OverviewPersonnelPublications

Our group works on the development of high-throughput quantitative approaches for the dynamic analysis of the deep proteome. We have developed a comprehensive technology that includes advanced peptide identification algorithms and a novel, multi-layered statistical model for the analysis of quantitative data. Our approach also includes a universally applicable method for stable-isotope labeling that allows full control of variance sources. We are working on the generalization of the statistical model and on the integration with systems biology algorithms to improve interpretation of results from a proteome-wide perspective. We have also developed a novel method for simultaneous analysis of relative protein abundance and dynamic alterations in the thiol redoxome.

We are applying these developments to the study of key aspects of cardiovascular disease, with the aim of defining molecular mechanisms and identifying specific protein factors for use as pharmacological targets or biomarkers. One area of interest is the study of dynamic expression changes to the secretome and other subcellular fractions of vascular smooth muscle cells in models of hypertension and hypertrophy, including the role of the calcineurin-NFAT pathway. We are also analyzing dynamic alterations to the mitochondrial proteome and the targets of oxidative damage that occur upon ischemia-reperfusion and the mechanisms of ischemic preconditioning in animal models of deletion or overexpression of several protein factors. Finally, we are studying protein interactions during T-cell activation by APCs and during leukocyte recruitment to the activated endothelium. This work has recently characterized the interactome of tetraspanins in T-lymphocytes and derived exosomes from human patients as well as from KO mouse models lacking specific tetraspanin components.

Figure 1. Top: Workflow scheme for high-throughput quantification of proteomes by stable isotope labeling. Bottom: The “Quixot” bioinformatics platform developed in the laboratory for identification, quantification and statistical analysis of mass spectrometry data.

Figure 2. Determination of changes in the redox state of cysteine-containing peptides in high-throughput proteomics experiments using GELSILOX technology. The figure shows the effect a thiol-specific oxidative agent on vascular endothelial cells. The abundance of peptides containing cysteines in the oxidized state (red points) tends to increase (towards the left), that of peptides containing reduced cysteines (blue points) tends to decrease (towards the right), while non-cysteine containing peptides remain unaltered (green curve). The effect is more evident when the standardized peptide log2-ratio distributions are analyzed separately (red and blue curves).

Figure 3. Left: Characterization of the intracellular tetraspanin interactome in human T-cells. Lower right: The tetraspanin interactome encompasses a large proportion of the composition of T-cell exosomes. Upper right: Quantitative high-throughput proteomics demonstrates that elimination of tetraspanin CD81 in KO mice diminishes the abundance in exosomes of some of its specific interaction partners, suggesting a role in the sorting machinery.