High performance MS-based proteomics by reducing stable isotopes complexity in vivo – SLIM-labeling

Our approaches are of two types: experimental and computational.
Experimental approaches consist in the production of biological samples enriched, or not, in carbon 12, the light carbon isotope. These samples are used to test the method of quantifying bottom-up proteome variations, in particular by establishing carbon-12 concentration ranges by controlled mixing of labelled and unlabelled samples. The biological systems tested are the bacterium Escherichia coli, the yeasts Saccharomyces cerevisiae and Candida albicans, Drosophila and human cultured cell lines, and the nematode Caenorhabditis elegans.
Computational approaches can be divided into three classes. The first class relates to experimental signal processing. We have searched for robust solutions to extract, from «machine« files, the intensity of the isotopic masses of the peptides that have given a positive identification in liquid chromatography/mass spectrometry coupled analyses. We have established a very effective collaboration with the developer of a high-performance algorithm to perform this operation. The second class consisted in the establishment of the theoretical model allowing the development of quantitative approaches in SLIM-Labeling. The third class consisted in the development of an analysis pipeline to produce the experimental quantitative data.

The main results are:
* a robust original theoretical model for the Bottom-Up quantification of complex proteomes based on SLIM metabolic labeling.
* a fast, robust and integral analysis pipeline using only open-source computational resources implemented in a KNIME work environment.
* Original biological data on proteome variations in the yeast Sacchoryces cerevisiae, highlighting in particular the changes induced by the presence of exogenous amino acids necessary to supplement classical auxotrophies carried by laboratory strains.
* significant improvements in the rate of protein identification in simple proteomes, but also in complex proteomes (higher eukaryotes)
* Preliminary but robust results proving the feasibility of using SLIM-Labeling for the quantification of intact proteins in Top-Down analyses.

The method for quantifying proteome variation using bottom-up approaches using the SLIM-Labeling strategy is now well established and fully operational. It is now applicable to cells whose growth depends on the exogenous supply of non carbon-12 enriched amino acids, such as human cells. Automatic analysis pipelines, implemented in a KNIME environment, are available to the scientific community. This opens up important perspectives for a large number of ambitious research projects in bilogy and medicine.
The priority for further work will be to extend these analytical methods to the study of proteome variations at the scale of intact proteins. To this end, we are developing a completely new method, using SLIM-Labeling, which allows quantitative analyses in «top-down«, even when it is not possible to obtain precise identification of the quantified proteins. In addition, the tools under development offer a new relevance score when using protein identification algorithms.
This area of research is currently one of the most active in proteomics.

Two publications in the process of being finalised as of 12/04/2020

One of the most challenging problems in modern biology is to address at the experimental level the analysis of the dynamics of proteome variations in composition and structure in order to decipher the fundamental mechanisms of gene expression and regulation in normal and pathological conditions. Using U-[12C]-glucose as the sole source of carbon to grow prototrophic cells, we developed a Simple Light Isotope Metabolic (SLIM) labeling strategy highly effective to analyze with an unprecedented depth complex proteomes in bottom-up and top-down experiments. We want now to elaborate an automatic workflow processing of MS bottom-up raw data for quantitative proteomics. This requires robust statistical analysis of the SLIM-labeling based quantitative proteomics procedures. We want to apply the SLIM-labeling strategy to analyze the quantitative variations of proteoforms in top-down experiments, addressing the complexity of proteome from multi-cellular organisms and higher eukaryote cells.