Spatially structured competition and cooperation alters algal carbon flow to bacteria

Microbial communities regulate the transformations of carbon in aquatic systems through metabolic interactions and food-web dynamics that can alter the balance of photosynthesis and respiration. Direct competition for resources is thought to drive microbial community assembly in algal systems, but other interaction modes that may shape communities are more challenging to isolate. Through untargeted metabolomics and metabolic modeling, we predicted the degree of resource competition between bacterial pairs when growing on model diatom Phaeodactylum tricornutum- derived substrates. In a subsequent sequential media experiment, we found that pairwise interactions were consistently more cooperative than predicted based on resource competition alone, indicating an unexpected role for cooperation in algal carbon processing. To link this directly to algal carbon fate, we chose a representative cooperative and competitive ‘influencer’ isolate and a model ‘recipient’ and applied single-cell isotope tracing in a custom porous microplate cultivation system. In the presence of live algae, the recipient drew down more algal carbon in the presence of the cooperative influencer compared to the competitive influencer, supporting the sequential experiment results. We also found that total carbon assimilation into bacterial biomass, integrated over influencer and recipient, was significantly higher for the cooperative interaction. Our findings support the notion that non-competitive interactions are critical for predicting algal carbon fate. Significance Statement Microbial interactions have widely been studied in the context of host resources but testing and measuring direct interactions in a lab has been particularly challenging. By combining untargeted metabolomics, sequential/(co-)culture, and metabolic modeling, we demonstrate that the presence of an unexpected interaction mode in a live system and show how it impacts the flow of host-derived resources. This top-down approach can help identify novel bacterial interactions that play a crucial role in microbial community-host ecosystems, which may have an impact in holobiont phenotypes including alga, fungal, or plant systems.