Ressource pédagogique : Dr Guido Santos - Multi-level computational modeling as a tool to understand molecular mechanisms behind bacterial lung infection

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Pneumonia is one of the most prevalent infectious diseases worldwide, whose main cause is the pathogen Streptococcus pneumoniae. This is an opportunistic disease affecting the most to sensitive groups (infants, elderly and immunosuppressed people). In these patients the inflammatory response generated in the lungs is the main risk factor that happens in the very first days of infection. Under this situation the main goal is finding therapeutical or preventive strategies that are able to cut the inflammatory response as soon as possible.  In order to identify possible molecular targets to focus on this early phase of infection we propose a computational approach to simulate the very first stages of the pneumococcal infection happening in a single alveolus. In vivo experiments at this level are unpracticable with the current technology, which makes in silico strategies the best approach. We created a multi-level mathematical model that combines the intracellular signalling pathways and the cellular interactions that play a role during the early stages of pneumococcal alveolar infection. By systematic perturbations of the model we obtained a high number of solutions that we analysed. The results of the analysis of the simulations predict two main processes that could control the establishment of the infection in the alveolus. Bacterial proliferation and bacterial adherence together can predict the evolution of the early phases of the pneumococcal infection.

"Domaine(s)" et indice(s) Dewey

• Maladies des poumons (hypertension artérielle pulmonaire, hypertension pulmonaire, maladie obstructive respiratoire chronique, maladies respiratoires, ouvrages généraux sur les maladies des bronches et des poumons) (616.24)

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