| Literature DB >> 35746713 |
Hongling Wei1, Zhongbao Guo2, Yu Long3, Mingzhu Liu1, Jun Xiao2, Lin Huang1, Qing Yu1, Pengfei Li1.
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.Entities:
Keywords: Singapore grouper iridovirus; antiviral effect; aptamer; high-throughput screening; medicinal plants components
Mesh:
Substances:
Year: 2022 PMID: 35746713 PMCID: PMC9227401 DOI: 10.3390/v14061242
Source DB: PubMed Journal: Viruses ISSN: 1999-4915 Impact factor: 5.818
Primers for detecting SGIV infection by RT-qPCR.
| Primer | Sequences |
|---|---|
| qMCP-F | 5′-GCACGCTTCTCTCACCTTCA-3′ |
| qMCP-R | 5′-AACGGCAACGGGAGCACTA-3′ |
| β-actin-F | 5′-TACGAGCTGCCTGACGGACA-3 |
| β-actin-R | 5′-GGCTGTGATCTCCTTCTGCA-3′ |
Figure 1Flow chart of Q2-AHTS and RT-qPCR technology. (a) Flow chart of AHTS technology. (b) Flow chart of qPCR technology.
Figure 2Monitoring SGIV infection by FAM-Q2. (a) Monitoring different MOI of SGIV infection by FAM-Q2. (b) Monitoring SGIV (MOI = 0.5) with different infection time by FAM-Q2. Fluorescence on SGIV-infected cells could be detected at 24 hpi, and the fluorescence increased over time. Results are presented as mean ± SD of three independent experiments (** p < 0.01). (c) LSCM showed the specific binding of FAM-Q2 to SGIV-infected cells but not to normal GS cells.
Figure 3Monitoring SGIV infection by RT-qPCR. (a) RT-qPCR detected SGIV (MOI = 0.125) infection as early as 6 hpi. (b) RT-qPCR detect SGIV (MOI = 0.5) infection at 48hpi. Results are presented as mean ± SD of three independent experiments (** p < 0.01).
Figure 4Antiviral analysis of 20 medical plant components against SGIV infection. AHTS results showed that fluorescence of target cells incubated with both SGIV and all components (Nos. 1–20) decreased obviously. Results are presented as mean ± SD of three independent experiments (** p < 0.01).
Figure 5Antiviral analysis of 20 medicinal plant components against SGIV infection. RT-qPCR showed that the expression of MCP gene decreased after treatment with components 1–20. Results are presented as mean ± SD of three independent experiments (** p < 0.01).
Figure 6Inhibitory percentage of medicinal plant components against SGIV infection analyzed by Q2-AHTS (a) and RT-qPCR (b).