Vasile Nicolò S, Cordara Alessandro, Usai Giulia, Re Angela
Centre for Sustainable Future Technologies, Fondazione Istituto Italiano di Tecnologia, Genova, Italy.
Department of Applied Science and Technology, Politecnico di Torino, Torino, Italy.
Front Microbiol. 2021 Apr 1;12:639482. doi: 10.3389/fmicb.2021.639482. eCollection 2021.
Cyanobacterial cell factories trace a vibrant pathway to climate change neutrality and sustainable development owing to their ability to turn carbon dioxide-rich waste into a broad portfolio of renewable compounds, which are deemed valuable in green chemistry cross-sectorial applications. Cell factory design requires to define the optimal operational and cultivation conditions. The paramount parameter in biomass cultivation in photobioreactors is the light intensity since it impacts cellular physiology and productivity. Our modeling framework provides a basis for the predictive control of light-limited, light-saturated, and light-inhibited growth of the sp. PCC 6803 model organism in a flat-panel photobioreactor. The model here presented couples computational fluid dynamics, light transmission, kinetic modeling, and the reconstruction of single cell trajectories in differently irradiated areas of the photobioreactor to relate key physiological parameters to the multi-faceted processes occurring in the cultivation environment. Furthermore, our analysis highlights the need for properly constraining the model with decisive qualitative and quantitative data related to light calibration and light measurements both at the inlet and outlet of the photobioreactor in order to boost the accuracy and extrapolation capabilities of the model.
蓝藻细胞工厂为实现气候变化中和与可持续发展开辟了一条充满活力的道路,因为它们有能力将富含二氧化碳的废物转化为一系列可再生化合物,这些化合物在绿色化学跨部门应用中具有重要价值。细胞工厂设计需要确定最佳的操作和培养条件。光生物反应器中生物质培养的首要参数是光强,因为它会影响细胞生理和生产力。我们的建模框架为平板光生物反应器中模式生物聚球藻PCC 6803在光限制、光饱和和光抑制条件下的生长预测控制提供了基础。本文提出的模型将计算流体动力学、光传输、动力学建模以及光生物反应器不同光照区域单细胞轨迹的重建相结合,以便将关键生理参数与培养环境中发生的多方面过程联系起来。此外,我们的分析强调了需要用与光生物反应器入口和出口处的光校准和光测量相关的决定性定性和定量数据对模型进行适当约束,以提高模型的准确性和外推能力。