MicroRNA-16 feedback loop with p53 and Wip1 can regulate cell fate determination between apoptosis and senescence in DNA damage response

<div><p>Cell fate regulation is an open problem whose comprehension impacts several areas of the biosciences. DNA damage induces cell cycle checkpoints that activate the p53 pathway to regulate cell fate mechanisms such as apoptosis or senescence. Experiments with different cell types show that the p53 pathway regulates cell fate through a switch behavior in its dynamics. For low DNA damage the pathway presents an oscillatory pattern associated with intense DNA damage repair while for high damage there are no oscillations and either p53 concentration increases inducing apoptosis or the cell enters a senescence state. Apoptosis and senescence phenotypes seem to have compensatory functions in tissues and the microRNA 16–1 (miR-16) is involved in the regulation of the fate between both phenotypes in cancer cells. To investigate the regulation of cell fate we developed a logical model of the G1/S checkpoint in DNA damage response that takes into account different levels of damage and contemplates the influence of miR-16 through its positive feedback loop formed with p53 and Wip1. The model reproduces the observed cellular phenotypes in experiments: oscillatory (for low DNA damage) regulated by negative feedback loops involving mainly p53 and Mdm2 and apoptotic or senescent (for high DNA damage) regulated by the positive p53/Wip1/miR-16 feedback loop. We find good agreement between the level of DNA damage and the probability of the phenotype produced according to experiments. We also find that this positive feedback makes senescent and apoptotic phenotypes to be determined stochastically (bistable), however controlling the expression level of miR-16 allows the control of fate determination as observed experimentally.</p></div

Regulatory network for the G1/S checkpoint pathway.

<p>Elliptic nodes represent proteins and rectangular nodes represent inputs or microRNA. The input node in grey at the top of the network denotes DNA damage level. Green lines represent activations and red lines inhibitions.</p

Phenotype probabilities for the wild-type case and damage S.

<p>Phenotype probabilities for the wild-type case and damage S.</p

Logical rules.

<p>Rules controlling the states of the network nodes based on the biochemical literature (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0185794#pone.0185794.s001" target="_blank">S1 File</a>). 0 is the default value.</p

Phenotype probabilities for different levels of expression and DNA damage S for node miR16.

<p>Phenotype probabilities for different levels of expression and DNA damage S for node miR16.</p

Phenotype probabilities for KD and activation (O) of node Mdm2 according to DNA damage S.

<p>Phenotype probabilities for KD and activation (O) of node Mdm2 according to DNA damage S.</p

Phenotype probabilities for KD and activation (O) of node Wip1 according to DNA damage S.

<p>Phenotype probabilities for KD and activation (O) of node Wip1 according to DNA damage S.</p

Stable states of the wild-type case.

<p>The left-most column lists the DNA damage levels that lead to stable states. Each line is a unique stable state characterized by the value of the components and the corresponding phenotype is indicated (see section <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0185794#sec003" target="_blank">Material and methods</a>). Numbers stand for variable values and empty spaces correspond to value zero.</p