An introduction to using counterdiabatic driving to eliminate genetic lag in changing environments
An introduction to using counterdiabatic driving to eliminate genetic lag in changing environments
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介绍如何使用反热量驾驶来消除不断变化的环境中的遗传滞后
DOI：
10.1162/isal_a_00344
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Scott, Jacob G.
中科院分区：
文献类型：
--
作者：
Dolson, Emily;Iram, Shamreen;Chiel, Joshua;Pelesko, Julia;Krishnan, Nikhil;Güngör, Özenç;Kuznets-Speck, Benjamin;Deffner, Sebastian;Ilker, Efe;Scott, Jacob G.
进化越来越被认为是建立和控制生命和类生命系统的强大工具。然而，进化过程的复杂性和随机性迄今为止使它更像是一个钝的工具，而不是一个可以精确控制的工具。在这里，我们提出了一种方法，可以开始给我们提供精细控制的水平，我们需要利用进化来实现更广泛的目的。利用进化来达到预期的最终结果的一个常见步骤是，随着时间的推移，沿着沿着某个连续的轴逐渐改变环境。目前，我们缺乏严格的理论来预测这种适应发生的速度，这意味着必须反复测试一个种群，才能知道它何时达到了预期的最终状态。这一要求并不理想，因为在某些情况下，这种检测是不可能的（例如测量患者体内耐药癌细胞的当前遗传状态）。在这里，我们描述了这个问题的解决方案的开始（在（Iram等人，2019年））。作为一个起点，我们考虑一个理想的情况下，我们有完美的知识的健身景观，频繁的突变，和一个大的人口。使用一种称为反绝热（CD）驱动的物理方法，我们可以从数学上推导出如何改变环境的处方，以便种群以快速和可预测的速度到达自适应的最终状态。CD驱动最初是在量子力学Demirplak and Rice（2003，2005）; Berry（2009）中提出的概念。最近，它已被用于经典物理应用，如创建一个光镊Martınez等人。（2016年）。从根本上说，CD驱动是一种通过使一系列不同的中间状态使一个有噪声的系统任意快速地平衡到一个新状态的方法。作为一个直观的例子，考虑一个服务员在托盘上端着一杯水（Sels和Polkovnikov，2017）。如果他在走路时保持托盘完全平坦，他将需要非常缓慢地移动，以避免溢出任何水。他可以走得更快，而不洒，如果他稍微倾斜托盘，以抵消他的加速度施加在玻璃上的力。在这样做的时候，他使用了CD力--一种新的自由度，可以被操纵来使系统在给定的开始和结束状态之间更快地移动。
Evolution is increasingly recognized as a powerful tool for building and controlling living and lifelike systems. However, the complexity and stochasticity of the evolutionary process have thus far made it more of a blunt instrument than a tool that can be precisely controlled. Here, we present an approach that can begin to give us the level of fine control we need to harness evolution for a wider variety of purposes. A common step in using evolution to achieve a desired end result is to gradually change an environment over time along some continuous axis. Currently, our lack of rigorous theory predicting the rate at which this adaptation will occur means a population must be repeatedly tested to know when it has reached the desired end state. This requirement is not ideal, as there are some contexts in which such testing is impossible (eg measuring the current genetic state of drug-resistant cancer cells in a patient’s body). Here, we describe the beginning of a solution to this problem (presented in full in (Iram et al., 2019)). As a starting point, we consider an ideal case where we have perfect knowledge of the fitness landscape, frequent mutations, and a large population. Using an approach from physics called counterdiabatic (CD) driving, we can mathematically derive a prescription for how to change the environment so that the population arrives at the adaptive end-state at a fast and predictable speed. CD driving is a concept originally developed in quantum mechanics Demirplak and Rice (2003, 2005); Berry (2009). More recently, it has been used in classical physics applications such as the creation of an optical tweezer Martınez et al.(2016). Fundamentally, CD driving is a way to force a noisy system to equilibrate to a new state arbitrarily quickly by subjecting it to a different series of intermediate states. As an intuitive example, consider a waiter carrying a glass of water on a tray (Sels and Polkovnikov, 2017). If he keeps the tray perfectly flat while walking, he will need to move very slowly to avoid spilling any water. He can walk much more quickly without spilling if he instead tilts the tray slightly to counteract the force his acceleration exerts on the glass. In so doing, he has used a CD force–a new degree of freedom that can be manipulated to move a system more quickly between a given start and end state.
影响因子：
4.3
作者：
Nichol D;Jeavons P;Fletcher AG;Bonomo RA;Maini PK;Paul JL;Gatenby RA;Anderson AR;Scott JG
通讯作者：
Scott JG
影响因子：
10.7
作者：
Brown, Kyle M.;Costanzo, Marna S.;Hartl, Daniel L.
通讯作者：
Hartl, Daniel L.
影响因子：
19.6
作者：
Iram, Shamreen;Dolson, Emily;Hinczewski, Michael
通讯作者：
Hinczewski, Michael