Küken Anika, Langary Damoun, Nikoloski Zoran
Bioinformatics, Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany.
Systems Biology and Mathematical Modeling, Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany.
Sci Adv. 2022 Apr;8(13):eabl6962. doi: 10.1126/sciadv.abl6962. Epub 2022 Mar 30.
Understanding the complexity of metabolic networks has implications for manipulation of their functions. The complexity of metabolic networks can be characterized by identifying multireaction dependencies that are challenging to determine due to the sheer number of combinations to consider. Here, we propose the concept of concordant complexes that captures multireaction dependencies and can be efficiently determined from the algebraic structure and operational constraints of metabolic networks. The concordant complexes imply the existence of concordance modules based on which the apparent complexity of 12 metabolic networks of organisms from all kingdoms of life can be reduced by at least 78%. A comparative analysis against an ensemble of randomized metabolic networks shows that the metabolic network of contains fewer concordance modules and is, therefore, more tightly coordinated than expected by chance. Together, our findings demonstrate that metabolic networks are considerably simpler than what can be perceived from their structure alone.
理解代谢网络的复杂性对于操纵其功能具有重要意义。代谢网络的复杂性可以通过识别多反应依赖性来表征,由于需要考虑的组合数量庞大,确定这些依赖性具有挑战性。在此,我们提出了协调复合物的概念,它捕获多反应依赖性,并且可以从代谢网络的代数结构和操作约束中有效地确定。协调复合物意味着存在协调模块,基于这些模块,来自生命所有王国的生物体的12个代谢网络的表观复杂性可以降低至少78%。与一组随机代谢网络的比较分析表明,[具体生物]的代谢网络包含较少的协调模块,因此,其协调性比随机预期的更为紧密。总之,我们的研究结果表明,代谢网络比仅从其结构所感知的要简单得多。