The Simons Center for Systems Biology, Institute for Advanced Study, Princeton, NJ 08540;
Laboratory of Living Matter, The Rockefeller University, New York, NY 10065.
Proc Natl Acad Sci U S A. 2019 Jul 9;116(28):13847-13855. doi: 10.1073/pnas.1903232116. Epub 2019 Jun 20.
Biological organisms exhibit diverse strategies for adapting to varying environments. For example, a population of organisms may express the same phenotype in all environments ("unvarying strategy") or follow environmental cues and express alternative phenotypes to match the environment ("tracking strategy"), or diversify into coexisting phenotypes to cope with environmental uncertainty ("bet-hedging strategy"). We introduce a general framework for studying how organisms respond to environmental variations, which models an adaptation strategy by an abstract mapping from environmental cues to phenotypic traits. Depending on the accuracy of environmental cues and the strength of natural selection, we find different adaptation strategies represented by mappings that maximize the long-term growth rate of a population. The previously studied strategies emerge as special cases of our model: The tracking strategy is favorable when environmental cues are accurate, whereas when cues are noisy, organisms can either use an unvarying strategy or, remarkably, use the uninformative cue as a source of randomness to bet hedge. Our model of the environment-to-phenotype mapping is based on a network with hidden units; the performance of the strategies is shown to rely on having a high-dimensional internal representation, which can even be random.
生物有机体表现出多种适应不同环境的策略。例如,一个生物种群可能在所有环境中都表现出相同的表型(“不变策略”),或者根据环境线索表达不同的表型以适应环境(“跟踪策略”),或者多样化为共存的表型以应对环境不确定性(“赌注对冲策略”)。我们引入了一个通用框架来研究生物体如何对环境变化做出反应,该框架通过从环境线索到表型特征的抽象映射来模拟适应策略。根据环境线索的准确性和自然选择的强度,我们发现不同的适应策略由映射表示,这些映射最大限度地提高了种群的长期增长率。之前研究的策略是我们模型的特例:当环境线索准确时,跟踪策略是有利的,而当线索存在噪声时,生物体可以使用不变策略,或者更令人惊讶的是,利用无信息线索作为随机性的来源来进行赌注对冲。我们的环境到表型映射模型基于具有隐藏单元的网络;策略的性能被证明依赖于具有高维内部表示,甚至可以是随机的。