Dynamic photo-mechanistic modelling of biomass growth and optical density for the cyanobacterium Synechococcus sp. PCC 11901

Fast-growing cyanobacterial species are potential chassis for converting inorganic carbon into biomass and biomolecules for industrial, medical, and herbicidal applications. However, unavailable mechanistic interpretations for the differing bioconversion rates among isolated strains with similar metabolic pathways and transport systems hinders the biotechnological exploitation. Therefore, this study investigates two strains: Synechococcus sp. PCC 11901, the fastest growing cyanobacterium ever isolated, and Synechocystis sp. PCC 6803, the benchmark cyanobacterial strain, under a wide range of operational light intensities from 300 – 900 μmol photons m^-2 s^-1. This study reports three original contributions. Firstly, strain specific photo-mechanistic influences were embedded into dynamic biomass and optical density (OD750nm) models, too sophisticated to be previously achieved in OD750nm. Secondly, bootstrapping parameter estimation methodology with 3-fold cross validations was utilised to simultaneously identify optimal model parameters and associated confidence intervals. This enabled probabilistic simulations and the thorough validation against unseen experimental datasets. For both species, the simulated errors averaged to less than 19 %, thus demonstrating the model reliability for predicting such highly nonlinear bioprocess dynamics. Thirdly, recounted mechanistic interpretations for the over two-folds faster growth of Synechococcus sp. PCC 11901 compared to Synechocystis sp. PCC 6803 despite the latter's high light utilisation efficiency. Hence, these models and findings will benefit strain specific photobioreactor design and upscaling of the future cyanobacterial biotechnology applications to produce biomass and biochemicals of industrial importance.