Chance and necessity in the evolution of minimal metabolic networks
Chance and necessity in the evolution of minimal metabolic networks
复制标题
DOI：
10.1038/nature04568
复制
发表时间：
2006-03-30
期刊：
影响因子：
64.8
通讯作者：
Hurst, LD
中科院分区：
文献类型：
--
作者：
Pál, C;Papp, B;Hurst, LD
可以从基因含量推断生物体生活方式的各个方面（1）。反过来也可以吗？在这里，我们考虑这个问题，通过模拟内共生细菌的基因组减少的进化。这些细菌中基因含量的多样性可能反映了选择力的变化和替代途径的偶然依赖性损失。利用大肠杆菌代谢网络的计算机表示，我们通过反复模拟基因的连续丢失，同时控制环境来研究偶然性的作用。最小网络的结果是可变的基因内容和数量。部分不同的代谢因此可以演变，由于偶然性。然而，模拟结果确实保留了核心代谢，这在严格的细胞内细菌中过度代表。此外，基于生活方式的最小网络之间的差异是可预测的：通过模拟各自的环境条件，我们可以模拟Buchnera aphidicola和Wigglesophoria glossinidia中基因内容的进化，准确率超过80%。我们的结论是，至少在这里考虑的特定情况下，生物体的基因含量可以预测其遥远的祖先和目前的生活方式的知识。
It is possible to infer aspects of an organism's lifestyle from its gene content(1). Can the reverse also be done? Here we consider this issue by modelling evolution of the reduced genomes of endosymbiotic bacteria. The diversity of gene content in these bacteria may reflect both variation in selective forces and contingency-dependent loss of alternative pathways. Using an in silico representation of the metabolic network of Escherichia coli, we examine the role of contingency by repeatedly simulating the successive loss of genes while controlling for the environment. The minimal networks that result are variable in both gene content and number. Partially different metabolisms can thus evolve owing to contingency alone. The simulation outcomes do preserve a core metabolism, however, which is over-represented in strict intracellular bacteria. Moreover, differences between minimal networks based on lifestyle are predictable: by simulating their respective environmental conditions, we can model evolution of the gene content in Buchnera aphidicola and Wigglesworthia glossinidia with over 80% accuracy. We conclude that, at least for the particular cases considered here, gene content of an organism can be predicted with knowledge of its distant ancestors and its current lifestyle.