The team uses classical methods of yeast molecular genetics (transformation, crosses, etc.) to generate mutant strains (auxin-dependent degron, conditional mutants, conditional expression) and fluorescent markers (redox or pH ratiometric probes, fusion proteins, fluorescent timers, etc.).
We have 4 inverted epifluorescence microscopes with motorized stage to image the cells in intervals of 3 to 20 minutes over periods of up to about 100h. In this way, we can capture the entire replicative life of a cell from birth to death (Aspert et al. 2022) or the metabolic transitions that occur in individual cells as population growth consumes all available resources (Jacquel et al. 2021).
We use the open source software Micromanager for microscope control and data acquisition and custom scripts to ensure robustness. Typically, we can image about 60 separate fields of view with 3 acquisition channels per 10-minute interval.
We develop our own PDMS microfluidic systems. For this purpose, we fabricate on site patterned molds by soft lithography using multi-layer SU-8 resin deposits with a Kub3 UV mask aligner. We have set up a clean microenvironment in the lab to make these samples.
We also develop mechanical parts by 3D printing with filament (Prusa) and stereolithography (Formlabs) after design with the help of Fusion360 software. Finally, we make our own temperature controllers and solenoid valves from simple electronic and electrofluidic components using the Arduino ecosystem.
Over the course of successive projects, we have developed several analysis and data mining pipelines whose links can be found below:
DetecDiv is a software to track large number of cells in different context and automatically detect their divisions, measure their volume and fluorescence, and more. It is based on deep-learning and parallel computing and can be adapted to many applications and cell types. It also includes a GUI and a set of functions for data visualisation, manual annotation, plotting and export (figures, movies...).
Ref. : Aspert et al, eLife, 2022
Database to explore the cell cycle dynamics of a collection of cell cycle mutants.
Software (with graphical user-interface) for semi-automated image processing of time lapse microscopy data: cell segmentation, sub-cellular object segmentation, cell tracking, lineage analysis, fluorescence quantification.
Ref. : Goulev et al, eLife, 2017
Command-line software for automated image processing of yeast single cell division data.
Since it is based on the architecture of PhyloCell, it requires PhyloCell functions to work properly.
A toolbox for combinatorial assembly of expression vectors in yeast. This method is a cloning-free technique to assemble yeast plasmids using the Golden Gate assembly technique.
In addition, a software has been developed to help.
Ref. : Goulev et al., Biorxiv 2019
