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

BMC Microbiology

Hong-Wei Zhou³  Hai Zhang²  Xiao-Tao Jiang³  Guan-Hua Deng³  Ben-Jie Zhou¹  Yan He³ 

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

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

Others  :  1143054
DOI  :  10.1186/1471-2180-13-208

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

【 摘 要 】

Background

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.

Results

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.

Conclusions

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.

【 授权许可】

   
2013 He et al.; licensee BioMed Central Ltd.

【 图 表 】

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