Integrating Magnetic-Bead-Based Sample Extraction and Molecular Barcoding for the One-Step Pooled RT-qPCR Assay of Viral Pathogens without Retesting.
Anal Chem
; 95(14): 6182-6190, 2023 04 11.
Article
en En
| MEDLINE
| ID: mdl-37005794
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.
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
COVID-19
Tipo de estudio:
Diagnostic_studies
/
Guideline
/
Prognostic_studies
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Risk_factors_studies
Límite:
Humans
Idioma:
En
Año:
2023
Tipo del documento:
Article