Identification of pathogens and detection of antibiotic susceptibility at single-cell resolution by Raman spectroscopy combined with machine learning.
Identification of pathogens and detection of antibiotic susceptibility at single-cell resolution by Raman spectroscopy combined with machine learning.
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DOI：
10.3389/fmicb.2022.1076965
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发表时间：
2022
影响因子：
5.2
通讯作者：
Fu, Yu Vincent
中科院分区：
文献类型：
--
作者：
Lu, Weilai;Li, Haifei;Qiu, Haoning;Wang, Lu;Feng, Jie;Fu, Yu Vincent
在单细胞分辨率下快速、准确、无标记地检测病原菌和抗生素耐药性是临床诊断的技术挑战。克服繁琐的病原菌培养过程和耗时的抗生素药敏测定将显着有利于早期诊断和优化临床抗生素的使用。拉曼光谱可以以无标记、不依赖培养物的方式收集病原菌的分子指纹，适合单细胞分辨率的病原菌诊断。在这里，我们报告了一种基于拉曼光谱与机器学习相结合的方法，可以在单细胞分辨率下快速准确地识别病原菌并检测抗生素耐药性。结果表明，机器学习方法对12种常见病原菌的识别平均准确率为90.73±9.72%。使用机器学习模型以 99.92±0.06% 的准确度区分从医院患者中分离出的鲍曼不动杆菌的抗生素敏感菌株和抗生素耐药菌株。同时，我们发现敏感菌株具有较高的核酸/蛋白质比，抗生素耐药菌株的蛋白质中具有丰富的酰胺II结构。这项研究表明拉曼光谱是一种快速识别病原体并检测其抗生素敏感性的有前途的方法。
Rapid, accurate, and label-free detection of pathogenic bacteria and antibiotic resistance at single-cell resolution is a technological challenge for clinical diagnosis. Overcoming the cumbersome culture process of pathogenic bacteria and time-consuming antibiotic susceptibility assays will significantly benefit early diagnosis and optimize the use of antibiotics in clinics. Raman spectroscopy can collect molecular fingerprints of pathogenic bacteria in a label-free and culture-independent manner, which is suitable for pathogen diagnosis at single-cell resolution. Here, we report a method based on Raman spectroscopy combined with machine learning to rapidly and accurately identify pathogenic bacteria and detect antibiotic resistance at single-cell resolution. Our results show that the average accuracy of identification of 12 species of common pathogenic bacteria by the machine learning method is 90.73 ± 9.72%. Antibiotic-sensitive and antibiotic-resistant strains of Acinetobacter baumannii isolated from hospital patients were distinguished with 99.92 ± 0.06% accuracy using the machine learning model. Meanwhile, we found that sensitive strains had a higher nucleic acid/protein ratio and antibiotic-resistant strains possessed abundant amide II structures in proteins. This study suggests that Raman spectroscopy is a promising method for rapidly identifying pathogens and detecting their antibiotic susceptibility.
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影响因子：
5.9
作者：
Germond A;Ichimura T;Horinouchi T;Fujita H;Furusawa C;Watanabe TM
通讯作者：
Watanabe TM
DOI：
10.1016/j.saa.2004.11.017
发表时间：
2005-05-01
影响因子：
4.4
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Wei L
影响因子：
3.9
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Baloch Z