Comprehensive evaluation of poly(I:C) induced inflammatory response in an airway epithelial model

Autor: Rachelle Prantil-Baun, Jeffrey T. Borenstein, T J Mulhern, James C. Comolli, Amanda R. Lever, Patrick Hayden, George R. Jackson, Hyoungshin Park
Rok vydání: 2015
Předmět:
Zdroj: Physiological Reports
ISSN: 2051-817X
DOI: 10.14814/phy2.12334
Popis: Respiratory viruses invade the upper airway of the lung, triggering a potent immune response that often exacerbates preexisting conditions such as asthma and COPD. Poly(I:C) is a synthetic analog of viral dsRNA that induces the characteristic inflammatory response associated with viral infection, such as loss of epithelial integrity, and increased production of mucus and inflammatory cytokines. Here, we explore the mechanistic responses to poly(I:C) in a well-defined primary normal human bronchial epithelial (NHBE) model that recapitulates in vivo functions and responses. We developed functional and quantifiable methods to evaluate the physiology of our model in both healthy and inflamed states. Through gene and protein expression, we validated the differentiation state and population of essential cell subtypes (i.e., ciliated, goblet, club, and basal cells) as compared to the human lung. Assays for total mucus production, cytokine secretion, and barrier function were used to evaluate in vitro physiology and response to viral insult. Cells were treated apically with poly(I:C) and evaluated 48 h after induction. Results revealed a dose-dependent increase in goblet cell differentiation, as well as, an increase in mucus production relative to controls. There was also a dose-dependent increase in secretion of IL-6, IL-8, TNF-α, and RANTES. Epithelial barrier function, as measured by TEER, was maintained at 1501 ± 355 Ω*cm² postdifferentiation, but dropped significantly when challenged with poly(I:C). This study provides first steps toward a well-characterized model with defined functional methods for understanding dsRNA stimulated inflammatory responses in a physiologically relevant manner.
Databáze: OpenAIRE
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