Abstract
Periodontitis is a chronic inflammatory disease associated with the presence of dysbiotic microbial communities. Several studies interrogating periodontitis pathogenesis have utilized the murine ligature-induced periodontitis (LIP) model, and have further examined the ligature-associated microbiome relying on 16SrRNA-based sequencing techniques. However, it is often very challenging to compare microbial profiles across studies, due to important differences in bioinformatic processing and databases used for taxonomic assignment. Thus, our study aim was to re-analyze microbiome sequencing data-sets from studies utilizing the LIP model, through a standardized bioinformatic analysis pipeline, generating a comprehensive overview of the microbial dysbiosis during experimental periodontitis.
We conducted a re-analysis of 16SrRNA gene sequencing datasets from 9 published studies utilizing the LIP model. Reads were grouped according the hypervariable region of the 16SrRNA gene amplified (V1-V3 and V4), preprocessed, binned into Operational Taxonomical Units (OTUs) and classified utilizing relevant databases. Alpha and beta-diversity analyses were conducted, alongside relative abundance profiling of microbial communities.
Our findings revealed similar microbial richness and diversity across studies, and determined shifts in microbial community structure determined by periodontitis induction and study of origin. Clear variations in the relative abundance of bacterial taxa were observed starting day 5 after ligation and onwards, consistent with a distinct microbial composition during health and experimental periodontitis. We also uncovered differentially represented bacterial taxa across studies, dominating periodontal health and LIP-associated communities.
Collectively, this re-analysis provides a unified overview of microbial dysbiosis during the LIP model, providing new insights that aim to inform further studies dedicated to unravelling oral host-microbial interactions.
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