Mathematical modelling of transcriptional network of liver regeneration

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Centre for Computational Natural Sciences and Bioinformatics, IIIT Hyderabad
"Mathematical modelling of transcriptional network of liver regeneration"
Tissue homeostasis and regeneration depend on the reversible transitions between quiescence (G0) and proliferation. The liver has a remarkable capacity to regenerate after injury or resection by cell growth and proliferation. During regeneration, the liver needs to maintain the essential metabolic tasks and meet the metabolic requirement for hepatocyte growth and division. In this work, we studied the crosstalk between cell cycle and metabolism during the liver generation after two-thirds partial hepatectomy (PH). First, we modeled the temporal gene expression data of liver regeneration using the Hidden Markov Model, which revealed the dynamic balance of metabolic and cell cycle genes in hepatocytes. We further developed a mathematical model of the transcriptional network of liver regeneration, which explained the coordination of different events of liver regeneration. We demonstrate that mutual antagonism between the cell cycle and liver metabolic function makes the system bistable, which controls the initiation and termination of liver regeneration and different stable population-level expressions. This framework was also used to explain the transition to an uncontrolled proliferation state in Hepatocellular Carcinoma (HCC).

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