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

生物常常为了群体成员的利益而做出自我牺牲。这些可能是复杂的行为，比如在其他动物觅食时观察捕食者，也可能是相对简单的行为，比如细菌产生帮助其他动物生长的分子。为什么个人要做出这些昂贵的牺牲，而他们可以简单地避免成本并免费从别人的牺牲中获益？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（自私的）遗传进化观点，该观点认为，如果其他携带这些基因副本的个体也能从中获益，那么导致代价高昂的帮助行为的基因就会受到青睐（因此，基因最终会帮助复制自身）。事实上，在许多生物系统中，个体帮助亲属是因为他们有更大的可能共享基因（例如，兄弟姐妹有50:50的机会共享基因）。显然，对他们来说，更好的策略是识别并将利益直接传递给那些肯定拥有自己基因副本的人。理查德·道金斯（Richard Dawkins）在一个思想实验中抓住了这一观点：一个基因产生一个信号（绿胡子），识别出其他基因发出的信号，然后改变行为，直接帮助其他绿胡子个体。这种“绿胡子”系统似乎提供了完美的解决方案。然而，如果绿胡子基因出现，它将提供如此大的优势，最终所有的个体都将拥有同样的绿胡子（所有的个体都会一直互相帮助）。这在生物系统中是看不到的。此外，生物学家认为，一个基因编码所有所需的不同特性（信号、识别、帮助行为）是不可能的。与这些预期相反，绿胡子基因已经在各种各样的生物中被描述，这些生物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。我们将在一个迷人的微生物系统中结合数学理论和实验测试来解决这个问题。我们对这个问题的解决方案来自于认识到在自然界中发现的绿胡子的两个令人困惑但又常见的特征的重要性。首先，同一物种的不同个体通常具有不同的绿须基因序列，这导致它们具有不同的特性。其次，绿胡子往往是由基因组中相邻的几个基因组成的。我们的假设是，需要这些特性来允许不同的相互作用的个体来测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多大程度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，我们将用它来从理论上探索这个假设。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，碟形盘基钢柱。这个系统非常适合，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亲缘关系，然后调整它们愿意做出多大的牺牲（因此，当它们不与亲戚在一起时，它们的自我牺牲就会减少）。我们还证明了这些变形虫有由两个基因组成的绿须，在每个菌株中都是不同的。我们将研究这些绿胡子基因与合作程度决定之间的联系，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令人难以置信的特性的潜在机制。

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.