The World Health Organization (WHO) has declared the coronavirus disease 2019 (COVID-19) as an international health emergency. Current diagnostic tests are based on the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) method, which is the gold standard test that involves the amplification of viral RNA. However, the RT-qPCR assay has limitations in terms of sensitivity and quantification. In this study, we tested both qPCR and droplet digital PCR (ddPCR) to detect low amounts of viral RNA. The cycle threshold (C T ) of the viral RNA by RT-PCR significantly varied according to the sequences of the primer and probe sets with in vitro transcript (IVT) RNA or viral RNA as templates, whereas the copy number of the viral RNA by ddPCR was effectively quantified with IVT RNA, cultured viral RNA, and RNA from clinical samples. Furthermore, the clinical samples were assayed via both methods, and the sensitivity of the ddPCR was determined to be equal to or more than that of the RT-qPCR. However, the ddPCR assay is more suitable for determining the copy number of reference materials. These findings suggest that the qPCR assay with the ddPCR defined reference materials could be used as a highly sensitive and compatible diagnostic method for viral RNA detection.

Microbial community analysis based on the 16S rRNA-gene is used to investigate both beneficial and harmful microorganisms in various fields and environments. Recently, the next-generation sequencing (NGS) technology has enabled rapid and accurate microbial community analysis. Despite these advantages of NGS based metagenomics study, sample transport, storage conditions, amplification, library preparation kits, sequencing, and bioinformatics procedures can bias microbial community analysis results. In this study, eight mock communities were pooled from genomic DNA of Lactobacillus acidophilus KCTC 3164T, Limosilactobacillus fermentum KCTC 3112T, Lactobacillus gasseri KCTC 3163T, Lacticaseibacillus paracasei subsp. paracasei KCTC 3510T, Limosilactobacillus reuteri KCTC 3594T, Lactococcus lactis subsp. lactis KCTC 3769T, Bifidobacterium animalis subsp. lactis KCTC 5854T, and Bifidobacterium breve KCTC 3220T. The genomic DNAs were quantified by droplet digital PCR (ddPCR) and were mixed as mock communities. The mock communities were amplified with various 16S rRNA gene universal primer pairs and sequenced by MiSeq, IonTorrent, MGIseq-2000, Sequel II, and MinION NGS platforms. In a comparison of primer-dependent bias, the microbial profiles of V1-V2 and V3 regions were similar to the original ratio of the mock communities, while the microbial profiles of the V1-V3 region were relatively biased. In a comparison of platform-dependent bias, the sequence read from short-read platforms (MiSeq, IonTorrent, and MGIseq-2000) showed lower bias than that of long-read platforms (Sequel II and MinION). Meanwhile, the sequences read from Sequel II and MinION platforms were relatively biased in some mock communities. In the data of all NGS platforms and regions, L. acidophilus was greatly underrepresented while Lactococcus lactis subsp. lactis was generally overrepresented. In all samples of this study, the bias index (BI) was calculated and PCA was performed for comparison. The samples with biased relative abundance showed high BI values and were separated in the PCA results. In particular, analysis of regions rich in AT and GC poses problems for genome assembly, which can lead to sequencing bias. According to this comparative analysis, the development of reference material (RM) material has been proposed to calibrate the bias in microbiome analysis.