Genomic Epidemiology of Fungi Identified in Bronchoalveolar Lavage Fluid from Asthmatic Horses in the US

TL;DR

This study explores how fungi in the airways of asthmatic horses vary by region and how this affects the type of inflammation they experience.

Contribution

The study identifies geographic variations in fungal exposure and their association with specific inflammatory responses in asthmatic horses.

Findings

Fungal community composition and inflammatory cell proportions in horse airways vary significantly by ecoregion.

Alternaria, Aspergillus, Cladosporium, and Epicoccum species show differing abundances across regions.

Geographic differences in fungal exposure may explain regional variations in asthma inflammation types.

Abstract

Asthma is a common cause of respiratory disease and poor performance in horses and can range in severity from occasional coughing and decreased athletic performance to difficulty breathing at rest. Along with variations in severity, different types of inflammation can occur in the lungs of horses with asthma. Fungal exposure, often from moldy hay, has long been known to trigger disease in horses; however, it is not known if exposure to specific types of fungi plays a role in determining the type and severity of disease. Little is known about the variation in airborne fungi encountered by horses in different geographic regions. Analysis of the fungal DNA present within the airways of horses with asthma living in different regions can identify the types of fungi that they are exposed to. In turn, comparisons of the different fungi present in different regions can be made. In addition, this information can help determine which fungi are associated with the various types of asthma in horses. This knowledge can improve asthma prevention and management, provide new targets for research and expand our understanding of the disease processes that lead to asthma in horses.

Fungal exposure is strongly implicated in the pathogenesis of asthma in horses, but the importance of specific fungi is unknown. Geographic variation in equine asthmatic endotypes is suspected and might be related to different fungal exposures due to different climatological and geographical conditions. This study had two objectives: evaluate the effect of the ecoregion upon BALF inflammatory cells and fungal community composition in horses with asthma and evaluate the effect of BALF fungal community composition upon the likelihood of neutrophilic, mastocytic and eosinophilic inflammation in these horses. Differential cytology counts were obtained from 916 BALF samples submitted from horses with poor performance and/or clinical signs of respiratory disease from five ecoregions. The effect of the ecoregion upon BALF inflammatory cell proportions was modeled using generalized linear models. Seventy banked BALF samples were subjected to sequencing of the internal transcribed spacer regions of fungal DNA. Diversity analysis was performed in QIIME, including alpha diversity metrics and the Bray–Curtis dissimilarity metric. After taxonomy was assigned, differential abundances between ecoregions and inflammatory phenotypes were estimated by generalized linear models in DESeq2. BALF neutrophil (p < 0.0001) and eosinophil (p < 0.0001) proportions varied by ecoregion, while mast cell proportions did not (p = 0.18). Alternaria, Aspergillus, Cladosporium and Epicoccum spp. were found to differ in abundance between regions. These geographical variations in fungal exposure might be responsible for differences in BALF neutrophil and eosinophil proportions between ecoregions.

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1. Introduction

Equine asthma is a heterogeneous, multifactorial disease that causes clinical signs that range from mild, occasional coughing and/or decreased performance (mild-to-moderate equine asthma, MEA) to severe respiratory impairment with frequent coughing, increased respiratory effort at rest and exercise intolerance (severe equine asthma, SEA) [1]. SEA affects approximately 14% of horses in Northern temperate climates [2], while MEA affects horses worldwide with a prevalence of up to 90% in racehorses [3,4]. Bronchoalveolar lavage fluid (BALF) cytology is the test of choice to characterize the phenotype and severity of airway inflammation. Horses with SEA exhibit marked airway neutrophilia (>25%), whereas horses with MEA might present mild neutrophilia, mastocytosis, eosinophilia, or any combination thereof [1]. Exposure to environmental dust particles and molds plays a central role in the pathogenesis of the disease [4,5,6]. SEA exacerbations are most commonly associated with stabling and exposure to organic dust from hay [5]. Similarly, evidence suggests that airway neutrophilia in MEA is triggered by exposure to respirable dust and endotoxin, while exposure to molds is associated with an increase in mast cells [4]. There is a lack of agreement between studies regarding the immunological mechanisms between the different cellular phenotypes of MEA [7,8,9], and current mitigation and prevention strategies are hampered by an incomplete understanding of the triggers of disease, particularly in cases of eosinophilic and mastocytic inflammation.

The potential for fungal exposure to trigger airway inflammation in horses with severe asthma has long been recognized [10,11,12,13]. Severe asthma in horses involves hypersensitivity to specific fungal-derived allergens [14,15], prevalence is correlated with total airborne mold counts [16], and inhalation challenge with various fungal extracts has been shown to result in varying degrees of pulmonary inflammation of lung dysfunction in these horses [12,13,17,18,19,20]. However, the relative importance of specific fungal species in triggering and exacerbating severe asthma in horses is incompletely understood.

Fungal exposure is similarly implicated in the development of MEA. Microscopic observation of fungal elements in tracheal wash fluid is associated with an increased risk of MEA diagnosis [6], and BALF mast cell proportions are related to respirable ß-glucan exposure [4]. Horses with MEA have higher concentrations of BALF IgE specific for fungal allergens when compared to healthy horses [21,22].

Targeted next-generation sequencing (tNGS) of the internal transcribed spacer 2 (ITS2) region in the fungal rRNA operon and the 18 s rRNA fungal gene has been used to characterize the fungal communities present in both barn environments and in the respiratory tract of healthy and asthmatic horses. Wallemia sebi, Aspergillus penicillioides and Epicoccum nigrum were the most common fungal species sequenced in airborne dust collected from a single stable in Poland [23]. While Eurotium amstelodami, Wallemia sebi and Aspergillus niger were the dominant species sequenced from the BALF of stabled healthy and severely asthmatic horses in Canada [24], another study found Vishniacozyma victoriae, Mycosphaerella tassiana, Epicoccum dendrobii, Preussia africana and Vishniacozyma carnescens to be the most commonly sequenced fungal species along the length of the respiratory tract of healthy Canadian horses housed at pasture [25]. To date, no study has addressed whether variations in the fungal flora (mycobiota) of the equine airway are related to varying ecologic conditions, though there is clear evidence of the effect of the environment in determining the fungal flora of the respiratory tract [24,26].

North America can be divided broadly into 15 ecological regions based on spatial correlation with climate, vegetation, soil and other factors [27]. Exposure to fungal allergens is a well-known risk factor for asthma in people, and sensitization to certain fungal allergens in people has been linked to particular ecoregions in the US [28]. Differences in fungal exposure across ecoregions are likely to be pertinent in equine populations as well and might play an important role in determining the cytologic response in equine asthma.

Therefore, this study was designed to investigate the geographic variation in asthma phenotypes in horses and to use tNGS of the ITS2 region of fungal DNA in the BALF of horses with MEA to examine fungal community composition across ecoregions and differing cytological diagnoses.

We hypothesized that BALF inflammatory cell proportions would vary between ecoregions. Furthermore, we hypothesized that tNGS sequencing of fungal ITS2 in BALF samples will reveal that fungal community composition varies by ecoregion and that BALF cytological profiles will be associated with particular BALF fungal communities.

2. Materials and Methods

2.1. Samples

Banked supernatants retrieved from BALF samples that were submitted by private equine veterinary practices for cytologic analysis due to poor performance or clinical signs of respiratory disease in horses of various breeds, disciplines and ages were used. Samples were shipped overnight on ice and processed for cytologic analysis immediately upon receipt. Aliquots of BALF were stored at −80 °C until tNGS analysis.

For each sample, an ecoregion was assigned based upon the zip code in which the horse resided, as reported by the referring veterinarian and the map of ecoregions (https://www.cec.org/files/atlas/?z=3&x=-93.1641&y=61.9803&lang=en&layers=terecoreg1&opacities=100&labels=true (accessed on 18 January 2026), Figure 1) [27]. The samples from zip codes containing more than one ecoregion were excluded from further analysis. Differential cytological counts had been previously performed and recorded. Upon receipt, BALF samples were subjected to cytocentrifugation and processed with Modified Wright’s stain. Differential cell counts were performed on 400–600 cells. Based upon reported clinical presentation that included cough, poor performance and/or increased tracheal mucus in addition to cytologic findings that included BALF neutrophil proportions greater than 5%, mast cell proportions >2% and/or eosinophil proportions greater than 1%, all horses included in this analysis met the diagnostic criteria for MEA [1]. In particular, no samples were included from horses with reported increased respiratory efforts at rest, fever, or if intracellular bacteria were observed.

2.2. Statistical Analysis of Cytology Data

The effect of the ecoregion upon BALF inflammatory cell proportions (% neutrophils, % mast cells, % eosinophils) was modeled using generalized linear models controlling for season of sample collection using SAS v. 9.4, (SAS Institute, Cary, NC, USA). Tukey’s method for multiple comparisons was used to control the error rate for pair-wise comparisons, with statistical significance set at p < 0.05.

2.3. NGS of Fungal ITS2 Region

Seventy-two samples were prepared for sequencing. Adequate preservation of samples was ensured by screening for diagnostic quality and timeliness of delivery. From the samples that were deemed to provide good diagnostic quality and had been received within 2 days of sample collection, 14 BALF samples from each ecoregion were randomly selected for sequencing. Two laboratory blanks were prepared in the BALF processing laboratory to control for any sample contamination. The BALF and laboratory blank samples were subjected to NGS of the fungal ITS2 region as follows.

Nucleic acid was extracted from BALF supernatant using the MagMax Core Nucleic Acid Purification Kit (Thermo Fisher Scientific, Waltham, MA, USA), according to the manufacturer’s instructions. The primer set ITS86F/ITS4R [29] was used to amplify a portion of the ITS2, prior to next-generation sequencing. Each PCR reaction was composed of a total volume of 50 μL containing 10 µL of template, 5.0 μL of 10X PCR Buffer (Invitrogen, Carlsbad, CA, USA), 5.0 μL of MgCl_2_ (50 mM), 1.0 μL dNTPs (10 mM), 0.5 μL of Platinum Taq, 26.5 μL of Sterile H_2_O, 1.0 μL of forward primer (100 μM) and 1.0 μL of reverse primer (100 μM). The thermocycler parameters included 1 cycle at 95 °C for 600 s, 25 cycles at 95 °C for 40 s, 55 °C for 120 s and 72 for 60 s and a final extension step at 72 °C for 420 s. Purification of the PCR products was performed according to the manufacturer’s instructions (PureLink PCR Micro Kit, Thermo Fisher Scientific). Purified products were submitted to the Purdue Genomics Core Facility (West Lafayette, IN, USA) for NGS using an Illumina MiSeq (San Diego, CA, USA).

The data files from Illumina reads in fastq format were downloaded and subjected to quality filtering and adapter trimming using Trim Galore (v0.6.10). For downstream analysis, the cleaned fastq files were imported into the QIIME2 software (v.2-2023.9) [30]. Denoising was performed using DADA2 [31], which additionally carried out quality-based trimming, error correction and merging of paired-end reads. Chimeric sequences were subsequently removed using UCHIME [32]. Reads were grouped into operational taxonomic units (OTUs) using distribution-based OTU clustering methods [33]. Consensus blast analysis was performed to identify taxonomic assignments using the “classify-consensus-blast” classification algorithm against the UNITE fungal database [34]. Hits with at least 95% identity with 30% coverage were extracted.

The diversity within each sample (alpha diversity) was measured by the number of observed OTUs, Shannon index and Simpson index, calculated using the QIIME “alpha-rarefaction” command. The effect of the ecoregion upon the Shannon index and Fath’s phylogenetic diversity was evaluated by the Kruskal–Wallis test. Fungal communities were compared between samples using the QIIME “beta-diversity” command. The Bray–Curtis dissimilarity metric was used to generate a distance matrix, which was then visualized with PCoA plots. PERMANOVA of weighted UniFrac distances was used to determine the statistical significance of the effect of the ecoregion upon phylogenetic diversity of the samples. Pair-wise differences were considered significant at a p-value (q-value) < 0.05. Differential abundance analysis was performed on the 10 pair-wise comparisons of the 5 ecoregions by comparing the abundance of specific OTUs. Enhanced volcano plots were generated based upon a false discovery rate ≤ 0.05 and a log 2-fold change ≥ or ≤±2. DESeq2 was also applied to identify taxa significant differential abundance between horses with neutrophilic inflammation (>5% neutrophils) and those without, horses with mastocytic inflammation (>2% mast cells) and those without and horses with eosinophilic inflammation (>1% eosinophils) and those without at the OTU and Genus levels. Log2-fold changes were estimated by generalized linear models in DESeq2. At the genus level, 95% confidence intervals were calculated using LFcSE [35,36], and adjusted p-values were calculated using the Benjamini–Hochberg false discovery rate method.

3. Results

3.1. Samples

One thousand forty-five diagnostic BALF samples from asthmatic horses of various breeds and disciplines were submitted between June 2018 and December 2022. The ecoregion could not be determined based on zip code for 129 samples, leaving 916 samples for further analysis. Quarter Horse was the most frequent breed represented (n = 660), followed by various warmblood breeds (n = 97) and Thoroughbreds (n = 20). Barrel racing was the most common discipline reported (n = 378). Discipline was not reported for 232 samples. Hunt seat and/or show jumping (n = 41), pleasure riding (n = 34) and dressage (n = 30) were the next most frequently reported uses for the horses sampled.

Six ecoregions of North America were represented, including Northern Forests (Ecoregion 5, n = 26), Northwestern Forested Mountains (Ecoregion 6, n = 5), Eastern Temperate Forests (Ecoregion 8, n = 243), Great Plains (Ecoregion 9, n = 516), North American Desserts (Ecoregion 10, n = 29), Mediterranean California (Ecoregion 11, n = 95), Southern Semi-Arid Highlands (Ecoregion 12, n = 1) and Tropical Wet Forests (Ecoregion 15, n = 1). Due to the sparsity of samples, Ecoregions 6, 12 and 15 were excluded from further analysis.

3.2. Effect of Ecoregion on BALF Cytology

Ecoregion and season significantly affected neutrophil (p < 0.0001 and p < 0.0001, respectively, Figure 2A and Figure 3A) and eosinophil (p < 0.0001 and p < 0.0001, respectively, Figure 2C and Figure 3C) proportions. Mast cell proportions did not vary with ecoregion or season (p = 0.18 and p = 0.68, respectively, Figure 2B and Figure 3B).

3.3. NGS of Fungal ITS2 Region

3.3.1. BALF Samples

Nucleic acid was extracted from 70 BALF samples (14 samples from each ecoregion) along with two laboratory blanks, and the targeted region of the ITS2 was amplified. Two samples from each region had minimal amplification upon PCR. Therefore, twelve samples from each region and two blanks were subjected to tNGS of the ITS2 fungal region (Supplemental Table S1). One sample from Mediterranean California and one sample from the Great Plains were excluded from further analysis due to low read counts. One blank sample had 65,305 non-chimeric sequencing reads after filtering. After denoising, removal of chimeric sequences and filtering out the OTUs with more than 100 reads in the blank sample, 34,863 OTUs were identified for further analysis.

3.3.2. Alpha Diversity

Neither the Shannon index (p = 0.0576, Figure 4) nor Faith’s phylogenetic alpha diversity index (p = 0.1925, Figure 5) varied by ecoregion.

3.3.3. Beta Diversity

PERMANOVA of weighted UniFrac distances indicated a statistically significant effect of ecoregion upon beta diversity (p = 0.045). However, no statistically significant pair-wise comparisons of beta diversity were found (p > 0.1, Figure 6).

3.3.4. Differential Abundance

BALF samples from Mediterranean California had a lower abundance of Cladosporium spp. and a higher abundance of Alternaria spp. than those from the Northern Forest, Great Plains and Eastern Temperate Forests regions. Samples from the Northern Forests region had a lower abundance of Alternaria spp. and a higher abundance of Aspergillus spp. than samples from the North American Deserts, Eastern Temperate Forests and Great Plains ecoregions. Samples from the North American Deserts ecoregion had a lower abundance of Epicoccum spp. and a higher abundance of Alternaria spp. relative to the Eastern Temperate Forests and Great Plains regions. Finally, the Eastern Temperate Forests BALF samples had a lower abundance of Epicoccum spp. and Alternaria spp. and a higher abundance of Cladosporium spp. than those from the Great Plains ecoregion (Figure 7).

When differential abundance was examined by asthma inflammatory phenotype, Aspergillus, Penicillium, Rhodotorula and Saccharomyces spp. were significantly more abundant in horses with neutrophilic inflammation. Additionally, sequences assigned to the order Wallemiales were more abundant in horses with neutrophilic inflammation and less abundant in those with mastocytic or eosinophilic inflammation. Aspergillus spp. were underexpressed in those with mastocytic inflammation. Rhodotorula spp. were underexpressed in horses with mastocytic inflammation and horses with eosinophilic inflammation, while Saccharomyces spp. were more abundant in horses with eosinophilic inflammation than those without. Epicoccum spp. were more abundant in both mastocytic and eosinophilic inflammation and significantly less abundant in cases of neutrophilic inflammation (Figure 8).

4. Discussion

We found that BAL neutrophil and eosinophil proportions differed by ecoregion and season, while BAL mast cell proportions did not. Ecoregions are defined by unique climatologic features such as temperature and humidity, flora, fauna and geographical features [27] that would be expected to influence the ambient particulate matter, including airborne fungal spores and other fungal elements. Therefore, we hypothesized that BALF inflammatory cell proportions of horses with asthma would vary depending on the ecoregion of residence. Because some ecoregion features (temperature, humidity and vegetation), along with fungal abundance, also vary with season, the effect of the season was included in the generalized linear models of inflammatory cell proportions. However, a great number of other potential confounders unrelated to ecology are known to affect BALF inflammatory cell proportions in horses, including genetic susceptibility, horse husbandry practices, dietary factors and variations in BAL techniques. Failure to control for these potential confounders should be considered when interpreting these results. In particular, differences in bedding and forage likely exist between ecoregions and might therefore play a key role in the differences observed in this study.

BALF from the Northern Forests region (ecoregion 5) and Eastern Temperate Forests region (ecoregion 8) had the highest neutrophil proportions and, along with Mediterranean California (ecoregion 11), the lowest eosinophil proportions. BALF from the North American Deserts region (ecoregion 10) and the Great Plains region (ecoregion 9) had the highest eosinophil proportions. While statistically significant, seasonal variation in neutrophil and eosinophil proportions was of a smaller magnitude than variation due to ecoregions. These findings are in general agreement with a retrospective report comparing the BALF cytologies of horses from the eastern United States to those in the western United States [37]. Higher BALF neutrophil proportions and lower eosinophil proportions were reported in horses in the eastern states, which included ecoregions 5 and 8, than those in the western states, which potentially included horses from ecoregions 6, 9, 10, 11, 12 and 13. Similarly to findings in the current study, mast cell proportions did not vary between east and west. The same report found that fungal elements were more frequently observed in samples from horses in the eastern United States [37].

Alpha diversity, a measure of the diversity as determined by the abundance and phylogeny of the sequences present within a given sample, did not vary between ecoregions. Neither the Shannon index, a metric of richness and evenness in the sequences present, nor the Faith index, a measure of the phylogenetic distance between sequenced organisms within the sample [38], differed significantly between the regions examined. Likewise, beta diversity, which summarizes the difference in abundance and phylogeny of sequences between samples, did not differ in any pair-wise comparisons between ecoregions.

While there was minimal evidence of differences in alpha or beta diversity between ecoregions, the differential abundance of specific genera between ecoregions was apparent. The abundance of Cladosporium, Alternaria, Aspergillus and Epicoccum spp. showed significant variation between ecoregions. Epicoccum, Cladosporium and Alternaria sensitization rates in people have also been found to vary by ecoregion [24]. Similarly, ITS sequencing of BAL from people with asthma and healthy controls revealed no difference in indices of neither alpha nor beta diversity, but found Cladosporium, Alternaria and Aspergillus to be among seven genera most strongly associated with a diagnosis of asthma as well as such clinical parameters as corticosteroid use and forced expiratory volume in 1 s (FEV1) [39].

A 2015 systematic review found that the homes of asthmatic patients had higher concentrations of Cladosporium, Alternaria and Aspergillus, and higher concentrations were associated with increased asthma exacerbations in both adults and children [40]. Cladosporium sensitization is associated with asthma severity in inner-city adults; however, a negative correlation was found between Cladosporium sensitization and asthma severity in inner-city children [41]. This finding is in contrast to the results of a prospective cohort study in Pennsylvania, which found that increased Cladosporium spore concentrations were associated with decreased peak expiratory flow rates in fourth- and fifth-grade schoolchildren [42]. Ambient Alternaria and Cladosporium spore counts are associated with increased reports of asthma symptoms in both adult and pediatric asthma patients in California [43]. Similarly, monthly ambient Alternaria and Cladosporium spore counts are associated with monthly prevalence of severe asthma diagnoses in horses presented to veterinary teaching hospitals [16].

Aspergillus exposure and sensitization have been implicated in the development and exacerbation of asthma in human and horse patients alike. In adults with asthma, the demonstration of Aspergillus fumigatus-specific IgE is associated with neutrophilic inflammation and reduced lung function [44], and Aspergillus sensitization in general is associated with increased corticosteroid use and more frequent exacerbations [45]. Similarly, Aspergillus fumigatus-specific antibodies are higher in the BAL of horses with severe asthma compared to healthy controls [21,46], as are Aspergillus fumigatus-specific Th17 cells [47]. In parallel, Th17 cells are key to neutrophilic inflammation in human patients with severe asthma associated with a poor response to therapy and increased corticosteroid use [48]. Horses with severe asthma develop profound neutrophilic airway inflammation upon disease exacerbation associated with exposure to moldy hay and develop both neutrophilic airway inflammation and deranged lung function upon inhalation challenge with Aspergillus fumigatus extracts [19]. Similarly, horses with severe asthma develop lung dysfunction and airway neutrophilia when challenged with a mixture of microspheres, endotoxin and Aspergillus fumigatus, Eurotium amstelodami and Lichthemia corymbifera spores, while control horses responded to this challenge with modest airway neutrophilia but no changes in lung function [20]. In the current study, Aspergillus was more abundant in horses with neutrophilic inflammation, further supporting its potential role in triggering neutrophilic asthma.

Wallemia is the single genus contained in the order Wallemiales, sequences from which were overexpressed in horses with neutrophilic asthma and underexpressed in horses with mastocytic or eosinophilic inflammation. Wallemia spp. are well recognized as important food contaminants and have been found in both agricultural and indoor environmental dusts and notably release spores small enough to easily penetrate deep within the lung [49]. W. sebi is among the fungal species identified as the probable causative agents in the pathogenesis of Farmer’s Lung in France and Finland [50,51]. W. sebi was the most prevalent species sequenced from airborne particulate matter collected in Polish horse barns, and along with Eurotium amstelodami and Aspergillus niger, W. sebi was significantly increased in the BAL of horses after stabling [24].

Penicillium, Rhodototula and Saccharomyces spp. were also more abundant in horses with neutrophilic inflammation. In human patients, poor asthma control has been associated with sensitization to Aspergillus and Penicillium [52]. Risk of wheeze and persistent cough was increased for infants in homes with high concentrations of Penicillium [53]. Similarly, the detection of Penicillium in the home is associated with an increased risk of high peak expiratory flow variability, an indication of poor disease control, in children with asthma [54]. Furthermore, indoor levels of Penicillium are associated with frequency of asthma symptoms in children [55]. Along with Aspergillus and Cladosporium, exposure to Penicillium poses a significant risk for the development of asthma in susceptible human populations, as well as exacerbation of symptoms in patients previously diagnosed with asthma [40].

Rhodotorula is a ubiquitous saprophytic yeast recently identified as an opportunistic pathogen [56,57]. Similarly to the findings of this study, ITS sequencing of induced sputum from patients with asthma or chronic obstructive pulmonary disorder (COPD) revealed enrichment of Rhodotorula spp. in patients with neutrophilic inflammation compared to those with eosinophilic inflammation, regardless of disease [58]. In that study, fungal communities varied by type of inflammation rather than by disease, further suggesting that the pulmonary inflammatory response is not merely determined by the overall severity of fungal exposure, but might also be influenced by the specific fungi present in the environment.

The identification of Saccharomyces as a genus enriched in the BAL of horses with neutrophilic and eosinophilic asthma is surprising. The genus contains such species as S. cerevisiae, which is widely used in the making of bread and beer. Saccharomyces is also used as a probiotic and has even been investigated for its potential to prevent or mitigate asthma. Only sporadic cases of asthma associated with hypersensitivity to Saccharomyces cerevisiae have been reported [59,60].

Information on the role of Epicoccum in the pathogenesis of asthma is sparse. Epicoccum spores are found more frequently and at higher concentrations in homes in which children with asthma reside when compared to homes with no asthmatic children [61]. The previously mentioned cohort study of children in Pennsylvania documented an increased incidence of morning cough reported when ambient Epicoccum spore counts were increased [42]. Cross-reactivity between Epicoccum and Alternaria antigens exists [62], and Epicoccum and Alternaria were both underexpressed in horses with neutrophilic asthma in this study. Similarly, ambient Epicoccum spore counts do not correlate with the diagnosis of severe asthma in horses, which is characterized by severe neutrophilic inflammation [16].

In the current study, Epicoccum, along with a sequence from the order Pleosporales, was more abundant in the BALF of horses with eosinophilic and mastocytic inflammation. While eosinophilic inflammation was found to vary by ecoregion, mast cell inflammation did not, suggesting that mast cell inflammation might be driven by factors unrelated to geographical and climatological variation. In horses, BALF mast cell proportions have been found to increase with increasing respirable β-glucan exposure [4], indicating that the overall magnitude of fungal exposure might be the main factor in determining the severity of airway mast cell inflammation. β-glucan, a component of fungal cell walls, acts as a pathogen-associated molecular pattern recognized by Dectin-1 receptors, which are highly expressed by dendritic cells and alveolar macrophages [63], and to a lesser extent, by mast cells [64]. The presence of Dectin-1 receptors on bronchial epithelial cells and macrophages in the equine lung has been documented, and dectin-1 expression was found to increase with stabling [24]. Murine models have demonstrated that, upon binding of β-glucan by Dectin-1 receptors, dendritic cells stimulate the differentiation of Th9 cells and production of IL-9 [65], which is necessary for mast cell proliferation and recruitment to the lung [66,67,68]. Though yet to be documented in the horse, this pathway is a possible explanation for the observed dose effect of respirable β-glucan exposure in horses.

This study is limited by the fact that no healthy horses were included in the analysis. All the horses included were presented for signs of respiratory disease and/or poor performance. Additionally, only relative abundances of fungal genera were compared. Quantitative analysis of fungal load, as well as comparisons with horses free of respiratory disease, will be important to further refine fungal risk factors for specific asthma endotypes. Application of environmental sampling techniques will be needed to determine the source of exposure to the different fungal genera, e.g., ambient air versus hay, before the design of any specific mitigation strategies. Finally, this retrospective analysis can only offer the observed associations between ecoregion, inflammation and specific fungal genera and provides no direct evidence of causation.

5. Conclusions

This study identifies fungal genera of potential importance in triggering asthmatic inflammation in horses, particularly in the ecoregions included, and highlights similarities in the factors that are associated with differing asthma phenotypes in horses and humans. These similarities support the hypothesis that specific fungi direct the pulmonary inflammatory response via unique molecular signatures presented upon inhalation exposure: inhaled spores and fragments damage the respiratory epithelium and present allergens, other proteins and bioactive molecules that interact with pathogen-associated molecular pattern receptors to influence both the cytologic response and the severity of that response [63].