Quantitative Analysis and Mathematical Modeling of Polarity Establishment in C.elegans Embryos

Even though polarity establishment in the one-cell stage C. elegans embryo has been studied qualitatively using forward genetic and RNAi-based functional genomics, how polarity components interact in space and time remains poorly understood. This is due in part to the lack of automated methods to gather quantitative information with subcellular precision. Consequently, data quantification is often performed manually, which is repetitive, inefficient and prevents the precise and consistent analysis of large datasets.       

To circumvent this limitation, we developed a multi-channel image analysis software coupled with a reference coordinate system that we termed ASSET (for Algorithm for the Segmentation and the Standardization of C. elegans Time-lapse recordings). By automatizing the segmentation, our algorithm enables us to combine the great spatial and temporal resolution achieved in live recordings with an efficient computational pipeline, permitting the fast and coherent processing of a large number of recordings. Consequently, ASSET provides an adequate platform for image-based automated quantifications of dynamical processes.       

We now use ASSET to precisely measure fluorescence intensities from time-lapse recordings of PAR fusion proteins, starting with the posterior GFP-PAR-2 fusion protein. Combined with an effective mathematical model [Goehring et al., Science, 2011], these recordings allow us to quantify precisely key spatio-temporal features of polarity establishment. Of particular importance, we can derive in this manner values for the parameters governing the mutual inhibition of the anterior and posterior polarity complexes, yielding important insights on the underlying molecular mechanisms. Ultimately, we aim at applying a systems biology approach to calibrated, challenge and improve our model using quantitative data. We expect this model to uncover general polarization principles, to be able to correctly predict known mutant behaviors and to provide a framework for further analysis.

Keywords: Image Analysis, Polarity, C. elegans, Automated Quantification, PDE



 Simon  Blanchoud

Simon Blanchoud
EPF Lausanne
Gönzy Lab UPGON
SV 1527 - Station 15
CH - 1015 Lausanne

Phone: +41 21 693 07 10