Influence of the existence of a resting state on the decay of synchronization in cell culture

Analysis of Western diet, palmitate and BMAL1 regulation of neuropeptide Y expression in the murine hypothalamus and BMAL1 knockout cell models

Western diets that are high in saturated fat and sugar disrupt circadian rhythms, induce weight gain, and lead to metabolic diseases including obesity. However, the mechanistic link between altered circadian rhythms and energy homeostasis remains poorly understood. In C57BL/6J mice, consuming a Western diet for 16 weeks significantly reduced food intake (at zeitgeber 12-16), in association with decreases in hypothalamic expression of the orexigenic neuropeptides, neuropeptide Y (Npy) and agouti-related peptide (AgRP). To examine the acute effects of the most prevalent saturated fatty acid in a Western diet, palmitate, and the role of the core clock gene, Bmal1, in the regulation of hypothalamic feeding neuropeptides, we used heterogeneous and clonal BMAL1 knockout (KO) immortalized hypothalamic cell lines, expressing specific neuropeptides, derived from male (M) and female (F) mice. Both mHypoA-BMAL1-KO/F and mHypoA-BMAL1-KO/M cells demonstrated a loss of circadian rhythmicity in expression of the clock gene, Per2, as compared to wild-type (control) cultures. Loss of BMAL1 also altered the time-dependent expression of Npy and proopiomelanocortin, and disrupted AgRP rhythmicity. Furthermore, palmitate increased BMAL1 binding to the Npy promotor region, and palmitate treatment (50 μM for 24 h) stimulated Npy expression in a BMAL1-dependent manner in both heterogeneous and clonal NPY-expressing female-derived cell models. The results of this study demonstrate that circadian expression of Bmal1 serves as a mechanistic link between Western diet- and palmitate-induced disruptions of the normal rhythmic patterns in hypothalamic feeding-related neuropeptides.

Heterogeneous structure of stem cells dynamics: statistical models and quantitative predictions

Understanding stem cell (SC) population dynamics is essential for developing models that can be used in basic science and medicine, to aid in predicting cells fate. These models can be used as tools e.g. in studying patho-physiological events at the cellular and tissue level, predicting (mal)functions along the developmental course, and personalized regenerative medicine. Using time-lapsed imaging and statistical tools, we show that the dynamics of SC populations involve a heterogeneous structure consisting of multiple sub-population behaviors. Using non-Gaussian statistical approaches, we identify the co-existence of fast and slow dividing subpopulations, and quiescent cells, in stem cells from three species. The mathematical analysis also shows that, instead of developing independently, SCs exhibit a time-dependent fractal behavior as they interact with each other through molecular and tactile signals. These findings suggest that more sophisticated models of SC dynamics should view SC populations as a collective and avoid the simplifying homogeneity assumption by accounting for the presence of more than one dividing sub-population, and their multi-fractal characteristics.

Three-dimensional cell cycle model with distributed transcription and translation

A computational cell cycle model that can describe three state properties, cell maturation age, specific mRNA and protein content, has been developed. Cell cycle progression is monitored by maturation age, and population heterogeneity is generated by the introduction of a probable random event embedded in the G1 phase. Specific mRNA is generated with a constant transcription rate at the single-cell level, and its turnover is governed by a first-order decay. Translation is modelled as a first-order dependence on the transcripts, and the protein product is subsequently exported. Dynamic chemostat simulations are used to demonstrate the ability of the model to track evolving parent and daughter subpopulations in maturation and cellular contents. The cell subpopulations eventually converge to an equilibrium distribution corresponding to the steady state of a chemostat, and halving of cellular content at cell division is the dominant driving force leading towards the population equilibrium state.

Modeling stem cell population growth: incorporating terms for proliferative heterogeneity

Expansion of the undifferentiated stem cell phenotype is one of the most challenging aspects in stem cell research. Clinical protocols for stem cell therapeutics will require standardization of defined culture conditions. A first step in the development of predictable and reproducible, scalable bioreactor processes is the development of mathematical growth models. This paper provides practical models for describing cell growth in general, which are particularly well suited for examining stem cell populations. The nonexponential kinetics of stem cells derive from proliferative heterogeneity, which is biologically recognized as mitosis, quiescence, senescence, differentiation, or death. Here, we examined the assumptions of the Sherley model, which describes heterogeneous expansion in the absence of cell loss. We next incorporated terms into the model to account for A) cell loss or apoptosis and B) cell differentiation. We conclude that the basic assumptions of the model are valid and a high correlation between the modified equations and experimental data obtained using muscle-derived stem cells was observed. Finally, we demonstrate an improved estimation of the kinetic parameters. This study contributes to both the biological and mathematical understanding of stem cell dynamics. Further, it is expected that the models will prove useful in establishing standardization of cell culture conditions and scalable systems and will be required to develop clinical protocols for stem cell therapeutics.