Large-Scale Quantitative Proteomics
Proteomic methods have evolved tremendously over the last two decades, thanks to the introduction of high-resolution, high-sequencing speed mass spectrometers and the improvement of bioinformatics software. They represent today a powerful tool to get new insights into complex biological systems.
We have expertise in discovery proteomics, e.g. all methods dedicated to the systematic, non-hypothesis-driven, and large-scale characterization of complex mixtures of proteins, in a qualitative and quantitative manner.
- Characterization of complex samples (proteomes, sub-proteomes, biological fluids, protein complexes…) with maximal analytical depth (number of proteins identified)
- Precise relative quantification of each protein in different samples using repeatable and reproducible analytical methods
- Semi-absolute quantification of different proteins in a complex mixture
We apply bottom-up strategies based on the enzymatic digestion of proteins with a specific protease (e.g. trypsin) and high-throughput analysis of resulting peptides by liquid nanochromatography coupled to mass spectrometry (nanoLC-MS), using fast-sequencing instruments.
According to the project, we design optimized analytical workflows including the following steps:
- Sample preparation. We can implement various protein extraction methods to:
- prepare total cellular lysates using various detergent, chaotropes, or mechanical disruption techniques
- perform sub-cellular fractionation for the enrichment of particular organelles
- enrich sub-proteomes corresponding to proteins bearing a PTM of interest
- affinity purify protein complexes
- process biological fluids and diluted secretomes and deplete highly-abundant proteins
- Pre-fractionation. In order to increase the analytical depth for highly complex proteomes, samples can be fractionated at protein or peptide level, prior to nanoLC-MS analysis:
- Protein: 1D SDS-PAGE
- Peptide: IEF, SCX, SAX, reverse-phase HPLC
- Quantitative methods. They are important for the accurate comparison of protein or PTM abundances across samples, in order to identify biomarkers or characterize molecular mechanisms. Different strategies can be used:
- Label-free analysis: samples are analyzed independently by nanoLC-MS. Easy to implement, this method relies on the stability and reproducibility of the nanoLC-MS system, and on powerful bioinformatics software for data analysis. We developed the Proline software for optimized label-free quantification.
- Isotopic labelling methods: they rely on the introduction of a mass marker containing heavy isotopes into the proteins or peptides to be compared across different samples, which can then be gathered and analyzed simultaneously. This can be done at protein level through metabolic labelling (SILAC) or at peptide level through chemical modification with dedicated mass tagging reagents (dimethyl labelling, iTRAQ or TMT). These methods are more expensive than label-free approaches, and allow to compare only a limited number of samples. However, they are less sensitive to technical variability and can be used when extensive upstream fractionation or biochemical processing of the samples is performed, and when very precise relative quantitation is necessary.
- NanoLC-MS analysis. At the heart of our analytical pipeline, we use stat-of-the art mass spectrometry methods, based on powerful chromatographic systems and last generation mass spectrometers for high-throughput peptide analysis and sequencing.
- Systems are strictly benchmarked and quality controlled to ensure a sustained level of performance.
- Typical nanoLC-MS runs are performed with chromatographic gradients ranging from 1 to a few hours. Data acquisition time and methods are adapted to the complexity of the samples.
- Different MS modes can be implemented, e.g. data dependent acquisition (DDA) or data independent acquisition (DIA) for improved sensitivity.
- Bioinformatic processing. A typical nanoLC-MS run yields dozens of thousands of survey MS scans (containing peptide masses and intensities) and MS/MS scans (containing sequencing data for each peptide). We use several software tools installed on clusters and/or multicore servers to process this data for:
- Protein database search and protein identification
- Protein quantification based on MS signal intensity
Our in-house developed tools (MS-Angel, Proline, mz-Scope) offer an optimized pipeline solution for data handling, processing and inspection.
- Statistical analysis. We offer support to interpret large-scale proteomic data using state-of-the-art statistical methods and tools, in order to identify differentially abundant proteins and control false-discovery rate.
We are equipped with last generation instruments dedicated to discovery shotgun proteomics and characterization of complex protein mixtures.
- LTQ-Orbitrap Velos
- Q-Exactive +
- Orbitrap Fusion
- Q-Exactive HFX