No abstract

Routine clinical microbiological identification of pathogenic microorganisms is largely based on nutritional and biochemical tests. In the case of severely ill patients, the unavoidable time delay associated with such identification procedures can be fatal. We present a novel identification method based on confocal Raman microspectroscopy. With this approach it is possible to obtain Raman spectra directly from microbial microcolonies on the solid culture medium, which have developed after only 6 h of culturing for the most commonly encountered organisms. Due to the limited thickness of microcolonies, some of the underlying culture medium is sampled together with the bacteria. Spectra measured at different depths in a microcolony contain different amounts of the medium signal. A mathematical routine, involving vector algebra, is described for the nonsubjective correction of spectra for variable signal contributions of the medium. To illustrate the possibilities of our approach for the identification of microorganisms, Raman spectra were collected from 6-h microcolonies of five bacterial strains on solid culture medium. The classification results show that confocal Raman microspectroscopy has great potential as a powerful new tool in clinical diagnostic microbiology.

Rapid identification of microbial pathogens reduces infection-related morbidity and mortality of hospitalized patients. Raman spectra and Fourier transform infrared (IR) spectra constitute highly specific spectroscopic fingerprints of microorganisms by which they can be identified. Little biomass is required, so that spectra of microcolonies can be obtained. A prospective clinical study was carried out in which the causative pathogens of bloodstream infections in hospitalized patients were identified. Reference libraries of Raman and IR spectra of bacterial and yeast pathogens highly prevalent in bloodstream infections were created. They were used to develop identification models based on linear discriminant analysis and artificial neural networks. These models were tested by carrying out vibrational spectroscopic identification in parallel with routine diagnostic phenotypic identification. Whereas routine identification has a typical turnaround time of 1 to 2 days, Raman and IR spectra of microcolonies were collected 6 to 8 h after microbial growth was detected by an automated blood culture system. One hundred fifteen samples were analyzed by Raman spectroscopy, of which 109 contained bacteria and 6 contained yeasts. One hundred twenty-one samples were analyzed by IR spectroscopy. Of these, 114 yielded bacteria and 7 were positive for yeasts. High identification accuracy was achieved in both the Raman (92.2%, 106 of 115) and IR (98.3%, 119 of 121) studies. Vibrational spectroscopic techniques enable simple, rapid, and accurate microbial identification. These advantages can be easily transferred to other applications in diagnostic microbiology, e.g., to accelerate identification of fastidious microorganisms.

Fourier transform infrared and Raman microspectroscopy are currently being developed as new methods for the rapid identification of clinically relevant microorganisms. These methods involve measuring spectra from microcolonies which have been cultured for as little as 6 h, followed by the nonsubjective identification of microorganisms through the use of multivariate statistical analyses. To examine the biological heterogeneity of microorganism growth which is reflected in the spectra, measurements were acquired from various positions within (micro)colonies cultured for 6, 12, and 24 h. The studies reveal that there is little spectral variance in 6-h microcolonies. In contrast, the 12-and 24-h cultures exhibited a significant amount of heterogeneity. Hierarchical cluster analysis of the spectra from the various positions and depths reveals the presence of different layers in the colonies. Further analysis indicates that spectra acquired from the surface of the colonies exhibit higher levels of glycogen than do the deeper layers of the colony. Additionally, the spectra from the deeper layers present with higher RNA levels than the surface layers. Therefore, the 6-h colonies with their limited heterogeneity are more suitable for inclusion in a spectral database to be used for classification purposes. These results also demonstrate that vibrational spectroscopic techniques can be useful tools for studying the nature of colony development and biofilm formation.In recent years, there has been much effort invested into the development of new techniques for the identification of microorganisms. Many of these methods are aimed at providing the clinician with more rapid identification of the microorganism responsible for infection in order to begin the appropriate course of antimicrobial treatment (1,9,15,21,27,31,44,51). The emergence of these novel methods reflects the rise in drug-resistant microorganisms, which requires that antimicrobial treatment be more effectively managed (2, 12, 28, 52). Among the new methods are those based on vibrational spectroscopic techniques, namely Fourier transform infrared (FT-IR) and Raman spectroscopies. Vibrational spectroscopic methods are reagentless procedures in which there is no need to add dyes or labels for spectral measurement. These nondestructive techniques are based on the absorption (FT-IR) or scattering (Raman) of light directed onto a sample. The amount of light absorbed or scattered depends on the molecules found within the sample and the environment in which these molecules are found. With these highly sensitive techniques, the frequency of light in the resulting spectrum provides biochemical information regarding the molecular composition and molecular structure of and molecular interaction in cells and tissues (24,55). Raman and infrared spectroscopies are complementary techniques which together can provide a more complete impression of the biochemical information within a sample. Furthermore, these two methods differ such that each is capable of providing informatio...