Expression of vitamin D receptor in bronchial asthma and its bioinformatics prediction

Abstract

Vitamin D receptors (VDRs) are associated with the occurrence and development of asthma. The aim of the present study was to analyze the secondary structure and B‑cell and T‑cell epitopes of VDR using online prediction software and aid in the future development of a highly efficient epitope‑based vaccine against asthma. Blood samples were collected from peripheral blood of asthmatic children. Reverse transcription quantitative‑polymerase chain reaction (RT‑qPCR) was performed to detect the expression of VDR in the peripheral blood. Mouse models of asthma were established. Hematoxylin and eosin staining was performed to observe the pathological alterations of the lungs of mice. Immunohistochemistry, western blot analysis and RT‑qPCR were performed to detect the expression of VDR in the lungs of asthmatic mice. Online prediction software immune epitope database and analysis resource, SYFPEITHI and linear epitope prediction based on propensity scale and support vector machines were used to predict the B‑cell and T‑cell epitopes and the RasMol and 3DLigandSite were used to analyze the tertiary structure of VDR. RT‑qPCR demonstrated that VDR expression in the peripheral blood of asthmatic children was decreased. Immunohistochemistry, western blotting and RT‑qPCR demonstrated that VDR expression also decreased in the lungs of mouse models of asthma. VDR B‑cell epitopes were identified at 37‑45, 88‑94, 123‑131, 231‑239, 286‑294 and 342‑350 positions of the amino acid sequence and VDR T‑cell epitopes were identified at 125‑130, 231‑239 and 265‑272 positions. A total of six B‑cell epitopes and three T‑cell epitopes for VDR were predicted by bioinformatics, which when validated, may in the future aid in immunological diagnosis and development of a targeted drug therapy for clinical asthma.

Figure 1.

VDR expression in patients and mice. (A) VDR mRNA expression levels in human patients. (B) Pathological observation of bronchial lung tissue in mice by hematoxylin and eosin staining. Inflammatory cells were marked with an arrow. The pulmonary bronchial vessels, pulmonary interstitium and pulmonary alveolar cavity were not shown. Data collected from the control and asthma groups (magnification, ×40). (C) VDR mRNA expression levels in mice. (D) Western blot assay was used to detect VDR protein expression in the bronchial lung tissue. *P<0.05 vs. the control group. VDR, vitamin D receptor; AS, asthma.

Figure 2.

Prediction of the components of the secondary structure of the protein encoded by vitamin D receptor gene. The predictions were made using SOPMA software.

Figure 3.

Prediction of vitamin D receptor B-cell epitopes by online software IEDB. (A) Prediction of antigenicity. (B) Prediction of flexibility of the region. (C) Prediction of surface accessibility. (D) Prediction of linear epitope. Yellow and green areas represent amino acid sequences that may form a B-cell epitope. (E) Prediction of hydrophilicity. (F) Prediction of β angle. Yellow and green areas represent amino acid sequences that may form a B-cell epitope. IEDB, immune epitope database.

Figure 3.

Prediction of vitamin D receptor B-cell epitopes by online software IEDB. (A) Prediction of antigenicity. (B) Prediction of flexibility of the region. (C) Prediction of surface accessibility. (D) Prediction of linear epitope. Yellow and green areas represent amino acid sequences that may form a B-cell epitope. (E) Prediction of hydrophilicity. (F) Prediction of β angle. Yellow and green areas represent amino acid sequences that may form a B-cell epitope. IEDB, immune epitope database.

Figure 3.

Prediction of vitamin D receptor B-cell epitopes by online software IEDB. (A) Prediction of antigenicity. (B) Prediction of flexibility of the region. (C) Prediction of surface accessibility. (D) Prediction of linear epitope. Yellow and green areas represent amino acid sequences that may form a B-cell epitope. (E) Prediction of hydrophilicity. (F) Prediction of β angle. Yellow and green areas represent amino acid sequences that may form a B-cell epitope. IEDB, immune epitope database.

Figure 4.

Prediction of VDR B-cell epitopes by online software LEPS. (A) Surface accessibility. (B) Polarity. (C) β angle. (D) Flexibility of the region. (E) Prediction of the hydrophilcity. (F) Antigenicity. VDR, vitamin D receptor; LEPS, linear epitope prediction based on propensity scale and support vector machines.

Figure 4.

Prediction of VDR B-cell epitopes by online software LEPS. (A) Surface accessibility. (B) Polarity. (C) β angle. (D) Flexibility of the region. (E) Prediction of the hydrophilcity. (F) Antigenicity. VDR, vitamin D receptor; LEPS, linear epitope prediction based on propensity scale and support vector machines.

Figure 5.

Tertiary structure of VDR predicted by online software 3DLigandSite. (A) Tertiary structure simulation model of VDR structure by 3DLigandSite. (B) Anterior view of the group structure. (C) Posterior view of the group structure. VDR, vitamin D receptor.