Postiglione, Lorena (2017) Feedback Control of Gene Expression in Mammalian Cells. [Tesi di dottorato]

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Tipologia del documento: Tesi di dottorato
Lingua: English
Titolo: Feedback Control of Gene Expression in Mammalian Cells
Autori:
AutoreEmail
Postiglione, Lorenalorena.postiglione@unina.it
Data: 7 Aprile 2017
Numero di pagine: 133
Istituzione: Università degli Studi di Napoli Federico II
Dipartimento: Ingegneria Elettrica e delle Tecnologie dell'Informazione
Dottorato: Information technology and electrical engineering
Ciclo di dottorato: 29
Coordinatore del Corso di dottorato:
nomeemail
Riccio, Danieledaniele.riccio@unina.it
Tutor:
nomeemail
di Bernardo, Diego[non definito]
Data: 7 Aprile 2017
Numero di pagine: 133
Parole chiave: Control Theory; System Identification; Gene Expression; Synthetic Biology; Mammalian Cells
Settori scientifico-disciplinari del MIUR: Area 09 - Ingegneria industriale e dell'informazione > ING-IND/34 - Bioingegneria industriale
Area 09 - Ingegneria industriale e dell'informazione > ING-INF/04 - Automatica
Depositato il: 09 Mag 2017 14:44
Ultima modifica: 08 Mar 2018 13:36
URI: http://www.fedoa.unina.it/id/eprint/11615
DOI: 10.6093/UNINA/FEDOA/11615

Abstract

Mammalian cells are dynamical systems. They detect, adapt and respond to time-varying inputs such as environmental cues, secreted molecules, and mechanical stimuli. These processes are controlled by networks of genes, proteins, small molecules, and their mutual interactions, the so-called gene regulatory networks, showing complex topologies. Understanding how these networks work is essential to identify triggering events both in common disease as well as in rare genetic disorders. Control Theory makes available several tools that can be applied to explore the mechanisms driving gene networks. Although recently several successful attempts to apply the Control Theory to steer gene expression from inducible promoters have been obtained in lesser eukaryotes, the application of control engineering to mammalian cells is still in its infancy because of complexity and the limited knowledge of their transcriptional networks. This Thesis is involved in this challenging topic. I propose the study and the in vitro implementation of feedback control strategies based on microfluidic platform aimed to precisely regulate the level of expression of a protein from the tetracycline inducible promoter in mammalian cells. This control approach allows to express a protein of interest at different levels or in a time-varying fashion from the same promoter and can be a unique tool for several applications, including studying the effects of gene dosage in disease, probing the function of endogenous regulatory networks, and for synthetic biology applications.

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