Abstract：
BACKGROUND: Bacterial spores are the main potential hazard in medium- and high-temperature sterilized meat products, and their germination and subsequent reproduction and metabolism can lead to food spoilage. Moreover, the spores of some species pose a health and safety threat to consumers. The rapid detection, prevention, and control of bacterial spores has always been a scientific problem and a major challenge for the medium and high-temperature meat industry. Early and sensitive identification of spores in meat products is a decisive factor in contributing to consumer health and safety.
RESULTS: In this study, we developed a novel and stable Ag@AuNP array substrate by using a two-step synthesis approach and a liquid-interface self-assembly method that can directly detect bacterial spores in actual meat product samples without the need for additional in vitro bacterial culture. The results indicate that the Ag@AuNP array substrate exhibits high reproducibility and Raman enhancement effects (1.35 × 105). The differentiation in the Surface enhanced Raman scattering (SERS) spectra of five bacterial spores primarily arises from proteins in the spore coat and inner membrane, peptidoglycan of cortex, and Ca2⁺-DPA within the spore core. The correct recognition rate of linear discriminant analysis for spores in the meat product matrix can reach 100 %. The average recovery accuracy of the SERS quantitative model was at around 101.77 %, and the limit of detection can reach below 10 CFU/mL.
CONCLUSIONS: It provides a promising technological strategy for the characteristic substance analysis and timely monitoring of spores in meat products.
RESULTS: In this study, we developed a novel and stable Ag@AuNP array substrate by using a two-step synthesis approach and a liquid-interface self-assembly method that can directly detect bacterial spores in actual meat product samples without the need for additional in vitro bacterial culture. The results indicate that the Ag@AuNP array substrate exhibits high reproducibility and Raman enhancement effects (1.35 × 105). The differentiation in the Surface enhanced Raman scattering (SERS) spectra of five bacterial spores primarily arises from proteins in the spore coat and inner membrane, peptidoglycan of cortex, and Ca2⁺-DPA within the spore core. The correct recognition rate of linear discriminant analysis for spores in the meat product matrix can reach 100 %. The average recovery accuracy of the SERS quantitative model was at around 101.77 %, and the limit of detection can reach below 10 CFU/mL.
CONCLUSIONS: It provides a promising technological strategy for the characteristic substance analysis and timely monitoring of spores in meat products.
摘要：
背景：细菌孢子是中高温灭菌肉制品中的主要潜在危害，它们的发芽以及随后的繁殖和代谢会导致食物腐败。此外，某些物种的孢子对消费者的健康和安全构成威胁。快速检测，预防,细菌孢子的控制一直是科学问题，也是中高温肉类行业面临的重大挑战。早期和敏感地识别肉制品中的孢子是促进消费者健康和安全的决定性因素。
结果：在这项研究中，我们通过使用两步合成方法和液体界面自组装方法开发了一种新颖且稳定的Ag@AuNP阵列基底，该方法可以直接检测实际肉制品样品中的细菌孢子，而无需额外的体外细菌培养。结果表明，Ag@AuNP阵列基板具有较高的再现性和拉曼增强效应（1.35×105）。五种细菌孢子的表面增强拉曼散射（SERS）光谱的差异主要来自孢子涂层和内膜中的蛋白质，皮质的肽聚糖，以及孢子核内的Ca2+DPA。线性判别分析对肉制品基质中孢子的正确识别率可达100%。SERS定量模型的平均回收率在101.77%左右,检出限可达10CFU/mL以下。
结论：它为肉制品中的特征物质分析和及时监测孢子提供了一种有前途的技术策略。
结果：在这项研究中，我们通过使用两步合成方法和液体界面自组装方法开发了一种新颖且稳定的Ag@AuNP阵列基底，该方法可以直接检测实际肉制品样品中的细菌孢子，而无需额外的体外细菌培养。结果表明，Ag@AuNP阵列基板具有较高的再现性和拉曼增强效应（1.35×105）。五种细菌孢子的表面增强拉曼散射（SERS）光谱的差异主要来自孢子涂层和内膜中的蛋白质，皮质的肽聚糖，以及孢子核内的Ca2+DPA。线性判别分析对肉制品基质中孢子的正确识别率可达100%。SERS定量模型的平均回收率在101.77%左右,检出限可达10CFU/mL以下。
结论：它为肉制品中的特征物质分析和及时监测孢子提供了一种有前途的技术策略。
