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Comparison of Different Label-Free Raman Spectroscopy Approaches for the Discrimination of Clinical MRSA and MSSA Isolates
Methicillin-resistant Staphylococcus aureus (MRSA) is classified as one of the priority pathogens that threaten human health. Resistance detection with conventional microbiological methods takes several days, forcing physicians to administer empirical antimicrobial treatment that is not always appropriate. A need exists for a rapid, accurate, and cost-effective method that allows targeted antimicrobial therapy in limited time. In this pilot study, we investigate the efficacy of three different label-free Raman spectroscopic approaches to differentiate methicillin-resistant and -susceptible clinical isolates of S. aureus (MSSA). Single-cell analysis using 532 nm excitation was shown to be the most suitable approach since it captures information on the overall biochemical composition of the bacteria, predicting 87.5% of the strains correctly. UV resonance Raman microspectroscopy provided a balanced accuracy of 62.5% and was not sensitive enough in discriminating MRSA from MSSA. Excitation of 785 nm directly on the petri dish provided a balanced accuracy of 87.5%. However, the difference between the strains was derived from the dominant staphyloxanthin bands in the MRSA, a cell component not associated with the presence of methicillin resistance. This is the first step toward the development of label-free Raman spectroscopy for the discrimination of MRSA and MSSA using single-cell analysis with 532 nm excitation. IMPORTANCE Label-free Raman spectra capture the high chemical complexity of bacterial cells. Many different Raman approaches have been developed using different excitation wavelength and cell analysis methods. This study highlights the major importance of selecting the most suitable Raman approach, capable of providing spectral features that can be associated with the cell mechanism under investigation. It is shown that the approach of choice for differentiating MRSA from MSSA should be single-cell analysis with 532 nm excitation since it captures the difference in the overall biochemical composition. These results should be taken into consideration in future studies aiming for the development of label-free Raman spectroscopy as a clinical analytical tool for antimicrobial resistance determination.
Revealing the Chemical Composition of Birch Pollen Grains by Raman Spectroscopic Imaging
The investigation of the biochemical composition of pollen grains is of the utmost interest for several environmental aspects, such as their allergenic potential and their changes in growth conditions due to climatic factors. In order to fully understand the composition of pollen grains, not only is an in-depth analysis of their molecular components necessary but also spatial information of, e.g., the thickness of the outer shell, should be recorded. However, there is a lack of studies using molecular imaging methods for a spatially resolved biochemical composition on a single-grain level. In this study, Raman spectroscopy was implemented as an analytical tool to investigate birch pollen by imaging single pollen grains and analyzing their spectral profiles. The imaging modality allowed us to reveal the layered structure of pollen grains based on the biochemical information of the recorded Raman spectra. Seven different birch pollen species collected at two different locations in Germany were investigated and compared. Using chemometric algorithms such as hierarchical cluster analysis and multiple-curve resolution, several components of the grain wall, such as sporopollenin, as well as the inner core presenting high starch concentrations, were identified and quantified. Differences in the concentrations of, e.g., sporopollenin, lipids and proteins in the pollen species at the two different collection sites were found, and are discussed in connection with germination and other growth processes.
Using Raman spectroscopy in infection research
Raman spectroscopy allows to analyze bacteria and other microorganisms label and destruction free. With different Raman techniques either colonies on agar plates or small structures like single bacterial cells can be analyzed allowing for their identification as well as enabling 2D and 3D information of intracellular bacteria or biofilms. Using surface enhanced Raman spectroscopy (SERS) allows detecting and identifying viruses as well as antibiotics relevant in the treatment of infections.