An allosteric pathway explains beneficial fitness in yeast for long-range mutations in an essential TIM barrel enzyme

Abstract

Protein evolution proceeds by a complex response of organismal fitness to mutations that can simultaneously affect protein stability, structure, and enzymatic activity. To probe the relationship between genotype and phenotype, we chose a fundamental paradigm for protein evolution, folding, and design, the (βα)₈ TIM barrel fold. Here, we demonstrate the role of long-range allosteric interactions in the adaptation of an essential hyperthermophilic TIM barrel enzyme to mesophilic conditions in a yeast host. Beneficial fitness effects observed with single and double mutations of the canonical βα-hairpin clamps and the α-helical shell distal to the active site revealed an underlying energy network between opposite faces of the cylindrical β-barrel. We experimentally determined the fitness of multiple mutants in the energetic phase plane, contrasting the energy barrier of the chemical reaction and the folding free energy of the protein. For the system studied, the reaction energy barrier was the primary determinant of organism fitness. Our observations of long-range epistatic interactions uncovered an allosteric pathway in an ancient and ubiquitous enzyme that may provide a novel way of designing proteins with a desired activity and stability profile.

Keywords: TIM barrel; allosteric pathway; biophysics; energy network; fitness; protein design; protein engineering.

FIGURE 1

Wire diagram of SsIGPS, a canonical TIM barrel protein. Sites of mutations are highlighted in green with their wildtype side chains displayed as spheres. βα‐Hairpin clamp partners are highlighted in white with their wildtype side chains displayed as spheres. Active site residues are highlighted in red with the Cα displayed as spheres. (PDB: 2C3Z)

FIGURE 2

Selection coefficients of single and double mutants in SsIGPS. Selection coefficients are plotted on a bar graph to show the relative fitness of the mutants to wildtype. Bars are colored qualitatively to distinguish mutants. Most mutations are neutral (s ~ 0) or beneficial (s > 0). Selection coefficients for beneficial mutations plateaus around s ~ 0.18. Vector‐only controls (not shown) result in lethality (s ~ −1). Errors are propagated from the standard deviation of measurements from three biological samples

FIGURE 3

Far‐UV mean residue ellipticities of WT and mutant SsIGPS. Far‐UV CD spectra of SsWT and mutants collected at (a) 25°C (b) 30°C in 10 mM KPi, pH 7.2. For reference, the SsWT spectrum is shown in black. Mutant spectra are shown using a qualitative color palette. At both temperatures, the prominent negative band at 222 nm is indicative of the presence of α‐helix secondary structure. At 30°C, reduced CD signals for I107A (light purple) and I45A/M73A (yellow) suggest the proteins are partially unfolded

FIGURE 4

Protein stabilities and interaction energies of WT and mutant SsIGPS. The entire CD spectra as a function of urea for each variant were globally fit to a three‐state model and the results plotted as fraction unfolded. (a) Collected sample reads are indicated by the filled circles. Fits to the data are indicated by the dash lines. Urea melts observed by CD at 222 nm show stabilities of mutants differed from SsWT for both the native and intermediate states. Mutant titrations are shown using a qualitative color palette. (b) Interaction energies, δ _NI and δ _IU, were calculated using the ΔΔG values for both the NI and IU transitions. All double mutants show nonzero interaction energies. Bars are colored by selection coefficients indicated by the color scale. Errors were propagated from the fit of the model

FIGURE 5

Catalytic properties of WT and mutant SsIGPS enzymes. (a) Initial velocity measurements were collected to determine the catalytic efficiency of each SsIGPS variants at 30°C in 10 mM KPi, pH 7.2. Fluorescence readings from the product formation (circle marker) were fit to the Michaelis–Menten equation (dashed line) to determine the kinetic parameters, k _cat, K _m, and k _eff. Markers are colored qualitatively to distinguish mutants. (b) The K _eff was plotted as a function of k _cat for each of the SsIGPS variants. A positive linear relationship was observed between the turnover number and the catalytic efficiency. Markers are colored by selection coefficient. Mutants are individually labeled near the marker. The fit is denoted by the black dashed line. The gray dotted lines are visual guides for the values associated with SsWT. (c) Interaction energies, δ _kcat, were calculated using the activation energy barrier energy, ΔΔG ^‡ values for the k _cat transitions. All double mutants show nonzero interaction energies. Bars are colored by selection coefficients indicated by the color scale. Errors are propagated from the standard deviation of measurements collected from three biological samples

FIGURE 6

Correlation of selection coefficients and activity and stability‐activity plot for WT and mutant SsIGPS. (a) Selection coefficient is negatively correlated with transition state activation energy of catalysis. Values of s were plotted as a function of ΔΔG ^‡ _kcat for each of the SsIGPS variants and showed a negative linear relationship. The fit is denoted by the black dashed line. Markers are colored by selection coefficient. The gray dotted lines are visual guides for the values associated with SsWT. (b) Fitness landscape of mutants on function‐stability energy plane. Markers are colored by selection coefficient. Within the native well of the folding free energy surface, a complex relationship is found between activity and stability. No mutants are found on the upper left quadrant of the energy plane in our experiments