“Kin Selection Explains the Evolution of Cooperation in the Gut Microbiota”, 2021-02-09 (; similar):
This is a comparative study attempting to explain the pattern of cooperation across a number of microbial species. Hamilton’s inclusive-fitness theory makes the very general prediction that increased genetic relatedness should drive the evolution of cooperation. Various arguments have dismissed the validity of this prediction in microbes, but without ever testing the broad taxonomic support for those arguments. Here, we rehabilitate the central role of relatedness by showing that its power to predict cooperative gene content holds across the full diversity of the human gut microbiota. Explaining broad-scale patterns is critical to an unifying variable for predictive science and broad applications. The manipulation of relatedness may offer an opportunity to engineering microbial communities, such as the gut microbiota.
Through the secretion of “public goods” molecules, microbes cooperatively exploit their habitat. This is known as a major driver of the functioning of microbial communities, including in human disease. Understanding why microbial species cooperate is therefore crucial to achieve successful microbial community management, such as microbiome manipulation.
A leading explanation is that of Hamilton’s inclusive-fitness framework. A cooperator can indirectly transmit its genes by helping the reproduction of an individual carrying similar genes. Therefore, all else being equal, as relatedness among individuals increases, so should cooperation. However, the predictive power of relatedness, particularly in microbes, is surrounded by controversy.
Using phylogenetic comparative analyses across the full diversity of the human gut microbiota and six forms of cooperation, we find that relatedness is predictive of the cooperative gene content evolution in gut-microbe genomes. Hence, relatedness is predictive of cooperation over broad microbial taxonomic levels that encompass variation in other life-history and ecology details.
This supports the generality of Hamilton’s central insights and the relevance of relatedness as a key parameter of interest to advance microbial predictive and engineering science.
[Keywords: cooperation, comparative analysis, microbiome, evolutionary microbiology]