# Shiga Toxin--A Model for Glycolipid-Dependent and Lectin-Driven Endocytosis
## 2 Receptor Binding and Toxin Clustering  
The receptor-binding B-subunit of Shiga toxin (STxB) is a homopentameric protein of 35 kDa. Each STxB pentamer displays a total of 15 Gb3 binding sites [4], and each of these binding sites has only millimolar affinity for the globotriose sugar moiety of Gb3 (reviewed in Reference [5]). Yet, Shiga toxin binds avidly and strongly to cells. This apparent high affinity is the result of multiple bond interactions, one STxB pentamer being in contact with several Gb3 molecules at a time. To release STxB from the membrane, all of these interactions have to be dissociated at the same time, which is statistically unlikely. Such avidity effect is a general hallmark of lectins. For example, the homopentameric receptor-binding B-subunit of cholera toxin from _Vibrio cholerae_ has a relatively low binding pocket affinity in the micromolar range for its cellular receptor, the GSL GM1 (reviewed in References [5; 6]). Yet, much like Shiga toxin, cholera toxin also binds to cells with apparent nanomolar affinity, due to avidity interactions.  
The avidity binding effect would be favored if the GSLs that function as toxin receptors were themselves clustered, such that several receptor binding sites on toxin pentamers would be occupied straight away upon the initial contact with the plasma membrane of target cells. Using an advanced electron microscopy technique, nanoclustering has indeed been documented for the gangliosides GM1 and GM3 [7]. This resembles the situation described for another class of glycosylated lipids, the glycosylphosphatidylidylinositol (GPI)-anchored proteins, which were equally described to exist in membranes as nanoclusters of a few molecules [8].  
For Shiga toxin, no direct interaction between toxins has been detected. Yet, on model membranes [9] and on cells [10], Shiga toxin clusters readily, suggesting that a membrane-mediated mechanism drives toxin molecules together. A recent study has investigated this aspect in further detail. Based on theoretical modeling, computer simulations, and experiments in model membrane  
Figure 1: Intracellular trafficking of Shiga toxin. Reproduced from [1]. 2010, Nature Publishing Group.  
systems and on cells, an original hypothesis has been proposed [10] according to which Shiga toxin molecules would suppress thermally excited membrane fluctuations not only at sites at which they bind, but also on the membrane patch between 2 adjacent toxin molecules, as long as these are not further apart than roughly the size of the toxin itself (Figure 2).  
Unperturbed fluctuation of the membrane outside this toxin-delineated patch would push the toxin molecules together, even if these were not experiencing a direct attractive force. On theoretical grounds, such thermally induced membrane fluctuation forces (also termed thermal Casimir-like forces; References [11; 12]; for a review, see Reference [13]) are expected to be as strong as electrostatic or van der Waals interactions, as long as the membrane inclusions that generate them are several nanometers in size [10]. However, as opposed to electrostatic or van der Waals interactions that operate at subnanometric distances, membrane fluctuation forces would have an effective radius of several nanometers, which corresponds to a gap in the interaction landscape of biological membranes between cytoskeleton-driven clustering that operates at tens to hundreds of nanometers [14], and the conventional subnanometric interaction forces. Of note, while membrane fluctuation forces are expected to apply to any tightly membrane-associated protein (or nanoparticle), other interaction forces would of course continue to be present in biological systems. Thereby, initial contacts that could be favored by the fluctuation forces would need to be further stabilized by other interactions for the generation of biologically meaningful outputs, and to avoid that all proteins (or nanoparticles) that are submitted to fluctuation forces coalesce into one big aggregate.