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. 2021 Nov;75(11):2641-2657.
doi: 10.1111/evo.14315. Epub 2021 Aug 18.

Molecular signatures of resource competition: Clonal interference favors ecological diversification and can lead to incipient speciation

Massimo Amicone  1 , Isabel Gordo  1
Affiliations

Molecular signatures of resource competition: Clonal interference favors ecological diversification and can lead to incipient speciation

Massimo Amicone et al. Evolution. 2021 Nov.

Abstract

Microbial ecosystems harbor an astonishing diversity that can persist for long times. To understand how such diversity is structured and maintained, ecological and evolutionary processes need to be integrated at similar timescales. Here, we study a model of resource competition that allows for evolution via de novo mutation, and focus on rapidly adapting asexual populations with large mutational inputs, as typical of many bacteria species. We characterize the adaptation and diversification of an initially maladapted population and show how the eco-evolutionary dynamics are shaped by the interaction between simultaneously emerging lineages - clonal interference. We find that in large populations, more intense clonal interference can foster diversification under sympatry, increasing the probability that phenotypically and genetically distinct clusters coexist. In smaller populations, the accumulation of deleterious and compensatory mutations can push further the diversification process and kick-start speciation. Our findings have implications beyond microbial populations, providing novel insights about the interplay between ecology and evolution in clonal populations.

Keywords: Clonal interference; competitive exclusion; diversification; eco-evolutionary dynamics; resource competition; speciation.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Ecological dynamics and individual‐based evolutionary processes. (A) Illustration of the eco‐evolutionary dynamics. Bacterial genotypes, represented by circles of different colors, grow according to the constant input of resources (squares and semicircles) and their phenotypic traits, represented by the enzyme‐like structures on the circles. Mutation events (red arrow) can generate new types whose fate will depend on drift and selection. (B) Constrained phenotypic space and mutation process. An initially maladapted monomorphic population (green circle) can acquire de‐novo mutations according to the given assumptions (as explained in the inset) and move inside the phenotypic space with an upper bound on the total energy. (C) Examples of different mutation regimes: from low/absent (NU << 1) to extensive (NU >>1) clonal interference. Each color represents a different genotype.
Figure 2
Figure 2
Diminishing return epistasis and the adaptation rate. (A) Analytical predictions of the diminishing return epistasis in monomorphic populations. The inset shows the effect of the energy constraint. (B) Dots represent the mean of the observed positive selection during the first 300 generations of adaptation. The dotted line represents the prediction using the average population trait sum (α^(t):=∑iM(t)ni(t)(α1(i)+α2(i))N). Each color represents an independent simulated population, which adapted with σ=0.05,ρ=0.5,N=107, and U =10−5. (C) The population average trait sum α^(t) is shown as proxy of adaptation under different σ and ρ conditions. Other parameters: R=2,N=107,U=10−8. Lines are the averages over 100 simulations and the shaded areas represent the confidence interval. (D) Same dynamics as in C, but on a different scale, as defined in panel. (E) Phenotypic adaptation across different mutational inputs (left) and expected strength and proportion of beneficial mutations at the end of the adaptation process. Lines represent the average across 100 populations and the shaded area their confidence interval. Other parameters for panel E: N=107,U=10−8,…,10−5,σ=0.05,ρ=0.5.
Figure 3
Figure 3
Genotypes’ dynamics and balance under competition for two resources. (A) Number of genotypes present in the environment over time, under neutrality (diamonds) or under selection (lines). Lines represent the average across 100 populations and the shaded area their confidence interval. On the right, zoom over the last 1000 generation. Other parameters: σ=0.05,ρ=0 and N=107,U=10−8,…,10−5. (B) Log‐log scaled rank abundance distribution of genotypes at generation 10000. Dots and dashed lines represent the mean across 100 populations under selection or neutrality, respectively. Parameters as in A. (C) Long‐lasting number of genotypes, computed as the average over the last 1000 generations (e.g., dotted line in the right panel of A). The lines represent the linear regressions: M∗=aNU+1 where NU:{0.1,0.5,1,5,10,50,100,500} and a={15.70±0.07,5.48±0.02} for the neutral or selection cases, respectively. Both axes are represented in log scale with ticks every {1,…,9}·10x. Other parameters as in A.
Figure 4
Figure 4
Ecological diversification under competition for two resources. (A) Two example populations evolving under the same conditions (N=107,U=10−5,ρ=0.5,σ=0.05,R=2). The phenotypes and the preference distributions show one population that has evolved into a single optimal cluster (squares) and another population that gave rise to a stable diverse community composed by two clusters (circles). Lines connecting the shapes represent mutations. (B) Counts of populations that evolved into 1,2 or more phenotypic clusters. Here, N=107,U=10−8,…,5·10−5,σ=0.05,R=2,ρ=0. C) Populations diversify with a probability that increases with ln(NU) and σ but decreases with ρ. The lines represent the fit of the data to the logistic function: P=11+ea(ln(NU)−b), NU:{0.1,0.2,0.3,0.4,0.5,0.6,1,5,10,50,100,500}. The inferred parameters a and b are reported in Tables S1‐2 and the full set of data is shown in Fig. S7. In the left plot:ρ=0, while in the right one: σ=0.05. The probabilities were computed as proportions out of 100 independent populations and their 95% confidence interval by normal approximation: P±zP(1−P)100,z=1.96.
Figure 5
Figure 5
Phenotypic and genetic characterization of the evolved populations. (A) Average pairwise genotypic (πG) and phenotypic (πP) diversity were measured within each population, as defined in the Methods. 100 independent populations were simulated for each of the conditions specified on the x‐axis and by the colors. Other parameters: σ = 0.05, 2 resources and N=107,U=10−8,…,5·10−5. (B) πP, πG, Tajima's D and fixations distributions of the populations that evolved into a single cluster (blue, n = 506) or into multiple ones (red, n = 294). Populations with different NU and ρ = 0 were pulled together for a total of 800 populations. The dotted lines represent the means of the corresponding distribution.
Figure 6
Figure 6
Speciation process in small populations with large mutational input. (A) Probability of diversification across different population sizes. Continuous lines represent the fit of the data to the logistic function: P=11+ea(ln(NU)−b), NU:{0.1,,0.5,1,5,10,50,100,500}, for N=103 (blue) or N=105,107, 109 together (orange). The inferred parameters a and b are reported in Tables S3. The dotted line represents the threshold (ln(NU)=4.78) when NUNs·ln(NU)>0.5, N=103and s=σ. The probabilities were computed as for Fig. 4. (B) Average trait sum over time and distribution of mutation effects at generations 8000 or 10,000. (C) Example population adapted with N=103,U=10−1,ρ=0,σ=0.05,R=2 for 10,000 generations. The inset shows the preference distribution at generations 10, 100, 1000, and 10,000. D) πG/NU and Tajima's D over time. Circles represent the median, while vertical bars range f//rom the 25th to the 75th quartiles. The dotted lines represent the expected value at neutral equilibrium. In particular πG=2NU and Tajima's D = 0. Other parameters: σ=0.05,ρ=0.
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References

    1. Abrams, P. A. 1988. How should resources be counted?. Theor. Popul. Biol. 10.1016/0040-5809(88)90014-7. - DOI
    1. Amado, A. , and Campos P. R. A.. 2019. Ecological specialization under multidimensional trade‐offs. Evolutionary Ecology. Springer International Publishing, 33:769–789. 10.1007/s10682-019-10013-4. - DOI
    1. Amicone, M. , and Gordo I. M.. 2021. Molecular signatures of resource competition: clonal interference favors ecological diversification and can lead to incipient speciation. Dryad, Dataset. 10.5061/dryad.15dv41nxt - DOI - PMC - PubMed
    1. Mac Arthur, R. 1969. Species Packing, and What Competition Minimizes. Proc. Natl. Acad. Sci. 64:1369–1371. 10.1073/pnas.64.4.1369. - DOI - PMC - PubMed
    1. Bailey, S. F. , and Kassen R.. 2012. Spatial structure of ecological opportunity drives adaptation in a bacterium. Am. Nat. 10.1086/666609. - DOI - PubMed

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