Comparison of microbial diversity determined with the same variable tag sequence extracted from two different PCR amplicons

BMC Microbiology

Research Article

Xiao-Tao Jiang¹  Yan He¹  Guan-Hua Deng¹  Hong-Wei Zhou¹  Ben-Jie Zhou²  Hai Zhang³ 

[1] Department of Environmental Health, School of Public Health and Tropical Medicine, Southern Medical University, 510515, Guangzhou, Guangdong, China;Department of Pharmacy, Zhujiang Hospital, Southern Medical University, 510282, Guangzhou, Guangdong, China;Network Center, Southern Medical University, Guangzhou, Guangdong, China;

关键词: Microbial diversity;    V46 hypervariable region;    V6 hypervariable region;    Illumina;    16S rRNA gene;    Meta-analysis;   

DOI  :  10.1186/1471-2180-13-208

 received in 2013-01-06, accepted in 2013-09-12,  发布年份 2013

来源: Springer

【 摘 要 】

BackgroundDeep 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.ResultsWe 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.ConclusionsOur 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.

【 授权许可】

Unknown   
© He et al.; licensee BioMed Central Ltd. 2013. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.