Distribution Of Putative Periodontal Pathogens In Subgingival Plaque Of Patients With Periodontal Disease

Periodontal disease comprises a group of inflammatory conditions of the supporting tissues of the teeth that are caused by bacteria. Various putative periodontal pathogens in subgingival plaque impact on the occurrence and development of periodontitis. There are many different types of periodontal pathogens in different diseases. It is very important to detect periodontal pathogens in the diagnosis and treatment of periodontitis.It is generally accepted that Porphyromonas gingivalis (Pg) is one of periodontal pathogens and has been detected frequently in people with periodontitis in accordance with most previous reports. In this study, we try to use PCR to amplify gene segment of 16S rDNA of Pg, then clone it into E. coli and analyse the sequence of it. It provides support for the application of clinical bacterial detection. Based on these methods, we try to detect 10 putative periodontal pathogens in subgingival plaque of Chinese people. This study is divided into two parts.Part one: Cloning and Sequencing of part of 16S rRNA gene of Porphyromonas gingivalisObjectives: To clone and analyse part of the sequence of 16S ribosomal RNA gene of Porphyromonas gingivalis, establish a method to identify Pg and provide a universalmethod for subsequent study. Meterial and methods Tocollect subgingival plaque samples from people with periodontitis. Bacterial genomic DNA was then isolated. Pg 381 was used as positive control. The specific PCR primer for Pg, TaqDNA polymerase, templates were mixed together with other reaction solutions. Under the suitable conditions, the PCR was performed. The PCR products were subjected to electrophoresis in 1.5% agarose gel-Tris-acetate EDTA buffer. The gel was stained with 0. 5ug/ml of ethidium bromide and photographed under UV illumination. DL2000 DNA marker was used as a molecular size standard. The PCR product was recollected and connected with T-vector. The connected product was transformed to competent E. coli cells. The transformed cells were then plated onto LB plates supplemented with Ampicillin and incubated. Colonies was collected. The size of inserts was determined by PCR. The plasmids were extracted and then cut by two restriction enzymes (HindIII/Xba I ). The reaction products were subjected to electrophoresis and observe the results. At last, the inserted DNA segment was sequenced. Results Genomic DNA extracted from part of subgingival plaque samples can be amplified a DNA segment of correct size of about 200 bases using PCR, which is same as Pg381. Cloned colonies can be acquired after the segment transformed into E.coli and the size can be confirmed by dual-enzyme cut reaction. The sequence of the segment of DNA is coincidence with that in Genbank on pubmed. Conclusions Part of 16S rRNA gene can be detected by PCR and that could be the used in clinical detection of Pg.Part two: Distribution of putative periodontalpathogens in subgingival plaque of patients with periodontal diseaseObjectives To detect and compare 10 putative periodontal pathogens in subgingival plaque from Chinese adult patients by using polymerase chain reaction assay; To describe the distribution of these pathogens in Chinese people; To examine the association between the microbiological profiles and clinical status of patients. Meterial and methods 10 specific PCR primers for Porphyromonas gingivalis Pg, Bacteriodes forsythus Bf, Prevotella intermedia Pi , Treponema denticola Td , Prevotella nigrescens Pn , Campylobacter rectus Cr , Eikenella corrodens EC, Actinobacillus actinomycetemcomitans Aa, Capnocytophaga ochracea Co, Capnocytophaga sputigena Cs were synthesized according to their different nucleotide sequences in the various parts of 16S rRNA. Subgingival plaque samples were collected from 3 groups of adults: 16 periodontal healthy patients, 17 chronic gingivitis patients and 29 adult periodontitis patients, 2 sites in each subject and got 124 samples altogether. At the same time, record the patients' general and clinical profiles, such as age, gender, smoking or...