引导和控制进化——从生物工程到对抗病原体。
Steering and controlling evolution - from bioengineering to fighting pathogens.
机构信息
Institute for Biological Physics, University of Cologne, Cologne, Germany.
Organismal and Evolutionary Biology Research Programme, Department of Computer Science, Institute of Biotechnology, University of Helsinki, Helsinki, Finland.
出版信息
Nat Rev Genet. 2023 Dec;24(12):851-867. doi: 10.1038/s41576-023-00623-8. Epub 2023 Jul 3.
Control interventions steer the evolution of molecules, viruses, microorganisms or other cells towards a desired outcome. Applications range from engineering biomolecules and synthetic organisms to drug, therapy and vaccine design against pathogens and cancer. In all these instances, a control system alters the eco-evolutionary trajectory of a target system, inducing new functions or suppressing escape evolution. Here, we synthesize the objectives, mechanisms and dynamics of eco-evolutionary control in different biological systems. We discuss how the control system learns and processes information about the target system by sensing or measuring, through adaptive evolution or computational prediction of future trajectories. This information flow distinguishes pre-emptive control strategies by humans from feedback control in biotic systems. We establish a cost-benefit calculus to gauge and optimize control protocols, highlighting the fundamental link between predictability of evolution and efficacy of pre-emptive control.
控制干预引导分子、病毒、微生物或其他细胞朝着期望的结果进化。应用范围从工程生物分子和合成生物到针对病原体和癌症的药物、治疗和疫苗设计。在所有这些情况下，控制系统都会改变目标系统的生态进化轨迹，从而产生新的功能或抑制逃逸进化。在这里，我们综合了不同生物系统中生态进化控制的目标、机制和动态。我们讨论了控制系统如何通过感测或测量、通过自适应进化或未来轨迹的计算预测来学习和处理有关目标系统的信息。这种信息流将人类的先发制人控制策略与生物系统中的反馈控制区分开来。我们建立了一个成本效益分析来评估和优化控制方案，突出了进化可预测性和先发制人控制效果之间的基本联系。
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