Analysis of data from 16SrRNA sequencing generated by high throughput of subgingival biofilm samples from diabetic patients

• Grant number: 13/20537-9
• Support Opportunities: Scholarships abroad - Research Internship - Post-doctor
• Effective date (Start): August 01, 2014
• Effective date (End): October 31, 2014
• Field of knowledge: Health Sciences - Dentistry - Periodontology
• Principal Investigator: Marcia Pinto Alves Mayer
• Grantee: Priscila Larcher Longo
• Supervisor: Purnima Kumar
• Host Institution: Instituto de Ciências Biomédicas (ICB). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Research place: Ohio State University, Columbus, United States
• Associated to the scholarship: 11/10057-4 - Analysis of subgingival microbiota diversity and serum cytokine and gingival fluid profile related to glycemic control in subjects with diabetes mellitus type II, BP.PD

Abstract

Despite an association between diabetes mellitus and periodontal disease, the microbial diversity in periodontal sites and mechanisms by which oral pathogens relate to glycemic control in diabetics are still not elucidated. This study aims to determine the diversity of the subgingival microbiota of patients with type 2 diabetes mellitus with appropriate and inappropriate glucose balance. Subgingival samples were collected from sites with different probing depths: shallow (PD d 3mm), medium (PD 4-6mm) and deep (PD e 7mm) from 10 periodontitis patients without diabetes (SDP); 20 periodontitis patients with diabetes, being 10 with adequate glycemic control (DMA + P) (HbA1c <8%) and 10 with inadequate glycemic control (DMI + P) (HbA1c e 8%); 10 diabetic patients without periodontal disease (SP) and 10 patients without diabetes and without periodontal disease (H). After DNA extraction, the hypervariable region V5-V6 from 16SrRNA was amplified. Amplicons were purified after gel electrophoresis (Qiaquick gel extraction kit, Qiagen Inc. CA, USA). Pyrosequencing (454 - Roche) was performed at the Center for Advanced Genomic Technologies (CATG), Biochemical Department in University of São Paulo (IQ-USP). The data obtained will be analyzed in collaboration with Prof. Kumar Purnima (College of Dentistry, Ohio State University) through the algorithm Pyronoise (Roche- 454) and software Black Box Chimera Check (B2C2). Sequences less than 300 bp in length will be discarded. Sequences will be grouped at the highest level into operational taxonomic units with 98% similarity, then they will be aligned with the database in GreenGenes BLAST algorithm. Phylogenetic trees will be generated and visualized using RAxML v7.0.4, under the GAMMA model. The analyzes will be carried out within the virtual environment provided by Quantitative Insights Into Microbial Ecology (QIIME). (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

LONGO, PRISCILA L.; DABDOUB, SHAREEF; KUMAR, PURNIMA; ARTESE, HILANA P. C.; DIB, SERGIO A.; ROMITO, GIUSEPPE A.; ALVES MAYER, MARCIA PINTO. Glycaemic status affects the subgingival microbiome of diabetic patients. JOURNAL OF CLINICAL PERIODONTOLOGY, v. 45, n. 8, p. 932-940, AUG 2018. (13/20537-9, 11/10057-4, 11/18618-5)