Due to the near transparency of cells, fluorescence microscopy
is one of the best techniques available to study the dynamics of
cellular components in living cells. However, the direct observation of dynamic
interactions between cellular components that are present at high density
or are highly clustered has been elusive due to the fact that
the resolution of the light microscope is ~ 250 nm, whereas interactions typically occur at the ~ 10 nm scale.
The primary goal of my research is to develop new optical techniques that are able to
probe cellular dynamics at the 10 nm scale and to apply these techniques to specific biological
and biophysical questions.
Projects
Fluorescence Intermittency Based Localization Microscopy
Fluorophores distributed with inter-particle spacing less than 250 nm become difficult to resolve due to the overlap of their observed intensity patterns. However, the positions of single emitters that are spatially well separated from other emitters can be found with an accuracy better than 10 nm by fitting the observed intensity with the known diffraction pattern using the center coordinates as fit parameters. New approaches have made use of emitter temporal fluctuations in order to identify individual emitters within a cluster, leading to more accurate localization of each emitter. Methods, such as that we are developing, that rely on emitter intensity fluctuations, and do not require the occurrence of isolated single emitters in a fluorescent state, have the potential of capturing dynamic processes.
 Paul Harrington |
Ph. D. student Paul Harrington has been awarded an NSF IGERT fellowship for the project "Fluorescence Nanoscopy using Quantum Dot Fluorescence Intermittency for the Study of Dynamic Membrane Protein Clusters." He is developing new analysis techniques for localization microscopy and will apply these to the study of the EGF receptor (ErbB1) and the high affinity IgE receptor FceRI.
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GPU Based Image Analysis
High-resolution, fluorescence microscopy based studies of cellular dynamics can genenate single data sets approaching 1GB in size. As is the case with our localization microscopy studies, quantitative analysis can require modeling of the physical system under study and must include the effects of the microscope optical transfer function and the photon shot noise inherent in fluorescence. This computationally intensive task can be performed on modern Graphics Processing Units (GPUs), which have more than ten times the floating point performance of modern CPUs. This project has developed into a collaboration with the image processing group at TU Delft to build a publicly available library of GPU based image processing functions as well as integration into DIPlib.
 Jonas Anderson |
Ph. D. student Jonas Anderson is the developer of our GPU based image processing library, which is written using NVIDIA's CUDA platform. He has also implemented speed optimizations to our single particle tracking codes. |