Refractory apical periodontitis (RAP) is an endodontic
apical inflammatory
disease caused by Enterococcus faecalis (E. faecalis). Bacterial detection
using surface-enhanced Raman scattering (SERS) technology is a hot
research topic, but the specific and direct detection of oral bacteria
is a challenge, especially in real clinical samples. In this paper,
we develop a novel SERS-based green platform for label-free detection
of oral bacteria. The platform was built on silver nanoparticles with
a two-step enhancement way using NaBH4 and sodium (Na+) to form “hot spots,” which resulted in an
enhanced SERS fingerprint of E. faecalis with fast, quantitative, lower-limit, reproducibility, and stability.
In combination with machine learning, four different oral bacteria
(E. faecalis, Porphyromonas
gingivalis, Streptococcus mutans, and Escherichia coli) could be intelligently
distinguished. The unlabeled detection method emphasized the specificity
of E. faecalis in simulated saliva,
serum, and even real samples from patients with clinical root periapical
disease. In addition, the assay has been shown to be environmentally
friendly and without secondary contamination through antimicrobial
assays. The proposed label-free, rapid, safe, and green SERS detection
strategy for oral bacteria provided an innovative solution for the
early diagnosis and prevention of RAP and other perioral diseases.