Descrizione del progetto
La fisica statistica fornisce informazioni approfondite sugli stati delle cellule stressate
Le cellule comprendono microambienti estremamente complessi, con interazioni multiple che si verificano simultaneamente tra tutti i componenti. Ciò rende sempre più difficile l’applicazione di metodi statistici per valutare il comportamento cellulare. Il progetto StatCell, finanziato dall’UE, si propone di superare questa sfida introducendo un quadro sperimentale e teorico per la descrizione, sotto il profilo della fisica statistica, di cellule soggette a forte stress. Combinando rivoluzionarie tecniche di biologia cellulare, StatCell consentirà di identificare le condizioni di rete cellulare che possono essere previste a livello quantitativo mediante un quadro di fisica statistica. Il lavoro del progetto fornirà significative informazioni in relazione ai meccanismi cellulari nell’invecchiamento e nella malattia.
Obiettivo
Statistical physics successfully accounts for phenomena involving a large number of components using a probabilistic approach with predictions for collective properties of the system. While biological cells contain a very large number of interacting components, (proteins, RNA molecules, metabolites, etc.), the cellular network is understood as a particular, highly specific, choice of interactions shaped by evolution, and therefore not amenable to a statistical physics description. My premise is that when a cell encounters an acute, but non-lethal, stress, its perturbed state can be modelled as random network dynamics, rather than as a regulated response. Strong perturbations may therefore reveal the dynamics of the underlying network that are amenable to a statistical physics description. Based on the striking similarity between our data on stressed bacteria and physical aging in disordered systems, my goal is to develop an experimental and theoretical framework for the statistical physics description of cells exposed to strong perturbations. We will critically probe the predictions of the statistical model using a multidisciplinary approach combining three frontline methodologies: (1) dynamics of single bacteria under acute stress in microfluidic devices and single cell transcriptomics; (2) theoretical framework and simulations for cellular networks under acute stress; and (3) new biophysical measurements of the transition from the regulated to the disrupted cellular network. This approach should provide a paradigm shift in the analysis of cells under stress, differentiating between conditions described by the regulation of gene networks from those that can be quantitatively predicted by a statistical physics framework. The new knowledge should lead to innovative ways of controlling the cellular network under strong perturbations, with implications ranging from new methodologies for synthetic biology to new avenues for treating bacterial infections and cancer.
Campo scientifico
- natural sciencesbiological sciencesmicrobiologybacteriology
- natural sciencesbiological sciencessynthetic biology
- engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationstelecommunications networksmobile network
- natural sciencesmathematicsapplied mathematicsstatistics and probability
- natural sciencesbiological sciencesgeneticsRNA
Programma(i)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Argomento(i)
Meccanismo di finanziamento
HORIZON-AG - HORIZON Action Grant Budget-BasedIstituzione ospitante
91904 Jerusalem
Israele