Using network analysis to explore co-occurrence patterns in soil microbial communities

Abstract

Exploring large environmental datasets generated by high-throughput DNA sequencing technologies requires new analytical approaches to move beyond the basic inventory descriptions of the composition and diversity of natural microbial communities. In order to investigate potential interactions between microbial taxa, network analysis of significant taxon co-occurrence patterns may help to decipher the structure of complex microbial communities across spatial or temporal gradients. Here, we calculated associations between microbial taxa and applied network analysis approaches to a 16S rRNA gene barcoded pyrosequencing dataset containing >160 000 bacterial and archaeal sequences from 151 soil samples from a broad range of ecosystem types. We described the topology of the resulting network and defined operational taxonomic unit categories based on abundance and occupancy (that is, habitat generalists and habitat specialists). Co-occurrence patterns were readily revealed, including general non-random association, common life history strategies at broad taxonomic levels and unexpected relationships between community members. Overall, we demonstrated the potential of exploring inter-taxa correlations to gain a more integrated understanding of microbial community structure and the ecological rules guiding community assembly.

Figure 1

Network of co-occurring 90% cutoff OTUs based on correlation analysis. A connection stands for a strong (Spearman's ρ>0.6) and significant (P-value <0.01) correlation. The size of each node is proportional to the number of connections (that is, degree). Left panel: OTUs colored by taxonomy. Right panel: OTUs colored by abundance and occupancy (generalists and specialists).

Figure 2

Abundance (y axis) and occupancy (x axis) plot for the 90% cutoff OTUs. Habitat generalists OTUs (in red) defined as appearing in >80 soil samples. Habitat specialists OTUs (in blue) defined as locally abundant (>18 sequences) and appearance in <10 soils.

Figure 3

Network of co-occurring generalists and specialists 90% cutoff OTUs based on correlation analysis. A connection stands for a strong (Spearman's ρ>0.6) and significant (P-value <0.01) correlation. The size of each node is proportional to the number of connections (that is, degree). Labels according to taxonomic affiliation: Ac, Acidobacteria. A.R, Alphaproteobacteria; Rhizobiales. A.Rh, Alphaproteobacteria; Rhodobacterales. A.S, Alphaproteobacteria; Sphingomonadales. Ba.F, Bacteroidetes; Flavobacteria. Ba.S, Bacteroidetes; Sphingobacteria. Ch, Chloroflexi. Cr, Crenarchaeota. Cy, Cyanobacteria; D, Deltaproteobacteria. De, Deinococcus. G, Gemmatimonadetes. Ga, Gammaproteobacteria. V, Verrucomicrobia.

Figure 4

Relative abundance of different microbial taxonomic groups. Top panel: number of sequences in all soil samples. Middle panel: number of significant co-occurrent OTUs (nodes from Figure 2). Low panel: number of cosmopolitan OTUs.