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Functional Genomics Center Zurich, ETH-University of Zurich, Zürich, Switzerland (previous affiliation); EMBL Partnership Institute for Genome Editing Technologies, Life Sciences Center, Vilnius University, Vilnius, Lithuania; Institute of Bioscience, Life Sciences Center, Vilnius University, Vilnius, Lithuania.
Published: August 2024
AI Article Synopsis
Article Abstract
Introduction: In this study, we used metatranscriptomics for the first time to investigate microbial composition, functional signatures, and antimicrobial resistance gene expression in endodontic infections.
Methods: Root canal samples were collected from ten teeth, including five primary and five persistent/secondary endodontic infections. RNA from endodontic samples was extracted, and RNA sequencing was performed on a NovaSeq6000 system (Illumina). Taxonomic analysis was performed using the Kraken2 bacterial database. Then, sequences with a taxonomic classification were annotated against the Universal Protein Knowledgebase for functional annotation and the Comprehensive Antibiotic Resistance Database for AR-like gene identification.
Results: Proteobacteria, Bacteroidetes, Firmicutes, and Actinobacteria represented the dominant phyla, whereas Fusobacteria, Spirochetes, and Synergistetes were among the nondominant phyla. The top ten species were mainly represented by obligate (or quasiobligate) anaerobes, including Gram-negative (eg, Capnocytophaga sp. oral taxon 323, Fusobacterium nucleatum, Prevotella intermedia, Prevotella oris, Tannerella forsythia, and Tannerella sp. oral taxon HOT-286) and Gram-positive species (eg, Olsenella uli and Parvimonas micra). Transcripts encoding moonlighting proteins (eg, glycolytic proteins, translational elongation factors, chaperonin, and heat shock proteins) were highly expressed, potentially affecting bacterial adhesion, biofilm formation, host defense evasion, and inflammation induction. Endodontic bacteria expressed genes conferring resistance to antibiotic classes commonly used in dentistry, with a high prevalence and expression of tetracycline and lincosamide resistance genes. Antibiotic efflux and antibiotic target alteration/protection were the main resistance mechanisms.
Conclusions: Metatranscriptomics revealed the activity of potential endodontic pathogens, which expressed putative virulence factors and a wide diversity of genes potentially involved in AR.
