House dust mite allergen Der f 2 drives IL-6 and GM-CSF expression in airway epithelial cells via p38 MAPK/NF-κB signaling.

OBJECTIVE: Der f 2, a major allergen derived from Dermatophagoides farinae, is a leading cause of allergic asthma. IL-6 and GM-CSF play essential roles in the exacerbation of asthma. However, the mechanical act by which Der f 2 mediates the expression of IL-6, IL-8, and GM-CSF in airway epithelial cells remains incompletely elucidated. Herein, we aimed to explore the effect of Der f 2 on IL-6 and GM-CSF expression in the human airway epithelial cell BEAS-2B and A549. METHODS: Recombinant Der f 2 (rDf2) was acquired using Pichia pastoris. BEAS-2B and A549 cells were used as cell model. The expression of genes and proteins and the involvement of the signaling cascade were assessed using RT-PCR, quantitative real-time PCR (qPCR), Western blotting, and ELISA, respectively. RESULTS: Our findings showed that rDf2 significantly induced mRNA expression and protein production of IL-6 and GM-CSF in BEAS-2B and A549 cells. In contrast, rDf2 did not influence IL-8 expression or production in both cells. Mechanistic studies revealed that rDf2 triggered activation of the p38 MAPK and JNK. Inhibition of p38, but not JNK, significantly attenuated rDf2-induced IL-6 and GM-CSF expression and production. CONCLUSION: This study demonstrates that Der f 2 promotes the expression and production of the pro-inflammatory cytokines IL-6 and GM-CSF in airway epithelial cells via activation of the p38 signaling pathway. These findings provide insights into the molecular mechanisms that Der f 2 may exacerbate airway inflammation.

SSRTool: A web tool for evaluating RNA secondary structure predictions based on species-specific functional interpretability.

RNA secondary structures can carry out essential cellular functions alone or interact with one another to form the hierarchical tertiary structures. Experimental structure identification approa ches can show the in vitro structures of RNA molecules. However, they usually have limits in the resolution and are costly. In silico structure prediction tools are thus primarily relied on for pre-experiment analysis. Various structure prediction models have been developed over the decades. Since these tools are usually used before knowing the actual RNA structures, evaluating and ranking the pile of secondary structure predictions of a given sequence is essential in computational analysis. In this research, we implemented a web service called SSRTool (RNA Secondary Structure prediction Ranking Tool) to assist in the ranking and evaluation of the generated predicted structures of a given sequence. Based on the computed species-specific interpretability significance in four common RNA structure-function aspects, SSRTool provides three functions along with visualization interfaces: (1) Rank user-generated predictions. (2) Provide an automated streamline of structure prediction and ranking for a given sequence. (3) Infer the functional aspects of a given structure. We demonstrated the applicability of SSRTool via real case studies and reported the similar trends between computed species-specific rankings and the corresponding prediction F1 values. The SSRTool web service is available online at https://cobisHSS0.im.nuk.edu.tw/SSRTool/, http://cosbi3.ee.ncku.edu.tw/SSRTool/, or the redirecting site https://github.com/cobisLab/SSRTool/.