Skip to Main content Skip to Navigation
Theses

Modélisation mathématique de la dégradation des ARNm bactériens et intégration de données omiques

Thibault Étienne 1, 2
2 IBIS - Modeling, simulation, measurement, and control of bacterial regulatory networks
LAPM - Laboratoire Adaptation et pathogénie des micro-organismes [Grenoble], Inria Grenoble - Rhône-Alpes, Institut Jean Roget
Abstract : Adaptation of bacterial physiology to environment involves regulations of gene expression. The control of mRNA concentrations is one of them. It results from a balance between mRNA transcription and degradation rates. While these two mechanisms are well-studied at the molecular level in Escherichia coli, their contributions to transcript levels at the genome-wide level remain poorly understood. The emergence of dynamic omics data opens up new opportunities to better understand the regulation of mRNA degradation in response to environmental changes. This mass of omics data is often under-utilised. Approaches without a priori are generally used to analyse these data. However, computational cost reduction and knowledge advancements about bacterial mRNA degradation and both mechanistic and statistical modelling should permit deeper investigations. In this work, different approaches to model and analyse dynamic transcriptomic data previously obtained by T. Esquerré in E.coli are approached with the angle of systems biology. The idea is to extend past work on the subject with mathematical and statistical modelling to push further our understanding of this biological problem. More precisely, a mechanistic model of bacterial mRNA degradation was created. This model allows to establish the key role of competition between mRNAs in the variability of mRNA stability and the occurrence of delays before degradation. A statistical methodology based on non-linear mixed-effect models was adapted to the mechanistic model and tested for the estimation of model parameters from dynamic omics data. Biological interpretation of the estimated parameters shows the pivotal role of competition in tuning mRNA stability through the tight coupling of mRNA degradation to transcription. This is a new global regulatory mechanism of mRNA decay. Sole 10% of mRNAs are regulated by additional factors such as small RNAs
Document type :
Theses
Complete list of metadata

https://tel.archives-ouvertes.fr/tel-03306903
Contributor : Abes Star :  Contact
Submitted on : Thursday, July 29, 2021 - 1:40:10 PM
Last modification on : Wednesday, August 25, 2021 - 9:33:13 AM

File

TH2020ETIENNETHIBAULT.pdf
Version validated by the jury (STAR)

Identifiers

  • HAL Id : tel-03306903, version 1

Collections

Citation

Thibault Étienne. Modélisation mathématique de la dégradation des ARNm bactériens et intégration de données omiques. Statistiques [math.ST]. Université de Lyon, 2020. Français. ⟨NNT : 2020LYSE1271⟩. ⟨tel-03306903⟩

Share

Metrics

Record views

49

Files downloads

194