Tibocha-Bonilla Juan D, Zuñiga Cristal, Godoy-Silva Rubén D, Zengler Karsten
1Grupo de Investigación en Procesos Químicos y Bioquímicos, Departamento de Ingeniería Química y Ambiental, Universidad Nacional de Colombia, Av. Carrera 30 No. 45-03, Bogotá, D.C. Colombia.
2Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0760 USA.
Biotechnol Biofuels. 2018 Sep 5;11:241. doi: 10.1186/s13068-018-1244-3. eCollection 2018.
Production of biofuels and bioenergy precursors by phototrophic microorganisms, such as microalgae and cyanobacteria, is a promising alternative to conventional fuels obtained from non-renewable resources. Several species of microalgae have been investigated as potential candidates for the production of biofuels, for the most part due to their exceptional metabolic capability to accumulate large quantities of lipids. Constraint-based modeling, a systems biology approach that accurately predicts the metabolic phenotype of phototrophs, has been deployed to identify suitable culture conditions as well as to explore genetic enhancement strategies for bioproduction. Core metabolic models were employed to gain insight into the central carbon metabolism in photosynthetic microorganisms. More recently, comprehensive genome-scale models, including organelle-specific information at high resolution, have been developed to gain new insight into the metabolism of phototrophic cell factories. Here, we review the current state of the art of constraint-based modeling and computational method development and discuss how advanced models led to increased prediction accuracy and thus improved lipid production in microalgae.
由光养微生物(如微藻和蓝细菌)生产生物燃料和生物能源前体,是从不可再生资源获取传统燃料的一种有前景的替代方案。几种微藻物种已被作为生物燃料生产的潜在候选者进行了研究,主要是因为它们具有积累大量脂质的特殊代谢能力。基于约束的建模是一种系统生物学方法,可准确预测光养生物的代谢表型,已被用于确定合适的培养条件以及探索生物生产的基因增强策略。核心代谢模型被用于深入了解光合微生物的中心碳代谢。最近,已经开发了包括高分辨率细胞器特异性信息的综合基因组规模模型,以深入了解光养细胞工厂的代谢。在此,我们综述了基于约束的建模和计算方法开发的当前技术水平,并讨论了先进模型如何提高预测准确性从而改善微藻脂质生产。