Combined Mutual Learning Net for Raman Spectral Microbial Strain Identification

Chen, Junfan1; Hu, Jiaqi1; Xue, Chenlong1; Zhang, Qian2; Li, Jingyan1; Wang, Ziyue1; Lv, Jinqian1; Zhang, Aoyan1; Dang, Hong1; Lu, Dan1; Zou, Defeng1; Cong, Longqing1; Li, Yuchao2; Chen, Gina Jinna1; Shum, Perry Ping1

2024-04-04

10.1021/acs.analchem.3c05107

ANALYTICAL CHEMISTRY   影响因子和分区

0003-2700

1520-6882

Infectious diseases pose a significant threat to global health, yet traditional microbiological identification methods suffer from drawbacks, such as high costs and long processing times. Raman spectroscopy, a label-free and noninvasive technique, provides rich chemical information and has tremendous potential in fast microbial diagnoses. Here, we propose a novel Combined Mutual Learning Net that precisely identifies microbial subspecies. It demonstrated an average identification accuracy of 87.96% in an open-access data set with thirty microbial strains, representing a 5.76% improvement. 50% of the microbial subspecies accuracies were elevated by 1% to 46%, especially for E. coli 2 improved from 31% to 77%. Furthermore, it achieved a remarkable subspecies accuracy of 92.4% in the custom-built fiber-optical tweezers Raman spectroscopy system, which collects Raman spectra at a single-cell level. This advancement demonstrates the effectiveness of this method in microbial subspecies identification, offering a promising solution for microbiology diagnosis.

SCI ; EI

英语

第一 ; 通讯

National Natural Science Foundation of China["62220106006","62205139"] ; National Natural Science Foundation of China["SGDX20211123114001001","JSGGKQ TD20221101115656030"] ; Shenzhen Science and Technology Program[2021B1515120013]

Chemistry

Chemistry, Analytical

WOS:001197381200001

AMER CHEMICAL SOC

CHEMISTRY

Web of Science

1.Southern Univ Sci & Technol, Dept EEE, State Key Lab Opt Fiber & Cable Manufacture Techno, Guangdong Key Lab Integrated Optoelect Intellisens, Shenzhen 518055, Peoples R China
2.Jinan Univ, Inst Nanophoton, Guangdong Prov Key Lab Nanophoton Manipulat, Guangzhou 511443, Peoples R China

Chen, Junfan,Hu, Jiaqi,Xue, Chenlong,et al. Combined Mutual Learning Net for Raman Spectral Microbial Strain Identification[J]. ANALYTICAL CHEMISTRY,2024,96(15).

Chen, Junfan.,Hu, Jiaqi.,Xue, Chenlong.,Zhang, Qian.,Li, Jingyan.,...&Shum, Perry Ping.(2024).Combined Mutual Learning Net for Raman Spectral Microbial Strain Identification.ANALYTICAL CHEMISTRY,96(15).

Chen, Junfan,et al."Combined Mutual Learning Net for Raman Spectral Microbial Strain Identification".ANALYTICAL CHEMISTRY 96.15(2024).