Automation and quantitative morphometry

Application

High throughput screening with visual readout

E.g.: siRNA-mediated screening in human cell lines for the alteration in the subcellular distribution of a protein of interest

E.g.: screening for morphological altérations at the cellular and subcellular levels

E.g.: screening for testing the effects of drugs in cellular différentiation protocoles

Equipment

  1. The BD Pathway ‘high content analysis system’ 435 (BD, U.S.A.)
  2. Plate-forme multimodale à haute résolution pour morphométrie quantitative

Description

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.

 

Contact:

Facility manager Academic supervisor
optique003
Laure TWYFFELS
Laure.Twyffels@ulb.ac.be
optique003
Denis LAFONTAINE
Denis.Lafontaine@ulb.ac.be
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Automation and quantitative morphometry