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Single molecule fluorescence spectroscopy has been largely implemented using methods which require tethering of molecules to a substrate in order to make high temporal resolution measurements. However, the act of tethering a molecule requires that the molecule be removed from its environment. This is especially perturbative when measuring biomolecules such as enzymes, which may rely on the non-equilibrium and crowded cellular environment for normal function. A method which may be able to un-tether single molecule fluorescence spectroscopy is real-time 3D single particle tracking (RT-3D-SPT). RT-3D-SPT uses active feedback to effectively lock-on to freely diffusing particles so they can be measured continuously with up to photon-limited temporal resolution over large axial ranges. This review gives an overview of the various active feedback 3D single particle tracking methods, highlighting specialized detection and excitation schemes which enable high-speed real-time tracking. Furthermore, the combination of these active feedback methods with simultaneous live-cell imaging is discussed. Finally, the successes in real-time 3D single molecule tracking (RT-3D-SMT) thus far and the roadmap going forward for this promising family of techniques are discussed.
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Combined online Bayesian and windowed estimation of background and signal localization facilitates active-feedback particle tracking in complex environments
Despite successes in tracking single molecules in vitro, the extension of active-feedback single-particle methods to tracking rapidly diffusing and unconfined proteins in live cells has not been realized. Since the existing active-feedback localization methods localize particles in real time assuming zero background, they are ill-suited to track in the inhomogeneous background environment of a live cell. Here, we develop a windowed estimation of signal and background levels using recent data to estimate the current particle brightness and background intensity. These estimates facilitate recursive Bayesian position estimation, improving upon current Kalman-based localization methods. Combined, online Bayesian and windowed estimation of background and signal (COBWEBS) surpasses existing 2D localization methods. Simulations demonstrate improved localization accuracy and responsivity in a homogeneous background for selected particle and background intensity combinations. Improved or similar performance of COBWEBS tracking extends to the majority of signal and background combinations explored. Furthermore, improved tracking durations are demonstrated in the presence of heterogeneous backgrounds for multiple particle intensities, diffusive speeds, and background patterns. COBWEBS can accurately track particles in the presence of high and nonuniform backgrounds, including intensity changes of up to three times the particle’s intensity, making it a prime candidate for advancing active-feedback single fluorophore tracking to the cellular interior.
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- Award ID(s):
- 1847899
- PAR ID:
- 10379689
- Publisher / Repository:
- American Institute of Physics
- Date Published:
- Journal Name:
- The Journal of Chemical Physics
- Volume:
- 157
- Issue:
- 18
- ISSN:
- 0021-9606
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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