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. 2015:2015:610482.
doi: 10.1155/2015/610482. Epub 2015 May 19.

Automatically Identifying Fusion Events between GLUT4 Storage Vesicles and the Plasma Membrane in TIRF Microscopy Image Sequences

Affiliations

Automatically Identifying Fusion Events between GLUT4 Storage Vesicles and the Plasma Membrane in TIRF Microscopy Image Sequences

Jian Wu et al. Comput Math Methods Med. 2015.

Abstract

Quantitative analysis of the dynamic behavior about membrane-bound secretory vesicles has proven to be important in biological research. This paper proposes a novel approach to automatically identify the elusive fusion events between VAMP2-pHluorin labeled GLUT4 storage vesicles (GSVs) and the plasma membrane. The differentiation is implemented to detect the initiation of fusion events by modified forward subtraction of consecutive frames in the TIRFM image sequence. Spatially connected pixels in difference images brighter than a specified adaptive threshold are grouped into a distinct fusion spot. The vesicles are located at the intensity-weighted centroid of their fusion spots. To reveal the true in vivo nature of a fusion event, 2D Gaussian fitting for the fusion spot is used to derive the intensity-weighted centroid and the spot size during the fusion process. The fusion event and its termination can be determined according to the change of spot size. The method is evaluated on real experiment data with ground truth annotated by expert cell biologists. The evaluation results show that it can achieve relatively high accuracy comparing favorably to the manual analysis, yet at a small fraction of time.

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Figures

Figure 1
Figure 1
Consecutive time frames from 11 to 30 (b) show that a prominent fusion event corresponds to the patch of interest in a TIRFM image sequence (a). ∗ indicates the fusion pore opening, that is, the initiation of a fusion event. ∗∗ indicates the initiation of a diffusion process. Here, transition time is 1.6 s (8 frames, sampling rate is 5 frames/s).
Figure 2
Figure 2
The process of detecting a fusion candidate vesicle. (a) A patch of image with a fusion candidate vesicle in. (b) The absolute differentiation of consecutive images results in a noisy difference image, from which the vesicle is hard to detect. (c) The forward moving average differentiation can achieve a high SNR difference image. (d) A vesicle spot mask derived from (c) with the MAD threshold, which can be used to calculate the intensity-weighted centroid (a red cross).
Figure 3
Figure 3
Four typical identification results compare to ground truth. Relationship between the variety of total instensity, intnesity at weighted centroid, and spot radius during vesicle movement. The integral average radius is also calculated (red dashed line) as a threshold for identifing diffusion initiation (>1.2 times, black asterisk) and fusion event (>2 times). (c) A nonfusion at the edge of cell is mistakenly identified as a fusion event, mainly due to unsymmetrical background. All values are normalized to the initiation of fusion pore opening.

References

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