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Transient and stochastic dynamics in cellular processes

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Transient and stochastic dynamics in cellular processes

Pau Rué Queralt, Presentation date: July 25, 2013

Author: Pau Rué Queralt
Title: Transient and stochastic dynamics in cellular processes.
Director: J. García-Ojalvo
Presentation date: July 25, 2013
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Abstract: This Thesis studies different cellular and cell population processes driven by non-linear and stochastic dynamics. The problems addressed here gravitate around the concepts of transient dynamics and relaxation from a perturbed to a steady state. In this regard, in all processes studied, stochastic fluctuations, either intrinsically present in or externally applied to these systems play an important and constructive role, by either driving the systems out of equilibrium, interfering with the underlying deterministic laws, or establishing suitable levels of heterogeneity. The first part of the Thesis is committed the analysis of genetically regulated transient cellular processes. Here, we analyse, from a theoretical standpoint, three genetic circuits with pulsed excitable dynamics. We show that all circuits can work in two different excitable regimes, in contrast to what was previously speculated. We also study how, in the presence of molecular noise, these excitable circuits can generate periodic polymodal pulses due to the combination of two noise induced phenomena: stabilisation of an unstable spiral point and coherence resonance. We also studied an excitable genetic mechanism for the regulation of the transcriptional fluctuations observed in some pluripotency factors in Embryonic Stem cells. In the embryo, pluripotency is a transient cellular state and the exit of cells from it seems to be associated with transcriptional fluctuations. In regard to pluripotency control, we also propose a novel mechanism based on the post-translational regulation of a small set of four pluripotency factors. We have validated the theoretical model, based on the formation of binary complexes among these factors, with quantitative experimental data at the single-cell level. The model suggests that the pluripotency state does not depend on the cellular levels of a single factor, but rather on the equilibrium of correlations between the different proteins. In addition, the model is able to anticipate the phenotype of several mutant cell types and suggests that the regulatory function of the protein interactions is to buffer the transcriptional activity of Oc4, a key pluripotency factor. In the second part of the Thesis we studied the behaviour of a computational cell signalling network of the human fibroblast in the presence of external fluctuations and signals. The results obtained here indicate that the network responds in a nontrivial manner to background chatter, both intrinsically and in the presence of external periodic signals. We show that these responses are consequence of the rerouting of the signal to different network information-transmission paths that emerge as noise is modulated. Finally, we also study the cell population dynamics during the formation of microbial biofilms, wrinkled pellicles of bacteria glued by an extracellular matrix that are one of the simplest cases of self-organised multicellular structures. In this Thesis we develop a spatiotemporal model of cellular growth and death that accounts for the experimentally observed patterns of massive bacterial death that precede wrinkle formation in biofilms. These localised patterns focus mechanical forces during biofilm expansion and trigger the formation of the characteristic ridges. In this sense, the proposed model suggests that the death patterns emerge from the mobility changes in bacteria due to the production of extracellular matrix and the spatially inhomogeneous cellular growth. An important prediction of the model is that matrix productions is crucial for the appearance of the patterns and, therefore for winkle formation. We have also experimentally validated validated this prediction with matrix deficient bacterial strains, which show neither death patterns nor wrinkles.