Smetana, S. | Search bioRxiv

bioRxiv2026

Experimental trophic flexibility guides a compartmentalized genome-scale model of red microalgae Galdieria sulphuraria

The thermoacidophilic red microalga Galdieria sulphuraria combines broad organic-carbon utilization with biotechnological robustness. We integrated cultivation data for strain SAG 107.79 with an organelle-resolved genome-scale metabolic model describing autotrophic, mixotrophic and heterotrophic metabolism. Heterotrophic cultures produced 2.29, 2.03 and 2.14 g L-1 biomass on glucose, xylose and their mixture, respectively, while mixed-sugar cultures consumed glucose before xylose. Biomass composition was similar under mixotrophy and heterotrophy, and stationary-phase glucose consumption supported a non-growth-associated maintenance demand of 1.7 mmol ATP gDW-1 h-1. These measurements informed trophic-state-specific biomass objective functions. The final model contains 2,487 reactions, 2,270 compartment-specific metabolites and 1,050 genes. The model reproduced the experimentally scored growth phenotypes, highlighted polyol-associated product capacity under heterotrophy and scored 90% in the archived MEMOTE report. To our knowledge, this is the first experimentally based, organelle-resolved genome-scale metabolic model for G. sulphuraria, providing a quantitative framework linking trophic state and substrate identity with carbon use, flux flexibility and product capacity. A user-friendly supplementary package provides the executable SBML model, modular biomass resources, reproducible scripts, quality reports and underlying experimental data.

systems biology↗

bioRxiv2022

Metabolic modeling of Hermetia illucens larvae resource allocation for high-value fatty acid production

All plant and animal kingdom organisms use highly connected biochemical networks to facilitate sustaining, proliferation and growth functions. While biochemical network details are well known, the understanding of intense regulation principles is still limited. We chose to investigate Hermetia illucens fly at the larval stage as it is crucial for successful resource accumulation and allocation for the consequential organisms developmental stages. We combined the iterative wet lab experiments and innovative metabolic modeling design approaches, to simulate and explain the H. illucens larval stage resource allocation processes and biotechnology potential. We performed time-based growth and high-value chemical compound accumulation wet lab chemical analysis experiments in larvae and Gainesville diet composition. To predict diet-based alterations on fatty acid allocation potential, we built and validated the first H. illucens medium-size stoichiometric metabolic model. Using optimization methods like Flux balance and Flux variability analysis on the novel insect metabolic model, it predicted that doubled essential amino acid consumption increased the growth rate by 32%, but pure glucose consumption had no positive impact on growth. In the case of doubled pure valine consumption, the model predicted a 2% higher growth rate. In this study, we describe a new framework to research the impact of dietary alterations on the metabolism of multi-cellular organisms at different developmental stages for improved, sustainable and directed high-value chemicals. Significance StatementMetabolic modeling serves as a platform for researchers to investigate and study in depth the possible states of the system based on the existing knowledgebase (e.g. metabolic reactions, substrates, products and their stoichiometry). These models can be applied for different industrial applications, to simulate resource allocation potential and growth conditions. Moreover, these models predict the required diet for living organisms and insects to improve survival and growth rates and accumulate higher-value products, like fatty acids.

systems biology↗