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Microvariation artifacts introduced by PCR and cloning of closely related 16S rRNA gene sequences.

ABSTRACT: A defined template mixture of seven closely related 16S-rDNA clones was used in a PCR-cloning experiment to assess and track sources of artifactual sequence variation in 16S rDNA clone libraries. At least 14% of the recovered clones contained aberrations. Artifact sources were polymerase errors, a mutational hot spot, and cloning of heteroduplexes and chimeras. These data may partially explain the high degree of microheterogeneity typical of sequence clusters detected in environmental clone libraries.

SUBMITTER: Speksnijder AG

PROVIDER: S-EPMC92603 | biostudies-literature | 2001 Jan

REPOSITORIES: biostudies-literature

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Microvariation artifacts introduced by PCR and cloning of closely related 16S rRNA gene sequences.

Speksnijder A G AG Kowalchuk G A GA De Jong S S Kline E E Stephen J R JR Laanbroek H J HJ

Applied and environmental microbiology 20010101 1

A defined template mixture of seven closely related 16S-rDNA clones was used in a PCR-cloning experiment to assess and track sources of artifactual sequence variation in 16S rDNA clone libraries. At least 14% of the recovered clones contained aberrations. Artifact sources were polymerase errors, a mutational hot spot, and cloning of heteroduplexes and chimeras. These data may partially explain the high degree of microheterogeneity typical of sequence clusters detected in environmental clone libr ...[more]

PMID: 11133483

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Project description:The advent of next generation sequencing has coincided with a growth in interest in using these approaches to better understand the role of the structure and function of the microbial communities in human, animal, and environmental health. Yet, use of next generation sequencing to perform 16S rRNA gene sequence surveys has resulted in considerable controversy surrounding the effects of sequencing errors on downstream analyses. We analyzed 2.7×10(6) reads distributed among 90 identical mock community samples, which were collections of genomic DNA from 21 different species with known 16S rRNA gene sequences; we observed an average error rate of 0.0060. To improve this error rate, we evaluated numerous methods of identifying bad sequence reads, identifying regions within reads of poor quality, and correcting base calls and were able to reduce the overall error rate to 0.0002. Implementation of the PyroNoise algorithm provided the best combination of error rate, sequence length, and number of sequences. Perhaps more problematic than sequencing errors was the presence of chimeras generated during PCR. Because we knew the true sequences within the mock community and the chimeras they could form, we identified 8% of the raw sequence reads as chimeric. After quality filtering the raw sequences and using the Uchime chimera detection program, the overall chimera rate decreased to 1%. The chimeras that could not be detected were largely responsible for the identification of spurious operational taxonomic units (OTUs) and genus-level phylotypes. The number of spurious OTUs and phylotypes increased with sequencing effort indicating that comparison of communities should be made using an equal number of sequences. Finally, we applied our improved quality-filtering pipeline to several benchmarking studies and observed that even with our stringent data curation pipeline, biases in the data generation pipeline and batch effects were observed that could potentially confound the interpretation of microbial community data.

Project description:16S rRNA gene sequences are commonly analyzed for taxonomic and phylogenetic studies because they contain variable regions that can help distinguish different genera. However, intra-genus distinction using variable region homology is often impossible due to the high overall sequence identities among closely related species, even though some residues may be conserved within respective species. Using a computational method that included the allelic diversity within individual genomes, we discovered that certain Escherichia and Shigella species can be distinguished by a multi-allelic 16S rRNA variable region single nucleotide polymorphism (SNP). To evaluate the performance of 16S rRNAs with altered variable regions, we developed an in vivo system that measures the acceptance and distribution of variant 16S rRNAs into a large pool of natural versions supporting normal translation and growth. We found that 16S rRNAs containing evolutionarily disparate variable regions were underpopulated both in ribosomes and in active translation pools, even for an SNP. Overall, this study revealed that variable region sequences can substantially influence the performance of 16S rRNAs and that this biological constraint can be leveraged to justify refining taxonomic assignments of variable region sequence data. IMPORTANCE This study reevaluates the notion that 16S rRNA gene variable region sequences are uninformative for intra-genus classification and that single nucleotide variations within them have no consequence to strains that bear them. We demonstrated that the performance of 16S rRNAs in Escherichia coli can be negatively impacted by sequence changes in variable regions, even for single nucleotide changes that are native to closely related Escherichia and Shigella species; thus, biological performance is likely constraining the evolution of variable regions in bacteria. Further, the native nucleotide variations we tested occur in all strains of their respective species and across their multiple 16S rRNA gene copies, suggesting that these species evolved beyond what would be discerned from a consensus sequence comparison. Therefore, this work also reveals that the multiple 16S rRNA gene alleles found in most bacteria can provide more informative phylogenetic and taxonomic detail than a single reference allele.

Dataset Information

Microvariation artifacts introduced by PCR and cloning of closely related 16S rRNA gene sequences.

Publications

Microvariation artifacts introduced by PCR and cloning of closely related 16S rRNA gene sequences.

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