CRISPR‐Cas‐based detection for food safety problems: Current status, challenges, and opportunities

清脆的 风险分析(工程) 食品安全 生化工程 数据科学 计算机科学 生物 业务 工程类 医学 生物化学 基因 病理
作者
Yaru Li,Shuli Man,Shengying Ye,Guozhen Liu,Long Ma
出处
期刊:Comprehensive Reviews in Food Science and Food Safety [Wiley]
卷期号:21 (4): 3770-3798 被引量:112
标识
DOI:10.1111/1541-4337.13000
摘要

Abstract Food safety is one of the biggest public issues occurring around the world. Microbiological, chemical, and physical hazards can lead to food safety issues, which may occur at all stages of the supply chain. In order to tackle food safety issues and safeguard consumer health, rapid, accurate, specific, and field‐deployable detection methods meeting diverse requirements are one of the imperative measures for food safety assurance. CRISPR‐Cas system, a newly emerging technology, has been successfully repurposed in biosensing and has demonstrated huge potential to establish conceptually novel detection methods with high sensitivity and specificity. This review focuses on CRISPR‐Cas–based detection and its current status and huge potential specifically for food safety inspection. We firstly illustrate the pending problems in food safety and summarize the popular detection methods. We then describe the potential applications of CRISPR‐Cas–based detection in food safety inspection. Finally, the challenges and futuristic opportunities are proposed and discussed. Generally speaking, the current food safety detection methods are still unsatisfactory in some ways such as being time‐consuming, displaying unmet sensitivity and specificity standards, and there is a comparative paucity of multiplexed testing and POCT. Recent studies have shown that CRISPR‐Cas–based biosensing is an innovative and fast‐expanding technology, which could make up for the shortcomings of the existing methods or even replace them. To sum up, the implementation of CRISPR‐Cas and the integration of CRISPR‐Cas with other techniques is promising and desirable, which is expected to provide “customized” and “smart” detection methods for food safety inspection in the coming future.
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