High throughput screening with visual readout, for example:
- screening for alteration in the subcellular distribution of a protein of interest
- screening for morphological alterations at the cellular and subcellular levels
- screening for testing the effects of drugs in cellular differentiation protocol
- The BD Pathway ‘high content analysis system’ 435 (BD, U.S.A.)
- Spinning-disk microscope equipped for live imaging (custom-built)
In Cell Biology, it is quite common that within a population many cells show different phenotype, a phenomenon known as “penetrance” that has to be quantified by statistical approaches. By numerical characterization, quantitative morphometry statistically validates various objects such as the different cell types or particular sub-cellular structures (for example the organelles).
It includes counting objects, calculating 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 their fluorescence signal (using protein or RNA reporters). As the segmentation of the images is highly dependent on the parameters chosen, a key aspect of our work is the exact determination of the parameters used by the imaging software for the autonomous recognition and discrimination of the objects of interest (see the illustration).
These automated analysis techniques (high-content analysis) allow to (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.
- The human box C/D snoRNAs U3 and U8 are required for pre-rRNA processing and tumorigenesis.
Langhendries JL, Nicolas E, Doumont G, Goldman S, Lafontaine DL. Oncotarget. 2016 Sep 13;7(37):59519-59534.
- Involvement of human ribosomal proteins in nucleolar structure and p53-dependent nucleolar stress.
Nicolas E, Parisot P, Pinto-Monteiro C, de Walque R, De Vleeschouwer C, Lafontaine DL. Nat Commun. 2016 Jun 6;7:11390.
- The cell proliferation antigen Ki-67 organises heterochromatin.
Sobecki M, Mrouj K, Camasses A, Parisis N, Nicolas E, Llères D, Gerbe F, Prieto S, Krasinska L, David A, Eguren M, Birling MC, Urbach S, Hem S, Déjardin J, Malumbres M, Jay P, Dulic V, Lafontaine DLj, Feil R, Fisher D. Elife. 2016 Mar 7;5:e13722.
- The human 18S rRNA base methyltransferases DIMT1L and WBSCR22-TRMT112 but not rRNA modification are required for ribosome biogenesis.
Zorbas C, Nicolas E, Wacheul L, Huvelle E, Heurgué-Hamard V, Lafontaine DL. Mol Biol Cell. 2015 Jun 1;26(11):2080-95.
- The complexity of human ribosome biogenesis revealed by systematic nucleolar screening of Pre-rRNA processing factors.
Tafforeau L, Zorbas C, Langhendries JL, Mullineux ST, Stamatopoulou V, Mullier R, Wacheul L, Lafontaine DL. Mol Cell. 2013 Aug 22;51(4):539-51.
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