Segmentation and 3D reconstruction of microtubules in total internal reflection fluorescence microscopy (TIRFM)
Stathis Hadjidemetriou1, Derek Toomre, James S Duncan
1Departments of Diagnostic Radiology and Biomedical Engineering, New Haven, CT 06520, USA. stathis@noodle.med.yale.edu
Abstract:
The interaction of the microtubules with the cell cortex plays numerous critical roles in a cell. For instance, it directs vesicle delivery, and modulates membrane adhesions pivotal for cell movement as well as mitosis. Abnormal function of the microtubules is involved in cancer. An effective method to observe microtubule function adjacent to the cortex is TIRFM. To date most analysis of TIRFM images has been done by visual inspection and manual tracing. In this work we have developed a method to automatically process TIRFM images of microtubules so as to enable high throughput quantitative studies. The microtubules are extracted in terms of consecutive segments. The segments are described via Hamilton-Jacobi equations. Subsequently, the algorithm performs a limited reconstruction of the microtubules in 3D. Last, we evaluate our method with phantom as well as real TIRFM images of living cells.
Insights
We developed an automated method to analyze total internal reflection fluorescence microscopy (TIRFM) images of microtubules, enabling high-throughput quantitative studies of their function in cell processes.
Area of Science:
- Cell biology
- Microscopy
- Biophysics
Background:
- Microtubule-cortex interactions are vital for cellular functions like vesicle transport, cell motility, and mitosis.
- Dysfunctional microtubules are implicated in cancer progression.
- Total internal reflection fluorescence microscopy (TIRFM) is crucial for observing microtubule dynamics near the cell cortex.
Purpose of the Study:
- To develop an automated method for processing TIRFM images of microtubules.
- To enable high-throughput quantitative analysis of microtubule behavior.
- To overcome limitations of manual analysis in TIRFM studies.
Main Methods:
- Image processing algorithm to automatically extract microtubule segments from TIRFM data.
- Utilizing Hamilton-Jacobi equations for segment description.
- Performing limited 3D reconstruction of microtubules.
Main Results:
- Successful automated processing of TIRFM images.
- Quantitative analysis of microtubule segments.
- Validation of the method using both phantom and real cell imaging data.
Conclusions:
- The developed automated method significantly enhances the efficiency and throughput of TIRFM image analysis.
- This approach facilitates high-throughput quantitative studies of microtubule-cortex interactions.
- The method holds potential for advancing research in cell biology and cancer.
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