Real-Time, Label-Free Identification and Differentiation of Environmental Responses In Living Biofilms

The current primary means of identifying biofilms mediated disease is by identifying the presence of specific bacteria. Blame is then assigned to these bacteria. This approach, however can lead to misdiagnosis. In fact, many bacteria associated with pathogenesis exist in a non-pathogenic form in the natural human microbial flora. Current methods in evaluating bacterial biofilm pathogenicity are focused on evaluating overall biofilm presence and/or viability. This approach implements bulk evaluation that limits the ability discern if a live biofilm is exhibiting pathogenic properties, or is surviving in a non-pathogenic capacity.  In an attempt to evolve analytical techniques to distinguish living biofilms in pathogenic and non-pathogenic modes, acidogenic dental pathogen Streptococcus mutans was used as a model. In this study, sucrose was used to control the exhibition of S. mutans pathogenic properties, which were then evaluated by surface enhanced Raman spectroscopy (SERS) to identify unique chemical signatures. These techniques require minimal sample preparation and offer a rapid, low-cost, high throughput system for clinical evaluations, or evaluating of the capacity of various materials to affect bacterial-mediated biofilm pathogenesis.