Li Xuhang, Yilmaz L Safak, Walhout Albertha J M
Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA.
Curr Opin Syst Biol. 2022 Mar;29. doi: 10.1016/j.coisb.2021.100407. Epub 2021 Nov 14.
In multicellular organisms, metabolism is compartmentalized at many levels, including tissues and organs, different cell types, and subcellular compartments. Compartmentalization creates a coordinated homeostatic system where each compartment contributes to the production of energy and biomolecules the organism needs to carrying out specific metabolic tasks. Experimentally studying metabolic compartmentalization and metabolic interactions between cells and tissues in multicellular organisms is challenging at a systems level. However, recent progress in computational modeling provides an alternative approach to this problem. Here we discuss how integrating metabolic network modeling with omics data offers an opportunity to reveal metabolic states at the level of organs, tissues and, ultimately, individual cells. We review the current status of genome-scale metabolic network models in multicellular organisms, methods to study metabolic compartmentalization , and insights gained from computational analyses. We also discuss outstanding challenges and provide perspectives for the future directions of the field.
在多细胞生物中，新陈代谢在许多层面上是分区进行的，包括组织和器官、不同的细胞类型以及亚细胞区室。分区形成了一个协调的稳态系统，其中每个区室都有助于产生生物体执行特定代谢任务所需的能量和生物分子。在系统层面上，通过实验研究多细胞生物中细胞和组织之间的代谢分区以及代谢相互作用具有挑战性。然而，计算建模方面的最新进展为解决这个问题提供了一种替代方法。在这里，我们讨论将代谢网络建模与组学数据相结合如何为揭示器官、组织乃至单个细胞水平的代谢状态提供了机会。我们回顾了多细胞生物中基因组规模代谢网络模型的现状、研究代谢分区的方法以及从计算分析中获得的见解。我们还讨论了突出的挑战，并为该领域的未来方向提供了展望。
