Issue 11, 2023

Ultra-fast, sensitive and low-cost real-time PCR system for nucleic acid detection

Abstract

Nucleic acid detection directly identifies the presence of pathogenic microorganisms and has various advantages, such as high sensitivity, commendable specificity and a short window period, and has been widely used in many fields, such as early tumor screening, prenatal diagnosis and infectious disease detection. Real-time PCR (polymerase chain reaction) is the most commonly used method for nucleic acid detection in clinical practice, but it always takes about 1–3 hours, severely limiting its application in particular scenarios such as emergency testing, large-scale testing and on-site testing. To solve the time-consuming problem, a real-time PCR system based on multiple temperature zones was proposed, which realized the speed of temperature change of biological reagents from 2–4 °C s−1 to 13.33 °C s−1. The system integrates the advantages of fixed microchamber-type and microchannel-type amplification systems, including a microfluidic chip capable of fast heat transfer and a real-time PCR device with a temperature control strategy based on the temperature difference. The detection of HCMV biological samples using the real-time PCR system in this research took only 15 min, which was 75% shorter compared to the commercial qPCR instrument such as BIO-RAD, and the detection sensitivity remained essentially the same. The system could complete nucleic acid detection within 9 min under extreme conditions, characterized by fast detection speed and high sensitivity, providing a promising solution for ultra-fast nucleic acid detection.

Graphical abstract: Ultra-fast, sensitive and low-cost real-time PCR system for nucleic acid detection

Supplementary files

Article information

Article type
Paper
Submitted
01 Mar 2023
Accepted
26 Apr 2023
First published
09 May 2023

Lab Chip, 2023,23, 2611-2622

Ultra-fast, sensitive and low-cost real-time PCR system for nucleic acid detection

S. Huang, Y. An, B. Xi, X. Gong, Z. Chen, S. Shao, S. Ge, J. Zhang, D. Zhang and N. Xia, Lab Chip, 2023, 23, 2611 DOI: 10.1039/D3LC00174A

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