Skip to main content

Effect of mutation supply on population dynamics and trait evolution in experimental microbial community

Cite this dataset

Cairns, Johannes; Jousset, Alexandre; Becks, Lutz; Hiltunen, Teppo (2021). Effect of mutation supply on population dynamics and trait evolution in experimental microbial community [Dataset]. Dryad.


Mutation supply can influence eco-evolutionary dynamics in important ways which have received little attention. Mutation supply determines key features of population genetics, such as the pool of adaptive mutations, evolutionary pathways available, and importance of processes such as clonal interference. The resultant trait evolutionary dynamics, in turn, can alter population size and species interactions. However, controlled experiments testing for the importance of mutation supply on rapid adaptation and thereby population and community dynamics are lacking. To close this knowledge gap, we performed a serial passage experiment with wild-type Pseudomonas fluorescens and an isogenic xerD mutant with reduced mutation rate. Bacteria were grown at two resource levels in combination with the presence of a ciliate predator. We found that a higher mutation supply enabled faster adaptation to the low-resource environment and anti-predatory defense. This was associated with higher population size at the ecological level and better access to high-recurrence mutational targets at the genomic level for the strain with higher mutation supply. In contrast, mutation rate did not affect growth under high-resource level, possibly because of more permissive conditions or high population size saturated in mutations. Our results demonstrate that intrinsic mutation rate influences population dynamics and trait evolution particularly when population size is constrained by extrinsic conditions.


The dataset was collected as part of an evolutionary experiment performed with the bacterial prey species Pseudomonas fluorescens F113 and the ciliate predator species Tetrahymena thermophila at two resource levels of King's B medium (0.5 and 2 %, representing low and high resource levels, respectively). The prey species had two substrains: a wild-type-like ("WTL") strain and mutant supply defective strain (insertional inactivation mutant, or "IM"). The experiment was performed using a full-factorial design, with four replicates per treatment combination. The data includes phenotypic and ecological data (F113_all_data.txt) and downstream genomic variant data from whole-genome sequencing (variants.txt).

Usage notes

The metadata in F113_all_data.txt  fileincludes the following fields:

day = day in serial transfer evolutionary experiment

bact_OD = bacterial population density (OD at 600 nm wavelength)

strain = bacterial strain (WTL/IM)

res_level = resource level (low/high)

predator = presene/absence of ciliate predation (yes/no)

rep = replicate (1-4)

id = unique sample id over time pasted from above fields except for day (e.g. "WTLhighno1")

pred_pop = ciliate predator population size (cells/ml)

xerD_expression = expression level of xerD (to control for gene function related to mutation supply in this model system)

delta_xerD_expression = change in expression level of xerD

res_use = growth ability (see manuscript for details)

delta_res_use = change in growth ability

D = anti-predatory defense level

delta_D = change in anti-predatory defense level

NA = data not measured for particular treatment or time point


The metadata in the variants.txt file includes the following fields for whole population (pool seq) samples from the evolutionary experimental end-point (day 58):

SAMPLE = unique sample id

STRAIN = bacterial strain (WTL/IM)

RESOURCE = resource level (low/high)

REPLICATE = replicate (1-4)

CHROM = name of F113 reference genome (one contiguous chromosome)   

POS = allele position (i.e. locus) on reference genome    

REF = reference allele (baseline)   

ALT = alternative allele (mutation against baseline)   

ANN_ALLELE = annotated allele (same as ALT as only those mutated positions kept with one ALT allele in an individual population)   

EFFECT = predicted effect of alternative allele (from variant effect prediction, VEP, using SnpEff) 

IMPACT = predicted impact of alternative allele (from variant effect prediction, VEP, using SnpEff)    

GENE = affected gene name    

GENEID = affected gene code   

HGVS_C = locus and base change in affected gene    

HGVS_P = locus and amino acid change in affected gene   

GT = genotype = alternative allele frequency in population (pool seq samples; 0-1)

EFFECT_CAT = EFFECT field simplified into three categories: nonsynonymous, synonymous and intergenic