NG-Tax, a highly accurate and validated pipeline for analysis of 16S rRNA amplicons from complex biomes

Javier Ramiro-Garcia; Gerben D A Hermes; Christos Giatsis; Detmer Sipkema; Erwin G Zoetendal; Peter J Schaap; Hauke Smidt

doi:10.12688/f1000research.9227.2

NG-Tax, a highly accurate and validated pipeline for analysis of 16S rRNA amplicons from complex biomes

F1000Res. 2016 Jul 22:5:1791. doi: 10.12688/f1000research.9227.2. eCollection 2016.

Authors

Javier Ramiro-Garcia^#^{1

2

3}, Gerben D A Hermes^#^{1

2}, Christos Giatsis⁴, Detmer Sipkema², Erwin G Zoetendal^{1

2}, Peter J Schaap^{1

3}, Hauke Smidt²

Affiliations

¹ TI Food and Nutrition (TIFN), Wageningen, 6703 HB, The Netherlands.
² Laboratory of Microbiology, Wageningen University, Wageningen, 6708 WE, The Netherlands.
³ Laboratory of Systems and Synthetic Biology, Wageningen University, Wageningen, 6708 WE, The Netherlands.
⁴ Aquaculture and Fisheries Group, Wageningen University, Wageningen, 6708 WD, The Netherlands.

^# Contributed equally.

Abstract

Background: Massive high-throughput sequencing of short, hypervariable segments of the 16S ribosomal RNA (rRNA) gene has transformed the methodological landscape describing microbial diversity within and across complex biomes. However, several studies have shown that the methodology rather than the biological variation is responsible for the observed sample composition and distribution. This compromises meta-analyses, although this fact is often disregarded. Results: To facilitate true meta-analysis of microbiome studies, we developed NG-Tax, a pipeline for 16S rRNA gene amplicon sequence analysis that was validated with different mock communities and benchmarked against QIIME as a frequently used pipeline. The microbial composition of 49 independently amplified mock samples was characterized by sequencing two variable 16S rRNA gene regions, V4 and V5-V6, in three separate sequencing runs on Illumina's HiSeq2000 platform. This allowed for the evaluation of important causes of technical bias in taxonomic classification: 1) run-to-run sequencing variation, 2) PCR-error, and 3) region/primer specific amplification bias. Despite the short read length (~140 nt) and all technical biases, the average specificity of the taxonomic assignment for the phylotypes included in the mock communities was 97.78%. On average 99.95% and 88.43% of the reads could be assigned to at least family or genus level, respectively, while assignment to 'spurious genera' represented on average only 0.21% of the reads per sample. Analysis of α- and β-diversity confirmed conclusions guided by biology rather than the aforementioned methodological aspects, which was not achieved with QIIME. Conclusions: Different biological outcomes are commonly observed due to 16S rRNA region-specific performance. NG-Tax demonstrated high robustness against choice of region and other technical biases associated with 16S rRNA gene amplicon sequencing studies, diminishing their impact and providing accurate qualitative and quantitative representation of the true sample composition. This will improve comparability between studies and facilitate efforts towards standardization.

Keywords: 16S rRNA amplicon analysis; bioinformatic pipeline; microbial community analysis; microbial ecology; next-generation sequencing.

Grants and funding

This work was funded by Top Institute Food and Nutrition (TIFN, Wageningen, The Netherlands), a public - private partnership on precompetitive research in food and nutrition. We are grateful for additional support from the European Community’s Seventh Framework Program (FP7/2007–2013) under grant agreement no. 227197 Promicrobe.