Reproducibility and quantitation of amplicon sequencing-based detection

Abstract

To determine the reproducibility and quantitation of the amplicon sequencing-based detection approach for analyzing microbial community structure, a total of 24 microbial communities from a long-term global change experimental site were examined. Genomic DNA obtained from each community was used to amplify 16S rRNA genes with two or three barcode tags as technical replicates in the presence of a small quantity (0.1% wt/wt) of genomic DNA from Shewanella oneidensis MR-1 as the control. The technical reproducibility of the amplicon sequencing-based detection approach is quite low, with an average operational taxonomic unit (OTU) overlap of 17.2% ± 2.3% between two technical replicates, and 8.2% ± 2.3% among three technical replicates, which is most likely due to problems associated with random sampling processes. Such variations in technical replicates could have substantial effects on estimating b-diversity but less on a-diversity. A high variation was also observed in the control across different samples (for example, 66.7-fold for the forward primer), suggesting that the amplicon sequencing-based detection approach could not be quantitative. In addition, various strategies were examined to improve the comparability of amplicon sequencing data, such as increasing biological replicates, and removing singleton sequences and less-representative OTUs across biological replicates. Finally, as expected, various statistical analyses with preprocessed experimental data revealed clear differences in the composition and structure of microbial communities between warming and non-warming, or between clipping and non-clipping. Taken together, these results suggest that amplicon sequencing-based detection is useful in analyzing microbial community structure even though it is not reproducible and quantitative. However, great caution should be taken in experimental design and data interpretation when the amplicon sequencing-based detection approach is used for quantitative analysis of the b-diversity of microbial communities.

Metagenomic analysis of a stable trichloroethene-degrading microbial community

“…The PhyloChip also detected many other taxa because it is more effective at detecting low abundance organisms (Brodie et al, 2006;DeSantis et al, 2007). This is because the PhyloChip is less sensitive to random sampling effects that impact sequencing-based approaches (Zhou et al, 2008(Zhou et al, , 2011. With the exception of Methanospirillum, the archaeal taxa detected in the metagenome were also detected by the PhyloChip, along with several other archaea.…”

Within-host competition betweenBorrelia afzelii ospCstrains in wild hosts as revealed by massively parallel amplicon sequencing

“…B 370: 20140293 of different genotypes. There is an ongoing debate about the utility of 454 amplicon sequencing (and other next-generation sequencing techniques) for quantification of microbes in other contexts, in particular in metagenomic analyses of environmental bacterial communities [27][28][29][30]. One potential problem stems from PCR amplification; even if primer-binding sites are identical, variable amplicon length or GC content can affect the efficiency of amplification, and slight differences in efficiency can generate large differences in the amount of end product.…”

“…The quality of the sequences was inspected with FastQC [21] and the first 245 bp of ospC that were critical for annotation (see below) had a satisfactory average quality score per base of 30 (range 20 -38). For rrs-rrlA IGS, the average quality score per base for the full length sequences was above 30 (range [25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40]. Demultiplexing of individual samples for the ospC dataset was done with the software GENEIOUS (v. 5.0, Biomatters, Auckland, New Zealand) that handles Roche's MID set.…”

The inconstant gut microbiota of Drosophila species revealed by 16S rRNA gene analysis

“…All the rarefaction curves tended to saturation (Supplementary Figure S3), indicating that the OTUs were representative of the total bacterial community in each sample. Close correspondence in the number and identity of the OTUs between two technical replicate samples (samples of the same genomic DNA) were obtained for both D. melanogaster in set-1 (Pearson's correlation coefficient r ¼ 0.998, Po0.0001) and D. quinaria in set-2 (r ¼ 0.959, Po0.0001) (Supplementary Figure S4), showing that random sampling effects, which have constrained the reproducibility of pyrosequencing data in certain complex bacterial communities (Zhou et al, 2011), were not significant in this study. The combined data for set-1 and set-2 (Supplementary Table S3e) were also processed by Pyrotagger, an alternative program used in our previous research on the gut microbiota of D. melanogaster (Wong et al, 2011).…”