Quantifying Yeast Microtubules and Spindles Using the Toolkit for Automated Microtubule Tracking (TAMiT)

Area of Science:

• Cell Biology
• Biophysics
• Microscopy and Imaging

Background:

• Fluorescence imaging of cytoskeletal polymers like microtubules is crucial for understanding cellular organization and dynamics.
• Current image analysis methods for fluorescent microtubules, especially in living cells, are often manual and limited by low signal-to-noise ratios.
• Automated tools for in vitro microtubule analysis exist, but robust methods for in-cell analysis are lacking.

Purpose of the Study:

• To develop and validate an automated software tool, TAMiT (Toolkit for Automated Microtubule Tracking), for accurate detection and tracking of fluorescent microtubules in living yeast cells.
• To overcome limitations of manual analysis and low signal-to-noise ratios in cellular fluorescence microscopy.
• To enable quantitative analysis of microtubule dynamics and organization in various yeast species and mutant backgrounds.

Main Methods:

• TAMiT utilizes a geometrical scanning technique to detect linear and curved polymers based on microtubule organization.
• Image analysis involves fitting microtubule parameters using non-linear least squares optimization in Matlab.
• Software performance was benchmarked using simulated images and applied to analyze microtubule bundles in *S. pombe* and astral microtubules in *S. cerevisiae*.

Main Results:

• TAMiT reliably detects microtubules with sub-pixel accuracy, even at low signal-to-noise ratios, as validated by simulated data.
• Automated analysis of *S. pombe* monopolar spindle microtubules revealed insights into bundle number, length, and lifetime, supporting a role for CLASP/Cls1 in bundling.
• Automated tracking of *S. cerevisiae* astral microtubules yielded dynamic instability parameters comparable to manual measurements.

Conclusions:

• TAMiT provides a robust, fully-automated solution for analyzing microtubule dynamics and organization in yeast cells.
• The software facilitates high-throughput quantitative analysis, overcoming limitations of manual methods in challenging imaging conditions.
• TAMiT can significantly advance research on microtubule-based processes in various cellular contexts.