Computational biology and chemistry · 2026
A hybrid continuous-discrete single-cell model for Chlorella vulgaris integrating photophysiology, internal nutrient quotas and multiple fission.
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Ferreira Antonio Átila Menezes, da Silva Felix John Hebert, de Oliveira Lucia Andrea Sindeaux, da Silva Thiago Queiroz, de Moraes Sousa Francisco Leonardo Alves, Dos Santos José Cleiton Sousa
Аннотация
Population-scale models of microalgal growth represent the culture as average biomass and do not explicitly describe discrete cell-cycle events such as commitment, size variation and daughter-cell number. This limitation is relevant for Chlorella vulgaris, which divides by multiple fission and produces a variable number of autospores according to its physiological state. This study proposed a hybrid continuous-discrete single-cell model integrating photophysiology, internal nitrogen and phosphorus quotas, chlorophyll dynamics, the functional state of photosystem II, reactive oxygen species, viability and discrete cell-commitment rules. The model was calibrated by differential evolution against eight quantitative endpoints compiled from the literature and compared, under the same protocol, with a quota-only model and a parametric empirical model. After calibration, the model reproduced the continuous endpoints with a standardized RMSE of 0.123, the discrete endpoints of the control and, under terbutryn, the reduction of the target autospore number before cell death. In the leave-one-source-out analysis, it showed the lowest error for the morphological endpoints and a classification accuracy of 1.00 for the target autospore number and dark-phase division, against 0.33 for the quota-only model. The convergence, sensitivity and parameter-recovery analyses indicated numerical stability and good identifiability of the parameters associated with commitment and multiple fission. It also reproduced the decline of Fv/Fm and the rise of ROS under PSII inhibition. The model constitutes a reproducible, hypothesis-generating framework whose predictive application requires prospective experimental validation.