Single-particle tracking (SPT) is widely used to study processes from membrane receptor organization to the dynamics of RNAs in living cells. While single-dye labeling strategies have the benefit of being minimally invasive, this comes at the expense of data quality; typically a data set of short trajectories is obtained and analyzed by means of the mean square displacements (MSD) or the distribution of the particles’ displacements in a set time interval (jump distance, JD). To evaluate the applicability of both approaches, a quantitative comparison of both methods under typically encountered experimental conditions is necessary. Here we use Monte Carlo simulations to systematically compare the accuracy of diffusion coefficients (D-values) obtained for three cases: one population of diffusing species, two populations with different D-values, and a population switching between two D-values. For the first case we find that the MSD gives more or equally accurate results than the JD analysis (relative errors of D-values <6%). If two diffusing species are present or a particle undergoes a motion change, the JD analysis successfully distinguishes both species (relative error <5%). Finally we apply the JD analysis to investigate the motion of endogenous LPS receptors in live macrophages before and after treatment with methyl-β-cyclodextrin and latrunculin B.

Bacterial outer membrane lipopolysaccharide (LPS) potently stimulates the mammalian innate immune system, and can lead to sepsis, the primary cause of death from infections. LPS is sensed by Toll-like receptor 4 (TLR4) in complex with its lipid-binding coreceptor MD-2, but subtle structural variations in LPS can profoundly modulate the response. To better understand the mechanism of LPS-induced stimulation and bacterial evasion, we have calculated the binding affinity to MD-2 of agonistic and antagonistic LPS variants including lipid A, lipid IVa, and synthetic antagonist Eritoran, and provide evidence that the coreceptor is a molecular switch that undergoes ligand-induced conformational changes to appropriately activate or inhibit the receptor complex. The plasticity of the coreceptor binding cavity is shown to be essential for distinguishing between ligands, whilst similar calculations for a model bacterial LPS bilayer reveal the “membrane-like” nature of the protein cavity. The ability to predict the activity of LPS variants should facilitate the rational design of TLR4 therapeutics.

DiC14-amidine is a cationic lipid that was originally designed as a lipid nanocarrier for nucleic acid transport, and turned out to be a Toll-like receptor 4 (TLR4) agonist as well. We found that while E. coli lipopolysaccharide (LPS) is a TLR4 agonist in all species, diC14-amidine nanoliposomes are full agonists for human, mouse and cat receptors but weak horse agonists. Taking advantage of this unusual species specificity, we used chimeric constructs based on the human and horse sequences and identified two regions in the human TLR4 that modulate the agonist activity of diC14-amidine. Interestingly, these regions lie outside the known LPS-binding domain. Competition experiments also support our hypothesis that diC14-amidine interacts primarily with TLR4 hydrophobic crevices located at the edges of the TLR4/TLR4* dimerization interface. We have characterized potential binding modes using molecular docking analysis and suggest that diC14-amidine nanoliposomes activate TLR4 by facilitating its dimerization in a process that is myeloid differentiation 2 (MD-2)-dependent and cluster of differentiation 14 (CD14)-independent. Our data suggest that TLR4 may be activated through binding at different anchoring points, expanding the repertoire of TLR4 ligands to non-MD-2-binding lipids.Electronic supplementary materialThe online version of this article (doi:10.1007/s00018-015-1915-1) contains supplementary material, which is available to authorized users.

TLR2 recognises bacterial lipopeptides and lipoteichoic acid, and forms heterodimers with TLR1 or TLR6. TLR2 is relatively well characterised in mice and humans, with published crystal structures of human TLR2/1/Pam3CSK4 and murine TLR2/6/Pam2CSK4. Equine TLR4 is activated by a different panel of ligands to human and murine TLR4, but less is known about species differences at TLR2. We therefore cloned equine TLR2, TLR1 and TLR6, which showed over 80% sequence identity with these receptors from other mammals, and performed a structure-function analysis. TLR2/1 and TLR2/6 from both horses and humans dose-dependently responded to lipoteichoic acid from Staphylococcus aureus, with no significant species difference in EC50 at either receptor pair. The EC50 of Pam2CSK4 was the same for equine and human TLR2/6, indicating amino acid differences between the two species' TLRs do not significantly affect ligand recognition. Species differences were seen between the responses to Pam2CSK4 and Pam3CSK4 at TLR2/1. Human TLR2/1, as expected, responded to Pam3CSK4 with greater potency and efficacy than Pam2CSK4. At equine TLR2/1, however, Pam3CSK4 was less potent than Pam2CSK4, with both ligands having similar efficacies. Molecular modelling indicates that the majority of non-conserved ligand-interacting residues are at the periphery of the TLR2 binding pocket and in the ligand peptide-interacting regions, which may cause subtle effects on ligand positioning. These results suggest that there are potentially important species differences in recognition of lipopeptides by TLR2/1, which may affect how the horse deals with bacterial infections.

The AIA is precise for measuring ACTH in horses. Although correlation between the instruments is good, the values obtained by the immunoassays cannot be used interchangeably and should be interpreted using reference intervals established for each analyzer to avoid false negatives. Diagnostic sensitivity and specificity of the AIA-360 should be evaluated before clinical use.