Whole-cell spatiotemporal model and multimodal data illuminate the multiscale light responses in a photosynthetic...

Photosynthetic microorganisms rely on multiple central carbon metabolism pathways to adapt to fluctuating light and energy availability across diel cycles. Mechanistic insight into the regulatory dynamics of this adaptation requires integrating processes that operate across disparate timescales, from rapid redox-dependent post-translational modifications (PTMs) to slower changes in protein expression and metabolic pathway usage. Here, we develop a whole-cell 4D (3D + time) model of the marine cyanobacterium Prochlorococcus marinus MED4 that explicitly represents the spatial, subcellular organization of key carbon fixation enzymes and genetic information processes coupled to a nonspatial genome-scale metabolic model (GSMM). We combine perturbative, time-resolved multi-omics measurements and cryoelectron tomography (cryo-ET)-derived 3D segmented volumes as constraints for this dynamic 4D framework. The integration of experiments and modeling across defined light regimes enables quantitative validation of system-level responses and forecasting under distinct light disturbances. We test the hypothesis that light-dependent redox PTMs regulate carbon fixation by controlling the structural assembly of a protein megacomplex, the "dark complex," at a conserved regulatory node of the Calvin-Benson cycle (CBC) in cyanobacteria. Our model shows that subcellular spatial organization buffers rapid light-induced changes in thylakoid reaction rates, which are followed by redox-PTM-mediated sequestration or release of CBC enzymes in the dark complex, ultimately impacting carbon fixation dynamics within carboxysomes. Comparison with an equivalently parameterized well-mixed stochastic model demonstrates the importance of spatial heterogeneity in understanding phenotypic robustness. Spatiotemporal sequestration creates a timing hierarchy spanning seconds to hours and noise-buffering behavior that cannot be recovered from well-mixed phenomenological models or purely time-resolved descriptions. Constrained by spatial heterogeneity, local enzyme stoichiometry and diffusion-limited assembly/disassembly determine effective stochastically varying control kinetics. Diffusion-driven fluctuations amplify transcription of highly expressed genes, whereas PTM-dependent regulation of enzyme stoichiometry maintains perturbation-driven phenotypic outcomes. 4D whole-cell modeling with perturbation-based multimodal experiments unlocks the ability to probe adaptive, spatiotemporally resolved mechanisms in photosynthetic machinery and light-dependent central carbon metabolism. The outcome of this work addresses a critical gap in genotype-to-phenotype inference and expands modeling and design capabilities for understudied or genetically intractable autotrophs such as P. marinus MED4.