Systems Biology Of Stem Cell Fate And Cellular Reprogramming Pdf
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Cellular reprogramming has been recently intensively studied experimentally. We developed a global potential landscape and kinetic path framework to explore a human stem cell developmental network composed of 52 genes. We uncovered the underlying landscape for the stem cell network with two basins of attractions representing stem and differentiated cell states, quantified and exhibited the high dimensional biological paths for the differentiation and reprogramming process, connecting the stem cell state and differentiated cell state.
Understanding and engineering chromatin as a dynamical system. In press at Cell Systems. Wang, N.
Systems biology of stem cell fate and cellular reprogramming
Human pluripotent stem cells hold great promise for developments in regenerative medicine and drug design. The mathematical modelling of stem cells and their properties is necessary to understand and quantify key behaviours and develop non-invasive prognostic modelling tools to assist in the optimisation of laboratory experiments. Here, the recent advances in the mathematical modelling of hPSCs are discussed, including cell kinematics, cell proliferation and colony formation, and pluripotency and differentiation. Human pluripotent stem cells hPSCs have the ability to self-renew indefinitely through repeated divisions mitosis and can differentiate into any bodily cell type the pluripotency property. The latter property underpins their promising clinical applications in drug discovery, cell-based therapies and personalised medicine [ 1 , 2 ]. Amongst others, cardiomyocytes [ 3 ], pancreatic cells [ 4 ] and corneal cells [ 5 ] have all been successfully created from hPSCs.
The application of Systems Biology approaches to Stem Cell research is becoming more and more necessary in order to address a variety of fundamental questions in this field. In particular, the identification of optimal sets of genes, whose perturbations can trigger specific cellular transitions, remains a challenge in the application of cellular reprogramming and differentiation strategies to regenerative medicine. In this talk, I will present computational approaches developed in our lab, which are based on cellular network models for the identification of cellular transition-dependent reprogramming and cell fate determinant genes. Our computational predictions have been experimentally validated in different cellular systems. Furthermore, this novel approach systematically makes these predictions without prior knowledge of potential candidate genes and pathways involved, providing guidance on systems where little is known.
Metrics details. Heterogeneous gene expressions of cells are widely observed in self-renewing pluripotent stem cells, suggesting possible coexistence of multiple cellular states with distinct characteristics. Though the elements regulating cellular states have been identified, the underlying dynamic mechanisms and the significance of such cellular heterogeneity remain elusive. We present a gene regulatory network model to investigate the bimodal Nanog distribution in stem cells. Our model reveals a novel role of dynamic conversion between the cellular states of high and low Nanog levels. Model simulations demonstrate that the low-Nanog state benefits cell differentiation through serving as an intermediate state to reduce the barrier of transition. Interestingly, the existence of low-Nanog state dynamically slows down the reprogramming process, and additional Nanog activation is found to be essential to quickly attaining the fully reprogrammed cell state.
Stem cell differentiation and the maintenance of self-renewal are intrinsically complex processes. They require the coordinated and dynamic.
Stem Cell Res. Online ahead of print. The pioneer and differentiation factor FOXA2 is a key driver of yolk-sac tumour formation and a new biomarker for paediatric and adult yolk-sac tumours. J Cell Mol Med.
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