Aptamer-Based High-Throughput Screening Model for Efficient Selection and Evaluation of Natural Ingredients against SGIV Infection

Abstract

Singapore grouper iridovirus (SGIV) causes high economic losses in mariculture. Effective drugs for managing SGIV infection are urgently required. Medicinal plant resources are rich in China. Medicinal plants have a long history and significant curative effects in the treatment of many diseases. Reverse-transcription quantitative real-time PCR is the most commonly used method for detecting virus infection and assessing antiviral efficacy with high accuracy. However, their applications are limited due to high reagent costs and complex time-consuming operations. Aptamers have been applied in some biosensors to achieve the accurate detection of pathogens or diseases through signal amplification. This study aimed to establish an aptamer-based high-throughput screening (AHTS) model for the efficient selection and evaluation of medicinal plants components against SGIV infection. Q2-AHTS is an expeditious, rapid method for selecting medicinal plant drugs against SGIV, which was characterized as being dram, high-speed, sensitive, and accurate. AHTS strategy reduced work intensity and experimental costs and shortened the whole screening cycle for effective ingredients. AHTS should be suitable for the rapid selection of effective components against other viruses, thus further promoting the development of high-throughput screening technology.