biostudies-literatureSoleymani FDeutsche ForschungsgemeinschaftEuropean Research CouncilNovo Nordisk Foundation Center for Basic Metabolic Research1572-1583https://www.ebi.ac.uk/biostudies/studies/S-EPMC12489276biostudies-literatureUnknown248(3)Comparative molecular and physiological analyses of organisms from one taxonomic group grown under similar conditions offer a strategy to identify gene targets for trait improvement. While this strategy can also be performed in silico using genome-scale metabolic models for the compared organisms, we continue to lack solutions for the de novo generation of such models, particularly for eukaryotes. To facilitate model-driven identification of gene targets for growth improvement in green algae, here we present a semiautomated platform for de novo generation of genome-scale algal metabolic models. We deployed this platform to reconstruct an enzyme-constrained, genome-scale metabolic model of Chlorella ohadii, the fastest growing green alga reported to date, and validated the growth predictionThe New phytologistConstraint-based metabolic modeling reveals metabolic properties underpinning the unprecedented growth of Chlorella ohadii.PMC12489276SCHR 617/13‐1NNF23OC0085412NI 1472/16‐1NI 1472/16-1SCHR 617/13-1101076560Correa SMTreves HNikoloski ZArend MSoleymani FRazaghi-Moghadam ZForghanisardaghi NfalseConstraint-based metabolic modeling reveals metabolic properties underpinning the unprecedented growth of Chlorella ohadii.Comparative molecular and physiological analyses of organisms from one taxonomic group grown under similar conditions offer a strategy to identify gene targets for trait improvement. While this strategy can also be performed in silico using genome-scale metabolic models for the compared organisms, we continue to lack solutions for the de novo generation of such models, particularly for eukaryotes. To facilitate model-driven identification of gene targets for growth improvement in green algae, here we present a semiautomated platform for de novo generation of genome-scale algal metabolic models. We deployed this platform to reconstruct an enzyme-constrained, genome-scale metabolic model of Chlorella ohadii, the fastest growing green alga reported to date, and validated the growth prediction2025-01-01T00:00:00Z2025 Nov2026-06-04T01:48:41.488Z2026-05-04T03:13:57.714ZS-EPMC124892764091334210.1111/nph.70528