Clinical Investigation of Bacteriome in Primary Endodontic Infections With Apical Periodontitis Using High-Throughput Sequencing Analysis

Introduction

This study characterized the bacteriome in primary endodontic infection (PEI) with apical periodontitis (AP), identified core and rare bacteriome species and community diversity metrics, and analyzed the relationship between the bacteriome composition, diversity and features, and patient variables.

Methods

Twenty-seven patients with PEI and AP were sampled. The DNA was extracted and quantified using quantitative polymerase chain reaction. Raw V3-V4 amplicon sequencing data were processed with the DADA2 pipeline to generate amplicon sequence variants, and taxonomic assignment of the amplicon sequence variants up to the species level was done against the Human Oral Microbiome Database. Core bacteriome and differential abundance analyses were performed using ANCOM. Alpha diversity was determined using Chao1, Shannon, and Simpson indexes. LeFse analysis was used to identify abundant taxa. Sparse Estimation of Correlations among Microbiomes analysis estimated linear and nonlinear relationships among bacteria.

Results

Of 27, 24 root canal samples were analyzed, and 3 root canal sampling were filtered out with a low read count. The bacterial phyla with top mean relative abundance were Bacteroidetes, Firmicutes, Synergistetes, Fusobacteria, and Actinobacteria. A total of 113 genera and 215 species were identified. The samples were gathered into 3 clusters. LefSe analysis identified differences in abundant taxa between distinct age, gender, symptomatology, and lesion size groups. Sparse Estimation of Correlations among Microbiomes distance analysis indicated Slackia exigua as the node with the highest degree.

Conclusions

The bacteriome in PEI with AP among the patients in this study was complex and displayed high microbial heterogeneity. Moreover, age, gender, symptomatology, and lesion size were associated with differences in bacteriome features in PEI with AP.