Predictive biology is the next great chapter in synthetic and systems biology, particularly for microorganisms. Tasks that once seemed infeasible are increasingly being realized such as designing and implementing intricate synthetic gene circuits that perform complex sensing and actuation functions, and assembling multi-species bacterial communities with specific, predefined compositions. These achievements have been made possible by the integration of diverse expertise across biology, physics and engineering, resulting in an emerging, quantitative understanding of biological design. As ever-expanding multi-omic data sets become available, their potential utility in transforming theory into practice remains firmly rooted in the underlying quantitative principles that govern biological systems. In this Review, we discuss key areas of predictive biology that are of growing interest to microbiology, the challenges associated with the innate complexity of microorganisms and the value of quantitative methods in making microbiology more predictable.

预测生物学是合成生物学和系统生物学的下一章，尤其是对于微生物学。曾经似乎不可行的任务越来越多地被实现，例如设计和实现执行复杂的传感和驱动功能的复杂的合成基因电路，以及将具有特定，预定组成的多物种细菌群落组装在一起。通过整合生物学，物理学和工程学领域的各种专业知识，使这些成就成为可能，从而使人们对生物学设计有了新的定量认识。随着越来越多的多组学数据集的出现，它们在将理论转化为实践中的潜在效用仍然牢固地植根于控制生物系统的基本定量原理。在这篇评论中，