Dataset Information

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.

SUBMITTER: Laursen MF

PROVIDER: S-EPMC5633598 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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

Laursen Martin F MF Dalgaard Marlene D MD Bahl Martin I MI

Frontiers in microbiology 20171005

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 an ...[more]

PMID: 29051756

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Project description: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.

Project description:BACKGROUND:In spite of extensive research on the effect of mutation and selection on codon usage, a general model of codon usage bias due to mutational bias has been lacking. Because most amino acids allow synonymous GC content changing substitutions in the third codon position, the overall GC bias of a genome or genomic region is highly correlated with GC3, a measure of third position GC content. For individual amino acids as well, G/C ending codons usage generally increases with increasing GC bias and decreases with increasing AT bias. Arginine and leucine, amino acids that allow GC-changing synonymous substitutions in the first and third codon positions, have codons which may be expected to show different usage patterns. PRINCIPAL FINDINGS:In analyzing codon usage bias in hundreds of prokaryotic and plant genomes and in human genes, we find that two G-ending codons, AGG (arginine) and TTG (leucine), unlike all other G/C-ending codons, show overall usage that decreases with increasing GC bias, contrary to the usual expectation that G/C-ending codon usage should increase with increasing genomic GC bias. Moreover, the usage of some codons appears nonlinear, even nonmonotone, as a function of GC bias. To explain these observations, we propose a continuous-time Markov chain model of GC-biased synonymous substitution. This model correctly predicts the qualitative usage patterns of all codons, including nonlinear codon usage in isoleucine, arginine and leucine. The model accounts for 72%, 64% and 52% of the observed variability of codon usage in prokaryotes, plants and human respectively. When codons are grouped based on common GC content, 87%, 80% and 68% of the variation in usage is explained for prokaryotes, plants and human respectively. CONCLUSIONS:The model clarifies the sometimes-counterintuitive effects that GC mutational bias can have on codon usage, quantifies the influence of GC mutational bias and provides a natural null model relative to which other influences on codon bias may be measured.

Project description:A limited number of studies have been conducted to analyze ribosomal RNA (rRNA, present in the ribosome) in bioaerosol samples to identify currently or potentially active airborne microbes, although its genomic counterpart, the rRNA gene (on the chromosome) has been frequently targeted for airborne microbial community analysis. A knowledge gap still exists regarding whether the bioaerosol rRNA abundances are affected by the bioaerosol collection process. We investigated the effect of air sampling stress on the measurement and characterization of 16S rRNA for bioaerosols in the laboratory and field experiments using quantitative polymerase chain reaction (qPCR) and high-throughput sequencing techniques. In a laboratory study, known quantities of freshly grown Escherichia coli cells were spiked onto the filter of a Button Aerosol Sampler and into liquids of BioSampler and SpinCon air samplers and then exposed to sampling stress when the samplers were operated for 2h. We found that the recovered cellular 16S rRNA abundance as determined by qPCR was dependent on sampler type. Further, two devices (Button Aerosol Sampler and BioSampler) that exhibited markedly different efficiency in preserving 16S rRNA were employed in an outdoor environment to collect bioaerosols simultaneously on eight days in two different seasons. The abundance of 16S rRNA in the outdoor air sample (1.3×106-4.9×107copies/m3) was about two orders of magnitude higher than that of 16S rRNA gene (6.9×103-1.5×105copies/m3). The 16S rRNA sequences revealed a different bacterial community compared with 16S rRNA gene-based results across all samples, and this difference depended on the sampling device. In addition, a number of bacterial taxa exhibited higher abundance in the 16S rRNA gene sequences than in 16S rRNA sequences, which suggests the potential activities of certain microbes in airborne phase. Overall, this study highlights the importance of sampling device selection when analyzing RNA in bioaerosols.

Dataset Information

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

Publications

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

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