Microbiomes in Supragingival Biofilms and Saliva of Adolescent Patients with Induced and Naturally Occurring Gingivitis Relative to Gingival Health

Autor: Roland Wirth, Gergely Maróti, Lídia Lipták, Mónika Mester, Alaa Al Ayoubi, Bernadett Pap, Melinda Madléna, Janos Minarovits, Kornél L. Kovács
Rok vydání: 2020
DOI: 10.21203/rs.3.rs-45630/v1
Popis: Background: Comparison of the microbiomes in supragingival biofilm and saliva samples collected from juvenile patients developing induced or spontaneous gingivitis with healthy controls.Results: 36 supragingival biofilm samples from 9 adolescent gingivitis patients wearing orthodontic appliances (induced gingivitis), 40 supragingival plaques from 10 patients having spontaneous gingivitis, and 36 control samples from 9 individuals without gingivitis in the same age group were analyzed by 16S rRNA gene amplicon sequencing. Salivary microbiomes of the same persons were characterized by shotgun metagenome sequencing to compare the sessile, i.e. biofilm immobilized communities with planktonic microbiota. The amplicon and whole genome data sets were scrutinized using bioinformatics workflows designed to minimize systemic biases. RDP and RefSeq reference databases were compared in the identification of microbiome members.The composition and diversity of bacterial communities did not differ extensively between the two groups of gingivitis patients and controls. In spite of the overall similarities, the relative abundance of the genera Fusobacterium, Accermansia, Treponema and Campylobacter was prominently higher in samples from gingivitis patients versus controls. In contrast, the genera Lautropia, Kingella, Neisseria, Actinomyces and Rothia were significantly more abundant in controls than in either of the two gingivitis groups. Conclusions: The higher relative abundance of certain gingivitis-associated taxa may either reflect their role in disease pathogenesis or may indicate that gingival inflammation favored the selective overgrowth of distinct bacterial clusters. At any rate, the abundance pattern of certain taxa rather than individual strains shows characteristic features of potential diagnostic value. Stringent bioinformatics treatment of the sequencing data is mandatory to avoid unintentional misinterpretations.
Databáze: OpenAIRE