Abstract The human embryo is a complex structure that emerges and develops as a result of cell-level decisions guided by both intrinsic genetic programs and cell–cell interactions. Given limited accessibility and associated ethical constraints of human embryonic tissue samples, researchers have turned to the use of human stem cells to generate embryo models to study specific embryogenic developmental steps. However, to study complex self-organizing developmental events using embryo models, there is a need for computational and imaging tools for detailed characterization of cell-level dynamics at the single cell level. In this work, we obtained live cell imaging data from a human pluripotent stem cell (hPSC)-based epiblast model that can recapitulate the lumenal epiblast cyst formation soon after implantation of the human blastocyst. By processing imaging data with a Python pipeline that incorporates both cell tracking and event recognition with the use of a CNN-LSTM machine learning model, we obtained detailed temporal information of changes in cell state and neighborhood during the dynamic growth and morphogenesis of lumenal hPSC cysts. The use of this tool combined with reporter lines for cell types of interest will drive future mechanistic studies of hPSC fate specification in embryo models and will advance our understanding of how cell-level decisions lead to global organization and emergent phenomena. Insight, innovation, integration: Human pluripotent stem cells (hPSCs) have been successfully used to model and understand cellular events that take place during human embryogenesis. Understanding how cell–cell and cell–environment interactions guide cell actions within a hPSC-based embryo model is a key step in elucidating the mechanisms driving system-level embryonic patterning and growth. In this work, we present a robust video analysis pipeline that incorporates the use of machine learning methods to fully characterize the process of hPSC self-organization into lumenal cysts to mimic the lumenal epiblast cyst formation soon after implantation of the human blastocyst. This pipeline will be a useful tool for understanding cellular mechanisms underlying key embryogenic events in embryo models.
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Stem cell-based models of early mammalian development
ABSTRACT The complex process by which a single-celled zygote develops into a viable embryo is nothing short of a miraculous wonder of the natural world. Elucidating how this process is orchestrated in humans has long eluded the grasp of scientists due to ethical and practical limitations. Thankfully, pluripotent stem cells that resemble early developmental cell types possess the ability to mimic specific embryonic events. As such, murine and human stem cells have been leveraged by scientists to create in vitro models that aim to recapitulate different stages of early mammalian development. Here, we examine the wide variety of stem cell-based embryo models that have been developed to recapitulate and study embryonic events, from pre-implantation development through to early organogenesis. We discuss the applications of these models, key considerations regarding their importance within the field, and how such models are expected to grow and evolve to achieve exciting new milestones in the future.
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- NSF-PAR ID:
- 10383126
- Date Published:
- Journal Name:
- Development
- Volume:
- 149
- Issue:
- 20
- ISSN:
- 0950-1991
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Early embryonic development involves forming all specialized cells from a fluid-like mass of identical stem cells. The differentiation process consists of a series of symmetry-breaking events, starting from a high-symmetry state (stem cells) to a low-symmetry state (specialized cells). This scenario closely resembles phase transitions in statistical mechanics. To theoretically study this hypothesis, we model embryonic stem cell (ESC) populations through a coupled Boolean network (BN) model. The interaction is applied using a multilayer Ising model that considers paracrine and autocrine signaling, along with external interventions. It is demonstrated that cell-to-cell variability can be interpreted as a mixture of steady-state probability distributions. Simulations have revealed that such models can undergo a series of first- and second-order phase transitions as a function of the system parameters that describe gene expression noise and interaction strengths. These phase transitions result in spontaneous symmetry-breaking events that generate new types of cells characterized by various steady-state distributions. Coupled BNs have also been shown to self-organize in states that allow spontaneous cell differentiation.more » « less
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ABSTRACT Human embryonic stem cells (hESCs) possess an immense potential to generate clinically relevant cell types and unveil mechanisms underlying early human development. However, using hESCs for discovery or translation requires accurately identifying differentiated cell types through comparison with their in vivo counterparts. Here, we set out to determine the identity of much debated BMP-treated hESCs by comparing their transcriptome to recently published single cell transcriptomic data from early human embryos ( Xiang et al., 2020). Our analyses reveal several discrepancies in the published human embryo dataset, including misclassification of putative amnion, intermediate and inner cell mass cells. These misclassifications primarily resulted from similarities in pseudogene expression, highlighting the need to carefully consider gene lists when making comparisons between cell types. In the absence of a relevant human dataset, we utilized the recently published single cell transcriptome of the early post implantation monkey embryo to discern the identity of BMP-treated hESCs. Our results suggest that BMP-treated hESCs are transcriptionally more similar to amnion cells than trophectoderm cells in the monkey embryo. Together with prior studies, this result indicates that hESCs possess a unique ability to form mature trophectoderm subtypes via an amnion-like transcriptional state.
This article has an associated First Person interview with the first author of the paper.
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Umulis, David (Ed.)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.more » « less
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Abstract During early development, sea lamprey embryos undergo programmatic elimination of DNA from somatic progenitor cells in a process termed programmed genome rearrangement (PGR). Eliminated DNA eventually becomes condensed into micronuclei, which are then physically degraded and permanently lost from the cell. Previous studies indicated that many of the genes eliminated during PGR have mammalian homologs that are bound by polycomb repressive complex (PRC) in embryonic stem cells. To test whether PRC components play a role in the faithful elimination of germline‐specific sequences, we used a combination of CRISPR/Cas9 and lightsheet microscopy to investigate the impact of gene knockouts on early development and the progression through stages of DNA elimination. Analysis of knockout embryos for the core PRC2 subunits EZH, SUZ12, and EED show that disruption of all three genes results in an increase in micronucleus number, altered distribution of micronuclei within embryos, and an increase in micronucleus volume in mutant embryos. While the upstream events of DNA elimination are not strongly impacted by loss of PRC2 components, this study suggests that PRC2 plays a role in the later stages of elimination related to micronucleus condensation and degradation. These findings also suggest that other genes/epigenetic pathways may work in parallel during DNA elimination to mediate chromatin structure, accessibility, and the ultimate loss of germline‐specific DNA.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1242/dev.201015
