Assessment of the inhibition of Dengue virus infection by carrageenan via real-time monitoring of cellular oxygen consumption rates within a microfluidic device

利用微流控装置实时监测细胞耗氧率,评估角叉菜胶对登革病毒感染的抑制作用

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Abstract

A microfluidic device combined with a light modulation system was developed to assess the inhibitory effect of carrageenan on Dengue virus (DENV) infection via real-time monitoring of cellular oxygen consumption rates (OCRs). Measuring cellular OCRs, which can reflect cellular metabolic activity, enabled us to monitor the process of viral infection in real time and to rapidly determine the antiviral activity of potential drugs/chemical compounds. The time variation of the cellular OCR of single cells that were infected in situ by DENV at different multiplicity of infection (m.o.i.) values was first successfully measured within a microfluidic device. The influence of the timing of carrageenan treatment on DENV infection was then examined by real-time monitoring of cellular OCRs in three groups. Cells that were pre-treated with carrageenan and then infected with DENV served as a pre-treatment group, cells to which carrageenan was added simultaneously with DENV served as a virucide group, and cells that were pre-infected with DENV and then treated with carrageenan served as a post-treatment group. By monitoring cellular OCRs, we could rapidly evaluate the inhibitory effect of carrageenan on DENV infection, obtaining a result within 7 h and showing that carrageenan had strong and effective anti-DENV activity in the three groups. In particular, a strong inhibitory effect was observed in the virucide group. Moreover, once the virus enters host cells in the post-treatment group, the immediate treatment with carrageenan for the infected cells has higher efficiency of antiviral activity. Our proposed platform enables to perform time-course or dose-response measurements of changes in cellular metabolic activity caused by diseases, chemical compounds, and drugs via monitoring of the cellular OCR, with rapid and real-time detection. This approach provides the potential to study a wide range of biological applications in cell-based biosensing, toxicology, and drug discovery.

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