The methane-driven interaction network in terrestrial methane hotspots

Abstract

Background: Biological interaction affects diverse facets of microbial life by modulating the activity, diversity, abundance, and composition of microbial communities. Aerobic methane oxidation is a community function, with emergent community traits arising from the interaction of the methane-oxidizers (methanotrophs) and non-methanotrophs. Yet little is known of the spatial and temporal organization of these interaction networks in naturally-occurring complex communities. We hypothesized that the assembled bacterial community of the interaction network in methane hotspots would converge, driven by high substrate availability that favors specific methanotrophs, and in turn influences the recruitment of non-methanotrophs. These environments would also share more co-occurring than site-specific taxa. Results: We applied stable isotope probing (SIP) using 13C-CH4 coupled to a co-occurrence network analysis to probe trophic interactions in widespread methane-emitting environments, and over time. Network analysis revealed predominantly unique co-occurring taxa from different environments, indicating distinctly co-evolved communities more strongly influenced by other parameters than high methane availability. Also, results showed a narrower network topology range over time than between environments. Co-occurrence pattern points to Chthoniobacter as a relevant yet-unrecognized interacting partner particularly of the gammaproteobacterial methanotrophs, deserving future attention. In almost all instances, the networks derived from the 13C-CH4 incubation exhibited a less connected and complex topology than the networks derived from the unlabelledC-CH4 incubations, likely attributable to the exclusion of the inactive microbial population and spurious connections; DNA-based networks (without SIP) may thus overestimate the methane-dependent network complexity. Conclusion: We demonstrated that site-specific environmental parameters more strongly shaped the co-occurrence of bacterial taxa than substrate availability. Given that members of the interactome without the capacity to oxidize methane can exert interaction-induced effects on community function, understanding the co-occurrence pattern of the methane-driven interaction network is key to elucidating community function, which goes beyond relating activity to community composition, abundances, and diversity. More generally, we provide a methodological strategy that substantiates the ecological linkages between potentially interacting microorganisms with broad applications to elucidate the role of microbial interaction in community function. © 2022, The Author(s).