Unveiling potential driver taxa in subgingival plaque and their roles in mediating periodontitis progression

Sep 30, 2026

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Periodontitis progression is associated with temporal shifts in the oral microbiome, yet the microbial transitions connecting disease stages and driving worsening severity remain insufficiently clarified. This study reprocessed subgingival 16S rRNA gene sequencing data, applied MaAsLin2 for differential taxa, and constructed co-occurrence networks to highlight candidates. NetMoss identified key microbes driving the health-to-periodontitis transition, followed by correlation and mediation analyses linking driver taxa to periodontal clinical indicators. Results showed periodontitis-enriched putative pathogens and health-enriched protective taxa, alongside progressively disrupted networks in advanced stages.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages14

Reading Time35 min

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Abstract

Introduction

Background and rationale

NGS-based evidence and recent classifications

JOURNAL OF ORAL MICROBIOLOGY 2026, VOL. 18, NO. 1, 2609452 [https://doi.org/10.1080/20002297.2025.2609452](https://doi.org/10.1080/20002297.2025.2609452) RESEARCH ARTICLE Unveiling potential driver taxa in subgingival plaque and their roles in mediating periodontitis progression Tianqi Xu, Ziyi Wei, Qingxiang Zeng, Qiang Feng and Mengfan Zhi Department of Human Microbiome, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Research Center of Dental Materials and Oral Tissue Regeneration & Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, People's Republic of China ABSTRACT Background: Periodontitis progression is accompanied by a succession of the oral microbiome. However, the dynamic microbial transitions that link different disease stages and contribute to disease progression remain incompletely understood. Objective: This study aims to identify microbial taxa that may serve as potential drivers underlying increasing severity of periodontitis. Design: Subgingival sample 16S rRNA gene sequencing data were reprocessed for quality control and taxonomic annotation. MaAsLin2 was used to identify microbial differences between groups, and co-occurrence networks were built based on the differential taxa. NetMoss algorithm was applied to identify key microbes driving the transition from health to periodontitis. Correlation and mediation analyses were used to assess the associations between these driver taxa and periodontal clinical indicators. Results: Putative novel pathogens (e.g. Filifactor alocis, Slackia exigua) were markedly enriched in periodontitis, whereas potential protective taxa (e.g. Haemophilus and Rothia) had higher relative abundance in the health group. The microbial cooccurrence networks in the periodontitis groups were progressively disrupted, characterized by reduced network robustness and heightened vulnerability in the Stage III and IV groups. The driver taxa probably influenced the severity of periodontitis through modulation of periodontal clinical indicators, with positive or negative correlations observed between these taxa and periodontal clinical indicators. Conclusions: Capnocytophaga, Paludibacter, Dialister pneumosintes, Eubacterium minutum and Phocaeicola abscessus are proposed as key driver taxa across different periodontal health conditions, and exhibited significant correlations with periodontal clinical indicators. ARTICLE HISTORY Received 21 October 2025 Revised 2 December 2025 Accepted 21 December 2025 KEYWORDS Periodontitis; subgingival microbiota; 16S rRNA gene sequencing; microbial co-occurrence networks; driver taxa Introduction Periodontitis is one of the most prevalent chronic infectious diseases of the oral cavity [ 1], characterised by clinical features such as periodontal attachment loss, alveolar bone resorption and the formation of periodontal pockets [2,3] . Dental plaque biofilm is recognised as the initiating factor of periodontitis [4,5], with subgingival plaque playing a critical role by providing a special hypoxic environment conducive to the proliferation of highly pathogenic anaerobic bacteria, such as Capnocytophaga, Fusobacterium and Prevotella [6,7] . With the advancement of next-generation sequencing (NGS), microbial profiles associated with healthy states and periodontitis have become increasingly well-defined [8]. A series of pivotal studies have reported the characteristics of subgingival microbial communities in both chronic and aggressive periodontitis [9–13] . In 2018, the American Academy of Periodontology (AAP) and the European Federation of Periodontology (EFP) jointly introduced a new classification for periodontitis based on severity, CONTACT Qiang Feng [fengqiangsdu@163.com](fengqiangsdu@163.com); Mengfan Zhi Dreamzmf@outlook.com Department of Human Microbiome, School and Hospital of Stomatol

FAQs

What is the primary objective of the study?

To identify microbial taxa that may act as potential drivers underlying increasing severity of periodontitis.

Which methods were used to discover potential driver taxa?

The study reprocessed subgingival 16S rRNA gene sequencing data, used MaAsLin2 for differential taxa, built co-occurrence networks, applied NetMoss to identify key transition-driving microbes, and performed correlation and mediation analyses with clinical indicators.

What microbial patterns were observed across health and periodontitis groups?

Putative novel pathogens were enriched in periodontitis, while potential protective taxa showed higher relative abundance in the health group; network robustness decreased and vulnerability increased in more advanced stages.

Sep 30, 2026

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