Comparison of microbial diversity determined with the same variable tag sequence extracted from two different PCR amplicons
- Equal contributors
1 Department of Environmental Health, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou, Guangdong 510515, China
2 Department of Pharmacy, Zhujiang Hospital, Southern Medical University, Guangzhou 510282, Guangdong, China
3 Network Center, Southern Medical University, Guangzhou, Guangdong, China
BMC Microbiology 2013, 13:208 doi:10.1186/1471-2180-13-208Published: 14 September 2013
Deep sequencing of the variable region of 16S rRNA genes has become the predominant tool for studying microbial ecology. As sequencing datasets have accumulated, meta-analysis of sequences obtained with different variable 16S rRNA gene targets and by different sequencing methods has become an intriguing prospect that remains to be evaluated experimentally.
We amplified a group of fecal samples using both V4F-V6R and V6F-V6R primer sets, excised the same V6 fragment from the two sets of Illumina sequencing data, and compared the resulting data in terms of the α-diversity, β-diversity, and community structure. Principal component analysis (PCA) comparing the microbial community structures of different datasets, including those with simulated sequencing errors, was very reliable. Procrustes analysis showed a high degree of concordance between the different datasets for both abundance-weighted and binary Jaccard distances (P < 0.05), and a meta-analysis of individual datasets resulted in similar conclusions. The Shannon’s diversity index was consistent as well, with comparable values obtained for the different datasets and for the meta-analysis of different datasets. In contrast, richness estimators (OTU and Chao) varied significantly, and the meta-analysis of richness estimators was also biased. The community structures of the two datasets were obviously different and led to significant changes in the biomarkers identified by the LEfSe statistical tool.
Our results suggest that beta-diversity analysis and Shannon’s diversity are relatively reliable for meta-analysis, while community structures and biomarkers are less consistent. These results should be useful for future meta-analyses of microbiomes from different data sources.