Superresolution microscope image reconstruction by spatiotemporal object decomposition and association: application in resolving t-tubule structure in skeletal muscle

Mingzhai Sun,Matthew Sermersheim,Kristyn Gumpper,Gejing De,Pei-Hui Lin,Jianjie Ma,Filiz Bunyak,Jiaqing Huang,George Liu,Kannappan Palaniappan

doi:10.1364/oe.22.012160

Abstract

One key factor that limits resolution of single-molecule superresolution microscopy relates to the localization accuracy of the activated emitters, which is usually deteriorated by two factors. One originates from the background noise due to out-of-focus signals, sample auto-fluorescence, and camera acquisition noise; and the other is due to the low photon count of emitters at a single frame. With fast acquisition rate, the activated emitters can last multiple frames before they transiently switch off or permanently bleach. Effectively incorporating the temporal information of these emitters is critical to improve the spatial resolution. However, majority of the existing reconstruction algorithms locate the emitters frame by frame, discarding or underusing the temporal information. Here we present a new image reconstruction algorithm based on tracklets, short trajectories of the same objects. We improve the localization accuracy by associating the same emitters from multiple frames to form tracklets and by aggregating signals to enhance the signal to noise ratio. We also introduce a weighted mean-shift algorithm (WMS) to automatically detect the number of modes (emitters) in overlapping regions of tracklets so that not only well-separated single emitters but also individual emitters within multi-emitter groups can be identified and tracked. In combination with a maximum likelihood estimator method (MLE), we are able to resolve low to medium density of overlapping emitters with improved localization accuracy. We evaluate the performance of our method with both synthetic and experimental data, and show that the tracklet-based reconstruction is superior in localization accuracy, particularly for weak signals embedded in a strong background. Using this method, for the first time, we resolve the transverse tubule structure of the mammalian skeletal muscle.

Highlights

The spatial resolution of conventional fluorescence microscopy is limited by the Abbe diffraction limit to λ / 2NA, where λ is the wavelength of the emission light and NA is the numerical aperture of the objective [1,2,3,4,5]
Stochastic optical reconstruction microscopy (STORM) [10], direct STORM [11, 12], photo-activated localization microscopy (PALM) [13], and fluorescence photoactivation localization microscopy [14] all belong to this category, and hold superior capability achieving a typical lateral resolution of ~20 nm [15,16,17]
One of the difficulties caused by combining multiple frames is that temporally separated emitters may overlap

Summary

Introduction

The spatial resolution of conventional fluorescence microscopy is limited by the Abbe diffraction limit to λ / 2NA , where λ is the wavelength of the emission light and NA is the numerical aperture of the objective [1,2,3,4,5]. In single molecule localization microscopy, a random subset of fluorophores (emitters) are activated, imaged, and localized to nanometer resolution. This procedure is repeated to allow different subsets of emitters to be switched on and localized. To achieve a superresolution image with resolution of 20 to 50-nm, the image acquisition can take tens of thousands of frames, requiring lengthy acquisition time. This greatly limits the application of superresolution techniques from the fast dynamics process

Methods

Results

Conclusion