Molecular evolutionary dynamics of energy limited microorganisms

Abstract

Microorganisms have the unique ability to survive extended periods of time in environments with extremely low levels of exploitable energy. To determine the extent that energy limitation affects microbial evolution, we examined the molecular evolutionary dynamics of a phylogenetically diverse set of taxa over the course of 1,000-days. We found that periodic exposure to energy limitation affected the rate of molecular evolution, the accumulation of genetic diversity, and the rate of extinction. We then determined the degree that energy limitation affected the spectrum of mutations as well as the direction of evolution at the gene level. Our results suggest that the initial depletion of energy altered the direction and rate of molecular evolution within each taxon, though after the initial depletion the rate and direction did not substantially change. However, this consistent pattern became diminished when comparisons were performed across phylogenetically distant taxa, suggesting that while the dynamics of molecular evolution under energy limitation are highly generalizable across the microbial tree of life, the targets of adaptation are specific to a given taxon.

Seed banks alter the molecular evolutionary dynamics ofBacillus subtilis

“…Despite the inability to form protective structures, all replicate populations of Δ spo0A from all transfer regimes survived the experiment. This pattern of consistent survival is a marked difference from a previous experiment that used an identical energy-limitation design, where bacterial taxa from diverse phyla (Bacteroidetes, Proteobacteria, and Deinococcus-Thermus) frequently went extinct in 10 and 100-day transfer regimes [31]. This comparison suggests that Bacillus is exceptionally capable of surviving and evolving in harsh environments, even without access to what is generally considered its primary survival strategy.…”

“…Populations were regularly plated to test for contamination. An identical experiment was concurrently run with the WT strain, which was previously described [31].…”

“…However, an unknown number of generations likely occurred while populations remained in stationary phase due to cells using dead cells as a nutrient source. This “cryptic growth” [25, 31–33] suggests that the estimated number of generations likely represents the true number of generations for 1-day transfers, while it is closer to an estimate of the minimum number of generations for 10 and 100-day transfers.…”

“…We tested for divergent/convergent evolution by examining the overlap of I between WT and Δ spo0A populations and populations from all three transfer regimes and comparing them to a null hypergeometric distribution as previously described [31]. To examine convergent/divergent evolution among enriched genes, we calculated the vector of relative multiplicities (ℳ i = m i / m i ) and compared the mean absolute difference between I genes for a given pair of transfer regimes or genetic backgrounds as …”

Predicting Parallelism and Quantifying Divergence in Experimental Evolution

“…The rise of evolve-and-resequence experiments as high-throughput screens for adaptation 4 has allowed researchers to identify recurrent mutations across replicate populations 4,5 , paring down the vast number of potentially adaptive mutations into those that putatively confer the largest fitness benefits. Furthermore, evolveand-resequence experiments have revealed that the outcomes of evolution are often conditional on the ancestral genotype of a microbial population [6][7][8][9][10] or the environment in which it was maintained [11][12][13][14][15] , a phenomenon known as divergent evolution.…”