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Published on: March 23, 2018
Development and Validation of Mock Communities as Quality Control Materials for Clinical Metagenomic Next-Generation
Dokyun Kim1, Songhee Lee2, Da Young Kang3
1Department of Laboratory Medicine and Research Institute of Bacterial Resistance, Yonsei University College of Medicine, Seoul, Korea.
Background:
Metagenomic next-generation sequencing (NGS) enables comprehensive detection of a broad spectrum of microorganisms. However, its clinical application faces two major challenges: the development of appropriate microbiome-based biomarkers and the need to ensure the reproducibility and quality of the microbiome analytical workflow. Therefore, we developed four types of bead-based mock communities as standard materials for microbiome analysis and evaluated potential experimental biases arising from nucleic acid extraction and sequence analysis.
Methods:
Mock communities were assembled from strains isolated from clinical specimens and selected considering Gram reaction, taxonomic phylogeny, and prevalence, and processed into frozen beads. The communities were analyzed using shotgun whole-metagenome sequencing. The effect of DNA extraction kit choice was evaluated using the Thermo Fisher Scientific MagMAX Microbiome Ultra Nucleic Acid Isolation Kit and Qiagen PowerSoil Kit.
Results:
Four types of mock communities comprising 26 species commonly found in the gastrointestinal tract, respiratory tract, skin, and genital tract plus cerebrospinal fluid were developed considering Gram reaction, GC content, and phylogenetic distribution. Across 25 repeated analyses, the median repeatability of each taxon was 18.97% (range, 2.87%-107.38%), while within-laboratory imprecision was 26.22% (range, 9.26%-153.83%). Repeatability remained below 10% for most dominant taxa with relative abundances >20%. The choice of DNA extraction kit had a significant effect on taxonomic distributions.
Conclusions:
Microbial mock communities are essential QC materials for clinical metagenomic NGS. Further studies are needed to minimize variability and establish a standardized protocol for clinical implementation.
