Metabolic erosion primarily through mutation accumulation, and not tradeoffs, drives limited evolution of substrate specificity in Escherichia coli

Abstract

Evolutionary adaptation to a constant environment is often accompanied by specialization and a reduction of fitness in other environments. We assayed the ability of the Lenski Escherichia coli populations to grow on a range of carbon sources after 50,000 generations of adaptation on glucose. Using direct measurements of growth rates, we demonstrated that declines in performance were much less widespread than suggested by previous results from Biolog assays of cellular respiration. Surprisingly, there were many performance increases on a variety of substrates. In addition to the now famous example of citrate, we observed several other novel gains of function for organic acids that the ancestral strain only marginally utilized. Quantitative growth data also showed that strains with a higher mutation rate exhibited significantly more declines, suggesting that most metabolic erosion was driven by mutation accumulation and not by physiological tradeoffs. These reductions in growth by mutator strains were ameliorated by growth at lower temperature, consistent with the hypothesis that this metabolic erosion is largely caused by destabilizing mutations to the associated enzymes. We further hypothesized that reductions in growth rate would be greatest for substrates used most differently from glucose, and we used flux balance analysis to formulate this question quantitatively. To our surprise, we found no significant relationship between decreases in growth and dissimilarity to glucose metabolism. Taken as a whole, these data suggest that in a single resource environment, specialization does not mainly result as an inevitable consequence of adaptive tradeoffs, but rather due to the gradual accumulation of disabling mutations in unused portions of the genome.

Figure 1. Biolog measurements are a poor proxy for growth performance.

(A) Biolog AUC as measured for the D-glucose on Biolog plates. The evolved strains have a lower AUC value than the ancestor on glucose, the carbon source available during evolution (p<0.0001, Welch's two sample t test). The mean AUC for the 20k and 50k isolates on glucose are not statistically different. (B) Scatter plot showing the measurement of function as Biolog AUC versus growth rate on all substrates, for all strains at 20k and 50k generations as well as the ancestors. The regression shown is for substrates after removal of categorical disagreements (growth without respiration or respiration without growth, 167/702 in total).

Figure 2. Relative growth rates across a variety of growth substrates for evolved strains from 20k (A) or 50k generations (B).

Heatmaps indicate the log ratio of growth rates relative to the average of the two ancestors on that carbon source. White indicates a growth rate equal to that of the ancestor average, red faster, and blue slower. The growth rates are plotted on a log scale with the limits of the color range set for twice as fast and half as fast as the ancestor average. An “x” in a box indicates that no growth was observed for that combination of strain and substrate over 48 h. Strains that were mutators by that time point are indicated.

Figure 3. Substrate dissimilarity does not predict metabolic erosion.

(A) A simple categorization of substrates as sugars and nonsugars finds that the correlation between relatedness to glucose and evolved metabolic changes is the opposite from what is hypothesized. (B) The FBA-predicted mutational target size does not correlate with decreases in growth rate. (C) Hamming distance between FBA-generated flux vectors for carbon sources partially predicts ancestral growth rate. Black dots indicate the growth rate of the two ancestral strains. A total of 268 reactions were predicted as necessary for optimal metabolism on glucose. (D) Hamming distance between a substrate and glucose does not correlate with increases or decreases in growth rate. The y axis is the log of the ratio of growth rate relative to the ancestor, with all ratios greater or less than e ² binned at the axis limit. For (C–D), purple dots are mutator strains, and orange dots are nonmutators. Larger dots at the axis extrema indicate more overlapping points, and the shading between purple and orange indicates the different proportions of mutators and nonmutators at that limit. For (B–D), substrates with the same x axis values were plotted with a slight offset, and the true value is listed in the axis label.

Figure 4. Temperature dependence of growth rate on alternative substrates.

For all strain/substrate measurements, we determined the relative change in growth rate by changing temperature from 37°C to 30°C. For (A–B), purple dots are mutator strains; orange dots nonmutators. Points that fall outside of the plot range are plotted at the edge of the graph. (A) Effect of temperature change on 20k isolates. (B) Effect on 50k isolates. (C) For 50k isolates, the number of mutators and nonmutators that were rescued from no growth at 37°C to growth at 30°C.