Biology subjects

Stalidzans, E.

Publications and source records attributed to Stalidzans, E..

3 recordsLinked to original sources

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↗

bioRxiv2024

Insulin resistance compromises midbrain organoid neural activity and metabolic efficiency predisposing to Parkinsons disease pathology

Growing evidence indicates that Type 2 Diabetes (T2D) is associated with an increased risk of developing Parkinsons disease through shared disease mechanisms. Studies show that insulin resistance, which is the driving pathophysiological mechanism of T2D plays a major role in neurodegeneration by impairing neuronal functionality, metabolism, and survival. To investigate insulin resistance caused pathological changes in the human midbrain, which could predispose a healthy midbrain to PD development, we exposed iPSC-derived human midbrain organoids from healthy individuals to either high insulin concentrations, promoting insulin resistance, or to more physiological insulin concentrations restoring insulin signalling function. We combined experimental methods with metabolic modelling to identify the most insulin resistance-dependent pathogenic processes. We demonstrate that insulin resistance compromises organoid metabolic efficiency, leading to increased levels of oxidative stress. Additionally, insulin-resistant midbrain organoids showed decreased neural activity and reduced amount of dopaminergic neurons, highlighting insulin resistance as a significant target in PD prevention.

neuroscience↗

bioRxiv2023

OptEnvelope: a target point guided method for growth-coupled production using knockouts

Finding the best knockout strategy for coupling biomass growth and production of a target metabolite using a metabolic model is a challenge in biotechnology. In this research, a three-step method named OptEnvelope is developed based on finding minimal active reactions for a target point in the feasible solution space using a mixed-integer linear programming formula. The method initially finds the reduced desirable solution space (envelope) in the product versus biomass plot by removing all inactive reactions. Then, with reinsertion of the deleted reactions, OptEnvelope attempts to reduce the number of knockouts so that the desirable envelope is preserved. Additionally, OptEnvelope searches for envelopes with higher minimum production rates or fewer knockouts by evaluating different target points within the desired solution space. It is possible to limit the maximal number of knockouts. The method was implemented on metabolic models of E. coli and S. cerevisiae to test the method benchmarking the capability of these industrial microbes for overproduction of acetate and glycerol under aerobic conditions and succinate and ethanol under anaerobic conditions. The results indicate that E. coli is more appropriate to produce acetate and succinate while S. cerevisiae is a better host for glycerol production. Gene deletions for some of the proposed reaction knockouts have been previously reported to increase the production of these metabolites in experiments. Both organisms are suitable for ethanol production, however, more knockouts for the adaptation of E. coli are required. OptEnvelope is available at https://github.com/lv-csbg/optEnvelope.

systems biology↗