Ewald Jan, Bartl Martin, Kaleta Christoph
Research Group Theoretical Systems Biology, Department of Bioinformatics, Friedrich-Schiller-Universität Jena, Jena, Germany
Research Group Theoretical Systems Biology, Department of Bioinformatics, Friedrich-Schiller-Universität Jena, Jena, Germany.
Biochem Soc Trans. 2017 Aug;45(4):1035-1043. doi: 10.1042/BST20170137. Epub 2017 Jul 28.
Understanding optimality principles shaping the evolution of regulatory networks controlling metabolism is crucial for deriving a holistic picture of how metabolism is integrated into key cellular processes such as growth, adaptation and pathogenicity. While in the past the focus of research in pathway regulation was mainly based on stationary states, more recently dynamic optimization has proved to be an ideal tool to decipher regulatory strategies for metabolic pathways in response to environmental cues. In this short review, we summarize recent advances in the elucidation of optimal regulatory strategies and identification of optimal control points in metabolic pathways. We discuss biological implications of the discovered optimality principles on genome organization and provide examples how the derived knowledge can be used to identify new treatment strategies against pathogens. Furthermore, we briefly discuss the variety of approaches for solving dynamic optimization problems and emphasize whole-cell resource allocation models as an important emerging area of research that will allow us to study the regulation of metabolism on the whole-cell level.
理解塑造控制新陈代谢的调控网络进化的最优性原理，对于全面了解新陈代谢如何融入生长、适应和致病性等关键细胞过程至关重要。过去，通路调控的研究重点主要基于稳态，而最近动态优化已被证明是解读代谢通路响应环境线索的调控策略的理想工具。在这篇简短的综述中，我们总结了在阐明最优调控策略和识别代谢通路中的最优控制点方面的最新进展。我们讨论了所发现的最优性原理对基因组组织的生物学意义，并举例说明如何利用所获得的知识来识别对抗病原体的新治疗策略。此外，我们简要讨论了解决动态优化问题的各种方法，并强调全细胞资源分配模型是一个重要的新兴研究领域，它将使我们能够在全细胞水平上研究新陈代谢的调控。
