Résumé
During development, lineage committed cells undergo numerous cell divisions. Mitosis represents a challenge to the inheritance of transcriptional states.During mitosis, chromosomes become condensed, packed with nucleosomes and Pol II, whilst most transcription factors are expelled from this particularly hostile chromatin landscape. How a cell maintains transcriptional fidelity across cell divisions is a fundamental question in biology, in healthy organisms as well as for relentlessly dividing cancerous cells. It is now clear that not all traces of transcriptional activation or repression are erased during mitosis (Festuccia et al., Development 2017). Live imaging of transcription dynamics provides the extent to which transcriptional status is inherited between cell generations, a phenomenon called mitotic memory. Using this technique in Drosophila embryos, our team has recently visualized transcriptional memory for the first time in a multicellular organism (Ferraro et al., Curr Biol 2016). When a mother nucleus is transcriptionally active, its descendants have a higher probability to activate transcription in the following cycle, compared to descendants of inactive mothers. With this tool in hand, we now seek to employ a mathematical model of mitotic memory to be able to formulate hypotheses on the potential supports and timescales of this memory. Indeed the support of this mitotic memory could involve mitotic retention of transcription factors or epigenetic modification on histone tails (bookmarking). Because too long a memory would prevent activation of new genes or shut down of old ones when this is needed, mitotic memory should be short-term and the processes involved should be dynamic (Bellec, Radulescu, Lagha, Curr Opinion Sys Biol 2018). Of course, this does not preclude other forms of cellular memory that are long-term. Previous mathematical models developed by our team (Dufourt et al., Nat Com 2018) were based on Markov chains and described transcriptional activation by a small number of discrete limiting transitions. Here we derive a mitotic memory model from very general principles using statistical field theory. In our model, the cell's transcriptional state is represented as one of the attractors of a multistationary Phi4 model. Contrary to our previous Markov chain model, which does not cope with mitotic events, the new model is the first to describe memory transmission across multiple mitoses. In this model, we interpret mitosis using the general concept of symmetry breaking. Seen as such, our model provides the normal form for a whole class of mitotic memory models. We validate our model by using single nuclei data recording the inheritance of transcriptional states down cell lineages, in vivo. For this we employ the MS2/MCP technique and live imaging of developing early Drosophila embryos (Ferraro et al., 2016 Curr Biol; Dufourt et al., Nat Com 2018; Bellec et al., Nat Com 2022).