A Model Simulation of the Adaptive Evolution through Mutation of the Coccolithophore Emiliania huxleyi Based on a Published Laboratory Study

Abstract

We expect the structure and functioning of marine ecosystems to change over this century in response to changes in key ocean variables associated with a changing climate. Organisms with generation times from years to decades have the capacity to adapt to changing environmental conditions over a few generations by selecting from existing genotypes/phenotypes, but it is unlikely that evolution through mutation will be a major factor for organisms with generation times of years to decades. However, phytoplankton and other microbes, with generation times of days or less, experience hundreds of generations each year, allowing the possibility for favorable mutations (i.e., those that produce organisms with fitness maxima nearer to the environmental conditions at that time) to dominate existing genotypes and survive in a changing climate. Several laboratories have grown phytoplankton cultures for hundreds to thousands of generations and demonstrated that they have changed genetic makeup. In particular Schlüter et al. (2014) grew replicates derived from a single cell of Emiliania huxleyi, a coccolithophorid with broad geographical and thermal range, for 3 years (∼1250 generations) at 15 • C, and then for a year at 26.3 • C, near their upper thermal limit. During the last year the intrinsic growth rate increased more or less linearly, which the authors attribute to genetic mutation. Here we simulate genetic mutation of a single trait (intrinsic growth rate), both for the control phase and the warm phase of their study. We consider sensitivities to frequency of mutation, changes with temperature in intrinsic growth rate, and use the experimental setup and results to place constraints on the way mutations occur. In particular, all numerical experiments with mutation result in a lag time ∼30-140 generations before a significant increase in realized growth rate occurs. This lag after a favorable mutation results from the number of generations required for a single favorable mutant cell to reach a significant fraction of the ∼10 5 cells in the culture. A numerical experiment that includes a simple plastic response formulation shows that plasticity could remove this lag and yield results more in agreement with those observed in the laboratory study.

Microbial evolutionary strategies in a dynamic ocean

“…However, because LT modifications are reversible, the fitness benefits and trait changes from LT modifications will be lost from the population more quickly than would be expected from HT modifications alone, especially in a dynamic environment where selective pressure can fluctuate. Theoretical (8,17) and empirical (9,12) data suggest that HT and LT modifications acting together best explain patterns of microbial evolution on timescales of hundreds of generations. For example, experimental evolution studies in yeast have shown that the interaction of short-term epigenetic inheritance with genetic mutation modifies the rate and type of adaptation, thereby impacting long-term evolution (12).…”

Changing Biogeochemistry of the Southern Ocean and Its Ecosystem Implications

“…As such, the biogeographic provinces of phytoplankton assemblages in the Southern Ocean are likely to shift spatially or change fundamentally in the coming decades (Deppeler and Davidson, 2017). On longer timescales, a persistent new set of environmental conditions may drive evolutionary adaptation of existing species (Denman, 2017). Changes in NPP and phytoplankton species composition influence many biogeochemical processes, such as the magnitude and stoichiometry of nutrient uptake and recycling (Arrigo et al, 1999;Weber and Deutsch, 2010; Section "Changes in Macronutrient Biogeochemistry") and carbon transfer to higher trophic levels (Section "Carbon Transfer and Storage in Pelagic and Benthic Food Webs").…”

Epigenetically facilitated mutational assimilation: epigenetics as a hub within the inclusive evolutionary synthesis

“…This raises the question of the timescale of such experimental detection studies. Furthermore, a recent theoretical paper concluded that in a large population of ∼10 5 individuals, the time for a single favourable mutation to reach a significant (and thus detectable) fraction of the population may take between 30 and 140 generations (Denman, ). Alternatively, epigenetically facilitated mutations can emerge more rapidly in large populations such as in microbes.…”