Micelle PCR reduces artifact formation in 16S microbiota profiling Stefan A. Boers1, John P. Hays1 and Ruud Jansen2 1 Erasmus University Medical Centre, Rotterdam, the Netherlands 2 Regional Laboratory for Public Health, Haarlem, the Netherlands The protocol utilized a two-step micPCR protocol, as well as a two-step traditional PCR protocol – used for comparative purposes – for NGS library preparation. Background Material & Methods Microbiota profiling methods are greatly enhancing our insights into the microbial diversity and taxonomy of many different types of environments and ecosystems. There are two major disadvantages associated with current bacterial 16S rRNA sequencing strategies: 1) the formation of chimeric sequences, leading to an overestimation of microbial diversity, and 2) biased amplification of targets due to competition between PCR amplification products, which can lead to unreliable quantification of 16S amplicons. Objective: Development of a novel micelle based amplification strategy to generate robust and accurate 16S microbiota profiles. Micelle PCR (micPCR) is designed as a beadless emulsion PCR whereby template DNA molecules are separated into a large number of physically distinct reaction compartments using water-in-oil emulsions. Universal 357F and 926R primers were used to amplify the 16S rRNA V3-V5 region from a synthetic microbial community (HM-782D supplied by BEI Resources) and three independent samples per clinical/environmental sample type (nose, feces, sludge). The protocol utilized a two-step micPCR protocol, as well as a two-step traditional PCR protocol – used for comparative purposes – for 454 NGS library preparation. Results Figure 1. Comparison of the number of chimeric sequences generated during traditional PCR/NGS and micPCR/NGS. NGS-data were automatically processed using the ‘Full Processing Amplicon’ pipeline (Roche). In order to characterize the number of chimeric sequences more precisely, no additional quality filtering was applied. Potentially chimeric sequences were detected with the UCHIME source code implemented in the mothur software platform, using firstly the sequences as their own reference and sequentially the SILVA alignment version of the gold database (available at: http://www.mothur.org/wiki/Silva_reference_alignement) as reference. Data points represent average values from triplicate experiments (Mock samples) or average values from three independent samples per sample type (nose, feces, sludge) and error bars show standard deviations. Figure 2. Comparison of rarefaction analyses between traditional PCR/NGS and micPCR/NGS using an equimolar synthetic microbial community (left), 3 independent nose swab samples (upper right), 3 independent feces samples (center right) and 3 independent sludge samples (lower right). The number of observed OTUs is shown as the function of the number of sequences obtained. Data points for the synthetic microbial community represent average values from triplicate experiments and error bars show standard deviations. Rarefaction curves were generated using mothur with an OTU defined at 97% similarity. Analysis was performed on a random 500 or 1,000-sequence subset from each sample. Discussion & Conclusion The compartmentalization per molecule by micPCR reduces the probability of chimera formation (Figure 1) and restrains PCR competition (Figure 3). As a result, the rarefaction analysis rapidly reached horizontal equilibrium of the expected 20 OTUs, indicating a highly reliable calculation of richness (Figure 2). Results for three independent samples per sample type (nose, feces, sludge) revealed that chimeric sequences were reduced in all samples, resulting in decreased richness values among all samples. The use of micPCR/NGS greatly reduces chimera formation compared to traditional PCR/NGS and is more accurate when estimating the diversity of microbiota profiles. The adoption of micPCR/NGS removes the reliance on traditional complex downstream computational methods for removing chimeric amplicons. MicPCR/NGS prevents amplicon competition in PCR reactions, resulting in the generation of highly accurate quantitative microbiota profiles. Figure 3. Quantitative accuracy of micPCR/NGS compared to traditional PCR/NGS of the synthethic microbial community 16S rRNA profiling. The observed species-level frequency data, corrected for the expected species-level frequency ratio for each of the synthetic community members, is shown as a heatmap using a binary logarithm scale. The expected frequency ratio is based on the reported equimolar 16S rRNA operon counts derived from 20 bacterial species. Blue shades indicate an overestimation of species frequency and red colors an underestimation of species frequency. Data of the triplicate experiments are presented separately. Staphylococcus aureus and Staphylococcus epidermidis present in the synthetic community could not be differentiated at a 97% similarity level, resulting in a maximum of 19 expected OTUs. This work was financially supported by the European Union via funding of the EU FP7 project ‘TAILORED-Treatment’ (www.tailored-treatment.eu). Contact: r.jansen@streeklabhaarlem.nl