382762 Systems Analysis of Signal Transduction in Insulin Mediated PI3K/AKT Pathway in Self-Renewal State of Human Embryonic Stem Cells
Motivation: Human Embryonic Stem Cells (hESCs) are an attractive raw material for regenerative medicine due to their unique properties of self-renewal and lineage specific differentiation. While the therapeutic potential of the differentiated lineages is well known, production of large quantities of the desired lineage requires abundant supply of pure starting material. During self-renewal, hESCs proliferate to give more copies of them and this is initiated by inhibition of differentiation signals and maintenance of signals that promote proliferation. As a result, self-renewal provides an avenue for obtaining large quantities of the raw material. Like any biological process, self-renewal is also prone to variability and rational methods are necessary to control and maintain a robust state. Currently, this is achieved by experimental means alone. While experiments have identified the key signaling players, knowledge of the systems level functioning of the signaling pathways in maintaining a robust self-renewal state is still under-developed. In this work, we have analyzed the systems level signal transfer properties of an important self-renewal pathway using a mechanistic mathematical model adapted for hESC specific behavior. Our primary goal is to identify robustness promoting mechanisms in the pathway using a quantitative framework in conjunction with efficient computational tools.
Methods: The phosphorylation dynamics of the key components of the insulin mediated PI3K/AKT pathway was first analyzed by experimentally stimulating H1 hESCs with 100 nM insulin after growth factor starvation. The dynamics was then compared to in silico simulations using a detailed mechanistic differential equation model of insulin mediated PI3K/AKT pathway (20 state variables, 25 parameters in the current form) by Sedaghat et al. . Global sensitivity analysis (GSA) was used to identify the key interactions in the pathway that affect the dynamics of self-renewal molecules like p-AKT. We utilized a computationally efficient algorithm called Random Sampling High Dimensional Model Representation (RS-HDMR) to capture sensitivity under combinatorial interactions between the model parameters. We recently validated the application of this algorithm for a signal transduction model . In this work, using GSA, we identified robustness promoting mechanisms that ensure (1) maintenance of a first order or overshoot dynamics of self-renewal molecule, p-AKT and (2) robust transfer of signals from oscillatory insulin stimulus to p-AKT in the presence of noise. For the latter, we tested various oscillatory scenarios of insulin stimulus to study the noise filtering capabilities of the PI3K/AKT pathway. The robustness metrics propounded by Kitano were used to quantify the input-output relationships .
Results and Discussion: In the first theme, we analyzed the dynamics and steady states of four major nodes of the PI3K/AKT pathway. These include the active insulin receptors (p-IR), tyrosine IRS1 (p-IRS1 (Y)), serine IRS1 (p-IRS1 (S)) and p-AKT. Dynamics from insulin stimulation experiments showed that intracellular components of PI3K/AKT in hESCs show the typical overshoot behavior influenced by negative feedback by p-IRS1 (S). Using phosphatase PTP as a control point to modulate the dynamics, we found that presence of negative feedback acts as a robustness promoting mechanism. For hESC specific parameter ranges that promote overshoot behavior, the system is insensitive to perturbations associated with the cascade reactions that propagate signals from the active receptors to the downstream kinases (or the direct trunk of the pathway topology). We predict that if the system looses its negative feedback character or shifts to a regime where PTP levels are very low, it will become vulnerable to the otherwise insensitive perturbations. In such a regime, the levels of self-renewal molecules like p-AKT will be high but also highly variable. This sets up a classical robustness tradeoff often seen in complex systems.
In the second theme, we evaluated the efficiency of signal transfer for time dependent variation in the input signal. Our results indicate that oscillations of small frequency (ω) and high amplitude (α) are transduced down the pathway, but with amplitude attenuation under nominal conditions. Our results also demonstrate that the downstream molecules follow the main signal with very high fidelity even in the presence of noise. Any modulation of upstream positive regulator IRS1 (p-IRS1 (Y)) can result in amplification or attenuation of the signals. Increasing the oscillation frequency, however, results in a regime where significant attenuation of the amplitude may be achieved. Finally, at very high frequencies (log10(ω min-1) > 0.5), all oscillations are cut-off. This region was not affected by parameter perturbations. This shows that the PI3K/AKT pathway has an intrinsic minimal response time and when the oscillations are faster than this response time, they are not transmitted.
Conclusions: Our detailed mechanistic model and experimental analysis identified the precise mechanisms to modulate self-renewal molecules like p-AKT. Our results show that faithful transfer of signal from the stimulating ligand to p-AKT occurs even in the presence of noise, albeit with signal attenuation and high frequency cut-off. This ensures that informative signals are transmitted down the pathway and high frequency noise is cut-off. Negative feedback contributes to signal attenuation, while positive regulators upstream of p-AKT contribute to signal amplification. Quantitative measures of robustness can be used to finely tune the signal transfer process in hESCs to ensure that the level as well as the variability is kept within sufficient limits. Further, understanding the parameter dependences of the signal filtering and cut-off processes can help in the design of optimal input stimulation scenarios to modulate the pathway. Our work presents a framework towards the design of targeted growth media to maintain robust cellular fate of hESCs.
 Sedaghat et al. A mathematical model of metabolic insulin signaling pathways. American J of Physiol Endocrinol and Metabol (2002) 283: E1084-E1101
 Mathew et al. Bioinformatics 2014, Article in Press, ID: bioinf-2013-2200.r1 (btu209).
 Kitano, H. (2007). Towards a theory of biological robustness. Mol Syst Biol, 3, 137.
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