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Copyright © 2005 The Biophysical Society. All rights reserved.
Biophysical Journal, Volume 89, Issue 5, L40-L42, 1 November 2005

doi:10.1529/biophysj.105.071688

Biophysical Letters

Weak Effect of Membrane Diffusion on the Rate of Receptor Accumulation at Adhesive Contacts

Olivier Thoumine^*, ,  , Edouard Saint-Michel^*, Caroline Dequidt^*, Julien Falk^†, Rachel Rudge^‡, Thierry Galli^‡, Catherine Faivre-Sarrailh^† and Daniel Choquet^*

^* CNRS 5091, Université Bordeaux 2, Bordeaux, France
^† CNRS 6184-NICN, Faculté de Médecine Nord, Marseille, France
^‡ Equipe Avenir, UMR 7592, Institut Jacques Monod, Université Paris VI, Paris, France

Address reprint requests and inquiries to O. Thoumine, Tel: 33-5-57-5740-91.

The formation of adhesive contacts between cells is fundamental in biology. It involves specific adhesion proteins, e.g., IgCAMs, which are implicated in neurite elongation and growth cone guidance 1. Contacts are initiated when adhesion molecules find counterreceptors on the surface of neighboring cells and make selective protein-protein bonds. Such interactions depend on the abundance of receptors expressed by the cells, but also on the ability of receptors to diffuse in the cell membrane 2. The regulation of receptor mobility by cytoplasmic partners, e.g., between L1/neurofascin and ankyrin 3,4, may then tune the rate at which adhesions form.

To assess if diffusion could affect the kinetics of receptor recruitment at adhesive sites, we used constructs of varying length (25–180kD), all tagged extracellularly with green fluorescent protein (GFP). These include L1-GFP, several truncated forms of neuronal-related cell adhesion molecule (NrCAM)-GFP 5, and glycosylphosphatidylinositol (GPI)-GFP (Figure 1F). We reasoned that size differences should result in contrasting lateral mobilities. To measure the diffusion coefficient of these receptors, we transfected primary culture neurons and labeled individual receptors with quantum dots (QD). Active growth cones were selected for the recordings (Figure 1A), since these structures are implicated in IgCAM-based locomotion and cell recognition; ∼40% of the receptors were expressed at the plasma membrane (Table 1), allowing QD to bind specifically to transfected cells (Figure 1B). QD attached to the cell surface and moved in two dimensions, exploring the entire growth cone surface (Figure 1C). QD showed a variety of behaviors, some moving fast, others staying almost immobile. We tracked individual QD and calculated an instantaneous diffusion coefficient for each trajectory.

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Figure 1

Lateral mobility of GFP tagged receptors. Growth cone expressing NrCAM-GFP (A), labeled with anti-GFP conjugated QD (B). (C) Image of the maximum intensity from the QD channel detected for each pixel along a 1min sequence, representing the global area explored by QD. Arrows indicate immobile QD. (D) Distributions of the diffusion coefficients for NrCAM-GFP and GPI-GFP. (E) Diagram of the various receptors. In all NrCAM constructs, the fibronectin type III domains have been replaced by GFP: ΔCter is deleted of the ankyrin binding motif, and downstream, ΔCyto of the entire cytoplasmic tail, ΔIg of the immunoglobulin domains, and ΔIgΔCyto of both extracellular and intracellular regions. (F) Average diffusion coefficient versus the molecular weight of each construct. The straight line is a linear fit (r=0.88). Bar=5μm.

We thereby obtained a distribution of diffusion coefficients for each construct (Figure 1DE) in the range of 0.1–1μm²/s 6. As receptor size diminishes, the distribution shifts to higher mobility values, resulting in a clear inverse relationship between the molecular weight of the receptor and its average diffusion coefficient (Figure 1G). Since these receptors interact similarly with lipid microdomains 5, differences in mobility are unlikely to be associated with variations in the lipid environment. Truncations of intracellular regions caused a slight decrease in lateral mobility 7, which may be attributed to trapping of L1 or NrCAM cytoplasmic tail within the membrane scaffold, or to specific interactions with cytoskeletal partners such as ankyrin or SAP102 3,4. Deletions of extracellular regions (fibronectin type III, immunoglobin (Ig), or both) strongly reduced receptor diffusion 8. This may be due to steric effects linked to the high glycosylation levels of L1 and NrCAM ectodomains. Alternatively, IgCAMs with intact fibronectin type III and/or Ig domains are able to interact in cis with themselves or other receptors 1, thus forming complexes with lower diffusion properties.

We then mimicked adhesive contacts using anti-GFP-coated latex microspheres, which selectively bound to transfected cells (Figure 2AB; Table 1) and recruited GFP-tagged membrane receptors (Figure 2CD). We placed microspheres on growth cones using optical tweezers, and followed the accumulation of receptors around them (Figure 2E). We quantified the ratio between the fluorescence level on the microsphere and that on adjacent regions. This enrichment factor increased in a few minutes, slightly faster for smaller receptors (Figure 2F), and reached a plateau around 3 with minor differences between the constructs (Table 1). That equilibrium value corresponded to the saturation of antibody binding sites on microspheres by GFP-tagged receptors.

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Figure 2

Kinetics of GFP-tagged receptor trapping. (A–D) Neurons transfected for NrCAM-GFP were incubated for 1h with 4μm anti-GFP-coated microspheres. (A) Differential interference contrast image; (B) GFP channel. Arrowheads indicate bound beads that have recruited NrCAM-GFP. (C and D) Higher magnification views showing the recruitment of NrCAM-GFP (C), and a corresponding surface immunostaining, using an antibody to the hemagglutinin tag located at the N-terminus of NrCAM-GFP (D). (E) Time sequence of NrCAM-GFP accumulation around a microsphere placed on a growth cone for 10s at time zero. (F) Individual data showing the enrichment factor versus time for NrCAM-GFP and NrCAMΔIgΔCyto-GFP (mean±SE). The plain curves represent fits with Eq. 1. (G) Rate constant k_onR versus the diffusion coefficient for all receptors (n=8–12 experiments for each construct). Bars=5μm.

We modeled the receptor recruitment data using first-order kinetics: dC/dt=k_on(R-C)(L-C)-k_offC, where R is the receptor density at the cell surface (≈1000/μm²), L the density of GFP binding sites on microspheres (≈4000/μm²), C the surface density of bonds between antibodies and receptors, and k_on and k_off the forward and reverse rate constants, respectively. Fluorescence measurements outside bead contacts indicated that there was no receptor depletion, so we took (R-C)=R. Furthermore, antibody-antigen bonds being very stable, we set k_off=0. This left Eq. 1: C(t)=L[1-exp(−k_onRt)], which was used to fit the data and gave the two parameters R/L (Table 1) and k_onR.

The association rate k_onR increased weakly with the receptor diffusion coefficient (Figure 2C), showing that receptor accumulation at microsphere contacts is not diffusion-limited. This agreed with a theoretical model taking into account the long-range diffusion of receptors toward a narrow zone where they can be irreversibly trapped by immobilized ligands 9. Beads coated with lower affinity ligands such as monoclonal antibodies against GFP (not shown), transient adhesion glycoprotein 1 5, or N-cadherin 10 all induced slower accumulation of counterreceptors, suggesting that the adhesive reaction is the limiting step there. Thus, there appears to be a large enough reservoir of highly diffusive IgCAMs that can be mobilized quickly at adhesive sites, waiting for ligand binding. It is still possible that subtle differences in the diffusion of less mobile receptor complexes, controlled locally by the cytoskeleton or the lipid environment, can modulate the initiation and durability of neuronal interactions.