Beyond Center for Fundamental Concepts in Science, Arizona State University, Tempe, AZ, USA.
School of Earth and Space Exploration, Arizona State University, Tempe, AZ, USA.
Sci Adv. 2019 Jan 16;5(1):eaau0149. doi: 10.1126/sciadv.aau0149. eCollection 2019 Jan.
The application of network science to biology has advanced our understanding of the metabolism of individual organisms and the organization of ecosystems but has scarcely been applied to life at a planetary scale. To characterize planetary-scale biochemistry, we constructed biochemical networks using a global database of 28,146 annotated genomes and metagenomes and 8658 cataloged biochemical reactions. We uncover scaling laws governing biochemical diversity and network structure shared across levels of organization from individuals to ecosystems, to the biosphere as a whole. Comparing real biochemical reaction networks to random reaction networks reveals that the observed biological scaling is not a product of chemistry alone but instead emerges due to the particular structure of selected reactions commonly participating in living processes. We show that the topology of biochemical networks for the three domains of life is quantitatively distinguishable, with >80% accuracy in predicting evolutionary domain based on biochemical network size and average topology. Together, our results point to a deeper level of organization in biochemical networks than what has been understood so far.
网络科学在生物学中的应用已经增进了我们对于个体生物代谢和生态系统组织的理解，但几乎没有被应用于行星尺度的生命研究。为了描述行星尺度的生物化学，我们使用了一个包含 28146 个注释基因组和宏基因组以及 8658 种分类生化反应的全球数据库来构建生化网络。我们揭示了控制生物化学多样性和网络结构的规律，这些规律在从个体到生态系统再到整个生物圈的各个组织层次上都具有共性。将真实的生化反应网络与随机反应网络进行比较表明，所观察到的生物缩放并不仅仅是化学的产物，而是由于常见的参与生命过程的特定选择反应的结构而产生的。我们表明，生命三个域的生化网络拓扑结构在定量上是可区分的，基于生化网络大小和平均拓扑结构，预测进化域的准确率超过 80%。总的来说，我们的研究结果表明，生化网络的组织程度比目前所理解的要更深。
