Effect of the Reproduction Method in an Artificial Selection Experiment at the Community Level

Abstract

Selection at the group level is proposed to be an evolutionary process occurring in the context of multilevel selection in natura. In artificial selection experiments, selecting at the community level can allow to find multispecies assemblages that are more efficient than a single species at solving a given problem. In such procedures, the main difficulty is to find a balance between variation and heritability, which are both essential for selection to act. The aim of our study was to determine if the way of creating offspring units of selection from parental units, called "reproduction method," could influence artificial selection efficiency through a differential in the variation/heritability balance. Selecting microbial communities depending on their biomass production and propagating them either one by one or in a mix of three communities, we showed that the effect of the reproduction method was not maintained over time with a loss of the effect of artificial selection on community phenotype at certain cycles and a very low heritability. However, mixing parental communities was more efficient at increasing biomass production than using a single parental community (+5% of biomass). We discussed the role of differences in community richness and structure in explaining these results.

Steering ecological-evolutionary dynamics during artificial selection of microbial communities

“…Theoretical work predicts that artificial selection of communities can succeed, at least under certain conditions [11,12,13,14,15,16,4]. Experimental work on community selection have yielded variable outcomes [17,18,19,20,21,22,23,24,25,26,27,28]. In some cases, communities indeed responded to selection, presumably driven by changes in the species composition [22,23,24,25] and/or evolution [17,18], although some of these experiments are not conclusive due to lack of a "no selection" control.…”

Artificially selecting microbial communities using propagule strategies

“…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) .…”

“…Thus, each selected community acts as the single parental community that seeds a new crop of N >1 new "offspring" communities. This method has been used in at least three different studies to our knowledge (Swenson et al 2000b;Arora et al 2019;Raynaud et al 2019) . An alternative method has also been used and termed the "migrant pool method" (Swenson et al 2000b) .…”

“…An alternative method has also been used and termed the "migrant pool method" (Swenson et al 2000b) . It relies on mixing together the highest performing communities, using the mixed pool as the inoculum from which the offspring generation will be seeded (Swenson et al 2000b;Blouin et al 2015;Panke-Buisse et al 2015;Raynaud et al 2019) .…”

Top-down engineering of complex communities by directed evolution

“…Directed evolution can be used to iteratively optimize the function of microbial communities, through sequential rounds of exploration and selection. Previous approaches to engineer communities from the top-down include enrichment (which is often followed by a perturbation such as a bottleneck, to reduce community complexity)[20,[22][23][24]28,82,83] , and selective breeding by artificial selection[1,[31][32][33][34][36][37][38][39][40][41][42] . The directed evolution approach we have studied here combines components of both approaches: the iterative search that is inherent of the latter, with the idea of building stable consortia and exploring compositional variants of the former.…”