title: Groundtruthing next-gen sequencing for microbial ecology-biases and errors in community structure estimates from PCR amplicon pyrosequencing.
abstract: Analysis of microbial communities by high-throughput pyrosequencing of SSU rRNA gene PCR amplicons has transformed microbial ecology research and led to the observation that many communities contain a diverse assortment of rare taxa-a phenomenon termed the Rare Biosphere. Multiple studies have investigated the effect of pyrosequencing read quality on operational taxonomic unit (OTU) richness for contrived communities, yet there is limited information on the fidelity of community structure estimates obtained through this approach. Given that PCR biases are widely recognized, and further unknown biases may arise from the sequencing process itself, a priori assumptions about the neutrality of the data generation process are at best unvalidated. Furthermore, post-sequencing quality control algorithms have not been explicitly evaluated for the accuracy of recovered representative sequences and its impact on downstream analyses, reducing useful discussion on pyrosequencing reads to their diversity and abundances. Here we report on community structures and sequences recovered for in vitro-simulated communities consisting of twenty 16S rRNA gene clones tiered at known proportions. PCR amplicon libraries of the V3-V4 and V6 hypervariable regions from the in vitro-simulated communities were sequenced using the Roche 454 GS FLX Titanium platform. Commonly used quality control protocols resulted in the formation of OTUs with >1% abundance composed entirely of erroneous sequences, while over-aggressive clustering approaches obfuscated real, expected OTUs. The pyrosequencing process itself did not appear to impose significant biases on overall community structure estimates, although the detection limit for rare taxa may be affected by PCR amplicon size and quality control approach employed. Meanwhile, PCR biases associated with the initial amplicon generation may impose greater distortions in the observed community structure.
authors.affiliation: Department of Biological Sciences, University of Waikato, Hamilton, New Zealand.
authors.forename: Charles K
authors.initials: CK
authors.lastname: Lee
authors.forename: Craig W
authors.initials: CW
authors.lastname: Herbold
authors.forename: Shawn W
authors.initials: SW
authors.lastname: Polson
authors.forename: K Eric
authors.initials: KE
authors.lastname: Wommack
authors.forename: Shannon J
authors.initials: SJ
authors.lastname: Williamson
authors.forename: Ian R
authors.initials: IR
authors.lastname: McDonald
authors.forename: S Craig
authors.initials: SC
authors.lastname: Cary
mesh_terms: D000465:Algorithms; D001419:Bacteria / Q000235:genetics*; D001483:Base Sequence; D015982:Bias; D058448:Biota; D017931:DNA Primers / Q000378:metabolism; D016133:Polymerase Chain Reaction / Q000379:methods*; D012336:RNA, Ribosomal, 16S / Q000235:genetics; D017422:Sequence Analysis, DNA / Q000379:methods*; D018709:Statistics, Nonparametric; D013696:Temperature
chemical_list: D017931:DNA Primers; D012336:RNA, Ribosomal, 16S