Eco-evolutionary dynamics of nested Darwinian populations and the emergence of community-level heredity

Abstract

Interactions among microbial cells can generate new chemistries and functions, but exploitation requires establishment of communities that reliably recapitulate communitylevel phenotypes. Using mechanistic mathematical models, we show how simple manipulations to population structure can exogenously impose Darwinian-like properties on communities. Such imposition causes communities to participate directly in the process of evolution by natural selection and drives the evolution of cell-level interactions to the point where, despite underlying stochasticity, derived communities give rise to offspring communities that faithfully re-establish parental phenotype. The mechanism (developmental correction) is akin to a developmental process that arises from density dependent interactions among cells. Knowledge of ecological factors affecting evolution of developmental correction has implications for understanding the evolutionary origin of egalitarian transitions in individuality, symbioses, and for top-down engineering of microbial communities.

Artificially selecting microbial communities using propagule strategies

“…In particular, the outcomes of both experiments are in reasonable agreement with, and can be explained from, qualitative expectations of standard breeding theory. Looking to the future, and given the considerable challenges of doing these experiments in high-throughput (but see (Blouin et al 2015) ), we suggest that simulations such as those performed elsewhere (Williams and Lenton 2007a,b;Doulcier et al 2019;Xie et al 2019) will be very useful to explore different selection regimes, and thus to extract generic conclusions. Such efforts will be critical in order to develop a Theory of artificial selection of microbial communities that can guide the design of new protocols and experiments.…”

“…The difficulty of engineering community functions from the bottom-up (Escalante et al 2015) has motivated a surge of interest in evolutionary design (Bentley 1999) approaches, which treat the community as a unit of selection and explore the ecological landscape in search of consortia with desirable traits (Arias-Sánchez et al 2019) . This approach has been found to work in silico (Penn 2003,Williams andLenton 2007a,b;Doulcier et al 2019;Xie et al 2019) and it has been attempted several times in the laboratory to optimize functions such as toxin removal (Swenson et al 2000a) , the manipulation of environmental pH (Swenson et al 2000b) , or the modulation of various host traits (Swenson et al 2000b;Mueller and Sachs 2015;Panke-Buisse et al 2015Gopal and Gupta 2016;Mueller et al 2016;Jochum et al 2019) . The results of these experimental studies have been mixed (Blouin et al 2015;Arora et al 2019) , and it is becoming increasingly clear that the details of how exactly the "offspring" communities are generated from the "parental" communities can be critical for the success of this approach (Mueller et al 2016;Raynaud et al 2019) .…”

Top-down engineering of complex communities by directed evolution

“…Together, these tools are The population dynamics within a single batch represent an ecological succession. Recently, they have been elegantly conceptualized as a kind of "developmental maturation", where a community is in an "infant" state at the time of inoculation, and it is an "adult" at the time of harvest and reproduction [54,55] . When death rates are high, it is possible for communities to reach a steady state within a single succession, thus reaching generational equilibrium by the time they are an adult [54] .…”

“…At the end of each batch, a small number of cells are randomly drawn from the community and used to seed a new habitat where all nutrients have been replenished, thus starting a new batch. Inspired by Doulcier et al, we may see each succession as a "developmental" process at the community level, where the communities at the end of a batch incubation can be thought of being in an "adult state" where they are ready for reproduction, whereas the communities at the beginning of a batch incubation are in an "infant state" [54] . In absence of artificial community-level selection, our in silico enrichment communities eventually self-assemble into a dynamical state where successions are identical every generation (Fig.…”

Toward a dynamical understanding of microbial communities

“…Consider then, the evolution of interactions among constituent species that improve the likelihood that the parental phenotype is recapitulated: a community with such capacity will, therefore, spread as a consequence of community-level selection. The process of community-level selection thus favours the evolution of interactions that increasingly align the reproductive fate of cells with that of the community [67]. Taken to the extreme, derived communities, after many generations of community-level selection, are likely to become organismlike, rather like insects and their symbionts, or the eukaryotic cell that evolved from a community of once independently replicating archaebacterial-and eubacterial-like cells [60].…”