Nested PCR Biases in Interpreting Microbial Community Structure in 16S rRNA Gene Sequence Datasets

Abstract

BackgroundSequencing of the PCR-amplified 16S rRNA gene has become a common approach to microbial community investigations in the fields of human health and environmental sciences. This approach, however, is difficult when the amount of DNA is too low to be amplified by standard PCR. Nested PCR can be employed as it can amplify samples with DNA concentration several-fold lower than standard PCR. However, potential biases with nested PCRs that could affect measurement of community structure have received little attention.ResultsIn this study, we used 17 DNAs extracted from vaginal swabs and 12 DNAs extracted from stool samples to study the influence of nested PCR amplification of the 16S rRNA gene on the estimation of microbial community structure using Illumina MiSeq sequencing. Nested and standard PCR methods were compared on alpha- and beta-diversity metrics and relative abundances of bacterial genera. The effects of number of cycles in the first round of PCR (10 vs. 20) and microbial diversity (relatively low in vagina vs. high in stool) were also investigated. Vaginal swab samples showed no significant difference in alpha diversity or community structure between nested PCR and standard PCR (one round of 40 cycles). Stool samples showed significant differences in alpha diversity (except Shannon’s index) and relative abundance of 13 genera between nested PCR with 20 cycles in the first round and standard PCR (P<0.01), but not between nested PCR with 10 cycles in the first round and standard PCR. Operational taxonomic units (OTUs) that had low relative abundance (sum of relative abundance <0.167) accounted for most of the distortion (>27% of total OTUs in stool).ConclusionsNested PCR introduced bias in estimated diversity and community structure. The bias was more significant for communities with relatively higher diversity and when more cycles were applied in the first round of PCR. We conclude that nested PCR could be used when standard PCR does not work. However, rare taxa detected by nested PCR should be validated by other technologies.

Diagnostic reliability of nested PCR depends on the primer design and threshold abundance ofHelicobacter pyloriin biopsy, stool, and saliva samples

“…An example of such an experiment on a biopsy specimen when DNA is amplified by nested PCR is shown in Figure . Nested PCR is prone to contamination because the tubes are opened to add the second round of primers and reagents . To avoid this problem, instead of a single negative control, a negative control was introduced after every sample (Figure ), and only cases with signal in the sample and no signal in the negative control in triplicate experiments were considered to be positive.…”

“…The first round targets a larger DNA region and the second round targets a narrower subregion of the products from the first round, which serves as the template. 6,18 Nested PCR is more sensitive than regular PCR because it can amplify target DNA with concentrations several-fold less than that of standard PCR. [18][19][20] On the other hand, this method is prone to contamination.…”

“…6,18 Nested PCR is more sensitive than regular PCR because it can amplify target DNA with concentrations several-fold less than that of standard PCR. [18][19][20] On the other hand, this method is prone to contamination. 18,21 However, nested PCR has the potential to be the gold standard for H pylori diagnostics when solving problems with sampling (uneven H pylori occurrence) and the frequent occurrence of false positives.…”

The highly variable microbiota associated to intestinal mucosa correlates with growth and hypoxia resistance of sea bass, Dicentrarchus labrax, submitted to different nutritional histories

“…Another potential source of bias may be due to resorting to nested PCR for mucosal samples with low concentration of bacterial 16S rRNA. Yu et al [21] expressed reservation about the detection of rare OTUs after using nested PCR. The present analysis focused on the most active OTUs, which were likely the most susceptible to dietary influence.…”

The effect of cigarette smoking on the oral and nasal microbiota

“…Sequence reads were processed to remove low quality and short reads (see details in [18]). The remaining reads (18,497 ± 14,130 reads/sample) were clustered into Operational Taxonomy Units (OTUs) at 97% identity using the command pick_open_reference_otus.py and Greengenes database as the reference (version 13_8) [19] in Quantitative Insights into Microbial Ecology (QIIME 1.8.0) [20].…”