Co-localization and confinement of ecto-nucleotidases modulate extracellular adenosine nucleotide distributions

Abstract

Nucleotides comprise small molecules that perform critical signaling roles in biological systems. Adenosine-based nucleotides, including adenosine tri-, di-, and mono-phosphate, are controlled through their rapid degradation by diphosphohydrolases and ecto-nucleotidases (NDAs). The interplay between nucleotide signaling and degradation is especially important in synapses formed between cells, which create signaling 'nanodomains'. Within these 'nanodomains', charged nucleotides interact with densely-packed membranes and biomolecules. While the contributions of electrostatic and steric interactions within such nanodomains are known to shape diffusion-limited reaction rates, less is understood about how these factors control the kinetics of nucleotidase activity. To quantify these factors, we utilized reaction-diffusion numerical simulations of 1) adenosine triphosphate (ATP) hydrolysis into adenosine monophosphate (AMP) and 2) AMP into adenosine (Ado) via two representative nucleotidases, CD39 and CD73. We evaluate these sequentially-coupled reactions in nanodomain geometries representative of extracellular synapses, within which we localize the nucleotidases. With this model, we find that 1) nucleotidase confinement reduces reaction rates relative to an open (bulk) system, 2) the rates of AMP and ADO formation are accelerated by restricting the diffusion of substrates away from the enzymes, and 3) nucleotidase co-localization and the presence of complementary (positive) charges to ATP enhance reaction rates, though the impact of these contributions on nucleotide pools depends on the degree to which the membrane competes for substrates. As a result, these contributions integratively control the relative concentrations and distributions of ATP and its metabolites within the junctional space. Altogether, our studies suggest that CD39 and CD73 nucleotidase activity within junctional spaces can exploit their confinement and favorable electrostatic interactions to finely control nucleotide signaling.

Fig 1. Systems studied in present work.

Left) Schematic of a synapse-like junctional space formed between adjacent cells. Nucleotidases confined within the junctional space hydrolyze adenosine triphosphate (ATP) into adenosine monophosphate (AMP) and adenosine (Ado) via CD39 and CD73, respectively. Right) The schematic is emulated with a model junction geometry, for which the reservoirs correspond to the extracellular environment surrounding the junctional space. The spatial and electrostatic configurations of the mock synaptic junction influence the reactivity of confined nucleotidases CD39 and CD73, which in turn control the local concentration of nucleotide signals.

Fig 2. Effects of confinement and proximity.

Predicted reaction rate coefficients for ATP to AMP at the CD39 enzyme, normalized to the analytical value from Eq 1. The bulk geometry is represented by a single CD39 enzyme in a junction of 16 nm radius with ATP = 1.0 mM on all boundaries (black). Results for different junction diameters are presented (in blue), including configurations where the enzyme is centered in the junction, or is adjacent to the junction wall.

Fig 3. Effects of nucleotidase confinement and co-localization on on adenosine (Ado) production rates.

Normalized reaction rate coefficient, k_prod,Ado, for CD73 with different junction sizes and CD39/CD73 proximities. ${\tilde{k}}_{prod,Ado}$ is normalized with respect to the maximal k_prod,Ado value, which is found under conditions of minimal enzyme separation distance and maximal junction radius. Red lines are for absorbing boundary conditions to emulate conditions where the membrane competes for the AMP intermediate. Blue lines are for reflective boundary conditions to represent membranes that are non-reactive to the substrate. The line thickness is proportional to the radius of the junction.

Fig 4. Effects of nucleotidase confinement and co-localization on Ado production efficiency.

Efficiency of reactivity of CD73 with respect to CD39 defined as k_eff ≡ k_prod,Ado/k_on,ATP. Left panel: co-localized enzymes. Right panel: enzymes separated by 8 nm.

Fig 5. ATP, AMP and Ado concentrations at midpoint between enzymes.

CD39 and CD73 are separated by a distance of 10.0 nm. In the uncharged cases, all surfaces are electrically neutral. In the charged cases, surface potentials are applied as described in Effects of surface charge on reaction rate coefficient. Bulk conditions (black and gray) are as described in Effects of molecular junction confinement on enzymatic activity. In non-reactive cases (blue) the junction surface reflects nucleotides, while in the reactive cases (red) the junction surface absorbs AMP. Cases are also shown (green) where the CD39 enzyme is inactive, resulting in no production of AMP or Ado.

Fig 6. Effects of junction membrane electrical potential on CD39 reactivity.

k_on,ATP is shown for various junction radii. Black curves represent cases where the junction membrane surface is electrically neutral. Blue curves represent cases where the junction membrane surface has an electric potential that attracts ATP. Red curves represent cases where the junction membrane surface has an electric potential that repels ATP. Φ_CD39 = 0, except where noted.

Fig 7. Effects of CD73 and membrane electric potential on CD73 reactivity.

z_ATP = -2, z_AMP = -1, z_Ado = 0 and Ω_CD39 > 0. Reaction rate coefficients for production of Ado as a function of distance between enzymes. The values are normalized to the k_prod,Ado value found for the minimal enzyme separation distance for each boundary condition under the neutral case. Left:reactive; right:Non-reactive to AMP.

Fig 8. Effect of Debye Length on reactivity of the sequential enzymes.

a)Reaction rate of CD39, k_on,ATP, as a function of Debye length parameter (κ) which is proportional to the square root of ionic strength. The circle shows simulation data and the solid lines are obtained by fitting to Eq 4. The subplot shows the linear relationship between ln(k_on) and (1 + aκ)⁻¹. Linear regression of Eq 4 yields the interaction strength U/RT and ln k_{on,I → ∞} (see Table 1). b)Production and effective reaction rates versus κ. The solid lines correspond to the left axis (k_prod,Ado) and the dashed to the right axis (k_eff).

Fig 9. Isometric sketch of model geometry.

Fig 10. Sketch of section through model geometry.

Top panel: identification of key model features. Middle panel: model boundary surfaces. Bottom panel: key dimensional parameters. For clarity, the sketches are not shown at scale.