Metabolite toxicity determines the pace of molecular evolution within microbial populations

Abstract

Background: The production of toxic metabolites has shaped the spatial and temporal arrangement of metabolic processes within microbial cells. While diverse solutions to mitigate metabolite toxicity have evolved, less is known about how evolution itself is affected by metabolite toxicity. We hypothesized that the pace of molecular evolution should increase as metabolite toxicity increases. At least two mechanisms could cause this. First, metabolite toxicity could increase the mutation rate. Second, metabolite toxicity could increase the number of available mutations with large beneficial effects that selection could act upon (e.g., mutations that provide tolerance to toxicity), which consequently would increase the rate at which those mutations increase in frequency.

Results: We tested this hypothesis by experimentally evolving the bacterium Pseudomonas stutzeri under denitrifying conditions. The metabolite nitrite accumulates during denitrification and has pH-dependent toxic effects, which allowed us to evolve P. stutzeri at different magnitudes of nitrite toxicity. We demonstrate that increased nitrite toxicity results in an increased pace of molecular evolution. We further demonstrate that this increase is generally due to an increased number of available mutations with large beneficial effects and not to an increased mutation rate.

Conclusions: Our results demonstrate that the production of toxic metabolites can have important impacts on the evolutionary processes of microbial cells. Given the ubiquity of toxic metabolites, they could also have implications for understanding the evolutionary histories of biological organisms.

Keywords: Denitrification; Experimental evolution; Microbial populations; Molecular evolution; Nitrite toxicity.

Fig. 1

The denitrification pathway of P. stutzeri. Nitrate is first reduced to nitrite in the cytoplasm. Nitrite is then actively transported to the periplasmic space where it is further reduced through several intermediates to dinitrogen gas. The consequence is that nitrite accumulates in the periplasm. Enzymes: Nar, nitrate reductase; Nir, nitrite reductase; Nor, nitric oxide reductase; Nos, nitrous oxide reductase

Fig. 2

The number of mutations that accumulated in clones after evolution at pH 6.5 (strong nitrite toxicity) or pH 7.5 (weak nitrite toxicity). Horizontal bars and P-values indicate the outcomes of two-sample Wilcoxon rank-sum tests. The arrow indicates the clone with a mutation in uvrA. Data are presented as Tukey box-plots

Fig. 3

The types of mutations that accumulated in clones after evolution at pH 6.5 (strong nitrite toxicity) or pH 7.5 (weak nitrite toxicity). Each mutation was categorized by type and frequency among all mutations. Data are presented as Tukey box-plots

Fig. 4

Relative time to stationary phase for each experimental evolution condition. Data are the time to reach stationary phase for the evolved clones divided by the time to stationary phase for the ancestral clones. The horizontal bar and P-value indicates the outcome of a two-sample Wilcoxon rank-sum test. The asterisk indicates P < 0.05. The data are presented as Tukey box-plots

Fig. 5

Competitive fitness of evolved clones relative to the ancestor. Evolved cells were initially present in the culture at a frequency of 5%. Differences were compared using an ANOVA test followed by a post hoc Tukey’s HSD test. Significant differences correspond to P < 0.01. Alphabetic assignments indicate groups that are statistically different from each other

Fig. 6

Functional categorization of genes that contain mutations in evolved clones for each experimental evolution condition. Each mutation was categorized by type. Data are presented as Tukey box-plots. Functional categories (COG): S, function unknown; N, cell motility; T, signal transduction; G, carbohydrate transport and metabolism; I, lipid transport and metabolism; C, energy production and conversion; P, inorganic ion transport and metabolism; K, transcription; E, amino acid transport and metabolism; H, coenzyme transport and metabolism; L, replication, recombination and repair; O, posttranslational modification, protein turnover, and chaperones

Fig. 7

Performance of evolved and ancestral clones to utilize alternative carbon substrates. Carbon utilization was measured for 95 different carbon substrates. Performance was quantified as the area under the growth curve for each individual carbon substrate (OD₆₀₀ vs. time), which takes into account both growth rate and yield. Data are presented as histograms. (a) Comparison of clones evolved at pH 7.5 with ancestral populations at pH 7.5; (b) comparison of clones evolved at pH 6.5 with ancestral clones at pH 6.5; (c) comparison of ancestral clones at pH 6.5 with ancestral clones at pH 7.5; (d) comparison of clones evolved at pH 6.5 with clones evolved at pH 7.5