Making Sense of Developmental Kinetics Under High-Sugar Stress: Mathematical Modeling of Phenotypic Plasticity in...

Background/Objectives: Although Drosophila melanogaster is widely used in genetics and nutrition research, developmental kinetics are rarely analyzed using formal mathematical modeling. Most dietary studies present developmental curves without rigorous fitting, limiting quantitative interpretation. This study applies and compares three primary models, as well as develops secondary models, to characterize the effects of high-sugar diets on egg-to-adult (life cycle) development. Methods: Standardized husbandry and an embryo-to-pupa feeding assay were performed across 11 sucrose concentrations. Synchronized embryo collection and high-resolution monitoring were used for this assay. Three primary models-dose-response, Gompertz, and logit-based linearization-were fitted to developmental curves to extract timing (t_mid) and synchrony (s_dvp) parameters. Secondary modeling was used to evaluate how these parameters change with respect to sucrose concentration. Results: Increasing sucrose concentration markedly delayed pupariation and reduced viability at the highest levels. All models showed increasing t_mid and decreasing s_dvp with rising sugar concentration, with the Gompertz model providing the best overall performance. Secondary modeling revealed a consistent bilinear response with a breakpoint at 0.52-0.62 M, separating low-, medium-, and high-sucrose conditions. Reduced sampling frequency decreased model robustness, while twice-daily observations remained sufficient. Conclusions: Mathematical modeling provides a robust, practical framework for quantifying the effects of diet on D. melanogaster development. The Gompertz model provided the best fit and yielded biologically interpretable parameters. The bilinear secondary model effectively captured sucrose-dependent stress responses and quantified plasticity through environment-dependent changes in developmental timing and synchrony. Overall, this work establishes a quantitative practical framework for modeling developmental kinetics under nutritional perturbations, and the approach can be extended with additional secondary environmental factors to improve predictive analyses of nutritional effects.