Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons

Abstract

Bacterial diversity among environmental samples is commonly assessed with PCR-amplified 16S rRNA gene (16S) sequences. Perceived diversity, however, can be influenced by sample preparation, primer selection, and formation of chimeric 16S amplification products. Chimeras are hybrid products between multiple parent sequences that can be falsely interpreted as novel organisms, thus inflating apparent diversity. We developed a new chimera detection tool called Chimera Slayer (CS). CS detects chimeras with greater sensitivity than previous methods, performs well on short sequences such as those produced by the 454 Life Sciences (Roche) Genome Sequencer, and can scale to large data sets. By benchmarking CS performance against sequences derived from a controlled DNA mixture of known organisms and a simulated chimera set, we provide insights into the factors that affect chimera formation such as sequence abundance, the extent of similarity between 16S genes, and PCR conditions. Chimeras were found to reproducibly form among independent amplifications and contributed to false perceptions of sample diversity and the false identification of novel taxa, with less-abundant species exhibiting chimera rates exceeding 70%. Shotgun metagenomic sequences of our mock community appear to be devoid of 16S chimeras, supporting a role for shotgun metagenomics in validating novel organisms discovered in targeted sequence surveys.

Figure 1.

Formation of chimeric sequences during PCR. An aborted extension product from an earlier cycle of PCR can function as a primer in a subsequent PCR cycle. If this aborted extension product anneals to and primes DNA synthesis from an improper template, a chimeric molecule is formed.

Figure 2.

Comparison of chimera detection sensitivity among methods. (A) Chimera detection sensitivity as a function of chimera divergence; (B) chimera detection sensitivity according to the shared level of taxonomy between the proposed parental sequences. Cumulative false-positive rates were as follows: CS, 1.6%; WigeoN, 0.67%; BellerophonGG, 7.13%; KmerGenus, 0%.

Figure 3.

Correlation of chimera content with sequence homology and organism abundance. (A) Percent of other organism abundance corresponding to chimeras with the indicated more abundant species (y-axis), plotted according to percent identity (x-axis) between homologous 16S genes. (B) Number of chimeric sequences corresponding to a given genus were plotted as a function of total genus-level classified reads for the even (eMC) and staggered (sMC) mock community. Total read counts were based on best BLASTN match (E ≤ 10⁻¹⁰) to reference sequences for nonchimeras in addition to the genus representation within the CS-predicted chimeras. (C) Percent of sequences that correspond to chimeras for each genus plotted according to genus-level sequence abundance. Error bars correspond to standard error from the mean based on four technical replicates.

Figure 4.

Alignment of sequences corresponding to chimeras between Streptococcus and Staphylococcus 16S rRNA genes. Only columns from the NAST multiple alignment containing nonidentical nucleotides between the reference sequences (top and bottom) are shown. Nucleotides matching Streptococcus sequences are colored red. Sequence prefixes correspond to the four experimental replicates A–D.