Metabolic network reconstruction is of great biological relevance because it offers a way to investigate the metabolic behavior of organisms. However, reconstruction remains a difficult task at both the biological and computational level. Building on previous work establishing an ASP-based approach to this problem, we present a report from the field resulting in the discovery of new biological knowledge. In fact, for the first time ever, we automatically reconstructed a metabolic network for a macroalgae. We accomplished this by taking advantage of ASP's combined optimization and enumeration capacities. Both computational tasks build on an improved ASP problem representation, incorporating the concept of reversible reactions. Interestingly, optimization greatly benefits from the usage of unsatisfiable cores available in the ASP solver unclasp. Applied to Ectocarpus siliculosus, only the combination of unclasp and clasp allowed us to obtain a metabolic network able to produce all recoverable metabolites among the experimentally measured ones. Moreover, 70% of the identified reactions are supported by an homologous enzyme in Ectocarpus siliculosus, confirming the quality of the reconstructed network from a biological viewpoint.