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<p>Peri-implantitis is a severe biofilm-associated infection affecting millions worldwide. This cross-sectional study aimed to identify taxonomic and functional biomarkers that reliably indicate peri-implantitis by utilizing paired data from full length 16S rRNA gene amplicon sequencing (full-16S) and metatranscriptomics (RNAseq) in 48 biofilm samples from 32 patients. Both full-16S and RNAseq analyses revealed significant differences between healthy and peri-implantitis samples, with a shift toward anaerobic Gram-negative bacteria in peri-implantitis. Metatranscriptomics identified enzymatic activities and metabolic pathways associated with peri-implantitis and uncovered complex peri-implant biofilm ecology related to amino acid metabolism. Integrating taxonomic and functional data enhanced predictive accuracy (AUC = 0.85) and revealed diagnostic biomarkers including health-associated <i>Streptococcus</i> and <i>Rothia</i> species and peri-implantitis-associated enzymes (urocanate hydratase, tripeptide aminopeptidase, NADH:ubiquinone reductase, phosphoenolpyruvate carboxykinase and polyribonucleotide nucleotidyltransferase). Thus, biofilm profiling at taxonomic and functional levels provides highly predictive disease biomarkers, laying the foundation for novel diagnostic and personalized treatment approaches for peri-implant disease.</p>

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Integrative microbiome- and metatranscriptome-based analyses reveal diagnostic biomarkers for peri-implantitis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月26日

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  • Amruta A. Joshi,
  • Szymon P. Szafrański,
  • Matthias Steglich,
  • Ines Yang,
  • Taoran Qu,
  • Paula Schaefer-Dreyer,
  • Xing Xiao,
  • Wiebke Behrens,
  • Jasmin Grischke,
  • Susanne Häussler,
  • Meike Stiesch

摘要

Peri-implantitis is a severe biofilm-associated infection affecting millions worldwide. This cross-sectional study aimed to identify taxonomic and functional biomarkers that reliably indicate peri-implantitis by utilizing paired data from full length 16S rRNA gene amplicon sequencing (full-16S) and metatranscriptomics (RNAseq) in 48 biofilm samples from 32 patients. Both full-16S and RNAseq analyses revealed significant differences between healthy and peri-implantitis samples, with a shift toward anaerobic Gram-negative bacteria in peri-implantitis. Metatranscriptomics identified enzymatic activities and metabolic pathways associated with peri-implantitis and uncovered complex peri-implant biofilm ecology related to amino acid metabolism. Integrating taxonomic and functional data enhanced predictive accuracy (AUC = 0.85) and revealed diagnostic biomarkers including health-associated Streptococcus and Rothia species and peri-implantitis-associated enzymes (urocanate hydratase, tripeptide aminopeptidase, NADH:ubiquinone reductase, phosphoenolpyruvate carboxykinase and polyribonucleotide nucleotidyltransferase). Thus, biofilm profiling at taxonomic and functional levels provides highly predictive disease biomarkers, laying the foundation for novel diagnostic and personalized treatment approaches for peri-implant disease.