Lung miRNA profiles show a time‐of‐day response in house dust mite‐induced allergic asthma in mice

To the Editor,

Asthma is a chronic inflammatory lung disease that shows a time‐of‐day effect (increased airway inflammation and altered lung function) on the severity of the disease.¹ Recent studies support the functional role of miRNAs in the molecular pathophysiology of asthma phenotypes/endotypes², ³ through the post‐transcriptional gene regulation of key signaling pathways and cellular processes in human airways, immune cells in asthmatics, and in mouse model of allergic asthma.^4–6 However, whether a rhythmic change in expression of miRNAs is responsible for the time‐of‐day effects observed during asthma and its exacerbations are not known.

In this study, we utilized high‐throughput miRNA and mRNA profiling using NanoString to determine the time‐of‐day effects using the house dust mite (HDM)‐induced allergic asthma model. We demonstrate that timed dosing of HDM at Zeitgeber time (ZT0: 6:00 a.m or ZT12: 6:00 p.m) shows differentially expressed (DE) miRNAs and their predicted mRNAs that are reflective of the asthma phenotype. DE analysis revealed a strong time‐of‐day difference in the miRNA expression at ZT0 versus ZT12 HDM exposed mice compared to PBS (control). We found 6 miRNAs (downregulated: miR‐125b‐5p, miR‐125a‐5p, miR‐150, miR‐23a, miR‐23b and miR‐15b) and 3 miRNAs (upregulated: miR‐652, miR‐200b and miR‐200c) significantly in HDM versus PBS at ZT0 (Figure 1A,B), and 21 miRNAs downregulated and 17 miRNAs upregulated significantly in HDM versus PBS at ZT12 (Figure 1C,D). Hierarchical cluster analysis of DE miRNAs in HDM versus PBS groups at ZT0 and ZT12 pairwise comparison along with their fold change/ratio, p‐value and the false discovery rate (FDR) adjusted p‐value is provided (Figure 1A–D).

FIGURE 1.

miRNA expression signatures in PBS (control) and house dust mite (HDM) exposed mouse lung. (A) Heat map shows unsupervised hierarchical clustering of nine differentially expressed (DE) miRNAs in HDM versus PBS exposed mouse lung at ZT0 analyzed by Morpheus tool. (B) Pairwise comparison analysis performed by nSolver 4.0 software showing DE miRNAs in HDM versus PBS at ZT0. (C) Heat map shows unsupervised hierarchical clustering of 38 DE miRNAs in HDM versus PBS exposed mouse lung at ZT12 analyzed by Morpheus tool. (D) Pairwise comparison analysis performed by nSolver 4.0 software showing DE miRNAs in HDM versus PBS at ZT12. Data are shown as fold change/ratio, p‐value (p < 0.05) and FDR adjusted p‐value < 1 (n = 6/group/time point)

When we compared the DE miRNAs in HDM versus PBS group, we found the same 6 miRNAs (downregulated) and 3 miRNAs (upregulated) at ZT0 pairwise comparisons were among the common miRNAs DE at both ZT0 and ZT12 (Figure S1A,B). Additionally, unsupervised clustering and Principal Component Analysis (PCA) of normalized counts from HDM versus PBS groups at ZT0 and ZT12 showed clusters separated based on the treatment groups (Figure S1C–D). Hierarchical cluster analysis of normalized counts from HDM versus PBS groups at ZT0 and ZT12 revealed close clustering of all DE miRNAs in PBS and HDM groups at ZT12 except for few HDM ZT0 samples that were clustered with either the PBS ZT0 or HDM ZT12 (Figure S1E).

To assess the degree of DE miRNAs in the lung of HDM versus PBS at ZT0 and ZT12, we performed multiple comparison analyses. Several of the miRNAs were either significantly downregulated or upregulated in PBS and HDM inter‐group comparisons (Figures 2A and S2A,–B). Eleven DE miRNAs (downregulated) and 8 DE miRNAs (upregulated) in the HDM‐exposed group significantly compared to PBS at ZT12, and 3 DE miRNAs significantly upregulated in the HDM‐exposed group compared to PBS at ZT0 (Figure S2A,B). However, several DE miRNA targets were either downregulated (2 miRNAs: miR‐720 and miR‐1944) or upregulated (9 miRNAs: miR‐151‐5p, miR‐199a‐3p, miR‐30c, let‐7d, miR‐15a, miR‐181a, miR‐25, let‐7e, and miR‐126‐3p) in PBS group at ZT0 versus ZT12 comparison (Figure S2A,B). The pairwise comparison data for HDM versus PBS at ZT0 and ZT12 revealed 9 miRNAs DE at ZT0 and 38 miRNAs at ZT12 among HDM versus PBS groups (Figure S3A,C). Statistical differences in PBS at ZT0 versus ZT12 and HDM ZT0 versus ZT12 pairwise comparison revealed several miRNAs DE were among those identified in HDM versus PBS pairwise comparison at ZT12 (Figure S1F). Overall, 21 miRNAs were significantly downregulated and 17 miRNAs upregulated in HDM versus PBS at ZT12 pairwise comparison (Figure S3A,C). These data clearly indicate that miRNA expression changes in lung tissues in a time‐dependent manner and that HDM exposure significantly affects the DE miRNAs at ZT12 versus ZT0.

FIGURE 2.

Representative data from differentially expressed miRNAs and selected mRNA targets were analyzed by NanoString nCounter analysis. (A) DE 9 miRNAs were significantly downregulated at ZT0 and ZT12 pairwise comparison. We observed a time‐of‐day effect in the expression of miRNAs in house dust mite (HDM) versus PBS exposed mouse lung. (B) Selected miRNA‐mRNA targets predicted by Ingenuity Pathway Analysis were further validated using NanoString mouse Myeloid Innate Immunity Panel and qPCR analysis (il13 mRNA). Normalized counts data are presented as analyzed by nSolver 4.0 software. (C) Bioinformatic analysis of DE miRNAs downregulated or upregulated in HDM exposed group at ZT12 using DIANA‐miRPath v3.0. KEGG pathways marked in red color were pathways identified by miRPath analysis of DE miRNAs in HDM versus PBS at ZT12. Data are shown as mean ± SEM (n = 6/group; *p < 0.05, **p < 0.01, ***p < 0.001, significant compared to respective PBS control; ^# p < 0.05, ^## p < 0.01, ^### p < 0.001, significant compared to PBS or HDM from ZT0; 2way ANOVA with Tukey's multiple comparison test)

Ingenuity Pathway Analysis (IPA) was used to predict mRNA target genes for DE miRNAs at ZT12 HDM versus PBS group. The target genes for validation were selected based on disease(s) and species filters focusing on inflammatory response and respiratory disease from our findings. The data from the NanoString Myeloid Innate Immunity panel was utilized to validate the miRNA‐mRNA targets identified by IPA. The predicted mRNA target genes for DE miRNAs were validated based on normalized counts and qPCR analysis as summarized (Figures 2B and S4A). The predicted miRNAs (downregulated) and associated mRNA target genes (upregulated) were validated by NanoString or qPCR analyses include il13, tnfrsf1b, arg1, fgf2, fut4, ccr2, vamp2, adamts3, cxcl10, cxcr5, yap1, ptgs2, ikbke, hla‐a, prg2, lat2, tlr2, pdcd1lg2, and usp18. These miRNA‐mRNA predictions were based on IPA and miRPath (DIANA tool), their gene annotation to specific signaling pathways (cytokine/chemokine signaling, growth factor signaling, Th2 activation, etc.) including their cell type associated (eosinophils, mast cells, monocytes ‐macrophages, neutrophils, and dendritic cells) with allergic asthma are summarized (Table S1, Figures 2C, and S4A–C).

Bioinformatics analyses with the DIANA miRPath tool revealed potential pathways regulated by miRNAs in HDM exposed group at ZT12. The top three KEGG pathways identified based on the number of genes regulated by downregulation of miRNAs were focal adhesion, MAPK and FoxO signaling pathways, while the number of genes regulated by upregulation of miRNAs belongs to Regulation of actin cytoskeleton, PI3K‐AKT and MAPK signaling pathways (Figures 2C and S4B). We speculate that the time‐of‐day difference in miRNA expression observed in allergic asthma may be due to dysregulation of core circadian clock genes (clock, bmal1, nr1d1, per2, cry2, rorα, npas2, etc.) that was among the KEGG pathways predicted by miRPath analysis that show >1 miRNAs interacting with at least 15 circadian genes (Figure S4C).

Overall, we found a significant time‐dependent change in the DE miRNAs in HDM versus PBS‐exposed mouse lungs. DE miRNAs at ZT12 based IPA‐predicted genes involved in cytokine/chemokine signaling, growth factor signaling and Th2 activation that was further validated by mouse myeloid innate immunity panel/qPCR analyses. miRPath analysis supports our findings from DE miRNAs that were linked to KEGG pathways belonging to asthma and inflammation. This study for the first time shows a time‐of‐day difference in miRNA expression in the lung following HDM exposure that may directly or indirectly involve the interaction of circadian clock genes that need to be further investigated using genetic and pharmacological approaches in a mouse model of asthma.

CONFLICT OF INTERESTS

The authors declare no competing interests.

AUTHOR CONTRIBUTIONS

Isaac Kirubakaran Sundar and Ashokkumar Srinivasan: designed the study and conducted the experiments; Isaac Kirubakaran Sundar: primarily responsible for the experimental design, critical interpretation of the data, preparation of figures, and writing of the entire manuscript. All the authors checked the content and approved the final version of the manuscript.

Supporting information

Supporting Information S1

Supporting Information S2

Supporting Information S3

Sundar IK, Srinivasan A. Lung miRNA profiles show a time‐of‐day response in house dust mite‐induced allergic asthma in mice. Clin Transl Allergy. 2021; 1‐XXX. 10.1002/clt2.12057