Adaptation in complex scenarios

复杂场景适配

• 批准号: NE/E013066/1
• 负责人: Sinead Collins
• 金额: $ 36.09万
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2007
• 资助国家: 英国
• 起止时间: 2007 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FE013066%2F1
• 关键词: Adaptation; complex; scenarios

The observation that organisms are adapted to their environment is obvious, yet we can only explain how this occurs in extreme scenarios such as the evolution of antibiotic and pesticide resistance, heavy metal tolerance, and starvation. Typical studies that aim to understand how organisms adapt following an environmental change proceed by placing a population in an environment to which it is poorly adapted. This stressful environment is usually extreme so as to provoke an observable response, and is also usually static. For example, a plant population may be transferred from a nutrient-rich environment to one where a particular nutrient is nearly absent. The population then adapts by the sequential fixation of novel mutations that increase its growth and reproduction in the new environment. Theory and experiments that use this framework have allowed us to describe how fast a population adapts over time, how many mutations are involved in a typical round of adaptation, and how many different outcomes we expect if the same population adapts to the same stressful environment many times. However, very few environmental changes outside of laboratories and natural disasters involve the sudden transition from one relatively stable environment to a second, drastically different, stable environment. Instead, environments tend to change gradually over time, such that most populations exist in an environment that is only slightly different from that of a recent ancestor, even though it may differ substantially from a more distant ancestor. Global change is an example of this, where plant populations are currently exposed to levels of carbon dioxide more than twice as high as those of the last glaciation 10,000 years ago, but only a few percent higher than those of a decade ago. Thus, at any given time, populations are adapting to a subtle shift in environment, but the environment does not hold still while they do it. This suggests that studies of adaptation should incorporate both the magnitude and rate of environmental change. A second consideration is that populations do not adapt in isolation, but must compete with other populations while they are doing so. If one considers two populations in a changing environment, it is possible that one population excludes the other, but it is also possible that the populations adapt during this succession, such that both the community composition (which species are present) as well as the genetic makeup of a given species changes over time. For example, if we wish to guess how much carbon will be taken up by oceans in the future, we need to know which species of phytoplankton will be dominant as well as if the future populations of the dominant species will take up carbon at much the same rate as contemporary populations of that same species. Because of this, it is important to know how and if ecological (competitive) and evolutionary (adaptive) processes interact. My research uses laboratory experiments, computer simulations, and studies of natural populations to examine how large populations of single-celled algae respond to different rates of environmental change, either alone or in communities. Using a microbial model system allows me to do experiments using very large populations and span hundreds of generations, which allows the fixation of novel beneficial mutations by natural selection. One of these environmental changes is elevated CO2. Because laboratory systems are necessarily artificial, I will look for similar patterns of adaptation in algal communities from naturally occurring high CO2 springs. This work provides insight into one of the most fundamental processes in biology, that of adaptation. In addition, this work uses ideas and techniques from many disciplines, namely evolutionary biology, ecology, population genetics and molecular genetics. This sort of interdisciplinary, problem-based approach allows me to examine complex scenarios where the theory to do so may be lack

生物适应环境的观察结果是显而易见的，但我们只能解释这种情况如何在极端情况下发生，例如抗生素和农药耐药性的进化，重金属耐受性和饥饿。典型的旨在了解生物体如何适应环境变化的研究是通过将种群置于其不太适应的环境中进行的。这种压力环境通常是极端的，以引起可观察到的反应，也通常是静态的。例如，一个植物种群可能从一个营养丰富的环境转移到一个几乎没有某种营养物质的环境。然后，种群通过新突变的连续固定来适应，这些突变增加了其在新环境中的生长和繁殖。使用这一框架的理论和实验使我们能够描述一个种群随着时间的推移适应的速度有多快，在典型的一轮适应中涉及多少突变，以及如果同一种群多次适应相同的压力环境，我们预计会有多少不同的结果。然而，在实验室和自然灾害之外，很少有环境变化涉及从一个相对稳定的环境突然过渡到另一个完全不同的稳定环境。相反，随着时间的推移，环境往往会逐渐改变，因此大多数种群所处的环境与最近的祖先只有轻微的不同，尽管它可能与更遥远的祖先有很大的不同。全球变化就是一个例子，植物种群目前暴露在二氧化碳水平下的程度是一万年前最后一次冰期的两倍多，但只比十年前高几个百分点。因此，在任何给定的时间，人口都在适应环境的微妙变化，但在他们适应的过程中，环境并没有保持不变。这表明，对适应的研究应该同时考虑环境变化的幅度和速度。第二个考虑是种群不能孤立地适应环境，而必须在适应环境的同时与其他种群竞争。如果考虑两个种群在不断变化的环境中，有可能一个种群排斥另一个种群，但也有可能种群在演替过程中适应，这样，群落组成（哪些物种存在）以及给定物种的基因组成都会随着时间的推移而变化。例如，如果我们希望猜测未来海洋将吸收多少碳，我们需要知道哪些种类的浮游植物将占主导地位，以及优势物种的未来种群吸收碳的速度是否与同一物种的当代种群相同。正因为如此，了解生态（竞争）和进化（适应）过程如何以及是否相互作用是很重要的。我的研究使用实验室实验、计算机模拟和对自然种群的研究来研究单细胞藻类的大种群是如何对不同的环境变化速率做出反应的，无论是单独的还是在群体中。利用微生物模型系统，我可以用非常大的种群做实验，跨越数百代，这使得自然选择可以固定新的有益突变。其中一个环境变化是二氧化碳浓度升高。由于实验室系统必然是人工的，我将从自然发生的高二氧化碳泉中寻找藻类群落的类似适应模式。这项工作提供了对生物学中最基本的过程之一的见解，即适应。此外，这项工作还使用了许多学科的思想和技术，即进化生物学、生态学、群体遗传学和分子遗传学。这种跨学科的、基于问题的方法使我能够检查可能缺乏理论的复杂场景

项目成果

Experimental evolution and global change

实验进化和全球变化

• 期刊: Evolutionary applications
• 影响因子: 4.1
• 作者: Sinead Collins (Author)

Fold or hold: experimental evolution in vitro.

• DOI: 10.1111/jeb.12233
• 发表时间: 2013-10
• 期刊: Journal of evolutionary biology
• 影响因子: 2.1
• 作者: Collins S;Rambaut A;Bridgett SJ
• 通讯作者: Bridgett SJ

Adaptive walks toward a moving optimum

• DOI: 10.1534/genetics.107.072926
• 发表时间: 2007-06-01
• 期刊: GENETICS
• 影响因子: 3.3
• 作者: Collins, Sinead;de Meaux, Juliette;Acquisti, Claudia
• 通讯作者: Acquisti, Claudia