM) with 10% FBS. Cells were transfected with the TRC shRNA encoded plasmid (pLKO.1) or guided RNA (gRNA) encoded plasmid (lentiCRISPRv2) along with packaging plasmids (pHCMV-G, and pHCMV-HIV-1) using Turbofect transfection reagent (Cat# R0534, ThermoFisher). Media was changed after 24h and virus particles were collected after 72h post-transfection. Media-containing lentivirus was sterile filtered and used to transduce macrophages. The mouse Xbp1 specific shRNA plasmid and the non-target control shRNA plasmid (Cat# SHC016) were purchased from Millipore Sigma (Table S2). The mouse IRE1α specific gRNA and the non-target gRNA control were previously cloned into lentiCRISPRv2. ⁶² Macrophages were transduced with lentivirus by mixing 1 mL of medium containing 10⁶ cells with 1 mL of medium containing virus in a 6-well plate. Cells were incubated for 48 h at 37^◦C in 5% CO₂ prior selecting transduced cells with puromycin (3 μg/mL). IRE1α knockout was confirmed by the loss of protein expression using anti-IRE1α antibody clone 14C10 (Cell Signaling) or by absence of its endonuclease activity when cells were infected with MRSA. The efficiency of Xbp1 knockdown was monitored by immunoblot analysis using anti-Xbp1 antibody clone E9V3E (Cell Signaling) when the cells were treated with ER stress inducer Thapsigargin (1 mM) (Cat# 10522, Cayman Chemical) to induce Xbp1 protein expression.

Immunophenotyping and TUNEL staining

BALF and lungs were collected from uninfected mice, 6hpi, or 48hpi in a total of 3 mL of PBS. The lungs were mechanically dissociated into a single-cell suspension using a 70 μm strainer, and red blood cells (RBC) were lysed by using an RBC lysis buffer (Cat# 420301, Biolegend). Cells were Fc blocked with TruStain FcX (anti-mouse CD16/32) Antibody (Cat# 101319, Biolegend), according to the manufacturer’s instructions. Subsequently, cells were stained with the following fluorescent dye conjugated anti-bodies; anti-CD45 clone 30-F11, anti-CD11c clone N418, anti-CD170 clone S17007L, anti-Ly-6C clone HK1.4, anti-Ly-6G clone 1A8, anti-CD11b clone M1/70, anti-CD3 clone 17A2, anti-CD19 clone 6D5, and anti-NK-1.1 clone PK136 (Biolegend) for 30 min. For TUNEL staining, cells from lung single cell suspensions were stained with anti-CD45, anti-CD11c, and anti-CD170 to label AMs and then stained with in Situ Cell Death Detection Kit according to manufacturer’s protocol (Cat# 11684795910, Roche). Cells were washed and analyzed on a LSRFortessa Cell Analyzer (BD Biosciences). Compensations were performed using UltraComp Plus Compensation Beads (Cat# 01–3333, ThermoFisher). Data was further analyzed with FlowJo software. The relative abundance of immune cells in BALF and lungs was determined by quantifying the percentage of AMs (CD11c⁺, CD170⁺), neutrophils (Ly-6G⁺, CD11b⁺), monocytes (Ly-6C⁺, CD11b⁺), T cells (CD3⁺), B cells (CD19⁺), and NK cells (NK1.1⁺) of total leukocytes (CD45⁺). Absolute cell counts were calculated by using CountBright Absolute Counting Beads, for flow cytometry (Cat# C36950, ThermoFisher) according to manufacturer’s instructions.

Bacterial burden and inflammatory mediator analysis

BALF and lung single cell suspensions were collected into 3 mL of PBS. BALF and lung suspensions were then diluted 1:20 in sterile ultrapure water to lyse host cells. Bacterial burden was quantified by enumerating CFU per sample after serial dilution and plating onto TSB agar plates. CFUs were counted using an Acolyte counter and confirmed by manual counting. To quantify inflammatory mediators, acellular fractions of lung single cell suspensions were collected by centrifugation and used in multiplex bead-based panels that allow quantification of multiple analytes simultaneously using Flow cytometry. The LEGENDplex mouse inflammation panel (Cat# 740446, Biolegend) and proinflammatory chemokine panel (Cat# 740451, Biolegend) were used according to the manufacturer’s protocol. Data were acquired by BD LSRFortessa flow cytometer and analyzed by LEGENDplex data analysis software suite.

Histology, immunofluorescence, and TUNEL staining

Lungs were inflated with 1.5 mL of 2% low melting point agarose in PBS and fixed with 10% neutral formalin for 2 days. The five lobes were separated and embedded in paraffin. Lungs were sectioned (5 μm per section) by the histology core at Louisiana Animal Disease Diagnostic Laboratory (LADDL) and stained with hematoxylin and eosin (H&E) staining. H&E slides were imaged on the HAMAMATSU NanoZoomer Slide Scanner System. For immunofluorescence staining, histology sections were deparaffinized and antigen retrieval was performed in sodium citrate buffer (10 mM sodium citrate, 0.05% Tween 20, pH 6.0). Sections were permeabilized with PBS +0.2% Triton X-100 for 30 min and then blocked by incubating in staining buffer (PBS +5% Bovine serum albumin (BSA, Cat# BP1600, Fisher Scientific) and 10% normal goat serum (Cat# 10000C, ThermoFisher) for 1h. Sections were stained with the following primary antibodies overnight at 4^◦ C: anti-T1α clone 8.1.1 (DSHB) and anti-CD169 clone 3D6.112 (Biolegend). Sections were incubated in the terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) (Cat# 11684795910, Roche) buffer for 1h at 37 ^◦ C. Slides were washed with 0.1% Triton X-100 in PBS and incubated with fluorescent conjugated secondary antibodies (ThermoFisher). Sections were then counterstained with DAPI to label DNA. Slides were washed with 0.1% Triton X-100 in PBS for 20 min and micro cover glasses (#1 thickness Cat# 48393–106, VWR) were mounted on using ProLong Diamond Antifade Mount-ant (Cat# P36961, ThermoFisher). Sections were imaged using an FV3000 confocal laser scanning microscope. The percentage of TUNEL-positive cells was quantified relative to the total cells based on DAPI staining by using ImageJ software. A semi-quantitative scoring of lung injury was performed based on microscopic assessment of inflammation, fibrin deposit/exudation, bacterial growth/accumulation and TUNEL positive area in histology lung sections. For each category, the following scores were given based on the percentage of area affected: no injury (0%) = 0; mild injury (1–25%) = 1, moderate injury (26–50%) = 2, marked injury (51–75%) = 3, severe injury (76–100%) = 4). Scores on each category were added for each mouse to get a total lung injury score (AU).

Cytospin and Diff-Quik staining

Rapid differential staining (Diff-Quik) was performed using a Quik-Dip Stain Kit (Cat# MER 1002, Mercedes Scientific) according to manufacturer’s protocol. Briefly, cells in the BALF were immobilized onto microscopy slides by centrifugation of 50 μL and 100 μL of collected BALF cells suspensions for 4 min at 2000 rpm using Wescor Cytopro cytocentrifuge. Slides were dried overnight at room temperature and then dipped sequentially for a few seconds into 3 solutions (1^st: Methyl Alcohol fixative, 2^nd: Eosin Y staining mix, 3^rd: Methylene Blue and Azure A staining mix). The slides were finally dipped into clean water to wash stain solutions and dried overnight. The slides were imaged using HAMAMATSU NanoZoomer Slide Scanner System using 40X objective lens and then processed using Olympus Olyvia software.

Immunoblot analysis

Cell lysates were collected in Triton X-100 lysis buffer containing PhosphotaseArrest II (Cat# 786–451, G-Biosciences) and Halt Protease Inhibitor Cocktail (Cat# 87785, ThermoFisher). Cell lysates were centrifuged, supernatant lysates were heated at 95^◦C for 3 min in Laemmli sample buffer (Cat# 1610747, Bio-Rad) with 10% β-mercaptoethanol (Cat# 1610710, Bio-Rad). Proteins were separated on Mini-PROTEAN TGX Stain-Free gels (Cat# 4568095, Bio-Rad) with 1X Tris/Glycine/SDS running buffer (Cat# 1610732, Bio-Rad). The gels were then transferred onto 0.45 μm nitrocellulose membranes (Cat# 10600002, Amersham) using Trans-Blot SD Semi-Dry Transfer system in 1X Tris/CAPS Buffer (Cat# 1610778, Bio-Rad). Membranes were blocked for 45 min in a blocking buffer (5% BSA +0.05% Tween 20 in PBS) at room temperature shaking on an orbital shaker. Membranes were incubated with primary anti-bodies (1:1000 dilution) in a blocking buffer overnight at 4^◦C. The primary antibodies used were rabbit anti-IL-1β (D6D6T) monoclonal antibody (Cat# 31202, Cell Signaling), rabbit anti-COX 2 (D5H5) monoclonal antibody (Cat# 12282, Cell Signaling), mouse anti-GAPDH (6C5) antibody (Cat# sc-32233, Santa Cruz), and rabbit anti-β-Actin (D6A8) monoclonal antibody (Cat# 8457, Cell Signaling). Membranes were washed with PBS for at least 15 min and incubated with secondary LI-COR antibodies (1:5000 dilution) for 1h at room temperature. The secondary antibodies used were IRDye 800CW goat anti-mouse IgG antibody (Cat# 925–32210, LI-COR) and IRDye 680RD goat anti-rabbit IgG antibody (Cat# 925–68071, LI-COR). Membranes were washed again and scanned using the Odyssey Infrared Imaging System (LI-COR Biosciences). The images were subjected to intensity based densitometric analysis on ImageJ software to quantify the protein levels. The intensity of each band was normalized to the intensity of endogenous control (GAPDH or Actin).

BALF protein and DNA quantification

BALF samples collected from lungs were centrifuged and the cell free supernatants were used to quantify protein and DNA. Protein quantification was performed using Pierce BCA Protein Assay Kit (Cat# 23225, ThermoFisher) according to manufacturer’s protocol. To quantify DNA in samples, total DNA was isolated from 200 μL of normalized BALF cell free supernatants using QIAGEN DNeasy Blood & Tissue Kit (Cat# 69506, QIAGEN) and eluted in 100 μL of elution buffer. DNA levels were quantified using a NanoDrop Spectrophotometer.

NanoString and reverse transcription real-time quantitative PCR (RT-qPCR) analysis

Total RNA was isolated from 500 μL of lysis/binding buffer used to lyse alveolar macrophages (MH-S) or lung cells using mirVana miRNA isolation kit (Cat# AM1561, ThermoFisher). RNA was quantified by Nanodrop and normalized across all conditions. cDNA was synthesized using M-MLV Reverse Transcriptase (Cat# 28025013, ThermoFisher), random hexamers (Cat# N8080127, ThermoFisher), dNTP Mix (Cat# 18427088, ThermoFisher), and RNase Inhibitor (Cat# N8080119, Applied Biosystems). RT-qPCR was performed using Applied Biosystems PowerUp SYBR Green Master Mix (Cat# A25778, ThermoFisher) with the following condition: [cycle 1: 50^◦C for 2 min, cycle 2: 95^◦C for 2 min, cycle 3: 95^◦C for 15 s, 55^◦C for 15 s, 72^◦C for 1 min (40 repeats), cycle 4: 95^◦C for 15 s, 60^◦C for 15 s and 95^◦C 15 s]. Endogenous controls (Gapdh or Actin) were used to calculate the relative gene expression and presented as fold change (2^−ΔΔCt). The Ct value of endogenous control was subtracted from Ct value of target gene to get ΔCt for each sample. Then, the average ΔCt of uninfected control group was subtracted from the ΔCt of each sample to get ΔΔCt. Finally, the fold change in gene expression was calculated using 2^−ΔΔCt. The primer sequences are listed in Table S2. For NanoString assay, the nCounter mouse host response panel (NanoString Technologies) were used to monitor changes in expression of 785 inflammatory genes in MRSA infected lungs of myeloid IRE1α deficient mice and control littermates. Normalized gene counts were calculated using nSolver 4.0 software (NanoString Technologies).

Xbp1 splicing assay

Total RNA was extracted by using Direct-zol RNA Kit (Cat# R2052, Zymo Research) or mirVana miRNA isolation kit (Cat# AM1561, ThermoFisher). cDNA was synthesized using 500 ng of total RNA as described above. Xbp1 transcripts (spliced and unspliced) were amplified by RT-PCR using cDNA obtained, GoTaq G2 Colorless Master Mix (Cat# M7832, Promega) and the primers listed in Table S2. Following were the PCR conditions: step 1, 95^◦C 2 min; step 2, 35 amplification cycles (95^◦C 30 s, 60^◦C 30 s, 72^◦C 30 s); and step 3, 72^◦C 10 min. The PCR product obtained was purified and digested with PstI restriction enzyme (Cat# R0140L, New England Biolabs) to discriminate between unspliced and spliced bands. DNA fragments were run by electrophoresis on a 2.5% agarose gel and imaged on Azure 600 Imager (Azure Biosystems). The intensity of unspliced and spliced bands were quantified using ImageJ software, and the percent spliced Xbp1 was calculated using the following formula: [Xbp1_S/(Xbp1_S + Xbp1_U)].

Lipidomics analysis

Supernatants from lung single-cell suspensions were collected by centrifugation and stored at − 20^◦C until analysis. Samples were thawed at 4^◦C for 2h and then 500 μL of each sample was extracted twice with 800 μL of ethyl acetate. Organic/aqueous phase extraction was facilitated by centrifugation at 13,000xg for 5 min. Following centrifugation, the ethyl acetate layer was removed, combined, and dried under a stream of nitrogen gas. Each sample was dissolved in 100 μL of methanol for LC-MS/MS analysis. Following extraction, proteins in the aqueous fraction were precipitated with 1 mL of ice-cold acetone by incubating on ice for 1h. The proteins were pelleted by centrifugation at maximum speed at 4^◦C for 10 min. The proteins were suspended in 200 μL of 1% SDS in PBS, sonicated twice with a probe sonicator, and incubated for 1h at 65^◦C. Proteins were quantified by BCA exactly as described in the kit instructions. LC-MS/MS analysis was performed at the LSU School of Veterinary Medicine Mass Spectrometry Resource Center on a Shimadzu 8060NX triple quadrupole mass spectrometer interfaced with a Shimadzu Nexera XS 40 series UHPLC and Shimadzu CTO-40S column oven. 5 μL of each sample, blank, or standard was analyzed in either positive or negative ionization mode, depending on the analyte. Chromatographic separation was achieved using a Phenomenex Kinetex C₈ column (150 mm length, 2.1 mm internal diameter, 2.6 μm particle size, 100 Å pore size) with a Phenomenex Security Guard C₈ guard column (2.1 mm internal diameter). Mobile phase A was 0.1% formic acid in water and mobile phase B was 0.1% formic acid in acetonitrile. The column oven was set to 40^◦C and the flow rate was set to 0.4 mL/min for the entire analysis. The starting condition was 10% B, which was ramped to 25% B over the first 5 min of the method. The B mobile phase was then ramped to 35% over the next 5 min. Finally, the B mobile phase was ramped to 75% over the next 10 min. The column was washed at 98% B for 8 min, then equilibrated to 10% B for 8 min. All instrument voltages were determined and optimized empirically prior to the analysis. The Q1 m/z, Q3 m/z, retention time, and ionization mode for each analyte is listed in Table S3. The area under the curve (AUC) from each sample was normalized to total protein for differences in starting material. Fold change of normalized AUC values of infected mice relative to the average of uninfected control mice were determined for each analyte.

QUANTIFICATION AND STATISTICAL ANALYSES

Experiments were performed at least n ≥ 3 times on different days unless otherwise stated. Graphs represent mean ± standard deviation from biological replicates. GraphPad was used to calculate the p-values. Student’s t test was used to determine significant differences between the two groups, a One-way ANOVA with either Tukey’s or Holm-Sidak’s post-test for multiple comparisons was used to determine significant differences between three or more groups, and a two-way ANOVA followed by Holm-Sidak’s multiple comparisons test was used to determine significant differences between groups that are defined by columns and rows. p-values of less than 0.05 were considered significant and all statistically significant comparisons within groups were considered. *p < 0.05; **p < 0.01, ***p < 0.001, ****p < 0.0001, ns: not statistically significant, nd: not a discovery.

Supplementary Material

SUPPLEMENTAL INFORMATION

Supplemental information can be found online at https://doi.org/10.1016/j.celrep.2025.115632.

KEY RESOURCES TABLE

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Antibodies
Rabbit anti-β-Actin (D6A8) mAb	Cell Signaling	Cat# 8457; RRID: AB_10950489
Rabbit anti-IL-1β(D6D6T) mAb	Cell Signaling	Cat# 31202; RRID: AB_2799001
Rabbit anti-COX 2 (D5H5) mAb	Cell Signaling	Cat# 12282; RRID: AB_2571729
Mouse anti-GAPDH (6C5) mAb	Santa Cruz	Cat# sc-32233; RRID: AB_627679
IRDye 800W Goat anti-Mouse IgG pAb	LI-COR	Cat# 925–32210; RRID: AB_2687825
IRDye 680RD Goat anti-Rabbit IgG pAb	LI-COR	Cat# 925–68071; RRID: AB_2721181
Goat anti-Mouse IgG pAb. Alexa Fluor 488	ThermoFisher	Cat# A11001; RRID: AB_2534069
Goat anti-Rabbit IgG pAb, Alexa Fluor 488	ThermoFisher	Cat# A11008; RRID: AB_143165
Goat anti-Mouse IgG pAb, Alexa Fluor 594	ThermoFisher	Cat# A-11005; RRID: AB_2534073
Goat anti-Rabbit IgG pAb Alexa Fluor 594	ThermoFisher	Cat# A-11012; RRID: AB_2534079
Goat anti-Rat IgG pAb Alexa Fluor 594	ThermoFisher	Cat# A11007; RRID: AB_10561522
Goat anti-Syrian Hamster IgG pAb Alexa Fluor 647	ThermoFisher	Cat# A-21451; RRID: AB_2535868
InVivoMAb rat IgG2a isotype control, anti-trinitrophenol	BioXCell	Cat# BE0089; RRID: AB_1107769
InVivoMAb anti-mouse Ly6G	BioXCell	Cat# BE0075–1; RRID: AB_1107721
IRE1α (14C10) Rabbit mAb	Cell Signaling	Cat# 3294; RRID: AB_823545
XBP-1s (E9V3E) Rabbit mAb	Cell Signaling	Cat# 40435; RRID: AB_2891025
TruStain FcX ™ (anti-mouse CD16/32) Antibody	Biolegend	Cat# 101319; RRID: AB_1574973
Alexa Fluor® 488 anti-mouse CD45 Antibody	Biolegend	Cat# 103122; RRID: AB_493531
PE/Cyanine7 anti-mouse CD11c Antibody	Biolegend	Cat# 117318; RRID: AB_493568
PE/Dazzle™ 594 anti-mouse CD170 (Siglec-F) Antibody	Biolegend	Cat# 155530; RRID: AB_2890716
Alexa Fluor® 647 anti-mouse Ly-6C Antibody	Biolegend	Cat# 128010; RRID: AB_1236550
Brilliant Violet 605™ anti-mouse Ly-6G Antibody	Biolegend	Cat# 127639; RRID: AB_2565880
Brilliant Violet 421™ anti-mouse/human CD11b Antibody	Biolegend	Cat# 101236; RRID: AB_11203704
Brilliant Violet 605™ anti-mouse CD3 Antibody	Biolegend	Cat# 100237; RRID: AB_2562039
Brilliant Violet 785™ anti-mouse CD19 Antibody	Biolegend	Cat# 115543; RRID: AB_11218994
PE/Cyanine7 anti-mouse NK-1.1 Antibody	Biolegend	Cat# 108714; RRID: AB_389364
anti-T1α	DSHB	Cat# 8.1.1; RRID: AB_531893
Purified anti-mouse CD169 (Siglec-1) Antibody	Biolegend	Cat# 142402; RRID: AB_10916523
CD11c (D1V9Y) Rabbit mAb	Cell Signaling	Cat# 97585; RRID: AB_2800282
Bacterial and virus strains
A community-associated methicillin-resistance Staphylococcus aureus (MRSA) strain USA300	Abuaita Lab	Nebraska Tn Mutant Library (NTML)
Influenza A Virus, A/Puerto Rico/8–9VMC3/1934 (H1N1)	Huang Lab	NR-29028
Chemicals, peptides, and recombinant proteins
Clodronate Liposomes & Control Liposomes (PBS)	Liposoma BV	Cat# CP-005–005
Difco™ LB Broth, Miller (Luria-Bertani)	Becton Dickinson	Cat# 244610
Difco™ Agar Technical Solidifying Agent	Becton Dickinson	Cat# 281210
Difco™ Tryptic Soy Broth	Becton Dickinson	Cat# 211825
4μ8C	MedChemExpress	Cat# HY-19707
DMSO, Dimethyl sulfoxide	VWR	Cat# N182–5X10ML
PEG 400, Polyethylene glycol 400	MedChemExpress	Cat# HY-Y0873A
Tween-80	MedChemExpress	Cat# HY-Y1891
HyClone™ RPMI 1640 media, with L-glutamine	Cytiva	Cat# SH30027.01
Fetal Bovine Serum	Biowest	Cat# S1620
Gentamicin Solution, 50 mg/mL	Quality Biological	Cat# 120–098-661
Acid-Phenol:Chloroform, pH 4.5 (with IAA, 125:24:1)	ThermoFisher	Cat# AM9720
Dulbecco’s Modified Eagle Medium (DMEM) with high glucose	Cytiva	Cat# SH30022.01
TurboFect ™ Transfection Reagent	ThermoFisher	Cat# R0534
Puromycin Dihydrochloride	ThermoFisher	Cat# A1113802
Thapsigargin	Cayman Chemical	Cat# 10522
RBC Lysis Buffer (10X)	Biolegend	Cat# 420301
UltraComp eBeads™ Plus Compensation Beads	ThermoFisher	Cat# 01–3333-42
CountBright™ Absolute Counting Beads, for flow cytometry	ThermoFisher	Cat# C36950
Agarose (Low-Melting, Nucleic Acid Recovery/Molecular Biology Grade)	Fisher scientific	Cat# BP165–25
Bovine Serum Albumin, Heat Shock Treated	Fisher scientific	Cat# BP1600
Normal Goat Serum	ThermoFisher	Cat# 10000C
DAPI	MilliporeSigma	Cat# 9542
ProLong™ Diamond Antifade Mountant	ThermoFisher	Cat# P36961
PhosphataseArrest™ II	G-Biosciences	Cat# 786–451
Halt™ Protease Inhibitor Cocktail, EDTA-Free (100X)	ThermoFisher	Cat# 87785
4x Laemmli Sample Buffer	Bio-Rad	Cat# 1610747
2-Mercaptoethanol	Bio-Rad	Cat# 1610710
4–20% Mini-PROTEAN® TGX Stain-Free™ Protein Gels, 12 well, 20 μL	Bio-Rad	Cat# 4568095
Amersham Protran 0.45 NC nitrocellulose Western blotting membranes	Cytiva	Cat# 10600002
M-MLV Reverse Transcriptase (200 U/μL)	ThermoFisher	Cat# 28025013
RNase Inhibitor	ThermoFisher	Cat# N8080119
PowerUp™ SYBR™ Green Master Mix for qPCR	ThermoFisher	Cat# A25778
Tween 20, 100% Nonionic Detergent	Bio-Rad	Cat# 1706531
10x Tris/CAPS Buffer for Semi-Dry Blotting	Bio-Rad	Cat# 1610778
10x Tris/Glycine/SDS	Bio-Rad	Cat# 1610732
Tris-HCL, 1M Solution, pH 8.0	ThermoFisher	Cat# J22638-AP
PstI	New England Biolabs	Cat# R0140L
TRIzol™ Reagent	ThermoFisher	Cat# 15596026
TRITON™ X-100 (Polyethylene glycol tert-octylphenyl ether), Proteomics Grade	VWR	Cat# 97063–864
Critical commercial assays
APExBIO Direct mouse genotyping kit	APExBIO	Cat# K1025
ELISA MAX™ Deluxe Set Mouse TNF-α	Biolegend	Cat# 430904
Prostaglandin E2 Express ELISA Kit	Cayman Chemical	Cat# 500141
Thromboxane B2 Express ELISA Kit - Monoclonal	Cayman Chemical	Cat# 10004023
Leukotriene B4 Express ELISA Kit	Cayman Chemical	Cat# 500003
Leukotriene C4 ELISA Kit	Cayman Chemical	Cat# 501070
15(S)-HETE ELISA Kit	Cayman Chemical	Cat# 534721
mirVana™ miRNA Isolation Kit, without phenol	ThermoFisher	Cat# AM1561
LEGENDplex™ Mouse Inflammation Panel (13-plex) with V-bottom Plate	Biolegend	Cat# 740446
LEGENDplex™ Mouse Proinflammatory Chemokine Panel (13-plex) with V-bottom Plate	Biolegend	Cat# 740451
Roche In Situ cell death detection kit	Roche	Cat# 11684795910
Quik-Dip® Stain Kit	Mercedes Scientific	Cat# MER 1002
Pierce™ BCA Protein Assay Kit	ThermoFisher	Cat# 23225
DNeasy Blood & Tissue Kit (250)	QIAGEN	Cat# 69506
nCounter mouse host response panel	NanoString Technologies	Nanostring.com
Direct-zol™ RNA MiniPrep	Zymo Research	Cat# R2052
GoTaq® G2 Colorless Master Mix	Promega	Cat# M7832
Experimental models: Cell lines
MH-S cells	ATCC	CRL-2019
HEK293T cells	ATCC	CRL-3216
Experimental models: Organisms/strains
C57BL/6J	Jackson Laboratory	Stock No: 000664
B6.129S4-Ccr2tm1Ifc /J (CCR2 KO)	Jackson Laboratory	Stock No: 004999
B6.129P2-Lyz2tm1(cre)Ifo /J (LysMcre)	Jackson Laboratory	Stock No: 004781
IRE1αf/f (IRE1α floxed)	Abuaita Lab	Sule et al.39
Oligonucleotides
Xbp1 specific shRNA plasmid pLKO.1 with sense sequence (GGTTGAGAACCAGGAGTTAAG)	MilliporeSigma	TRCN0000232018
MISSION® pLKO.1-puro Non-Target shRNA Control Plasmid DNA	MilliporeSigma	SHC016
Packaging plasmid, pHCMV-G	Abuaita Lab	Abuaita et al.24
Packaging plasmid, pHCMV-HIV-1	Abuaita Lab	Abuaita et al.24
lentiCRISPRv2	addgene	Cat# 52961
Random Hexamers (50 μM)	ThermoFisher	Cat# N8080127
dNTP Mix (10 mM ea)	ThermoFisher	Cat# 18427088
Software and algorithms
Excel 2024	Microsoft	Microsoft.com
ImageJ	NIH	ImageJ.nih.gov
Prism 10	GraphPad	Graphpad.com
Data Analysis Software Suite for LEGENDplex™	Biolegend	Legendplex.qognit.com
nSolver 4.0	NanoString	Nanostring.com
Other
Micro Cover Glasses, Rectangular (24 × 60 mm No.1)	VWR	Cat# 48393–106

Highlights.

• The IRE1α-Xbp1 arm of the UPR elevates alveolar macrophage inflammatory responses

• IRE1α activation during infection increases cytokine storm, cell death, and lung injury

• Loss of myeloid IRE1α promotes type II interferon-mediated antimicrobial defenses

• Silencing or inhibition of IRE1α protects mice from primary and secondary MRSA pneumonia