Microbial community structure and associations during a marine dinoflagellate bloom

Abstract

Interactions between microorganisms and algae during bloom events significantly impacts their physiology, alters ambient chemistry, and shapes ecosystem diversity. The potential role these interactions have in bloom development and decline are also of particular interest given the ecosystem impacts of algal blooms. We hypothesized that microbial community structure and succession is linked to specific bloom stages, and reflects complex interactions among taxa comprising the phycosphere environment. This investigation used pyrosequencing and correlation approaches to assess patterns and associations among bacteria, archaea, and microeukaryotes during a spring bloom of the dinoflagellate Alexandrium catenella. Within the bacterial community, Gammaproteobacteria and Bacteroidetes were predominant during the initial bloom stage, while Alphaproteobacteria, Cyanobacteria, and Actinobacteria were the most abundant taxa present during bloom onset and termination. In the archaea biosphere, methanogenic members were present during the early bloom period while the majority of species identified in the late bloom stage were ammonia-oxidizing archaea and Halobacteriales. Dinoflagellates were the major eukaryotic group present during most stages of the bloom, whereas a mixed assemblage comprising diatoms, green-algae, rotifera, and other microzooplankton were present during bloom termination. Temperature and salinity were key environmental factors associated with changes in bacterial and archaeal community structure, respectively, whereas inorganic nitrogen and inorganic phosphate were associated with eukaryotic variation. The relative contribution of environmental parameters measured during the bloom to variability among samples was 35.3%. Interaction analysis showed that Maxillopoda, Spirotrichea, Dinoflagellata, and Halobacteria were keystone taxa within the positive-correlation network, while Halobacteria, Dictyochophyceae, Mamiellophyceae, and Gammaproteobacteria were the main contributors to the negative-correlation network. The positive and negative relationships were the primary drivers of mutualist and competitive interactions that impacted algal bloom fate, respectively. Functional predictions showed that blooms enhance microbial carbohydrate and energy metabolism, and alter the sulfur cycle. Our results suggest that microbial community structure is strongly linked to bloom progression, although specific drivers of community interactions and responses are not well understood. The importance of considering biotic interactions (e.g., competition, symbiosis, and predation) when investigating the link between microbial ecological behavior and an algal bloom’s trajectory is also highlighted.