Single cell carbon and nitrogen incorporation and remineralization profiles are uncoupled from phylogenetic groupings of diatom-associated bacteria

Author:

Mayali XavierORCID,Samo TyORCID,Kimbrel JeffORCID,Stuart Rhona K.ORCID,Morris MeganORCID,Rolison Kristina,Ramon Christina,Kim Young-MoORCID,Munoz-Munoz NathalieORCID,Nicora Carrie,Purvine SamORCID,Lipton MaryORCID,Weber Peter K.ORCID

Abstract

AbstractBacterial remineralization of algal organic matter is thought to fuel algal growth, but this has not been quantified. Consequently, we cannot currently predict whether some bacterial taxa may provide more remineralized nutrients to algae than others, nor whether this is linked their incorporation. We quantified bacterial incorporation of algal-derived complex dissolved organic C (DOC) and N (DON) and net algal incorporation of remineralized C and N at the single cell level using isotope tracing and NanoSIMS for fifteen bacterial co-cultures growing with the diatom Phaeodactylum tricornutum. We found unexpected variability in the net C and N fluxes between algae and bacteria, including non-ubiquitous complex DON utilization and remineralization. We identified three distinct functional categories of metabolic interactions, which we termed macromolecule remineralizers, macromolecule users, and small-molecule users, the latter exhibiting efficient growth under low carbon availability. The functional categories were not linked to phylogeny and could not be elucidated strictly from metabolic capacity as predicted by comparative genomics. Using comparative proteogenomic analyses, we show that a complex DON incorporating strain expressed proteins related to growth and peptide transport, and a non-incorporator prioritized reactive oxygen species scavenging and inorganic nutrient uptake. Our analysis suggests that phylogeny does not predict the extent of algae-bacteria metabolite exchange, and activity-based measurements are indispensable to classify the high diversity of microbes into functional groups. These categorizations are useful for conceptual understanding and mechanistic numerical modeling to ultimately predict the fate of elemental cycles in response to environmental change.

Publisher

Cold Spring Harbor Laboratory

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