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.

生物体经常做出自我牺牲，使其群体成员受益。这些可能是复杂的行为，例如在其他人觅食时观察捕食者，或者是相对简单的行为，例如细菌产生有助于其他人生长的分子。为什么个人要做出这些昂贵的牺牲，当他们可以简单地避免成本和白吃别人所做的牺牲？这个问题困扰了生物学家几十年。一个潜在的解决方案来自于进化的（自私的）遗传学观点，它表明，如果其他携带这些基因副本的个体获得了好处，那么导致代价高昂的帮助行为的基因可能会受到青睐（因此该基因最终会帮助自己的副本）。事实上，在许多生物系统中，个体会帮助亲属，因为他们分享基因的可能性更大（例如，兄弟姐妹分享基因的可能性为50：50）。显然，对他们来说，更好的策略是识别和指导那些肯定与他们共享基因副本的人的利益。理查德·道金斯（Richard Dawkins）在一个思想实验中捕捉到了这一想法，在这个实验中，一个单一的基因产生一个信号（一个绿色胡子），识别其他人的信号，并修改行为，以指导对其他绿色胡子个体的帮助。这种“绿胡子”系统似乎提供了完美的解决方案。然而，如果一个绿胡子基因出现了，它将提供一个巨大的优势，最终所有的个体都将拥有同样的绿胡子（所有的个体都将一直互相帮助）。这在生物系统中是看不到的。此外，生物学家认为，一个单一的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。与这些预期相反，绿胡子基因在各种各样的生物体中被描述，这些生物体仍然选择谁或何时帮助他人。显然，我们对形成识别、合作和绿胡子基因作用的进化过程的理解是不够的。我们将通过在一个迷人的微生物系统中将数学理论与实验测试相结合来解决这个问题。我们对这个问题的解决方案来自于认识到自然界中绿胡子的两个令人困惑但又共同的特征的重要性。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，这导致它们具有不同的特性。其次，绿胡子往往是由几个基因组成的，这些基因在基因组中彼此相邻。我们的假设是，这些属性是必需的，允许不同的相互作用的个体来衡量这些基因是否是共享的，然后使用基因共享的数量来确定他们愿意做出多大的自我牺牲来造福他们的群体。我们已经开发了一个数学框架，我们将使用它来从理论上探讨这个假设。我们还将进行实验研究来验证这一理论。为此，我们将使用一个简单的微生物模型，盘基网柄藻。这种系统非常适合，因为单细胞个体聚集在一起，其中一些细胞牺牲自己并死亡，以帮助剩余的细胞作为孢子分散。我们之前已经证明，不同的菌株会衡量它们与群体的关系，然后调整它们愿意做出的牺牲程度（因此，当它们不与亲戚在一起时，它们会减少自我牺牲）。我们还证明了这些变形虫有一个由两个基因组成的绿胡子，每个菌株都不同。我们将研究这些绿胡子基因之间的联系，以及决定合作的程度，它们是如何进化的，它们包含的变异类型，并剖析允许这些基因编码绿胡子所有难以置信的特性的潜在机制。

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