Dental plaque microbiota sequence counts for microbial profiling and resistance genes detection

Area of Science:

• Microbiology
• Genomics
• Bioinformatics

Background:

• Shotgun metagenomics is widely applied but lacks clear guidelines on sequencing depth for taxonomic profiling and antimicrobial resistance gene (ARG) detection.
• Oral microbiota studies require sufficient sequencing data for reliable microbial identification and ARG analysis.

Purpose of the Study:

• To determine optimal sequencing depths for shotgun metagenomics in oral microbiota analysis.
• To evaluate the impact of sequencing volume on taxonomic profiling and ARG detection accuracy.

Main Methods:

• Downsampling of high-coverage (approx. 100 million reads) human plaque samples and a microbial community standard.
• Analysis of microbial species identification, abundance estimation, and ARG presence/absence across varying read counts.

Main Results:

• Taxonomic profiling showed discrepancies in species identification and abundance, particularly below 40 million reads, indicating limitations in profiling methods.
• Antimicrobial resistance gene detection was significantly impacted, with over half lost below 20 million reads and 23% showing inconsistent presence/absence.
• Recommended sequence numbers: 40 million for microbiota profiling, 50 million for low-abundance species detection, and 20 million for ARG identification.

Conclusions:

• Sequencing depth critically affects qualitative metagenomic data, especially below 40 million reads.
• Abundance estimation is less sensitive to read count, though low-abundance species detection benefits from higher coverage.
• Specific sequencing depths are recommended based on the primary analytical goals of oral microbiome shotgun metagenomics studies.