The relationship between evolutionary and physiological variation in hemoglobin

Abstract

Physiological and evolutionary adaptations operate at very different time scales. Nevertheless, there are reasons to believe there should be a strong relationship between the two, as together they modify the phenotype. Physiological adaptations change phenotype by altering certain microscopic parameters; evolutionary adaptation can either alter genetically these same parameters or others to achieve distinct or similar ends. Although qualitative discussions of this relationship abound, there has been very little quantitative analysis. Here, we use the hemoglobin molecule as a model system to quantify the relationship between physiological and evolutionary adaptations. We compare measurements of oxygen saturation curves of 25 mammals with those of human hemoglobin under a wide range of physiological conditions. We fit the data sets to the Monod-Wyman-Changeux model to extract microscopic parameters. Our analysis demonstrates that physiological and evolutionary change act on different parameters. The main parameter that changes in the physiology of hemoglobin is relatively constant in evolution, whereas the main parameter that changes in the evolution of hemoglobin is relatively constant in physiology. This orthogonality suggests continued selection for physiological adaptability and hints at a role for this adaptability in evolutionary change.

Fig. 1.

Hemoglobin saturation curve and the MWC model. (a) The oxygen saturation curve depicts the proportion of heme groups bound to oxygen as a function of the partial pressure of oxygen. The half-saturation point, p₅₀, is the partial pressure at which half of the sites are occupied. The cooperativity n quantifies the extent to which a change in the partial pressure of oxygen affects the level of saturation. It is schematically shown here although it is actually defined as the slope in the Hill plot [log(Y/(1 − Y)) versus log(pO2)]. (b) The MWC model. The hemoglobin tetramer is assumed to be in one of two symmetric conformations: a state T with low affinity (K_T) or a state R with high affinity (K_R). In each conformation there are five states subscripted by the number of oxygens bound (0–4). The equilibrium constant between the fully deoxygenated states is L₀ (≫ 1) and between the fully oxygenated states is L₄ (≪ 1). At low oxygen levels the molecule is in the T state. At high levels of oxygen, the equilibrium shifts toward the R state as binding of oxygen is increased. L_T0R4 is the equilibrium constant under standard conditions between states T₀ and R₄. (c) Energy diagram for the MWC model. The physical meaning of the equilibrium constants L and the affinities K can be understood from this plot depicting the energy levels under standard conditions. For a detailed discussion see SI Text. (d) Measured saturation curves and the MWC fits for several organisms (squares) and several physiological conditions (circles). For depiction in Hill space see SI Fig. 6.

Fig. 2.

Phenotypic parameters for human hemoglobin under varying physiological conditions (a) and for different mammals (b). The parameters are based on fits to data measured by various groups. Different colors denote different sources of information (see details in SI Tables 1 and 2). Note that p₅₀ in units of mmHg is given in log scale.

Fig. 3.

Relationship of microscopic parameters to phenotypic saturation properties. (a) Sensitivity of the saturation curve to different parameter changes. Normal human saturation curve (blue) versus 2-fold increase (red) or decrease (green) in the value of K_R while keeping L₄ and K_T constant (i); K_T (equivalently l_T0R4) while keeping L₄ and K_R constant (ii); and l₄ while keeping K_R and L_T0R4 constant (iii). We use the notation l_T0R4 = LT0R₄^1/4 and l₄ = L₄^1/4 as explained in SI Text. (b) The cooperativity n depends strongly on L₄. Parameters based on nonlinear least-squares curve fitting are shown for different organisms. The gray dotted line shows the theoretical relationship given in the text and is derived in SI Text. (c) The half-saturation pressure, p₅₀, depends strongly on L_T0R4. Values of the parameters for different organisms are shown. The thick dotted line shows the first-order theoretical relationship given in the text; the thin dotted line shows the second-order approximation. For full derivations, see SI Text. Mammals' index legends are as in Fig. 2b pO2 and pO5 are in units of mmHg.

Fig. 4.

Variation in microscopic parameters in evolution and physiology. (a and b) Microscopic parameters for human hemoglobin under varying physiological conditions (a) and for different mammals (b). Parameters are extracted from fits to data measured by various groups (different colors denote different sources of information, see details in SI Tables 1 and 2). (c) The cooperativity n changes more through evolutionary adaptations than through physiological adaptations. In contrast, p₅₀ changes more in physiological adaptations than in evolutionary adaptations. The trend observed for phenotypic parameters is also evident in microscopic parameters. L₄ changes more in evolutionary adaptations than by physiological adaptations. In contrast, L_T0R4 changes more in physiological adaptations than by evolutionary adaptations. Bar heights are proportional to the SD in the parameters' evolutionary and physiological ranges.

Fig. 5.

Schematic of the Baldwin effect and its possible implementations. (a) The fitness of an organism, when adapted to environment e₁, is plotted as a function of the prevailing environmental conditions. Physiological adaptation (red), also referred to as somatic adaptation, increases the inherent (blue) range of fitness of the organism. On a change from condition e₁ to e₂, instead of extinguishing all organisms (assuming mutations do not yet exist), physiological adaptation allows survival. (b) After evolutionary adaptation to environment e₂ the maximal fitness is centered at the prevailing condition. If evolutionary adaptation occurred by genetic assimilation of the microscopic physiological response (black), the range of further physiological adaptations would be compromised. In contrast, if the evolutionary adaptation was achieved via an independent parameter, survival by physiological adaptation would still be possible under further changing conditions (green). (c) The physiological adaptation is assumed to have a limited biochemical dynamic range. Evolutionary adaptation by changing the original value of p₁ to p₂ (black line) compromises the ability to further increase this parameter in the future to the same extent as before. An adaptation using an orthogonal axis (p2′; green line) preserves the full dynamic range for physiological adaptations.