Assessing the Accuracy of Quantitative Molecular Microbial Profiling
O'Sullivan, D.M., Laver, T., Temisak, S., Redshaw, N., Harris, K.A., Foy, C.A., Studholme, D.J., Huggett, J.F.
The application of high-throughput sequencing in profiling microbial communities is providing an unprecedented ability to investigate microbiomes. Such studies typically apply one of two methods: amplicon sequencing using PCR to target a conserved orthologous sequence (typically the 16S ribosomal RNA gene) or whole (meta)genome sequencing (WGS). Both methods have been used to catalog the microbial taxa present in a sample and quantify their respective abundances. However, a comparison of the inherent precision or bias of the different sequencing approaches has not been performed. We previously developed a metagenomic control material (MCM) to investigate error when performing different sequencing strategies. Amplicon sequencing using four different primer strategies and two 16S rRNA regions was examined (Roche 454 Junior) and compared to WGS (Illumina HiSeq). All sequencing methods generally performed comparably and in good agreement with organism specific digital PCR (dPCR); WGS notably demonstrated very high precision. Where discrepancies between relative abundances occurred they tended to differ by less than twofold. Our findings suggest that when alternative sequencing approaches are used for microbial molecular profiling they can perform with good reproducibility, but care should be taken when comparing small differences between distinct methods. This work provides a foundation for future work comparing relative differences between samples and the impact of extraction methods. We also highlight the value of control materials when conducting microbial profiling studies to benchmark methods and set appropriate thresholds.
O'Sullivan, D.M., Laver, T., Temisak, S., Redshaw, N., Harris, K.A., Foy, C.A., Studholme, D.J., Huggett, J.F. "Assessing the Accuracy of Quantitative Molecular Microbial Profiling" International Journal of Molecular Sciences (2014): 21,476–91