Threshold response and bistability in gene regulation by small noncoding RNA

Dynamical Mechanisms for Gene Regulation Mediated by Two Noncoding RNAs in Long-Term Memory Formation

Noncoding RNAs such as miRNAs and piRNAs have long-lasting effects on the regulation of gene expression involved in long-term synaptic changes. To characterize gene regulation mediated by small noncoding RNAs associated with long-term memory in Aplysia, we consider two noncoding RNAs stimulated by 5-HT into a gene regulatory network motif model, including miR-124 that binds to and inhibits the mRNA of CREB1 and piR-F that facilitates serotonin-dependent DNA methylation to lead to repression of CREB2. Codimension-1 and -2 bifurcation analyses of 5-HT regulating both miR-124 and piR-F and a negative feedback strength for oscillation reveal rich dynamical properties of bistability and oscillations robust to variations in all other parameters. More importantly, we verify three stimulus protocols of 5-HT in experiments by our model and find that application of five pulses of 5-HT leads to a transient decrease of miR-124 but increase of piR-F concentrations, which matters sustained high level of CREB1 concentration associated with long-term memory. Furthermore, we perform bifurcation analyses for the concentrations of miR-124 and piR-F as two parameters to explore dynamical mechanisms underlying the epigenetic regulation in long-term memory formation. This study provides insights into revealing regulatory roles of epigenetic changes in gene expression involving noncoding RNAs associated with synaptic plasticity.

Computational Modeling of Oxidative Stress in Fatty Livers Elucidates the Underlying Mechanism of the Increased Susceptibility to Ischemia/Reperfusion Injury

QUESTION

Donor liver organs with moderate to high fat content (i.e. steatosis) suffer from an enhanced susceptibility to ischemia/reperfusion injury (IRI) during liver transplantation. Responsible for the cellular injury is an increased level of oxidative stress, however the underlying mechanistic network is still not fully understood.

METHOD

We developed a phenomenological mathematical model of key processes of hepatic lipid metabolism linked to pathways of oxidative stress. The model allows the simulation of hypoxia (i.e. ischemia-like conditions) and reoxygenation (i.e. reperfusion-like conditions) for various degrees of steatosis and predicts the level of hepatic lipid peroxidation (LPO) as a marker of cell damage caused by oxidative stress.

RESULTS & CONCLUSIONS

Our modeling results show that the underlying feedback loop between the formation of reactive oxygen species (ROS) and LPO leads to bistable systems behavior. Here, the first stable state corresponds to a low basal level of ROS production. The system is directed to this state for healthy, non-steatotic livers. The second stable state corresponds to a high level of oxidative stress with an enhanced formation of ROS and LPO. This state is reached, if steatotic livers with a high fat content undergo a hypoxic phase. Theoretically, our proposed mechanistic network would support the prediction of the maximal tolerable ischemia time for steatotic livers: Exceeding this limit during the transplantation process would lead to severe IRI and a considerable increased risk for liver failure.