Prymnesium parvum is a toxin-producing haptophyte microalga known to cause harmful algal blooms (HABs) with severe ecological impact. However, the molecular and ecological mechanisms underlying its toxicity remain unclear. An emerging hypothesis suggests that environmental stressors, such as nutrient limitation, can alter toxin production not only directly, but also indirectly, by reshaping the surrounding microbiome. This, in turn, may modulate biotic interactions with the host, thereby influencing its physiology and capacity for toxin release.

In this study, we aim to explore the role of the microbiome in supporting P. parvum growth by uncovering cross-feeding interactions under different nutrient conditions. These interactions, involving metabolite exchanges between organisms, were shown to play a critical role in shaping microbial community structure and function. One way of exploring cross-feeding interactions is through the use of the constraint-based metabolic modeling framework. This approach relies on the reconstruction of genome-scale metabolic models (GEMs), which represent the network of biochemical reactions an organism can carry out, including the metabolites it produces, consumes, and exchanges with its environment. GEMs enable predictions of metabolite secretion profiles and potential cross-feeding exchanges between interacting species, helping to identify prototroph–auxotroph relationships under variable nutrient conditions.

Notably, P. parvum has been identified as an auxotroph for B12 vitamin (cobalamin), a complex yet essential cofactor for multiple vital processes. A recent co-culture experiment involving P. parvum and a synthetic community of 15 bacterial species comprising B12 producers showed sustained algal growth in the absence of exogenous B12, indicating potential cross-feeding of B12 or its precursors.

By leveraging the metabolic modeling framework, we aim to predict B12 biosynthesis and release capacity within this synthetic community, and potential cross-feeding interactions with P. parvum under varying nutrient conditions. Moreover, our approach aims to facilitate the design of minimal synthetic consortia optimized for algal support under nutrient stress conditions. We discuss how this modeling framework can guide community member selection, generate testable hypotheses concerning microbial interactions and growth outcomes, and ultimately improve our understanding of microalgal-microbiome interactions in ecologically relevant contexts.