The great complexity of plant metabolism, with multiple subcellular compartments, cell types, tissues and organs, greatly complicates its analysis. This problem is compounded by the extensive changes that occur in metabolism over time, both during day/night cycles and throughout the course of an entire life cycle. In this context in silico network flux analysis, including both isotope labelling and stoichiometric modelling approaches, represent an important tool to study plant metabolism, providing a framework for the integration of data from a number of experimental strategies. Together, these methods have provided insight into the subcellular distribution of metabolic flux, the interactions between different cell types, source and sink relationships between organs, and how metabolic flux alters over time both at the cellular and whole plant scale. In this review we discuss how network flux analysis has contributed to our understanding of the spatial and temporal organisation of plant metabolism, looking in detail at key studies that address questions surrounding plant metabolism at different scales, from subcellular to whole plant.

中文翻译：

---

通过网络通量分析洞察植物代谢的时空组织

植物代谢的高度复杂性，包括多个亚细胞区室，细胞类型，组织和器官，极大地使其分析复杂化。在白天/黑夜的整个周期以及整个生命周期的整个过程中，新陈代谢随时间发生的广泛变化都使问题变得更加复杂。在这种情况下，计算机网络通量分析（包括同位素标记和化学计量建模方法）是研究植物代谢的重要工具，为集成来自许多实验策略的数据提供了框架。这些方法共同为深入了解代谢通量的亚细胞分布，不同细胞类型之间的相互作用，器官之间的源库关系，以及在细胞和整个植物范围内代谢通量如何随时间变化。在这篇综述中，我们讨论了网络通量分析如何促进我们对植物代谢的时空组织的理解，详细研究了解决从亚细胞到整个植物的不同规模的植物代谢问题的关键研究。