PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Towards the understanding of the CFTR dynamic interactome: the example of inflammation. Communication in ECFS Conference - New Frontiers in Basic Science of Cystic Fibrosis.
Florence Borot, Ludovic Jeanson, Chiara Guerrera, J Colas, P Pawlowski, farida zehraoui, Florence d'Alché-Buc, P Zielenkiewicz, E Escudier, Franck Brouillard, Mario Ollero and Aleksander Edelman
In: ECFS 2008, 9 – 13 April 2008, Portugal.

Abstract

To better characterize the molecular mechanisms underlying the inflammatory disturbances in CF, and in particular the eicosanoid pathway, we investigated the total protein expression pattern in (i) normal vs CF cells and (ii) in membrane microdomains from cells treated or not by TNFα, a pro-inflammatory cytokine. As an index of activation of the eicosandoid pathway we analysed the synthesis of leukotriene B4 and prostaglandin E2. The study was performed on Calu-3 and CFBE cell lines, and primary cultured cells derived from nasal polyps of controls and CF patients. We have used the classical cell and membrane biology methods followed by mass spectrometry identification, including relative protein quantification (emPAI and ITRAC). The results indicate that the eicosanoid pathway is activated by TNFα within 10 minutes, showing the importance of this mechanism during acute inflammation. The response to TNFα is correlated with the appearance of a CFTR-annexin-1-cPLA2 macrocomplex in detergent resistant microdomains (DRM), which can be prevented by the inhibition of CFTR function. In addition, double SDS-PAGE analysis suggests that an important number of proteins are recruited in DRM by TNFα, suggesting that the macrocoplex may be much larger. Furthermore, the identification and quantification of differentially expressed proteins in human primary cultured cells suggests that the expression of major known CFTR-interacting proteins is altered. This may result in the disturbance of potential macrocomplexes involved in ion transport, inflammation, and/or protein trafficking. The results will be discussed in the context of all direct protein interactions described in the BioGrid database (i.e. 110 proteins found to interact physically with CFTR on the first or second degree will be analyzed by statistical learning and topological methods). Altogether, the data from experimental and in silico analyses indicate that the formation of dynamic macrocomplexes with or without CFTR is fundamental for an appropriate cell response to inflammation. This further indicates the necessity for studies on CFTR-related spatio-temporary protein-protein interactions at a large scale.

EPrint Type:Conference or Workshop Item (Talk)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:5270
Deposited By:farida zehraoui
Deposited On:24 March 2009