Identification of microorganisms in irreversible pulpitis and primary endodontic infections with respect to clinical and radiographic findings

微生物学 生物 牙科 白色念珠菌 牙密螺旋体 牙髓炎 医学 牙龈卟啉单胞菌 牙周炎 牙髓(牙)
作者
Nazanin Zargar,Hengameh Ashraf,S. M. Amin Marashi,Mohammad Sabeti,Alireza Aziz
出处
期刊:Clinical Oral Investigations [Springer Nature]
卷期号:24 (6): 2099-2108 被引量:16
标识
DOI:10.1007/s00784-019-03075-9
摘要

The aim of this study was to evaluate the composition of microbiota of irreversible pulpitis and primary endodontic infections with respect to clinical and radiographic findings by performing cultures and 16s rDNA sequencing in Iranian patients. In this prospective cross-sectional study, samples were collected from 41 root canals for 4 main groups of patients. Bacterial identification was performed by the polymerase chain reaction (PCR) and 16s rDNA sequencing of aerobic and anaerobic cultivable colonies taken from patients’ culture plates. Additionally, the presence of 13 bacterial species and 3 nonbacterial species was also explored using PCR and species-specific primers. Sixteen microbial species, 1 fungus (Candida albicans), and 1 virus (Herpes simplex virus) were discovered and isolated. Species with the highest prevalence were Dialister invisus (68.3%), Porphyromonas gingivalis (58.8%), Streptococcus salivarius (58.5%), and Treponema denticola (56.1%). Lysinibacillus fusiformis (19.1%) was detected in the root canals for the first time. Candida albicans was seen in 11 cases (26.8%). Herpes simplex virus (HSV) was seen in 4 patients (9.8%). Our results suggest that Gram-negative anaerobic oral bacteria are the majority of the microbes in primary endodontic infections. Various combinations of bacterial species were related to different clinical and radiographic conditions. Lysinibacillus fusiformis was detected for the first time in primary endodontic infections. The results of this investigation might help clinicians choose to identify suspected endodontic pathogens in the etiology of each form of pulpal and periradicular diseases to determine the best therapeutic measures.
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