Tawatchai Chumponsuk1, Lucsame Gruneck2, Eleni Gentekaki3, Paiboon Jitprasertwong4, Niwed Kullawong5, Jiro Nakayama6, Siam Popluechai7. 1. School of Science, Mae Fah Luang University, Muang, Chiang Rai, Thailand. 2. Gut Microbiome Research Group, Mae Fah Luang University, Muang, Chiang Rai, Thailand. 3. School of Science, Mae Fah Luang University, Muang, Chiang Rai, Thailand; Gut Microbiome Research Group, Mae Fah Luang University, Muang, Chiang Rai, Thailand. 4. School of Geriatric Oral Health, Institute of Dentistry, Suranaree University of Technology, Nakhon Ratchasima, Thailand. 5. School of Health Science, Mae Fah Luang University, Muang, Chiang Rai, Thailand. 6. Department of Bioscience and Biotechnology, Faculty of Agriculture, Kyushu University, Fukuoka, Japan. 7. School of Science, Mae Fah Luang University, Muang, Chiang Rai, Thailand; Gut Microbiome Research Group, Mae Fah Luang University, Muang, Chiang Rai, Thailand. Electronic address: siam@mfu.ac.th.
Abstract
OBJECTIVE: This study aimed to investigate abundance of specific bacterial taxa in the saliva of 105 Thai adults with different BMI (lean, overweight, and obese) and T2DM subjects using qPCR targeting the 16S rRNA gene of various bacteria taxa. DESIGN: We employed qPCR targeting 16S rRNA genes to explore the bacterial profiles and abundances in the saliva of Thai adult subjects with different BMI and T2DM. Multivariate statistical analyses (multiple factor analysis (MFA) and sparse Partial Least Squares Discriminant Analysis (sPLS-DA) were performed to assess the associations of salivary bacteria with diet, blood profile, gender, age, and use of antibiotics. RESULTS: We found that abundance profiles of the examined salivary bacteria were similar across the four groups. When diet, blood profile, and gender, age, and use of antibiotics were considered, significant differences were noted between subgroups. A positive correlation was also found between consumption of carbonate soft drinks and Bacteroidetes, Gamma-proteobacteria, Veillonella, Fusobacterium and Fusobacterium nucleatum. CONCLUSIONS: This is the first study demonstrating the relative abundance of salivary bacteria in adult Thai subjects with different levels of BMI and T2DM. Regardless of the similar pattern of bacterial profiles across groups, sPLS-DA analysis highlighted the influence of host variables (gender, age, and use of antibiotics) on the abundance of salivary microbiota. Our findings pave the way for further hypothesis testing to gain insight into the association between host factors and salivary microbiome.
OBJECTIVE: This study aimed to investigate abundance of specific bacterial taxa in the saliva of 105 Thai adults with different BMI (lean, overweight, and obese) and T2DM subjects using qPCR targeting the 16S rRNA gene of various bacteria taxa. DESIGN: We employed qPCR targeting 16S rRNA genes to explore the bacterial profiles and abundances in the saliva of Thai adult subjects with different BMI and T2DM. Multivariate statistical analyses (multiple factor analysis (MFA) and sparse Partial Least Squares Discriminant Analysis (sPLS-DA) were performed to assess the associations of salivary bacteria with diet, blood profile, gender, age, and use of antibiotics. RESULTS: We found that abundance profiles of the examined salivary bacteria were similar across the four groups. When diet, blood profile, and gender, age, and use of antibiotics were considered, significant differences were noted between subgroups. A positive correlation was also found between consumption of carbonate soft drinks and Bacteroidetes, Gamma-proteobacteria, Veillonella, Fusobacterium and Fusobacterium nucleatum. CONCLUSIONS: This is the first study demonstrating the relative abundance of salivary bacteria in adult Thai subjects with different levels of BMI and T2DM. Regardless of the similar pattern of bacterial profiles across groups, sPLS-DA analysis highlighted the influence of host variables (gender, age, and use of antibiotics) on the abundance of salivary microbiota. Our findings pave the way for further hypothesis testing to gain insight into the association between host factors and salivary microbiome.