374168 Mechanistic Insights into Early Endoderm Differentiation of Human Embryonic Stem Cells Using Systems Level Analysis of Signaling Interactions
Introduction: 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. hESCs are directed to mature cell types using various chemical cocktails that replicate signaling programs active during in vivo development. These signaling pathways employ large number of mediators that are controlled by several regulatory mechanisms. Current efforts to develop chemical modulators for controlling differentiation are purely experimental and they have successfully identified the key players. However, systems level analysis of the dynamics of this process is still under-developed. We recently demonstrated the strength of quantitative systems level approaches to uncover the role of regulatory mechanisms in the self-renewal state of hESCs . Here, we present a complete systems level analysis of the dynamics of regulatory interactions in the TGF-β/SMAD and PI3K/AKT pathways, directing the early endoderm differentiation of hESCs, by integrating efficient computational tools and targeted experimental perturbations.
Materials and Methods:
Experimental analysis: For self-renewal, H1 hESCs were maintained on matrigel-coated plates in mTeSR1. Endoderm differentiation was performed using 100 ng/ml Activin A (to activate TGF-β/SMAD2,3) with or without modulation of PI3K/AKT pathway using PI3K inhibitor, Wortmannin. The phosphorylation dynamics of participating signaling molecules were measured using MagPix Luminex xMAP technology. The initial selection of key molecules was based on the study by Singh et al. . Nucleo-cytoplasmic shuttling rates of molecules were measured using Fluorescence Recovery After Photobleaching (FRAP) analysis. Key transcription factors characterizing endoderm were measured using qRT-PCR. Mathematical and computational tools described in the next section were used to guide generation of data by in-house experiments.
Mathematical analysis: We first employed data-driven modeling tools like Partial Least Squares Regression (PLSR) and Dynamic Bayesian Network Analysis (DBN) to identify key molecules, hypothesize interactions and identify most informative time points. Detailed mechanistic Ordinary Differential Equation (ODE) model for the TGF-β/SMAD2,3 pathway with crosstalk interactions of PI3K/AKT was developed for a systems level analysis. The model was calibrated using Replica Exchange Ensemble Modeling (EM) and sensitive reactions were identified using computationally efficient Global Sensitivity Approach (GSA).
Results and Discussion: PLSR results indicated that endoderm markers of hESCs correlate well with the early but not the late signaling events. Application of DBN on the early signaling dynamics showed that the molecules, p-SMAD2 and SMAD4 form the core interactions (± p-AKT) and, p-SMAD3 and p-ERK were only influenced by the core interactions (Fig. 1A). Interestingly, our experiments showed that the dynamics and fold-change of p-SMAD2 and p-SMAD3 diverge, a novel result seen only in hESCs. The reason for the divergence was investigated using a detailed ODE model with crosstalk interactions with AKT. We generated hESC specific model with SMAD2 and SMAD3 interactions modeled separately. EM on the detailed ODE model captured the parameter ensembles that explained the differentiating hESC system (Fig. 1B). The nucleo-cytoplasmic shuttling rates of SMAD2 and SMAD3 (separately) measured through FRAP analysis was used to constrain the parameter ensembles. From among the various hypotheses, AKT was found to primarily influence the phosphorylation rates of SMAD molecules. GSA results indicated that the sensitive parameters for p-SMAD2 and p-SMAD3 were of similar ranking but of varying strengths resulting in the divergent dynamics. Phosphorylation and de-phosphorylation of SMADs were the most sensitive reactions, while SMAD nucleo-cytoplasmic shuttling rates were associated with modulation of the aforementioned reactions. Further, negative feedback via SMAD7 constrained the propagation of parameter uncertainty as well as promoted a robust signaling response.
Conclusions: Our results show that early signaling dynamics of p-SMAD, p-AKT and p-ERK encode the long-term endoderm differentiation response of hESCs. We provide mechanistic explanations for the divergence of p-SMAD2 and p-SMAD3 dynamics in hESCs. Further, our results present the importance of negative feedback via SMAD7 in controlling the long-term signal propagation and population variability in hESCs. Application of mechanistic information revealed by such an analysis will direct precise perturbations through designed small molecules, hence offering an avenue to remove xenogenic factors in current culture conditions.
 Mathew et al. Bioinformatics 2014, Article in Press, ID: bioinf-2013-2200.r1 (btu209).
 Singh et al. Cell Stem Cell 2012, 10(3): 312-26
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