Comparison of 16S rRNA Gene Based Microbial Profiling Using Five Next-Generation Sequencers and Various Primers

Area of Science:

• Microbiology
• Genomics
• Bioinformatics

Background:

• 16S rRNA gene sequencing is crucial for microbial community analysis.
• Next-generation sequencing (NGS) offers rapid and accurate microbial analysis.
• Potential biases in NGS workflows can affect microbiome study outcomes.

Purpose of the Study:

• To evaluate primer-dependent and platform-dependent biases in 16S rRNA gene sequencing.
• To identify specific microorganisms that are underrepresented or overrepresented in NGS data.
• To propose solutions for calibrating biases in microbiome analysis.

Main Methods:

• Construction of eight mock microbial communities from known bacterial genomic DNA.
• Amplification of 16S rRNA gene regions using various primer pairs.
• Sequencing of mock communities on multiple NGS platforms (MiSeq, IonTorrent, MGIseq-2000, Sequel II, MinION).
• Analysis of sequence data to assess primer and platform biases using bias index (BI) and principal component analysis (PCA).

Main Results:

• V1-V2 and V3 regions showed less bias than the V1-V3 region.
• Short-read platforms (MiSeq, IonTorrent, MGIseq-2000) exhibited lower bias than long-read platforms (Sequel II, MinION).
• Lactobacillus acidophilus was consistently underrepresented, while Lactococcus lactis subsp. lactis was overrepresented across platforms and regions.
• High BI values correlated with biased relative abundance and distinct separation in PCA plots.

Conclusions:

• Primer selection and NGS platform significantly influence microbial community profiling.
• Specific bacterial taxa can be systematically misrepresented in NGS-based microbiome studies.
• Development of reference materials is recommended to standardize and calibrate microbiome analysis, improving accuracy and reliability.