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Exploring the interaction patterns among taxa and environments from marine metagenomic data |
Ze-Gang Wei, Shao-Wu Zhang( ), Fang Jing |
Key Laboratory of Information Fusion Technology of Ministry of Education, College of Automation, Northwestern Polytechnical University, Xi’an 710072, China |
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Abstract The sequencing revolution driven by high-throughput technologies has generated a huge amount of marine microbial sequences which hide the interaction patterns among microbial species and environment factors. Exploring these patterns is helpful for exploiting the marine resources. In this paper, we use the complex network approach to mine and analyze the interaction patterns of marine taxa and environments in spring, summer, fall and winter seasons. With the 16S rRNA pyrosequencing data of 76 time point taken monthly over 6 years, we first use our MtHc clustering algorithm to generate the operational taxonomic units (OTUs). Then, employ the k-means method to divide 76 time point samples into four seasonal groups, and utilize mutual information (MI) to construct the four correlation networks among microbial species and environment factors. Finally, we adopt the symmetrical non-negative matrix factorization method to detect the interaction patterns, and analysis the relationship between marine species and environment factors. The results show that the four seasonal microbial interaction networks have the characters of complex networks, and interaction patterns are related with the seasonal variability; the same environmental factor influences different species in the four seasons; the four environmental factors of day length, photosynthetically active radiation, NO2+NO3 and silicate may have stronger influences on microbes than other environment factors.
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Author Summary
Exploring microbial functions and roles plays a key role in the research of environmental and ecological system biology. High-throughput metagenomic technologies can produce massive sequencing data, which make it possible to analyze the structure of microbial communities and changes across environmental factors. Here we use the complex network approach to mine and analyze the interaction patterns of marine taxa and environments in four seasons at the West English Channel from 16S rRNA data. It is shown that marine microbial interaction patterns changes with the seasons. We also analyze the interactions among different species within a community and their relationship with environment factors. |
Keywords
marine microbe
operational taxonomic unit
interaction pattern
network
clustering
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Corresponding Author(s):
Shao-Wu Zhang
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About author: Tongcan Cui and Yizhe Hou contributed equally to this work. |
Just Accepted Date: 05 April 2016
Online First Date: 11 May 2016
Issue Date: 26 May 2016
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