Inventaire
Site en français
LAFONTAINE Denis



Units

RNA Metabolism

Person in charge of the Unit : Oui

RNA is central stage in gene expression. The 'RNA Metabolism' Lab is trying to understand why all cellular RNAs are working in very close association with proteins within so-called RiboNucleoProtein particles or RNPs. My Lab is interested both in the modes of synthesis and function(s) of the RNPs under normal and disease situations. Defects in the synthesis and/or function(s) of the RNPs irremediably lead to severe human auto-immune and genetic diseases. Our fundamental research therefore has clear biomedical implications. One of our our major experimental paradigm is Eukaryotic Ribosome. These large RNPs are mostly synthesized within a specialized subcellular compartment: the nucleolus. Nucleolar morphogenesis is therefore also of great interest to the Lab. Nucleolar function provide an excellent readout for the overall cellular activity and cancer cells specifically over express nucleolar proteins which are thus potent markers for diagnosis and prognosis. Our research also focuses on these nucleolar proteins. 

Projetcs

Eukaryotic RNA surveillance

Identification and characterization of Eukaryotic RNA surveillance mechanisms.Within a cell, RNAs all undergo numerous maturation steps (processing, covalent modification, assembly with proteins, transport, etc) prior to becoming functional. Each step is prone to an error rate. Each error has potential lethal consequences for the cell. In this project, we are studying the 'quality control' mechanisms that eukaryotic cells developed to target aberrant RNAs for degradation.

Automation and Quantitative Morphometry

In Cell Biology, it is quite frequent that within a population not all cells show the same phenotype, a phenomenon known as 'penetrance' that has to be met by statistical approaches. Quantitative morphometry precisely aims at the statistically validated numerical characterization of various objects such as the different cell types or particular sub-cellular structures (for example the organelles). It includes counting objects, calculation of their diameter, surface, volume, level of the co-localization of different antigens etc. The recognition of the cellular and sub-cellular structures can either be done on the basis of their particular morphology (histochemistry) or on the basis of their fluorescence (using protein or RNA reporters). A key aspect of our work consists in the segmentation of the images (see the illustration), i.e. the exact determination of the parameters used by the imaging software for the autonomous recognition and discrimination of the objects of interest. By combining automated analysis techniques (high-content analysis), which allow to analyze numerous samples without the intervention of a human operator, with software trained to perform automatic recognition and morphometric analysis, we will be in a position to, for example, (i) determine the number of bacteria in the cytoplasm of macrophages, (ii) test the effects of dozens of synthetic molecules ('drug design') on stem cell differentiation or (iii) on the sub-cellular localization pattern of antigens of interest (for ex. the dynamic re-localization of a membrane  receptor in the cytoplasm). Macroscopic applications such as lytic plaque analysis or the calculation of the relative distribution of several species of pathogenic organisms are possible. The development of working protocols is done in collaboration with the RNA metabolism laboratory of the Université Libre de Bruxelles.