Marine bacterial, archaeal and protistan association networks reveal ecological linkages

Abstract

Microbes have central roles in ocean food webs and global biogeochemical processes, yet specific ecological relationships among these taxa are largely unknown. This is in part due to the dilute, microscopic nature of the planktonic microbial community, which prevents direct observation of their interactions. Here, we use a holistic (that is, microbial system-wide) approach to investigate time-dependent variations among taxa from all three domains of life in a marine microbial community. We investigated the community composition of bacteria, archaea and protists through cultivation-independent methods, along with total bacterial and viral abundance, and physico-chemical observations. Samples and observations were collected monthly over 3 years at a well-described ocean time-series site of southern California. To find associations among these organisms, we calculated time-dependent rank correlations (that is, local similarity correlations) among relative abundances of bacteria, archaea, protists, total abundance of bacteria and viruses and physico-chemical parameters. We used a network generated from these statistical correlations to visualize and identify time-dependent associations among ecologically important taxa, for example, the SAR11 cluster, stramenopiles, alveolates, cyanobacteria and ammonia-oxidizing archaea. Negative correlations, perhaps suggesting competition or predation, were also common. The analysis revealed a progression of microbial communities through time, and also a group of unknown eukaryotes that were highly correlated with dinoflagellates, indicating possible symbioses or parasitism. Possible 'keystone' species were evident. The network has statistical features similar to previously described ecological networks, and in network parlance has non-random, small world properties (that is, highly interconnected nodes). This approach provides new insights into the natural history of microbes.

Figure 1

Subnetworks organized around 10 SAR11 OTUs (abbreviated S11, a) and 7 stramenopile OTUs (abbreviated Dia: Diatom, Str: stramenopile, b). Abbreviated names are followed by OTU fragment size for bacteria and eukaryotes. Circles are bacteria, diamonds are eukaryotes, triangles are archaea, squares are biotic environmental variables and hexagons are abiotic environmental variables. Sizes of the bacterial and eukaryotic nodes indicate the average abundance of the OTUs as measured by ARISA and TRFLP, respectively. Solid lines show a positive correlation, dashed lines show a negative correlation, arrows indicate a 1-month shift in the correlation. Abbreviations for other nodes are translated in Table 1.

Figure 2

Alveolate subnetwork and highly connected eukaryotic cluster. The subnetwork is organized around 17 alveolates (abbreviated Alv: alveolate, Cil: ciliate, Din: dinoflagellate) as central nodes (a). Fifteen eukaryotic OTUs are highly correlated with Alv 562, Din 198 and Din 241. When visualized separately, these OTUs form a highly inter-connected cluster (b). This cluster accounts for the eukaryotes with the highest connectedness in the overall network.

Figure 3

Subnetwork built around γ-proteobacteria OTUs as central nodes (abbreviated Alt: alteromonas, CHB: CHABI-7, Gam: γ-proteobacterium, S86: SAR86, S92: SAR92). This subnetwork identifies 12 γ-proteobacterial OTUs. γ-proteobacteria OTUs correlate with eukaryotes and Crenarchaea (Cren), as well as environmental parameters and bacterial production.

Figure 4

Subnetworks built around four cyanobacteria OTUs (abbreviated Pro: Prochlorococcus and Syn: Synechococcus, a) and built around three ciliate OTUs and two OTUs identified as ciliates or choanoflagellates OTU (abbreviated Cil: ciliate, Cfl: choanoflagellate, b). Correlations among physico-chemical variables and archaea, bacteria and eukarya show the potential for this network visualization to provide information about ecological relationships of the targeted OTUs.