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Contents 1 Introduction 2 Proof of principle 2.1 Can such a system work? 2.2 Can it work on a lawn of bacteria? 2.3 And for a growing culture? 3 Is the behavior robust? 3.1 do molecular details change something? 3.2 Even with stochasticity? 4 Conclusion 5 Tools 5.1 Biocham 5.2 MGS 6 Source of the models

Introduction

Proof of principle

Those models are at macroscopic scale. They are focused on the evolution of the population, with global rules avoiding description of all the microscopic mechanisms. We present tree different works, with different approaches (ODE, automaton)...

Can such a system work?

We present here a theoretical approach based on population dynamics. We consider here the case of a well mixed, homogeneous, culture of the SMB organism, i.e. there is no space in this analysis and we follow only the variation of the different cell lines concentrations in the culture volume.

Can it work on a lawn of bacteria?

We want with this work to characterize the diffusion of the DAP and the effect on the cells. We have a lawn of bacteria with germinal cells and some somatic cells.

And for a growing culture?

We try with this model to see the effect of DAP on the cells. We have a growing culture with germinal cells and somatic cells. We want to see if we can have different kinds of evolution for our cells. as we can see in the simple automaton the diffusion mechanism and the effect on differentiation can be describe more accurately, so for the moment we just ignore the diffusion putting a black box on it and just focused on the total number of DAP entities.

Is the behavior robust?

Those models considered here are at microscopic scale. They are focused on the description of the microscopic mechanisms like exportation, diffusion, mechanism of differentiation... We present two different works, with different approaches (ODE, Gillespie)...

do molecular details change something?

This model aims at describing the dynamic evolution of populations of germen and soma type bacteria. It is based on a set of differential equations describing DAP synthesis, DAP transport, differentiation of germen bacteria into soma and bacteria death. This approach differs form the precedents one by the level of description of the model and the numerical analysis done on the model.

Even with stochasticity?

Conclusion

Tools

For our simulations we used unusual tools, Biocham and MGS. Thanks to their specificities and capacities, we were able to simulate easily the mechanisms that we wanted to focus on.

Biocham

MGS

Source of the models