In the course of time the laboratory diagnosis of periodontal infection has been influenced by the difficulties encountered in the transport, growth and identification of the different pathogenic species involved in periodontal disease: species that form a complex biofilm on the subgengival plaque and require anaerobic conditions. The traditional cultural diagnostic method has been replaced by molecular ones (PCR), a technique able to identify the different species responsible for periodontal disease and which, in its real time PCR version, is also able to quantify the different bacteria species present in a sample. The core of the “PCR based method” procedure is represented by the in silico diagnostic system that includes: (i) a genetic target, representative of the single bacteria species under examination, (ii) oligonucleotides (primers and/or fluorescent probes) with optimal thermodynamic characteristics. Nevertheless, even though the methods available in the literature and from commercial kits provide procedures that are considered specific, sensitive and fast, they do not take into consideration the most important parameter of polymicrobial infection analysis: namely selectivity. The selectivity of a diagnostic test is represented not only by its ability to reveal low titles of a single pathogen species compared to high titles of other ones, but also by its capacity to point out simultaneously and with the same level of accuracy, the presence and/or the concentration of different microbial species. The purpose of this work is the description of the current sequences of nine different primary periodontal pathogens deposited in DNA Data Banks: Tannerella forsythensis, Porphyromonas gingivalis, Treponema denticola, Prevotella intermedia, Fusobacterium nucleatum ssp, Camphylobacter gracilis, Prevotella nigriscens, Eichenella corrodens, Aggregatibacter actinomycetemcomitans and subsequently the in silico evaluation of the DNA regions characterized by a good selectivity.
Genic targets used for the identification of periodontal pathogens by PCR base methods
ORRU, GERMANO;
2007-01-01
Abstract
In the course of time the laboratory diagnosis of periodontal infection has been influenced by the difficulties encountered in the transport, growth and identification of the different pathogenic species involved in periodontal disease: species that form a complex biofilm on the subgengival plaque and require anaerobic conditions. The traditional cultural diagnostic method has been replaced by molecular ones (PCR), a technique able to identify the different species responsible for periodontal disease and which, in its real time PCR version, is also able to quantify the different bacteria species present in a sample. The core of the “PCR based method” procedure is represented by the in silico diagnostic system that includes: (i) a genetic target, representative of the single bacteria species under examination, (ii) oligonucleotides (primers and/or fluorescent probes) with optimal thermodynamic characteristics. Nevertheless, even though the methods available in the literature and from commercial kits provide procedures that are considered specific, sensitive and fast, they do not take into consideration the most important parameter of polymicrobial infection analysis: namely selectivity. The selectivity of a diagnostic test is represented not only by its ability to reveal low titles of a single pathogen species compared to high titles of other ones, but also by its capacity to point out simultaneously and with the same level of accuracy, the presence and/or the concentration of different microbial species. The purpose of this work is the description of the current sequences of nine different primary periodontal pathogens deposited in DNA Data Banks: Tannerella forsythensis, Porphyromonas gingivalis, Treponema denticola, Prevotella intermedia, Fusobacterium nucleatum ssp, Camphylobacter gracilis, Prevotella nigriscens, Eichenella corrodens, Aggregatibacter actinomycetemcomitans and subsequently the in silico evaluation of the DNA regions characterized by a good selectivity.
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