Comparative metagenomic and rRNA microbial diversity characterization using archaeal and bacterial synthetic communities
Shakya M, Quince C, Campbell JH, Yang ZK, Schadt CW, Podar M.
2013 January 08, Environmental Microbiology (2013), 15(6): 1882-1899
Next-generation sequencing has dramatically changed the landscape of microbial ecology, largescale and in-depth diversity studies being now widely accessible. However, determining the accuracy of taxonomic and quantitative inferences and comparing results obtained with different approaches are complicated by incongruence of experimental and computational data types and also by lack of knowledge of the true ecological diversity. Here we used highly diverse bacterial and archaeal synthetic communities assembled from pure genomic DNAs to compare inferences from metagenomic and SSU rRNA amplicon sequencing. Both Illumina and 454 metagenomic data outperformed amplicon sequencing in quantifying the community composition, but the outcome was dependent on analysis parameters and platform. New approaches in processing and classifying amplicons can reconstruct the taxonomic composition of the community with high reproducibility within primer sets, but all tested primers sets lead to significant taxon-specific biases. Controlled synthetic communities assembled to broadly mimic the phylogenetic richness in target environments can provide important validation for fine-tuning experimental and computational parameters used to characterize natural communities.
Taxonomic and functional characterization of microbial communities by rRNA gene and metagenomic sequencing have been used extensively. Determining accuracy and performing cross-comparisons between approaches are limited by data incongruences and the lack of knowledge of the true ecological diversity
We used complex mixes of bacterial and archaeal pure genomic DNAs to directly compare inferences from metagenomic and rRNA amplicon sequencing. Both Illumina and 454 metagenomic data outperformed amplicon sequencing in quantifying the community composition. The accuracy of public analysis platforms (IMG, MG-RAST) and several widely used software was highly dependent on analysis parameters. Sources of errors were identified and we proposed alternatives to correct them.
A synthetic community approach is important for calibrating and validating experimental design and data analysis in long term environmental studies.
Shakya, M., Quince, C., Campbell, J. H., Yang, Z. K., Schadt, C. W. and Podar, M. (2013), Comparative metagenomic and rRNA microbial diversity characterization using archaeal and bacterial synthetic communities. Environmental Microbiology, 15: 1882â1899. doi: 10.1111/1462-2920.12086