Studying the variability ofbacterial growth in microfluidicdroplets

Abstract : This thesis presents some results about the variability of the growth of bacteria in microfluidics droplets. In the first chapter, the microfluidic chip used throughout the PhD is presented. It allows to encapsulate bacteria in an array of 1.500 nano-liter sized droplets, and to follow their growth in each droplet in parallel through fluorescence microscopy. The link between the measured fluorescence and the number of bacteria in a droplet is discussed, and other technical questions are addressed, such as the variability in droplet size and the cell-to-cell fluorescence variability. Next, we develop a stochastic model to account for the observed variability of population size in the droplet during the exponential phase of growth. A well-known stochastic model, the Bellman-Harris model, is adapted to take into account the external sources of randomness due to our experimental system (initial distribution of bacteria per droplet, different division time of the first generations). They are taken into account, along with the effects of the cell-to-cell variability of division times in our model, which is successful to predict the variability observed in the microfluidics experiments. Then we tackle the inverse problem, which is to recover the cell-to-cell variability from the observation of the growth in droplets. We propose an inference scheme based on following each droplet in time. The deviation from pure exponential growth is linked back to the cell-to-cell variability, and this inference scheme is proven to be successful on simulations that mimic the experimental constrains. However, we cannot completely apply it to our experiments because of a lack of accuracy in our fluorescence measurements. Finally, we demonstrate how our chip can represent a gain of space and time to quantify the effect of antibiotics on a bacterial strain compared to classical susceptibility measurement methods. We also show how it can be used to study the variability of the SOS response of bacteria, which is a bacterial stress response induced when the DNA of the cell is damaged, and relate it to the ability to survive an antibiotic treatment.
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Antoine Barizien. Studying the variability ofbacterial growth in microfluidicdroplets. Bioinformatics [q-bio.QM]. Université Paris-Saclay, 2019. English. ⟨NNT : 2019SACLX020⟩. ⟨tel-02168120⟩

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