Genomic GC-Content Affects the Accuracy of 16S rRNA Gene Sequencing Based Microbial Profiling due to PCR Bias

Abstract

Profiling of microbial community composition is frequently performed by partial 16S rRNA gene sequencing on benchtop platforms following PCR amplification of specific hypervariable regions within this gene. Accuracy and reproducibility of this strategy are two key parameters to consider, which may be influenced during all processes from sample collection and storage, through DNA extraction and PCR based library preparation to the final sequencing. In order to evaluate both the reproducibility and accuracy of 16S rRNA gene based microbial profiling using the Ion Torrent PGM platform, we prepared libraries and performed sequencing of a well-defined and validated 20-member bacterial DNA mock community on five separate occasions and compared results with the expected even distribution. In general the applied method had a median coefficient of variance of 11.8% (range 5.5–73.7%) for all 20 included strains in the mock community across five separate sequencing runs, with underrepresented strains generally showing the largest degree of variation. In terms of accuracy, mock community species belonging to Proteobacteria were underestimated, whereas those belonging to Firmicutes were mostly overestimated. This could be explained partly by premature read truncation, but to larger degree their genomic GC-content, which correlated negatively with the observed relative abundances, suggesting a PCR bias against GC-rich species during library preparation. Increasing the initial denaturation time during the PCR amplification from 30 to 120 s resulted in an increased average relative abundance of the three mock community members with the highest genomic GC%, but did not significantly change the overall evenness of the community distribution. Therefore, efforts should be made to optimize the PCR conditions prior to sequencing in order to maximize accuracy.

Ecological and microbiological diversity of chigger mites, including vectors of scrub typhus, on small mammals across stratified habitats in Thailand

“…Pooling appears to be an obvious solution to the problem of low biomass samples [65], but is not without its own drawbacks. Genomic GC content is now well known as a source of bias in 16S rRNA datasets, with higher GC content leading to underrepresentation [66], as we observed here with Geobacillus spp. (relatively high median GC of ~52%) in pooled samples.…”

Breastmilk-promoted bifidobacteria produce aromatic amino acids in the infant gut

“…Sequences from SKOT and CIG were analyzed separately. Briefly, they were de-multiplexed according to barcode and trimmed as previously described 65, 66 in CLC Genomic Workbench (v8.5. CLCbio, Qiagen, Aarhus, DK).…”

Metagenome complexity and template length are the main causes of bias in PCR‐based bacteria community analysis

“…PCR amplification conditions such as cycle number, annealing temperature, stringency of primers, and GC content of the template are considered as important sources of biases in multi‐template amplification . Cycle number was reported to greatly affect the bias in multi‐template amplification.…”

“…By using the four‐species model and the complementary matched primer PF‐PR, we examined the effect of GC content of templates. According to Laursen , lower GC content of 16S rRNA gene fragment amplified better because 16S rRNA gene fragment dissociated into single‐strand molecules with higher efficiency. The GC content of four stains Rho, Cellu, Micro, and Agro decreased in turn.…”

“…However, lack of knowledge regarding the contribution of each parameter involved in such analysis does not allow for quantitative conclusions. Each step in community analysis is open to error or bias , including cell lysis, DNA extraction and purification , primer selection, PCR conditions , and cloning. Although, many studies have attempted to reduce the PCR bias and artifacts in artificial communities, it remains difficult to apply these results to environmental samples.…”