Integrative metabolic modeling for rational biodesign of Spirulina toward sustainable future foods

Spirulina has long been utilized in food, feed, and pharmaceutical applications, yet its biomass production remains suboptimal. This study employed a genome-scale metabolic model (GEM) integrated with transcriptomic data to investigate carbon and nitrogen utilization and to identify strategies for enhancing biomass productivity and nutrient use efficiency in Arthrospira (Spirulina) platensis C1. The refined GEM (iAK888), comprising 888 genes, 1,438 reactions, and 1,096 metabolites, was expanded to include additional genes, pathways, and cellular compartments. Using the COBRA Toolbox and GIMME algorithm in MATLAB, the model was integrated with gene expression data obtained under temperature stress and nitrogen (N) starvation. Spirulina was cultivated in Zarrouk’s medium within a tubular photobioreactor at 35 °C and 200 μmol photons m–² s–¹ under continuous chemostat conditions across various growth rates. Stepwise correlation between biomass production rates and flux distributions in the transcriptome-constrained model identified reactions highly associated with biomass biosynthesis. Positively correlated reactions were primarily linked to the biosynthesis of cellular macromolecules, vitamins, cofactors, and nitrogen and mineral transport. Two strongly negative correlations—(i) conversion of aspartate and α-ketoglutarate to glutamate and oxaloacetate, and (ii) deamination of alanine to ammonium and pyruvate—suggested glutamate and ammonium as promising rational feed supplements. Subsequent cultivation experiments using 5 mM ammonium demonstrated enhanced growth rates of Spirulina—1.33- and 1.24-fold increases when ammonium was supplied as an additional or sole nitrogen source (0.0378 and 0.0352 h–¹, respectively) compared to nitrate-grown controls (0.0284 h–¹). Moreover, cultures grown with ammonium as the sole nitrogen source achieved 76–93% higher nitrogen uptake efficiency and 52–120% greater nitrogen use efficiency. This study demonstrates that rational process design based on nutrient-specific metabolic responses can substantially improve Spirulina biomass production, advancing efficient and sustainable microalgal cultivation systems.