Modelling metabolic CO₂ evolution--a fresh perspective on respiration.

Modelling metabolic CO₂ evolution--a fresh perspective on respiration.
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模拟代谢二氧化碳演化——呼吸作用的新视角。

DOI:
10.1111/pce.12105
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发表时间:
2013
期刊:
Plant, cell & environment
影响因子:
--
通讯作者:
R. Ratcliffe
R. Ratcliffe
中科院分区:
--
文献类型:
--
作者:
L. Sweetlove;T. Williams;C. Y. M. Cheung;R. Ratcliffe

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呼吸作用是植物与大气之间CO-₂净交换的主要贡献者,因此是全球气候变化模型中植被部分的一个重要方面。然而,呼吸作用的机制模型是缺乏的,因此我们在这里探索利用通量平衡分析来预测细胞CO₂释放速率的可能性。代谢通量分析表明,呼吸作用并不总是CO₂的主要来源,代谢过程,如氧化戊糖磷酸途径和脂质合成可能在数量上是重要的。此外,进化的CO₂的代谢来源在组织、物种和条件之间有相当大的差异。通过与通量测量结果比较,可以预测CO₂在不同组织/物种和不同条件下的代谢起源。然而,FBA在预测某些代谢过程中的流量方面做得很差,例如OPPP,我们确定了维护成本的计算方法,作为未来FBA研究的主要改进领域。我们得出结论,以其标准形式,FBA可以用于预测一系列植物组织中CO₂的演变以及对环境的响应。
Respiration is a major contributor to net exchange of CO₂ between plants and the atmosphere and thus an important aspect of the vegetation component of global climate change models. However, a mechanistic model of respiration is lacking, and so here we explore the potential for flux balance analysis (FBA) to predict cellular CO₂ evolution rates. Metabolic flux analysis reveals that respiration is not always the dominant source of CO₂, and that metabolic processes such as the oxidative pentose phosphate pathway (OPPP) and lipid synthesis can be quantitatively important. Moreover, there is considerable variation in the metabolic origin of evolved CO₂ between tissues, species and conditions. Comparison of FBA-predicted CO₂ evolution profiles with those determined from flux measurements reveals that FBA is able to predict the metabolic origin of evolved CO₂ in different tissues/species and under different conditions. However, FBA is poor at predicting flux through certain metabolic processes such as the OPPP and we identify the way in which maintenance costs are accounted for as a major area of improvement for future FBA studies. We conclude that FBA, in its standard form, can be used to predict CO₂ evolution in a range of plant tissues and in response to environment.
DOI: 10.1016/j.phytochem.2007.03.042
发表时间: 2007-08-01
期刊: PHYTOCHEMISTRY
影响因子: 3.8
作者:
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