分子生物学
IVD分子诊断
细胞培养与分析
蛋白研究
细胞因子
重组蛋白
抗体
高通量测序建库
病原检测UCF系列
生物医药
工具酶
抑制剂激活剂与常用试剂
仪器
耗材

Integrating Magnetic-Bead-Based Sample Extraction and Molecular Barcoding for the One-Step Pooled RT-qPCR Assay of Viral Pathogens without Retesting

Xinyu Zhuang, Zibin Zhao, Xianzhen Feng, Grace C. Y. Lui, Denise Chan, Shui Shan Lee, I-Ming Hsing

Journal:ANALYTICAL CHEMISTRY

IF:7.4

DOI:10.1021/acs.analchem.3c00885

PMID:37005794

Published:2023-04-03

research field:公共卫生分子诊断生物技术病毒学

Abstract

Pooling multiple samples prior to real-time reverse-transcription polymerase chain reaction (RT-PCR) analysis has been proposed as a strategy to minimize expenses and boost test throughput during the COVID-19 pandemic. Nevertheless, the traditional pooling approach cannot be effectively deployed in high-prevalence settings due to the need for secondary tests in the case of a positive pool. In this study, we present a pooling test platform with high adaptability and simplicity that allows sample-specific detection of multiple-tagged samples in a single run without the need for retesting. This was accomplished by labeling distinct samples with predefined ID-Primers and identifying tagged pooled samples using one-step RT-PCR followed by melting curve analysis with rationally designed universal fluorescence- and quencher-tagged oligo probes. Using magnetic beads (MBs), nucleic acid targets from different individuals can be tagged and extracted concurrently and then pooled before RT, eliminating the need for extra RNA extraction and separate RT and enzyme digestion steps in the recently developed barcoding strategies. Pools of six samples (positive and negative) were successfully identified by melting temperature values under two fluorescent channels, with a detection sensitivity of 5 copies/μL. We validated the reproducibility of this assay by running it on 40 clinical samples with a hypothetical infection rate of 15%. In addition, to aid the scenario of large-scale pooling tests, we constructed a melting curve autoreadout system (MCARS) for statistical analysis of melting curve plots to eliminate error-prone manual result readout. Our results suggest that this strategy could be a simple and adaptable tool for alleviating existing bottlenecks in diagnostic pooling testing.

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