Tuberculosis
caused by Mycobacterium tuberculosis complex (MTBC) is one of the major infectious diseases in the world.
Identification of MTBC and differential diagnosis of nontuberculous
mycobacteria (NTM) species impose challenges because of their taxonomic
similarity. This study describes a differential diagnosis method using
the surface-enhanced Raman scattering (SERS) measurement of molecules
released by Mycobacterium species.
Conventional principal component analysis and linear discriminant
analysis methods successfully separated the acquired spectrum of MTBC
from those of NTM species but failed to distinguish between the spectra
of different NTM species. A novel sensible functional linear discriminant
analysis (SLDA), projecting the averaged spectrum of a bacterial specie
to the subspace orthogonal to the within-species random variation,
thereby eliminating its influence in applying linear discriminant
analysis, was employed to effectively discriminate not only MTBC but
also species of NTM. The successful demonstration of this SERS–SLDA
method opens up new opportunities for the rapid differentiation of Mycobacterium species.