One-Pot Assay for Rapid Detection of Stenotrophomonas maltophilia by RPA-CRISPR/Cas12a.

IF 3.7 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
ACS Synthetic Biology Pub Date : 2024-10-18 Epub Date: 2024-10-02 DOI:10.1021/acssynbio.4c00481
Jiangli Zhang, Ling Qin, Yingying Chang, Yulong He, Weichao Zhao, Yongyou Zhao, Yanan Ding, Jin Gao, Xiting Zhao
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Abstract

Stenotrophomonas maltophilia (S. maltophilia, SMA) is a common opportunistic pathogen that poses a serious threat to the food industry and human health. Traditional detection methods for SMA are time-consuming, have low detection rates, require complex and expensive equipment and professional technical personnel for operation, and are unsuitable for on-site detection. Therefore, establishing an efficient on-site detection method has great significance in formulating appropriate treatment strategies and ensuring food safety. In the present study, a rapid one-pot detection method was established for SMA using a combination of Recombinase Polymerase Amplification (RPA) and CRISPR/Cas12a, referred to as ORCas12a-SMA (one-pot RPA-CRISPR/Cas12a platform). In the ORCas12a-SMA detection method, all components were added into a single tube simultaneously to achieve one-pot detection and address the problems of nucleic acid cross-contamination and reduced sensitivity caused by frequent cap opening during stepwise detection. The ORCas12a-SMA method could detect at least 3 × 10° copies·μL-1 of SMA genomic DNA within 30 min at 37 °C. Additionally, this method exhibited sensitivity compared to the typical two-step RPA-CRISPR/Cas12a method. Overall, the ORCas12a-SMA detection offered the advantages of rapidity, simplicity, high sensitivity and specificity, and decreased need for complex large-scale instrumentation. This assay is the first application of the one-pot platform based on the combination of RPA and CRISPR/Cas12a in SMA detection and is highly suitable for point-of-care testing. It helps reduce losses in the food industry and provides assistance in formulating timely and appropriate antimicrobial treatment plans.

通过 RPA-CRISPR/Cas12a 快速检测嗜麦芽僵菌的一锅检测法。
嗜麦芽霉单胞菌(S. maltophilia,SMA)是一种常见的机会性病原体,对食品工业和人类健康构成严重威胁。传统的 SMA 检测方法耗时长、检出率低、需要复杂昂贵的设备和专业技术人员操作,而且不适合现场检测。因此,建立一种高效的现场检测方法对制定适当的处理策略和确保食品安全具有重要意义。本研究采用重组酶聚合酶扩增(RPA)和CRISPR/Cas12a相结合的方法,建立了一种快速的SMA单锅检测方法,简称ORCas12a-SMA(one-pot RPA-CRISPR/Cas12a platform)。在 ORCas12a-SMA 检测方法中,所有成分被同时添加到一个试管中,实现了一次检测,解决了分步检测过程中频繁开盖导致的核酸交叉污染和灵敏度降低的问题。ORCas12a-SMA 方法可在 37 ℃ 下 30 分钟内检测到至少 3 × 10° 拷贝-μL-1 的 SMA 基因组 DNA。此外,与典型的两步 RPA-CRISPR/Cas12a 方法相比,该方法具有更高的灵敏度。总之,ORCas12a-SMA 检测法具有快速、简便、灵敏度高、特异性强以及无需复杂的大型仪器等优点。该检测方法是基于 RPA 和 CRISPR/Cas12a 组合的一锅式平台在 SMA 检测中的首次应用,非常适合床旁检测。它有助于减少食品行业的损失,并为制定及时、适当的抗菌治疗计划提供帮助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
8.00
自引率
10.60%
发文量
380
审稿时长
6-12 weeks
期刊介绍: The journal is particularly interested in studies on the design and synthesis of new genetic circuits and gene products; computational methods in the design of systems; and integrative applied approaches to understanding disease and metabolism. Topics may include, but are not limited to: Design and optimization of genetic systems Genetic circuit design and their principles for their organization into programs Computational methods to aid the design of genetic systems Experimental methods to quantify genetic parts, circuits, and metabolic fluxes Genetic parts libraries: their creation, analysis, and ontological representation Protein engineering including computational design Metabolic engineering and cellular manufacturing, including biomass conversion Natural product access, engineering, and production Creative and innovative applications of cellular programming Medical applications, tissue engineering, and the programming of therapeutic cells Minimal cell design and construction Genomics and genome replacement strategies Viral engineering Automated and robotic assembly platforms for synthetic biology DNA synthesis methodologies Metagenomics and synthetic metagenomic analysis Bioinformatics applied to gene discovery, chemoinformatics, and pathway construction Gene optimization Methods for genome-scale measurements of transcription and metabolomics Systems biology and methods to integrate multiple data sources in vitro and cell-free synthetic biology and molecular programming Nucleic acid engineering.
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