The adaptive landscape of a metallo-enzyme is shaped by environment-dependent epistasis

Abstract

Enzymes can evolve new catalytic activity when environmental changes present them with novel substrates. Despite this seemingly straightforward relationship, factors other than the direct catalytic target can also impact adaptation. Here, we characterize the catalytic activity of a recently evolved bacterial methyl-parathion hydrolase for all possible combinations of the five functionally relevant mutations under eight different laboratory conditions (in which an alternative divalent metal is supplemented). The resultant adaptive landscapes across this historical evolutionary transition vary in terms of both the number of "fitness peaks" as well as the genotype(s) at which they are found as a result of genotype-by-environment interactions and environment-dependent epistasis. This suggests that adaptive landscapes may be fluid and molecular adaptation is highly contingent not only on obvious factors (such as catalytic targets), but also on less obvious secondary environmental factors that can direct it towards distinct outcomes.

Fig. 1. Functional evolutionary history of MPH gene family.

a Phylogenetic reconstruction of MPH family and its DHCH relatives. The catalytic activities (kcat/KM) of the enzymes for dihydrocoumarin and methylparathion are displayed in bar graphs (error bars show standard deviation). The five key mutations between the ancestral DHCH enzyme and MPH are labeled in orange on the branch between MPH-m5 and the derived MPH. The schematic phylogenetic was constructed using previously published phylogenetic reconstruction. b Overlay of the cartoon representations of the crystal structures of DHCH (cyan, PDB ID: 6c2c) and MPH (orange, PDB ID: 1p9e). The five key mutations are highlighted as sticks and labeled in orange. The two active site metal ions are shown as spheres. Residues involved in coordinating the active site metal ions are highlighted as sticks and labeled in gray. The docking pose of the methyl-parathion substrate is shown as sticks. c A cropped multiple sequence alignment of representative sequences of extant MPH, DHCH, and resurrected ancestral enzymes. Residues at the positions where the five active site mutations have occurred between DHCH and MPH are highlighted in orange. c is adapted from Yang et al..

Fig. 2. Effect of all substitutions when introduced in different metal environments.

a The lysate activity of the ancestral DHCH genotype (open circles) and fully derived MPH genotype (solid circles) in eight different metal environments. Activities shown are the average of three biological replicates, with error bars indicating the standard deviation. b The collective effect of all five historical substitutions (fold-change in lysate activity between the ancestral genotype and the derived genotype) in each metal environment. Activities shown are the average of three biological replicates, with error bars indicating the standard deviation. The activities of purified enzymes in the eight different metal environments is presented in Supplementary Fig. 2.

Fig. 3. Adaptive landscape and likely historical evolutionary trajectories for alternative metal environments.

a–h The adaptive landscape encompassing all 32 genotypes that define this evolutionary transition for all metal environments tested. Local and global optimal genotypes are highlighted with larger nodes while the ancestral genotype (DHCH) is highlighted by a star node. Dashed lines or arrows indicate transitions that are within the margin of error. Blue nodes and lines indicate those that reach the derived genotype (11111); red nodes and lines indicate those that reach the second most common optimal genotype (01100); green nodes and lines indicate those that reach the third most common optimal genotype (01101).

Fig. 4. The average effect of each of the five historical substitutions when introduced in different metal environments.

Average effect is shown with solid bars while the effect of each mutation introduced in the 16 alternate genetic backgrounds is shown with dots (each bar therefore representing the corresponding average across all 16 dots for each environment).

Fig. 5. Changes in epistatic interactions.

a The pairwise epistatic interaction effects for each metal environment. The two interacting residues are denoted on the x-axis by their positions, with an “x” in between them (e.g., 72 × 193 denote the pair-wise effects of mutations at positions 72 and 193). b The relationship between the effect of mutating position 271 and the number of previously fixed substitutions at other sites for each metal. Symbol (*) denotes a statistically significant correlation (p < 0.05 after correcting for multiple tests). c The impact of previous substitutions at positions 72, 193, 258. and 273 on the effect of the substitution at position 271.

Fig. 6. Change in functional impact of substitutions along adaptive trajectories.

The impact of substitutions as they are accumulated along the projected adaptive trajectory in each metal environment. Colored dots indicate the corresponding metal environment’s “end point” for the projected trajectory beginning at the ancestral DHCH genotype. Genotypes are labeled using a binary system, with “0” indicating the residue being in the ancestral state and “1” indicating the residue being in the derived state and are ordered according to the order of the residues in the enzyme sequence (e.g., the first number indicates the state of position 72, the second the state of position 193, the third the state of position 258 and so on).