Disentangling temporal associations in marine microbial networks

Abstract Microbial interactions are fundamental for Earth’s ecosystem functioning and biogeochemical cycling. Nevertheless, they are challenging to identify and remain barely known. The omics-based censuses are helpful to predict microbial interactions through the inference of static association networks. However, since microbial interactions are highly dynamic, we have developed an approach to generate a temporal network from a single static network. We applied it to understand the monthly microbial associations’ dynamics occurring over ten years in the Blanes Bay Microbial Observatory (Mediterranean Sea). For the decade, we identified persistent, seasonal, and temporary microbial associations. Moreover, we found that the temporal network appears to follow an annual cycle, collapsing and reassembling when transiting between colder and warmer waters. We observed higher repeatability in colder than warmer months. Altogether, our results indicate that marine microbial networks follow recurrent temporal dynamics, which need to be accounted to better understand the dynamics of the ocean microbiome.