High-resolution mass spectrometry-based proteomics and label-free quantitative methods have progressed tremendously in recent years, and became increasingly popular as an attractive and powerful way to analyse differential protein expression in complex biological samples, particularly in the field of biomarker discovery.
However proteomic analysis of body fluids represents a real challenge due to the very large dynamic range of protein concentrations: basically, the vast majority of the protein content is represented by only one or a few proteins, which hinder the detection of low-abundant species. We have been involved in the testing of the Proteominer technology, which represents a powerful tool to go much deeper into the proteome characterization.
Our group has also been involved in the development of bioinformatics methods for the large-scale quantitative analysis of complex proteomes through label-free approaches. The program MFPaQ (Mascot File Parsing and Quantification) (Bouyssie et al., MCP 2007) was adapted for label-free quantification (Mouton-Barbosa et al, MCP 2010) and allowed us to perform large-scale protein expression profiling in complex samples such as biological fluids or whole cellular proteomes.
Examples of such applications include the in-depth quantitative analysis of cerebrospinal fluid (Mouton-Barbosa et al, MCP 2010), the profiling of clinical urine samples for the identification of biomarkers of obstructive nephropathy, a kidney pathology of newborn infants (Lacroix et al, MCP 2014) or the search for biomarkers of abdominal aortic aneurysms (Martinez-Pinna R et al, Proteomics Clin Appl. 2014).