In-silico Selection of the Best 16S rRNA Gene Primers for Detecting Oral Bacteria and Archaea

Objectives: The objectives of the present study were: 1) To analyse the coverage of 16S rRNA gene primers in silico using oral-specific databases containing 16S rRNA gene sequences from bacteria and archaea found in the oral cavity; and 2) To describe the best primer pairs for each domain. Methods: A total of 369 distinct, individual primers were identified from oral microbiome studies and other ecosystems. These were evaluated against a previously published oral bacteria 16S rRNA sequence database, which was modified by our group, and a self-created oral-archaea database. Each database contained the genomic variants detected for all the species included. Primers with a species coverage (SC) ≥75.00% were selected for the analyses, and the two databases were used to examine 4638 primer pairs. These base pairs were then grouped into three categories according to their mean amplicon length: 100-300, 301-600 and > 600 bps. Results: In relation to the three amplicon-length categories, the best bacteria-specific pairs targeted the 3-4, 4-7 and 3-7 16S rRNA gene regions, with SC of 97.14-98.83%; the optimum archaea-specific primer pairs amplified regions 5-6, 3-5 and 3-6, with an estimated SC of 95.88%. Finally, the best pairs for detecting the two domains targeted regions 4-5, 3-5 and 5-9, with SC values of 94.54-95.71% and 96.91-99.48% for bacteria and archaea, respectively. Conclusions: The primer pairs with the best coverage for detecting oral bacteria were: KP_F048-OP_R043 (primer pair position for Escherichia coli J01859.1: 342-529); KP_F051-OP_R030 (514-1079); and KP_F048-OP_R030 (342-1079). The optimum pairs for detecting oral archaea were: OP_F066-KP_R013 (784-undefined); KP_F020-KP_R013 (518-undefined); and OP_F114-KP_R013 (340-undefined), while for the two domains jointly, they were: KP_F020-KP_R032 (518-801); OP_F114-KP_R031 (340-801); and OP_F066-OP_R121 (784-1405). The primer pairs with the best coverage identified herein are not among those described most widely in the oral microbiome literature.

keywords: bioinformatics