Department of Biotechnology, Bhupat Jyoti Mehta School of Biosciences.
Initiative for Biological Systems Engineering (IBSE).
Bioinformatics. 2020 Aug 1;36(15):4309-4315. doi: 10.1093/bioinformatics/btaa497.
Genome-scale metabolic models are widely constructed and studied for understanding various design principles underlying metabolism, predominantly redundancy. Metabolic networks are highly redundant and it is possible to minimize the metabolic networks into smaller networks that retain the functionality of the original network.
Here, we establish a new method, MinReact that systematically removes reactions from a given network to identify minimal reactome(s). We show that our method identifies smaller minimal reactomes than existing methods and also scales well to larger metabolic networks. Notably, our method exploits known aspects of network structure and redundancy to identify multiple minimal metabolic networks. We illustrate the utility of MinReact by identifying multiple minimal networks for 77 organisms from the BiGG database. We show that these multiple minimal reactomes arise due to the presence of compensatory reactions/pathways. We further employed MinReact for a case study to identify the minimal reactomes of different organisms in both glucose and xylose minimal environments. Identification of minimal reactomes of these different organisms elucidate that they exhibit varying levels of redundancy. A comparison of the minimal reactomes on glucose and xylose illustrates that the differences in the reactions required to sustain growth on either medium. Overall, our algorithm provides a rapid and reliable way to identify minimal subsets of reactions that are essential for survival, in a systematic manner.
Algorithm is available from https://github.com/RamanLab/MinReact.
Supplementary data are available at Bioinformatics online.
基因组规模的代谢模型被广泛构建和研究，以了解代谢的各种设计原则，主要是冗余性。代谢网络具有高度的冗余性，因此可以将代谢网络最小化到保留原始网络功能的更小网络中。
在这里，我们建立了一种新的方法 MinReact，该方法可以系统地从给定的网络中删除反应，以识别最小的反应组。我们表明，我们的方法比现有方法识别更小的最小反应组，并且也可以很好地扩展到更大的代谢网络。值得注意的是，我们的方法利用了网络结构和冗余性的已知方面来识别多个最小代谢网络。我们通过从 BiGG 数据库中识别 77 个生物体的多个最小网络来说明 MinReact 的实用性。我们表明，这些多个最小反应组是由于存在补偿反应/途径而产生的。我们进一步将 MinReact 用于案例研究，以确定不同生物体在葡萄糖和木糖最小环境中的最小反应组。不同生物体的最小反应组的鉴定表明，它们表现出不同程度的冗余。对葡萄糖和木糖上最小反应组的比较表明，在任一培养基上维持生长所需的反应存在差异。总的来说，我们的算法提供了一种快速可靠的方法，以系统地识别对于生存至关重要的最小反应子集。
该算法可从 https://github.com/RamanLab/MinReact 获得。
补充数据可在《生物信息学》在线获得。
