77 / 155
Single-Cell Biophysics: Measurement, Modulation, and Modeling
Poster Abstracts
72
55-POS
Board 28
Analysis of Single Particle Tracking Data under Heterogeneous Conditions
Martin Lindén
1
, Vladimir Curic
1,2
, Elias Amselem
1
, Johan Elf
1
.
1
Uppsala University, Uppsala, Sweden,
2
IMINT Image Intelligence, Uppsala., Sweden.
Recent advances in single particle tracking (SPT) microscopy make it possible to obtain tens of
thousands of macromolecular trajectories from living cells in just a few minutes. Since molecules
typically change their movement properties upon interactions, these trajectories contain
information about locations and rates of intracellular reactions. Effectively extracting this
information is a statistical challenge, and an active research area. A particular difficulty is
heterogeneity in the data across and within nominally identical experiments. Unaccounted for,
such variations can induce analysis artifacts and present a serious hurdle for quantitative analysis
for large data sets. For example, the localization errors of single emitters may vary due to out-of-
focus motion, drift, motion blur, fluorophore intensity fluctuations, heterogeneous background,
or gradual photo-bleaching of the background or labeled molecule. To deal with such variations,
we have extended localization methods to estimate both position and localization uncertainty
from images of single emitters. We find that an uncertainty estimate based on the Bayesian
posterior density and constrained by simple microscope properties performs well in a wide range
of conditions relevant for live cell imaging. Furthermore, this additional information about
localization uncertainty can be incorporated into trajectory analysis methods to improve
diffusion constant estimates, detection of binding events, and the localization of single emitters.
Here, we will discuss ongoing progress in this area, including attempts to estimate the number of
diffusive states in multi-state SPT experiments.