Toscano, Elvira (2023) Modelling cultured cell migration and proliferation by integrating a phenomenological and a molecular approach. [Tesi di dottorato]
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Tipologia del documento: | Tesi di dottorato |
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Lingua: | English |
Titolo: | Modelling cultured cell migration and proliferation by integrating a phenomenological and a molecular approach |
Autori: | Autore Email Toscano, Elvira elvira.toscano@unina.it |
Data: | 9 Marzo 2023 |
Numero di pagine: | 129 |
Istituzione: | Università degli Studi di Napoli Federico II |
Dipartimento: | Medicina Molecolare e Biotecnologie Mediche |
Dottorato: | Medicina molecolare e biotecnologie mediche |
Ciclo di dottorato: | 35 |
Coordinatore del Corso di dottorato: | nome email Santoro, Massimo massimo.santoro@unina.it |
Tutor: | nome email Paolella, Giovanni [non definito] |
Data: | 9 Marzo 2023 |
Numero di pagine: | 129 |
Parole chiave: | cell migration; cell cycle modelling; cell growth simulation |
Settori scientifico-disciplinari del MIUR: | Area 05 - Scienze biologiche > BIO/10 - Biochimica |
Depositato il: | 21 Mar 2023 10:34 |
Ultima modifica: | 10 Apr 2025 13:58 |
URI: | http://www.fedoa.unina.it/id/eprint/15162 |
Abstract
Cell cultures are a fundamental model system widely used to study the mechanisms involved in promoting and regulating cell proliferation and movement. Here we use a quantitative approach to study the behaviour of cultured cells by using models which reduce complex experimental observations to simpler systems, in which the contribution of different players may be more easily evaluated. Following this approach, cell culture experiments were analysed by using a new motion model, developed to accurately evaluate cell migration features, such as randomness, persistence and directional bias, even when present in more complex combinations. The model was used to study the role of MAPK pathway in cell movement and to generate, within an in-house developed simulation tool, synthetic cell populations able to reproduce the same movement features. The simulation was later improved by pairing it with a biochemical simulator based on ordinary differential equations (ODE), which provided the ability to finely regulate the behaviour of synthetic cells according to the state of signalling pathways such as EGFR/ERK. In order to support the hour-long simulations needed to emulate cell cycle progression, several novel aspects had to be implemented, including synthesis and degradation of many proteins and a link between molecular pathways and cell mass and volume growth. To reproduce the delay, not easily obtained with ODEs, but typically introduced by gene transcription and mRNA translation, new modules were developed which attain this goal while maintaining a good balance between complexity and execution time, on one side, and manageability and accuracy, on the other. In its present state, the developed system reproduces different experimental situations and opens up future perspectives for further cell proliferation and movement studies.
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