Marashi Sayed-Amir, Kouhestani Hawa, Mahdavi Majid
Department of Biotechnology, College of Science, University of Tehran, Tehran 1417614411, Iran ; School of Computer Science, Institute for Research in Fundamental Sciences (IPM), P.O. Box 19395-5746, Tehran, Iran.
Department of Biology, Faculty of Natural Science, University of Tabriz, Tabriz 5166616471, Iran.
ScientificWorldJournal. 2013 Nov 14;2013:615697. doi: 10.1155/2013/615697. eCollection 2013.
Robustness is the key feature of biological networks that enables living organisms to keep their homeostatic state and to survive against external and internal perturbations. Variations in environmental conditions or nutrients and intracellular changes such as genetic mutations have the potential to change stability and efficiency of an organism. Structural robustness helps biological systems to choose alternative routes of adaptation to varying conditions. In this study, in order to estimate the structural robustness in metabolic networks we presented a novel flux balance-based approach inspired by bond percolation theory. Fourteen in silico metabolic models were studied in this work in order to examine the possible relationship between the lifestyle of organisms and their metabolic robustness. The results of this study confirm that in organisms which are highly adapted to their environment robustness to mutations may decrease compared to other organisms.
鲁棒性是生物网络的关键特征，它使生物体能够维持其稳态并抵御外部和内部干扰而生存。环境条件或营养物质的变化以及细胞内变化（如基因突变）有可能改变生物体的稳定性和效率。结构鲁棒性有助于生物系统选择适应不同条件的替代途径。在本研究中，为了估计代谢网络中的结构鲁棒性，我们提出了一种受键渗流理论启发的基于通量平衡的新方法。为了研究生物体的生活方式与其代谢鲁棒性之间的可能关系，本研究对14个计算机模拟代谢模型进行了研究。这项研究的结果证实，与其他生物体相比，高度适应其环境的生物体对突变的鲁棒性可能会降低。
