NERC-FAPESP: Unravelling the evolutionary processes shaping greenbeard recognition systems and the control of cooperative behaviour

NERC-FAPESP：揭示塑造绿胡子识别系统的进化过程和合作行为的控制

• 批准号: NE/V012002/1
• 负责人: Christopher Thompson
• 金额: $ 82.86万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FV012002%2F1
• 关键词: NERC; FAPESP; Unravelling; evolutionary; processes

Organisms often make self sacrifices that benefit members of their group. These may be complex behaviours, such as watching for predators while others forage, or relatively simple behaviours, such as bacteria that produce molecules that help others grow. Why do individuals make these costly sacrifices when they could simply avoid the costs and freeload on the sacrifices made by others? This question has perplexed biologists for decades. A potential solution comes from a (selfish) genetic perspective on evolution, which suggests that genes that result in costly helping behaviours can be favoured if the benefits are reaped by other individuals carrying copies of those genes (so the gene ends up helping copies of itself). Indeed, in many biological systems, individuals help relatives because they have an increased likelihood of sharing genes (e.g. siblings have a 50:50 chance of gene sharing). Obviously, an even better strategy would be for them to identify and direct benefits to others who definitely share copies of their genes. Richard Dawkins' captured this idea in a thought experiment where a single gene produces a signal (a green beard), identifies that signal in others, and modifies behaviour to direct help towards other green bearded individuals. Such 'greenbeard' systems would appear to provide the perfect solution. However, if a greenbeard gene arose it would provide such a big advantage that eventually all individuals would have the same greenbeard (and all individuals would help one another all the time). This is not seen in biological systems. Furthermore, biologists have argued that it is implausible for a single gene to encode all the different properties required (signal, recognition, helping behaviour). Contrary to these expectations, greenbeard genes have been described in a diverse array of organisms that still select who or when to help others. Clearly our understanding of the evolutionary processes that shape recognition, cooperation, and the role of greenbeard genes is insufficient. We will address this problem by combining mathematical theory with experimental tests in a fascinating microbial system. Our solution to this problem comes from recognising the importance of two puzzling yet common features of greenbeards identified in nature. Firstly, different individuals of the same species typically have different greenbeard gene sequences, which causes them to have different properties. Secondly, greenbeards tend to be composed of several genes found next to each other in the genome. Our hypothesis is that these properties are required to allow different interacting individuals to measure whether these genes are shared and then use the amount of gene sharing to determine how much they are willing to make self-sacrifices that benefit their group. We have developed a mathematical framework that we will use to explore this hypothesis theoretically. We will also perform experimental studies to test this theory. For this, we will use a simple microbial model, Dictyostelium discoideum. This system is ideally suited because single-celled individuals come together in groups, where some cells sacrifice themselves and die to help the remaining cells disperse as spores. We have previously demonstrated that different strains measure their relatedness to their group and then adjust how much of a sacrifice they are willing to make (so they make less of a self-sacrifice when they are not with relatives). We have also demonstrated that these amoebae have a greenbeard composed of two genes, which differ in each strain. We will investigate the link between these greenbeard genes and the decision of how much to cooperate, how they have evolved, the type of variation they contain, and dissect the underlying mechanisms that allow these to encode all the implausible properties of a greenbeard.

有机体经常做出自我牺牲，使他们的小组成员受益。这些可能是复杂的行为，例如观察捕食者，而其他人觅食或相对简单的行为，例如产生帮助他人成长的分子的细菌。当个人可以简单地避免其他人的牺牲的成本和免费负担时，为什么会做出这些昂贵的牺牲？这个问题几十年来一直困扰着生物学家。一个潜在的解决方案来自对进化的（自私的）遗传学观点，这表明，如果携带这些基因副本的其他个体获得益处，则会有利于昂贵的帮助行为的基因（因此基因最终有助于自身的副本）。实际上，在许多生物系统中，个人会帮助亲戚，因为他们的分享基因的可能性增加（例如，兄弟姐妹有50:50的基因共享机会）。显然，一个更好的策略是让他们确定和直接给其他肯定具有其基因副本的人。理查德·道金斯（Richard Dawkins）在一个思想实验中捕获了这一想法，其中一个基因产生信号（绿胡须），识别在他人中信号的信号，并修改行为以直接帮助其他绿色胡须的个体。这种“绿色”系统似乎可以提供完美的解决方案。但是，如果出现了一个绿胡子基因，它将提供一个很大的优势，以至于最终所有个人都会拥有相同的绿胡子（所有个人都会一直在互相帮助）。这在生物系统中没有看到。此外，生物学家认为，单个基因编码所需的所有不同特性（信号，识别，帮助行为）是不可能的。与这些期望相反，已经在各种生物体中描述了绿胡子基因，这些生物仍然选择谁或何时帮助他人。显然，我们对塑造识别，合作和绿胡子基因作用的进化过程的理解是不够的。我们将通过将数学理论与引人入胜的微生物系统中的实验测试相结合来解决这个问题。我们解决这个问题的解决方案来自于认识到自然界中发现的两个令人困惑但共同特征的重要性的重要性。首先，同一物种的不同个体通常具有不同的绿胡子基因序列，这会导致它们具有不同的特性。其次，绿色面包倾向于由基因组中彼此相邻的几个基因组成。我们的假设是，这些属性必须允许不同的相互作用的个体来衡量这些基因是否共享，然后使用基因共享的数量来确定他们愿意做出有益于受益的自我成分的程度。我们已经开发了一个数学框架，我们将使用该框架来理论上探索这一假设。我们还将进行实验研究以检验该理论。为此，我们将使用简单的微生物模型Dictyostelium Discoideum。理想情况下，该系统非常适合，因为单细胞个体聚集在一起，其中一些细胞会牺牲自己并死亡，以帮助其余细胞分散为孢子。我们以前曾证明，不同的菌株衡量了他们与群体的相关性，然后调整他们愿意做出的牺牲的程度（因此，当他们不与亲戚在一起时，他们会减少自我牺牲）。我们还证明，这些变形虫具有由两个基因组成的绿胡子，每个基因在每个菌株上都不同。我们将研究这些绿胡子基因之间的联系，并决定要合作多少，它们如何发展，它们所包含的变异类型，并剖析了允许这些机制，这些机制允许这些机制编码绿色的所有不可思议的特性。

项目成果

The genetic architecture underlying prey-dependent performance in a microbial predator.

微生物捕食者依赖猎物表现的遗传结构。

• DOI: 10.1038/s41467-021-27844-x
• 发表时间: 2022-01-14
• 期刊: Nature communications
• 影响因子: 16.6
• 作者: Stewart B;Gruenheit N;Baldwin A;Chisholm R;Rozen D;Harwood A;Wolf JB;Thompson CRL
• 通讯作者: Thompson CRL