Urinary tract infection (UTI) is a very common infection. Up to every second woman will experience at least one UTI episode during her lifetime. The gold standard for identifying the infectious microorganisms is the urine culture. However, culture methods are time-consuming and need at least 24 h until the results are available. Here, we report about a culture independent identification procedure by using Raman microspectroscopy in combination with innovative chemometrics. We investigated, for the first time directly, urine samples by Raman microspectroscopy on a single-cell level. In a first step, a database of eleven important UTI bacterial species, which were grown in sterile filtered urine, was built up. A support vector machine (SVM) was used to generate a statistical model, which allows a classification of this data set with an accuracy of 92% on a species level. This model was afterward used to identify infected urine samples of ten patients directly without a preceding culture step. Thereby, we were able to determine the predominant bacterial species (seven Escherichia coli and three Enterococcus faecalis ) for all ten patient samples. These results demonstrate that Raman microspectroscopy in combination with support vector machines allow an identification of important UTI bacteria within two hours without the need of a culture step.

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Both biofilm formations as well as planktonic cells of water bacteria such as diverse species of the Legionella genus as well as Pseudomonas aeruginosa, Klebsiella pneumoniae, and Escherichia coli were examined in detail by Raman microspectroscopy. Production of various molecules involved in biofilm formation of tested species in nutrient-deficient media such as tap water was observed and was particularly evident in the biofilms formed by six Legionella species. Biofilms of selected species of the Legionella genus differ significantly from the planktonic cells of the same organisms in their lipid amount. Also, all Legionella species have formed biofilms that differ significantly from the biofilms of the other tested genera in the amount of lipids they produced. We believe that the significant increase in the synthesis of this molecular species may be associated with the ability of Legionella species to form biofilms. In addition, a combination of Raman microspectroscopy with chemometric approaches can distinguish between both planktonic form and biofilms of diverse bacteria and could be used to identify samples which were unknown to the identification model. Our results provide valuable data for the development of fast and reliable analytic methods based on Raman microspectroscopy, which can be applied to the analysis of tap water-adapted microorganisms without any cultivation step.

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A soil habitat consists of a significant number of bacteria that cannot be cultivated by conventional means, thereby posing obvious difficulties in their classification and identification. This difficulty necessitates the need for advanced techniques wherein a well-compiled biomolecular database consisting of the already cultivable bacteria can be used as a reference in an attempt to link the noncultivable bacteria to their closest phylogenetic groups. Raman spectroscopy has been successfully applied to taxonomic studies of many systems like bacteria, fungi, and plants relying on spectral differences contributed by the variation in their overall biomolecular composition. However, these spectral differences can be obscured due to Raman signatures from photosensitive microbial pigments like carotenoids that show enormous variation in signal intensity hindering taxonomic investigations. In this study, we have applied laser-induced photobleaching to expel the carotenoid signatures from pigmented cocci bacteria. Using this method, we have investigated 12 species of pigmented bacteria abundant in soil habitats belonging to three genera mainly Micrococcus, Deinococcus, and Kocuria based on their Raman spectra with the assistance of a chemometric tool known as the radial kernel support vector machine (SVM). Our results demonstrate the potential of Raman spectroscopy as a minimally invasive taxonomic tool to identify pigmented cocci soil bacteria at a single-cell level.

Mg(2+), Na(+), and SO(4)(2-) are common ions in natural systems, and they are usually found in water bodies. Precipitation processes have great importance in environmental studies because they may be part of complex natural cycles; natural formation of atmospheric particulate matter is just one case. In this work, Na(2)Mg(SO(4))(2)·5H(2)O (konyaite), Na(6)Mg(SO(4))(4) (vanthoffite), and Na(12)Mg(7)(SO(4))(13)·15H(2)O (loeweite) were synthesized and their Raman spectra reported. By slow vaporization (at 20 °C and relative humidity of 60-70%), crystallization experiments were performed within small droplets (diameter ≤ 1-2 mm) of solutions containing MgSO(4) and Na(2)SO(4), and crystal formations were studied by Raman spectroscopy. Crystallization of Na(2)Mg(SO(4))(2)·4H(2)O (bloedite) was observed, and the formation of salt mixtures was confirmed by Raman spectra. Bloedite, konyaite, and loeweite, as well as Na(2)SO(4) and MgSO(4)·6H(2)O, were the components found to occur in different proportions. No crystallization of Na(6)Mg(SO(4))(4) (vanthoffite) was observed under the crystallization condition used in this study.

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