In Search of Spectroscopic Signatures of Periodontitis: A SERS-Based Magnetomicrofluidic Sensor for Detection of Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans

Recently, Porphyromonas gingivalis, the keystone pathogen implicated in the development of gum disease (periodontitis), was detected in the brains of Alzheimer's disease patients, opening up a fascinating possibility that it is also involved in the pathobiology of this neuro-degenerative illness. To verify this hypothesis, an unbiased, specific, and sensitive method to detect this pathogen in biological specimens is needed. To this end, our interdisciplinary studies demonstrate that P. gingivalis can be easily identified by surface-enhanced Raman scattering (SERS). Moreover, based on SERS measurements, P. gingivalis can be distinguished from another common periodontal pathogen, Aggregatibacter actinomycetemcomitans, and also from ubiquitous oral Streptococcus spp. The results were confirmed by principal component analysis (PCA). Furthermore, we have shown that different P. gingivalis and A. actinomycetemcomitans strains can easily adsorb to silver-coated magnetic nanoparticles (Fe2O3@AgNPs). Thus, it is possible to magnetically separate investigated bacteria from other components of a specimen using the microfluidic chip. To obtain additional enhancement of the Raman signal, the NPs adsorbed to bacterial cells were magnetically attracted to the Si/Ag SERS platform. Afterward, the SERS spectra could be recorded. Such a time-saving procedure can be very helpful in rapid medical diagnostics and thus in starting the appropriate pharmacological therapy to prevent the development of periodontitis and associated comorbidities, e.g., Alzheimer's disease.

Automated summary

Recent studies suggest a potential link between Porphyromonas gingivalis and Alzheimer's disease. A method using surface-enhanced Raman scattering (SERS) to easily identify P. gingivalis and distinguish it from other pathogens has been proposed. By utilizing magnetic nanoparticles and microfluidic chips, bacteria can be separated for further analysis.