CBB Predoc course, October 2010

Kota Miura, Centre for Molecular and Cellular Imaging, EMBL

• Anisotropies in cortical tension reveal the physical basis of polarizing cortical flows, Mayer et al., Nature 467 , 617–621 (30 September 2010) doi:10.1038/nature09376
  • http://www.nature.com/nature/journal/v467/n7315/full/nature09376.html (PDF available from within EMBL)

… Maybe also

• Bray, D. & White, J. G. Cortical flow in animal cells. Science 239, 883–888 (1988)
  • http://www.sciencemag.org/cgi/content/abstract/239/4842/883 (PDF available)
  • A Classic paper initially hypothesized Cortical Flow.

Theme title: Optimization of Analysis Strategy for Studying Microtubule Plolarity in Drosophila embryo

Regulation of cytoskeletal orientation is a basic mechanism for controlling cell polarity, and hence the dynamics of coordinated cell movment. We try to establish analysis protocol for studying microtubule orientation within Drosophila embryo as a first step to examine the role of MT orientation in tissue dynamics. For this, we use Microtubule binding protein EB1. This protein moves towards the plus end of microtubule, so we could know MT polarity by tracking EB1 movement.

Using sevral available tools for Quantification, find a best strategy for quantifying the microtubule polarity from EB1 labeled cells.

ImageJ/Fiji Plugins (http://pacific.mpi-cbg.de/wiki/index.php/Fiji)

1. Manual Tracking (Manual_Tracking.class)
   • bundled in Fiji
   • http://rsbweb.nih.gov/ij/plugins/track/track.html
2. Particle Tracking (ParticleTracker.jar)
   • https://weeman.inf.ethz.ch/ParticleTracker/
3. Flow Analysis (kbi_ij_plugins_882b-101003.jar)
   • http://hasezawa.ib.k.u-tokyo.ac.jp/zp/Kbi/KbiFlow
   • SCALA runtime library (http://www.scala-lang.org/downloads/index.html)
   • KBI olugins (http://hasezawa.ib.k.u-tokyo.ac.jp/zp/Kbi/kbi_ij_plugins_882b-101003.jar)
   • a bit more in http://hasezawa.ib.k.u-tokyo.ac.jp/zp/Kbi/ImageJKbiPlugins

Drosophila EMbryo sequence was provided by Sasha Necakov @ Stefano De Renzis lab.

XY scale 1 pixel = 0.266 micrometrer

Time/Frame

We analyze movement of EB1 signal using three strategies with following steps:

• Track them either manually or automatically.
• Using coordinates, calculate the directon of EB1 movement (hence MT orientaiton)
• Plot the results in histogram. Do some statistics.

Our aim is to plot a histogram of movement orientation, and test whether there is bias in the movement. Compare three tools, and find the best way to analyze the microtubule orientation.

Conversion of Cartesian Coordinates to Polar Coordinates

• R Package: fisheyeR
• http://finzi.psych.upenn.edu/R/library/fisheyeR/html/toCartesian.html
• function toPolar(x, y)
• see maybe also
  • http://en.wikipedia.org/wiki/Polar_coordinate_system

von Mises likelihood estimates

• see http://en.wikipedia.org/wiki/Von_Mises_distribution
• R Package: CircStats
• http://finzi.psych.upenn.edu/R/library/CircStats/html/vm.ml.html
• vm.ml(…)
• mu (mean), kappa (concentration parameter) is returned.

• R Package: circular (more parameters)
• http://finzi.psych.upenn.edu/R/library/circular/html/mle.vonmises.html
• function mle.vonmises(…)
• Maximum likelihood estimate of concentration parameter (kappa) is a good indicator of bias in directionality.

Data Plotting

• R Package: CircStats
• http://finzi.psych.upenn.edu/R/library/CircStats/html/00Index.html