Respiratory viral infections have been associated with an increased incidence of allergic asthma. However, the mechanisms by which respiratory infections facilitate allergic airway disease are incompletely understood. We previously showed that exposure to a low dose of house dust mite (HDM) resulted in enhanced HDM-mediated allergic airway inflammation, and, importantly, marked airway hyperreactivity only when allergen exposure occurred during an acute influenza A infection. In this study, we evaluated the impact of concurrent influenza infection and allergen exposure at the genomic level, using whole-genome microarray. Our data showed that, in contrast to exposure to a low dose of HDM, influenza A infection led to a dramatic increase in gene expression, particularly of TLRs, C-type lectin receptors, several complement components, as well as FcεR1. Additionally, we observed increased expression of a number of genes encoding chemokines and cytokines associated with the recruitment of proinflammatory cells. Moreover, HDM exposure in the context of an influenza A infection resulted in the induction of unique genes, including calgranulin A (S100a8), an endogenous damage-associated molecular pattern and TLR4 agonist. In addition, we observed significantly increased expression of serum amyloid A (Saa3) and serine protease inhibitor 3n (Serpina3n). This study showed that influenza infection markedly increased the expression of multiple gene classes capable of sensing allergens and amplifying the ensuing immune-inflammatory response. We propose that influenza A infection primes the lung environment in such a way as to lower the threshold of allergen responsiveness, thus facilitating the emergence of a clinically significant allergic phenotype.

Allergic asthma is a chronic immune-inflammatory disease of the airways that occurs following sensitization to common aeroallergens, such as house dust mite (HDM), the most ubiquitous indoor aeroallergen worldwide. However, despite universal exposure, only ∼20% of the population develops the disease (1). This suggests that the natural response to allergens is immunologic homeostasis and that additional factors contribute to triggering aberrant immune responses to these allergens (2). In addition to a genetic predisposition, environmental factors, such as respiratory viral infections, have been implicated with the clinical expression of allergic airway inflammation (3, 4). In this regard, there is abundant evidence in humans of an association between viral infections and the expression of asthma (5, 6). In mice, we previously reported that exposure to a concentration of HDM, which by itself elicits negligible airway inflammation and no changes in lung function, results in a phenotype characterized by robust allergic airway inflammation, enhanced mucus production, and marked lung dysfunction in the context of an acute influenza A virus (Flu) infection (7).

In this study, we used genome-wide transcriptional profiling to investigate the nature of the Flu-induced environment in the lung, by examining global gene expression during the early phase (EP; 4 d) and late phase (LP; 7 d) of HDM exposure. We found that exposure to a low concentration of HDM alone elicited minimal alterations in the gene profile, whereas Flu infection led to a pervasive upregulation of genes associated with the general response to stimuli and stress. In particular, Flu infection dramatically increased the expression of a number of cell surface receptors, notably TLRs, C-type lectin receptors (CLRs), and FcRs, and a prolific number of chemokines and chemokine receptors. Interestingly, exposure to HDM in the context of this Flu-induced environment led to the increased expression of several hundred genes, which were not expressed in mice exposed to allergen alone. These data suggested that Flu lowered the threshold of HDM responsiveness by establishing a global, heightened state of immune sensing in the lung and launching multiple pathways involved in inflammatory responses to exogenous Ags.

Female BALB/c mice (6–8 wk old) were purchased from Charles River Laboratories (Saint-Constant, QC, Canada). The mice were housed under specific pathogen-free conditions and maintained on a 12-h light-dark cycle, with food and water ad libitum. All experiments described in this study were approved by the Animal Research Ethics Board of McMaster University.

Flu strain A/PR/8/34 (H1N1) was prepared, as described previously (8), and kindly provided by MedImmune. The viral stock suspension (109 PFU/ml) was diluted, and 10 PFU was administered intranasally to isoflurane-anesthetized BALB/c mice in 35 μl sterile PBS solution. Animals were monitored for signs of illness twice daily for 10 d following infection.

Allergen administration.

HDM extract (Greer Laboratories, Lenoir, NC) was resuspended in sterile PBS at a concentration of 0.5 mg (protein)/ml, and 10 μl (5-μg dose) was administered to isoflurane-anesthetized mice intranasally. Groups of mice were infected with Flu or exposed to PBS. Seven days later, separate groups of mice were exposed to saline or HDM for 3 or 6 d, and lungs were harvested 24 h after the last exposure, at day 4 (EP) or day 7 (LP) (Fig. 1).

FIGURE 1.

Experimental plan. AD, Separate groups of mice were infected with Flu or exposed to PBS. Seven days later, mice were either exposed to saline or HDM for 10 d, resulting in four treatment groups: PBS (A), HDM (B), Flu (C), and Flu+HDM (D) (7). Lungs were harvested, and RNA was isolated 24 h after the third or sixth dose of HDM at day 4 or 7, representing the EP or LP response, respectively.

FIGURE 1.

Experimental plan. AD, Separate groups of mice were infected with Flu or exposed to PBS. Seven days later, mice were either exposed to saline or HDM for 10 d, resulting in four treatment groups: PBS (A), HDM (B), Flu (C), and Flu+HDM (D) (7). Lungs were harvested, and RNA was isolated 24 h after the third or sixth dose of HDM at day 4 or 7, representing the EP or LP response, respectively.

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Lungs were harvested 24 h after the last allergen challenge, snap-frozen in liquid nitrogen, and stored at −80°C until further processing. Total RNA was extracted using RNA-STAT60 reagent (Tel-Test, Friendwood, TX), as per the manufacturer’s protocol. The extracted total RNA was further purified using an RNeasy Mini Kit (QIAGEN, Valencia, CA), and quality was assessed with the Agilent Bioanalyzer 2100 (Agilent Technologies, Santa Clara, CA). Preparation of wild-type sense cDNA targets, hybridization to Affymetrix Mouse Gene 1.0 ST arrays (Affymetrix, Santa Clara, CA), and scanning were performed according to standard Affymetrix protocols. In brief, 100 ng total RNA from each sample was used for the synthesis of dsDNA with random hexamers tagged with a T7 promoter sequence. The double-stranded cDNA was subsequently used as template and amplified by T7 RNA polymerase, producing many copies of antisense cRNA. In the second cycle of cDNA synthesis, random hexamers were used to prime reverse transcription of the cRNA from the first cycle to produce ssDNA in the sense orientation with incorporated deoxyuridine triphosphate. Fragmentation of the ssDNA was performed using a combination of uracil DNA glycosylase and apurinic/apyramidine endonuclease 1 that breaks DNA at deoxyuridine triphosphate residues. Labeling of fragmented DNA by terminal deoxynucleotidyl transferase with the Affymetrix DNA labeling reagent covalently linked to biotin was used in the final step of target preparation. Fragmented and biotin-labeled cDNA was hybridized at 45°C for 17 h to Affymetrix Mouse Gene 1.0 ST arrays. The arrays were washed and stained with streptavidin-PE, followed by signal amplification with a biotinylated anti-streptavidin Ab. The arrays were scanned according to the manufacturer’s instructions.

Gene-expression measurements were generated from quantified Affymetrix image files (“*CEL” files) using the robust multiarray analysis algorithm (9) and GeneSpring 10.0 software (Agilent Technologies). All 21 CEL files were analyzed simultaneously with quantile normalization and median polish probe summarization using the PBS samples as a baseline (control). Transcripts with expression levels in the first quantile were filtered out to remove noise from downstream statistical analyses. One-way ANOVA was applied to the filtered and log2-transformed probe sets. A Tukey post hoc test was applied successively to identify transcripts with a statistically significant expression among the treatment groups. Genes were defined as differentially expressed if they had fold changes of at least ±1.5, with p values ≤ 0.05. This selection criterion includes the maximum number of differentially expressed genes used to identify biologically relevant gene families and pathways. Functional annotations of the differentially expressed genes were identified using NetAffx (Affymetrix) and the Database for Annotation, Visualization and Integrated Discovery (DAVID) v6.7 (10, 11). Gene ontology (GO) analysis of the differentially expressed genes was performed using GoMiner software (12), and GO biological processes that had a Fisher exact p value < 0.05 (false discovery rate corrected; p < 0.05) were considered significantly enriched. Microarray data files from this study are available at European Molecular Biology Laboratory-European Bioinformatics Institute ArrayExpress database (http://www.ebi.ac.uk/microarray-as/ae). ArrayExpress accession number for these files is E-MEXP-3325.

RNA was quantified and normalized, and RNA integrity was assessed by Agilent Bioanalyzer. cDNA was generated using the Super Script III Reverse Transcriptase kit (Life Technologies, Carlsbad, CA), according to the manufacturer’s instructions. Relative transcript expression assay was conducted, as described previously (13), using the Fluidigm Biomark system (Fluidigm, San Francisco, CA). BestKeeper (version 1) (14) was used to identify the stably expressed housekeeping gene to be used as an internal reference. Among the four housekeeping genes, β-actin (Actb), β-2-microglobulin (B2m), Gapdh, and hypoxanthine phosphoribosyltransferase 1 (Hprt1), Hprt1 emerged as the most stably expressed and, thus, was selected for normalizing genes of interest. Data analysis of cycle threshold values was conducted using the Relative Expression Software Tool-384 (REST-384) version 1, and the pair-wise fixed reallocation randomization test was performed to determine the fold changes and statistical significance (15).

To investigate the global impact of exposure to a low dose of HDM, Flu, and HDM in the context of Flu infection (Flu+HDM) on gene-expression profiles (Fig. 1), we conducted a principal component analysis, which allows visualization of the effects of multiple treatments on gene-expression profiles. To this end, the analysis included all genes from all arrays without any prior filtering. Our analysis revealed the differential effects of HDM exposure, Flu infection, or Flu+HDM coexposure, during the EP and LP of the response, on gene expression by placing them along the planes of the x-, y-, and z-axes (Fig. 2). Our data showed that EP and LP HDM treatment falls in close proximity to the PBS control group along the x- and z-axes, thus suggesting that exposure to such a low dose of HDM (5 μg) for 3 or 6 d had only minimal effects on gene expression. In contrast, Flu LP and Flu+HDM LP groups clustered together along the y-axis, farthest from the xz plane; similarly, the expression profile during the EP of Flu and Flu+HDM clustered together along the yz plane, indicating that Flu infection and Flu+HDM coexposure during EP or LP had similar effects on lung gene-expression profiles, which is distinct from that observed in the lungs of mice exposed to PBS or HDM. Interestingly, the genes expressed during the EP in Flu and Flu+HDM groups were clustered apart from those expressed during the LP, highlighting the impact of time on gene expression in these two treatment groups.

FIGURE 2.

Principal component analysis evaluating the impact of treatment and time on gene expression. Separate groups of mice were either infected with Flu or exposed to PBS; 7 d later, they were exposed to 5 μg HDM or treated with saline for 3 or 6 d. Gene-expression profiles were evaluated 24 h after the last exposure, at day 4 (EP) or 7 (LP) (n = 3 mice/group).

FIGURE 2.

Principal component analysis evaluating the impact of treatment and time on gene expression. Separate groups of mice were either infected with Flu or exposed to PBS; 7 d later, they were exposed to 5 μg HDM or treated with saline for 3 or 6 d. Gene-expression profiles were evaluated 24 h after the last exposure, at day 4 (EP) or 7 (LP) (n = 3 mice/group).

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To quantify the number of genes differentially regulated in response to HDM, Flu, or Flu+HDM, each individual treatment group was compared with PBS controls. Genes with a differential regulation of at least ±1.5-fold changes (p ≤ 0.05) were considered statistically significant. Using this selection criterion, we identified a total of 51 differentially expressed genes in mice exposed to HDM only during the EP (Fig. 3A). In contrast, we identified a total of 1443 genes in mice infected with Flu only at the same time point. Exposure to Flu+HDM led to the regulation of a total of 1592 genes compared with PBS controls. However, a majority of the genes regulated in the Flu+HDM group (1235 genes) were also expressed in mice infected with Flu only (common genes), whereas 330 genes were only expressed in the Flu+HDM group. Heretofore, we refer to these 330 genes as “unique genes” (Fig. 3A). During the LP of the response, representing the time point at which Flu infection enters into the resolving phase (i.e., 14 d after the initial infection), the number of differentially expressed genes was reduced to 1378 in the Flu-only group and 1362 in the Flu+HDM-treated group. In addition, during the LP, Flu and Flu+HDM groups shared 1038 genes, whereas a total of 240 genes was uniquely expressed in the Flu+HDM group (Fig. 3B).

FIGURE 3.

Venn analysis of differentially expressed genes. Separate groups of mice were either infected with Flu or exposed to PBS; 7 d postinfection, they were either exposed to 5 μg HDM or saline treated for 3 or 6 d. Gene-expression profiles were evaluated 24 h after the last exposure, at day 4 (EP) or 7 (LP). Venn diagram showing number of common and unique genes expressed following Flu, HDM, and Flu+HDM treatment during EP (A) and LP (B) (n = 3 mice/group). Genes were filtered based on fold change (≥1.5). p < 0.05, one-way ANOVA, Tukey post hoc test.

FIGURE 3.

Venn analysis of differentially expressed genes. Separate groups of mice were either infected with Flu or exposed to PBS; 7 d postinfection, they were either exposed to 5 μg HDM or saline treated for 3 or 6 d. Gene-expression profiles were evaluated 24 h after the last exposure, at day 4 (EP) or 7 (LP). Venn diagram showing number of common and unique genes expressed following Flu, HDM, and Flu+HDM treatment during EP (A) and LP (B) (n = 3 mice/group). Genes were filtered based on fold change (≥1.5). p < 0.05, one-way ANOVA, Tukey post hoc test.

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To gain an appreciation of the various functions associated with the dramatic increase in differentially expressed genes following Flu and Flu+HDM exposure, we next performed a GO analysis and compared the biological profiles between these two groups (Fig. 4). Our data showed that, during both the EP and LP of the response, Flu- and Flu+HDM-treated mice have similar profiles with respect to various GO biological processes (Fig. 4). Interestingly, at least five of these GO processes, including “response to stimulus” (GO:0050896), “response to stress” (GO:0006950), “response to wounding” (GO:0009611), “inflammatory response” (GO:0006954), and “chemotaxis” (GO:0006935) were enriched with a greater number of genes in the Flu+HDM-treated group compared with the Flu-alone–treated group in both EP and LP; specifically, the “response to stimulus” process was enriched with 265 and 218 genes during EP and LP, respectively, in mice infected with Flu only, whereas in the Flu+HDM group this same process was enriched with 283 (EP) and 243 (LP) genes. To gain greater insight into the biological significance of these diverse processes, we identified specific genes associated with these functional groups. Our analysis revealed that these biological processes are associated with the expression of genes encoding complement components and their receptors (Table I) or various C-type lectins (including CLRs), FcRs, and TLRs (Table II). In addition, we identified genes encoding chemokines and chemokine receptors (Table III), as well as various cytokines and cytokine receptors (Table IV). The majority of these genes was found to be upregulated in both Flu and Flu+HDM groups, during both the EP and LP responses.

FIGURE 4.

GO biological processes in mice infected with Flu and exposed to HDM. GO biological processes enriched with genes from Flu and Flu+HDM during EP (A) and LP (B) response. Numbers in parentheses represent the number of genes enriching each process (n = 3 mice/group). p < 0.05, Fisher exact test (false discovery rate corrected).

FIGURE 4.

GO biological processes in mice infected with Flu and exposed to HDM. GO biological processes enriched with genes from Flu and Flu+HDM during EP (A) and LP (B) response. Numbers in parentheses represent the number of genes enriching each process (n = 3 mice/group). p < 0.05, Fisher exact test (false discovery rate corrected).

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Table I.
Differentially expressed genes associated with complement pathway during EP and LP responses after exposure to HDM, Flu, or Flu+HDM
EP
LP
Gene SymbolGene NameHDMFluF+HHDMFluF+H
C3ar1 Complement component 3a receptor 1 – 8.66 8.71 1.56 4.47 3.71 
C1qc Complement component 1, q C chain – 5.73 6.59 – 5.46 4.70 
C1qb Complement component 1, q, β polypeptide – 6.11 5.67 1.53 4.30 4.52 
C1qa Complement component 1, q, α polypeptide – 5.17 4.91 – 4.26 3.76 
Cfb Complement factor B −1.52 3.55 3.68 – – 1.69 
C5ar1 Complement component 5a receptor 1 – – 1.89 – – – 
C1rb Complement component 1, r – 1.74 1.88 – – – 
C4b|C4a Complement component 4B /4A – 1.70 1.80 – – – 
C1s Complement component 1, s – 2.36 1.80 – – – 
C2 Complement component 2 (within H-2S) – – 1.78 – – – 
C1qbp Complement component 1, q binding protein – – 1.59 – 1.84 1.79 
C1r Complement component 1, r – – 1.56 – – – 
Cr2 Complement receptor 2 – – −1.68 – – – 
C1qtnf7 C1q and TNF related protein 7 – −1.71 −2.16 – −1.72 −1.67 
Cfd Complement factor D (adipsin) – −2.12 −2.38 −2.78 −1.60 −2.12 
C7 Complement component 7 – – – – −2.24 −1.75 
C3 Complement component 3 – 1.51 – 1.74 – 1.55 
Cfh Complement component factor h – – – – −1.83 – 
EP
LP
Gene SymbolGene NameHDMFluF+HHDMFluF+H
C3ar1 Complement component 3a receptor 1 – 8.66 8.71 1.56 4.47 3.71 
C1qc Complement component 1, q C chain – 5.73 6.59 – 5.46 4.70 
C1qb Complement component 1, q, β polypeptide – 6.11 5.67 1.53 4.30 4.52 
C1qa Complement component 1, q, α polypeptide – 5.17 4.91 – 4.26 3.76 
Cfb Complement factor B −1.52 3.55 3.68 – – 1.69 
C5ar1 Complement component 5a receptor 1 – – 1.89 – – – 
C1rb Complement component 1, r – 1.74 1.88 – – – 
C4b|C4a Complement component 4B /4A – 1.70 1.80 – – – 
C1s Complement component 1, s – 2.36 1.80 – – – 
C2 Complement component 2 (within H-2S) – – 1.78 – – – 
C1qbp Complement component 1, q binding protein – – 1.59 – 1.84 1.79 
C1r Complement component 1, r – – 1.56 – – – 
Cr2 Complement receptor 2 – – −1.68 – – – 
C1qtnf7 C1q and TNF related protein 7 – −1.71 −2.16 – −1.72 −1.67 
Cfd Complement factor D (adipsin) – −2.12 −2.38 −2.78 −1.60 −2.12 
C7 Complement component 7 – – – – −2.24 −1.75 
C3 Complement component 3 – 1.51 – 1.74 – 1.55 
Cfh Complement component factor h – – – – −1.83 – 

Values represent mean fold changes compared with PBS (n = 3 mice/group).

p < 0.05, one-way ANOVA, Tukey post hoc test.

–, Genes that showed no significant regulation in that treatment group; F+H, Flu+HDM.

Table II.
Differential expression of genes encoding cell surface receptors during EP and LP responses after exposure to HDM, Flu, or Flu+HDM
EP
LP
Gene SymbolGene NameHDMFluF+HHDMFluF+H
C-Type Lectins
Clec12a C-type lectin domain family 12, a – 5.56 4.48 – 2.74 2.81 
Clec5a C-type lectin domain family 5, a – 4.34 4.11 – 2.93 3.75 
Clec4a2 C-type lectin domain family 4, a2 – 2.74 3.03 – 1.66 1.81 
Clec4a1 C-type lectin domain family 4, a1 – 4.23 2.95 – 1.75 1.97 
Clec4a3 C-type lectin domain family 4, a3 – 3.81 2.54 1.63 1.79 1.75 
Clec4d C-type lectin domain family 4, d – 2.07 2.39 – 1.84 2.38 
Clec4n C-type lectin domain family 4, n – 2.39 2.10 – 2.81 3.45 
Clec7a C-type lectin domain family 7, a – 2.63 1.77 – 2.49 2.99 
Clec14a C-type lectin domain family 14, a – −2.92 −3.07 – −4.26 −3.74 
Clec1a C-type lectin domain family 1, a −1.86 −2.09 – −2.59 −2.23 – 
FcRs
Fcgr4 FcR, IgG, low affinity IV – 8.10 8.18 – 2.68 2.56 
Fcgr1 FcR, IgG, high affinity I – 5.42 6.24 – 2.37 2.30 
Fcer1g FcR, IgE, high affinity I, γ – 3.17 3.80 – 2.44 2.25 
Fcgr2b FcR, IgG, low affinity IIb – 3.14 3.17 2.12 2.43 3.88 
Fcgr3 FcR, IgG, low affinity III – 2.60 2.26 – 2.04 2.09 
Fcer2a FcR, IgE, low affinity II, α – −1.51 −2.20 – – – 
TLRs
Tlr13 TLR13 – 3.40 3.70 – 2.05 2.41 
Tlr2 TLR2 – 2.02 2.10 – – – 
Tlr7 TLR7 – 1.81 1.91 – – – 
Tlr1 TLR1 – 2.15 1.80 – – – 
Tlr8 TLR8 – 1.88 1.77 – – – 
EP
LP
Gene SymbolGene NameHDMFluF+HHDMFluF+H
C-Type Lectins
Clec12a C-type lectin domain family 12, a – 5.56 4.48 – 2.74 2.81 
Clec5a C-type lectin domain family 5, a – 4.34 4.11 – 2.93 3.75 
Clec4a2 C-type lectin domain family 4, a2 – 2.74 3.03 – 1.66 1.81 
Clec4a1 C-type lectin domain family 4, a1 – 4.23 2.95 – 1.75 1.97 
Clec4a3 C-type lectin domain family 4, a3 – 3.81 2.54 1.63 1.79 1.75 
Clec4d C-type lectin domain family 4, d – 2.07 2.39 – 1.84 2.38 
Clec4n C-type lectin domain family 4, n – 2.39 2.10 – 2.81 3.45 
Clec7a C-type lectin domain family 7, a – 2.63 1.77 – 2.49 2.99 
Clec14a C-type lectin domain family 14, a – −2.92 −3.07 – −4.26 −3.74 
Clec1a C-type lectin domain family 1, a −1.86 −2.09 – −2.59 −2.23 – 
FcRs
Fcgr4 FcR, IgG, low affinity IV – 8.10 8.18 – 2.68 2.56 
Fcgr1 FcR, IgG, high affinity I – 5.42 6.24 – 2.37 2.30 
Fcer1g FcR, IgE, high affinity I, γ – 3.17 3.80 – 2.44 2.25 
Fcgr2b FcR, IgG, low affinity IIb – 3.14 3.17 2.12 2.43 3.88 
Fcgr3 FcR, IgG, low affinity III – 2.60 2.26 – 2.04 2.09 
Fcer2a FcR, IgE, low affinity II, α – −1.51 −2.20 – – – 
TLRs
Tlr13 TLR13 – 3.40 3.70 – 2.05 2.41 
Tlr2 TLR2 – 2.02 2.10 – – – 
Tlr7 TLR7 – 1.81 1.91 – – – 
Tlr1 TLR1 – 2.15 1.80 – – – 
Tlr8 TLR8 – 1.88 1.77 – – – 

Values represent mean fold changes compared with PBS (n = 3 mice/group).

p < 0.05, one-way ANOVA, Tukey post hoc test.

–, Genes that showed no regulation in that treatment group; F+H, Flu+HDM.

Table III.
Differential expression of genes encoding chemokines and chemokine receptors during EP and LP responses after exposure to HDM, Flu, or Flu+HDM
Gene Symbol
EP
LP
ChemokinesCommon NameReceptorHDMFluF+HHDMFluF+H
Cxcl10 IP-10 CXCR3 – 22.20 23.30 2.26 5.91 7.41 
Cxcl9 MIG CXCR3 – 14.50 12.93 – 7.03 6.64 
Ccl8 MCP-2 CCR1, CCR2b, CCR5 – 11.81 9.78 4.37 7.54 6.62 
Ccl3 MIP1a CCR1 – 7.36 7.69 – 2.62 3.78 
Ccl12 MCP-5 – – 5.34 6.12 1.74 2.82 2.82 
Cxcl13 BCA-1/BLC CXCR5 – 5.34 5.57 1.64 3.37 5.62 
Ccl2 MCP-1 CCR2 – 5.21 5.46 – 1.64 1.68 
Ccl7 MCP-3/MARC CCR2 – 4.00 5.13 1.61 1.56 1.94 
Ccl5 RANTES CCR5 – 3.32 2.69 – 2.11 1.54 
Cxcl16 SRPSOX CXCR6 – 2.44 2.26 – 1.79 1.83 
Cxcl5 ENA-78 CXCR2 – 2.46 2.26 2.02 2.33 4.18 
Ccl9 RP-2, CCF18, MIP-1? CCR1 – 1.67 2.04 1.70 1.72 2.25 
Cxcl17 DMC, VCC-1 – – – 1.51 – 2.48 2.49 
Cx3cl1 Fractalkine CX3CR1 – −1.75 −1.55 – – – 
Ccl21a 6Ckine, Exodus-2 CCR7 1.51 – – – 1.69 1.50 
Ccl22 MDC CCR4 – – – – – 1.58 
Ccl11 Eotaxin CCR2, CCR3, CCR5 – – – 2.88 – 1.59 
Ccl20 LARC, Exodus-1 CCR6 – – – – – 1.71 
Ccl17 TARC CCR4 – – – – 1.64 1.81 
Ccl6 C10, MRP-2 CCR1 – – – – 1.89 1.90 
Ccl19 ELC, Exodus-3 CCR7 2.20 – – – – – 
Receptors
 
Cellular Expression
 
Ligands
 

 

 

 

 

 

 
Ccr5 DC and memory Th1 cells CCL2, CCL3, CCL4, CCL5, CCL11, CCL13, CCL14, CCL16 – 9.28 8.78 1.71 3.21 3.56 
Cxcr6 – CXCL16 – 6.54 4.58 – 2.84 3.56 
Cxcr3 T, NK, and B cell CXCL9, CXCL10, CXCL11 – 4.37 4.17 – 2.58 2.14 
Ccr2 Monocytes, memory T cells, B cells, basophils, macrophages CCL2, CCL8, CCL16 – 3.06 2.28 – – 1.72 
Cxcr7 T and B cells CXCL12 – – 1.69 – – – 
Cxcr2 Neutrophils CXCL1 to CXCL7 – – 1.63 1.63 – 1.62 
Ccrl1 – CCL19/CCL21/SLC and CCL25/TECK – −1.71 −2.07 – – −1.75 
Cxcr4 Hematopoietic cells CXCL12 – −1.68 −2.11 – −1.73 −1.71 
Ccrl2 Neutrophils and monocytes  –  – – −1.69 −1.87 
Xcr1 – – – 2.11 – – 1.50 1.59 
Cx3cr1 – CX3CL1 – 1.68 – – 1.83 – 
Gene Symbol
EP
LP
ChemokinesCommon NameReceptorHDMFluF+HHDMFluF+H
Cxcl10 IP-10 CXCR3 – 22.20 23.30 2.26 5.91 7.41 
Cxcl9 MIG CXCR3 – 14.50 12.93 – 7.03 6.64 
Ccl8 MCP-2 CCR1, CCR2b, CCR5 – 11.81 9.78 4.37 7.54 6.62 
Ccl3 MIP1a CCR1 – 7.36 7.69 – 2.62 3.78 
Ccl12 MCP-5 – – 5.34 6.12 1.74 2.82 2.82 
Cxcl13 BCA-1/BLC CXCR5 – 5.34 5.57 1.64 3.37 5.62 
Ccl2 MCP-1 CCR2 – 5.21 5.46 – 1.64 1.68 
Ccl7 MCP-3/MARC CCR2 – 4.00 5.13 1.61 1.56 1.94 
Ccl5 RANTES CCR5 – 3.32 2.69 – 2.11 1.54 
Cxcl16 SRPSOX CXCR6 – 2.44 2.26 – 1.79 1.83 
Cxcl5 ENA-78 CXCR2 – 2.46 2.26 2.02 2.33 4.18 
Ccl9 RP-2, CCF18, MIP-1? CCR1 – 1.67 2.04 1.70 1.72 2.25 
Cxcl17 DMC, VCC-1 – – – 1.51 – 2.48 2.49 
Cx3cl1 Fractalkine CX3CR1 – −1.75 −1.55 – – – 
Ccl21a 6Ckine, Exodus-2 CCR7 1.51 – – – 1.69 1.50 
Ccl22 MDC CCR4 – – – – – 1.58 
Ccl11 Eotaxin CCR2, CCR3, CCR5 – – – 2.88 – 1.59 
Ccl20 LARC, Exodus-1 CCR6 – – – – – 1.71 
Ccl17 TARC CCR4 – – – – 1.64 1.81 
Ccl6 C10, MRP-2 CCR1 – – – – 1.89 1.90 
Ccl19 ELC, Exodus-3 CCR7 2.20 – – – – – 
Receptors
 
Cellular Expression
 
Ligands
 

 

 

 

 

 

 
Ccr5 DC and memory Th1 cells CCL2, CCL3, CCL4, CCL5, CCL11, CCL13, CCL14, CCL16 – 9.28 8.78 1.71 3.21 3.56 
Cxcr6 – CXCL16 – 6.54 4.58 – 2.84 3.56 
Cxcr3 T, NK, and B cell CXCL9, CXCL10, CXCL11 – 4.37 4.17 – 2.58 2.14 
Ccr2 Monocytes, memory T cells, B cells, basophils, macrophages CCL2, CCL8, CCL16 – 3.06 2.28 – – 1.72 
Cxcr7 T and B cells CXCL12 – – 1.69 – – – 
Cxcr2 Neutrophils CXCL1 to CXCL7 – – 1.63 1.63 – 1.62 
Ccrl1 – CCL19/CCL21/SLC and CCL25/TECK – −1.71 −2.07 – – −1.75 
Cxcr4 Hematopoietic cells CXCL12 – −1.68 −2.11 – −1.73 −1.71 
Ccrl2 Neutrophils and monocytes  –  – – −1.69 −1.87 
Xcr1 – – – 2.11 – – 1.50 1.59 
Cx3cr1 – CX3CL1 – 1.68 – – 1.83 – 

Values represent mean fold changes compared with PBS (n = 3 mice/group).

p < 0.05, one-way ANOVA, Tukey post hoc test.

–, Genes that showed no significant regulation in that treatment group; F+H, Flu+HDM.

Table IV.
Differential expression of genes encoding cytokines and cytokine receptors during EP and LP responses after exposure to HDM, Flu, or Flu+HDM
EP
LP
Gene SymbolGene NameHDMFluF+HHDMFluF+H
Receptors        
Tnfrsf12a TNFR superfamily, member 12a – 1.72 2.75 – 1.60 1.50 
Il1r2 IL-1R, type II – 1.61 2.48 – – 2.14 
Il2rb IL-2R, β-chain – 2.22 2.43 – – – 
Il1rn IL-1R antagonist – 2.00 1.97 – 1.58 2.03 
Tnfrsf9 TNFR superfamily, member 9 – 2.00 1.87 – – 1.97 
Il21r IL-21R – 1.90 1.82 – 1.67 1.72 
Il2rg IL-2R, γ-chain – 2.18 1.55 – – 1.63 
Tnfsf10 TNF (ligand) superfamily, member 10 – – −1.72 – −1.94 −1.63 
Il17rd IL-17R D – −1.68 −1.88 – −1.62 −1.68 
Ifngr2 IFN-γR 2 – – – – – 1.52 
Il18rap IL-18R accessory protein – 1.57 – – – – 
Il10ra IL-10Rα – 1.63 – – – – 
Cytokines        
Irf7 IFN regulatory factor 7 – 3.03 4.44 – 1.72 1.86 
Irf1 IFN regulatory factor 1 – 2.22 2.40 – – 1.51 
Il18bp IL-18 binding protein – 2.07 2.38 – – 1.51 
Tnf TNF – 2.11 2.24 – – 1.56 
Il1b IL-1β – 1.95 2.00 1.57 2.23 2.93 
Tnfrsf1b TNFR superfamily, member 1b – 1.82 1.99 – – 1.67 
Irf8 IFN regulatory factor 8 – 1.99 1.83 – – 1.61 
Tnfaip6 TNF-α–induced protein 6 – – – 1.85 – 1.56 
Il1f9 IL-1 family, member 9 – – – – – 1.59 
Tnfaip2 TNF-α–induced protein 2 – – – – 1.63 1.88 
Il33 IL-33 – 1.64 – 1.58 – 1.93 
Il6st IL 6 signal transducer – – – – −1.63 – 
Tnfsf13b TNF (ligand) superfamily, member 13b – 1.63 – – – – 
Il1a IL-1α – – – – – – 
EP
LP
Gene SymbolGene NameHDMFluF+HHDMFluF+H
Receptors        
Tnfrsf12a TNFR superfamily, member 12a – 1.72 2.75 – 1.60 1.50 
Il1r2 IL-1R, type II – 1.61 2.48 – – 2.14 
Il2rb IL-2R, β-chain – 2.22 2.43 – – – 
Il1rn IL-1R antagonist – 2.00 1.97 – 1.58 2.03 
Tnfrsf9 TNFR superfamily, member 9 – 2.00 1.87 – – 1.97 
Il21r IL-21R – 1.90 1.82 – 1.67 1.72 
Il2rg IL-2R, γ-chain – 2.18 1.55 – – 1.63 
Tnfsf10 TNF (ligand) superfamily, member 10 – – −1.72 – −1.94 −1.63 
Il17rd IL-17R D – −1.68 −1.88 – −1.62 −1.68 
Ifngr2 IFN-γR 2 – – – – – 1.52 
Il18rap IL-18R accessory protein – 1.57 – – – – 
Il10ra IL-10Rα – 1.63 – – – – 
Cytokines        
Irf7 IFN regulatory factor 7 – 3.03 4.44 – 1.72 1.86 
Irf1 IFN regulatory factor 1 – 2.22 2.40 – – 1.51 
Il18bp IL-18 binding protein – 2.07 2.38 – – 1.51 
Tnf TNF – 2.11 2.24 – – 1.56 
Il1b IL-1β – 1.95 2.00 1.57 2.23 2.93 
Tnfrsf1b TNFR superfamily, member 1b – 1.82 1.99 – – 1.67 
Irf8 IFN regulatory factor 8 – 1.99 1.83 – – 1.61 
Tnfaip6 TNF-α–induced protein 6 – – – 1.85 – 1.56 
Il1f9 IL-1 family, member 9 – – – – – 1.59 
Tnfaip2 TNF-α–induced protein 2 – – – – 1.63 1.88 
Il33 IL-33 – 1.64 – 1.58 – 1.93 
Il6st IL 6 signal transducer – – – – −1.63 – 
Tnfsf13b TNF (ligand) superfamily, member 13b – 1.63 – – – – 
Il1a IL-1α – – – – – – 

Values represent mean fold changes compared with PBS (n = 3 mice/group).

p < 0.05, one-way ANOVA, Tukey post hoc test.

–, Genes that showed no significant regulation in that treatment group; F+H, Flu+HDM.

In addition to the 330 and 240 uniquely expressed genes in the Flu+HDM-treated mice during the EP and LP, respectively (Fig. 3), we selected genes whose expression was shared among the three treatment groups but that exhibited additional regulation in response to HDM when allergen exposure occurred during ongoing Flu infection. A selection criterion of a 1.5-fold difference in expression was applied to the 1262 commonly expressed genes in the EP that resulted in the inclusion of 34 genes shared between Flu and Flu+HDM groups and 2 genes shared among all three treatments (HDM, Flu, and Flu+HDM). Collectively, a total of 366 genes were additionally regulated in response to HDM exposure in the context of Flu infection (Supplemental Table I). The same selection criterion was applied to the genes commonly expressed in the LP, which resulted in a total of 263 genes (240 were unique to Flu+HDM; 11 were common among all three treatments; 8 were common among Flu and Flu+HDM; 4 were common among HDM and Flu+HDM) (Supplemental Table I). According to available functional annotations, these genes could be classified into 13 major functional categories. Functional annotations for 146 genes from EP and 86 genes from LP are not available and, thus, were classified in the “other” category (Table V).

Table V.
Functional categories of uniquely expressed genes in mice concurrently exposed to Flu+HDM during the EP and LP response
F+H Treatment Group
EP
LP
Biological FunctionNo. of GenesNo. of Genes
Translation regulation 
Other metabolic genes 
Nucleotide/DNA/chromosome binding 
Lipid/fatty acid metabolism 10 
Ion transport/binding 11 12 
Carbohydrate metabolism 11 
Protein transport 16 
Tissue/muscle development or reorganization 19 16 
Transcription regulation 22 19 
Cell division/cell cycle regulation 22 16 
Protein metabolism/regulation 30 16 
Immune/inflammatory response 32 46 
Intracellular signaling 36 12 
Others 146 86 
Total genes 366 263 
F+H Treatment Group
EP
LP
Biological FunctionNo. of GenesNo. of Genes
Translation regulation 
Other metabolic genes 
Nucleotide/DNA/chromosome binding 
Lipid/fatty acid metabolism 10 
Ion transport/binding 11 12 
Carbohydrate metabolism 11 
Protein transport 16 
Tissue/muscle development or reorganization 19 16 
Transcription regulation 22 19 
Cell division/cell cycle regulation 22 16 
Protein metabolism/regulation 30 16 
Immune/inflammatory response 32 46 
Intracellular signaling 36 12 
Others 146 86 
Total genes 366 263 

Genes were selected based on a mean fold change of ±1.5 compared with PBS control-, HDM only-, or Flu-only–treated groups (n = 3 mice/group).

p < 0.05, one-way ANOVA, Tukey post hoc test.

F+H, Flu+HDM.

To further understand the contribution of immune genes in regulating the response to HDM during acute viral infection, we examined in more detail those genes that were part of the “immune/inflammatory response” category. Our data identified 32 genes in the EP, of which 8 genes were shared between Flu and Flu+HDM (Table VI), and 46 genes expressed during the LP, of which 7 genes were shared between these two treatment groups (Table VII). These shared genes showed additional regulation to HDM exposure, resulting in additional fold increases in expression levels following HDM exposure in mice infected with influenza (Flu+HDM) compared with those infected with influenza only. Importantly, for the majority of these immune/inflammatory-responsive genes, the expression levels were upregulated and, for only a few of these genes (11 genes in EP; 4 genes in LP), the levels were downregulated. We identified serum amyloid A (Saa3), tissue inhibitor of metalloproteinase 1 (Timp1), and serine protease inhibitor A3 (Serpina3n) among those genes that were additionally upregulated by HDM exposure during EP and LP, whereas S100 calcium-binding protein A8 (S100a8) was one of the uniquely expressed genes that emerged during the EP.

Table VI.
Immune inflammatory genes with additional responsiveness to HDM in the lungs of mice infected with Flu and exposed to HDM for 3 d (EP)
Gene SymbolGene NameFluF+H
Saa3 Serum amyloid A 3 15.74 17.35 
Cxcl9 Chemokine (CXC motif) ligand 9 14.50 12.93 
Timp1 Tissue inhibitor of metalloproteinase 1 8.01 10.07 
Ccl8 Chemokine (CC motif) ligand 8 11.81 9.78 
Serpina3n Serine (or cysteine) peptidase inhibitor, clade A, member 3N 4.09 9.25 
IghmAC38.205.12 Ig μ chain V region AC38 205.12 3.65 5.65 
Igh-Ia IgH Ia 2.96 4.94 
Cd163 CD163 Ag – 2.54 
C5ar1 Complement component 5a receptor 1 – 1.89 
C2 Complement component 2 (within H2S) – 1.78 
S100a8 S100 calcium binding protein A8 (calgranulin A) – 1.70 
Ndrg1 Nmyc downstream regulated gene 1 – 1.68 
Il8rb IL-8R, β – 1.63 
Nupr1 Nuclear protein 1 – 1.62 
G6pdx Glucose-6 phosphate dehydrogenase X-linked – 1.62 
Enpp1 Ectonucleotide pyrophosphatase/phosphodiesterase 1 – 1.58 
C1r Complement component 1, r subcomponent – 1.56 
H2Q2|H2t9|H2D1 MHC class Ib T9 – 1.54 
Fn1 Fibronectin 1 – 1.53 
Cxcl17 Chemokine (CXC motif) ligand 17 – 1.51 
H2T24 Histocompatibility 2, T region locus 24 – 1.50 
Bpgm 2,3 bisphosphoglycerate mutase – −1.62 
Cr2 Complement receptor 2 – −1.68 
Tnfsf10 TNF (ligand) superfamily, member 10 – −1.72 
Cbfa2t3 Core-binding factor, runt domain, α subunit 2, translocated to 3 (human) – −1.72 
Enpp2 Ectonucleotide pyrophosphatase/phosphodiesterase 2 – −1.74 
Ms4a1 Membrane spanning 4 domains, subfamily A, member 1 – −1.79 
Bank1 B cell scaffold protein with ankyrin repeats 1 – −1.80 
Itga1 Integrin α 1 – −1.82 
Lyz1 Lysozyme 1 – −1.94 
Cd209a CD209a Ag – −2.14 
Hc Hemolytic complement −2.00 −5.56 
Gene SymbolGene NameFluF+H
Saa3 Serum amyloid A 3 15.74 17.35 
Cxcl9 Chemokine (CXC motif) ligand 9 14.50 12.93 
Timp1 Tissue inhibitor of metalloproteinase 1 8.01 10.07 
Ccl8 Chemokine (CC motif) ligand 8 11.81 9.78 
Serpina3n Serine (or cysteine) peptidase inhibitor, clade A, member 3N 4.09 9.25 
IghmAC38.205.12 Ig μ chain V region AC38 205.12 3.65 5.65 
Igh-Ia IgH Ia 2.96 4.94 
Cd163 CD163 Ag – 2.54 
C5ar1 Complement component 5a receptor 1 – 1.89 
C2 Complement component 2 (within H2S) – 1.78 
S100a8 S100 calcium binding protein A8 (calgranulin A) – 1.70 
Ndrg1 Nmyc downstream regulated gene 1 – 1.68 
Il8rb IL-8R, β – 1.63 
Nupr1 Nuclear protein 1 – 1.62 
G6pdx Glucose-6 phosphate dehydrogenase X-linked – 1.62 
Enpp1 Ectonucleotide pyrophosphatase/phosphodiesterase 1 – 1.58 
C1r Complement component 1, r subcomponent – 1.56 
H2Q2|H2t9|H2D1 MHC class Ib T9 – 1.54 
Fn1 Fibronectin 1 – 1.53 
Cxcl17 Chemokine (CXC motif) ligand 17 – 1.51 
H2T24 Histocompatibility 2, T region locus 24 – 1.50 
Bpgm 2,3 bisphosphoglycerate mutase – −1.62 
Cr2 Complement receptor 2 – −1.68 
Tnfsf10 TNF (ligand) superfamily, member 10 – −1.72 
Cbfa2t3 Core-binding factor, runt domain, α subunit 2, translocated to 3 (human) – −1.72 
Enpp2 Ectonucleotide pyrophosphatase/phosphodiesterase 2 – −1.74 
Ms4a1 Membrane spanning 4 domains, subfamily A, member 1 – −1.79 
Bank1 B cell scaffold protein with ankyrin repeats 1 – −1.80 
Itga1 Integrin α 1 – −1.82 
Lyz1 Lysozyme 1 – −1.94 
Cd209a CD209a Ag – −2.14 
Hc Hemolytic complement −2.00 −5.56 

Values represent mean fold changes compared with PBS (n = 3 mice/group).

p < 0.05, one-way ANOVA, Tukey post hoc test.

–, Genes that showed no significant regulation in that treatment group; F+H, Flu+HDM.

Table VII.
Immune inflammatory genes with additional responsiveness to HDM in the lungs of mice infected with Flu and exposed to HDM for 6 d (LP)
Gene SymbolGene NameFluF+H
Igj Ig joining chain 9.61 11.17 
IghmAC38.205.12 Ig μ chain V region AC38 205.12 8.72 10.80 
Saa3 Serum amyloid A 3 5.88 10.61 
Cxcl10 Chemokine (CXC motif) ligand 10 5.91 7.41 
Timp1 Tissue inhibitor of metalloproteinase 1 5.27 6.82 
Cxcl13 Chemokine (CXC motif) ligand 13 3.37 5.62 
Cxcl5 Chemokine (CXC motif) ligand 5 2.33 4.18 
Irg1 Immunoresponsive gene 1 – 2.22 
Orm1 Orosomucoid 1 – 1.91 
Itgax Integrin α X – 1.79 
Mpa2l Guanylate binding protein 10 – 1.77 
Mpa2l Macrophage activation 2 like – 1.74 
Oasl2 2′5′ oligoadenylate synthetase-like 2 – 1.73 
H2Eb1 Histocompatibility 2, class II Ag E β – 1.72 
Ccr2 Chemokine (CC motif) receptor 2 – 1.72 
Cd274 CD274 Ag – 1.72 
Igbp1 Ig (CD79A) binding protein 1 – 1.71 
Ccl20 Chemokine (CC motif) ligand 20 – 1.71 
Gbp2 Guanylate binding protein 2 – 1.71 
Cfb Complement factor B – 1.69 
Tnfrsf1b TNFR superfamily, member 1b – 1.67 
Oas1a 2′5′ oligoadenylate synthetase 1A – 1.65 
H2Q8 Histocompatibility 2, Q region locus 1 – 1.63 
Il2rg IL-2R, γ-chain – 1.63 
Irf8 IFN regulatory factor 8 – 1.61 
Vav1 Vav 1 oncogene – 1.61 
Gbp3 Guanylate binding protein 3 – 1.61 
H2Q2|H2gs10|H2Q1 Histocompatibility 2, Q region locus 5 – 1.61 
Il1f9 IL-1 family, member 9 – 1.59 
H2Aa Histocompatibility 2, class II Ag A, α – 1.59 
Ccl22 Chemokine (CC motif) ligand 22 – 1.58 
Plek Pleckstrin – 1.57 
Psme1 Proteasome (prosome, macropain) 28 subunit, α – 1.57 
Ptafr Platelet-activating factor receptor – 1.57 
Fn1 Fibronectin 1 – 1.56 
Lsp1 Lymphocyte specific 1 – 1.54 
Sirpa Signal regulatory protein α – 1.54 
Lax1 Lymphocyte transmembrane adaptor 1 – 1.53 
Mx1 Myxovirus (influenza virus) resistance 1 – 1.52 
Il18bp IL-18 binding protein – 1.51 
Irf1 IFN regulatory factor 1 – 1.51 
Pomp Proteasome maturation protein – 1.51 
H2T24 Histocompatibility 2, T region locus 24 – −1.50 
Mfge8 Milk fat globule EGF factor 8 protein – −1.53 
Ear2 Eosinophil-associated, RNase A family, member 3 – −1.56 
Alas2 Aminolevulinic acid synthase 2, erythroid – −1.87 
Gene SymbolGene NameFluF+H
Igj Ig joining chain 9.61 11.17 
IghmAC38.205.12 Ig μ chain V region AC38 205.12 8.72 10.80 
Saa3 Serum amyloid A 3 5.88 10.61 
Cxcl10 Chemokine (CXC motif) ligand 10 5.91 7.41 
Timp1 Tissue inhibitor of metalloproteinase 1 5.27 6.82 
Cxcl13 Chemokine (CXC motif) ligand 13 3.37 5.62 
Cxcl5 Chemokine (CXC motif) ligand 5 2.33 4.18 
Irg1 Immunoresponsive gene 1 – 2.22 
Orm1 Orosomucoid 1 – 1.91 
Itgax Integrin α X – 1.79 
Mpa2l Guanylate binding protein 10 – 1.77 
Mpa2l Macrophage activation 2 like – 1.74 
Oasl2 2′5′ oligoadenylate synthetase-like 2 – 1.73 
H2Eb1 Histocompatibility 2, class II Ag E β – 1.72 
Ccr2 Chemokine (CC motif) receptor 2 – 1.72 
Cd274 CD274 Ag – 1.72 
Igbp1 Ig (CD79A) binding protein 1 – 1.71 
Ccl20 Chemokine (CC motif) ligand 20 – 1.71 
Gbp2 Guanylate binding protein 2 – 1.71 
Cfb Complement factor B – 1.69 
Tnfrsf1b TNFR superfamily, member 1b – 1.67 
Oas1a 2′5′ oligoadenylate synthetase 1A – 1.65 
H2Q8 Histocompatibility 2, Q region locus 1 – 1.63 
Il2rg IL-2R, γ-chain – 1.63 
Irf8 IFN regulatory factor 8 – 1.61 
Vav1 Vav 1 oncogene – 1.61 
Gbp3 Guanylate binding protein 3 – 1.61 
H2Q2|H2gs10|H2Q1 Histocompatibility 2, Q region locus 5 – 1.61 
Il1f9 IL-1 family, member 9 – 1.59 
H2Aa Histocompatibility 2, class II Ag A, α – 1.59 
Ccl22 Chemokine (CC motif) ligand 22 – 1.58 
Plek Pleckstrin – 1.57 
Psme1 Proteasome (prosome, macropain) 28 subunit, α – 1.57 
Ptafr Platelet-activating factor receptor – 1.57 
Fn1 Fibronectin 1 – 1.56 
Lsp1 Lymphocyte specific 1 – 1.54 
Sirpa Signal regulatory protein α – 1.54 
Lax1 Lymphocyte transmembrane adaptor 1 – 1.53 
Mx1 Myxovirus (influenza virus) resistance 1 – 1.52 
Il18bp IL-18 binding protein – 1.51 
Irf1 IFN regulatory factor 1 – 1.51 
Pomp Proteasome maturation protein – 1.51 
H2T24 Histocompatibility 2, T region locus 24 – −1.50 
Mfge8 Milk fat globule EGF factor 8 protein – −1.53 
Ear2 Eosinophil-associated, RNase A family, member 3 – −1.56 
Alas2 Aminolevulinic acid synthase 2, erythroid – −1.87 

Values represent mean fold changes compared with PBS (n = 3 mice/group).

p < 0.05, one-way ANOVA, Tukey post hoc test.

–, Genes that showed no significant regulation in that treatment group; F+H, Flu+HDM.

To validate the gene-expression data obtained by microarray analysis, we examined gene-expression levels for a number of genes using quantitative real-time PCR (qPCR). To this end, we chose to examine genes with various fold changes across different gene classes as representative samples; these included a selection of genes expressed following Flu infection, as well as representative genes from the “uniquely expressed” list of genes following HDM exposure in the context of an ongoing Flu infection. These included complement component 1, q subcomponent, C chain (C1qc); chemokine (CC motif) ligand 7 (Ccl7); chemokine (CC motif) ligand 8 (Ccl8); C-type lectin domain family 14, member a (Clec14a); chemokine (CXC motif) ligand 10 (Cxcl10); chemokine (CXC motif) ligand 5 (Cxcl5); chemokine (CXC motif) ligand 9 (Cxcl9); chemokine (CXC motif) receptor 3 (Cxcr3); FcR, IgG, low affinity IV (Fcgr4); Ig μ chain V region AC38 205.12 (IghmAC38.205.12); Saa3; and Timp1 (Fig. 5). All of these genes demonstrated the same directional fold changes (11 genes upregulated and 1 gene downregulated) analyzed by qPCR as that observed by microarray analysis. Ccl7, Ccl8, Cxcl10, Cxcl5, Saa3, and Timp1 from the microarray experiment were found to be upregulated in the HDM-treatment group in the LP only, which was confirmed by qPCR analysis. Furthermore, none of these genes was significantly expressed in the HDM treatment group in the EP, as analyzed either by microarray or qPCR.

FIGURE 5.

Representative genes from microarray experiment validated by qPCR. Data are expressed as mean ± SEM (n = 4). *p < 0.05, **p < 0.01, pair-wise fixed reallocation randomization test.

FIGURE 5.

Representative genes from microarray experiment validated by qPCR. Data are expressed as mean ± SEM (n = 4). *p < 0.05, **p < 0.01, pair-wise fixed reallocation randomization test.

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The conditions under which allergen sensitization and ultimately, allergic inflammation, occur remain to be fully elucidated. HDM, the most ubiquitous aeroallergen worldwide, comprises a biochemically complex mixture of hundreds of protein and nonprotein components that confer immunogenic activities (16). Studies examining mechanisms associated with HDM-induced inflammation have identified various molecular constituents capable of activating innate defense mechanisms at mucosal surfaces (17, 18). However, these studies relied on the administration of concentrations of allergen designed to elicit maximal immune responses. In this regard, we recently reported detailed dose responses to HDM in a mouse system (19). Our data showed that although exposure to a concentration of 25 μg daily elicited near-maximal responses, exposure to 1 μg represented the threshold of visible responsiveness. Although it is exceedingly difficult to determine, on clinical and epidemiological grounds, the precise amount of HDM that humans inhale, it is reasonable to argue that most individuals are exposed to amounts that are insufficient to elicit allergic sensitization and, particularly, allergic asthma. Furthermore, we must be mindful that, in humans, allergen exposure rarely occurs in isolation but, rather, coupled to concurrent exposures to a plethora of chemicals (e.g., pollution) and biological entities, such as respiratory viruses, which can elicit substantial immune changes in the lung. Thus, priming of the immune environment of the lung through environmental coexposures may shift HDM responsiveness and, thus, increase the susceptibility to develop allergic sensitization and, eventually, allergic asthma.

The research we report in this article is based on a previous study in which we described a distinctive asthmatic phenotype in mice exposed to a low concentration of HDM (5 μg daily) in the context of an acute influenza infection (7). In this model, exposure to HDM alone elicits minimal allergic sensitization and airway eosinophilia and, importantly, does not alter lung function. Hence, we define this dose as a subclinical dose of allergen exposure. However, if HDM exposure takes place during the course of an ongoing acute influenza infection, strong Th2-mediated immunity, robust eosinophilia and, importantly, the generation of marked lung dysfunction ensue. We sought to investigate the genomic basis of this phenotype. As shown in Fig. 2, our data indicated that the global gene-expression profile in the lungs of mice exposed to HDM alone approximated the expression profile of mice exposed to PBS. In contrast, infection with Flu led to a gene-expression profile that was remarkably different from that observed in mice exposed to either HDM alone or PBS. Interestingly, the expression pattern in the lungs of Flu+HDM-treated mice was similar, but not identical, to that induced by Flu alone, despite the overt differences in phenotype observed between these two groups (7). Venn analysis revealed that 80% of genes expressed in Flu+HDM-treated mice were also expressed in the lungs of mice infected with Flu only (Fig. 3). A similar examination revealed that mice exposed to HDM alone or Flu+HDM shared only 1.5% and 6% of expressed genes in the EP and LP, respectively. In contrast to shared genes, we identified a set of 330 and 240 unique genes expressed only in mice exposed to Flu+HDM during the EP and LP of the response, respectively; these genes represent 23% and 19% of the total regulated genes in this treatment group. These data revealed that, compared with the minimal impact elicited by a subclinical dose of allergen, Flu infection has a major impact on global gene regulation, involving hundreds of genes involved in the regulation of a number of distinct biological pathways.

Based on the initial global gene-expression analysis, we sought to uncover potential pathways by which influenza may enhance allergen responsiveness. To this end, we analyzed in greater detail the biological roles of genes induced following influenza infection and, then, focused our analysis on specific gene classes that may facilitate innate responsiveness to allergen exposure. From a functional perspective, the gene-expression profile observed following Flu and Flu+HDM treatment showed that these genes pertained to a wide range of biological processes. Major categories included response to stimuli, stress, and wounding and genes mainly associated with inflammatory responses and chemotaxis (Fig. 4). Many of these processes were highly enriched with genes associated with the initiation of immune inflammatory responses encoding proteins for pattern recognition receptors and damage-associated molecular patterns, such as TLRs, CLRs, and several members of the complement pathway (Tables I, II). Among the TLRs, our study showed that Flu infection particularly led to increased and sustained expression of TLR13, a recently described member of the TLR family, shown to be expressed largely by myeloid cells, particularly dendritic cells (DCs) (20, 21). Similarly, we observed increased expression for a number of CLR family members, most notably Dectin 1 (Clec7a) and Dectin 2 (Clec4n) expressed on DCs and macrophages (22, 23). These receptors were shown to respond to complex carbohydrate structures, including glycans present on HDM aeroallergens, such as Dermatophagoides farinae and Dermatophagoides pteronyssinus (24). Interestingly, we detected increased expression of a number of FcR molecules, most notably FcεR1. Grayson et al. (25) reported, in a mouse model of sendai virus infection, increased type-1 IFNR-dependent upregulation of FcεR1 on lung DCs, which, upon receptor cross-linking, led to the production of CCL28, a Th2-associated chemokine. Furthermore, evidence from a microarray analysis of PBMCs isolated during acute virus-associated asthma exacerbations from HDM-sensitized children, revealed increased FcεR1 gene expression on monocytes and DCs (26); interestingly, this was associated with increased expression of CCR2, a chemokine receptor necessary for the recruitment of monocytes and DCs to inflamed tissues. In accordance with these findings, our study showed that influenza infection triggers the expression of FcεRI in the lung, along with concomitant increases in CCR2 and type I IFN-stimulated genes (Table III). The nature of our study prevented identification of the specific cell types expressing these molecules. However, these findings collectively suggested that viral infections may amplify the allergic immune-inflammatory response through a mechanism that involves type-1 IFN and FcεR1 and the recruitment of monocytes and DCs into the inflamed lung environment.

Lastly, our data revealed increased expression of several components of the complement pathway, most notably several C1q subunits (C1qa, C1qb, C1qc), C3, and C3ar, which are key components necessary for the generation and signaling of anaphylatoxins C3a and C5a. Anaphylatoxins are involved in the recruitment and activation of a number of leukocytes, including mast cells, eosinophils, and basophils, and were also implicated in the regulation of DC and T cell signaling (27). Thus, Flu infection enhanced the expression of a substantial number of innate molecules involved in the sensing and response to HDM.

Activation of innate-immune pathways through signaling of cell surface receptors leads to the recruitment of immune inflammatory cells capable of producing a plethora of cytokines. Consistent with our previous report of increased expression of proinflammatory cytokines and the accumulation of neutrophils, DCs, and monocytes into the lung of mice during the acute phase of the response (7), influenza infection at day 10 postinfection regulated the expression of a substantial number of chemokines and their receptors involved in the recruitment of various leukocytes, such as monocytes, macrophages, DCs’ Th cells, eosinophils, and mast cells (Table III). The cytokine gene profile elicited by influenza reflects its potent Th1 cell-promoting effects, with strong induction of members of the type I IFN family, as well as proinflammatory cytokines, such as TNF-α and several members of the IL-1 family of proteins, including IL-1β, IL-18bp and, notably, IL-33 (7, 28) (Table IV). Interestingly, IL-33 was shown to amplify both Th1- and Th2-type responses by targeting mast cells, basophils, and Th2 cells, as well as NK and NK T cells, hence suggesting an important role in asthma pathogenesis (29). Importantly, our study showed that this cytokine is also increased 7 d following HDM exposure, and its expression is further enhanced in mice exposed to HDM in the context of an ongoing Flu infection. Thus, through the activation of innate and adaptive immune pathways, influenza infection induces a number of gene families involved in the initiation and propagation of a variety of Th-mediated inflammatory responses.

In addition to the pervasive upregulation of genes involved in innate immune responsiveness following influenza infection, we identified a subset of genes uniquely expressed as a result of Flu+HDM coexposure; these consisted of 366 and 263 genes during the EP and LP of the response, respectively (Table V, Supplemental Table I). Of these, 330 and 240 genes were identified as unique genes in mice exposed to Flu+HDM and were not expressed in any other treatment groups (Fig. 3). An additional 36 and 23 genes were shared among HDM-, Flu-, and Flu+HDM–treated groups; however, these shared genes were found to be significantly up- or downregulated in Flu-infected mice concurrently exposed to HDM. Although 30–40% of these genes do not have ascribed functions, the remaining 60–70% are known to be involved in a wide range of biological processes; these could be divided into 13 functional categories, including immune inflammatory responses, intracellular signaling, metabolism, and transcriptional and translational regulation, as well as tissue/muscle development and reorganization. These data showed that a subclinical dose of HDM, which by itself did not lead to significantly altered gene expression, elicited distinct, unique changes when administered in the context of an ongoing Flu infection.

To further understand how the interaction between HDM and Flu affected gene expression from an immunological perspective, we evaluated the contribution of genes expressed within the functional group “immune inflammatory-responsive genes.” In addition to the increased expression of several members of the chemokine and cytokine family and genes encoding additional complement components, we particularly observed increased expression of genes encoding proteins, such as Saa3, Timp1, and serine peptidase inhibitor, clade A, member 3N (Serpina3n). Although Timp1 was reported to play a role in extracellular matrix remodeling, and its role in the development of allergic asthma is well described (30, 31), the functional role of Serpina3n has not been established. In humans, SERPIN3A, commonly known as antichymotrypsin, is produced by a variety of cell types, including hepatocytes and bronchial epithelial cells during acute inflammatory responses, and studies showed that serum levels of two other serpin family members, SERPINB3 and SERPINB4, are elevated in patients with asthma (32, 33). Interestingly, in a recent animal model of allergic asthma, the murine ortholog, Serpin3ba, was shown to mediate HDM-induced mucus production (34). Thus, our study suggested that, similar to other serpin family members, Serpina3n may likely play an important role in HDM-mediated allergic disease, particularly in the context of an acute viral infection.

Saa3, is a major acute-phase protein that can act as a chemoattractant for phagocytes (35) and recently was shown to promote Th17-mediated allergic asthma through the activation of the NLRP3 inflammasome complex (36). Our data showed that this gene was significantly upregulated following Flu infection, with an additional 2-fold increase following HDM exposure during the EP that was sustained through the LP, where we observed a 5-fold difference in expression level between Flu- and Flu+HDM-treated mice (Tables VI, VII). Interestingly, the expression of Saa3 in the lung is regulated by S100a8 (37), which was also found to be exclusively expressed in Flu+HDM-treated mice, albeit at lower levels. Indeed, S100A8 was recently identified as an important damage-associated molecular pattern released by activated phagocytes and was shown to be an endogenous activator of TLR4 on monocytes (38, 39). Although the functional role of S100a8 remains to be elucidated, our findings intimate the potential importance of the Saa3–S100a8 axis in allergic disease. Considering that S100A8 can activate TLR4 signaling, the increased expression of these genes may amplify inflammatory responses (40). Thus, HDM exposure in the context of a prior Flu infection leads to the expression of a number of unique immune genes that collectively function to either facilitate or amplify allergic inflammatory responses.

We describe the concentration of HDM used in this study as “subclinical” because, per se, it induced minimal immune-inflammatory responses and no airway physiological changes. In this study, we investigated the impact of an ongoing Flu infection on the response to such low concentration of HDM at the genomic level. Under these conditions, the phenotype elicited is characterized by robust allergic airway inflammation and airway hyperreactivity. Our data showed that the potential mechanisms by which Flu infection may facilitate this phenotype are manifold and impact different processes in the generation of allergic-inflammatory responses. A first repercussion may be conceptualized as a heightened state of immune alertness, illustrated by the enhanced expression of a number of innate molecules involved in Ag sensing. A second repercussion may be visualized as an amplification event exhibited by the enhanced expression of chemokines and chemokines receptors that facilitate the recruitment of a variety of immune-inflammatory cell types. We suggest that the overall consequence of these effects is a significant lowering of the threshold of allergen responsiveness required to manifest a clinically meaningful phenotype. Indeed, this outcome is depicted by the increased expression of molecules distinctly associated with features of the allergic phenotype. Clearly, the immune priming induced by Flu, and likely other respiratory viruses, is archetypically complex because it involves the expression of hundreds of genes and multiple interacting pathways and, moreover, additional posttranscriptional and translational regulation. Thus, it seems unlikely that the generation of an allergic phenotype under these conditions could be conceptualized linearly or attributed to a single critical signal. This notion has implications for the design and expectations of therapeutic strategies to prevent viral-induced allergic asthma.

We thank Tina Walker and Ashley E. Keller for technical help and Marie Bailey for administrative assistance.

This work was supported in part by the Canadian Institute of Health Research and MedImmune LLC. A.A.-G. holds a scholar award from the King Abdullah University of Science and Technology, and M.J. holds a Senior Canada Research Chair in Immunobiology of Respiratory Disease and Allergy.

The sequences presented in this article have been submitted to the European Molecular Biology Laboratory-European Bioinformatics Institute ArrayExpress database (http://www.ebi.ac.uk/microarray-as/ae) under accession number E-MEXP-3325.

The online version of this article contains supplemental material.

Abbreviations used in this article:

CLR

C-type lectin receptor

DC

dendritic cell

EP

early phase

Flu

influenza A virus

Flu+HDM

house dust mite in the context of influenza A virus infection

GO

gene ontology

HDM

house dust mite

LP

late phase

qPCR

quantitative real-time PCR.

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A.A.H. and R.K. are employees of MedImmune, LLC. A.J.C. is an employee of Pfizer, Inc.