Reaction-Diffusion Modeling of E. coli Colony Growth Based on Nutrient Distribution and Agar Dehydration.

The bacterial colony is a powerful experimental platform for broad biological research, and reaction-diffusion models are widely used to study the mechanisms of its formation process. However, there are still some crucial factors that drastically affect the colony growth but are not considered in the current models, such as the non-homogeneously distributed nutrient within the colony and the substantially decreasing expansion rate caused by agar dehydration. In our study, we propose two plausible reaction-diffusion models (the VN and MVN models) based on the above two factors and validate them against experimental data. Both models provide a plausible description of the non-homogeneously distributed nutrient within the colony and outperform the classical Fisher-Kolmogorov equation and its variation in better describing experimental data. Moreover, by accounting for agar dehydration, the MVN model captures how a colony's expansion slows down and the change of a colony's height profile over time. Furthermore, we demonstrate the existence of a traveling wave solution for the VN model.

A Predictive Reaction-diffusion Based Model of E.coli Colony Growth Control.

Bacterial colony formations exhibit diverse morphologies and dynamics. A mechanistic understanding of this process has broad implications to ecology and medicine. However, many control factors and their impacts on colony formation remain underexplored. Here we propose a reaction-diffusion based dynamic model to quantitatively describe cell division and colony expansion, where control factors of colony spreading take the form of nonlinear density-dependent function and the intercellular impacts take the form of density-dependent hill function. We validate the model using experimental E. coli colony growth data and our results show that the model is capable of predicting the whole colony expansion process in both time and space under different conditions. Furthermore, the nonlinear control factors can predict colony morphology at both center and edge of the colony.

PIM1 kinase as a promise of targeted therapy in prostate cancer stem cells.

Since the last decade, the PIM family serine/threonine kinases have become a focus in cancer research. Numerous clinical data supports that overexpression of PIM1 is associated with tumor formation in various tissues. However, little is known regarding the function of PIM1 in cancer stem cells. In cancer cells, PIM1 has essential roles in the regulation of the cell cycle, cell proliferation, cell survival and multiple drug resistance. In stem cells, PIM1 kinase exhibits a significant function in stem cell proliferation, self-renewal and expansion. Thus, PIM1 shows a great promise in cancer therapy by targeting stem cells. Furthermore, it is imperative to investigate Pim-1 targeting in cancer stem cells by applicable inhibitors for improving future outcomes. The present review investigated the potential of PIM1 as a therapy target in prostate cancer stem cells.