The principles of automation (automatism and programming) in the unfolding of spatio-temporal patterns during animal development are deduced from experimental data reconsidered from the point of view of cell sociology. The developmental programme in the egg is not part of the genetic information but a part of the cytoplasmic information. Throughout development cells store extra-cellular information released by their neighbours in the form of cytoplasmic information. Successive determinations cannot be considered as successive reprogrammings of cells: each one consists of a (...) selection of one specific programme from the total information previously stored. This programme specifies cell interactions in the determined population as a whole; it is very imprecise and is progressively completed during the course of further differentiation by information released by neighbouring cell populations. Complicated patterns may emerge from only two homogeneous populations involved in distinct differentiation pathways and confronting each other. Consequently the egg developmental programme provides gene effectors and specific physico-chemical conditions necessary for the starting of at least two distinct differentation pathways. Experimental data suggest that there are two components in this programme. One is a molecular machinery which starts at fertilization in the whole cytoplasm. It yields two programmes of differentiation, typically first an endodermal and then an ectodermal one. The other component of the egg developmental programme, which does not require specific information, allows the interception of the first (endodermal) programme. The application of informatics to developmental automatism is discussed in the latter part of the paper. (shrink)

The principles of automation in animal development, as previously inferred from the concept of Cell Sociology do not fit in well with the current concept of sequential gene derepression. A more adequate explanation for those principles has been found in the literature dealing with the biochemical aspects of differentiation. Since oocytes and embryonic cells contain a greater variety of mRNAs than differentiated cells, as well as many tissue-specific (luxury) substances, it is concluded that the diversification of tissues consists of a (...) progressive selection of specific metabolic strategies, mediated by cell-to-cell contacts, from a broad range of pre-existing strategies. For each tissue, prior to its final determination, one luxury metabolic strategy is progressively intensified and becomes dominant. The others are either suppressed or maintained as latent metabolic strategies. The latter may on occasion become dominant again (transdifferentiation). These phenomena require a theory which considers gene regulation as the activation of otherwise repressed genes by specific activator RNAs. The high (apparently maximal) transcriptional activity on the lampbrush chromosomes may represent the synthesis of all the kinds of activator RNAs which are required for the reactivation of the genes during early development. A general conception is propounded of the automatism and programming of animal development, as inferred from the confrontation of these ideas with the concept of Cell Sociology. (shrink)

Despite the recent progress in the description of the molecular mechanisms of proliferation and differentiation controls in vitro, the regulation of the homeostasis of normal stratified epithelia remains unclear in vivo. Computer simulation represents a powerful tool to investigate the complex field of cell proliferation regulation networks. It provides huge computation capabilities to test, in a dynamic in silico context, hypotheses about the many pathways and feedback loops involved in cell growth and proliferation controls.Our approach combines a model of cell (...) proliferation and a spatial representation of cells in 2D using the Voronoi graph. The cell proliferation model includes intracellular (cyclins, Cyclin Dependent Kinases - CDKs, Retinoblastoma protein - Rb, CDK inhibitors) and extracellular controls (growth and differentiation factors, integrins). The Voronoi graph associates a polygon with every cell and the set of these polygons defines the tissue architecture. Thus, the model provides a quantitative model of extracellular signals and cell motility as a function of the neighborhood during time dependent simulations. (shrink)