RNA-seq evaluation of equine alveolar macrophages and monocyte-derived macrophages exposed to an inflammatory stimulus

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Lee, Dorothee Bienzle, Jutta Hammermüller, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7122919/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Feb, 2026 Read the published version in BMC Veterinary Research → Version 1 posted 12 You are reading this latest preprint version Abstract Background Severe equine asthma is common and analogous to neutrophilic asthma in humans. Caused by exposure to organic and inorganic environmental particulates, the disease manifests in mature horses as hyperreactive airways and severe neutrophilic lower airway inflammation. Macrophage populations in the lung, including resident alveolar macrophages (AMs) and recruited monocyte-derived macrophages (MDMs), recognize these barn dust particulates, and orchestrate an immune response thought the cytokines they produce. Despite their importance, the specific contributions of these macrophage subsets to equine asthma remain poorly understood. Our work aimed to investigate the contributions of AMs and MDMs to the early inflammatory response using RNA-seq. Therefore, we undertook a 6-hour exposure of AMs and MDMs from six healthy female Standardbred horses to a mixture of f ungal spores, l ipopolysaccharide, and s ilica microspheres (FLS), as these form the major components of barn dust, with tissue culture medium as control. We hypothesized that AMs and MDMs would have differing transcriptional responses to FLS. Results From our RNA-seq analyses, we identified differentially expressed genes and associated biological pathways. “Cytokine signaling” was identified as the major biological process activated by FLS in both cell types. Pathways including JAK-STAT/IL-15, TNF receptor binding, and IFN signaling were more highly upregulated in MDMs than AMs, suggesting that the two cell types have unique signalling pathways and inflammatory responses. Conclusions These results indicate that equine AMs and MDMs have distinct responses to common inflammatory signals, and therefore, provide differing contributions to the early inflammatory response. These insights provide a foundation for future investigations of the role of equine AMs and MDMs to the pathogenesis of severe equine asthma. Cell culture differentially expressed genes gene-set enrichment analysis horse innate immune cells transcriptome Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Severe equine asthma (sEA), is a naturally occurring disease of mature animals that has features of airway hyperresponsiveness, mucus hypersecretion, bronchial remodelling, fibrosis, and lung mucosal epithelial dysfunction, that mirror the human condition (1-3). The prevalence of sEA is estimated at 14% in the northern hemisphere (4); higher than that suggested for adult humans (5, 6). Additionally, as horses are long lived, the disease and response to therapy can be evaluated over many years in the same individual (7). Alveolar macrophages (AMs) phagocytose and coordinate cytokine-mediated immune responses against inhaled antigens in the lung (8, 9). For example, in response to moldy hay challenge, sEA-affected horses had increased gene expression of the proinflammatory tumor necrosis factor (TNF) and interleukin (IL)-1β, and the anti-inflammatory IL-10, and decreased surface expression of CD163 and CD206, suggesting an aberrant anti-inflammatory immunophenotype (9, 10). In pulmonary inflammation, circulating monocytes infiltrate the lung and develop a gene expression pattern similar to resident AMs (11). Both phagocytes express pattern recognition receptors including dectin-1 and toll-like receptor (TLR)-4, which, on engaging fungal β-glucan and bacterial lipopolysaccharide (LPS) respectively, induce a cytokine response cascade (12). Even though resident AMs and newly recruited MDMs share similarities in their phenotypes, important differences, including propensity for phagocytosis and the nature of the inflammatory responses each engenders, have been identified (9, 13). Additionally, AMs and MDMs had differing cytokine and immunophenotype responses when cultured with a mixture of f ungal spores, L PS and s ilica microspheres (FLS), to emulate the barn particulates that exacerbate sEA (9, 13). However, RNA-seq studies separately investigating equine AM and MDM responses in pulmonary disease are rare (14, 15). RNA-seq analysis is an advanced method to measure gene transcripts in a given sample, that permits a snapshot assessment of differences in gene expression and transcription activation between two conditions (16). RNA-seq analysis can include differential gene expression and other comparative transcriptomic analyses that can reveal the underlying response to environmental stimuli and molecular mechanisms that drive disease pathogenesis (2). Although a powerful tool, RNA-seq has uncommonly been used to evaluate equine lung diseases (2, 9, 17, 18). For example, a defective response of the bronchial epithelium to a moldy hay challenge was a feature of horses with sEA, where >100 differentially expressed genes (DEGs) were identified between sEA-affected and healthy horses (2). Differing quiescent and LPS-induced gene expression was observed in equine peritoneal macrophages and AMs using comparative transcriptomic analysis (19). However, similar information is lacking for how AMs and MDMs regulate the early lower airway immune response in horses. In the present study, we exposed AMs and MDMs from horses without lower airway disease to FLS (7) or to cell culture medium (control) in vitro , followed by RNA-seq evaluation of cellular responses. We hypothesized that AMs and MDMs would have distinct gene expression responses to FLS exposure, suggesting differing roles in the early inflammatory response. Our objective was to compare AM and MDM gene expression, including identifying the corresponding pathways from those DEGs. We undertook this work because a more detailed understanding of the responses of these different lung phagocytes could reveal unique roles for AMs and MDMs in the early inflammatory response, and identify likely preventive or therapeutic targets. Furthermore, it is possible that similar to human asthma, aberrant phagocytic responses and increased monocyte recruitment to the lung contribute to the asthma phenotype in sEA-affected horses (20, 21). Therefore, if we identified different roles for AMs and MDMs in lung inflammation, then future studies of their responses in sEA-affected horses would be warranted. Methods The study was a parallel controlled design where AMs and MDMs were collected from each of six clinically healthy female Standardbred horses between the ages of 10 and 21 years. These horses are part of the University of Guelph’s closed research horse herd and are kept at pasture with run-in barn access. To reduce animal distress, horses were shipped in groups of two to the Large Animal Health Sciences Centre of the University of Guelph, sampled, and returned to their herd in the same day with a 24-hour close monitoring period for development of fever or cough. No adverse events occurred. The inclusion criterion was good health status, which was confirmed through physical examination, airway endoscopy, complete blood count, serum biochemical profile, and bronchoalveolar lavage fluid (BALF) cytology evaluation. The exclusion criteria included a previous history of equine asthma, poor physical health, or having diagnostic testing results outside of the reference interval. No horse was excluded. From each horse, 10 6 AMs and 10 6 MDMs were seeded into each well of a 6-well culture plate in technical triplicates, under both treatment and control conditions, for a total of 18 x 10 6 from each of AMs and MDMs. The sample size was determined based on a previous equine RNA-seq evaluation,(22) and best practice recommendations for DEG studies.(23) Each sample was split into FLS-exposure and non-exposure groups. Because FLS is green and the cell culture medium, or control, is pink in color, a blinded approach was not possible, and randomization was not used to allocate plate position of FLS-treatment or control. Confounders, such as the order of plate location, were not controlled. The variables assessed were DEGs between exposure conditions and within and between the two cell types. The project was approved under Animal Use Protocols 3816 and 4675 by the University of Guelph's Animal Care Committee, adhering to Canadian Council on Animal Care standards. Portions of this work represent research presented in the PhD thesis of the primary author, Dr. Kang, and have been presented previously in that form (9). Cell Collection and Exposure Using an endoscope, 500 mL of warmed sterile saline was instilled into a 4 th to 6 th generation bronchus (7) and approximately 350 mL of BALF was retrieved, then within 20 minutes, was centrifuged at 400 g for 10 minutes at 4°C. AM isolation was achieved by capitalizing on the adherent properties of AMs, in that the cell pellet was washed in PBS, resuspended in RPMI 1640 medium with HEPES, and incubated in 75 cm² flasks at 37°C with 5% CO2 for 30 minutes. AMs were detached (TrypLE™ Select Enzyme 10X, Thermo Fisher Scientific (TFS), Mississauga, ON, Canada) and 10 6 cells per well were transferred to 6-well culture plates. Cells were incubated for 6 hours at 37°C with 5% CO 2 in serum-free RPMI containing 10 6 /mL Aspergillus fumigatus spores, 100 ng/mL LPS (E. coli O111:B4, MilliporeSigma, Etobicoke, ON, Canada) and 10 6 /mL silica microspheres ( FLS ) (Polysciences, Warrington, PA, USA) (7), or with cell culture medium as the control condition (9). Peripheral blood mononuclear cells were isolated (SepMate™ STEMCELL Technologies, Vancouver, BC, Canada) from EDTA-anticoagulated blood and incubated in a complete cell culture medium with RPMI 1640, HEPES, 10% heat-inactivated horse serum, and penicillin-streptomycin (Gibco™; TFS). Cells were cultured for 7 days, with medium replacement every two days. On day 7, MDMs were detached and treated under the same conditions as outlined above for AMs (9). The purity of AMs and MDMs exceeded 98%, as confirmed by flow cytometry (13). RNA Isolation and Sequencing After 6 hours’ exposure time, total RNA was isolated using the RNeasy Mini Kit (Qiagen, Toronto, ON, Canada). RNA integrity was assessed, ensuring an integrity number >7. cDNA libraries were prepared using the NEBNext Ultra II Directional RNA Library Preparation Kit for Illumina (New England BioLabs, Whitby, ON, Canada). Sequencing was performed on a NovaSeq 6000 SP (Illumina, Mississauga, ON) platform to generate paired-end reads of 100 bases (9). Data Analysis Raw RNA-seq read quality was assessed using FastQC (v.0.11.5), and adaptors were trimmed using Trim Galore (v.0.5.0). STAR aligner (v.2.6.0c) was used to align raw trimmed reads to the reference genome (Ensembl EquCab3.0). HTSeq (v.0.6.1p2) extracted raw read counts for genes from STAR alignments. DGE profiling used DESeq2 (v.1.26.0s) in R (v.3.6.1), with a minimal filtering criterion of 10 read counts per gene in at least two samples. The false discovery rate (FDR) adjusted p-value was set at <0.05. R (v.3.6.1) was used to generate diagnostic plots for data quality control and initial data exploration, followed by volcano plots to visualize global DGE results, and heatmaps to more finely focus on gene expression patterns (9). Horse genes originating from gene ontology and KEGG databases (https://www.kegg.jp) were used to annotate the gene sets used in gene set enrichment analysis (GSEA; GSEA software v.4.0.3). The pathway databases Reactome (https://reactome.org) and BioCarta (http://www.biocarta.com) were changed to equine from human identifiers to perform network comparisons. GSEA results were visualized in Cytoscape (v.3.8.1; https://cytoscape.org) using the EnrichmentMap (v.3.3.3) plugin. These datasets can be accessed in NCBI’s Gene Expression Omnibus (GEO) under accession number GSE207864 (9). Results Bronchoalveolar lavage fluid cytology A differential count of 500 BALF cells confirmed the absence of airway inflammation, i.e., neutrophils ≤ 5%, mast cells ≤ 2%, eosinophils ≤ 1% for all horses ( 9 , 13 ). RNA-seq analysis of equine AM and MDM transcriptomes The average RNA concentration and integrity number over the 24 samples were 69 ng/µL and 9.9, respectively. Each sample yielded > 35 million paired-end reads after comprehensive quality control analyses. Ninety-two % – 98% of reads successfully aligned with the equine genome (EquCab3.0) of which 91% – 95% of reads aligned uniquely (Figure A1) ( 9 ). Diagnostic plots Principal component analysis (PCA) and a heatmap of the most significant 50 DEGs between control AMs and MDMs showed grouping among replicates between treatment conditions and cell types (Fig. 1 ) and broadly similar gene expression within groups (Figure A2). The sample groups spread across two principal components (PCs), where PC1 accounted for 57% and PC2 accounted for 26% of sample variability, suggesting that cell type accounted for the greatest variance. The multidimensional scaling (Figure A3) and sample clustering plots (Figure A4) yielded similarly grouped results ( 9 ). Gene set enrichment analysis For each pathway, the GSEA evaluated whether the pathway was enriched in DEGs and whether these genes were over- or under-expressed compared to the reference level. For each comparison, the top 10 most significant pathways enriched in up-regulated and down-regulated genes were listed (Tables A1A-A3B). The comparison between FLS-stimulated and control AMs indicated “cytokine signaling” as the top biological theme activated by FLS exposure (Figure A5). The comparison between stimulated and control MDMs identified “cytokine signaling in immune response” as the major biological process in FLS-exposed MDMs (Figure A6). Because few DEGs were identified between AMs and MDMs (Figure A7), pathways with an FDR < 0.25 were analysed to create their network (Fig. 2 ). Relatively few immune-related biological themes showed differences between AMs and MDMs in their responses to FLS exposure, but “JAK-STAT/IL-15 signaling”, “TNF receptor binding” and “inhibition of caspase8 activity” differed (Fig. 2 ) ( 9 ). Differential gene expression The pairwise comparison between FLS-stimulated and control AMs yielded 2815 DEGs with an FDR 1, with 1569 genes upregulated and 1246 genes downregulated (Figure A7). There were 2788 DEGs detected between FLS-stimulated and control MDMs, among which 1624 were upregulated and 1164 were down regulated (Figure A8). The comparison between AM and MDM in response to FLS yielded 589 DEGS, of which 198 were upregulated in AMs and 391 were upregulated in MDMs (Figure A9) ( 9 ). These data revealed upregulation of proinflammatory genes, IDO1 , CD80 , and IL20 in stimulated AMs, but not MDMs. In contrast, the immune-modulating genes CD200 and CD83 were upregulated in activated MDMs but not AMs. Finally, for FLS-exposed AMs and MDMs, the 50 most significant DEGs with the lowest FDR were plotted in a hierarchical heatmap, to visualize gene expression patterns (Fig. 5 ). This plot revealed similarities and differences between AM and MDM groups. After FLS stimulation the expression of CD40 was upregulated in both AMs and MDMs. The CD40-related gene, SLAMF1 , had increased expression in stimulated MDMs only. Expression of CXXC5 , another CD40-related gene ( 24 ), was downregulated in stimulated AMs, but expression appeared static across MDMs. The IL10 gene did not appear on any plot. Discussion To our knowledge, this is the first study to analyze the complete transcriptome and molecular pathways of equine AMs and MDMs in response to a defined inflammatory stimulus (FLS) ( 9 ). This mixture simulates the components in inhaled air that are associated with the development of asthma in horses, and was previously used to cause asthma exacerbation in susceptible horses ( 7 ). Previous studies evaluating the transcriptomic response of human AMs and MDMs evaluated the effect of exposure to Mycobacteria ( 25 ) or respiratory viruses ( 26 ), and studies of equine MDMs assessed the response to infection with equine infectious anemia virus ( 27 ). None of these studies are comparable to the experimental design of our study. Limitations of the current study are that samples from healthy horses were evaluated, and since viable fungal spores that would germinate over time were used, a time-course study was not achievable. Evaluation of changes in gene expression over time is pertinent to future work. Broadly, our identification of mixed pro- and anti-inflammatory responses mirrors results of previous work. Namely, using RT-qPCR, evaluation of AMs retrieved from healthy horses after a hay/straw inhalation challenge, identified higher IL1 and IL10 gene expression compared to horses with sEA ( 28 ). While another group identified an increase in IL6 expression in healthy horse AMs, which was considered an anti-inflammatory response to challenge material ( 29 ). Pathway analyses of BALF total-cell lysates from horses with mild-moderate neutrophilic asthma identified enhanced activity in inflammation-related pathways ( 18 ), and AMs from healthy horses had increased expression of the TNF, CD40 and several apoptosis-related genes in response to LPS exposure, as identified by RNA microarray analyses ( 19 ). In the present work, cytokine signaling was the main biological process driven by FLS exposure in both AMs and MDMs, indicating a commonality of response ( 9 ). However, some 589 DEGs attributable to FLS exposure were detected between AMs and MDMs. Likewise, pathway analysis revealed that AMs and MDMs had similarly upregulated biological processes in response to FLS exposure, which is expected in related phagocytes ( 9 ). Nevertheless, the differences between AMs and MDMs within several inflammatory signaling pathways indicate differing roles for AMs and MDMs in the early response to stimuli. Therefore, exploring distinctions between AMs and MDMs in sEA is pertinent to advancing our understanding of disease dynamics. Because there were few differences in the pathway analysis between AMs and MDMs an FDR of 0.25 was applied (Fig. 2 ). Pathways including “TNF receptor binding”, “JAK-STAT signaling”, “inhibition of caspase8 activity”, “NOD-like receptor signaling pathway”, and “RIG-I-like receptor signaling pathway” were identified as upregulated in MDMs compared to AMs. This suggests that MDMs may be more responsive to inflammatory stimuli than AMs ( 9 ). Although caspase 8 positively regulates cell apoptosis ( 30 ), mirroring other work in healthy horse AMs exposed to LPS ( 19 ), inhibition of caspase 8 results in necroptosis ( 31 ), implying that AMs and MDMs may have different programmed cell death mechanisms ( 9 ). Although the latter pathways are important in innate antiviral immunity ( 32 ), NOD-like and RIG-I-like receptors also played important roles in anti-fungal immunity ( 33 ). Hence, MDMs may contribute more to recognizing fungal elements. Generally speaking, our results were similar to those of previous studies that identified higher activity in inflammation-related pathways of BALF total-cell lysates in horses with mild-moderate neutrophilic asthma ( 18 ), and a mixed pro- and anti-inflammatory response in AMs retrieved from healthy horses after exposure to inhaled challenge material ( 28 , 29 ). Although similar responses to FLS exposure were noted between cell types (Fig. 2 ), the PCA (Fig. 1 ) and DEG heatmap (Fig. 5 ) plots demonstrated distinct gene expression in each type under both exposure and control conditions. In our previous work, AMs of healthy horses had naturally higher surface expression of the anti-inflammatory markers CD163 and CD206 than MDMs ( 13 ), suggesting a greater role in maintaining lung homeostasis in the steady state. However, an influx of proinflammatory monocytes, expected to promote neutrophilic inflammation, was identified in asthmatic horses ( 34 ), and monocytes are implicated in the pathogenesis of human neutrophilic asthma ( 20 ). Additionally, in an earlier study, we identified an increase in the expression of these two markers in sEA-affected horses, but not in healthy horses after exposure to moldy hay ( 10 ). This suggested that similar to some types of human asthma ( 21 ), macrophages with high phagocytic capacity contributed to the disease phenotype. Genes upregulated in AMs but not MDMs, associated with a proinflammatory phenotype, included IDO1 , CD80 , and IL20 . The IDO1 gene encodes indoleamine dioxygenase, and similar to human macrophages, equine forms have increased IDO1 expression in response to LPS stimulation, whereas dissimilar to horses and humans, mouse macrophages have increased NOS2 ( 19 ). Pro-inflammatory macrophages express CD80, an important co-stimulatory molecule for T-cell activation ( 35 ), which was also noted in LPS- and interferon-polarized AMs from healthy and sEA-affected horses ( 28 ). Greater expression of CD80 on AMs than MDMs would suggest more efficient T-cell antigen presentation ( 36 ). IL-20 can promote or attenuate inflammation depending on the tissue context ( 37 ), and decreased IL-20 is pivotal in the pathogenesis of autoimmune diseases, intestinal inflammatory diseases, and human allergic asthma ( 9 , 37 – 40 ). Our results suggest that AMs could be a major source of IL-20 in the lower respiratory tract, and therefore, present a potential therapeutic target to modulate airway inflammation ( 9 ). However, an assay to measure equine IL-20 is not currently available to corroborate this hypothesis ( 13 ). Members of the immunoglobulin supergene family upregulated in MDMs but not AMs included CD200 (Fig. 2 ) and CD83 (Fig. 4 ) ( 41 ). CD200 is a cell-surface protein induced by TLR activation that along with its costimulatory molecule, CD200R, inhibits myeloid cell activation ( 42 ). Decreased expression of CD200 on circulating monocytes was associated with childhood asthma exacerbation ( 41 ). Despite the potent proinflammatory response induced by FLS, greater expression of CD200 mRNA by MDMs suggests an ability to modulate the inflammatory response ( 9 ). The expression of CD83, a molecule that is decreased on the dendritic cells of human asthmatic smokers ( 43 ) and that controls and resolves inflammation ( 44 ), on MDMs also supports an immunomodulatory role for these cells. However, this difference may be because monocyte-derived cells are sources of CD83 while resident macrophages are not ( 9 , 44 ). A comparison of the top 50 up- and downregulated genes between stimulated and control AMs and MDMs also revealed similarities and differences within and between groups in genes associated with several human lung diseases, cancer progression, apoptosis, and resistance to infection (Fig. 5 ). CD40 , which encodes the cognate of CD40L was upregulated in both cell types after stimulation. This result is similar to other work wherein CD40 expression increased in healthy horse AMs after LPS exposure ( 19 ). Upregulation of CD40 has been associated with the potential for pulmonary fibrosis in mice ( 24 ), and increased gene expression may suggest it also plays a role in the structural changes noted in sEA. SLAMF1 , the product of which negatively regulates the CD40 signalling pathway ( 45 ), had increased expression in stimulated MDMs only. CXXC5 , encodes a widely expressed protein that bore an inverse relationship with CD40 and CD40L expression in mouse lungs suggesting an inhibitory effect on development of fibrosis ( 45 ). This gene was downregulated in stimulated AMs, and expression appeared constant across MDMs. Together, these results suggest that each cell type has a differential contribution to dampening the effects of potentially harmful pathway activation. Finally, although IL-10 production was increased in MDMs after FLS exposure ( 13 ) it did not feature on any of our DEG plots. This finding is in contrast to a previous study that identified increased IL-10 expression in AMs of healthy horses after a hay/straw inhalation challenge using RT-qPCR ( 28 ). The absence in our work may relate to IL-10’s known feedback inhibition on mRNA, or autocrine signalling inducing IL-10 production. However, the latter is considered less likely because 18 hours of incubation time was required to see this effect in human MDMs exposed to IL-10 and LPS ( 46 ). Conclusions In summary, equine AMs and MDMs exposed to a standardized challenge capable of causing sEA exacerbation had many common and a few distinct gene expression responses. Therefore, both types of innate immune cells likely have critical but differing roles in protecting the host against the effects of inhaled agonists and on regulating inflammation. A deeper exploration of whether these macrophages alter their function in horses with sEA would contribute significantly to our understanding of this disease’s pathogenesis. Declarations Ethics approval: The project was approved under Animal Use Protocols 3816 and 4675 by the University of Guelph's Animal Care Committee Consent for publication: Not applicable. Horses were from the University of Guelph equine research herd. Availability of data and materials: All datasets were deposited in the NCBI’s Gene Expression Omnibus (GEO) under accession number GSE207864 Competing interests: The authors declare that they have no competing interests. Funding: Funding for this study was provided by Equine Guelph, Grant Number EG 2017 01 and The Ontario Ministry of Agriculture, Food and Agribusiness Grant Number 27364. Neither funding source had any role in the design, analysis or reporting of the study. Authors’ contributions: Conception and design: JBM, HK, DB, BNL, LGA, JH; Analysis and interpretation: HK, JBM, DB, BNL, LGA, JH, GKCL; Drafting of the manuscript for important intellectual content: HK, JBM, DB, BNL. Acknowledgements: The authors thank Dr. Roumiana Alexandrova and Dr. Giovanna Pellecchia for their assistance with the RNA-seq data analysis. References Bond S, Leguillette R, Richard EA, Couetil L, Lavoie JP, Martin JG, et al. 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The correlation between IL-20 and the Th2 immune response in human asthma. Asian Pac J Allergy Immunol. 2014;32(4):316-20. Lauzon-Joset JF, Marsolais D, Tardif-Pellerin E, Patoine D, Bissonnette EY. CD200 in asthma. Int J Biochem Cell Biol. 2019;112:141-4. Mukhopadhyay S, Pluddemann A, Hoe JC, Williams KJ, Varin A, Makepeace K, et al. Immune inhibitory ligand CD200 induction by TLRs and NLRs limits macrophage activation to protect the host from meningococcal septicemia. Cell Host Microbe. 2010;8(3):236-47. Spears M, McSharry C, Donnelly I, Jolly L, Brannigan M, Thomson J, et al. Peripheral blood dendritic cell subtypes are significantly elevated in subjects with asthma. Clin Exp Allergy. 2011;41(5):665-72. Grosche L, Knippertz I, König C, D. R, Wild AB, Zinser E, et al. The CD83 Molecule - An Important Immune Checkpoint. Front Immunol. 2020;11:721. Kohn EM, Dos Santos Dias L, Dobson HE, He X, Wang H, Klein BS, et al. SLAMF1 Is Dispensable for Vaccine-Induced T Cell Development but Required for Resistance to Fungal Infection. J Immunol. 2022;208(6):1417-23. Staples KJ, Smallie T, Williams LM, Foey A, Burke B, Foxwell BM, et al. IL-10 induces IL-10 in primary human monocyte-derived macrophages via the transcription factor Stat3. J Immunol. 2007;178(8):4779-85. Additional Declarations No competing interests reported. Supplementary Files Additionalfile1KangetalJuly152025.docx Cite Share Download PDF Status: Published Journal Publication published 06 Feb, 2026 Read the published version in BMC Veterinary Research → Version 1 posted Editorial decision: Revision requested 27 Oct, 2025 Reviews received at journal 24 Oct, 2025 Reviewers agreed at journal 25 Sep, 2025 Reviews received at journal 19 Sep, 2025 Reviewers agreed at journal 27 Aug, 2025 Reviews received at journal 19 Aug, 2025 Reviewers agreed at journal 23 Jul, 2025 Reviewers invited by journal 21 Jul, 2025 Editor assigned by journal 20 Jul, 2025 Editor invited by journal 18 Jul, 2025 Submission checks completed at journal 17 Jul, 2025 First submitted to journal 17 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7122919","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":489384174,"identity":"080cc68e-89e6-4b15-a0a7-955da56f9714","order_by":0,"name":"Heng Kang","email":"","orcid":"","institution":"Sanofi (Canada)","correspondingAuthor":false,"prefix":"","firstName":"Heng","middleName":"","lastName":"Kang","suffix":""},{"id":489384175,"identity":"a32747df-50b0-407c-920e-71e1c18fbe32","order_by":1,"name":"Gary K.C. Lee","email":"","orcid":"","institution":"IDEXX Laboratories Pty. Ltd","correspondingAuthor":false,"prefix":"","firstName":"Gary","middleName":"K.C.","lastName":"Lee","suffix":""},{"id":489384176,"identity":"b00c7302-8b32-4822-9631-a588cdc2b453","order_by":2,"name":"Dorothee Bienzle","email":"","orcid":"","institution":"University of Guelph","correspondingAuthor":false,"prefix":"","firstName":"Dorothee","middleName":"","lastName":"Bienzle","suffix":""},{"id":489384177,"identity":"7193d3c4-8d19-4832-9ada-5f1df14408e7","order_by":3,"name":"Jutta Hammermüller","email":"","orcid":"","institution":"University of Guelph","correspondingAuthor":false,"prefix":"","firstName":"Jutta","middleName":"","lastName":"Hammermüller","suffix":""},{"id":489384178,"identity":"4d621b96-702d-4d44-b42e-28527221ad49","order_by":4,"name":"Luis G. Arroyo","email":"","orcid":"","institution":"University of Guelph","correspondingAuthor":false,"prefix":"","firstName":"Luis","middleName":"G.","lastName":"Arroyo","suffix":""},{"id":489384179,"identity":"a046a903-9c39-4bd7-ac1c-260ffbbd9763","order_by":5,"name":"Brandon N. Lillie","email":"","orcid":"","institution":"University of Guelph","correspondingAuthor":false,"prefix":"","firstName":"Brandon","middleName":"N.","lastName":"Lillie","suffix":""},{"id":489384180,"identity":"bffb425c-e278-4218-9490-bd363ee42928","order_by":6,"name":"Janet Beeler-Marfisi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYBACxhlA4gEQ80P4FgwGRGlJAGLJBjBfgrAWoBqIFoMDxGphnt188EFCxb1o4xvJh1/zVEjkmTMwP/yA12FzjiUbJJwpzt12Iy3NmueMRLFlA5uxBH6/5JhJJLYlALXkmBnztkkkbjjAw0BAS/73H4n/EnI3zwBp+QfWwvyDgC1sDIkNCbkbJHKMH/M2gLWw4bdlzjFjiYRjCbkzzjxLA3Ikig0Os5lZ4NNiOLv54YcPNQm5/e3Jhz+8qbHJMzje/PgGXi0NCDYbJI6Y8akHAnkkNvMHBki0joJRMApGwShAAQCD6E6E5z5iWQAAAABJRU5ErkJggg==","orcid":"","institution":"University of Guelph","correspondingAuthor":true,"prefix":"","firstName":"Janet","middleName":"","lastName":"Beeler-Marfisi","suffix":""}],"badges":[],"createdAt":"2025-07-14 15:53:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7122919/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7122919/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12917-026-05322-0","type":"published","date":"2026-02-06T15:59:04+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":87440089,"identity":"648f2b07-b2a1-4308-8346-a7dfcdcca750","added_by":"auto","created_at":"2025-07-23 19:37:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":23196,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal component analysis (PCA) of all samples. The plot was generated using rlog-transformed counts. The percentage of variance indicates how much of the difference between AM and MDM treatment and control responses was explained by PC1 and PC2. The major differences are caused by cell type and treatment. AM: alveolar macrophage; MDM: monocyte-derived macrophage; C: control, serum-free RPMI alone; T: treatment, serum-free RPMI containing fungal spores, LPS and silica microspheres (FLS). Each number represents one horse.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7122919/v1/96646582646b43ff1661e3a0.png"},{"id":87439005,"identity":"bb4944e9-c5bd-47a1-baca-0dc1e1c9965a","added_by":"auto","created_at":"2025-07-23 19:21:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":200349,"visible":true,"origin":"","legend":"\u003cp\u003eGene-set enrichment analysis of the differentially expressed genes between alveolar macrophages and monocyte-derived macrophages reflecting the effect of FLS on expression change. Each node represents a gene-set. FDR: false discovery rate q-value, centre of each node. NES: normalized enrichment score, edge of each node. Connecting lines: genes overlap between sets. Size of the node: number of genes annotated to the gene-set. FDR threshold was set at 0.25. Interferon antiviral response is the most prominent biological theme upregulated by FLS.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7122919/v1/ab39e7f6b80234912f47d71c.png"},{"id":87439007,"identity":"57a5f253-1b77-42a7-a24c-3345204cc49b","added_by":"auto","created_at":"2025-07-23 19:21:23","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":167493,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of the top 100 differentially expressed genes in alveolar macrophages between treatment and control conditions with an absolute log2 fold change \u0026gt;1. FDR threshold was set at 0.05.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7122919/v1/e8e4360aa54711a65127784e.png"},{"id":87439826,"identity":"85d0c076-f619-461c-9ccf-dbf77883f34c","added_by":"auto","created_at":"2025-07-23 19:29:23","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":175854,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of the top 100 differentially expressed genes in monocyte-derived macrophages between treatment and control conditions with an absolute log2 fold change \u0026gt;1. FDR threshold was set at 0.05.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7122919/v1/b7b28af89fb919cbf4729927.png"},{"id":87439828,"identity":"ea296ab5-99d9-4a2b-8e2b-f68ee940c0ed","added_by":"auto","created_at":"2025-07-23 19:29:23","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":45163,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of the top 50 differentially expressed genes between alveolar macrophages and monocyte-derived macrophages reflecting the effect of FLS on expression change. For each comparison, the top 50 genes with the lowest FDR were plotted in a hierarchical heatmap. FDR threshold was set at 0.25. See Figure A2 for the top 50 differentially expressed genes between alveolar macrophages and monocyte-derived macrophages in response to FLS or cell culture medium as the control exposure condition.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7122919/v1/2317d23a8c13c1b6ee2b470c.png"},{"id":102234369,"identity":"841d5eca-d9ff-4a88-88e5-c70cd9aeae2e","added_by":"auto","created_at":"2026-02-09 16:10:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1027856,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7122919/v1/1c7b5fa6-9f9e-4040-8eb7-4195e52535e6.pdf"},{"id":87439025,"identity":"1e5490e3-2e6a-409f-b41a-ffca70124887","added_by":"auto","created_at":"2025-07-23 19:21:23","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":19844512,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1KangetalJuly152025.docx","url":"https://assets-eu.researchsquare.com/files/rs-7122919/v1/1487bf3d4308443b48051f18.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"RNA-seq evaluation of equine alveolar macrophages and monocyte-derived macrophages exposed to an inflammatory stimulus","fulltext":[{"header":"Background","content":"\u003cp\u003eSevere equine asthma (sEA), is a naturally occurring disease of mature animals that has features of airway hyperresponsiveness, mucus hypersecretion, bronchial remodelling, fibrosis, and lung mucosal epithelial dysfunction, that mirror the human condition (1-3). The prevalence of sEA is estimated at 14% in the northern hemisphere (4); higher than that suggested for adult humans (5, 6). Additionally, as horses are long lived, the disease and response to therapy can be evaluated over many years in the same individual\u0026nbsp;(7).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAlveolar macrophages (AMs) phagocytose and coordinate cytokine-mediated immune responses against inhaled antigens in the lung\u0026nbsp;(8, 9). For example, in response to moldy hay challenge, sEA-affected horses had increased gene expression of the proinflammatory tumor necrosis factor (TNF) and interleukin (IL)-1\u0026beta;, and the anti-inflammatory IL-10, and decreased surface expression of CD163 and CD206, suggesting an aberrant anti-inflammatory immunophenotype (9, 10). In pulmonary inflammation, circulating monocytes infiltrate the lung and develop a gene expression pattern similar to resident AMs\u0026nbsp;(11). Both phagocytes express pattern recognition receptors including dectin-1 and toll-like receptor (TLR)-4, which, on engaging fungal \u0026beta;-glucan and bacterial lipopolysaccharide (LPS) respectively, induce a cytokine response cascade\u0026nbsp;(12). Even though resident AMs and newly recruited MDMs share similarities in their phenotypes, important differences, including propensity for phagocytosis and the nature of the inflammatory responses each engenders, have been identified\u0026nbsp;(9, 13). Additionally, AMs and MDMs had differing cytokine and immunophenotype responses when cultured with a mixture of \u003cstrong\u003e\u003cu\u003ef\u003c/u\u003e\u003c/strong\u003eungal spores, \u003cstrong\u003e\u003cu\u003eL\u003c/u\u003e\u003c/strong\u003ePS and \u003cstrong\u003e\u003cu\u003es\u003c/u\u003e\u003c/strong\u003eilica microspheres (FLS), to emulate the barn particulates that exacerbate sEA\u0026nbsp;(9, 13). However, RNA-seq studies separately investigating equine AM and MDM responses in pulmonary disease are rare\u0026nbsp;(14, 15).\u003c/p\u003e\n\u003cp\u003eRNA-seq analysis is an advanced method to measure gene transcripts in a given sample, that permits a snapshot assessment of differences in gene expression and transcription activation between two conditions\u0026nbsp;(16). RNA-seq analysis can include differential gene expression and other comparative transcriptomic analyses that can reveal the underlying response to environmental stimuli and molecular mechanisms that drive disease pathogenesis\u0026nbsp;(2). Although a powerful tool, RNA-seq has uncommonly been used to evaluate equine lung diseases (2, 9, 17, 18). For example, a defective response of the bronchial epithelium to a moldy hay challenge was a feature of horses with sEA, where \u0026gt;100 differentially expressed genes (DEGs) were identified between sEA-affected and healthy horses\u0026nbsp;(2). Differing quiescent and LPS-induced gene expression was observed in equine peritoneal macrophages and AMs using comparative transcriptomic analysis\u0026nbsp;(19). However, similar information is lacking for how AMs and MDMs regulate the early lower airway immune response in horses.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the present study, we exposed AMs and MDMs from horses without lower airway disease to FLS\u0026nbsp;(7)\u0026nbsp;or to cell culture medium (control) \u003cem\u003ein vitro\u003c/em\u003e, followed by RNA-seq evaluation of cellular responses. We hypothesized that AMs and MDMs would have distinct gene expression responses to FLS exposure, suggesting differing roles in the early inflammatory response. Our objective was to compare AM and MDM gene expression, including identifying the corresponding pathways from those DEGs. We undertook this work because a more detailed understanding of the responses of these different lung phagocytes could reveal unique roles for AMs and MDMs in the early inflammatory response, and identify likely preventive or therapeutic targets. Furthermore, it is possible that similar to human asthma, aberrant phagocytic responses and increased monocyte recruitment to the lung contribute to the asthma phenotype in sEA-affected horses (20, 21). Therefore, if we identified different roles for AMs and MDMs in lung inflammation, then future studies of their responses in sEA-affected horses would be warranted.\u003c/p\u003e"},{"header":"Methods ","content":"\u003cp\u003eThe study was a parallel controlled design where AMs and MDMs were collected from each of six clinically healthy female Standardbred horses between the ages of 10 and 21 years. These horses are part of the University of Guelph’s closed research horse herd and are kept at pasture with run-in barn access. To reduce animal distress, horses were shipped in groups of two to the Large Animal Health Sciences Centre of the University of Guelph, sampled, and returned to their herd in the same day with a 24-hour close monitoring period for development of fever or cough. No adverse events occurred. The inclusion criterion was good health status, which was confirmed through physical examination, airway endoscopy, complete blood count, serum biochemical profile, and bronchoalveolar lavage fluid (BALF) cytology evaluation. The exclusion criteria included a previous history of equine asthma, poor physical health, or having diagnostic testing results outside of the reference interval. No horse was excluded. From each horse, 10\u003csup\u003e6\u003c/sup\u003e AMs and 10\u003csup\u003e6\u003c/sup\u003e MDMs were seeded into each well of a 6-well culture plate in technical triplicates, under both treatment and control conditions, for a total of 18 x 10\u003csup\u003e6\u003c/sup\u003e from each of AMs and MDMs. The sample size was determined based on a previous equine RNA-seq evaluation,(22) and best practice recommendations for DEG studies.(23)\u0026nbsp; Each sample was split into FLS-exposure and non-exposure groups. Because FLS is green and the cell culture medium, or control, is pink in color, a blinded approach was not possible, and randomization was not used to allocate plate position of FLS-treatment or control. Confounders, such as the order of plate location, were not controlled. The variables assessed were DEGs between exposure conditions and within and between the two cell types. The project was approved under Animal Use Protocols 3816 and 4675 by the University of Guelph's Animal Care Committee, adhering to Canadian Council on Animal Care standards. Portions of this work represent research presented in the PhD thesis of the primary author, Dr. Kang, and have been presented previously in that form (9).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCell Collection and Exposure\u003c/p\u003e\n\u003cp\u003eUsing an endoscope, 500 mL of warmed sterile saline was instilled into a 4\u003csup\u003eth\u003c/sup\u003e to 6\u003csup\u003eth\u003c/sup\u003e generation bronchus (7) and approximately 350 mL of BALF was retrieved, then within 20 minutes, was centrifuged at 400 \u003cstrong\u003eg\u003c/strong\u003e for 10 minutes at 4°C. AM isolation was achieved by capitalizing on the adherent properties of AMs, in that the cell pellet was washed in PBS, resuspended in RPMI 1640 medium with HEPES, and incubated in 75 cm² flasks at 37°C with 5% CO2 for 30 minutes. AMs were detached (TrypLE™ Select Enzyme 10X, Thermo Fisher Scientific (TFS), Mississauga, ON, Canada) and 10\u003csup\u003e6\u003c/sup\u003e cells per well were transferred to 6-well culture plates. Cells were incubated for 6 hours at 37°C with 5% CO\u003csub\u003e2\u003c/sub\u003e in serum-free RPMI containing 10\u003csup\u003e6\u003c/sup\u003e/mL \u003cem\u003eAspergillus fumigatus\u003c/em\u003e spores, 100 ng/mL LPS (E. coli O111:B4, MilliporeSigma, Etobicoke, ON, Canada) and 10\u003csup\u003e6\u003c/sup\u003e/mL silica microspheres (\u003cstrong\u003eFLS\u003c/strong\u003e) (Polysciences, Warrington, PA, USA)\u0026nbsp;(7), or with cell culture medium as the control condition\u0026nbsp;(9).\u003c/p\u003e\n\u003cp\u003ePeripheral blood mononuclear cells were isolated (SepMate™ STEMCELL Technologies, Vancouver, BC, Canada) from EDTA-anticoagulated blood and incubated in a complete cell culture medium with RPMI 1640, HEPES, 10% heat-inactivated horse serum, and penicillin-streptomycin (Gibco™; TFS). Cells were cultured for 7 days, with medium replacement every two days. On day 7, MDMs were detached and treated under the same conditions as outlined above for AMs (9). The purity of AMs and MDMs exceeded 98%, as confirmed by flow cytometry (13).\u003c/p\u003e\n\u003cp\u003eRNA Isolation and Sequencing\u003c/p\u003e\n\u003cp\u003eAfter 6 hours’ exposure time, total RNA was isolated using the RNeasy Mini Kit (Qiagen, Toronto, ON, Canada). RNA integrity was assessed, ensuring an integrity number \u0026gt;7. cDNA libraries were prepared using the NEBNext Ultra II Directional RNA Library Preparation Kit for Illumina (New England BioLabs, Whitby, ON, Canada). Sequencing was performed on a NovaSeq 6000 SP (Illumina, Mississauga, ON) platform to generate paired-end reads of 100 bases (9).\u003c/p\u003e\n\u003cp\u003eData Analysis\u003c/p\u003e\n\u003cp\u003eRaw RNA-seq read quality was assessed using FastQC (v.0.11.5), and adaptors were trimmed using Trim Galore (v.0.5.0). STAR aligner (v.2.6.0c) was used to align raw trimmed reads to the reference genome (Ensembl EquCab3.0). HTSeq (v.0.6.1p2)\u0026nbsp;extracted raw read counts for genes from STAR alignments. DGE profiling used DESeq2 (v.1.26.0s) in R (v.3.6.1), with a minimal filtering criterion of 10 read counts per gene in at least two samples. The false discovery rate (FDR) adjusted p-value was set at \u0026lt;0.05. R (v.3.6.1) was used to generate diagnostic plots for data quality control and initial data exploration, followed by volcano plots to visualize global DGE results, and heatmaps to more finely focus on gene expression patterns (9).\u003c/p\u003e\n\u003cp\u003eHorse genes originating from gene ontology and KEGG databases (https://www.kegg.jp) were used to annotate the gene sets used in gene set enrichment analysis (GSEA; GSEA software v.4.0.3). The pathway databases Reactome (https://reactome.org) and BioCarta (http://www.biocarta.com) were changed to equine from human identifiers to perform network comparisons. GSEA results were visualized in Cytoscape (v.3.8.1; https://cytoscape.org) using the EnrichmentMap (v.3.3.3) plugin. These datasets can be accessed in NCBI’s Gene Expression Omnibus (GEO) under accession number GSE207864 (9).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eBronchoalveolar lavage fluid cytology\u003c/p\u003e\u003cp\u003eA differential count of 500 BALF cells confirmed the absence of airway inflammation, i.e., neutrophils\u0026thinsp;\u0026le;\u0026thinsp;5%, mast cells\u0026thinsp;\u0026le;\u0026thinsp;2%, eosinophils\u0026thinsp;\u0026le;\u0026thinsp;1% for all horses (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRNA-seq analysis of equine AM and MDM transcriptomes\u003c/p\u003e\u003cp\u003eThe average RNA concentration and integrity number over the 24 samples were 69 ng/\u0026micro;L and 9.9, respectively. Each sample yielded\u0026thinsp;\u0026gt;\u0026thinsp;35\u0026nbsp;million paired-end reads after comprehensive quality control analyses. Ninety-two % \u0026ndash; 98% of reads successfully aligned with the equine genome (EquCab3.0) of which 91% \u0026ndash; 95% of reads aligned uniquely (Figure A1) (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDiagnostic plots\u003c/p\u003e\u003cp\u003ePrincipal component analysis (PCA) and a heatmap of the most significant 50 DEGs between control AMs and MDMs showed grouping among replicates between treatment conditions and cell types (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and broadly similar gene expression within groups (Figure A2). The sample groups spread across two principal components (PCs), where PC1 accounted for 57% and PC2 accounted for 26% of sample variability, suggesting that cell type accounted for the greatest variance. The multidimensional scaling (Figure A3) and sample clustering plots (Figure A4) yielded similarly grouped results (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eGene set enrichment analysis\u003c/p\u003e\u003cp\u003eFor each pathway, the GSEA evaluated whether the pathway was enriched in DEGs and whether these genes were over- or under-expressed compared to the reference level. For each comparison, the top 10 most significant pathways enriched in up-regulated and down-regulated genes were listed (Tables A1A-A3B). The comparison between FLS-stimulated and control AMs indicated \u0026ldquo;cytokine signaling\u0026rdquo; as the top biological theme activated by FLS exposure (Figure A5). The comparison between stimulated and control MDMs identified \u0026ldquo;cytokine signaling in immune response\u0026rdquo; as the major biological process in FLS-exposed MDMs (Figure A6). Because few DEGs were identified between AMs and MDMs (Figure A7), pathways with an FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.25 were analysed to create their network (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Relatively few immune-related biological themes showed differences between AMs and MDMs in their responses to FLS exposure, but \u0026ldquo;JAK-STAT/IL-15 signaling\u0026rdquo;, \u0026ldquo;TNF receptor binding\u0026rdquo; and \u0026ldquo;inhibition of caspase8 activity\u0026rdquo; differed (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e) (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDifferential gene expression\u003c/p\u003e\u003cp\u003eThe pairwise comparison between FLS-stimulated and control AMs yielded 2815 DEGs with an FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and absolute log2 fold change\u0026thinsp;\u0026gt;\u0026thinsp;1, with 1569 genes upregulated and 1246 genes downregulated (Figure A7). There were 2788 DEGs detected between FLS-stimulated and control MDMs, among which 1624 were upregulated and 1164 were down regulated (Figure A8). The comparison between AM and MDM in response to FLS yielded 589 DEGS, of which 198 were upregulated in AMs and 391 were upregulated in MDMs (Figure A9) (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). These data revealed upregulation of proinflammatory genes, \u003cem\u003eIDO1\u003c/em\u003e, \u003cem\u003eCD80\u003c/em\u003e, and \u003cem\u003eIL20\u003c/em\u003e in stimulated AMs, but not MDMs. In contrast, the immune-modulating genes \u003cem\u003eCD200\u003c/em\u003e and \u003cem\u003eCD83\u003c/em\u003e were upregulated in activated MDMs but not AMs. Finally, for FLS-exposed AMs and MDMs, the 50 most significant DEGs with the lowest FDR were plotted in a hierarchical heatmap, to visualize gene expression patterns (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). This plot revealed similarities and differences between AM and MDM groups. After FLS stimulation the expression of \u003cem\u003eCD40\u003c/em\u003e was upregulated in both AMs and MDMs. The CD40-related gene, \u003cem\u003eSLAMF1\u003c/em\u003e, had increased expression in stimulated MDMs only. Expression of \u003cem\u003eCXXC5\u003c/em\u003e, another CD40-related gene (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e), was downregulated in stimulated AMs, but expression appeared static across MDMs. The \u003cem\u003eIL10\u003c/em\u003e gene did not appear on any plot.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo our knowledge, this is the first study to analyze the complete transcriptome and molecular pathways of equine AMs and MDMs in response to a defined inflammatory stimulus (FLS) (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). This mixture simulates the components in inhaled air that are associated with the development of asthma in horses, and was previously used to cause asthma exacerbation in susceptible horses (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Previous studies evaluating the transcriptomic response of human AMs and MDMs evaluated the effect of exposure to \u003cem\u003eMycobacteria\u003c/em\u003e (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) or respiratory viruses (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), and studies of equine MDMs assessed the response to infection with equine infectious anemia virus (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). None of these studies are comparable to the experimental design of our study. Limitations of the current study are that samples from healthy horses were evaluated, and since viable fungal spores that would germinate over time were used, a time-course study was not achievable. Evaluation of changes in gene expression over time is pertinent to future work.\u003c/p\u003e\u003cp\u003eBroadly, our identification of mixed pro- and anti-inflammatory responses mirrors results of previous work. Namely, using RT-qPCR, evaluation of AMs retrieved from healthy horses after a hay/straw inhalation challenge, identified higher \u003cem\u003eIL1\u003c/em\u003e and \u003cem\u003eIL10\u003c/em\u003e gene expression compared to horses with sEA (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). While another group identified an increase in \u003cem\u003eIL6\u003c/em\u003e expression in healthy horse AMs, which was considered an anti-inflammatory response to challenge material (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Pathway analyses of BALF total-cell lysates from horses with mild-moderate neutrophilic asthma identified enhanced activity in inflammation-related pathways (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), and AMs from healthy horses had increased expression of the \u003cem\u003eTNF, CD40\u003c/em\u003e and several apoptosis-related genes in response to LPS exposure, as identified by RNA microarray analyses (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn the present work, cytokine signaling was the main biological process driven by FLS exposure in both AMs and MDMs, indicating a commonality of response (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). However, some 589 DEGs attributable to FLS exposure were detected between AMs and MDMs. Likewise, pathway analysis revealed that AMs and MDMs had similarly upregulated biological processes in response to FLS exposure, which is expected in related phagocytes (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Nevertheless, the differences between AMs and MDMs within several inflammatory signaling pathways indicate differing roles for AMs and MDMs in the early response to stimuli. Therefore, exploring distinctions between AMs and MDMs in sEA is pertinent to advancing our understanding of disease dynamics.\u003c/p\u003e\u003cp\u003eBecause there were few differences in the pathway analysis between AMs and MDMs an FDR of 0.25 was applied (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Pathways including \u0026ldquo;TNF receptor binding\u0026rdquo;, \u0026ldquo;JAK-STAT signaling\u0026rdquo;, \u0026ldquo;inhibition of caspase8 activity\u0026rdquo;, \u0026ldquo;NOD-like receptor signaling pathway\u0026rdquo;, and \u0026ldquo;RIG-I-like receptor signaling pathway\u0026rdquo; were identified as upregulated in MDMs compared to AMs. This suggests that MDMs may be more responsive to inflammatory stimuli than AMs (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Although caspase 8 positively regulates cell apoptosis (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e), mirroring other work in healthy horse AMs exposed to LPS (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), inhibition of caspase 8 results in necroptosis (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), implying that AMs and MDMs may have different programmed cell death mechanisms (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Although the latter pathways are important in innate antiviral immunity (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), NOD-like and RIG-I-like receptors also played important roles in anti-fungal immunity (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Hence, MDMs may contribute more to recognizing fungal elements. Generally speaking, our results were similar to those of previous studies that identified higher activity in inflammation-related pathways of BALF total-cell lysates in horses with mild-moderate neutrophilic asthma (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), and a mixed pro- and anti-inflammatory response in AMs retrieved from healthy horses after exposure to inhaled challenge material (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAlthough similar responses to FLS exposure were noted between cell types (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e), the PCA (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and DEG heatmap (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) plots demonstrated distinct gene expression in each type under both exposure and control conditions. In our previous work, AMs of healthy horses had naturally higher surface expression of the anti-inflammatory markers CD163 and CD206 than MDMs (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), suggesting a greater role in maintaining lung homeostasis in the steady state. However, an influx of proinflammatory monocytes, expected to promote neutrophilic inflammation, was identified in asthmatic horses (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e), and monocytes are implicated in the pathogenesis of human neutrophilic asthma (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Additionally, in an earlier study, we identified an increase in the expression of these two markers in sEA-affected horses, but not in healthy horses after exposure to moldy hay (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). This suggested that similar to some types of human asthma (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), macrophages with high phagocytic capacity contributed to the disease phenotype.\u003c/p\u003e\u003cp\u003eGenes upregulated in AMs but not MDMs, associated with a proinflammatory phenotype, included \u003cem\u003eIDO1\u003c/em\u003e, \u003cem\u003eCD80\u003c/em\u003e, and \u003cem\u003eIL20\u003c/em\u003e. The \u003cem\u003eIDO1\u003c/em\u003e gene encodes indoleamine dioxygenase, and similar to human macrophages, equine forms have increased \u003cem\u003eIDO1\u003c/em\u003e expression in response to LPS stimulation, whereas dissimilar to horses and humans, mouse macrophages have increased \u003cem\u003eNOS2\u003c/em\u003e (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Pro-inflammatory macrophages express CD80, an important co-stimulatory molecule for T-cell activation (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e), which was also noted in LPS- and interferon-polarized AMs from healthy and sEA-affected horses (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Greater expression of CD80 on AMs than MDMs would suggest more efficient T-cell antigen presentation (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). IL-20 can promote or attenuate inflammation depending on the tissue context (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e), and decreased IL-20 is pivotal in the pathogenesis of autoimmune diseases, intestinal inflammatory diseases, and human allergic asthma (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan additionalcitationids=\"CR38 CR39\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Our results suggest that AMs could be a major source of IL-20 in the lower respiratory tract, and therefore, present a potential therapeutic target to modulate airway inflammation (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). However, an assay to measure equine IL-20 is not currently available to corroborate this hypothesis (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMembers of the immunoglobulin supergene family upregulated in MDMs but not AMs included \u003cem\u003eCD200\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e) and \u003cem\u003eCD83\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). CD200 is a cell-surface protein induced by TLR activation that along with its costimulatory molecule, CD200R, inhibits myeloid cell activation (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). Decreased expression of CD200 on circulating monocytes was associated with childhood asthma exacerbation (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). Despite the potent proinflammatory response induced by FLS, greater expression of \u003cem\u003eCD200\u003c/em\u003e mRNA by MDMs suggests an ability to modulate the inflammatory response (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). The expression of CD83, a molecule that is decreased on the dendritic cells of human asthmatic smokers (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e) and that controls and resolves inflammation (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e), on MDMs also supports an immunomodulatory role for these cells. However, this difference may be because monocyte-derived cells are sources of CD83 while resident macrophages are not (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eA comparison of the top 50 up- and downregulated genes between stimulated and control AMs and MDMs also revealed similarities and differences within and between groups in genes associated with several human lung diseases, cancer progression, apoptosis, and resistance to infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). \u003cem\u003eCD40\u003c/em\u003e, which encodes the cognate of CD40L was upregulated in both cell types after stimulation. This result is similar to other work wherein \u003cem\u003eCD40\u003c/em\u003e expression increased in healthy horse AMs after LPS exposure (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Upregulation of CD40 has been associated with the potential for pulmonary fibrosis in mice (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e), and increased gene expression may suggest it also plays a role in the structural changes noted in sEA. \u003cem\u003eSLAMF1\u003c/em\u003e, the product of which negatively regulates the CD40 signalling pathway (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e), had increased expression in stimulated MDMs only. \u003cem\u003eCXXC5\u003c/em\u003e, encodes a widely expressed protein that bore an inverse relationship with CD40 and CD40L expression in mouse lungs suggesting an inhibitory effect on development of fibrosis (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). This gene was downregulated in stimulated AMs, and expression appeared constant across MDMs. Together, these results suggest that each cell type has a differential contribution to dampening the effects of potentially harmful pathway activation. Finally, although IL-10 production was increased in MDMs after FLS exposure (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) it did not feature on any of our DEG plots. This finding is in contrast to a previous study that identified increased IL-10 expression in AMs of healthy horses after a hay/straw inhalation challenge using RT-qPCR (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). The absence in our work may relate to IL-10\u0026rsquo;s known feedback inhibition on mRNA, or autocrine signalling inducing IL-10 production. However, the latter is considered less likely because 18 hours of incubation time was required to see this effect in human MDMs exposed to IL-10 and LPS (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, equine AMs and MDMs exposed to a standardized challenge capable of causing sEA exacerbation had many common and a few distinct gene expression responses. Therefore, both types of innate immune cells likely have critical but differing roles in protecting the host against the effects of inhaled agonists and on regulating inflammation. A deeper exploration of whether these macrophages alter their function in horses with sEA would contribute significantly to our understanding of this disease\u0026rsquo;s pathogenesis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval:\u003c/strong\u003e The project was approved under Animal Use Protocols 3816 and 4675 by the University of Guelph\u0026apos;s Animal Care Committee\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e Not applicable. Horses were from the University of Guelph equine research herd.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e All datasets were deposited in the NCBI\u0026rsquo;s Gene Expression Omnibus (GEO) under accession number GSE207864\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eFunding for this study was provided by Equine Guelph, Grant Number EG 2017 01 and The Ontario Ministry of Agriculture, Food and Agribusiness Grant Number 27364. Neither funding source had any role in the design, analysis or reporting of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions:\u0026nbsp;\u003c/strong\u003eConception and design: JBM, HK, DB, BNL, LGA, JH; Analysis and interpretation: HK, JBM, DB, BNL, LGA, JH, GKCL; Drafting of the manuscript for important intellectual content: HK, JBM, DB, BNL.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eThe authors thank Dr. Roumiana Alexandrova and Dr. Giovanna Pellecchia for their assistance with the RNA-seq data analysis.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBond S, Leguillette R, Richard EA, Couetil L, Lavoie JP, Martin JG, et al. Equine asthma: Integrative biologic relevance of a recently proposed nomenclature. J Vet Intern Med. 2018;32(6):2088-98.\u003c/li\u003e\n \u003cli\u003eTessier L, Cote O, Clark ME, Viel L, Diaz-Mendez A, Anders S, et al. 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Alveolar macrophage phenotypes in severe equine asthma. Vet J. 2020;256:105436.\u003c/li\u003e\n \u003cli\u003eLaan TT, Bull S, Pirie R, Fink-Gremmels J. The role of alveolar macrophages in the pathogenesis of recurrent airway obstruction in horses. J Vet Intern Med. 2006;20(1):167-74.\u003c/li\u003e\n \u003cli\u003eFritsch M, Gunther SD, Schwarzer R, Albert MC, Schorn F, Werthenbach JP, et al. Caspase-8 is the molecular switch for apoptosis, necroptosis and pyroptosis. Nature. 2019;575(7784):683-7.\u003c/li\u003e\n \u003cli\u003eTummers B, Green DR. Caspase-8: regulating life and death. Immunol Rev. 2017;277(1):76-89.\u003c/li\u003e\n \u003cli\u003eLi D, Wu M. Pattern recognition receptors in health and diseases. Signal Transduct Target Ther. 2021;6(1):291.\u003c/li\u003e\n \u003cli\u003ePatin EC, Thompson A, Orr SJ. Pattern recognition receptors in fungal immunity. 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IL-20: biological functions and clinical implications. J Biomed Sci. 2006;13(5):601-12.\u003c/li\u003e\n \u003cli\u003eHsu YH, Chang MS. IL-20 in rheumatoid arthritis. Drug Discov Today. 2017;22(6):960-4.\u003c/li\u003e\n \u003cli\u003eWu J, Wang G, Hao J, Gong W. The correlation between IL-20 and the Th2 immune response in human asthma. Asian Pac J Allergy Immunol. 2014;32(4):316-20.\u003c/li\u003e\n \u003cli\u003eLauzon-Joset JF, Marsolais D, Tardif-Pellerin E, Patoine D, Bissonnette EY. CD200 in asthma. Int J Biochem Cell Biol. 2019;112:141-4.\u003c/li\u003e\n \u003cli\u003eMukhopadhyay S, Pluddemann A, Hoe JC, Williams KJ, Varin A, Makepeace K, et al. Immune inhibitory ligand CD200 induction by TLRs and NLRs limits macrophage activation to protect the host from meningococcal septicemia. Cell Host Microbe. 2010;8(3):236-47.\u003c/li\u003e\n \u003cli\u003eSpears M, McSharry C, Donnelly I, Jolly L, Brannigan M, Thomson J, et al. Peripheral blood dendritic cell subtypes are significantly elevated in subjects with asthma. Clin Exp Allergy. 2011;41(5):665-72.\u003c/li\u003e\n \u003cli\u003eGrosche L, Knippertz I, K\u0026ouml;nig C, D. R, Wild AB, Zinser E, et al. The CD83 Molecule - An Important Immune Checkpoint. Front Immunol. 2020;11:721.\u003c/li\u003e\n \u003cli\u003eKohn EM, Dos Santos Dias L, Dobson HE, He X, Wang H, Klein BS, et al. SLAMF1 Is Dispensable for Vaccine-Induced T Cell Development but Required for Resistance to Fungal Infection. J Immunol. 2022;208(6):1417-23.\u003c/li\u003e\n \u003cli\u003eStaples KJ, Smallie T, Williams LM, Foey A, Burke B, Foxwell BM, et al. IL-10 induces IL-10 in primary human monocyte-derived macrophages via the transcription factor Stat3. J Immunol. 2007;178(8):4779-85.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-veterinary-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [BMC Veterinary Research](http://bmcvetres.biomedcentral.com/)","snPcode":"12917","submissionUrl":"https://submission.nature.com/new-submission/12917/3?","title":"BMC Veterinary Research","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Cell culture, differentially expressed genes, gene-set enrichment analysis, horse, innate immune cells, transcriptome","lastPublishedDoi":"10.21203/rs.3.rs-7122919/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7122919/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSevere equine asthma is common and analogous to neutrophilic asthma in humans. Caused by exposure to organic and inorganic environmental particulates, the disease manifests in mature horses as hyperreactive airways and severe neutrophilic lower airway inflammation. Macrophage populations in the lung, including resident alveolar macrophages (AMs) and recruited monocyte-derived macrophages (MDMs), recognize these barn dust particulates, and orchestrate an immune response thought the cytokines they produce. Despite their importance, the specific contributions of these macrophage subsets to equine asthma remain poorly understood. Our work aimed to investigate the contributions of AMs and MDMs to the early inflammatory response using RNA-seq.\u0026nbsp;Therefore, we undertook a 6-hour exposure of AMs and MDMs from six healthy female Standardbred horses to a mixture of \u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003ef\u003c/span\u003eungal spores, \u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003el\u003c/span\u003eipopolysaccharide, and \u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003es\u003c/span\u003eilica microspheres (FLS), as these form the major components of barn dust, with tissue culture medium as control. We hypothesized that AMs and MDMs would have differing transcriptional responses to FLS.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFrom our RNA-seq analyses, we identified differentially expressed genes and associated biological pathways. \u0026ldquo;Cytokine signaling\u0026rdquo; was identified as the major biological process activated by FLS in both cell types. Pathways including JAK-STAT/IL-15, TNF receptor binding, and IFN signaling were more highly upregulated in MDMs than AMs, suggesting that the two cell types have unique signalling pathways and inflammatory responses.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThese results indicate that equine AMs and MDMs have distinct responses to common inflammatory signals, and therefore, provide differing contributions to the early inflammatory response. These insights provide a foundation for future investigations of the role of equine AMs and MDMs to the pathogenesis of severe equine asthma.\u003c/p\u003e","manuscriptTitle":"RNA-seq evaluation of equine alveolar macrophages and monocyte-derived macrophages exposed to an inflammatory stimulus","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-23 19:21:18","doi":"10.21203/rs.3.rs-7122919/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-28T03:45:49+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-24T16:52:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"261209851092065878401828134561865816698","date":"2025-09-25T07:58:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-20T03:54:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"295959855027386802264817288197301454334","date":"2025-08-27T09:26:18+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-19T08:38:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"126242804744351488605045036013848246671","date":"2025-07-23T07:00:50+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-21T04:00:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-20T23:50:21+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-18T05:27:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-17T22:26:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Veterinary Research","date":"2025-07-17T18:06:16+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-veterinary-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [BMC Veterinary Research](http://bmcvetres.biomedcentral.com/)","snPcode":"12917","submissionUrl":"https://submission.nature.com/new-submission/12917/3?","title":"BMC Veterinary Research","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"500c7a29-146d-4f9d-b461-f28f33ea0782","owner":[],"postedDate":"July 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-09T16:06:52+00:00","versionOfRecord":{"articleIdentity":"rs-7122919","link":"https://doi.org/10.1186/s12917-026-05322-0","journal":{"identity":"bmc-veterinary-research","isVorOnly":false,"title":"BMC Veterinary Research"},"publishedOn":"2026-02-06 15:59:04","publishedOnDateReadable":"February 6th, 2026"},"versionCreatedAt":"2025-07-23 19:21:18","video":"","vorDoi":"10.1186/s12917-026-05322-0","vorDoiUrl":"https://doi.org/10.1186/s12917-026-05322-0","workflowStages":[]},"version":"v1","identity":"rs-7122919","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7122919","identity":"rs-7122919","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}