We aim to study the steady-state cell size distribution of a population of E. coli cells, integrating information collected at the individual scale. To that extent, we propose a stochastic individual-based dynamic model which can be calibrated using temporal single-cell lineage data acquired via micro˛uidic techniques. In particular, this data also grants access to the age structure, which then can be used to to provide a more precise non-Markovian characterisation of the growing population. Using probabilistic techniques, we prove the exponential convergence of the expected value of our stochastic process towards the unique stationary distribution, which can also be observed in real time in the data. A brief heuristic idea of the sufficient criteria for convergence which were used are discussed. We finally compare the predicted distributions to empirical distributions issued from macroscopic observations to validate the proposed micro-to-macro links for healthy and perturbed bacterial populations under different growing conditions.
By Nick Barton
By Quentin Griette
By Ada Altieri
By Mete Demircigil
By Elisa Thébault
By Sebastian Schreiber
By Jean-François Arnoldi
By Michael Scott
By Florence Bansept
By Apolline Louvet
By Aliene MacPherson
By Vincent Bansaye
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By Raphael Forien
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By Léo Girardin
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By Mikhail Gromov
By Mikhail Gromov
By Mikhail Gromov
By Vasilis Dakos
