分类： 生物学 >> 生物物理学 提交时间： 2016-05-11
Han, Renmin
Xu, Fan
Ren, Fei
Zhang, Fa
Han, Renmin
Xu, Fan
Ren, Fei
Zhang, Fa
Han, Renmin
Xu, Fan
Wang, Liansan
Zhang, Yongdeng
Zhang, Mingshu
Liu, Zhiyong
摘要： Background: The recent developments of far-field optical microscopy (single molecule imaging techniques) have overcome the diffraction barrier of light and improve image resolution by a factor of ten compared with conventional light microscopy. These techniques utilize the stochastic switching of probe molecules to overcome the diffraction limit and determine the precise localizations of molecules, which often requires a long image acquisition time. However, long acquisition times increase the risk of sample drift. In the case of high resolution microscopy, sample drift would decrease the image resolution. Results: In this paper, we propose a novel metric based on the distance between molecules to solve the drift correction. The proposed metric directly uses the position information of molecules to estimate the frame drift. We also designed an algorithm to implement the metric for the general application of drift correction. There are two advantages of our method: First, because our method does not require space binning of positions of molecules but directly operates on the positions, it is more natural for single molecule imaging techniques. Second, our method can estimate drift with a small number of positions in each temporal bin, which may extend its potential application. Conclusions: The effectiveness of our method has been demonstrated by both simulated data and experiments on single molecular images.
分类： 生物学 >> 生物物理学 >> 细胞生物学 提交时间： 2016-05-05
Shan, Hong
Yin, Chang-Cheng
Sun, Fei
Wang, Zihao
Zhang, Fa
Wang, Zihao
Zhang, Fa
Wang, Zihao
Sun, Fei
Xiong, Yong
Sun, Fei
摘要： Single particle analysis, which can be regarded as an average of signals from thousands or even millions of particle projections, is an efficient method to study the three-dimensional structures of biological macromolecules. An intrinsic assumption in single particle analysis is that all the analyzed particles must have identical composition and conformation. Thus specimen heterogeneity in either composition or conformation has raised great challenges for high-resolution analysis. For particles with multiple conformations, inaccurate alignments and orientation parameters will yield an averaged map with diminished resolution and smeared density. Besides extensive classification approaches, here based on the assumption that the macromolecular complex is made up of multiple rigid modules whose relative orientations and positions are in slight fluctuation around equilibriums, we propose a new method called as local optimization refinement to address this conformational heterogeneity for an improved resolution. The key idea is to optimize the orientation and shift parameters of each rigid module and then reconstruct their three-dimensional structures individually. Using simulated data of 80S/70S ribosomes with relative fluctuations between the large (60S/50S) and the small (40S/30S) subunits, we tested this algorithm and found that the resolutions of both subunits are significantly improved. Our method provides a proof-of-principle solution for high-resolution single particle analysis of macromolecular complexes with dynamic conformations.
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