Engineering carbon assimilation in plants

鲁比斯科 固碳 光合作用 碳同化 同化(音韵学) 蓝藻 碳通量 生化工程 生物 藻类 碳循环 叶绿体 代谢工程 合成生物学 植物 生物化学 计算生物学 细菌 生态学 生态系统 工程类 基因 哲学 遗传学 语言学
作者
Kezhen Qin,Xingyan Ye,Shanshan Luo,Alisdair R. Fernie,Youjun Zhang
出处
期刊:Journal of Integrative Plant Biology [Wiley]
卷期号:67 (4): 926-948 被引量:13
标识
DOI:10.1111/jipb.13825
摘要

Abstract Carbon assimilation is a crucial part of the photosynthetic process, wherein inorganic carbon, typically in the form of CO 2 , is converted into organic compounds by living organisms, including plants, algae, and a subset of bacteria. Although several carbon fixation pathways have been elucidated, the Calvin–Benson–Bassham (CBB) cycle remains fundamental to carbon metabolism, playing a pivotal role in the biosynthesis of starch and sucrose in plants, algae, and cyanobacteria. However, Ribulose‐1,5‐bisphosphate carboxylase/oxygenase (RuBisCO), the key carboxylase enzyme of the CBB cycle, exhibits low kinetic efficiency, low substrate specificity, and high temperature sensitivity, all of which have the potential to limit flux through this pathway. Consequently, RuBisCO needs to be present at very high concentrations, which is one of the factors contributing to its status as the most prevalent protein on Earth. Numerous attempts have been made to optimize the catalytic efficiency of RuBisCO and thereby promote plant growth. Furthermore, the limitations of this process highlight the potential benefits of engineering or discovering more efficient carbon fixation mechanisms, either by improving RuBisCO itself or by introducing alternative pathways. Here, we review advances in artificial carbon assimilation engineering, including the integration of synthetic biology, genetic engineering, metabolic pathway optimization, and artificial intelligence in order to create plants capable of performing more efficient photosynthesis. We additionally provide a perspective of current challenges and potential solutions alongside a personal opinion of the most promising future directions of this emerging field.
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