Symbiosis, the living together of unlike organisms as symbionts, is ubiquitous in the natural world. Symbioses occur within and across all scales of life, from microbial to macro-faunal systems. Further, the interactions between symbionts are multimodal in both strength and type, can span from parasitic to mutualistic within one partnership, and persist over generations. Studying the ecological and evolutionary dynamics of symbiosis in natural or laboratory systems poses a wide range of challenges, including the long time scales at which symbioses evolve de novo, the limited capacity to experimentally control symbiotic interactions, the weak resolution at which we can quantify interactions, and the idiosyncrasies of current model systems. These issues are especially challenging when seeking to understand the ecological effects and evolutionary pressures on and of a symbiosis, such as how a symbiosis may shift between parasitic and mutualistic modes and how that shift impacts the dynamics of the partner population. In digital evolution, populations of computational organisms compete, mutate, and evolve in a virtual environment. Digital evolution features perfect data tracking and allows for experimental manipulations that are impractical or impossible in natural systems. Furthermore, modern computational power allows experimenters to observe thousands of generations of evolution in minutes (as opposed to several months or years), which greatly expands the range of possible studies. As such, digital evolution is poised to become a keystone technique in our methodological repertoire for studying the ecological and evolutionary dynamics of symbioses. Here, we review how digital evolution has been used to study symbiosis, and we propose a series of open questions that digital evolution is well-positioned to answer.

Simple multicellularity evolves readily in diverse unicellular species, but nascent multicellular groups are prone to reversion to unicellularity. Successful transitions to multicellularity therefore require subsequent mutations that promote the entrenchment of the higher-level unit, stabilizing it through time. Here we explore the causes of entrenchment using digital evolution. When faced with a trade-off between cellular metabolic productivity and information fidelity, digital "multicells" often evolve reproductive division of labor. Because digital "unicells" cannot circumvent this trade-off, unicellular revertants tend to exhibit low fitness relative to their differentiated multicellular ancestors. Thus, division of labor can drive the entrenchment of multicellularity. More generally, division of labor may play a crucial role in major transitions, enriching the complexity and functionality of higher-level units while enhancing their evolutionary stability.

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