Z Qi1, H Cao2, H Jiang2, J Zhao2, Z Tang1. 1. Department of Endodontics, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Key Laboratory of Stomatology, Shanghai, China. 2. Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, State Key Lab of Transducer Technology, Shanghai, China.
Abstract
AIM: To use microarrays to detect 11 selected bacteria in infected root canals, revealing bacterial combinations that are associated with clinical symptoms and signs of primary endodontic infections in a Chinese population. METHODOLOGY: DNA was extracted from 90 samples collected from the root canals of teeth with primary endodontic infections in a Chinese population, and the 16S rRNA gene was amplified by polymerase chain reaction (PCR). The PCR products were hybridized to microarrays containing specific oligonucleotide probes targeting 11 species, and the arrays were screened with a confocal laser scanner. Pearson's chi-squared test and cluster analysis were performed to investigate the associations between the bacterial combinations and clinical symptoms and signs using SAS 8.02. RESULTS: Seventy-seven samples (86%) yielded at least one of the 11 target species. Parvimonas micra (56%), Porphyromonas endodontalis (51%), Tannerella forsythia (48%), Prevotella intermedia (44%) and Porphyromonas gingivalis (37%) were the most prevalent taxa and were often concomitant. The following positive associations were found between the bacterial combinations and clinical features: P. endodontalis and T. forsythia with abscess; P. gingivalis and P. micra with sinus tract; P. gingivalis and P. endodontalis or P. micra and P. endodontalis with abscess and sinus tract; and the combination of P. endodontalis, P. micra, T. forsythia and P. gingivalis with sinus tract (P < 0.05). CONCLUSIONS: Various combinations of P. micra, P. endodontalis, T. forsythia and P. gingivalis may contribute to abscesses or sinus tracts of endodontic origin with bacterial synergism in a Chinese population.
AIM: To use microarrays to detect 11 selected bacteria in infected root canals, revealing bacterial combinations that are associated with clinical symptoms and signs of primary endodontic infections in a Chinese population. METHODOLOGY: DNA was extracted from 90 samples collected from the root canals of teeth with primary endodontic infections in a Chinese population, and the 16S rRNA gene was amplified by polymerase chain reaction (PCR). The PCR products were hybridized to microarrays containing specific oligonucleotide probes targeting 11 species, and the arrays were screened with a confocal laser scanner. Pearson's chi-squared test and cluster analysis were performed to investigate the associations between the bacterial combinations and clinical symptoms and signs using SAS 8.02. RESULTS: Seventy-seven samples (86%) yielded at least one of the 11 target species. Parvimonas micra (56%), Porphyromonas endodontalis (51%), Tannerella forsythia (48%), Prevotella intermedia (44%) and Porphyromonas gingivalis (37%) were the most prevalent taxa and were often concomitant. The following positive associations were found between the bacterial combinations and clinical features: P. endodontalis and T. forsythia with abscess; P. gingivalis and P. micra with sinus tract; P. gingivalis and P. endodontalis or P. micra and P. endodontalis with abscess and sinus tract; and the combination of P. endodontalis, P. micra, T. forsythia and P. gingivalis with sinus tract (P < 0.05). CONCLUSIONS: Various combinations of P. micra, P. endodontalis, T. forsythia and P. gingivalis may contribute to abscesses or sinus tracts of endodontic origin with bacterial synergism in a Chinese population.
Authors: Maria Tereza P Albuquerque; Joshua D Evans; Richard L Gregory; Marcia C Valera; Marco C Bottino Journal: Clin Oral Investig Date: 2015-08-29 Impact factor: 3.573
Authors: M I Torres-Ramos; U J Martín-Camacho; J L González; M F Yañez-Acosta; L Becerra-Solano; Y K Gutiérrez-Mercado; M Macias-Carballo; Claudia M Gómez; O A González-Vargas; J A Rivera-Mayorga; Alejandro Pérez-Larios Journal: Int J Mol Sci Date: 2022-06-29 Impact factor: 6.208