Klaus-Dieter Peschke

Chemotaxonomic Identification of Single Bacteria by Micro-Raman Spectroscopy: Application to Clean-Room-Relevant Biological Contaminations

ABSTRACT Microorganisms, such as bacteria, which might be present as contamination inside an industrial food or pharmaceutical clean room process need to be identified on short time scales in order to minimize possible health hazards as well as production downtimes causing financial deficits. Here we describe the first results of single-particle micro-Raman measurements in combination with a classification method, the so-called support vector machine technique, allowing for a fast, reliable, and nondestructive online identification method for single bacteria.

Micro-Raman spectroscopic identification of bacterial cells of the genus Staphylococcus and dependence on their cultivation conditions

Microbial contamination is not only a medical problem, but also plays a large role in pharmaceutical clean room production and food processing technology. Therefore many techniques were developed to achieve differentiation and identification of microorganisms. Among these methods vibrational spectroscopic techniques (IR, Raman and SERS) are useful tools because of their rapidity and sensitivity. Recently we have shown that micro-Raman spectroscopy in combination with a support vector machine is an extremely capable approach for a fast and reliable, non-destructive online identification of single bacteria belonging to different genera. In order to simulate different environmental conditions we analyzed in this contribution different Staphylococcus strains with varying cultivation conditions in order to evaluate our method with a reliable dataset. First, micro-Raman spectra of the bulk material and single bacterial cells that were grown under the same conditions were recorded and used separately for a distinct chemotaxonomic classification of the strains. Furthermore Raman spectra were recorded from single bacterial cells that were cultured under various conditions to study the influence of cultivation on the discrimination ability. This dataset was analyzed both with a hierarchical cluster analysis (HCA) and a support vector machine (SVM).

Raman-Spectroscopy for a rapid identification of single microorganisms

A rapid analysis of microorganisms is necessary for medical, pharmaceutical or food technology applications to identify harmful bacteria. Conventional identification methods require pure cultures from isolates and are often time demanding. Raman spectroscopy offers an alternative approach to identify microorganisms. With Raman microscopy it is possible to measure structures in the sub micrometer range, and therefore single bacteria cells are accessible. Micro-Raman mapping experiments proof that the bacterium shows a spatial homogeneity, since bacteria normally exhibit no compartments, therefore one spectrum of a single vegetative bacterial cell is sufficient to identify the strain. In contrary bacterial spores and yeast cells exhibit a high spatial dependency of the observed Raman spectra. For heterogeneous samples like single spores or yeast cells a mean spectrum from up to ten different positions is required to describe the complete cell. Using micro-Raman spectra of single bacterial cells and average spectra of yeast cells it is possible to create a database and identify microorganisms on species or even strain level.

Rapid identification of single microbes by various Raman spectroscopic techniques

A fast and unambiguous identification of microorganisms is necessary not only for medical purposes but also in technical processes such as the production of pharmaceuticals. Conventional microbiological identification methods are based on the morphology and the ability of microbes to grow under different conditions on various cultivation media depending on their biochemical properties. These methods require pure cultures which need cultivation of at least 6 h but normally much longer. Recently also additional methods to identify bacteria are established e.g. mass spectroscopy, polymerase chain reaction (PCR), flow cytometry or fluorescence spectroscopy. Alternative approaches for the identification of microorganisms are vibrational spectroscopic techniques. With Raman spectroscopy a spectroscopic fingerprint of the microorganisms can be achieved. Using UV-resonance Raman spectroscopy (UVRR) macromolecules like DNA/RNA and proteins are resonantly enhanced. With an excitation wavelength of e.g. 244 nm it is possible to determine the ratio of guanine/cytosine to all DNA bases which allows a genotypic identification of microorganisms. The application of UVRR requires a large amount of microorganisms (> 106 cells) e.g. at least a micro colony. For the analysis of single cells micro-Raman spectroscopy with an excitation wavelength of 532 nm can be used. Here, the obtained information is from all type of molecules inside the cells which lead to a chemotaxonomic identification. In this contribution we show how wavelength dependent Raman spectroscopy yields significant molecular information applicable for the identification of microorganisms on a single cell level.