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      Association Between Oral Microbiota and Cigarette Smoking in the Chinese Population

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          Abstract

          The oral microbiota has been observed to be influenced by cigarette smoking and linked to several human diseases. However, research on the effect of cigarette smoking on the oral microbiota has not been systematically conducted in the Chinese population. We profiled the oral microbiota of 316 healthy subjects in the Chinese population by 16S rRNA gene sequencing. The alpha diversity of oral microbiota was different between never smokers and smokers ( P = 0.002). Several bacterial taxa were first reported to be associated with cigarette smoking by LEfSe analysis, including Moryella ( q = 1.56E-04), Bulleidia ( q = 1.65E-06), and Moraxella ( q = 3.52E-02) at the genus level and Rothia dentocariosa ( q = 1.55E-02), Prevotella melaninogenica ( q = 8.48E-08), Prevotella pallens ( q = 4.13E-03), Bulleidia moorei ( q = 1.79E-06), Rothia aeria ( q = 3.83E-06), Actinobacillus parahaemolyticus ( q = 2.28E-04), and Haemophilus parainfluenzae ( q = 4.82E-02) at the species level. Two nitrite-producing bacteria that can increase the acidity of the oral cavity, Actinomyces and Veillonella, were also enriched in smokers with FDR-adjusted q-values of 3.62E-06 and 1.10E-06, respectively. Notably, we observed that two acid production-related pathways, amino acid-related enzymes ( q = 6.19E-05) and amino sugar and nucleotide sugar metabolism ( q = 2.63E-06), were increased in smokers by PICRUSt analysis. Finally, the co-occurrence analysis demonstrated that smoker-enriched bacteria were significantly positively associated with each other and were negatively correlated with the bacteria decreased in smokers. Our results suggested that cigarette smoking may affect oral health by creating a different environment by altering bacterial abundance, connections among oral microbiota, and the microbiota and their metabolic function.

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          Most cited references45

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          DADA2: High resolution sample inference from Illumina amplicon data

          We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
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            Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

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              Metagenomic biomarker discovery and explanation

              This study describes and validates a new method for metagenomic biomarker discovery by way of class comparison, tests of biological consistency and effect size estimation. This addresses the challenge of finding organisms, genes, or pathways that consistently explain the differences between two or more microbial communities, which is a central problem to the study of metagenomics. We extensively validate our method on several microbiomes and a convenient online interface for the method is provided at http://huttenhower.sph.harvard.edu/lefse/.
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                Author and article information

                Contributors
                Journal
                Front Cell Infect Microbiol
                Front Cell Infect Microbiol
                Front. Cell. Infect. Microbiol.
                Frontiers in Cellular and Infection Microbiology
                Frontiers Media S.A.
                2235-2988
                28 May 2021
                2021
                : 11
                : 658203
                Affiliations
                [1] 1 School of Public Health, Sun Yat‐sen University , Guangzhou, China
                [2] 2 State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat‐sen University Cancer Center , Guangzhou, China
                Author notes

                Edited by: Sinem Esra Sahingur, University of Pennsylvania, United States

                Reviewed by: Oleh Andrukov, University Dental Clinic Vienna, Austria; Laura de Freitas, University of São Paulo, Brazil

                *Correspondence: Wei-Hua Jia, jiawh@ 123456sysucc.org.cn

                †These authors have contributed equally to this work and share first authorship

                This article was submitted to Bacteria and Host, a section of the journal Frontiers in Cellular and Infection Microbiology

                Article
                10.3389/fcimb.2021.658203
                8195269
                34123872
                fcfb9ef2-997e-4824-aa85-8c8e8471a84d
                Copyright © 2021 Jia, Liao, He, Zheng, Tong, Xue, Zhang, Yuan, Zhang and Jia

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 25 January 2021
                : 19 April 2021
                Page count
                Figures: 4, Tables: 1, Equations: 0, References: 45, Pages: 10, Words: 5503
                Funding
                Funded by: National Key Research and Development Program of China 10.13039/501100012166
                Award ID: 2016YFC1302700
                Funded by: National Natural Science Foundation of China 10.13039/501100001809
                Award ID: 81973131
                Categories
                Cellular and Infection Microbiology
                Original Research

                Infectious disease & Microbiology
                oral microbiota,cigarette smoking,16s rrna gene sequencing,china,saliva

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