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      Genetic architecture promotes the evolution and maintenance of cooperation.

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          Abstract

          When cooperation has a direct cost and an indirect benefit, a selfish behavior is more likely to be selected for than an altruistic one. Kin and group selection do provide evolutionary explanations for the stability of cooperation in nature, but we still lack the full understanding of the genomic mechanisms that can prevent cheater invasion. In our study we used Aevol, an agent-based, in silico genomic platform to evolve populations of digital organisms that compete, reproduce, and cooperate by secreting a public good for tens of thousands of generations. We found that cooperating individuals may share a phenotype, defined as the amount of public good produced, but have very different abilities to resist cheater invasion. To understand the underlying genetic differences between cooperator types, we performed bio-inspired genomics analyses of our digital organisms by recording and comparing the locations of metabolic and secretion genes, as well as the relevant promoters and terminators. Association between metabolic and secretion genes (promoter sharing, overlap via frame shift or sense-antisense encoding) was characteristic for populations with robust cooperation and was more likely to evolve when secretion was costly. In mutational analysis experiments, we demonstrated the potential evolutionary consequences of the genetic association by performing a large number of mutations and measuring their phenotypic and fitness effects. The non-cooperating mutants arising from the individuals with genetic association were more likely to have metabolic deleterious mutations that eventually lead to selection eliminating such mutants from the population due to the accompanying fitness decrease. Effectively, cooperation evolved to be protected and robust to mutations through entangled genetic architecture. Our results confirm the importance of second-order selection on evolutionary outcomes, uncover an important genetic mechanism for the evolution and maintenance of cooperation, and suggest promising methods for preventing gene loss in synthetically engineered organisms.

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          Most cited references16

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          The evolution of cooperation.

          Cooperation in organisms, whether bacteria or primates, has been a difficulty for evolutionary theory since Darwin. On the assumption that interactions between pairs of individuals occur on a probabilistic basis, a model is developed based on the concept of an evolutionarily stable strategy in the context of the Prisoner's Dilemma game. Deductions from the model, and the results of a computer tournament show how cooperation based on reciprocity can get started in an asocial world, can thrive while interacting with a wide range of other strategies, and can resist invasion once fully established. Potential applications include specific aspects of territoriality, mating, and disease.
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            Bacterial quorum sensing and metabolic incentives to cooperate.

            The opportunistic pathogen Pseudomonas aeruginosa uses a cell-cell communication system termed "quorum sensing" to control production of public goods, extracellular products that can be used by any community member. Not all individuals respond to quorum-sensing signals and synthesize public goods. Such social cheaters enjoy the benefits of the products secreted by cooperators. There are some P. aeruginosa cellular enzymes controlled by quorum sensing, and we show that quorum sensing-controlled expression of such private goods can put a metabolic constraint on social cheating and prevent a tragedy of the commons. Metabolic constraint of social cheating provides an explanation for private-goods regulation by a cooperative system and has general implications for population biology, infection control, and stabilization of quorum-sensing circuits in synthetic biology.
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              Horizontal Gene Transfer of the Secretome Drives the Evolution of Bacterial Cooperation and Virulence

              Summary Background Microbes engage in a remarkable array of cooperative behaviors, secreting shared proteins that are essential for foraging, shelter, microbial warfare, and virulence. These proteins are costly, rendering populations of cooperators vulnerable to exploitation by nonproducing cheaters arising by gene loss or migration. In such conditions, how can cooperation persist? Results Our model predicts that differential gene mobility drives intragenomic variation in investment in cooperative traits. More mobile loci generate stronger among-individual genetic correlations at these loci (higher relatedness) and thereby allow the maintenance of more cooperative traits via kin selection. By analyzing 21 Escherichia genomes, we confirm that genes coding for secreted proteins—the secretome—are very frequently lost and gained and are associated with mobile elements. We show that homologs of the secretome are overrepresented among human gut metagenomics samples, consistent with increased relatedness at secretome loci across multiple species. The biosynthetic cost of secreted proteins is shown to be under intense selective pressure, even more than for highly expressed proteins, consistent with a cost of cooperation driving social dilemmas. Finally, we demonstrate that mobile elements are in conflict with their chromosomal hosts over the chimeric ensemble's social strategy, with mobile elements enforcing cooperation on their otherwise selfish hosts via the cotransfer of secretome genes with “mafia strategy” addictive systems (toxin-antitoxin and restriction-modification). Conclusion Our analysis matches the predictions of our model suggesting that horizontal transfer promotes cooperation, as transmission increases local genetic relatedness at mobile loci and enforces cooperation on the resident genes. As a consequence, horizontal transfer promoted by agents such as plasmids, phages, or integrons drives microbial cooperation.
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                Author and article information

                Journal
                PLoS Comput. Biol.
                PLoS computational biology
                Public Library of Science (PLoS)
                1553-7358
                1553-734X
                2013
                : 9
                : 11
                Affiliations
                [1 ] INSERM U1001, Université Paris Descartes, Sorbonne Paris Cité, Faculté de Médecine Paris Descartes, Paris, France.
                Article
                PCOMPBIOL-D-13-00846
                10.1371/journal.pcbi.1003339
                3836702
                24278000
                d5cf1a3c-2dcb-41b7-9d7f-47ff3004bf80
                History

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