School of Environmental and Chemical Engineering, Shanghai University, Shanghai, 200444, P. R. China.
Center for Molecular Recognition and Biosensing, Joint International Research Laboratory of Biomaterials and Biotechnology in Organ Repair, Ministry of Education, Shanghai Engineering Research Center of Organ Repair, School of Life Sciences, Shanghai University, Shanghai, 200444, P. R. China.
Small. 2024 Nov;20(45):e2403878. doi: 10.1002/smll.202403878. Epub 2024 Jul 26.
Effective identification of multiple cariogenic bacteria in saliva samples is important for oral disease prevention and treatment. Here, a simple colorimetric sensor array is developed for the identification of cariogenic bacteria using single-atom nanozymes (SANs) assisted by machine learning. Interestingly, cariogenic bacteria can increase oxidase-like activity of iron (Fe)─nitrogen (N)─carbon (C) SANs by accelerating electron transfer, and inversely reduce the activity of Fe─N─C further reconstruction with urea. Through machine-learning-assisted sensor array, colorimetric responses are developed as "fingerprints" of cariogenic bacteria. Multiple cariogenic bacteria can be well distinguished by linear discriminant analysis and bacteria at different genera can also be distinguished by hierarchical cluster analysis. Furthermore, colorimetric sensor array has demonstrated excellent performance for the identification of mixed cariogenic bacteria in artificial saliva samples. In view of convenience, precise, and high-throughput discrimination, the developed colorimetric sensor array based on SANs assisted by machine learning, has great potential for the identification of oral cariogenic bacteria so as to serve for oral disease prevention and treatment.
有效识别唾液样本中的多种致龋菌对于口腔疾病的预防和治疗至关重要。在这里，我们开发了一种简单的比色传感器阵列，用于使用机器学习辅助的单原子纳米酶 (SANs) 识别致龋菌。有趣的是，致龋菌可以通过加速电子转移来提高铁 (Fe) - 氮 (N) - 碳 (C) SANs 的氧化酶样活性，而脲则会进一步降低 Fe-N-C 的活性重构。通过机器学习辅助的传感器阵列，比色响应被开发为致龋菌的“指纹”。线性判别分析可很好地区分多种致龋菌，而层次聚类分析也可区分不同属的细菌。此外，比色传感器阵列在人工唾液样本中混合致龋菌的识别方面表现出优异的性能。鉴于其便利性、精确性和高通量的区分能力，基于机器学习辅助的 SANs 的比色传感器阵列在识别口腔致龋菌方面具有很大的潜力，可用于口腔疾病的预防和治疗。
