ABSTRACT
AIMS: Approximately 10% of children are born prematurely, and bacterial vaginosis during pregnancy is associated with preterm delivery. Highly accurate species-level vaginal microflora analysis helps control bacteria-induced preterm birth. Therefore, we aimed to conduct a bioinformatic analysis of gene sequences using 16S databases and compare their efficacy in comprehensively identifying potentially pathogenic vaginal microbiota in Japanese women. METHODS AND RESULTS: The 16 s rRNA databases, Silva, Greengenes, and the basic local alignment search tool (BLAST) were compared to determine whether the classification quality could be improved using the V3-V4 region next-generation sequencing (NGS) sequences. It was found that NGS data were aligned using the BLAST database with the QIIME 2 platform, whose classification quality was higher than that of Silva, and the combined Silva and Greengenes databases based on the mutual complementarity of the two databases. CONCLUSIONS: The reference database selected during the bioinformatic processing influenced the recognized sequence percentage, taxonomic rankings, and accuracy. This study showed that the BLAST database was the best choice for NGS data analysis of Japanese women's vaginal microbiota.
