期刊论文详细信息
BMC Research Notes
Optimization of quantitative polymerase chain reactions for detection and quantification of eight periodontal bacterial pathogens
关键词: QPCR;    Periodontal pathogens;    Specificity;    Quantification limit;    Intercycler portability;   
DOI  :  10.1186/1756-0500-5-664
来源: DOAJ
【 摘 要 】

Abstract

Background

The aim of this study was to optimize quantitative (real-time) polymerase chain reaction (qPCR) assays for 8 major periodontal pathogens, i.e. Aggregatibacter actinomycetemcomitans, Fusobacterium nucleatum, Parvimonas micros, Porphyromonas gingivalis, Prevotella intermedia, Tanerella forsythia and Treponema denticola, and of the caries pathogen Streptococcus mutans.

Results

Eighteen different primer pairs were analyzed in silico regarding specificity (using BLAST analysis) and the presence of secondary structures at primer binding sites (using mFOLD). The most specific and efficiently binding primer pairs, according to these analyses, were selected for qPCR-analysis to determine amplification efficiency, limit of quantification and intra-run reproducibility. For the selected primer pairs, one for each species, the specificity was confirmed by assessing amplification of DNA extracts from isolates of closely related species. For these primer pairs, the intercycler portability was evaluated on 3 different thermal cyclers (the Applied Biosystems 7300, the Bio-Rad iQ5 and the Roche Light Cycler 480). For all assays on the different cyclers, a good correlation of the standard series was obtained (i.e. r2 ≥ 0.98), but quantification limits varied among cyclers. The overall best quantification limit was obtained by using a 2 μl sample in a final volume of 10 μl on the Light Cycler 480.

Conclusions

In conclusion, the proposed assays allow to quantify the bacterial loads of S. mutans, 6 periodontal pathogenic species and the genus Fusobacterium.This can be of use in assessing periodontal risk, determination of the optimal periodontal therapy and evaluation of this treatment.

【 授权许可】

Unknown   

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