Limitations of Qdot labelling compared to directly-conjugated probes for single particle tracking of B cell receptor mobility

Abstract

Single-particle tracking (SPT) is a powerful method for exploring single-molecule dynamics in living cells with nanoscale spatiotemporal resolution. Photostability and bright fluorescence make quantum dots (Qdots) a popular choice for SPT. However, their large size could potentially alter the mobility of the molecule of interest. To test this, we labelled B cell receptors on the surface of B-lymphocytes with monovalent Fab fragments of antibodies that were either linked to Qdots via streptavidin or directly conjugated to the small organic fluorophore Cy3. Imaging of receptor mobility by total internal reflection fluorescence microscopy (TIRFM), followed by quantitative single-molecule diffusion and confinement analysis, definitively showed that Qdots sterically hinder lateral mobility regardless of the substrate to which the cells were adhered. Qdot labelling also drastically altered the frequency with which receptors transitioned between apparent slow- and fast-moving states and reduced the size of apparent confinement zones. Although we show that Qdot-labelled probes can detect large differences in receptor mobility, they fail to resolve subtle differences in lateral diffusion that are readily detectable using Cy3-labelled Fabs. Our findings highlight the utility and limitations of using Qdots for TIRFM and wide-field-based SPT, and have significant implications for interpreting SPT data.

Diffusion analysis of single particle trajectories in a Bayesian nonparametrics framework

“…The spatial precision of particle localization was estimated to be 23nm and 30nm for Qdot and Cy3 labelling, respectively. Full methods are reported in our original paper [28].…”

“…We examine six datasets, each from a separate experiment. Three experimental datasets used directly-conjugated Cy3-labelling of IgG and three used Qdot-labelling of IgG [28]. For the Cy3 experiments, the datasets contained 1886, 1768 and 1733 tracks, respectively, with average numbers of frames per track of 58 (standard deviation 77).…”

“…For the Qdot experiments, the datasets contained 2394, 4468 and 1526 tracks, respectively, with average numbers of frames per track of 83 (standard deviation 94). Before applying our iHMMSPT algorithm, we first applied an immobilility threshold to remove immobile tracks, as previously described [28]. We allow the algorithm to complete 10000 iterations in total, with a burn-in phase of 3000 iterations.…”

“…We show validation using simulated data and provide a technical improvement to the algorithm that assists with convergence for the problem at hand. Finally, we apply our method to real data from experiments using TIRF microscopy to visualize motion of surface receptors on the membrane of live B cells [28] and discuss biological implications and possible future directions for study.…”

3D neural network-based particle tracking reveals spatial heterogeneity of the cytosol

“…Applications of particle tracking to measure cytosolic properties in a living cell have been limited due to challenges in creating ideal probes, rapid 3D imaging, and tracking. Live-cell single particle tracking has previously been applied to track receptors in cell membranes (13,14). In contrast, we seek to spatially resolve cytosolic properties within whole cell volumes, which requires 3D multiple-particle tracking of inert, genetically expressed probes of known size.…”