Department of Plant and Microbial Biology, University of California, Berkeley, Berkeley, California, United States of America.
Feedstocks Division, Joint BioEnergy Institute, Emeryville, California, United States of America.
PLoS Biol. 2023 Jul 17;21(7):e3002190. doi: 10.1371/journal.pbio.3002190. eCollection 2023 Jul.
Our basic understanding of carbon cycling in the biosphere remains qualitative and incomplete, precluding our ability to effectively engineer novel solutions to climate change. How can we attempt to engineer the unknown? This challenge has been faced before in plant biology, providing a roadmap to guide future efforts. We use examples from over a century of photosynthesis research to illustrate the key principles that will set future plant engineering on a solid footing, namely, an effort to identify the key control variables, quantify the effects of systematically tuning these variables, and use theory to account for these observations. The main contributions of plant synthetic biology will stem not from delivering desired genotypes but from enabling the kind of predictive understanding necessary to rationally design these genotypes in the first place. Only then will synthetic plant biology be able to live up to its promise.
我们对生物圈碳循环的基本理解仍然是定性的和不完整的，这限制了我们有效设计应对气候变化的新解决方案的能力。我们怎么能尝试设计未知的东西呢？在植物生物学中，我们以前就面临过这个挑战，为未来的努力提供了一个指导路线图。我们使用一个多世纪的光合作用研究的例子来说明将为未来的植物工程奠定坚实基础的关键原则，即努力确定关键控制变量，量化系统调整这些变量的影响，并利用理论来解释这些观察结果。植物合成生物学的主要贡献将不是来自于提供所需的基因型，而是来自于能够实现首先进行合理设计这些基因型所需的那种预测性理解。只有这样，合成植物生物学才能不负众望。
