Sousa Filipa L, Hordijk Wim, Steel Mike, Martin William F
Institute of Molecular Evolution, Heinrich Heine Universität, Düsseldorf, Germany.
SmartAnalytiX.com, Lausanne, Switzerland.
J Syst Chem. 2015;6(1):4. doi: 10.1186/s13322-015-0009-7. Epub 2015 Apr 1.
A central unsolved problem in early evolution concerns self-organization towards higher complexity in chemical reaction networks. In theory, autocatalytic sets have useful properties to help model such transitions. Autocatalytic sets are chemical reaction systems in which molecules belonging to the set catalyze the synthesis of other members of the set. Given an external supply of starting molecules - the food set - and the conditions that (i) all reactions are catalyzed by at least one molecule, and (ii) each molecule can be constructed from the food set by a sequence of reactions, the system becomes a reflexively autocatalytic food-generated network (RAF set). Autocatalytic networks and RAFs have been studied extensively as mathematical models for understanding the properties and parameters that influence self-organizational tendencies. However, despite their appeal, the relevance of RAFs for real biochemical networks that exist in nature has, so far, remained virtually unexplored.
Here we investigate the best-studied metabolic network, that of , for the existence of RAFs. We find that the largest RAF encompasses almost the entire cytosolic reaction network. We systematically study its structure by considering the impact of removing catalysts or reactions. We show that, without biological knowledge, finding the minimum food set that maintains a given RAF is NP-complete. We apply a randomized algorithm to find (approximately) smallest subsets of the food set that suffice to sustain the original RAF.
The existence of RAF sets within a microbial metabolic network indicates that RAFs capture properties germane to biological organization at the level of single cells. Moreover, the interdependency between the different metabolic modules, especially concerning cofactor biosynthesis, points to the important role of spontaneous (non-enzymatic) reactions in the context of early evolution. Graphical Abstract metabolic network in the context of autocatalytic sets.
早期进化中一个核心未解决的问题涉及化学反应网络向更高复杂性的自组织。理论上，自催化集具有有助于模拟此类转变的有用特性。自催化集是化学反应系统，其中属于该集合的分子催化该集合中其他成员的合成。给定起始分子的外部供应——食物集——以及以下条件：（i）所有反应都由至少一种分子催化，（ii）每个分子都可以通过一系列反应从食物集构建而成，该系统就成为一个自反自催化食物生成网络（RAF集）。自催化网络和RAF集作为数学模型已被广泛研究，用于理解影响自组织趋势的特性和参数。然而，尽管它们具有吸引力，但迄今为止，RAF集与自然界中存在的真实生化网络的相关性几乎尚未得到探索。
在这里，我们研究了研究最深入的代谢网络—— 的代谢网络——中RAF集的存在情况。我们发现最大的RAF集几乎涵盖了整个 胞质反应网络。我们通过考虑去除催化剂或反应的影响来系统地研究其结构。我们表明，在没有生物学知识的情况下，找到维持给定RAF集的最小食物集是NP完全问题。我们应用一种随机算法来找到（近似）足以维持原始RAF集的食物集的最小子集。
微生物代谢网络中RAF集的存在表明，RAF集捕捉了单细胞水平上与生物组织相关的特性。此外，不同代谢模块之间的相互依赖性，特别是关于辅因子生物合成的相互依赖性，表明自发（非酶促）反应在早期进化背景下的重要作用。图形摘要：自催化集背景下的代谢网络。
