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Updated: Feb 20, 2026

Porphyromonas gingivalis as a Model Organism for Assessing Interaction of Anaerobic Bacteria with Host Cells
Published on: December 17, 2015
Comparison of Real-Time Polymerase Chain Reaction and Anaerobic Culture for Detecting and Quantifying Porphyromonas
T Rachita1, Shubha Kumaraswamy2, Sravya Kodati3
1Department of Periodontology, Index Institute of Dental Sciences, Indore, IND.
Abstract:
Background Porphyromonas gingivalis (P. gingivalis) is a key pathogen in chronic periodontitis that drives dysbiosis and tissue destruction. Anaerobic culture often underestimates fastidious bacteria, whereas real-time polymerase chain reaction (RT-PCR) can provide higher sensitivity and accurate quantification. This study compared both methods for detecting and quantifying P. gingivalis in subgingival plaque from patients with chronic periodontitis and healthy controls. Methodology In total, 32 participants (16 with chronic periodontitis and 16 healthy) were included. Pooled subgingival plaque samples were analyzed by anaerobic culture on selective media and by RT-PCR targeting the 16S rRNA gene with a TaqMan probe and standard curve quantification. Clinical parameters were recorded (probing depth (PD), clinical attachment loss (CAL), and gingival index (GI)), and data were analyzed using t-tests, chi-square tests, Pearson's correlation, and diagnostic metrics. Results Participants with chronic periodontitis had significantly higher clinical parameters (PD = 6.38 ± 0.96 mm, CAL = 3.63 ± 1.09 mm, GI = 2.50 ± 0.22; all p = 0.001) and P. gingivalis loads (culture = 82.13 ± 54.26 CFU/mL, p = 0.031; RT-PCR = 97.44 ± 59.02 CFU equivalents/mL, p = 0.039) than controls. Bacterial load showed moderate positive correlations with clinical parameters (r = 0.35-0.42, p < 0.05). RT-PCR detected P. gingivalis in 59.4% of samples versus 50% by culture, achieving 100% sensitivity and 90.6% accuracy. Conclusions RT-PCR is more sensitive than culture for P. gingivalis detection, supporting its use for improved periodontal diagnosis and risk assessment.

