Microbial Community Composition and Diversity via 16S rRNA Gene Amplicons: Evaluating the Illumina Platform

Abstract

As new sequencing technologies become cheaper and older ones disappear, laboratories switch vendors and platforms. Validating the new setups is a crucial part of conducting rigorous scientific research. Here we report on the reliability and biases of performing bacterial 16S rRNA gene amplicon paired-end sequencing on the MiSeq Illumina platform. We designed a protocol using 50 barcode pairs to run samples in parallel and coded a pipeline to process the data. Sequencing the same sediment sample in 248 replicates as well as 70 samples from alkaline soda lakes, we evaluated the performance of the method with regards to estimates of alpha and beta diversity. Using different purification and DNA quantification procedures we always found up to 5-fold differences in the yield of sequences between individually barcodes samples. Using either a one-step or a two-step PCR preparation resulted in significantly different estimates in both alpha and beta diversity. Comparing with a previous method based on 454 pyrosequencing, we found that our Illumina protocol performed in a similar manner – with the exception for evenness estimates where correspondence between the methods was low. We further quantified the data loss at every processing step eventually accumulating to 50% of the raw reads. When evaluating different OTU clustering methods, we observed a stark contrast between the results of QIIME with default settings and the more recent UPARSE algorithm when it comes to the number of OTUs generated. Still, overall trends in alpha and beta diversity corresponded highly using both clustering methods. Our procedure performed well considering the precisions of alpha and beta diversity estimates, with insignificant effects of individual barcodes. Comparative analyses suggest that 454 and Illumina sequence data can be combined if the same PCR protocol and bioinformatic workflows are used for describing patterns in richness, beta-diversity and taxonomic composition.

Evaluation of Alternative High-Throughput Sequencing Methodologies for the Monitoring of Marine Picoplanktonic Biodiversity Based on rRNA Gene Amplicons

“…A recent study comparing the Illumina and 454 platforms to study bacterial diversity via 16 S rRNA gene amplicons in sediments and soda lakes also found that both methodologies performed in a similar manner and that the general trends in alphadiversity were conserved with the exception of evenness estimates where correspondence between methods was low (Sinclair et al, 2015). It is known that the OTU clustering method can influence the estimates of diversity (Edgar, 2013;Flynn et al, 2015;Sinclair et al, 2015). We used the UPARSE algorithm, which offers an improved accuracy compared to other methods, resulting in fewer OTUs likely closer to the expected number of species in a community (Edgar et al, 2011).…”

“…No significant differences in Chao1, Shannon, and Simpson indices were found between platforms. A recent study comparing the Illumina and 454 platforms to study bacterial diversity via 16 S rRNA gene amplicons in sediments and soda lakes also found that both methodologies performed in a similar manner and that the general trends in alphadiversity were conserved with the exception of evenness estimates where correspondence between methods was low (Sinclair et al, 2015). It is known that the OTU clustering method can influence the estimates of diversity (Edgar, 2013;Flynn et al, 2015;Sinclair et al, 2015).…”

“…Currently, only a few cross-platform studies are available; these two methodologies have been compared in metagenomic studies (Luo et al, 2012), and other applications such identifying single nucleotide substitutions in whole genome sequences (Ratan et al, 2013). Regarding tag sequencing, comparisons have been performed in lake, soil or human samples (Claesson et al, 2010;Sinclair et al, 2015). The initial results showed that the taxonomic classification of reads from the first Illumina sequencers was worse than 454 due to their shorter length and higher error rates (Claesson et al, 2010).…”

“…The initial results showed that the taxonomic classification of reads from the first Illumina sequencers was worse than 454 due to their shorter length and higher error rates (Claesson et al, 2010). Nonetheless, the improvement in quality and length reads of later Illumina sequencers has shown promising results; Illumina performed in a similar manner than 454 with regards to estimates of alpha-and betadiversity except when estimating evenness in soil and lake samples (Sinclair et al, 2015). Here, a careful comparison of the performance of sequencing 16 and 18 S (for marine planktonic prokaryotes and small Picoeukaryotes, respectively) rRNA gene tags by using 454 and Illumina (pair-ended 2 × 250 bp) has been performed to determine and quantify marine picoplankton biodiversity, and the robustness of the results has been tested.…”

Distinct Anaerobic Bacterial Consumers of Cellobiose-Derived Carbon in Boreal Fens with Different CO 2 /CH 4 Production Ratios

“…After raw amplicon sequencing data were demultiplexed into individual samples, sequence pairs were assembled using an in-house bioinformatic pipeline (94). The pipeline further removed sequences with missing primers and unassigned base pairs.…”