Title of the article

An article by Sofia Strubbia for the MoDaL project

Whether it is genomic data, in vitro or in vivo imaging, animal or plant models, data in life sciences are today mostly processed “in silos”. The projet federatedtear Modal (Multi-Scale Data Links), supported by the Biogenouest network, aims to decompartmentalize resources and promote moments of exchange and collaborative work around the integration of multi-scale biological data. The aim of these meetings is to discover the diversity of profiles of research in biology and health in the West.

I met Perrine Paul-Gilloteaux for the MoDaL meetings on July 10, 2020 in the premises of the UMR_S 1087 / UMR_C 6291 team of the Research Unit of the Thorax Institute, in Nantes.

Perrine Paul-Gilloteaux

Perrine Paul-Gilloteaux

Presentation and scientific background

A research engineer at the CNRS, Perrine Paul-Gilloteaux specializes in the processing and analysis of imaging data in the biomedical field. After studying electronics and computer science, Perrine did her doctorate on monitoring brain deformities during craniotomy procedures by creating a stereoscopic reconstruction of the patient's brain from surgical microscope images. She then continued to gain expertise in image analysis by approaching a wide range of imaging techniques, such as augmented reality in surgery and tumor segmentation in ultrasound. Among its achievements: the development of an intelligent fluorescent microscope, making the decision of the area to be imaged and the acquisition frequency, on the basis of real-time analysis of the image content. Today she runs the platform MicroPICell (in Nantes) and works on his own research subjects on the acquisition and analysis of correlative multimodal images.

The fascinating world of microscopy

In the world of microscopy, Perrine told us about photon imaging. Often used with immuno-fluorescent labels, this technique allows the use of several specific labels, making it possible to study the interactions between different elements as well as monitoring changes over time, the localization of labeled RNA, etc. a spatial and dynamic dimension on the organization of biological phenomena. This imagery can be three-dimensional, cover resolutions (the possibility of seeing the details of what one observes) and fields of view which vary greatly depending on the microscopy systems used. Some systems are made to observe cells or tissues on glass coverslips, living or fixed (vitro), others to observe cells directly in a living animal model for example (in vivo). There are also more and more imaging systems that do not require labeling samples to characterize them. There are many other imaging techniques that are not based on the use of light and photons: for example theatomic force microscopic imaging (AFM) is a technique used to study the composition of different biological tissues. The microscope has a tip that allows you to exert force and measure the resistance response offered by the different tissues (this is not part of the MicroPICell platform equipment). A common denominator is that to interpret your images you need the help of computers and programs image analysis.

For more information on the different imaging modalities used in research, Perrine invites us to read the article by Walter et al., 2020 (table 2 and 3).

An example of multiscale data analysis

Within the Thorax Institute and several platforms of the SFR a multi-scale project is taking place to characterize the mechanisms at the origin of certain valve diseases, which are based on different disciplines and expertise. An animal model has been characterized: with micro-scanner (microCT) techniques, the morphology of rat hearts is examined at the scale of a few microns (µm) in order to identify the deformed parts of a valve. These parts are then specifically examined under microscopy. A 3D visualization of histological slides is possible thanks to a technique, developed by the MicroPICell platform, which makes it possible to integrate a camera into the microtome. In addition, the integration of genomic data and biological markers makes it possible to identify the actors and mechanisms involved in valve disease. These studies have made it possible to study the role of a protein in the cytoskeleton of cells, filamin-A, which enables them to adapt to the mechanical stress they may undergo. Thus, some patients with valvular heart disease carry filamin-A mutations that specifically disrupt valve cell responses. These cells could be predisposed, because they are permanently subjected to a very important mechanical stress during each cardiac contraction (mechanical transduction).

MoDaL project