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Last update: May 2021

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Intact cell molecular phenotyping

plaque MALDI avec dépôt
Direct analysis of whole cells (eukaryotes or prokaryotes) by MALDI-TOF mass spectrometry in proteomics and lipidomics.

We offer high-throughput cell phenotyping using direct analysis by MALDI-TOF mass spectrometry, more commonly known as ICM-MS (Intact Cell MALDI-TOF Mass Spectrometry). This approach is applied either :
- on whole and intact higher eukaryotic cells to characterise biomarkers of a peptide, protein or lipid nature, without prior extraction.
- on micro-organisms for their identification/authentication. This activity is carried out in partnership with the CIRM (International Centre for Microbial Resources).

principe ICM-MS

The cells are directly deposited on the MALDI plate and then mixed with a matrix used for analysis by MALDI-TOF mass spectrometry. After drying, the co-crystallised cell-matrix mixture is subjected to a laser beam to cause ionisation of the biological molecules. The ions thus generated are sorted by the time-of-flight (TOF) analyser and then recorded in order to obtain a characteristic spectrum of the cells.
Peptide and protein profiles are obtained in a mass range from 1 to 30 kDa while lipid profiles are obtained in a mass range from 100 to 1500 Da.
The profiling approach by ICM-MS has many advantages as it requires very little preparation of cell samples and no prior extraction or separation of biomolecules. It is extremely sensitive and reproducible as it allows spectral profiling of groups of cells (biopsies) down to the single cell scale (individual oocytes or embryos).
It allows differences in the presence/absence or fine variations in the abundance of biomolecules to be seen.


ICM-MS on eukaryotic cells  :

The ICM-MS is well known for its applications in phyloproteomics (identification/taxonomy of microorganisms), yet little data is currently available for the analysis of higher eukaryotic cells. To overcome the scarcity and poverty of various cell types, we have developed this cell phenotyping approach by profiling from the direct analysis of whole eukaryotic cells by MALDI-TOF (Matrix Assisted Laser Desorption/Ionisation-Time Of Flight) mass spectrometry to search for markers of interest (peptides, proteins, lipids).
We have adapted the ICM-MS to the analysis of different eukaryotic cells, particularly mammalian cells, and performed differential analyses at different physiological states or after a given treatment. Currently, we are applying this methodology to the analysis of spermatozoa (avian, porcine, ovine, equine, bovine and human), follicular cells (cumulus cells, granulosa cells) bovine, equine and human up to the single cell scale : the bovine oocyte, primordial germ cells (chicken), bovine embryos, blood cells (porcine, bovine and murine neutrophils, avian heterophilic granulocytes and other cell types (tumour cells in culture, whole plant cells or in the state of protoplasts (Catharensus).
Today, quantitative differential analysis by ICM-MS, on a large scale with supporting statistical analyses, has now become routine. It is possible to compare multiple conditions (more than a thousand spectra) in a single bioinformatics study and thus to characterise very quickly numerous peptide/protein or lipid markers. After spectral acquisitions of a given cell type, with several replicas for each of the physiological conditions, the spectra are processed on a computerized level (smoothing of spectra, alignment, normalization on the basis of the total ion current, automatic detection of molecular species). Robust statistical analyses are then carried out to characterise the biomarkers.

In fundamental research, through quantitative differential analyses (statistical analyses), cell phenotyping offers the possibility of accessing new molecular information (not addressed by classical proteomics approaches). It thus makes it possible to characterise new biomarkers for a better understanding of the molecular mechanisms involved in a given function.
Moreover, in applied research, the coupling of molecular phenotypes to mathematical modelling (correlation test) or to the "Machine learning" method (Genetic algorithm/Supervised Neural Network) makes it possible to develop and create diagnostic molecular tests (for classification or prediction) that can be used in the field of Artificial Intelligence and predictive biology (human and veterinary preclinical research).
However, the ICM-MS approach only allows the detection of biomolecules (visualization of 150 to 250 peaks per spectrum). To identify endogenous protein species, we combine ICM-MS with a top-down approach based on the use of high-resolution mass spectrometry. It consists in directly selecting whole and intact molecular species of interest upon fragmentation, in order to obtain sequence labels to identify them. The two main advantages of the top-down strategy are the potential access to the complete protein sequence and the ability to localise and characterise post-translational modifications in the same analysis. However, this approach is only possible after extraction of the proteins - µpurification of markers, analysis by MS and MS/MS and interpretation of the data by adapted bioinformatics tools.

ICM-MS on microorganisms for phyloproteomics :

In partnership with the CIRM (International Centre for Microbial Resources), which preserves more than 20,000 strains, we have set up, since 2015, the molecular phenotyping of prokaryotic cells with the aim of phenotyping the different collections of the CIRM's Biological Resource Centres (5 BRCs in France) and to be able to offer a phyloprotomics service open to external public or private laboratories. As a result, in alliance with the CIRM, the cluster offers a complete solution of mass spectrometry (MALDI-TOF RapiFleX, Bruker) and bioinformatics tools (MALDI Biotyper, Bruker) adapted for the identification/authentication of strains of micro-organisms (bacteria, mycobacteria). We are currently building a spectral reference database specifically for the fields of animal and human health (pathogenic bacteria), agri-food, and plant health (plant-associated bacteria).