Raman spectroscopic identification of Mycobacterium tuberculosis

被引:54
作者
Stoeckel, Stephan [1 ,2 ,3 ]
Meisel, Susann [1 ,2 ,3 ]
Lorenz, Bjoern [1 ,2 ,3 ]
Kloss, Sandra [1 ,2 ,3 ]
Henk, Sandra [4 ]
Dees, Stefan [4 ]
Richter, Elvira [5 ,8 ]
Andres, Soenke [5 ]
Merker, Matthias [6 ]
Labugger, Ines [4 ]
Roesch, Petra [1 ,2 ,3 ]
Popp, Juergen [1 ,2 ,3 ,7 ]
机构
[1] Friedrich Schiller Univ Jena, Inst Phys Chem, Helmholtzweg 4, D-077433 Jena, Germany
[2] Friedrich Schiller Univ Jena, Abbe Ctr Photon, Helmholtzweg 4, D-07743 Jena, Germany
[3] InfectoGnost Res Campus Jena,Philosophenweg 7, D-07743 Jena, Germany
[4] Alere Technol GmbH, Lobstedter Str 103-105, D-07749 Jena, Germany
[5] Res Ctr Borstel, Natl Reference Ctr Mycobacteria, Parkallee 1-40, D-23845 Borstel, Germany
[6] Res Ctr Borstel, Mol & Expt Mycobacteriol, Parkallee 1-40, D-23845 Borstel, Germany
[7] Leibniz Inst Photon Technol, Albert Einstein Str 9, D-07745 Jena, Germany
[8] Lab Dr Limbach, Heidelberg, Germany
关键词
Raman spectroscopy; microscopy; mycobacteria; M; tuberculosis; identification; analytical methods; RAPID IDENTIFICATION; DIAGNOSIS; REGIONS;
D O I
10.1002/jbio.201600174
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
In this study, Raman microspectroscopy has been utilized to identify mycobacteria to the species level. Because of the slow growth of mycobacteria, the per se cultivation-independent Raman microspectroscopy emerges as a perfect tool for a rapid on-the-spot mycobacterial diagnostic test. Special focus was laid upon the identification of Mycobacterium tuberculosis complex (MTC) strains, as the main causative agent of pulmonary tuberculosis worldwide, and the differentiation between pathogenic and commensal nontuberculous mycobacteria (NTM). Overall the proposed model considers 26 different mycobacteria species as well as antibiotic susceptible and resistant strains. More than 8800 Raman spectra of single bacterial cells constituted a spectral library, which was the foundation for a two-level classification system including three support vector machines. Our model allowed the discrimination of MTC samples in an independent validation dataset with an accuracy of 94% and could serve as a basis to further improve Raman microscopy as a first-line diagnostic point-of-care tool for the confirmation of tuberculosis disease. [GRAPHICS] .
引用
收藏
页码:727 / 734
页数:8
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