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Understanding individual heterogeneity in ageing from stochastic dynamics of sigma factor regulatory network in bacteria

Project description

Gaining insight into ageing from bacterial transcriptional regulation

Sigma factors are the main constituents of transcription regulation in bacteria, playing a key role in gene expression regulation in response to environmental changes. They could provide insight into heterogeneity in ageing among individuals, going beyond bacteria and observed in diverse populations including humans. Scientific understanding of the molecular control of ageing via genetic and metabolic pathways does not fully explain this heterogeneity demonstrated by different ageing rates and patterns and even observed with fixed genetics and environment. With the support of the Marie Skłodowska-Curie Actions programme, the ASNet project will combine high-tech experimental techniques with mathematical modelling to elucidate the roles and mechanisms of four sigma factors in ageing processes of individual bacterial cells.

Objective

Ageing is controlled at the molecular level via genetic and metabolic pathways. Ageing rates and patterns vary substantially even with fixed genetics and environment. However, molecular mechanisms of ageing generating individual heterogeneity are poorly understood. Stochastic dynamics of gene expression can be a main source of the variation in cellular damage dynamics leading to individual heterogeneity in ageing. The sigma factor regulatory networks constitute the core part of the bacterial gene expression networks and therefore play important role in deciding the fate of bacterial cells. In this project, I focus on exploring the role and interplays of four major sigma factors rpoD, rpoS, rpoH, rpoN in individual E. coli cells. I plan to (1) obtain these sigma factors’ expression dynamics and the demographic fates at individual E. coli cells in microfluidic platforms under fluorescent microscope; (2) process and analyze big image data in an automated manner; (3) develop mathematical models to interpret expression and demographic signals for damage and ageing. I will combine the knowledge and methods from the disciplines of molecular biology, genetics, fluorescent microscopy and microfluidics, machine learning, population and evolutionary dynamics and mathematical modelling to shed light on the link from stochastic expression dynamics in sigma factor regulatory network towards individual variations observed in ageing fates.

Coordinator

FREIE UNIVERSITAET BERLIN
Net EU contribution
€ 189 687,36
Address
KAISERSWERTHER STRASSE 16-18
14195 Berlin
Germany

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Region
Berlin Berlin Berlin
Activity type
Higher or Secondary Education Establishments
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Total cost
No data