![]() ![]() Circular consensus sequencing of PacBio allows amplicon sequences to be recovered with excellent quality 18. Recently, rapid technical improvement in third-generation sequencing platforms, such as PacBio Single-Molecule Long-Read Sequencing (Pacific Biosystems, USA) allow the reading of sequences with an average length of 10–20 kb 17. Therefore, the amplicon method of the partial variable region (V3–V4) is limited for strains with high similarity at the species level 16. ![]() However, this short read amplicon-based platform is not only vulnerable to the identification bias due to the potential chimeric sequences produced during PCR amplification for library construction, but also is limited to microbial classification at the genus level according to a commonly used 16S rRNA gene-based microbial taxonomy database. It is widely used for various metagenome studies by reducing the high-cost burden of NGS 15. In general, high-throughput short-read sequencing of the 16S rRNA gene amplicon based on the Illumina MiSeq 2 × 300 bp platform (Illumina, USA) specifically targets the V3–V4 hypervariable region of the nine variable regions. Currently, the second-generation sequencing platforms are being utilized for microbial diversity analysis by reading a single or combination of the hypervariable regions (e.g., V1V2, V3V4, V4, and V5V6 regions on the 16S rRNA gene) 12, 13, 14. The Pyrosequencing-based Roche 454 GS-FLX used in early metagenome studies, despite its new paradigm for microbial research, was discontinued due to some issues, including high base-calling errors and sequencing cost differences 11. In metagenomic sequencing, the nine hypervariable regions (V1–V9) of 16S rRNA gene are frequently used for determining of the bacterial taxonomy such as genera or species in the diverse microbial population 10. However, with the recent rapid development of the next-generation sequencing (NGS) technology, metagenome sequencing is becoming a powerful approach to understanding the complex microbial communities in the human GUT 9. There have historically been many challenges regarding the efficient analysis of microbial communities due to the impossibility of identifying those that cannot be cultured, and microbial identification analysis was previously limited to culture-dependent sequencing methods based on Sanger sequencing technology 7, 8. Therefore, characterizing the diversity and composition of the microbial communities inhabiting specimen is one of the primary objectives of current microbial studies 4, 5, 6. Recently, studies regarding the human GUT microbiota have been conducted worldwide, and many, such as the human microbiome project (HMP), have shown that the human GUT microbiota are strongly related to the development of various diseases 2, 3. The microbiota is the total microbial complex containing the wide variety of bacterial species and is found everywhere, from humans (e.g., the microbiota inhabiting animal intestines) to natural environments 1. Therefore, this study suggests that the new sFL16S method is a suitable tool to overcome the weakness of the V3V4 method. Furthermore, we demonstrated that sFL16S could overcome the microbial misidentification caused by different sequence similarity in each 16S variable region through comparison the identification accuracy of Bifidobacterium, Bacteroides, and Alistipes strains classified from both methods. At the species level, we confirmed that sFL16S showed better resolutions than V3V4 in analyses of alpha-diversity, relative abundance frequency and identification accuracy. Our comparison analyses of sFL16S and V3V4 sequencing data showed that they were highly similar at all classification resolutions except the species level. ![]() ![]() We compared a 16S full-length-based synthetic long-read (sFL16S) and V3-V4 short-read (V3V4) methods using 24 human GUT microbiota samples. Loop Genomics recently proposed a new 16S full-length-based synthetic long-read sequencing technology (sFL16S). A short-read sequencing platform for reading partial regions of the 16S rRNA gene is most commonly used by reducing the cost burden of next-generation sequencing (NGS), but misclassification at the species level due to its length being too short to consider sequence similarity remains a challenge. Characterizing the microbial communities inhabiting specimens is one of the primary objectives of microbiome studies. ![]()
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