In this study, 24 soil samples used for network analysis of microbial communities were collected from the Biocon (biodiversity, CO2, and N) experimental site located at the Cedar Creek Ecosystem Science Reserve in Minnesota (45°N, 93°W). Of these 24 samples, 12 were from aCO2 replicate plots and 12 were from eCO2 replicate plots. All of the plots contained 16 species without additional N supply. The soil samples were collected in July 2007, and each sample was a composite of five soil cores from depths of 0 to 15 cm (10 (link)).
Two MENs were constructed with the following steps. First, the experimental data used for constructing pMENs were generated by pyrosequencing of 16S rRNA genes (10 (link)). Since the sequence numbers of individual OTUs obtained varied significantly among different samples, the relative proportions of sequence numbers were used for subsequent Pearson correlation analysis. Second, a similarity matrix was obtained by taking the absolute values of the correlation matrix. This similarity matrix measures the degree of concordance between the abundance profiles of individual OTUs across different samples. Third, an appropriate threshold for defining network structure, st, is defined using the RMT-based network approach (38 , 49 ) to obtain an adjacency matrix, which encodes the strength of the connection between each pair of nodes. Fourth, the submodules within a large module were detected by fast greedy modularity optimization (32 (link)). In addition, for network comparison, random networks corresponding to all pMENs were generated using the Maslov-Sneppen procedure (50 (link)) and keeping the numbers of nodes and links constant but rewiring all of the links’ positions in the pMENs. A standard Z or t test was employed to determine the significance of network indexes between the pMENs and random networks and across different experimental conditions. Finally, sample trait-based significance (24 (link)) was defined and a Mantel test was used to examine the relationships between the trait-based gene significance and soil variables for understanding the importance of network interactions in ecosystem functioning. More detailed information about the Materials and Methods used in this study is provided in the supplemental material.
Two MENs were constructed with the following steps. First, the experimental data used for constructing pMENs were generated by pyrosequencing of 16S rRNA genes (10 (link)). Since the sequence numbers of individual OTUs obtained varied significantly among different samples, the relative proportions of sequence numbers were used for subsequent Pearson correlation analysis. Second, a similarity matrix was obtained by taking the absolute values of the correlation matrix. This similarity matrix measures the degree of concordance between the abundance profiles of individual OTUs across different samples. Third, an appropriate threshold for defining network structure, st, is defined using the RMT-based network approach (38 , 49 ) to obtain an adjacency matrix, which encodes the strength of the connection between each pair of nodes. Fourth, the submodules within a large module were detected by fast greedy modularity optimization (32 (link)). In addition, for network comparison, random networks corresponding to all pMENs were generated using the Maslov-Sneppen procedure (50 (link)) and keeping the numbers of nodes and links constant but rewiring all of the links’ positions in the pMENs. A standard Z or t test was employed to determine the significance of network indexes between the pMENs and random networks and across different experimental conditions. Finally, sample trait-based significance (24 (link)) was defined and a Mantel test was used to examine the relationships between the trait-based gene significance and soil variables for understanding the importance of network interactions in ecosystem functioning. More detailed information about the Materials and Methods used in this study is provided in the supplemental material.
