HOW DOES A ROBUST AND ADAPTIVE CELL DIVISION EMERGE FROM THE NUMEROUS INTERACTIONS OF INVOLVED PLAYERS?
The lab aims to address this question using a multi-disciplinary approach.
We will account for the emergence of properties like robustness to perturbations (either for good, in development, or for bad in cancerous cells able to divide despite their accumulated defects) or adaptability to protein evolution.
To do so, the relevant level is, rather than the protein or protein complex level, the mechanism that can be seen as a (broad) pathway, which is well-conserved thorough evolution. This is a network of interacting players well approached by the statistical physics. Such a change of paradigm is highly promising for future applications in cancer therapy.
In contrast to previous “biochemical” systems biology approaches, we focus on mechanics, in vivo. Indeed, mitosis involves regulation of forces that position the spindle, separate sister chromatids, etc. We benefit from the growing corpus of in vitro experiments shedding light on the properties and roles of microfilaments and molecular motors. We investigate not only the dynamics of components but also pseudo-balance in forces, for example the slow elongation of the spindle (out-of-equilibrium in the words of physics). This pseudo-balance provides an advantage in adaptability .
To do so, we develop microscopy, image processing and data analysis tools to quantify the dynamics in vivo using Caenorhabditis elegans as a model organism.
The video hereafter shows an example of detection and monitoring of centrosomes in a genetically engineered C. elegans embryo expressing a fluorescent protein associated with centrosomes. High frequency and high sensibility image acquisition allows for a detailed recording of signal dynamics. The tracking software developed by CeDRE analyzes the signal from each film's image to record the positions of the anterior and posterior centrosomes as represented on the graphics in the lower part of the video. This semi-automated image analysis provides quantitative data to analyze the mechanics of cell division.
We then model the dynamics (using mathematical equations and numerical simulations) using out-of-equilibrium statistical physics.
Indeed, we aim to build a multi-scale model, using out-of-equilibrium statistical physics, linking the molecular details to the “macroscopic” mechanisms, completed by numerical simulations (virtual cell division) to test the role of each component in silico. This model could serve as a predictive tool for fundamental and applied research (testing/screening of drugs e.g.). To ease the applicability of our recapitulating models, we started testing our tools and models on cultured human cells (leukemia).
The scheme below summarizes our research process detailed above.