Single-particle tracking reports on the mobility of biomolecules in living cells with high spatial and temporal resolution. From single-particle trajectories, information such as the diffusion coefficient and diffusion state can be derived. Changes in particle dynamics within single trajectories can be extracted by segmentation, which provides information on transitions between different functional states of a biomolecule. However, such analyses of single-particle tracking data is complex and time-consuming. Here, we present a pipeline that enables a straightforward and rapid analysis of single-particle tracking data. It incorporates mean-squared displacement analysis of trajectories that distinguishes between immobile, confined, and free diffusion states, as well as the analysis of diffusion state transitions within a trajectory with transition counts and hidden Markov modeling. We apply this analysis to single-molecule trajectories of un-activated Fab-bound and internalin B-bound MET receptors in the plasma membrane of live HeLa cells. We found that ligand activated receptors move slower and more confined and exhibit more transitions from free to confined diffusion states than un-activated receptors. This suggests that the confined diffusion state functions as an intermediate between free and immobile, as this state is most likely changing the diffusion type in the following segment. Hidden Markov modeling reported three diffusion states with increased transition probabilities towards the less mobile and immobile states upon ligand activation. The less mobile state operates as an intermediate state, as it has the highest transition probabilities. The analysis pipeline can be readily applied to single-particle tracking data of other membrane proteins and provides rapid access to information that can be associated with functional states.
In the brain, the strength of each individual synapse is defined by the complement of proteins present or the “local proteome.” Activity-dependent changes in synaptic strength are the result of changes in this local proteome and posttranslational protein modifications. Although most synaptic proteins have been identified, we still know little about protein copy numbers in individual synapses and variations between synapses. We use DNA-point accumulation for imaging in nanoscale topography as a single-molecule super-resolution imaging technique to visualize and quantify protein copy numbers in single synapses. The imaging technique provides near-molecular spatial resolution, is unaffected by photobleaching, enables imaging of large field of views, and provides quantitative molecular information. We demonstrate these benefits by accessing copy numbers of surface AMPA-type receptors at single synapses of rat hippocampal neurons along dendritic segments.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.