In the last years the identification of microorganisms by means of different IR and Raman spectroscopic techniques
has become quite popular. Most of the studies however apply the various vibrational spectroscopic methods to bulk
samples which require at least a short cultivation time of several hours. Nevertheless, bulk identification methods
achieve high classification rates which enable even the discrimination between closely related strains or the distinction
between resistance capabilities.
However, applying micro-Raman spectroscopy with visible excitation wavelengths enables for the detection of
single microorganisms. Especially for time critical process like the fast diagnosis of severe diseases or the identification
of bacterial contamination on food samples or pharmaceuticals, a cultivation-free identification of bacteria is required.
In doing so, we established different isolation techniques in combination with Raman spectroscopic identification.
Isolating bacteria from different matrixes always has an impact on the Raman spectroscopic identification capability.
Therefore, these isolation techniques have to be specially designed to fulfill the spectroscopic requirements. In total the
method should enable the identification of pathogens within the first 3 hours.
Pathogen detection is essential without time delay especially for severe diseases like sepsis. Here, the survival rate is
dependent on a prompt antibiosis. For sepsis three hours after the onset of shock the survival rate of the patient drops
below 60 %. Unfortunately, the results from standard diagnosis methods like PCR or microbiology can normally be
received after 12 or 36 h, respectively. Therefore diagnosis methods which require less cultivation or even no cultivation
at all have to be established for medical diagnosis. Here, Raman spectroscopy, as a vibrational spectroscopic method, is a
very sensitive and selective approach and monitors the biochemical composition of the investigated sample. Applying
micro-Raman spectroscopy allows for a spatial resolution below 1 μm and is therefore in the size range of bacteria.
Raman spectra of bacteria depend on the physiological status. Therefore, the databases require the inclusion of the
necessary environmental parameters such as temperature, pH, nutrition, etc. Such large databases therefore require a
specialized chemometric approach, since the variation between different strains is small. In this contribution we will
demonstrate the capability of Raman spectroscopy to identify pathogens without cultivation even from real
environmental or medical samples.
Here we present our latest results concerning the application of Raman microspectroscopy in combination with
innovative chemometrics to characterize biological cells. The first part of this manuscript deals with the application of
micro-Raman spectroscopy to identify microbial contaminations while the main focus within the second part of this
presentation is concerned with Raman studies on eukaryotic cells where we will report about the development of an
algorithm to differentiate between breast cancer cells and normal epithelial cells.