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Future Directions / Projects

M2 internship proposal - Academic year 2021 - 2022

Development of imaging algorithms to follow constitutive heterochromatin dynamics.

Student training profile: Bioinformatics. Bioinformatique.

This project is part of a larger research program studying the impact of environmental hazards on developmental robustness of organ development using Drosophila melanogaster as a model system. Developmental robustness is understood here as the invariance of an organ in face of a set of intrinsic and extrinsic disturbances during its formation. We propose to analyse the organisation of constitutive heterochromatin during cell fate determination and differentiation as well as after the cellular response to these environmental risks. Constitutive heterochromatin is a condensed form of chromatin that has been proposed to have a major role on nuclei structural organisation as well as on silencing of gene expression. It is known to be affected by environmental factors (lead, temperature) and present data suggest that it plays a role on the robustness of organogenesis.

We will study the constitutive heterochromatin dynamics during mechanosensory organ morphogenesis in control and under different experimental conditions (different developmental times or hazardous conditions). To follow the constitutive heterochromatin, we will use fly lines expressing (1) a fluorescent form of the specific heterochromatin binding protein HP1 and (2) a fluorescent form of lamin to visualize the nucleus. The analysis will be performed on so-called 5D recordings (three dimensional images, in conjunction with temporal and fluorescence channels). The student will participate to develop image analysis algorithms in order to (1) identify (ie numerical segmentation) the nuclei within an epithelial tissue, (2) identify heterochromatin inside each nuclei and (3) extract different parameters of the heterochromatin, such as size, texture, number of lobes, intra-nuclear position. The first part of the project, nuclei segmentation, will be based on state of the art deep-learning methods, such as StarDist or CellPose, or any relevant methods. The second part, chromatin segmentation and analysis, will rely largely on the 3D ImageJ Suite developed by T. Boudier at the IBPS. Nowadays, the segmentation of nuclei from 3D images is still challenging. Given the growing interest in the analysis of intranuclear structures, the student will participate in the development of user-friendly tools that can be generalized for other purposes as well as to other tissues and biological models.

The student will benefit from two areas of expertise. On the one hand, he / she will work closely with Jean-François Gilles, an expert in 3D image processing and analysis who is part of the IBPS Imaging Platform and on the other hand, with the team of M. Gho, who has developed a great expertise in in vivo recording techniques applied to the Drosophila model.

Contacts :  mailto:michel.gho@sorbonne-universite.fr