PCR Biases Distort Bacterial and Archaeal Community Structure in Pyrosequencing Datasets

Abstract

As 16S rRNA gene targeted massively parallel sequencing has become a common tool for microbial diversity investigations, numerous advances have been made to minimize the influence of sequencing and chimeric PCR artifacts through rigorous quality control measures. However, there has been little effort towards understanding the effect of multi-template PCR biases on microbial community structure. In this study, we used three bacterial and three archaeal mock communities consisting of, respectively, 33 bacterial and 24 archaeal 16S rRNA gene sequences combined in different proportions to compare the influences of (1) sequencing depth, (2) sequencing artifacts (sequencing errors and chimeric PCR artifacts), and (3) biases in multi-template PCR, towards the interpretation of community structure in pyrosequencing datasets. We also assessed the influence of each of these three variables on α- and β-diversity metrics that rely on the number of OTUs alone (richness) and those that include both membership and the relative abundance of detected OTUs (diversity). As part of this study, we redesigned bacterial and archaeal primer sets that target the V3–V5 region of the 16S rRNA gene, along with multiplexing barcodes, to permit simultaneous sequencing of PCR products from the two domains. We conclude that the benefits of deeper sequencing efforts extend beyond greater OTU detection and result in higher precision in β-diversity analyses by reducing the variability between replicate libraries, despite the presence of more sequencing artifacts. Additionally, spurious OTUs resulting from sequencing errors have a significant impact on richness or shared-richness based α- and β-diversity metrics, whereas metrics that utilize community structure (including both richness and relative abundance of OTUs) are minimally affected by spurious OTUs. However, the greatest obstacle towards accurately evaluating community structure are the errors in estimated mean relative abundance of each detected OTU due to biases associated with multi-template PCR reactions.

The proof of concept that culturomics can be superior to metagenomics to study atypical stool samples

“…We are grateful to the authors for their remarks, and we agree with the biases linked to metagenomics explaining the absence of reproducibility between the different studies about the gut microbiota repertoire and have reported this elsewhere [2][3][4]. Nevertheless, the aim of this study was to compare the most commonly used molecular method to explore the microbiota (pyrosequencing of 16 rRNA amplicons targeting the V6 region) used as a standard with culturomics [5].…”

Metagenomics insights into food fermentations

“…However, the data generated need to be interpreted with the awareness of culture‐independent PCR biases that have been reviewed elsewhere (Sipos et al ., 2010), such as the possibility of preferential amplification, due to the different efficiency of the primer towards selected species, that may result in the under‐representation of some clades (Pinto and Raskin, 2012). …”

Microbial community structure and diversity in the soil spatial profile of 5-year-old Robinia pseudoacacia ‘Idaho,’ determined by 454 sequencing of the 16S RNA gene

“…The remaining sequences were assigned to different groups by the RDP classifier using the same parameters described above, and the classification results before and after sequence trimming were compared. Although the sequencing effort in this study was not very deep, it has been shown that β-diversity-based analyses can be electively performed without requiring deep sequencing (Pinto and Raskin, 2012;Reeder and Knight, 2010). Specifically, deeper sequencing does not improve the accuracy of β-diversity estimates; it only improves precision (Pinto and Raskin, 2012).…”