Analysis of alternative signaling pathways of endoderm induction of human embryonic stem cells identifies context specific differences

Abstract

Background: Lineage specific differentiation of human embryonic stem cells (hESCs) is largely mediated by specific growth factors and extracellular matrix molecules. Growth factors initiate a cascade of signals which control gene transcription and cell fate specification. There is a lot of interest in inducing hESCs to an endoderm fate which serves as a pathway towards more functional cell types like the pancreatic cells. Research over the past decade has established several robust pathways for deriving endoderm from hESCs, with the capability of further maturation. However, in our experience, the functional maturity of these endoderm derivatives, specifically to pancreatic lineage, largely depends on specific pathway of endoderm induction. Hence it will be of interest to understand the underlying mechanism mediating such induction and how it is translated to further maturation. In this work we analyze the regulatory interactions mediating different pathways of endoderm induction by identifying co-regulated transcription factors.

Results: hESCs were induced towards endoderm using activin A and 4 different growth factors (FGF2 (F), BMP4 (B), PI3KI (P), and WNT3A (W)) and their combinations thereof, resulting in 15 total experimental conditions. At the end of differentiation each condition was analyzed by qRT-PCR for 12 relevant endoderm related transcription factors (TFs). As a first approach, we used hierarchical clustering to identify which growth factor combinations favor up-regulation of different genes. In the next step we identified sets of co-regulated transcription factors using a biclustering algorithm. The high variability of experimental data was addressed by integrating the biclustering formulation with bootstrap re-sampling to identify robust networks of co-regulated transcription factors. Our results show that the transition from early to late endoderm is favored by FGF2 as well as WNT3A treatments under high activin. However, induction of late endoderm markers is relatively favored by WNT3A under high activin.

Conclusions: Use of FGF2, WNT3A or PI3K inhibition with high activin A may serve well in definitive endoderm induction followed by WNT3A specific signaling to direct the definitive endoderm into late endodermal lineages. Other combinations, though still feasible for endoderm induction, appear less promising for pancreatic endoderm specification in our experiments.

Figure 1

Work-flow for the entire analysis from data collection to identification of robust biclusters. In short, we start with the qRT-PCR data and perform bootstrap with re-sampling to obtain 1000 pseudo-datasets. Each of these datasets is subjected to biclustering analysis to obtain the most coherent pattern in each dataset. The resulting biclusters are then analyzed for the most repeated subsets of biclusters.

Figure 2

Fold change data for the 12 transcriptional markers across 15 experimental conditions. (a) The fold change calculated from the mean expression data from qRT-PCR on day 4 of the differentiation process is plotted from the expression matrix, X, constructed using rows as the TFs and columns as the experimental conditions. (b) Variation observed in the 12 transcriptional markers with changes in the signaling pathways presented as mean ± SE. All the major DE markers CER, CXCR4, FOXA2, SOX17 and the later endoderm markers HNF4α, HNF1β and GATA4 show significant changes with the nature of DE induction.

Figure 3

Hierarchical clustering on the mean expression data. The conditions cluster into two major groups, one containing BMP4 in the absence of exogenous FGF2 and the other containing all the other treatments and BMP4 in combination with exogenous FGF2. Activin A is common among all the treatments. The TFs cluster into two groups, the late and early endoderm markers.

Figure 4

Biclusters obtained from the normalized mean expression data. (a) Optimal Bicluster The bicluster contains 3 genes across 5 conditions. (b) Subsequent bicluster containing 3 genes and 7 conditions. The bicluster parameters selected were δ = 1.5, Wc, Wr = 1.

Figure 5

Robust subsets identified from the 1000 bootstrap datasets. Robust biclusters are the most repeated subsets (>500). The bicluster parameters selected were δ = 1.5, Wc, Wr = 1. Note: Group 1 contains five subsets only one of which is shown.

Figure 6

Robust subsets of co-regulated genes presented as a bipartite graph.. We have identified high Activin along with PI3K inhibition or activin in combination with WNT3A to work the best to co-regulate early endoderm marker CER and late endoderm markers HNF6. The Group 2 TFs HNF4α and HNF6 are part of the network inducing NGN3 and PDX1, reminiscent of the pancreatic genotype and are favored by high activin with PI3KI and WNT3A.

Figure 7

Figure summarizing the functional dependence of the co-regulated genes on the active signaling pathways of endoderm induction. CER and HNF6 are favoured by High activin and PI3KI, WNT3A, FGF2 while HNF4α and HNF6 are favoured by High activin, WNT3A and PI3KI. Combining the early and late stages, high activin with PI3KI and WNT3A together is an effective strategy for endoderm differentiation.