Allopatric divergence of cooperators confers cheating resistance and limits effects of a defector mutation

Abstract

Background Social defectors may meet diverse cooperators. Genotype-by-genotype interactions may constrain the ranges of cooperators upon which particular defectors can cheat, limiting cheater spread. Upon starvation, the soil bacterium Myxococcus xanthus cooperatively develops into spore-bearing fruiting bodies, using a complex regulatory network and several intercellular signals. Some strains (cheaters) are unable to sporulate effectively in pure culture due to mutations that reduce signal production but can exploit and outcompete cooperators within mixed groups. Results In this study, interactions between a cheater disrupted at the signaling gene csgA and allopatrically diversified cooperators reveal a very small cheating range. Expectedly, the cheater failed to cheat on all natural-isolate cooperators owing to non-cheater-specific antagonisms. Surprisingly, some lab-evolved cooperators had already exited the csgA mutant’s cheating range after accumulating fewer than 20 mutations and without experiencing cheating during evolution. Cooperators might also diversify in the potential for a mutation to reduce expression of a cooperative trait or generate a cheating phenotype. A new csgA mutation constructed in several highly diverged cooperators generated diverse sporulation phenotypes, ranging from a complete defect to no defect, indicating that genetic backgrounds can limit the set of genomes in which a mutation creates a defector. Conclusions Our results demonstrate that natural populations may feature geographic mosaics of cooperators that have diversified in their susceptibility to particular cheaters, limiting defectors’ cheating ranges and preventing them from spreading. This diversification may also lead to variation in the phenotypes generated by any given cooperation-gene mutation, further decreasing the chance of a cheater emerging which threatens the persistence of cooperation in the system.

Ecological histories determine the success of social exploitation

“…We assessed cheating by calculating the relative fitness parameter W ij (Manhes et al . 2022; Schaal et al . 2022): Positive and negative values of this parameter indicate that the cheater exhibits higher or lower relative spore production than WT in pairwise mixes.…”

“…We tested for the ability of each known cheater strain to cheat on WT during sporulation for all four combinations of predevelopment nutritional histories. We assessed cheating by calculating the relative fitness parameter Wij (Manhes et al 2022;Schaal et al 2022):…”

“…Groups of tens-of-thousands of M. xanthus cells aggregate, but only a small minority become spherical spores; the remaining cells either die or remain rod-shaped cells (Amherd et al 2018;Lee et al 2012;Zusman et al 2007). In this system, developmental cheaters are defined as strains that are defective at spore production in monoculture (compared to high-sporulating cooperators) but which produce proportionally more spores than cooperators in mixed groups (Schaal et al 2022;Velicer et al 2000). Laboratory experiments have repeatedly shown that developmental cheaters can rapidly increase in frequency due to their exploitation of cooperators, in some cases leading to large population crashes and even extinction events (Fiegna & Velicer 2003;Manhes & Velicer 2011;Velicer et al 2000).…”

“…2007). In this system, developmental cheaters are defined as strains that are defective at spore production in monoculture (compared to high-sporulating cooperators) but which produce proportionally more spores than cooperators in mixed groups (Schaal et al . 2022; Velicer et al .…”

Deletion of an sRNA primes development in a multicellular bacterium

“…4a) [9][10][11] , and the temporal dynamics and expression levels of those genes shared between the studies may vary, too. These differences are likely due to protocol differences and genetic backgrounds (different reference strains), but study idiosyncrasies may also reflect the molecular complexity and plasticity intrinsic to fruiting-body development 11,[44][45][46] . Discrepancies in specific gene-expression levels from our transcriptome profiles can be ascribed to the different physiological states in which cells were sampled (growing vs starving cells).…”