Ruolo, Iacopo (2023) Elucidation of TFEB nuclear translocation dynamics in human cells by means of Quantitative Modelling and Microfluidics. [Tesi di dottorato]
Anteprima |
Testo
Ruolo_Iacopo_35.pdf Download (3MB) | Anteprima |
Tipologia del documento: | Tesi di dottorato |
---|---|
Lingua: | English |
Titolo: | Elucidation of TFEB nuclear translocation dynamics in human cells by means of Quantitative Modelling and Microfluidics |
Autori: | Autore Email Ruolo, Iacopo iacoporuolo@gmail.com |
Data: | 7 Maggio 2023 |
Numero di pagine: | 128 |
Istituzione: | Università degli Studi di Napoli Federico II |
Dipartimento: | Ingegneria Chimica, dei Materiali e della Produzione Industriale |
Dottorato: | Ingegneria dei prodotti e dei processi industriali |
Ciclo di dottorato: | 35 |
Coordinatore del Corso di dottorato: | nome email D'Anna, Andrea andrea.danna@unina.it |
Tutor: | nome email di Bernardo, Diego [non definito] |
Data: | 7 Maggio 2023 |
Numero di pagine: | 128 |
Parole chiave: | TFEB, Systems Biology, Control Engineering |
Settori scientifico-disciplinari del MIUR: | Area 09 - Ingegneria industriale e dell'informazione > ING-IND/34 - Bioingegneria industriale |
Depositato il: | 21 Mar 2023 09:28 |
Ultima modifica: | 09 Apr 2025 13:16 |
URI: | http://www.fedoa.unina.it/id/eprint/15020 |
Abstract
Mammalian cells are dynamic systems capable of detecting, adjusting and responding to time-varying inputs. Transcriptional regulatory networks, which are important for directing cell homeostasis response to environmental stimuli, acquire information about the extracellular and intracellular environments via signaling pathways, which are critical in cell state regulation. The nucleo-cytoplasmic shuttling of transcription factors allows the cell to control how genes are expressed in response to its environment. The Transcription Factor EB (TFEB) has recently been discovered as a master regulator in the transcriptional control of lysosomal biogenesis and autophagy in response to starvation. The kinase mTOR controls TFEB activity. In nutrient-rich conditions, mTOR sequesters TFEB in the cytoplasm and phosphorylates it there. Unphosphorylated TFEB translocates into the nucleus and controls the expression of its target genes when mTOR is suppressed during starvation. The purpose of this Thesis is to characterize the dynamics of TFEB nuclear shuttling on the basis of experimental and computational investigations, in line with the general framework of Systems Biology. Specifically, I took advantage of the experimental data to study the nuclear localisation of TFEB in real time on individual cells growing in two complementary microfluidics-based platforms. Following starvation, TFEB translocates to the nucleus but later partially relocalises to the cytoplasm, exhibiting a previously unknown "overshoot" dynamic. These experimental features were then employed in the subsequent modelling efforts aiming at discriminating among alternative hypotheses that most likely explain the experimental results, and thus help determine the mechanism that is responsible for the observed shuttling dynamics. The results suggest that Calcium-Calcineurin signaling drives TFEB overshoot dynamic. In this Thesis, I will introduce the Systems Biology fundamentals and I will review TFEB signalling in Chapter 1; I will then describe the technological experimental platform in Chapter 2. Here, I will also provide details on the methods used to conduct experimental and computational analyses, including the image analysis algorithms and the modelling approach. Chapters 3 and 4 will represent the body of the Thesis. Particularly, I will focus on the experimental data in the former (Chapter 3), starting with the preliminary data that revealed the overshoot dynamics, and consequently I will explain the experiments that followed and that were based on the suppression of critical TFEB signaling regulators to identify the source of this novel mechanism. In Chapter 4, I will investigate and explore in silico the role of each individual reaction involved in TFEB nuclear shuttling which has been reported in literature and derive the optimal model based on the preexisting literature to recapitulate the experimental features. Finally, in Chapter 5, I will provide some concluding remarks on future studies to empirically verify the computational results I obtained.
Downloads
Downloads per month over past year
Actions (login required)
![]() |
Modifica documento |