Fast DNA biosensing based on isothermal amplification, unmodified gold nanoparticles, and smartphone detection

环介导等温扩增 胶体金 计算生物学 多路复用 重组酶聚合酶扩增 化学 纳米技术 DNA 计算机科学 纳米颗粒 材料科学 生物 生物化学 遗传学
作者
Luis Antonio Tortajada-Genaro,María Isabel Lucío,Ángel Maquieira
出处
期刊:Food Control [Elsevier BV]
卷期号:137: 108943-108943 被引量:2
标识
DOI:10.1016/j.foodcont.2022.108943
摘要

The protection of the consumer against foodborne illnesses and fraudulent practices requires methods capable of detecting critical components. Classical instrumental and DNA-based technologies have assay time, portability, and cost limitations. Thus, food control needs alternative methodologies for massive and cost-effective screening. Herein, we report an instrument-free method based on detecting genes that encode proteins related to food allergies and ingredients associated with illegal practices. Tailed recombinase polymerase amplification (tailed-RPA) provided the selective isothermal amplification of target regions. A reproducible and fast optical detection was developed based on the salt-induced aggregation of 15 nm gold nanoparticles (AuNPs). The target presence was directly observed (naked-eye detection) and quantified using a smartphone and RGB image decomposition. The advantages arise from the effective formation of a hybrid complex between non-functionalized nanoparticles and amplification products with a single-strand tail, featuring short incubation time, simplicity, and low sample and reagent volumes. As proof of concept, two targets were determined: trnL gene and ITS region. The first sequence is located in the chloroplast genome of cereals and is valuable to control the adulteration of meat products. The second is a fragment common to the three main gluten-containing cereals, applicable to the indirect detection of this allergen. The novelty also is the integration of a low-cost assay platform and a straightforward interpretation system to foster its implementation in the industry. The RPA-AuNP assay offered a good sensitivity (genomic DNA 0.8 ng), selectivity (absence of unspecific response), reproducibility (standard deviation 2–11%), and accuracy in marketed food products (100%). Therefore, a competitive biosensing system enables better control according to food industry/consumers demands from Farm to Fork strategy.
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