Mapping of a Subgingival Dual-Species Biofilm Model Using Confocal Raman Microscopy

Techniques for continuously monitoring the formation of subgingival biofilm, in relation to the determination of species and their accumulation over time in gingivitis and periodontitis, are limited. In recent years, advancements in the field of optical spectroscopic techniques have provided an alternative for analyzing three-dimensional microbiological structures, replacing the traditional destructive or biofilm staining techniques. In this work, we have demonstrated that the use of confocal Raman spectroscopy coupled with multivariate analysis provides an approach to spatially differentiate bacteria in an in vitro model simulating a subgingival dual-species biofilm. The present study establishes a workflow to evaluate and differentiate bacterial species in a dual-species in vitro biofilm model, using confocal Raman microscopy (CRM). Biofilm models of Actinomyces denticolens and Streptococcus oralis were cultured using the “Zürich in vitro model” and were analyzed using CRM. Cluster analysis was used to spatially differentiate and map the biofilm model over a specified area. To confirm the clustering of species in the cultured biofilm, confocal laser scanning microscopy (CLSM) was coupled with fluorescent in vitro hybridization (FISH). Additionally, dense bacteria interface area (DBIA) samples, as an imitation of the clusters in a biofilm, were used to test the developed multivariate differentiation model. This confirmed model was successfully used to differentiate species in a dual-species biofilm and is comparable to morphology. The results show that the developed workflow was able to identify main clusters of bacteria based on spectral “fingerprint region” information from CRM. Using this workflow, we have demonstrated that CRM can spatially analyze two-species in vitro biofilms, therefore providing an alternative technique to map oral multi-species biofilm models.

Microstructural Analysis of Whey/Soy Protein Isolate Mixed Gels Using Confocal Raman Microscopy

This work explores the potential of confocal Raman microscopy to investigate the microstructure of mixed protein gel systems. Heat-set protein gels were prepared using whey protein isolate (WPI), soy protein isolate (SPI), and mixtures thereof, with a total of five different whey-to-soy protein ratios (100, 75, 50, 25, and 0%). These were analysed using confocal Raman microscopy, and different data analysis approaches were used to maximize the amount of structural and compositional information extracted from the spectral datasets generated, including both univariate and multivariate analysis methods. Small spectral differences were found between pure WPI and SPI gels, mainly attributed to conformational differences (amide bands), but SPI exhibited considerably greater auto-fluorescence than WPI. The univariate analysis method allowed for a rapid microstructural analysis, successfully mapping the distribution of protein and water in the gels. The greater fluorescence of the capsule-like structures found in the mixed gels, compared to other regions rich in proteins, suggested that these may be enriched in soy proteins. Further analysis, using a multivariate approach, allowed us to distinguish proteins with different levels of hydration within the gels and to detect non-proteinaceous compounds. Raman microscopy proved to be particularly useful to detect the presence of residual lipids in protein gels.

Temporal Imaging of Live Cells by High-Speed Confocal Raman Microscopy

Label-free live cell imaging was performed using a custom-built high-speed confocal Raman microscopy system. For various cell types, cell-intrinsic Raman bands were monitored. The high-resolution temporal Raman images clearly delineated the intracellular distribution of biologically important molecules such as protein, lipid, and DNA. Furthermore, optical phase delay measured using quantitative phase microscopy shows similarity with the image reconstructed from the protein Raman peak. This reported work demonstrates that Raman imaging is a powerful label-free technique for studying various biomedical problems in vitro with minimal sample preparation and external perturbation to the cellular system.