QuoVadoPro, an Autonomous Tool for Measuring Intracellular Dynamics using Temporal Variance.

Area of Science:

• Cell Biology
• Biophysics
• Computational Biology

Background:

• Intracellular cargo trafficking is crucial for cell function and is implicated in diseases such as cancer and neurodegeneration.
• Accurate quantification of intracellular traffic is essential for understanding cellular processes, disease mechanisms, and therapeutic drug development.

Purpose of the Study:

• To introduce QuoVadoPro, an autonomous algorithm for quantifying fluorescently tagged intracellular cargo movement.
• To provide a versatile tool applicable to diverse experimental conditions and cell types, especially non-neuronal cells.

Main Methods:

• QuoVadoPro infers intracellular motility by analyzing the variance of pixel illumination in time-lapse images.
• The algorithm utilizes temporal variance, an unconventional approach for automatic measurement of intracellular traffic.
• It is designed to handle low temporal/spatial resolution images and cargo of varying shapes/sizes (e.g., mitochondria, endoplasmic reticulum).

Main Results:

• QuoVadoPro autonomously quantifies intracellular cargo movement.
• The algorithm is effective in non-neuronal cells exhibiting short, multi-directional movements.
• It overcomes limitations of conventional methods like kymography and particle tracking in specific scenarios.

Conclusions:

• QuoVadoPro offers a novel and autonomous method for measuring intracellular dynamics.
• The algorithm is particularly valuable for analyzing cargo trafficking in challenging experimental contexts.
• It provides a robust tool for researchers studying cellular transport and related pathologies.