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Cortical Actin Flow in T Cells Quantified by Spatio-temporal Image Correlation Spectroscopy of Structured Illumination Microscopy Data
Published on: December 17, 2015
Event ordering in live-cell imaging determined from temporal cross-correlation asymmetry
Daniel R Sisan1, Defne Yarar, Clare M Waterman
1Department of Physics, Georgetown University, Washington, District of Columbia, USA. dan.sisan@gmail.com
Biophysical Journal
|June 2, 2010
Summary
This study introduces a new method using cross-correlation to determine the order of cellular events in live-cell imaging. This technique accurately analyzes noisy biological data, revealing hidden temporal sequences in cellular processes.
Area of Science:
- Cell Biology
- Biophysics
- Biochemistry
Background:
- Live-cell imaging generates complex, often noisy, data.
- Determining the precise temporal order of cellular events is crucial for understanding biological pathways.
- Stochasticity and noise can obscure event sequencing in raw data.
Purpose of the Study:
- To develop a quantitative method for determining the temporal ordering of spatially localized cellular events.
- To provide a robust analysis for noisy and stochastic live-cell imaging data.
- To enable statistical interpretation of cellular signaling dynamics.
Main Methods:
- Utilizing the temporal asymmetry of the cross-correlation function.
- Applying the method to simulations of biophysical models with known temporal order.
- Analyzing multichannel fluorescence imaging data from live cells.
Main Results:
- The cross-correlation method successfully determined temporal ordering in simulated data.
- The technique accurately identified the sequence of actin, sorting nexin 9, and clathrin during endocytosis.
- The approach demonstrated robustness in noisy, stochastic systems.
Conclusions:
- The temporal asymmetry of cross-correlation is a powerful tool for deciphering cellular event order.
- This method offers an automated, quantitative approach to analyze complex live-cell imaging data.
- The technique is broadly applicable to non-equilibrium biochemical reactions and cellular signaling.
