Development of high-precision quantitative analysis detection for three yeasts based on CRISPR/Cas12a

Abstract Objectives Yeast plays a crucial role in fermented foods, yet the application of the CRISPR/Cas system for yeast detection has been rarely reported. The objective of this study is to develop a rapid and quantitative detection method for brewing yeast based on the CRISPR-Cas12a system, aiming to achieve higher sensitivity than quantitative real-time polymerase chain reaction (qPCR) assay and fill the gap in the application of CRISPR for yeast detection in fermented foods. Materials and Methods This work established one-step Recombinase Polymerase Amplification (RPA)-CRISPR/Cas12a (ORCC) detection for quantifying yeasts in fermented foods by integrating target amplification and the CRISPR system into a one-pot reaction. Results A numerical standardized definition was established for the quantifiable state in ORCC detection of yeasts. Using ORCC detection, which occurs at 37 °C, absolute quantification of Saccharomyces cerevisiae, Wickerhamomyces anomalus, and Zygosaccharomyces bailii can be completed in less than 45 min. Under optimal conditions, the limits of quantification and the limits of detection for three yeasts were 100 copies/μL and 1 copy/μL, with no cross-reaction observed among non-target yeasts. In the pure yeast samples, ORCC detection of the target yeasts achieved a detection rate of 91.60%–116.57%. In the simulated fermentation samples, the recovery rate for spiked target yeasts using ORCC detection ranged from 92.78% to 106.90%. In the original naturally fermented samples, target yeasts can be quantified by ORCC detection but not by qPCR assay. In the spiked naturally fermented samples, the recovery rates of the qPCR assay were generally lower than those of ORCC detection. Conclusions ORCC detection is simple, rapid, accurate, and highly sensitive for detecting three yeasts in fermented foods. It has significant potential for precisely monitoring yeast growth and fermentation process in various fermentation systems.

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Publication Details

Journal
Food Quality and Safety
Published
2025-01-01
DOI
https://doi.org/10.1093/fqsafe/fyaf017
Primary Topic
Agriculture, Soil, Plant Science
Type
article
Field-Weighted Citation Impact
0.00

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article

Development of high-precision quantitative analysis detection for three yeasts based on CRISPR/Cas12a

Jian Mao, Ruikang Tu, Xiaogang Liu, Jinyu Hu et al.
1 links
Food Quality and Safety
Agriculture, Soil, Plant Science
article

Development of high-precision quantitative analysis detection for three yeasts based on CRISPR/Cas12a

Jian Mao, Ruikang Tu, Xiaogang Liu, Jinyu Hu, Xiaofeng Jiang, Tiantian Liu, Yanfei Xiong, Qilin Yang, Ting Zhao, Shuangping Liu, Caihong Shen, Mingliang Li
article en

Abstract

Abstract Objectives Yeast plays a crucial role in fermented foods, yet the application of the CRISPR/Cas system for yeast detection has been rarely reported. The objective of this study is to develop a rapid and quantitative detection method for brewing yeast based on the CRISPR-Cas12a system, aiming to achieve higher sensitivity than quantitative real-time polymerase chain reaction (qPCR) assay and fill the gap in the application of CRISPR for yeast detection in fermented foods. Materials and Methods This work established one-step Recombinase Polymerase Amplification (RPA)-CRISPR/Cas12a (ORCC) detection for quantifying yeasts in fermented foods by integrating target amplification and the CRISPR system into a one-pot reaction. Results A numerical standardized definition was established for the quantifiable state in ORCC detection of yeasts. Using ORCC detection, which occurs at 37 °C, absolute quantification of Saccharomyces cerevisiae, Wickerhamomyces anomalus, and Zygosaccharomyces bailii can be completed in less than 45 min. Under optimal conditions, the limits of quantification and the limits of detection for three yeasts were 100 copies/μL and 1 copy/μL, with no cross-reaction observed among non-target yeasts. In the pure yeast samples, ORCC detection of the target yeasts achieved a detection rate of 91.60%–116.57%. In the simulated fermentation samples, the recovery rate for spiked target yeasts using ORCC detection ranged from 92.78% to 106.90%. In the original naturally fermented samples, target yeasts can be quantified by ORCC detection but not by qPCR assay. In the spiked naturally fermented samples, the recovery rates of the qPCR assay were generally lower than those of ORCC detection. Conclusions ORCC detection is simple, rapid, accurate, and highly sensitive for detecting three yeasts in fermented foods. It has significant potential for precisely monitoring yeast growth and fermentation process in various fermentation systems.

Food Quality and SafetyVol. 9
Jiangnan University (CN), ITRI International (US), Shaoxing University (CN), Chinese Pharmaceutical Association (CN), Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (CN), Luye Pharma (China) (CN), State Key Laboratory of Food Science and Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 90%
Agriculture, Soil, Plant Science
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