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Reconstruction of a genome-scale metabolic model for Auxenochlorella protothecoides
Tamburro, Jacob
Tamburro, Jacob
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2025
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Microalgae show strong potential as alternative energy platforms for biofuel production and high-value product synthesis, yet the complexity of photosynthetic metabolism has posed significant modeling and engineering challenges. Recent developments in genome-scale metabolic models (GEMs) have substantially advanced our understanding of microalgal biology by integrating omics data, improving light-harvesting simulations, and automating large portions of the reconstruction process. Building upon these methodological gains, a new GEM iPro4643 was reconstructed for Auxenochlorella protothecoides, capturing the organism’s metabolic versatility under autotrophic, mixotrophic, and heterotrophic conditions. This model highlights both shared pathways with other algal species and features such as rapid heterotrophic growth and energy storage dynamics that are especially relevant to industrial-scale applications. Additionally, an in-depth 13C metabolic flux analysis (MFA) of heterotrophically grown A. protothecoides reveals that actual carbon flux is similar to that predicted by the model while diverging from model predictions optimized strictly for growth, pointing to an underestimation of flux toward starch. These findings underscore the need for objective functions and modeling frameworks that incorporate energy storage and regulatory constraints, particularly under fluctuating environmental conditions. By uniting insights from state-of-the-art GEM methodologies, a refined and experimentally validated metabolic model, and empirical MFA data, this body of work paves the way for more accurate predictive capabilities and targeted metabolic engineering strategies aimed at enhancing lipid productivity and other commercially valuable bioproducts in microalgae.
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