Application of Meta-Mesh on the analysis of microbial communities from human associated-habitats

Abstract

With the current fast accumulation of microbial community samples and related metagenomic sequencing data, data integration and analysis system is urgently needed for in-depth analysis of large number of metagenomic samples (also referred to as “microbial communities”) of interest. Although several existing databases have collected a large number of metagenomic samples, they mostly serve as data repositories with crude annotations, and offer limited functionality for analysis. Moreover, the few available tools for comparative analysis in the literature could only support the comparison of a few pre-defined set of metagenomic samples. To facilitate comprehensive comparative analysis on large amount of diverse microbial community samples, we have designed a Meta-Mesh system for a variety of analyses including quantitative analysis of similarities among microbial communities and computation of the correlation between the meta-information of these samples. We have used Meta-Mesh for systematically and efficiently analyses on diverse sets of human associate-habitat microbial community samples. Results have shown that Meta-Mesh could serve well as an efficient data analysis platform for discovery of clusters, biomarker and other valuable biological information from a large pool of human microbial samples.

Graphical abstract

Keywords

metagenome / microbial community / data mining

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ACKNOWLEDGMENTS

This work is supported in part by Chinese Academy of Sciences’ e-Science grant (NO. INFO-115-D01-Z006), Ministry of Science and Technology’s high-tech (863) grant (NO. 2009AA02Z310 and NO. 2014AA21502), National Science Foundation of China grant (NO. 61103167, NO. 31271410 and NO. 61303161), and The Open Fund of Key Laboratory of Marine Ecology and Environmental Science,Institute of Oceanology, Chinese Academy of Sciences (NO. KLMEES201304).

The authors Xiaoquan Su, Xiaojun Wang, Gongchao Jing, Shi Huang, Jian Xu and Kang Ning declare that they have no conflict of interest.ƒ

This article does not contain any studies with human or animal subjects performed by any of the authors.

RIGHTS & PERMISSIONS

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg