Skip to main content
Oxford University Press logoLink to Oxford University Press
. 2026 Sep 24;118(10):qiag131. doi: 10.1093/jleuko/qiag131

Δ9-Tetrahydrocannabinol exposure shifts eosinophil and macrophage transcriptional programs toward an anti-inflammatory phenotype in helminth infection

Jennell Jennett 1, Martin Olmos 2, Ka Man Lam 3, Sarah Midou 4, Nicholas V DiPatrizio 5, Meera G Nair 6,✉,2
PMCID: PMC13653213  PMID: 42784722

Abstract

Cannabis use is increasing globally, yet the immunological effects of Δ9-tetrahydrocannabinol, the main intoxicating component of cannabis, remain incompletely understood. Given prior evidence that endocannabinoid signaling influences helminth immunity and type 2 inflammation, we investigated how sustained Δ9-tetrahydrocannabinol exposure alters immune responses to the helminth Nippostrongylus brasiliensis, which infects the lung and small intestine of mice. C57BL/6J mice were treated with Δ9-tetrahydrocannabinol (5 mg/kg/d) or vehicle for 14 d prior to helminth infection and assessed for parasite burden, innate immune cell and T cell responses, and transcriptional changes in lung eosinophils and macrophages. Δ9-Tetrahydrocannabinol exposure did not significantly alter infection-associated weight loss or helminth burden; however, Δ9-tetrahydrocannabinol selectively restrained infection-induced circulating eosinophils and monocytes while increasing regulatory T cells. T cell activation assays showed reduced TNFα and IFNγ secretion in splenocytes from Δ9-tetrahydrocannabinol-treated infected mice. Bulk RNA sequencing showed that Δ9-tetrahydrocannabinol shifted lung eosinophils and CD11c+ lung macrophage-enriched cells from inflammatory, fibrotic, and costimulatory pathways toward stress and metabolic-adaptive transcriptional programs. Within the infected macrophage-enriched population, Δ9-tetrahydrocannabinol reduced CD80 expression while increasing MHC class II and antigen presentation-associated genes, suggesting a potential shift in macrophage-mediated T cell activation. Consistent with altered inflammatory and tissue remodeling-associated programs, immunofluorescent staining showed that Δ9-tetrahydrocannabinol mitigated infection-associated loss of lung collagen. Collectively, these findings indicate that Δ9-tetrahydrocannabinol reshapes the immune response to helminth infection by restraining innate and T cell effector responses while altering lung eosinophil and macrophage activation programs.

Keywords: eosinophils, helminth infection, macrophages, THC, type 2 inflammation


THC reshapes helminth-induced type 2 inflammation by restraining inflammatory leukocyte responses and reprogramming lung eosinophils and macrophages.

1. Introduction

Cannabis is one of the most used psychoactive substances in the United States. In 2022, an estimated 61.9 million people aged 12 yr or older reported past-year cannabis use, corresponding to 22.0% of the population in this age group. Cannabis use was highest among young adults aged 18 to 25, with 38.2% reporting past-year use.1 As cannabis use increases with expanding medical and recreational legalization, there is a growing need to understand how cannabis-derived compounds affect immune function. Δ9-Tetrahydrocannabinol (THC) is the primary intoxicating component of cannabis and acts as a partial agonist of cannabinoid receptors.2 Although THC is commonly studied for its neurological and behavioral effects, cannabinoid receptors and endocannabinoid pathways are also involved in immune regulation, raising important questions about how THC exposure alters inflammatory responses.3,4

The endocannabinoid system has emerged as an important regulator of host immunity during infection and inflammation. In helminth infection, both host- and helminth-derived endocannabinoids are generated and can influence host immune responses and parasite burden.5 Human studies have also suggested a relationship between cannabis use and helminth infection. Among Aka foragers of the Congo Basin, cannabis use was highly prevalent, and levels of urinary Δ9-tetrahydrocannabinol-11-oic acid (THC-COOH, the primary metabolite of THC) were negatively associated with parasite infection and reinfection.6 However, this study evaluated whole-cannabis exposure in a human population and could not determine whether THC directly altered parasite burden, host immunity, or both. Together, these findings suggest that cannabinoid pathways intersect with anti-helminth immunity, but the specific effects of THC on host immune responses remain unclear.

Infection with Nippostrongylus brasiliensis, a rodent hookworm, is a well-established murine model of helminth infection and type 2 inflammation, inducing eosinophilia, macrophage activation, Th2 cytokine responses, and lung tissue remodeling.7–9 This model provides a controlled system to determine whether THC changes the magnitude or quality of immune responses during type 2 infection and inflammation. Prior work from our group showed that inhibition of peripheral cannabinoid receptor subtype 1 during N. brasiliensis infection increased airway eosinophilia and worsened pulmonary pathology, suggesting that cannabinoid signaling can restrain eosinophilic inflammation in this setting.10 Considering that THC is a partial cannabinoid receptor agonist, these findings raise the possibility that THC exposure may alter endocannabinoid signaling at cannabinoid receptors and ensuing inflammatory responses during helminth infection-induced type 2 immunity.

THC has also been shown to regulate immune pathways relevant to inflammatory activation. In activated human T cells, THC suppresses proliferation, reduces IFNγ production, and alters Th1/Th2 cytokine balance.11 In the myeloid compartment, THC has been reported to inhibit macrophage chemotaxis and alter macrophage differentiation through reactive oxygen species-dependent mechanisms.12–15 These findings suggest that THC can regulate both adaptive and innate immune pathways. However, whether THC exposure alters the balance between immune activation, inflammatory restraint, and tissue remodeling during type 2 inflammation remains poorly understood.

Despite these observations, critical gaps remain. First, it is unclear whether THC alone is sufficient to alter parasite burden in a controlled helminth infection model, especially given human studies linking cannabis consumption to reduced helminth burden.6 Second, it is unknown whether THC alters type 2 inflammation by reducing immune cell accumulation, changing inflammatory function, or modifying immune cell activation states. In addition, the consequences of THC-associated immune modulation for lung tissue repair following infection-induced injury remain unclear.9,16 To address these gaps, we used N. brasiliensis infection as a controlled model of helminth infection and type 2 inflammation to evaluate how THC exposure affects parasite burden, innate and T cell immune responses, and overall outcomes in infection-induced lung tissue injury.

2. Materials and methods

2.1. Mouse studies

All animal procedures were approved by the University of California, Riverside Institutional Animal Care and Use Committee (AUP#48). Six-week-old male C57BL/6J mice were maintained under standard vivarium conditions with ad libitum chow and water. THC was stored, prepared, and administered by authorized personnel in accordance with DEA controlled substance requirements and UCR institutional procedures. THC was dissolved in a vehicle consisting of 7.5% DMSO, 7.5% Tween 80, and 85% sterile saline. Mice were injected intraperitoneally daily with THC (5 mg/kg/d; generously donated by the National Institute on Drug Abuse Drug Supply Program) or vehicle for 14 d prior to infection. The 5 mg/kg/d THC dose was selected based on prior pharmacokinetic studies showing peak plasma THC concentrations in adult mice comparable to those observed in humans after smoking a single cannabis cigarette.17 On day 14, mice were briefly anesthetized with isoflurane and infected subcutaneously with 550 N. brasiliensis L3 larvae, as previously described.7,9 THC or vehicle treatment was paused from day 0 to day 4 postinfection, then resumed until collection on day 8 postinfection. Fecal egg burden was measured at day 7 postinfection, and blood, bronchoalveolar lavage fluid (BALF), lungs, spleens, and small intestines were collected at day 8 postinfection for immune analyses and adult worm counts.

2.2. BALF, lung, and blood leukocyte isolation and flow cytometry

BALF, lung, and blood leukocytes were isolated for flow cytometry. BALF was collected by 3 lavages with 0.7 mL sterile 1× PBS. Lungs were dissociated using the mouse Lung Dissociation Kit and gentleMACS Octo Dissociator with Heaters (Miltenyi Biotec). Blood was collected into 4% sodium citrate, diluted, and separated on Histopaque-1077. Viable leukocytes were counted, blocked with CD16/32 and rat IgG, stained with the antibody panels listed in Tables S1 and S2, and analyzed using NovoExpress and FlowJo.

2.3. Ex vivo splenocyte stimulation

Spleens were mechanically dissociated, red blood cells were lysed, and splenocytes were cultured in complete T cell culture media. Cells were plated at 5 × 106 cells per well and stimulated with anti-CD3, anti-CD28, and recombinant mouse IL-2 for 72 h at 37 °C. Culture supernatants were collected for cytokine analysis. IFNγ was measured by LEGENDplex Mouse Th1/Th2 Panel, and TNFα was measured by ELISA.

2.4. Lung macrophage and eosinophil isolation for bulk RNA sequencing

Whole-lung single-cell suspensions were filtered and enriched by magnetic bead purification. CD11c+ cells were isolated using biotinylated anti-mouse CD11c antibody and Streptavidin MicroBeads, and the CD11c-negative flow-through was used to enrich Siglec-F+ eosinophils. Enriched cell fractions were lysed in Buffer RLT, and RNA was isolated using the RNeasy Mini Kit. Libraries were prepared and sequenced by the Novogene Corporation. Raw sequencing reads were assessed for quality using FastQC18 and summarized with MultiQC.19 Adapter sequences and low-quality bases were trimmed using Trimmomatic.20 Trimmed reads were aligned to the mouse reference genome using STAR aligner,21 and gene-level read counts were generated using FeatureCounts.22 Downstream analyses were performed in R. Differential gene expression analysis was conducted using DESeq2.23 Genes with an adjusted P-value, using Benjamini–Hochberg correction, ≤0.05 and an absolute log2 fold change > 1 were considered differentially expressed unless otherwise indicated. For targeted antigen presentation and costimulation-associated genes, an adjusted P-value ≤ 0.05 and absolute log2 fold change > 0.25 were used. Variance-stabilized expression values generated by DESeq2 were used for heatmap visualization. Gene set enrichment analysis was performed using Hallmark gene sets.24,25

2.5. Principal component analysis

For Principal component analysis (PCA), genes with at least 10 counts in at least 2 samples were variance-stabilized using DESeq2. PCA was performed on the 500 most variable genes using centered, unscaled expression values and plotted in ggplot2 by treatment, infection status, and cell type.

2.6. Digital cell quantification analysis

Immune-cell deconvolution was performed in R using immunedeconv. Mouse Ensembl identifiers were mapped to gene symbols, duplicate symbols were summed, and digital cell quantification (DCQ) was used to estimate relative macrophage and dendritic-cell enrichment. Nonnegative estimates were normalized within each sample and interpreted as inferred relative composition, not direct cell frequency.

2.7. Lung immunofluorescent staining and imaging

Lungs were inflated with 4% paraformaldehyde, fixed overnight in 10% neutral buffered formalin, transferred to 70% ethanol, and paraffin-embedded by the UCLA Translational Pathology Core Laboratory. Five-micrometer FFPE sections were stained with antibodies against Collagen VI and GSL I (Table S3), quenched for autofluorescence, mounted with DAPI-containing antifade medium, and imaged at 20× on a Keyence microscope. Collagen VI signal was quantified in Fiji/ImageJ as integrated density per field after 16-bit grayscale conversion and background subtraction.

2.8. Statistical analysis

Statistical analyses of non-sequencing data were performed using GraphPad Prism. Fecal egg and adult worm burdens were analyzed using an unpaired t-test, as these comparisons involved 2 independent treatment groups. Outcomes measured across both treatment and infection conditions, including immune-cell frequencies, cytokine concentrations, and Collagen VI staining, were analyzed by 2-way ANOVA to evaluate the main effects of treatment, infection, and their interaction. Tukey's multiple-comparisons test was used for post hoc pairwise comparisons. Differential gene expression was analyzed in R using DESeq2, which models RNA-sequencing count data using a negative binomial distribution. Benjamini–Hochberg correction was applied to control the false-discovery rate. Genes with an adjusted P-value < 0.05 and an absolute log2 fold change > 1 were considered differentially expressed, except for the targeted antigen-presentation and costimulation analysis, for which an absolute log2 fold change > 0.25 was used. Hallmark gene-set enrichment results with an adjusted P-value < 0.05 were considered significant. Data are presented as mean ± SEM unless otherwise indicated, and P < 0.05 was considered statistically significant.

3. Results

3.1. THC exposure does not alter parasite burden following N. brasiliensis infection but affects circulating leukocyte responses

Cannabis use has been associated with altered helminth burden in a human population,6 raising the possibility that cannabinoid exposure may influence host parasite responses. To determine whether THC exposure altered helminth burden and infection-associated immune responses, we employed an established murine model of helminth infection with N. brasiliensis (Nb), a rodent hookworm that infects the lung and small intestine with an acute infection cycle of 7 to 10 d.7,8,26 Mice were treated intraperitoneally with THC or vehicle for 2 weeks prior to Nb infection, followed by assessment of infection-associated weight change, fecal egg burden, and intestinal worm burden (Fig. 1a). Following Nb infection, vehicle- and THC-treated mice showed acute weight loss between days 2 and 4 postinfection, consistent with the timing of Nb-associated lung migration and tissue injury (Fig. 1b). However, THC treatment did not significantly alter fecal egg burden or adult worm burden compared with vehicle-treated infected controls (Fig. 1c and d).

Figure 1.

Four-panel figure displaying experimental layout and outcome metrics following Nippostrongylus brasiliensis infection. Panel A shows a diagram of the experimental timeline. Panel B is a line graph showing percentage body weight change over time. Panels C and D are bar graphs displaying fecal egg counts and adult worm burden, respectively, comparing vehicle- and THC-treated groups.

THC exposure does not alter infection-induced weight loss or parasite burden following Nippostrongylus brasiliensis infection. Vehicle- and THC-treated mice were left naïve or infected with Nb. a) Experimental design. Created by Biorender. b) Percent body weight change. c) Fecal egg burden. d) Adult worm burden. Data are mean ± SEM pooled from 2 independent experiments (n = 4 to 7 mice per group). Statistical analysis was performed using an unpaired t-test for egg burden and worm burden. ns, not significant.

We next examined whether THC altered immune cell responses following Nb infection. Analysis was conducted 8 d postinfection, consistent with prior work from our lab demonstrating immune changes influenced by cannabinoid receptor signaling.5,10 Whole blood flow cytometry was performed to quantify monocytes, eosinophils, and CD4+ T cells (Figure S1). Nb infection increased circulating eosinophil frequencies in vehicle-treated mice, whereas this infection-induced eosinophil response was reduced in THC-treated animals (Fig. 2a). Nb infection also increased circulating monocyte frequencies in vehicle-treated mice, and THC-treated infected mice had reduced circulating monocyte frequencies compared with vehicle-treated infected controls (Fig. 2b). In contrast, CD4+CD25+ regulatory T cell frequencies were increased in THC-treated infected mice (Fig. 2c). Total CD4+ T cell frequencies in the blood were not significantly altered by THC treatment (Figure S1), indicating that THC did not broadly impact the proportion of circulating CD4+ T cells.

Figure 2.

Three-panel figure showing flow cytometry data for circulating leukocyte populations in vehicle- and THC-treated naive and infected mice. Panels A, B, and C display representative flow cytometry gating plots alongside corresponding summary scatter/bar plots for eosinophil frequencies (A), monocyte frequencies (B), and CD4+ CD25+ regulatory T cell frequencies (C) among CD45+ cells.

THC exposure reduces infection-induced circulating eosinophilia and alters circulating leukocyte responses. Whole-blood leukocytes were assessed in vehicle- and THC-treated naïve and Nb-infected mice. a to c) Representative plots and frequencies of eosinophils (a), monocytes (b), and CD4+CD25+ regulatory T cells (c) among CD45+ cells. Data are mean ± SEM pooled from 2 independent experiments (n = 4 to 7 mice per group). Two-way ANOVA with Tukey's multiple-comparisons test. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0,001; ns, not significant.

Together, these data indicate that THC exposure does not significantly alter parasite burden or infection-associated weight loss following Nb infection but does alter systemic immune responses. Specifically, THC limited infection-induced circulating eosinophilia and monocyte responses while increasing regulatory T cell frequencies. Overall, these findings support a model in which THC does not broadly suppress anti-helminth immunity but instead shifts the balance of systemic inflammatory and regulatory immune responses during type 2 inflammation.

3.2. THC and helminth infection induce broad transcriptional changes in lung CD11c+ enriched macrophages and eosinophils

We next evaluated lung-specific changes. Although THC reduced circulating eosinophils and monocytes, BAL and lung eosinophil and myeloid cell frequencies in naïve mice or following Nb infection were not significantly changed with THC exposure (Figures S2 and S3). We investigated whether THC altered the gene expression profiles of these innate immune cells within the lungs of naïve and Nb-infected mice that had been exposed to vehicle or THC (Fig. 3a). Lung single-cell suspensions were processed for column purification to isolate CD11c+ alveolar macrophages (86% purity). In the infected mouse groups, which had sufficient eosinophil numbers, the flow-through was next used for Siglec-F column purification to isolate eosinophils (87% purity). Following bulk RNA sequencing and standard quality control filtering, PCA revealed distinct clustering according to cell type and infection status (Figure S4a, n = 4 per group). Additional validation analysis was conducted to determine macrophage purity of the CD11c+ fraction by DCQ, which predicted that macrophages were the dominant cell subset in all groups investigated with minimal dendritic cell contamination (Figure S4b). We also evaluated cannabinoid receptor expression in the enriched macrophages and eosinophils and observed higher CB2R mRNA in all groups compared to CB1R, but no changes in CB1R or CB2R expression with THC exposure or infection (Figure S5a). We assessed the overall transcriptional impact of infection and THC exposure by comparing the number of differentially expressed genes across RNA sequencing datasets. In CD11c+ lung macrophage-enriched cells, Nb infection induced the greatest transcriptional changes in both vehicle- and THC-treated mice; vehicle-treated macrophage-enriched cells had 2,956 genes upregulated and 2,980 genes downregulated with infection, compared to THC-treated macrophage-enriched cells (3,045 genes up versus 3,502 genes down with infection) (Fig. 3b). While THC did not substantially affect macrophage gene expression from naïve mice (254 genes up versus 184 genes down with THC), there were more genes that were changed in the infected mouse groups (Fig. 3c). Eosinophils had more downregulated (1,546) than upregulated genes (688), followed by macrophages with 1,136 genes downregulated versus 925 genes upregulated with THC exposure in the infected groups. Together, these data indicate that THC has a broad transcriptional impact on macrophages and eosinophils during infection with a greater effect in suppressing gene expression.

Figure 3.

Three-panel figure illustrating cell sorting strategy and RNA-sequencing gene expression counts. Panel A is a flow diagram detailing magnetic cell separation for CD11c+ macrophage-enriched cells and CD11c– Siglec-F+ eosinophils. Panels B and C are bar charts displaying differentially expressed gene counts across treatment and infection conditions for CD11c+ macrophage-enriched cells and eosinophils.

THC exposure and helminth infection induce broad transcriptional changes in lung macrophage-enriched CD11c+ cells and eosinophils. Vehicle- and THC-treated mice were left naïve or infected with Nb. a) Magnetic sorting strategy for CD11c+ macrophage-enriched cells and CD11c−Siglec-F+ eosinophils. b) Differentially expressed gene counts comparing naïve and infected CD11c+ macrophage-enriched cells. c) Differentially expressed gene counts after THC exposure in infected eosinophils, naïve macrophage-enriched cells, and infected macrophage-enriched cells. Differential expression was defined by DESeq2 adjusted P < 0.05 and absolute log2 fold change > 1. Data are from one experiment with 7 mice per group pooled into 4 RNA-sequencing libraries per group.

Given prior evidence that THC can alter macrophage inflammatory potential,12–14 we examined the genes and functional pathways that were changed in macrophages from naïve mice upon THC exposure (Fig. 4, Table 1). Transcripts reduced in THC-treated naïve cells included chemokine and inflammatory signaling-associated genes such as Cxcl1, Cxcl2, Il2rg, Cish, and Scimp, as well as heat shock-associated genes including Hsph1 and Hspa8.27–32 In contrast, genes increased with THC included Cirbp, Cd300lf, Adap2, Rgcc, Pex11a, Cerk, and Pla2g6, consistent with altered stress adaptation, inhibitory signaling, and lipid handling.33–35 Gene set enrichment analysis supported this basal shift in CD11c+ lung macrophage-enriched cells (Fig. 4b). THC-treated naïve cells showed enrichment of pathways associated with TGFβ signaling, heme metabolism, and fatty acid metabolism. In contrast, vehicle-treated cells were enriched for inflammatory response, TNFα signaling via NFκB, IL-6/JAK/STAT3 signaling, interferon responses, complement, and allograft rejection pathways.

Figure 4.

Four-panel figure displaying RNA-sequencing data for CD11c+ lung macrophage-enriched cells. Panels A and C show gene expression heatmaps of the top 50 differentially expressed genes in naïve and infected conditions, respectively, comparing vehicle and THC treatments. Panels B and D display Hallmark Gene Set Enrichment Analysis (GSEA) bar plots highlighting enriched pathways for the corresponding comparisons.

THC dampens basal and Nb-induced inflammatory and tissue-remodeling programs in CD11c+ lung macrophage-enriched cells. CD11c+ macrophage-enriched cells from naïve or Nb-infected mice treated with vehicle or THC were analyzed by bulk RNA sequencing. a, c) Heatmaps of the top 50 differentially expressed genes in naïve (a) and Nb-infected (c) comparisons. b, d) Hallmark GSEA for naïve (b) and Nb-infected (d) comparisons. Heatmap genes met adjusted P < 0.05 and absolute log2 fold change > 1; GSEA pathways met adjusted P < 0.05. Data are from one experiment with 7 mice per group pooled into 4 RNA-sequencing libraries per group.

Table 1.

Naïve lung CD11c+ enriched macrophage differentially expressed genes.

Category Down in THC Up in THC Interpretation
Stress response Hsph1, Hspa8, Chordc1 Cirbp THC reduces classical heat-shock stress, enhances stress buffering
Chemokines Cxcl1, Cxcl2 — Vehicle macs show higher basal chemokine production
Cytokine signaling and activation Il2rg, Cish, Tfec, Scimp Cd300lf, Adap2 (inhibitory) THC upregulates inhibitory receptors, lowering activation potential
Cell cycle/proliferation Mcm4, Tmpo, Psip1 Rgcc, Pex11a, Gpd1, Slc16a6 THC shifts toward metabolic/FAO genes rather than proliferation
Lipid turnover — Cerk, Pla2g6 THC enhances lipid-handling without inflammatory activation

We next examined whether THC altered CD11c+ lung macrophage-enriched cell responses during Nb infection. Differential gene expression analysis showed that THC altered the transcriptional response of infected CD11c+ lung macrophage-enriched cells (Fig. 4c, Table 2). THC reduced expression of genes associated with pathogen sensing, chemotaxis, motility, and remodeling. Reduced transcripts included Tlr4, Fpr1, and P2ry13, as well as heat shock-associated genes such as Hsph1, Hsp90aa1, and Hspa8.27,36–39 THC also reduced genes linked to cytoskeletal remodeling and fibrotic programs, including Myo1f, Bin2, Spice1, and P4ha1.40–43 Conversely, THC increased expression of genes associated with stress adaptation, regulatory signaling, and metabolic remodeling, including Cirbp, Rbm3, Foxred2, Eci2, Pik3ip1, Lpxn, Susd3, Retnlg, and Pdcd4.33,44–47

Table 2.

Infected lung CD11c+-enriched macrophage differentially expressed genes.

Category Down in THC Up in THC Interpretation
Pathogen sensing/chemotaxis Tlr4, Fpr1, P2ry13 — THC reduces PRR/chemotaxis signaling
Stress response Hsph1, Hsp90aa1, Hspa8 (heat-shock proteins) Cirbp, Rbm3, Foxred2 (cold-shock/stress-buffering) THC shifts from inflammatory stress responses to protective stress buffering
Metabolism Pla2g15 (lipid metabolism for inflammation) Eci2 (FAO) THC redirects metabolism away from inflammatory lipid use toward FAO
Cytoskeletal/adhesion Myo1f, Bin2, Spice1 — Reduced motility/adhesion signatures
Fibrosis/ECM remodeling P4ha1 — Lower fibrosis/ECM remodeling potential
Immune regulation — Pik3ip1, Lpxn, Susd3, Retnlg, Pdcd4 THC increases inhibitory/checkpoint signals

Pathway analysis confirmed that THC altered macrophage-enriched transcriptional responses during infection. In vehicle-treated macrophages from infected mice, pathways associated with inflammatory response, TNFα signaling via NFκB, mTORC1 signaling, protein secretion, unfolded protein response, cholesterol homeostasis, and mitotic spindle were enriched. On the other hand, THC exposure promoted the enrichment of genes associated with oxidative phosphorylation, E2F targets, DNA repair, Myc targets, interferon responses, adipogenesis, and xenobiotic metabolism pathways (Fig. 4d). Together, these macrophage-enriched datasets from the lungs of naïve and Nb-infected mice indicate that THC reduces inflammatory, chemokine-associated, and remodeling programs, especially with infection, and instead promotes genes associated with metabolic adaptation, stress regulation, and immune restraint.

Although THC reduced circulating eosinophilia, lung eosinophil accumulation following Nb infection was not significantly reduced with THC exposure (Figure S2). We therefore investigated whether THC altered the transcriptional state of eosinophils that reached the lung during infection. Differential gene expression analysis revealed that THC altered the transcriptional profile of infected lung eosinophils (Fig. 5a, Table 3). Among the top 50 differentially expressed genes, THC-treated eosinophils showed increased expression of transcripts associated with stress adaptation and cellular buffering, including Ucp2, Cirbp, Rbm3, and Gadd45a.33,44,48–50 THC-treated eosinophils also showed increased expression of genes associated with lipid mediator regulation and inhibitory receptor signaling, including Pla2g7, Cyp4f18, Cd300lf, and Siglecf.34,51–54 In contrast, transcripts associated with adhesion, migration, and inflammatory stress, including Macf1, Syne2, Afap1l2, Neat1, and Hsph1, were reduced in THC-treated eosinophils.27,55,56

Figure 5.

Two-panel figure illustrating transcriptomic changes in lung eosinophils from infected mice. Panel A shows a heatmap of the top 50 differentially expressed genes comparing vehicle and THC treatments. Panel B displays a Hallmark GSEA plot highlighting enriched signaling pathways, including NFkB, STAT, mTOR, and oxidative phosphorylation.

THC shifts infected lung eosinophils from inflammatory NFκB/STAT signaling to mTOR signaling and oxidative phosphorylation. CD11c−Siglec-F+ lung eosinophils from vehicle- and THC-treated Nb-infected mice were analyzed by bulk RNA sequencing. a) Heatmap of the top 50 differentially expressed genes. b) Hallmark GSEA. Heatmap genes met adjusted P < 0.05 and absolute log2 fold change > 1; GSEA pathways met adjusted P < 0.05. Data are from one experiment with 7 mice per group pooled into 4 RNA-sequencing libraries per group.

Table 3.

CD11c-Siglec-F+ enriched lung eosinophil differentially expressed genes.

Category Down in THC Up in THC Interpretation
Stress response/antioxidant — Ucp2, Cirbp, Rbm3, Gadd45a Enhanced buffering of oxidative and cellular stress
Lipid mediator metabolism — Pla2g7, Cyp4f18 Reduced PAF/LTB4 signaling capacity (neutrophil recruitment)
Inhibitory receptors — Cd300lf, Siglecf Higher activation threshold
Cytoskeleton/adhesion Macf1, Syne2, Afap1l2 — Lower migratory and adhesion potential
Stress/inflammatory regulators Neat1, Hsph1 — Reduced stress-induced inflammatory signaling

Gene set enrichment analysis further supported a THC-induced shift in the eosinophil metabolic state. Pathways associated with oxidative phosphorylation, adipogenesis, reactive oxygen species, PI3K–AKT–mTOR signaling, and heme metabolism were enriched in THC-treated eosinophils (Fig. 5b). In contrast, inflammatory response, TNFα signaling through NFκB, IL-2 STAT5 signaling, TGFβ signaling, and cholesterol homeostasis pathways were enriched in vehicle-treated eosinophils. We investigated if THC treatment affected expression of type 2 cytokine/chemokine and their receptors associated with eosinophil recruitment, including eotaxin/CCR3 and IL-5/IL-13 receptor signaling (Figure S5). THC treatment significantly increased CCR3 expression in both macrophages and eosinophils of helminth-infected mice, but there were no significant differences in eotaxin expression. Together, these data suggest that THC does not limit eosinophil accumulation in the lung during Nb infection but instead alters the transcriptional state of lung eosinophils that enter the tissue. Here, THC may restrain eosinophil inflammatory potential at 2 levels: by reducing the circulating eosinophil response and by shifting infected lung eosinophils toward a less inflammatory, more antioxidant-associated transcriptional state after tissue entry.

3.3. THC alters antigen presentation and costimulatory gene expression while limiting inflammatory T cell activation

Given that THC altered circulating leukocyte responses and triggered anti-inflammatory transcriptional programs in CD11c+ lung macrophages, we hypothesized that inflammatory T cell responses may be changed. Flow cytometric analysis of BALF showed that THC-treated infected mice had increased CD4+ T cell frequencies compared with vehicle-treated infected mice (Fig. 6a and b). To determine whether this increase corresponded with enhanced inflammatory T cell function, splenocytes from vehicle- and THC-treated mice were stimulated ex vivo with anti-CD3/CD28 and IL-2 for 72 h, and cytokine secretion was measured in culture supernatants (Fig. 6c). Splenocytes from THC-treated infected mice generated significantly less IFNγ and TNFα following stimulation compared with splenocytes from vehicle-treated infected controls (Fig. 6d and e), although there were no differences in IL-4 and IL-5 production (Figure S5). These data indicate that THC increased CD4+ T cell accumulation in the BALF; however, its systemic impact was immunosuppressive, characterized by increased blood Tregs and reduced inflammatory cytokine production by splenic T cells.

Figure 6.

Six-panel figure detailing T cell activation, cytokine production, and antigen presentation markers. Panel A displays representative BALF flow cytometry plots, and Panel B is a scatter plot showing CD4+ T cell frequencies. Panel C shows a diagram of the ex vivo splenocyte stimulation protocol. Panels D and E are scatter plots of IFNγ and TNFα protein concentrations. Panel F shows a targeted heatmap of MHC class II, antigen-presentation, and costimulatory gene expression.

THC limits inflammatory T cell activation while preserving antigen presentation programs. a, b) Representative BALF flow plots (a) and CD4+ T cell frequencies among CD45+ cells (b). c) Ex vivo splenocyte stimulation schematic. Created with Biorender. d, e) IFNγ and TNFα concentrations after stimulation. f) Targeted heatmap of MHC class II, antigen-presentation, and costimulation genes in infected CD11c+ macrophage-enriched cells. Flow cytometry and cytokine data are mean ± SEM pooled from 2 independent experiments (n = 4 to 7 mice per group). RNA-Seq data are from one experiment with 7 mice per group pooled into 4 libraries. Two-way ANOVA with Tukey's test; genes in (f) met adjusted P < 0.05 and absolute log2 fold change > 0.25. *P < 0.05; ***P < 0.001; ****P < 0.0001.

Given that antigen-presenting cells regulate T cell activation through MHC-dependent antigen presentation and CD80/CD86-mediated costimulatory signaling,57 we next examined antigen presentation and costimulation-associated genes in CD11c+ lung macrophages. Under naïve conditions, there were no significant differences in antigen presentation or costimulation-associated genes between vehicle- and THC-treated mice. During infection, however, THC-treated CD11c+ lung macrophages maintained or increased expression of multiple MHC class II and antigen presentation-associated genes, including H2-Aa, H2-Ab1, H2-Eb1, Cd74, H2-DMb1, H2-DMb2, H2-Oa, B2m, and Tap158 (Fig. 6f). We validated increased surface expression of MHC class II in THC-treated helminth-infected mice by flow cytometry of the lung CD11c+ cells (Figure S2b). In contrast, Cd80 expression was reduced in THC-treated infected cells, while Cd86 was not significantly changed. Together, these data indicate that THC-treated mice have increased airway CD4+ T cell frequencies but reduced inflammatory cytokine output following stimulation. This pattern suggests that THC does not block antigen presentation or fully eliminate costimulatory potential but may partially dampen costimulatory signaling in a manner that limits inflammatory T cell activation.12

3.4. THC treatment is associated with retained lung Collagen VI following Nb infection

Based on the transcriptomic profiling results showing that THC altered inflammatory and remodeling-associated transcriptional programs in lung macrophage-enriched cells, we next assessed whether THC was associated with tissue-level changes in the lung. We chose to investigate collagen deposition in the lung as a measure of tissue remodeling following the severe infection-induced injury caused by Nb burrowing through the lung during the acute infection stages. Immunofluorescent staining for Collagen VI was performed on lung sections from vehicle- and THC-treated naïve and infected mice (Fig. 7a). Vehicle-treated infected mice showed reduced Collagen VI staining compared with vehicle naïve controls, consistent with infection-associated disruption or remodeling of the lung extracellular matrix.9,16,26 In contrast, Collagen VI signal was not significantly reduced in THC-treated infected mice compared with THC-treated naïve controls (Fig. 7b). Together, these data suggest that Nb infection is associated with loss of lung Collagen VI in vehicle-treated mice, whereas THC-treated mice retain Collagen VI following infection. This pattern suggests that THC-associated immune reprogramming is accompanied by altered extracellular matrix remodeling during Nb-induced lung inflammation.59

Figure 7.

Two-panel figure evaluating lung extracellular matrix remodeling. Panel A shows representative immunofluorescence microscopy images of lung tissue stained for DAPI, GSL I, and Collagen VI across treatment groups, accompanied by a 20 µm scale bar. Panel B is a scatter plot quantifying Collagen VI integrated signal density across naive and infected vehicle- and THC-treated groups.

THC treatment is associated with retained lung Collagen VI following Nb infection. Lung extracellular matrix remodeling was assessed in vehicle- and THC-treated naïve and Nb-infected mice. a) Representative DAPI, GSL I, and Collagen VI immunofluorescence images. Scale bar = 20 µm. b) Quantification of Collagen VI integrated density. Data are from individual animals with mean ± SEM. Two-way ANOVA with Tukey's multiple-comparisons test. *P < 0.05; ns, not significant.

4. Discussion

The goal of this study was to determine how THC exposure alters immune responses during type 2 inflammation. To achieve a controlled experimental environment, we employed the N. brasiliensis infection model and investigated whether THC impacted parasite burden, systemic immune activation, T cell inflammatory function, and lung eosinophil and macrophage gene expression. We found that THC did not alter infection-associated weight loss or parasite burden. Instead, THC restrained infection-induced eosinophilia, increased regulatory T cells, and reduced T cell-derived inflammatory cytokines. Bulk RNA sequencing of lung innate immune cells further showed that THC reduced basal and infection-associated inflammatory programming in CD11c+ macrophage-enriched cells and shifted infected lung eosinophils away from migratory and inflammatory activation to an altered metabolic state involving mTOR signaling and oxidative phosphorylation.

An important finding from this study is that THC exposure did not alter N. brasiliensis burden. This is notable because human studies have suggested a relationship between cannabis use and helminthiasis. Among Aka foragers of the Congo Basin, urinary THCA levels were negatively associated with parasite infection and reinfection, supporting the possibility that cannabis exposure may influence helminth burden.6 However, that study evaluated whole cannabis use in a human population, where additional cannabinoids, route of exposure, tobacco co-use, nutrition, behavior, and environmental variables may contribute to parasite outcomes. In our controlled preclinical model, THC exposure alone did not alter egg or worm burden. These findings suggest that purified THC exposure is not sufficient to reproduce the cannabis-associated reduction in parasite burden observed in human populations. Instead, the major effects of THC in this study were immunologic rather than antiparasitic.

Although parasite burden was unchanged, THC exposure altered the host immune response. The reduction in infection-induced circulating eosinophilia is consistent with prior work implicating cannabinoid signaling in eosinophilic inflammation during helminth infection. Inhibition of peripheral cannabinoid receptor subtype 1 during N. brasiliensis infection increased airway eosinophilia and worsened pulmonary pathology, suggesting that cannabinoid signaling can restrain eosinophilic lung inflammation.5,10 Our results indicating reduced circulating eosinophils and decreased inflammatory pathways in lung eosinophils in THC-treated mice are consistent with the broader concept that cannabinoid pathways dampen eosinophil-associated inflammation. RNA sequencing of infected lung eosinophils showed that THC altered eosinophil transcriptional states without reducing lung eosinophil accumulation. THC-treated eosinophils showed increased expression of genes associated with stress adaptation, lipid mediator regulation, and inhibitory receptor signaling, including Ucp2, Cirbp, Rbm3, Pla2g7, Cyp4f18, Cd300lf, and Siglecf. Increased Rbm3 is consistent with prior work linking it to restrained type 2 lung inflammation, while Cirbp and Gadd45a are defined as stress-response genes with context-dependent roles in inflammation.33,44,50 Increased Cyp4f18, Pla2g7, Cd300lf, and Siglecf is consistent with altered lipid mediator and inhibitory receptor-associated programs in eosinophils, given prior evidence linking CYP4F18 to leukotriene B4 metabolism and CD300/Siglec-family receptors to eosinophil survival, chemotaxis, and effector function.34,51–54 In contrast, genes associated with adhesion, migration, and inflammatory stress, including Macf1, Syne2, Afap1l2, Neat1, and Hsph1, were reduced. These transcriptional changes suggest that THC does not primarily attenuate eosinophilic inflammation by blocking eosinophil entry into the lung. Instead, THC may alter the activation state of eosinophils that enter inflamed tissue. This distinction is important because eosinophils can contribute to both protective type 2 immunity and tissue pathology depending on their inflammatory context, activation state, and tissue localization.60

THC also altered CD11c+ lung macrophage-enriched cells before and during infection. Under naïve conditions, THC reduced chemokine and cytokine signaling and heat shock-associated transcripts in CD11c+ macrophage-enriched cells, while increasing genes associated with stress buffering, lipid handling, and inhibitory signaling. During infection, THC reduced inflammatory, stress-associated, chemotactic, and remodeling-associated genes, including Tlr4, Fpr1, P2ry13, Hsph1, Hsp90aa1, and P4ha1. Reduced Tlr4, Fpr1, and P2ry13 are consistent with dampened pathogen-sensing, formyl peptide receptor, and purinergic inflammatory programs, pathways previously linked to helminth-associated Th2 responses, lung leukocyte recruitment, and macrophage inflammatory regulation.27,36,37,39,43 Reduced P4ha1 is also consistent with decreased collagen-processing or ECM-remodeling-associated transcriptional programs.43 These data indicate that THC changes the baseline state of lung macrophage-enriched cells and alters their response during inflammatory challenge. This is consistent with prior studies showing that THC can regulate myeloid cell biology, including inhibition of macrophage costimulatory activity, alveolar macrophage inflammatory responses, and ROS-associated macrophage differentiation.12–14 The transcriptional changes observed in macrophage-enriched cells may have implications for tissue remodeling. THC reduced expression of genes associated with motility, inflammatory stress, and fibrotic remodeling, while increasing metabolic and stress-adaptive pathways. Consistent with this transcriptional pattern, vehicle-treated infected mice showed reduced lung Collagen VI staining, whereas THC-treated infected mice retained Collagen VI signal following infection. Collagen VI is a structural extracellular matrix protein, and changes in its deposition may reflect altered tissue remodeling during inflammation. These data suggest that THC-associated immune reprogramming is accompanied by altered lung matrix remodeling.9,59

In CD11c+ macrophage-enriched cells from infected mice, THC-treated samples maintained or increased expression of multiple MHC class II-associated genes, while Cd80 was reduced. Because CD80-mediated costimulation contributes to optimal T cell activation and cytokine production, reduced Cd80 expression may help explain why CD4+ T cells accumulated in the airway but showed reduced inflammatory output after stimulation.57 The combination of maintained antigen presentation genes, reduced Cd80, and reduced TNFα and IFNγ production is consistent with incomplete inflammatory T cell activation or an anergy-like functional state.12,57,58 These findings are consistent with prior work showing that THC suppresses proliferation, reduces IFNγ production, and alters Th1/Th2 cytokine balance in activated human T cells.11

There remain limitations to this study. First, although THC is a partial cannabinoid receptor agonist, we did not directly test whether the observed effects were mediated through CB1R, CB2R, or cannabinoid receptor-independent pathways.2,12,14 Future studies using receptor antagonists, conditional deletion mouse models, or cell-specific approaches will be needed to determine receptor dependence. The route of THC administration is also an important consideration. We used intraperitoneal injection to provide consistent, body-weight-adjusted dosing and to isolate the systemic immunologic effects of THC from potential airway irritation or local pulmonary changes caused by inhaled exposure. However, intraperitoneal administration does not reproduce the pharmacokinetics or local airway exposure associated with human cannabis inhalation, and future studies using vaporized THC will be needed to determine whether the observed immune effects are maintained with a more clinically relevant exposure route. Second, the CD11c+ lung population used for RNA sequencing was macrophage-enriched but may also contain dendritic cells or other CD11c-expressing populations. Third, although reduced Cd80 expression and lower TNFα and IFNγ release are consistent with reduced costimulatory activation,11,12,57 direct lung T cell assays will be required to determine whether THC induces T cell anergy, altered proliferation, or changes in antigen-specific effector function. Lastly, many physiological effects of cannabis are mediated by THC; however, pure THC is rarely consumed on its own, as people typically consume whole cannabis or concentrated cannabis extracts. Future studies should evaluate possible differential effects for THC versus whole cannabis, which contains over 100 phytocannabinoid chemicals.61

In conclusion, chronic THC exposure reprograms eosinophils and macrophages toward restrained, oxidative, and stress-adaptive phenotypes during type 2 inflammation, associated with reduced inflammatory T cell responses. The immune skewing potential of THC on lung innate immune cells may offer therapeutic potential in inflammatory settings where excessive leukocyte activation contributes to tissue pathology.9,16,26

Supplementary Material

qiag131_Supplementary_Data

Acknowledgments

We would like to thank the following University of California equipment cores: UC Riverside School of Medicine Research Core for the flow cytometry equipment, figure editing and biostatistics analysis (somresearch.ucr.edu), UC Riverside High Performance Computing Center for bioinformatics data processing (hpcc.ucr.edu), and UC Los Angeles Translational Pathology Core Laboratory for tissue processing. We also thank Diana Del Castillo and Keziyah Yisrael, PhD, from the laboratory of David Lo, MD, PhD, for their assistance and guidance with mouse lung processing.

Contributor Information

Jennell Jennett, Division of Biomedical Sciences, School of Medicine, University of California Riverside, 900 University Avenue, Riverside, CA 92521, United States.

Martin Olmos, Division of Biomedical Sciences, School of Medicine, University of California Riverside, 900 University Avenue, Riverside, CA 92521, United States.

Ka Man Lam, Division of Biomedical Sciences, School of Medicine, University of California Riverside, 900 University Avenue, Riverside, CA 92521, United States.

Sarah Midou, Division of Biomedical Sciences, School of Medicine, University of California Riverside, 900 University Avenue, Riverside, CA 92521, United States.

Nicholas V DiPatrizio, Division of Biomedical Sciences, School of Medicine, University of California Riverside, 900 University Avenue, Riverside, CA 92521, United States.

Meera G Nair, Division of Biomedical Sciences, School of Medicine, University of California Riverside, 900 University Avenue, Riverside, CA 92521, United States.

Author contributions

M.G.N., J.J., M.O., and N.D.P. conceptualized the study and designed the experiments. J.J., M.O., K.M.L., and S.M. performed the experiments. J.J. and K.M.L. analyzed the data. J.J., N.D.P., and M.G.N. interpreted the results. J.J. and M.G.N. wrote the manuscript. M.G.N. acquired project funding. All co-authors approved the manuscript.

Supplementary material

Supplementary material is available at Journal of Leukocyte Biology online.

Funding

This work was supported by the National Institutes of Health (R01AI153195 to M.G.N. and J.J.; R21AI180561, R01AI191470 to M.G.N.) and the California Institute of Regenerative Medicine (CIRM) RAMP Award EDUC5-13636 to K.M.L. The contents of this publication are solely the responsibility of the authors and do not necessarily represent official views of CIRM or other agencies of the State of California.

Data availability

The RNA-sequencing data generated in this study have been deposited in the NCBI Gene Expression Omnibus (GEO) under accession number GSE334156 and can be accessed at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE334156 using the reviewer access token krypoeuqtpczhgt.

References

  • 1. Substance Abuse and Mental Health Services Administration . Key substance use and mental health indicators in the United States: Results from the 2022 National Survey on Drug Use and Health. HHS Publication No. PEP23-07-01-006, NSDUH Series H-58. Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration: 2023. [accessed 2026 May 13]. https://www.samhsa.gov/data/sites/default/files/reports/rpt42731/2022-nsduh-nnr.pdf
  • 2. Howlett  AC  et al.  International Union of Pharmacology. XXVII. Classification of cannabinoid receptors. Pharmacol Rev. 2002:54:161–202. 10.1124/pr.54.2.161 [DOI] [PubMed] [Google Scholar]
  • 3. Roth  MD, Baldwin  GC, Tashkin  DP. Effects of delta-9-tetrahydrocannabinol on human immune function and host defense. Chem Phys Lipids. 2002:121:229–239. 10.1016/s0009-3084(02)00159-7 [DOI] [PubMed] [Google Scholar]
  • 4. Maggirwar  SB, Khalsa  JH. The link between cannabis use, immune system, and viral infections. Viruses. 2021:13:1099. 10.3390/v13061099 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5. Batugedara  HM  et al.  Host- and helminth-derived endocannabinoids that have effects on host immunity are generated during infection. Infect Immun. 2018:86:e00441-18. 10.1128/IAI.00441-18 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6. Roulette  CJ, Kazanji  M, Breurec  S, Hagen  EH. High prevalence of cannabis use among Aka foragers of the Congo Basin and its possible relationship to helminthiasis. Am J Hum Biol. 2016:28:5–15. 10.1002/ajhb.22740 [DOI] [PubMed] [Google Scholar]
  • 7. Reece  JJ, Siracusa  MC, Scott  AL. Innate immune responses to lung-stage helminth infection induce alternatively activated alveolar macrophages. Infect Immun. 2006:74:4970–4981. 10.1128/IAI.00687-06 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Voehringer  D, Shinkai  K, Locksley  RM. Type 2 immunity reflects orchestrated recruitment of cells committed to IL-4 production. Immunity. 2004:20:267–277. 10.1016/s1074-7613(04)00026-3 [DOI] [PubMed] [Google Scholar]
  • 9. Sutherland  TE  et al.  Ym1 induces RELMα and rescues IL-4Rα deficiency in lung repair during nematode infection. PLoS Pathog. 2018:14:e1007423. 10.1371/journal.ppat.1007423 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10. Wiley  MB, Bobardt  SD, Nordgren  TM, Nair  MG, DiPatrizio  NV. Cannabinoid receptor subtype-1 regulates allergic airway eosinophilia during lung helminth infection. Cannabis Cannabinoid Res. 2021:6:242–252. 10.1089/can.2020.0167 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11. Yuan  M  et al.  Delta 9-tetrahydrocannabinol regulates Th1/Th2 cytokine balance in activated human T cells. J Neuroimmunol. 2002:133:124–131. 10.1016/s0165-5728(02)00370-3 [DOI] [PubMed] [Google Scholar]
  • 12. Chuchawankul  S, Shima  M, Buckley  NE, Hartmann  CB, McCoy  KL. Role of cannabinoid receptors in inhibiting macrophage costimulatory activity. Int Immunopharmacol. 2004:4:265–278. 10.1016/j.intimp.2003.12.011 [DOI] [PubMed] [Google Scholar]
  • 13. Preteroti  M, Wilson  ET, Eidelman  DH, Baglole  CJ. Modulation of pulmonary immune function by inhaled cannabis products and consequences for lung disease. Respir Res. 2023:24:95. 10.1186/s12931-023-02399-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Preteroti  MW  et al.  Receptor-mediated effects of Δ(9) -tetrahydrocannabinol and cannabidiol on the inflammatory response of alveolar macrophages. Immunol Cell Biol. 2023:101:156–170. 10.1111/imcb.12614 [DOI] [PubMed] [Google Scholar]
  • 15. Carter  TH  et al.  Delta-9-tetrahydrocannabinol blocks bone marrow-derived macrophage differentiation through elimination of reactive oxygen species. Antioxidants (Basel). 2024:13:887. 10.3390/antiox13080887 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16. Sveiven  SN  et al.  Myeloid- and epithelial-derived RELMα contribute to tissue repair following lung helminth infection. Front Parasitol. 2023:2:1242866. 10.3389/fpara.2023.1242866 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17. Torrens  A  et al.  Comparative pharmacokinetics of Δ(9)-tetrahydrocannabinol in adolescent and adult male mice. J Pharmacol Exp Ther. 2020:374:151–160. 10.1124/jpet.120.265892 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18. Babraham Bioinformatics . FastQC: A quality control tool for high throughput sequence data. Babraham Institute. [accessed 2026 May 13]. https://www.bioinformatics.babraham.ac.uk/projects/fastqc/
  • 19. Ewels  P, Magnusson  M, Lundin  S, Käller  M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics. 2016:32:3047–3048. 10.1093/bioinformatics/btw354 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20. Bolger  AM, Lohse  M, Usadel  B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014:30:2114–2120. 10.1093/bioinformatics/btu170 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21. Dobin  A  et al.  STAR: ultrafast universal RNA-Seq aligner. Bioinformatics. 2013:29:15–21. 10.1093/bioinformatics/bts635 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22. Liao  Y, Smyth  GK, Shi  W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. 2014:30:923–930. 10.1093/bioinformatics/btt656 [DOI] [PubMed] [Google Scholar]
  • 23. Love  MI, Huber  W, Anders  S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014:15:550. 10.1186/s13059-014-0550-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24. Liberzon  A  et al.  The Molecular Signatures Database (MSigDB) hallmark gene set collection. Cell Syst. 2015:1:417–425. 10.1016/j.cels.2015.12.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25. Subramanian  A  et al.  Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005:102:15545–15550. 10.1073/pnas.0506580102 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26. Nair  MG  et al.  Alternatively activated macrophage-derived RELM-α is a negative regulator of type 2 inflammation in the lung. J Exp Med. 2009:206:937–952. 10.1084/jem.20082048 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. Choudhury  A  et al.  Inhibition of HSP90 and activation of HSF1 diminish macrophage NLRP3 inflammasome activity in alcohol-associated liver injury. Alcohol Clin Exp Res. 2020:44:1300–1311. 10.1111/acer.14338 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28. Sawant  KV  et al.  Chemokine CXCL1 mediated neutrophil recruitment: role of glycosaminoglycan interactions. Sci Rep. 2016:6:33123. 10.1038/srep33123 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29. Lin  JX, Leonard  WJ. The common cytokine receptor γ chain family of cytokines. Cold Spring Harb Perspect Biol. 2018:10:a028449. 10.1101/cshperspect.a028449 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30. Shoger  KE  et al.  CISH attenuates homeostatic cytokine signaling to promote lung-specific macrophage programming and function. Sci Signal. 2021:14:eabe5137. 10.1126/scisignal.abe5137 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31. Luo  L  et al.  SCIMP is a transmembrane non-TIR TLR adaptor that promotes proinflammatory cytokine production from macrophages. Nat Commun. 2017:8:14133. 10.1038/ncomms14133 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32. Luo  L  et al.  SCIMP is a universal Toll-like receptor adaptor in macrophages. J Leukoc Biol. 2020:107:251–262. 10.1002/JLB.2MA0819-138RR [DOI] [PubMed] [Google Scholar]
  • 33. Zhu  X, Bührer  C, Wellmann  S. Cold-inducible proteins CIRP and RBM3, a unique couple with activities far beyond the cold. Cell Mol Life Sci. 2016:73:3839–3859. 10.1007/s00018-016-2253-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34. Rozenberg  P, Reichman  H, Moshkovits  I, Munitz  A. CD300 family receptors regulate eosinophil survival, chemotaxis, and effector functions. J Leukoc Biol. 2018:104:21–29. 10.1002/JLB.2MR1117-433R [DOI] [PubMed] [Google Scholar]
  • 35. Candels  LS, Becker  S, Trautwein  C. PLA2G7: a new player in shaping energy metabolism and lifespan. Signal Transduct Target Ther. 2022:7:195. 10.1038/s41392-022-01052-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36. Pellefigues  C  et al.  Toll-like receptor 4, but not neutrophil extracellular traps, promote IFN type I expression to enhance Th2 responses to Nippostrongylus brasiliensis. Front Immunol. 2017:8:1575. 10.3389/fimmu.2017.01575 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37. Leslie  J  et al.  FPR-1 is an important regulator of neutrophil recruitment and a tissue-specific driver of pulmonary fibrosis. JCI Insight. 2020:5:e125937. 10.1172/jci.insight.125937 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38. Gemperle  C  et al.  Regulation of the formyl peptide receptor 1 (FPR1) gene in primary human macrophages. PLoS One. 2012:7:e50195. 10.1371/journal.pone.0050195 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39. Klaver  D, Thurnher  M. Control of macrophage inflammation by P2Y purinergic receptors. Cells. 2021:10:1098. 10.3390/cells10051098 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40. Kim  SV  et al.  Modulation of cell adhesion and motility in the immune system by Myo1f. Science. 2006:314:136–139. 10.1126/science.1131920 [DOI] [PubMed] [Google Scholar]
  • 41. Piedra-Quintero  ZL  et al.  Myosin 1F regulates M1-polarization by stimulating intercellular adhesion in macrophages. Front Immunol. 2018:9:3118. 10.3389/fimmu.2018.03118 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42. Sánchez-Barrena  MJ  et al.  Bin2 is a membrane sculpting N-BAR protein that influences leucocyte podosomes, motility and phagocytosis. PLoS One. 2012:7:e52401. 10.1371/journal.pone.0052401 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43. Yang  X  et al.  P4HA1: an important target for treating fibrosis related diseases and cancer. Front Pharmacol. 2024:15:1493420. 10.3389/fphar.2024.1493420 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44. Badrani  JH  et al.  RNA-binding protein RBM3 intrinsically suppresses lung innate lymphoid cell activation and inflammation partially through CysLT1R. Nat Commun. 2022:13:4435. 10.1038/s41467-022-32176-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45. Uche  UU  et al.  PIK3IP1/TrIP restricts activation of T cells through inhibition of PI3K/Akt. J Exp Med. 2018:215:3165–3179. 10.1084/jem.20172018 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46. Liu  H  et al.  Macrophage migration and phagocytosis are controlled by kindlin-3's link to the cytoskeleton. J Immunol. 2020:204:1954–1967. 10.4049/jimmunol.1901134 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47. Pine  GM, Batugedara  HM, Nair  MG. Here, there and everywhere: resistin-like molecules in infection, inflammation, and metabolic disorders. Cytokine. 2018:110:442–451. 10.1016/j.cyto.2018.05.014 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48. Emre  Y  et al.  Mitochondria contribute to LPS-induced MAPK activation via uncoupling protein UCP2 in macrophages. Biochem J. 2007:402:271–278. 10.1042/BJ20061430 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49. Emre  Y  et al.  Role of uncoupling protein UCP2 in cell-mediated immunity: how macrophage-mediated insulitis is accelerated in a model of autoimmune diabetes. Proc Natl Acad Sci U S A. 2007:104:19085–19090. 10.1073/pnas.0709557104 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50. Salerno  DM, Tront  JS, Hoffman  B, Liebermann  DA. Gadd45a and Gadd45b modulate innate immune functions of granulocytes and macrophages by differential regulation of p38 and JNK signaling. J Cell Physiol. 2012:227:3613–3620. 10.1002/jcp.24067 [DOI] [PubMed] [Google Scholar]
  • 51. Christmas  P  et al.  Cytochrome P-450 4F18 is the leukotriene B4 omega-1/omega-2 hydroxylase in mouse polymorphonuclear leukocytes: identification as the functional orthologue of human polymorphonuclear leukocyte CYP4F3A in the down-regulation of responses to LTB4. J Biol Chem. 2006:281:7189–7196. 10.1074/jbc.M513101200 [DOI] [PubMed] [Google Scholar]
  • 52. Winslow  V  et al.  Altered leukotriene B4 metabolism in CYP4F18-deficient mice does not impact inflammation following renal ischemia. Biochim Biophys Acta. 2014:1841:868–879. 10.1016/j.bbalip.2014.03.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53. Kiwamoto  T, Katoh  T, Tiemeyer  M, Bochner  BS. The role of lung epithelial ligands for Siglec-8 and Siglec-F in eosinophilic inflammation. Curr Opin Allergy Clin Immunol. 2013:13:106–111. 10.1097/ACI.0b013e32835b594a [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54. Zimmermann  N  et al.  Siglec-F antibody administration to mice selectively reduces blood and tissue eosinophils. Allergy. 2008:63:1156–1163. 10.1111/j.1398-9995.2008.01709.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55. Cusseddu  R, Robert  A, Côté  JF. Strength through unity: the power of the mega-scaffold MACF1. Front Cell Dev Biol. 2021:9:641727. 10.3389/fcell.2021.641727 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56. Jönsson  F, Gurniak  CB, Fleischer  B, Kirfel  G, Witke  W. Immunological responses and actin dynamics in macrophages are controlled by N-cofilin but are independent from ADF. PLoS One. 2012:7:e36034. 10.1371/journal.pone.0036034 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57. Lanier  LL  et al.  CD80 (B7) and CD86 (B70) provide similar costimulatory signals for T cell proliferation, cytokine production, and generation of CTL. J Immunol. 1995:154:97–105. 10.4049/jimmunol.154.1.97 [DOI] [PubMed] [Google Scholar]
  • 58. Stables  MJ  et al.  Transcriptomic analyses of murine resolution-phase macrophages. Blood. 2011:118:e192–e208. 10.1182/blood-2011-04-345330 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59. Mereness  JA  et al.  Collagen VI deficiency results in structural abnormalities in the mouse lung. Am J Pathol. 2020:190:426–441. 10.1016/j.ajpath.2019.10.014 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60. Ramirez  GA  et al.  Eosinophils from physiology to disease: a comprehensive review. Biomed Res Int. 2018:2018:9095275. 10.1155/2018/9095275 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61. Mechoulam  R, Hanuš  LO, Pertwee  R, Howlett  AC. Early phytocannabinoid chemistry to endocannabinoids and beyond. Nat Rev Neurosci. 2014:15:757–764. 10.1038/nrn3811 [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

qiag131_Supplementary_Data

Data Availability Statement

The RNA-sequencing data generated in this study have been deposited in the NCBI Gene Expression Omnibus (GEO) under accession number GSE334156 and can be accessed at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE334156 using the reviewer access token krypoeuqtpczhgt.


Articles from Journal of Leukocyte Biology are provided here courtesy of Oxford University Press

RESOURCES