Biology subjects

Grosse-Sommer, J. M.

Publications and source records attributed to Grosse-Sommer, J. M..

3 recordsLinked to original sources

bioRxiv2026

Fitness effects of new mutations are small and heavily confounded with non-genetic sources of variation in Escherichia coli

The distribution of fitness effects (DFE) of new mutations underpins our understanding of molecular evolution, mutation load and the maintenance of quantitative genetic variation. Most direct estimates in microbes rely on mutation-accumulation (MA) lines that harbour many mutations, so that only the mean and variance of the DFE can be inferred reliably and non-genetic ('environmental') differences between lines are usually ignored. Here we generated 192 Escherichia coli MA lines that accumulated no mutations, one mutation or more than one mutation in similar proportions. Comparing the growth rates of lines with mutations with the mutation-free controls allowed us to partition fitness variation into genetic and non-genetic components. We estimate the average selection coefficient of a single mutation is unlikely to be less than -0.0020 (with 95% credibility) - a value that is small, not significantly different from zero, and largely concordant with most previous estimates from multi-mutant MA studies, although those earlier results have often been misinterpreted as implying much larger deleterious effects. Crucially, systematic non-genetic effects among lines were an order of magnitude larger than mutational effects, and failure to model them would have biased the mean selection coefficient downwards by an order of magnitude. Our study demonstrates that spontaneous mutations in E. coli are typically only mildly deleterious and that rigorous controls for environmental effects are essential for unbiased inference of the DFE in microbial systems.

evolutionary biology↗

bioRxiv2026

Selection bias in colony-based microbial mutation accumulation lines

In microbial mutation-accumulation (MA) studies, it is widely thought that natural selection is silenced by repeated single-cell bottlenecks. In support of this claim, 40 published tests for selection bias failed to detect a deficit of non-synonymous relative to synonymous mutations in wild-type microbes. Here we show that this most likely reflects selective reporting and lack of power. Our meta-analysis of 10,856 mutations from wild-type microbial MA reveals a clear signal of selection: non-synonymous mutations are observed 7.7% less often than synonymous mutations. However, our inference of the bias is hampered by a widespread failure to consider the mutation spectrum. To overcome this, we provide a multinomial-logit model that jointly estimates the mutation spectrum and selection. By applying this to a 194-line Escherichia coli MA experiment and five previous E. coli datasets (869 mutations) we reveal a deficit of non-synonymous mutations, although the reduction is not significant. While approaches do exist for correcting for selection bias, all currently assume that microbial MA lines are grown in well-mixed liquid culture rather than as surface colonies where competition is spatially structured. Although existing theory suggests selection bias should be stronger under colony growth, using agent-based simulations we show that this actually depends on the scale over which neighbouring cells compete and how unevenly they divide: it can be weaker, equivalent to, or stronger than in homogeneous growth. While our preliminary assessment is that it is considerably stronger, quantitative predictions will require the empirical details of colony growth to be better resolved.

genetics↗

bioRxiv2022

The dynamics of adaptation to stress from standing genetic variation and de novo mutations

Adaptation from standing genetic variation is an important process underlying evolution in natural populations but we rarely get the opportunity to observe the dynamics of fitness changes in real time. Here, we used the power of microbial experimental evolution and whole population sequencing to track the phenotypic and genomic changes of genetically diverse yeast populations in environments with different stress levels. We found that populations rapidly and in parallel increased in fitness in stressful environments. The founders genetic diversity was quickly depleted, however, not to the same degree in all populations and environments. Some populations fixed all ancestral variation in < 30 generations while others maintained diversity across hundreds of generations. We also observed parallelism at the gene and pathway level. Specifically, we detected up to seven genes harbouring multiple independent mutations in different populations, and a general enrichment for mutations affecting downstream effectors of the high-osmolarity-glycerol pathway in three out of four environments. Adaptation to the most stressful environment was characterised by the fast evolution of functional haploidy, likely driven by standing genetic variation. Almost 40% of all populations contained aneuploidies (losses or gains of chromosomes) at least once during experimental evolution. Some aneuploidies were maintained for hundreds of generations in parallel in different replicates, suggesting they were adaptive. This work shows that experimental evolution is a great tool to address the interplay between standing variation and the influx of de novo mutations, leading to a better understanding of the demographic and environmental drivers and constraints of a populations capacity to adapt to environmental change.

evolutionary biology↗