Classification and Identification of Archaea Using Single-Cell Raman Ejection and Artificial Intelligence: Implications for Investigating Uncultivated Microorganisms

Wang, Yi1; Xu, Jiabao2; Cui, Dongyu1; Kong, Lingchao3; Chen, Songze1; Xie, Wei4,5; Zhang, Chuanlun1,6,7

2021-12-01

10.1021/acs.analchem.1c03495

ANALYTICAL CHEMISTRY   影响因子和分区

0003-2700

1520-6882

Archaea can produce special cellular components such as polyhydroxyalkanoates, carotenoids, rhodopsin, and ether lipids, which have valuable applications in medicine and green energy production. Most of the archaeal species are uncultivated, posing challenges to investigating their biomarker components and biochemical properties. In this study, we applied Raman spectroscopy to examine the biological characteristics of nine archaeal isolates, including halophilic archaea (Haloferax larsenii, Haloarcula argentinensis, Haloferax mediterranei, Halomicrobium mukohataei, Halomicrobium salinus, Halorussus sp., Natrinema gari), thermophilic archaea (Sulfolobus acidocaldarius), and marine group I (MGI) archaea (Nitrosopumilus maritimus). Linear discriminant analysis of the Raman spectra allowed visualization of significant separations among the nine archaeal isolates. Machine-learning classification models based on support vector machine achieved accuracies of 88-100% when classifying the nine archaeal species. The predicted results were validated by DNA sequencing analysis of cells isolated from the mixture by Raman-activated cell sorting. Raman spectra of uncultured archaea (MGII) were also obtained based on Raman spectroscopy and fluorescence in situ hybridization. The results combining multiple Raman-based techniques indicated that MGII may have the ability to produce lipids distinct from other archaeal species. Our study provides a valuable approach for investigating and classifying archaea, especially uncultured species, at the single-cell level.

SCI ; EI

英语

NI论文

第一 ; 通讯

National Natural Science Foundation of China[91851210,42141003] ; State Key R&D project of China[2018YFA0605800] ; Stable Support Plan Program of Shenzhen Natural Science Fund[20200925173954005] ; Shenzhen Key Laboratory of Marine Archaea Geo-Omics, Souther n University of Science and Technology[ZDSYS201802081843490] ; Souther n Marine Science and Engineering Guangdong Laboratory (Guangzhou)[K19313901] ; China Postdoctoral Science Foundation[2020M682769]

Chemistry

Chemistry, Analytical

WOS:000733827900001

AMER CHEMICAL SOC

20220111414894

Cytology ; Discriminant analysis ; DNA sequences ; Fluorescence microscopy ; Gene encoding ; Lipids ; Microorganisms ; Molecular biology ; Raman scattering ; Support vector machines

Biological Materials and Tissue Engineering:461.2 ; Biology:461.9 ; Computer Software, Data Handling and Applications:723 ; Light/Optics:741.1 ; Organic Compounds:804.1 ; Information Sources and Analysis:903.1 ; Statistical Methods:922 ; Quantum Theory; Quantum Mechanics:931.4 ; Optical Instruments:941.3

CHEMISTRY

Web of Science

1.Southern Univ Sci & Technol, Shenzhen Key Lab Marine Archaea Geo, Shenzhen 518055, Peoples R China
2.Univ Oxford, Dept Engn Sci, Oxford OX1 3PJ, England
3.Southern Univ Sci & Technol, Sch Environm Sci & Engn, State Environm Protect Key Lab Integrated Surface, Shenzhen 518055, Peoples R China
4.Sun Yat Sen Univ, Sch Marine Sci, Zhuhai 519082, Peoples R China
5.Southern Marine Sci & Engn Guangdong Lab Zhuhai, Zhuhai 519082, Peoples R China
6.Southern Marine Sci & Engn Guangdong Lab Guangzho, Guangzhou 510000, Peoples R China
7.Shanghai Sheshan Natl Geophys Observ, Shanghai 200000, Peoples R China

Wang, Yi,Xu, Jiabao,Cui, Dongyu,et al. Classification and Identification of Archaea Using Single-Cell Raman Ejection and Artificial Intelligence: Implications for Investigating Uncultivated Microorganisms[J]. ANALYTICAL CHEMISTRY,2021,93:17012-17019.

Wang, Yi.,Xu, Jiabao.,Cui, Dongyu.,Kong, Lingchao.,Chen, Songze.,...&Zhang, Chuanlun.(2021).Classification and Identification of Archaea Using Single-Cell Raman Ejection and Artificial Intelligence: Implications for Investigating Uncultivated Microorganisms.ANALYTICAL CHEMISTRY,93,17012-17019.

Wang, Yi,et al."Classification and Identification of Archaea Using Single-Cell Raman Ejection and Artificial Intelligence: Implications for Investigating Uncultivated Microorganisms".ANALYTICAL CHEMISTRY 93(2021):17012-17019.