Cargo binding promotes KDEL receptor clustering at the mammalian cell surface

Abstract

Transmembrane receptor clustering is a ubiquitous phenomenon in pro- and eukaryotic cells to physically sense receptor/ligand interactions and subsequently translate an exogenous signal into a cellular response. Despite that receptor cluster formation has been described for a wide variety of receptors, ranging from chemotactic receptors in bacteria to growth factor and neurotransmitter receptors in mammalian cells, a mechanistic understanding of the underlying molecular processes is still puzzling. In an attempt to fill this gap we followed a combined experimental and theoretical approach by dissecting and modulating cargo binding, internalization and cellular response mediated by KDEL receptors (KDELRs) at the mammalian cell surface after interaction with a model cargo/ligand. Using a fluorescent variant of ricin toxin A chain as KDELR-ligand (eGFP-RTA(H/KDEL)), we demonstrate that cargo binding induces dose-dependent receptor cluster formation at and subsequent internalization from the membrane which is associated and counteracted by anterograde and microtubule-assisted receptor transport to preferred docking sites at the plasma membrane. By means of analytical arguments and extensive numerical simulations we show that cargo-synchronized receptor transport from and to the membrane is causative for KDELR/cargo cluster formation at the mammalian cell surface.

Figure 1. H/KDEL-cargo binding to the mammalian cell surface induces receptor cluster formation.

(A) (top) Schematic outline of the fluorescent model cargo eGFP-RTA^HDEL consisting of the cytotoxic A-subunit of ricin (RTA), mammalian enhanced GFP (eGFP) and a C-terminal (His)₆-Tag for purification. (bottom) eGFP-RTA lacking a KDELR binding motif served as negative control. (B) Cell surface biotinylation of mammalian KDELR1. HeLa cells were transiently transfected with KDELR1 (Erd2.1-V5 (+)) or an empty vector (−) and cultivated for 48 h. Cell surface proteins were biotinylated by treatment with (+) or without (−) Sulfo-NHS-SS-Biotin and purified with streptavidin beads. Whole cell lysates (input) served as control to determine the total amount of Erd2.1-V5 (detected with anti-V5), while β-actin and Na+/K+ ATPase served as cytosolic and plasma membrane marker proteins, respectively. Membrane fraction (surface) illustrates the total fraction of proteins at the cell surface. (C) (bottom) Schematic outline of α-bungarotoxin (Btx) cell surface binding. HeLa cells expressing a KDELR variant in which a Btx binding site (BBS) was inserted between positions T114 and P115 of c-myc-tagged KDELR1 (Erd2.1) were treated with Alexa488-labeled α-Btx. As Btx is incapable to cross the mammalian PM, any physical interaction between Btx and BBS can only occur if KDELR1 is present in the PM. (top) Confocal laser scanning microscopy of HeLa cells transfected with pERD2.1-BBS-cmyc or an empty vector control and treated with 10 μg/ml Alexa488-labeled α-Btx. (D) In vivo toxicity of eGFP-RTA^H/KDEL against HeLa cells. Cell viability (N = 3, n = 5 replicates) was determined after 48 h in the presence or absence of 160 μg/ml of the indicated RTA variant (Mock, PBS buffer). Mean values and standard deviations are displayed (***P < 0.001, t test). (E) Fluorescence microscopy of cargo binding at the cell surface. HeLa cells were treated with 160 μg/ml eGFP-RTA^H/KDEL or eGFP-RTA for 5 min and cargo binding was analyzed after 10 washing steps. (F) Live cell imaging (45 frames/h) of HeLa cells treated with 160 μg/ml eGFP-RTA^HDEL. Three representative time points (0, 30, 60 min) are shown. (G) Temporal evolution of the density of cargo signals at the surface of HeLa cells. The accumulation of fluorescent signals is shown after treatment with 160 μg/ml eGFP-RTA^HDEL or eGFP-RTA. The symbols represent the optimal signal-to-noise ratio in image analysis. The error bars reflect the variation range of signal intensity for different threshold values of image analysis parameters. The functional form only weakly depends on the choice of the threshold values.

Figure 2

(A) Schematic representation of (left) the minimal model of receptor cycle between the PM and endosomes, and (right) the simulation method. An example of a randomly chosen area for endocytosis (vesicle arrival) is marked in red (blue). Possible scenarios for the evolution of the surface receptor population during the next simulation step are shown. (B) Time evolution of the density of accumulated cargo at the cell surface. A comparison is made between experimental data, simulation results (a single realization), and the analytical expressions Eqs 2 and 3. The dotted line indicates the analytical prediction via Eq. 2 for α_gain = α_loss = 1.3 × 10⁻⁴ s⁻¹. The starting time of simulations and analytical expression 2 is shifted to take into account the initial inactive regime in experiments.

Figure 3. KDELR/cargo clustering is dose- and temperature-dependent.

(A) Changes in cargo accumulation of eGFP-RTA^HDEL at the surface of HeLa cells cultivated at 25 °C or 37 °C. The 3-fold reduced activity in simulations (left) represents the known effect of temperature on intracellular transport processes (e.g. endocytosis and exocytosis). (right) The experimental results at 25 °C and 37 °C. (B) Effect of changing the concentration of the model cargo eGFP-RTA^HDEL on KDELR/cargo clustering at the plasma membrane. The indicated rates in simulations (left) were adopted to obtain the best fits to the experimental data (right).

Figure 4. Preferential arrival sites of KDELRs at the plasma membrane.

(A) The log-log plots of cluster-size distribution P(s) of eGFP-RTA^HDEL (160 μg/ml) treated HeLa cells at the indicated time points. The dashed line corresponds to the best power-law fit P(s) ~ s^−β with . (B) Evolution of the receptor clusters at the plasma membrane. A randomly chosen region of the cell surface is shown at different time points (see Suppl. Info. for the detailed description of the methodology of distinguishing the clusters and obtaining the cluster-size distribution). (C) A comparison of the resulting P(s) from different receptor dynamic scenarios in simulations. The solid, dashed, and dotted lines denote the shape of P(s) at t = 120 min for randomly distributed immobile receptors, aggregation process including lateral diffusion of receptors and nearest-neighbor attraction between them, and preferential attachment process, respectively. (D) The frequency of vesicle arrival at a sample cell periphery over a time window of 500 s. (E) In vivo dynamics of mCherry-ERD2.1. The transfected HeLa cells with mCherry-ERD2.1 were analyzed by CLSM (720 frames/h). The illustrated heat map represents the accumulated fluorescent signals of successive frames. The regions with high traffic load, e.g. around Golgi, are eliminated to provide a more clear color distinction near the cell surface. (F) The frequency of vesicle transport near the plasma membrane of untreated or eGFP-RTA^HDEL treated cells. The data is averaged over bins of size 10 μm (**P ≤ 0.01, t test).

Figure 5. Microtubule-assisted KDELR transport is required for cargo clustering at the cell surface.

(A) Tracking of single KDELR clusters (red) moving along the microtubule network (green). A sequence of five successive live cell imaging pictures (720 frames/h) of HeLa cells expressing mCherry-tagged Erd2.1 and GFP-tagged β-tubulin is shown. The arrows indicate an example of tubulin/KDELR signal co-localization. (B) Co-localization of GFP-tubulin and mCherry-Erd2.1. The ratio of correlated tubulin and KDELR pixels of the live cell imaging experiment is shown during 150 s. (C) KDELR/cargo cluster formation in colchicine (red) and phalloidin (inset) pre-treated cells (2.5 μM colchicine, 60 min or 10 μM phalloidin, 90 min) after incubation with 160 μg/ml eGFP-RTA^HDEL. Temporal evolution of the accumulated KDELR/cargo is compared with the untreated control cells. The inset shows a comparison between untreated (solid line) and phalloidin-treated HeLa cells (dashed line).