The translational and rotational dynamics of anisotropic
optical
nanoprobes revealed in single particle tracking (SPT) experiments
offer molecular-level information about cellular activities. Here,
we report an automated high-speed multidimensional SPT system integrated
with a deep learning algorithm for tracking the 3D orientation of
anisotropic gold nanoparticle probes in living cells with high localization
precision (<10 nm) and temporal resolution (0.9 ms), overcoming
the limitations of rotational tracking under low signal-to-noise ratio
(S/N) conditions. This method can resolve the azimuth (0°–360°)
and polar angles (0°–90°) with errors of less than
2° on the experimental and simulated data under S/N of ∼4.
Even when the S/N approaches the limit of 1, this method still maintains
better robustness and noise resistance than the conventional pattern
matching methods. The usefulness of this multidimensional SPT system
has been demonstrated with a study of the motions of cargos transported
along the microtubules within living cells.