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Updated: Jul 10, 2026
Simultaneous Interference Reflection and Total Internal Reflection Fluorescence Microscopy for Imaging Dynamic Microtubules and Associated Proteins
Published on: May 3, 2022
Automatic microtubule tracking for QD-based in vivo cell imaging and drug efficacy study
Koon Yin Kong1, Adam I Marcus, Jin Young Hong
1Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA 30332, USA. kykong@gatech.edu
Abstract:
Microtubules (MT) are dynamic polymers that rapidly transition between states of growth, shortening, and pause. These dynamic events are critical for many microtubule functions such as intracellular trafficking and signaling. In addition, cancer chemotherapy drugs that target microtubules, such as the taxanes and the vinca alkaloids, are known to suppress microtubule dynamics at low doses, leading to mitotic arrest and cell death. Quantification of microtubule dynamics can be used as a read-out of anticancer-drug activity and can be a surrogate marker of drug sensitivity/resistance. The emerging nanotechnology such as quantum dots has provided properties such as less photo bleaching, higher probe imaging intensity, better specificity and sensitivity, which finally makes visualizing subcellular events over long enough time a possibility. But it also results in big increase in data acquisition. The traditional way of annotating MT manually is becoming a daunting task. Thus, the goal is to research and develop an efficient, reliable, and rapid MT tracking. In this paper, we describe active contour-based tracking methods to automatically track MT. We redefine the internal energy terms specifically for open snake, and examine different external energy terms for locating the end tips of a microtubule. This algorithm has been validated using simulated images, images of untreated MCF-7 breast cancer cells, and image of cells treated with the microtubule-targeting chemotherapeutic agent, Taxol.
Insights
This study introduces an active contour-based method for automatically tracking microtubule dynamics, crucial for understanding cancer drug efficacy. The developed algorithm efficiently quantifies microtubule behavior, aiding in drug sensitivity assessments.
Area of Science:
- Cell Biology
- Bioimaging
- Computational Biology
Background:
- Microtubules (MT) are essential dynamic polymers involved in vital cellular processes.
- Microtubule dynamics are a key target for cancer chemotherapy drugs like taxanes and vinca alkaloids.
- Quantifying microtubule dynamics serves as a biomarker for anticancer drug activity and drug resistance.
Purpose of the Study:
- To develop an efficient, reliable, and rapid method for automatically tracking microtubule dynamics.
- To address the challenges posed by large data acquisition from advanced imaging techniques like quantum dots.
- To provide a robust tool for analyzing microtubule behavior in response to chemotherapeutic agents.
Main Methods:
- Utilized active contour-based tracking methods, specifically "snakes", for automated microtubule tracking.
- Redefined internal energy terms for open snakes to accurately capture microtubule structures.
- Examined various external energy terms to precisely locate microtubule end tips.
Main Results:
- Validated the active contour-based tracking algorithm using simulated images.
- Successfully applied the algorithm to images of untreated MCF-7 breast cancer cells.
- Demonstrated the algorithm's efficacy on cells treated with the microtubule-targeting agent Taxol.
Conclusions:
- The developed active contour-based method provides an efficient and reliable approach for automated microtubule tracking.
- This technique facilitates the quantification of microtubule dynamics, essential for evaluating anticancer drug responses.
- The algorithm shows promise as a tool for assessing drug sensitivity and resistance in cancer research.
