Porphyromonas gingivalis, a major pathogen of chronic periodontitis, colonizes in subgingival crevice and affects surrounding oral tissues, especially in periodontitis patients. Oral cancer mainly occurs in old-aged persons, and are exposed to the P. gingivalis, released from periodontitis, one of the most common inflammatory disease of oral cavity. Thus oral cancer cells may be infected with P. gingivalis, and its biologic behavior are autologously and/or heterogeneously modulated by altering gene expression. Exosomes which are derived from cells contain not only coding genes but also non-coding RNAs such as long non-coding RNAs, miRNA, and piRNAs. Here, to investigate the effect of P. gingivalis on oral cancer cells and to gain insight into the crosstalk between inflammatory signal from tumor microenvironment and oral cancer, we observed miRNA profiles of exosomes from P. gingivalis–infected oral cancer cells. Upregulation of 6 miRNAs, miR-203-3p, miR-6516-3p, miR-483-5p, miR-1275, miR-8485, and miR-19a-3p, were observed whereas 14 miRNAs including let-7a-3p, miR-106a-5p were downregulated. In addition, KEGG pathway analysis using the upregulated- and downregulated- miRNAs showed association with cell adhesion molecules pathway and ECM-receptor interaction pathway, respectively. These findings suggest that P. gingivalis could modulate biologic behavior of oral cancer cells through changes of exosomal miRNAs.

Accurate identification of microbes facilitates the prediction, prevention, and treatment of human diseases. To increase the accuracy of microbiome data analysis, a long region of the 16S rRNA is commonly sequenced via paired-end sequencing. In paired-end sequencing, a sufficient length of overlapping region is required for effective joining of the reads, and high-quality sequencing reads are needed at the overlapping region. Trimming sequences at the reads distal to a point where sequencing quality drops below a specific threshold enhance the joining process. In this study, we examined the effect of trimming conditions on the number of reads that remained after quality control and chimera removal in the Illumina paired-end reads of the V3–V4 hypervariable region. We also examined the alpha diversity and taxa assigned by each trimming condition. Optimum quality trimming increased the number of good reads and assigned more number of operational taxonomy units. The pre-analysis trimming step has a great influence on further microbiome analysis, and optimized trimming conditions should be applied for Divisive Amplicon Denoising Algorithm 2 analysis in QIIME2 platform.

In the oral cavity, complex microbial community is shaped by various host and environmental factors. Extensive literature describing the oral microbiome in the context of oral health and disease is available. Advances in DNA sequencing technologies and data analysis have drastically improved the analysis of the oral microbiome. For microbiome study, bacterial 16S ribosomal RNA gene amplification and sequencing is often employed owing to the cost-effective and fast nature of the method. In this review, practical considerations for performing a microbiome study, including experimental design, molecular analysis technology, and general data analysis, will be discussed.