Development of a method based on chemometric analysis of Raman spectra for the discrimination of heterofermentative lactobacilli

Polydimethylsiloxane-graphene oxide nanocomposite coatings with improved anti-corrosion and anti-biofouling properties

We demonstrate enhanced anti-corrosion and anti-biofouling properties of graphene oxide-silica-polydimethylsiloxane (GSP) coating on carbon steel (CS). Electrochemical analyses of GSP-coated carbon steel exposed to Gram-positive Bacillus sp., Gram-negative Pseudomonas sp., and freshwater bacterial cultures for 72 h showed a 3-5 orders of magnitude reduction in i_corr values and high impedance values (10⁷ Ω) as compared with polished specimens. The corrosion protection efficiency of GSP-coated specimens was 99.9% against Bacillus sp. and freshwater culture and it was 89.6% against Pseudomonas sp. Evaluation of anti-biofouling property of GSP coating using microbiological and epifluorescence microscopic techniques showed three order reductions in total viable cells on GSP-coated specimens exposed to bacterial cultures. Confocal laser scanning microscopic analysis of biofilm architecture confirmed a significant reduction of biomass and biofilm thickness on GSP-coated CS demonstrating an excellent anti-biofouling activity of GSP.

Characterization and Discrimination of Gram-Positive Bacteria Using Raman Spectroscopy with the Aid of Principal Component Analysis

Raman scattering and its particular effect, surface-enhanced Raman scattering (SERS), are whole-organism fingerprinting spectroscopic techniques that gain more and more popularity in bacterial detection. In this work, two relevant Gram-positive bacteria species, Lactobacillus casei (L. casei) and Listeria monocytogenes (L. monocytogenes) were characterized based on their Raman and SERS spectral fingerprints. The SERS spectra were used to identify the biochemical structures of the bacterial cell wall. Two synthesis methods of the SERS-active nanomaterials were used and the recorded spectra were analyzed. L. casei and L. monocytogenes were successfully discriminated by applying Principal Component Analysis (PCA) to their specific spectral data.

Discrimination of wine lactic acid bacteria by Raman spectroscopy

Species of Lactobacillus, Pediococcus, Oenococcus, and Leuconostoc play an important role in winemaking, as either inoculants or contaminants. The metabolic products of these lactic acid bacteria have considerable effects on the flavor, aroma, and texture of a wine. However, analysis of a wine's microflora, especially the bacteria, is rarely done unless spoilage becomes evident, and identification at the species or strain level is uncommon as the methods required are technically difficult and expensive. In this work, we used Raman spectral fingerprints to discriminate 19 strains of Lactobacillus, Pediococcus, and Oenococcus. Species of Lactobacillus and Pediococcus and strains of O. oeni and P. damnosus were classified with high sensitivity: 86-90 and 84-85%, respectively. Our results demonstrate that a simple, inexpensive method utilizing Raman spectroscopy can be used to accurately identify lactic acid bacteria isolated from wine.

Applications of Infrared and Raman Spectroscopies to Probiotic Investigation

In this review, we overview the most important contributions of vibrational spectroscopy based techniques in the study of probiotics and lactic acid bacteria. First, we briefly introduce the fundamentals of these techniques, together with the main multivariate analytical tools used for spectral interpretation. Then, four main groups of applications are reported: (a) bacterial taxonomy (Subsection 4.1); (b) bacterial preservation (Subsection 4.2); (c) monitoring processes involving lactic acid bacteria and probiotics (Subsection 4.3); (d) imaging-based applications (Subsection 4.4). A final conclusion, underlying the potentialities of these techniques, is presented.

Raman spectroscopy and chemometrics for identification and strain discrimination of the wine spoilage yeasts Saccharomyces cerevisiae, Zygosaccharomyces bailii, and Brettanomyces bruxellensis

The yeasts Zygosaccharomyces bailii, Dekkera bruxellensis (anamorph, Brettanomyces bruxellensis), and Saccharomyces cerevisiae are the major spoilage agents of finished wine. A novel method using Raman spectroscopy in combination with a chemometric classification tool has been developed for the identification of these yeast species and for strain discrimination of these yeasts. Raman spectra were collected for six strains of each of the yeasts Z. bailii, B. bruxellensis, and S. cerevisiae. The yeasts were classified with high sensitivity at the species level: 93.8% for Z. bailii, 92.3% for B. bruxellensis, and 98.6% for S. cerevisiae. Furthermore, we have demonstrated that it is possible to discriminate between strains of these species. These yeasts were classified at the strain level with an overall accuracy of 81.8%.