Spatial structure affects evolutionary dynamics and drives genomic diversity in experimental populations of Pseudomonas fluorescens

Abstract

Most populations live in spatially structured environments and that structure has the potential to impact the evolutionary dynamics in a number of important ways. Theoretical models tracking evolution in structured environments using a range of different approaches, suggest that local interactions and spatial heterogeneity can increase the adaptive benefits of motility, impact both the rate and extent of adaptation, and increase the probability of parallel evolution. We test these general predictions in a microbial evolution experiment tracking phenotypic and genomic changes in replicate populations of Pseudomonas fluorescens evolved in both well-mixed and spatially-structured environments, where spatial structure was generated through the addition of semi-solid agar. In contrast to the well-mixed environment, populations evolved in the spatially-structured environment adapted more slowly, retained the ability to disperse more rapidly, and had a greater putatively neutral population genomic diversity. The degree of parallel evolution measured at the gene-level, did not differ across these two types of experimental environments, perhaps because the populations had not evolved for long enough to near their fitness optima. These results confirm important general impacts of spatial structure on evolutionary dynamics at both the phenotypic and genomic level.

Experimental evidence that network topology can accelerate the spread of beneficial mutations

“…By contrast, a rich theoretical literature exists on the effects of different forms of spatial structure on the population genetics of neutral variation ( Hanski & Gilpin, 1997 ; Harrison & Hastings, 1996 ; Pannell & Charlesworth, 2000 ; Slatkin, 1985 ) and the interplay between migration and selection in adaptation ( Blanquart et al, 2012 ; Guillaume, 2011 ; Yeaman & Otto, 2011 ). Empirical work has considered the impact of spatial structure through habitat fragmentation on trait evolution ( Cheptou et al, 2017 ; Urban et al, 2008 ), how population subdivision modulates the extent of adaptive change ( Bailey et al, 2021 ; Baym et al, 2016 ; Chao & Levin, 1981 ; Habets et al, 2006 , 2007 ; Korona et al, 1994 ; Kryazhimskiy et al, 2012 ; Miralles et al, 1999 ; Nahum et al, 2015 ; Perfeito et al, 2007 ; Zhang et al, 2011 ) and community resilience ( Limdi et al, 2018 ). Other work in microbiology has examined the emergence and fate of diversity in spatially structured environments associated with colony growth or biofilms ( Borer et al, 2020 ; Celik Ozgen et al, 2018 ; France et al, 2018 , 2019 ; Kerr et al, 2002 ; Nadell et al, 2010 , 2016 ; Steenackers et al, 2016 ; Trubenová et al, 2022 ) but lacks explicit descriptions of spatial structure or conflates it with variation in conditions of growth that generate divergent selection ( Chen & Kassen, 2020 ; Leale & Kassen, 2018 ).…”

Formation and emergent dynamics of spatially organized microbial systems

“…Selective forces overall are predicted to be weaker in SOMS due to population fragmentation [93], potentiating coexistence of variants with differing fitness levels. Additionally, there is experimental evidence for increased genetic drift and clonal interference in SOMS [91,[100][101][102]. These royalsocietypublishing.org/journal/rsfs Interface Focus 13: 20220062 effects can reduce competitive exclusion that is expected to dominate under well-mixed conditions, resulting in an increased diversity in SOMS.…”

“…We hypothesize that emergent, nonlinear dynamics arising from ecology-cell physiology feedbacks are common to most SOMS and await discovery through application of appropriate measurements and models. Similarly, study of ecology-evolution feedback is so far explored in one-or two-species biofilms and synthetic systems [12,91,[100][101][102], but should now move towards in situ measurements of natural or nature-derived SOMS. This shift in research focus will benefit crucially from development of tractable model systems and spatio-temporal measurement methods (figure 3).…”

Experimental evidence that network topology can accelerate the spread of beneficial mutations

“…The well-mixed topology serves as a control. Previous experimental work on the impact of spatial structure on adaptive evolution has considered the impact of population subdivision on the magnitude or extent of adaptive change [13][14][15][16][17][18][19] , the emergence and maintenance of diversity [20][21][22][23] , and community resilience 24 , rather than the speed or probability of fixation.…”