A Generalized Gene-Regulatory Network Model of Stem Cell Differentiation for Predicting Lineage Specifiers

Abstract

Identification of cell-fate determinants for directing stem cell differentiation remains a challenge. Moreover, little is known about how cell-fate determinants are regulated in functionally important subnetworks in large gene-regulatory networks (i.e., GRN motifs). Here we propose a model of stem cell differentiation in which cell-fate determinants work synergistically to determine different cellular identities, and reside in a class of GRN motifs known as feedback loops. Based on this model, we develop a computational method that can systematically predict cell-fate determinants and their GRN motifs. The method was able to recapitulate experimentally validated cell-fate determinants, and validation of two predicted cell-fate determinants confirmed that overexpression of ESR1 and RUNX2 in mouse neural stem cells induces neuronal and astrocyte differentiation, respectively. Thus, the presented GRN-based model of stem cell differentiation and computational method can guide differentiation experiments in stem cell research and regenerative medicine.

Figure 1

Proposed Model of Binary-Fate Stem Cell Differentiation Governed by GRN Motifs In this model two different daughter cell types (daughter 1 and daughter 2) from a common stem/progenitor cell correspond to two stable steady states, which are stabilized by strongly connected components of any number of genes consisting of differentially expressed TFs between two daughter cells. The same strongly connected components are used for maintaining the stem/progenitor state, in which pair(s) of TFs exhibit a more balanced expression pattern in comparison with that in two daughter cells (indicated by asterisks). TFs that do not show this balanced expression pattern are still necessary for stabilizing the expression balance of TFs marked with asterisks. The classical toggle switch that consists of two TFs (n = 2) is the simplest case of this model. Red nodes are TFs upregulated in daughter 1. Blue nodes are TFs upregulated in daughter 2. Purple nodes indicate TF expression in the stem/progenitor cell. Pointed arrows indicate activation and blunted arrows indicate inhibition. Note that motifs shown in this figure are examples of each n. Motifs with different topologies (not shown) are possible.

Figure 2

Schematic View of Proposed Method Differentially expressed genes are computed between two daughter cells and Boolean GRNs are reconstructed from differentially expressed TFs by first retrieving literature-based interactions and then pruning this network by removing interactions incompatible with Booleanized gene-expression data of two daughter cells. In parallel, statistically significant NRD TF pairs are computed. Finally, for each significant NRD TF pair, the most frequent strongly connected component is identified among the best GRN solutions. If two paired TFs are directly connected to each other in that strongly connected component, they are considered predicted opposing cell-fate determinants together with their GRN motif.

Figure 3

Predicted Opposing Cell-Fate Determinant Pairs, Their GRN Motifs, and Their Experimental Validation in mNSCs (A–F) Red nodes are TFs upregulated in daughter 1 (mesoderm, erythroid, neuron, osteoblast, and MESP1⁺ CPC). Blue nodes are TFs upregulated in daughter 2 (ectoderm, myeloid, astrocyte, adipocyte and MESP1⁻ CPC). Pointed arrows indicate activation, blunted arrows indicate inhibition. Asterisks indicate TFs that showed a significant NRD. GRN motifs of (A) Pou5f1-Sox2 pair in mESCs, (B) Gata1-Spi1 pair in mHSCs, (C) Runx2-Pparg pair in mMSCs, (D) Esr1-Runx2 pair in mNSCs, (E) Gata1-Fos pairs in mHSCs, and (F) GATA4-NANOG and GATA4-NANOG pairs in hCPCs. (G) Lineage marker (TUJ1 and glial fibrillary acidic protein [GFAP]) immunostaining of cells cultivated under maintenance conditions for 5 days after transduction with lentiviruses encoding GFP (negative control), ESR1, or RUNX2. Scale bar, 20 μm. (H–K) Diagrams showing the percentage of TUJ1-positive (H, J) and GFAP-positive (I, K) cells transduced with lentiviruses encoding GFP, ESR1, or RUNX2 (mean ± SEM; n ≥ 420 cells, N = 3 independent mNSC cultures; ^∗p < 0.05, t test).