A multiscale model via single-cell transcriptomics reveals robust patterning mechanisms during early mammalian embryo development

Abstract

During early mammalian embryo development, a small number of cells make robust fate decisions at particular spatial locations in a tight time window to form inner cell mass (ICM), and later epiblast (Epi) and primitive endoderm (PE). While recent single-cell transcriptomics data allows scrutinization of heterogeneity of individual cells, consistent spatial and temporal mechanisms the early embryo utilize to robustly form the Epi/PE layers from ICM remain elusive. Here we build a multiscale three-dimensional model for mammalian embryo to recapitulate the observed patterning process from zygote to late blastocyst. By integrating the spatiotemporal information reconstructed from multiple single-cell transcriptomic datasets, the data-informed modeling analysis suggests two major processes critical to the formation of Epi/PE layers: a selective cell-cell adhesion mechanism (via EphA4/EphrinB2) for fate-location coordination and a temporal attenuation mechanism of cell signaling (via Fgf). Spatial imaging data and distinct subsets of single-cell gene expression data are then used to validate the predictions. Together, our study provides a multiscale framework that incorporates single-cell gene expression datasets to analyze gene regulations, cell-cell communications, and physical interactions among cells in complex geometries at single-cell resolution, with direct application to late-stage development of embryogenesis.

NANOG/GATA6 Interactions Revisited: A Statistical Mechanics Approach towards Cell Fate Decisions

“…This is the well-known Hill equation that is also commonly used in the same context [10,11,15,16]. In the following we will refer to this as p hill A .…”

“…Under the notion that transcriptional regulation occurs based on inhibition and auto-activation, previous models have proposed to use the product of two Hill functions [10,11,16]. In the context of probabilities this would imply stochastic independence.…”

“…From here on, we will designate the cells with high NANOG expression and low GATA6 expression from steady state (18) as N+G-. Analogously, (16) describes N-G-cells and (17) N-G+ cells. At the single cell level, we are able to exclude N-G-cells using inequality (29).…”

How a cell decides its own fate: a single-cell view of molecular mechanisms and dynamics of cell-type specification

“…Mutual repression of TFs is one mechanism by which multiple, alternative cell types can be created. A prominent example is an interaction between the TFs GATA6 and NANOG, which governs the lineage decision between two of the earliest cell types in the mammalian embryo [21][22][23]. The conceptual framework discussed in the final section of this review explains how various stable cell types and unidirectional differentiation dynamics emerge from gene regulatory networks, see Figure 1, right.…”

Global cell-cell communication enables spatial segregation of cells in organoids of the inner cell mass

“…To this date however, it has only been observed that the number of E-cadherin, the molecules involved in the adhesion of these cells, differs only after the cells have differentiated [9]. Alternatively, Eph/Ephrin ligand receptor pairings have recently been proposed to account for differential adhesion [28]. Another recent study has performed a quantitative analysis of the signaling range of FGF4 [19].…”