Recently, Professor Malong Ma’s research group at Tianjin University of Science and Technology reported a novel method for visual detection of foodborne pathogens based on Argonaute protein, which integrates Tag-specific primer extension and exonuclease I (Exo I), called NOTE-Ago. This method utilizes the programmability and sequence specificity of Argonaute to achieve one-step cleavage detection of foodborne pathogens, and has been successfully applied to detect food (milk, eggs) and other complex samples for foodborne pathogen contamination. The related results were published in the international authoritative journal Journal of Hazardous Materials, 2023, 454, 131485 (IF=14.224).Background Introduction
Foodborne pathogens are the main cause of microbial contamination in food safety. In recent decades, there has been a sharp increase in foodborne disease outbreaks caused by the consumption of food contaminated with harmful bacteria, leading to high morbidity and mortality worldwide. The detection of harmful bacteria in food has become an important factor in understanding and preventing food safety and public health issues. Therefore, establishing a highly sensitive and rapid nucleic acid sensing platform is crucial for identifying different types of foodborne pathogens.
Argonaute is a programmable and targeted nuclease, a highly conserved protein that has defense and regulatory functions in both eukaryotes and prokaryotes. Argonaute can use complementary single-stranded “guide RNA” or “guide DNA” based on Watson-Crick base pairing to cut invasive RNA or DNA. The recognition and cleavage of pAgo are guided by DNA or RNA, but not limited to the PAM sequence in the target. Recently, due to the programmability and high specificity of Argonaute, nucleic acid detection technologies based on PfAgo (Pyrococcus furiosus Argonaute) and TtAgo (Thermus thermophilus Argonaute) have been continuously researched and established. Compared to the CRISPR/Cas system, Argonaute-mediated biosensors also have high specificity for nucleic acid recognition, without relying on the limitations of the PAM sequence. Therefore, it has the advantage of being easier to achieve multiplex detection.Main Content of the ResearchIn this study, the authors established a biosensing strategy based on Argonaute that integrates Tag-specific primer extension and exonuclease I (Exo I), which we named NOTE-Ago (Novel and One-step cleavage method based on Argonaute by integrating Tag-specific primer extension and Exponuclease I). In this method, Tag-specific primers were used to amplify the invA gene of Salmonella Typhi and the nuc gene of Staphylococcus aureus, and the remaining primers were digested with Exo I. The amplicons were then used as guide DNA for PfAgo. Therefore, the FAM-BHQ1 reporter probe can be cleaved by PfAgo, resulting in a change in fluorescence intensity. Through this strategy, the target nucleic acid signal can be cleverly converted into a fluorescence signal. The detection limit of the NOTE-Ago method can be as low as 1 CFU/mL, with a dynamic range of 1 to 108 CFU/mL. The satisfactory selectivity of the NOTE-Ago method further promotes its application in detecting food samples contaminated with Salmonella Typhi and Staphylococcus aureus. This work enriches the detection category based on Argonaute and provides a method for ultra-sensitive detection of bacteria that is one-step cleavage and rebuilding-free.The detection principle of NOTE-Ago is shown in Scheme 1. (A) The sensing strategy of NOTE-Ago for detecting foodborne pathogens and the time allocation required; (B) The previous two-step cleavage detection principle based on Ago; (C) A schematic diagram of the previous PCR-based detection.As shown in Figure 1, the feasibility verification and condition optimization of the NOTE-Ago sensing strategy. (A and B) Each sample at an excitation wavelength of 484nm, with emission wavelengths from 500nm to 650nm fluorescence spectrum, with a fluorescence peak at a wavelength of 529nm. (C) Fluorescence images of the samples taken by the fluorescence detection device and converted grayscale photos. (D) Grayscale readings of each sample. (E)PfAgo reaction system optimization of the amount of amplification product added. Optimization of the concentration of PfAgo in the reaction system (F), the concentration of the reporter probe (G), and the reaction time of PfAgo. (ΔFL=F−F0; F represents the measured fluorescence intensity after the reaction, F0 represents the background fluorescence intensity. “+” indicates the presence of the target or Exo I, “-” indicates the absence of the target or Exo I).Figure 2: Performance analysis of the proposed NOTE-Ago method. (A and B) Fluorescence spectrum analysis of different concentrations of Salmonella Typhi and Staphylococcus aureus samples at an excitation wavelength of 484nm and emission wavelengths from 500nm to 650nm. (C) Fluorescence readings of different concentrations of Salmonella Typhi and Staphylococcus aureus samples at an emission wavelength of 529nm. (D) Selectivity analysis of the proposed NOTE-Ago method for detecting Salmonella Typhi and Staphylococcus aureus. The concentrations of Salmonella Typhi, Staphylococcus aureus, and interfering cells were 108CFU/mL.(ΔFL=F−F0; F represents the fluorescence intensity measured after the reaction, F0 represents the background fluorescence intensity).As shown in Figure 3, a comparison of the proposed NOTE-Ago method with qPCR in detecting the capacity of samples contaminated with Salmonella Typhi and Staphylococcus aureus. (A and B) Analysis of Salmonella Typhi detected by the NOTE-Ago method, SBYR Green method, and TaqMan method. (C) ROC curve analysis of Salmonella Typhi detection results. (D and E) Analysis of Staphylococcus aureus detected by the NOTE-Ago method, SBYR Green method, and TaqMan method. (F) ROC curve analysis of Staphylococcus aureus detection results. (ΔFL=F−F0; F represents the fluorescence intensity measured after the reaction, F0 represents the background fluorescence intensity).As shown in Figure 4, the use of the NOTE-Ago method to detect Salmonella Typhi and Staphylococcus aureus in orange juice. (A) Fluorescence readings of Salmonella Typhi and Staphylococcus aureus detection results in orange juice samples. (B) Fluorescence images of Salmonella Typhi (a) and Staphylococcus aureus (b) in orange juice samples taken by the fluorescence detection device. (C) Grayscale readings of Salmonella Typhi and Staphylococcus aureus detection results in orange juice samples. (D) Converted grayscale photos of Salmonella Typhi (a) and Staphylococcus aureus (b). (E and F) Detection results of Salmonella Typhi and Staphylococcus aureus in orange juice samples using plate counting method. (ΔFL=F−F0; F represents the fluorescence intensity measured after the reaction, F0 represents the background fluorescence intensity).As shown in Figure 5, the use of the NOTE-Ago method to detect Salmonella Typhi and Staphylococcus aureus in eggs. (A) Fluorescence readings of Salmonella Typhi and Staphylococcus aureus detection results in egg samples. (B) Fluorescence images of Salmonella Typhi (a) and Staphylococcus aureus (b) in egg samples taken by the fluorescence detection device. (C) Grayscale readings of Salmonella Typhi and Staphylococcus aureus detection results in egg samples. (D) Converted grayscale photos of Salmonella Typhi (a) and Staphylococcus aureus (b). (E and F) Detection results of Salmonella Typhi and Staphylococcus aureus in egg samples using plate counting method. (ΔFL=F−F0; F represents the fluorescence intensity measured after the reaction, F0 represents the background fluorescence intensity).Conclusion
This work proposes a universal, rebuilding-free detection platform that combines Tag-specific primers and PfAgo to detect foodborne pathogens such as Salmonella Typhi and Staphylococcus aureus in an ultra-sensitive manner, called NOTE-Ago. The proposed biosensor demonstrates excellent detection performance, with the lowest LoD value (1 CFU/mL) and the widest detection range from 100 to 108 CFU/mL. The designed fluorescence detection device serves as a tool for visualizing fluorescence signals, further enhancing the field detection capability of the NOTE-Ago method. Furthermore, the NOTE-Ago method has the ability to distinguish detection targets among multiple pathogens. Finally, the satisfactory selectivity of the NOTE-Ago method has also been confirmed by food samples contaminated with Salmonella Typhi and Staphylococcus aureus. This work expands the detection category based on Argonaute and provides a new, rebuilding-free sensing platform for foodborne pathogen detection that is simple, sensitive, accurate, and has the potential for multiplex detection.
Original Link
https://doi.org/10.1016/j.jhazmat.2023.131485
Author ProfileMalong Ma, male, born in 1983, obtained his PhD from the University of Edinburgh in the UK, and has conducted postdoctoral research at the University of St Andrews in the UK. He is currently a professor at the School of Biological Engineering, Tianjin University of Science and Technology, a doctoral supervisor, deputy director of the Key Laboratory of Industrial Microbiology of the Ministry of Education, and PI of the National Key Laboratory of Food Nutrition and Safety co-built by the province and the ministry. In the past five years, he has presided over two projects of the National Natural Science Foundation of China, the Tianjin Overseas High-level Talent Introduction Project, Tianjin Science and Technology Plan Project, Tianjin Natural Science Foundation, Tianjin Key R&D Project, etc. In recent years, he has published nearly 80 SCI papers, of which 72 are published in journals of the I and II districts. The total impact factor of the articles is >560, with more than 55 articles having an impact factor >5, and 16 articles having an impact factor >10; the total citation of the articles is nearly 2000 times, with an H-index >25. His main research areas include detection of food hazards and bioactivity of foodborne natural products. He was awarded the “Overseas High-level Talent Introduction” in Tianjin in 2015, the first level of the “131” Innovation Talent in Tianjin in 2018, the “Young and Middle-aged Science and Technology Innovation Leading Talents” in Tianjin in 2019, the national silver award of the first national postdoctoral innovation and entrepreneurship competition in 2021, the “Tianjin Youth May Fourth Medal” in 2022, and other honors such as Tianjin Excellent Scientific and Technological Workers. The laboratory has good experimental conditions and sufficient teacher guidance, and welcomes young scholars who are interested in pursuing master’s and doctoral degrees and conducting postdoctoral research to contact and communicate; contact information: [email protected].Food Safety Research Achievements|Scholar Research Achievements（Click to view Scholar Name Check）
Thanks Ming Yong Academician Sun Bao Guo Academician Chen Jian Academician Sun Da Wen Academician
Zhu Bei Wei Academician Zhou Guang Hong Associate Jiang Lian Zhou Associate Chen Feng Associate
Nie Shao Ping Associate Xue Chang Hu Associate Zhao Mou Ming Associate Zhao Guo Hua Associate Li Bin Associate Wang Shu Jun Associate Liu Xue Bo Associate Tang Chuan He Associate Zhang Min Associate Xie Jian Hua Associate Chen Wei Associate Tan Ming Qian Associate Zhang Yu Hao Associate Wang Jing Associate Xu Yan Associate Li Chun Bao Associate Kong Bao Hua Associate Chen Shi Guo Associate Wang Xing Guo Associate Gao Yan Xiang Associate Huang Qiang Associate Fang Ya Peng Associate Wang Yong Associate Li Yuan Fa Associate Zhang Hong Yin Associate Sheng Zhan Wu Researcher Jiang Zhan Mei Associate
Zhang De Quan Researcher Qi Xiang Hui Associate Zheng Jia Rong Associate Chen Yi Ping Professor
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