Microbial ecology has been profoundly advanced by the ability to profile complex microbial communities by sequencing of marker genes amplified from environmental samples. However, inclusion of appropriate controls is vital to revealing the limitations and biases of this technique. "Mock community" samples, in which the composition and relative abundances of community members are known, are particularly valuable for guiding library preparation and data processing decisions. I generated a set of three mock communities using 19 different fungal taxa and demonstrate their utility by contrasting amplicon sequencing data obtained for the same communities under modifications to PCR conditions during library preparation. Increasing the number of PCR cycles elevated rates of chimera formation, and of errors in the final data set. Extension time during PCR had little impact on chimera formation, error rate or observed community structure. Polymerase fidelity impacted error rates significantly. Despite a high error rate, a master mix optimized to minimize amplification bias yielded profiles that were most similar to the true community structure. Bias against particular taxa differed among ITS1 vs. ITS2 loci. Preclustering nearly identical reads substantially reduced error rates, but did not improve similarity to the expected community structure. Inaccuracies in amplicon sequence-based estimates of fungal community structure were associated with amplification bias and size selection processes, as well as variable culling rates among reads from different taxa. In some cases, the numerically dominant taxon was completely absent from final data sets, highlighting the need for further methodological improvements to avoid biased observations of community profiles.
Keywords: MiSeq; amplicon sequencing; internal transcribed spacer (ITS); metabarcoding; mock community.
Published 2018. This article is a U.S. Government work and is in the public domain in the USA.