Dataset Information

Self-organization of the human embryo in the absence of maternal tissues.

ABSTRACT: Remodelling of the human embryo at implantation is indispensable for successful pregnancy. Yet it has remained mysterious because of the experimental hurdles that beset the study of this developmental phase. Here, we establish an in vitro system to culture human embryos through implantation stages in the absence of maternal tissues and reveal the key events of early human morphogenesis. These include segregation of the pluripotent embryonic and extra-embryonic lineages, and morphogenetic rearrangements leading to generation of a bilaminar disc, formation of a pro-amniotic cavity within the embryonic lineage, appearance of the prospective yolk sac, and trophoblast differentiation. Using human embryos and human pluripotent stem cells, we show that the reorganization of the embryonic lineage is mediated by cellular polarization leading to cavity formation. Together, our results indicate that the critical remodelling events at this stage of human development are embryo-autonomous, highlighting the remarkable and unanticipated self-organizing properties of human embryos.

SUBMITTER: Shahbazi MN

PROVIDER: S-EPMC5049689 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Self-organization of the human embryo in the absence of maternal tissues.

Shahbazi Marta N MN Jedrusik Agnieszka A Vuoristo Sanna S Recher Gaelle G Hupalowska Anna A Bolton Virginia V Fogarty Norah N M NNM Campbell Alison A Devito Liani L Ilic Dusko D Khalaf Yakoub Y Niakan Kathy K KK Fishel Simon S Zernicka-Goetz Magdalena M

Nature cell biology 20160504 6

Remodelling of the human embryo at implantation is indispensable for successful pregnancy. Yet it has remained mysterious because of the experimental hurdles that beset the study of this developmental phase. Here, we establish an in vitro system to culture human embryos through implantation stages in the absence of maternal tissues and reveal the key events of early human morphogenesis. These include segregation of the pluripotent embryonic and extra-embryonic lineages, and morphogenetic rearran ...[more]

PMID: 27144686

Similar Datasets

Project description:Embryonic stem cells (ESCs) can self-organize in vitro into developmental patterns with spatial organization and molecular similarity to that of early embryonic stages. This self-organization of ESCs requires transmission of signaling cues, via addition of small molecule chemicals or recombinant proteins, to induce distinct embryonic cellular fates and subsequent assembly into structures that can mimic aspects of early embryonic development. During natural embryonic development, different embryonic cell types co-develop together, where each cell type expresses specific fate-inducing transcription factors through activation of non-coding regulatory elements and interactions with neighboring cells. However, previous studies have not fully explored the possibility of engineering endogenous regulatory elements to shape self-organization of ESCs into spatially-ordered embryo models. Here, we hypothesized that cell-intrinsic activation of a minimum number of such endogenous regulatory elements is sufficient to self-organize ESCs into early embryonic models. Our results show that CRISPR-based activation (CRISPRa) of only two endogenous regulatory elements in the genome of pluripotent stem cells is sufficient to generate embryonic patterns that show spatial and molecular resemblance to that of pre-gastrulation mouse embryonic development. Quantitative single-cell live fluorescent imaging showed that the emergence of spatially-ordered embryonic patterns happens through the intrinsic induction of cell fate that leads to an orchestrated collective cellular motion. Based on these results, we propose a straightforward approach to efficiently form 3D embryo models through intrinsic CRISPRa-based epigenome editing and independent of external signaling cues. CRISPRa-Programmed Embryo Models (CPEMs) show highly consistent composition of major embryonic cell types that are spatially-organized, with nearly 80% of the structures forming an embryonic cavity. Single cell transcriptomics confirmed the presence of main embryonic cell types in CPEMs with transcriptional similarity to pre-gastrulation mouse embryos and revealed novel signaling communication links between different embryonic cell types. Our findings offer a programmable embryo model and demonstrate that minimum intrinsic epigenome editing is sufficient to self-organize ESCs into highly consistent pre-gastrulation embryo models.

Project description:BackgroundParallel high-throughput microarray and sequencing experiments produce vast quantities of multidimensional data which must be arranged and analyzed in a concerted way. One approach to addressing this challenge is the machine learning technique known as self organizing maps (SOMs). SOMs enable a parallel sample- and gene-centered view of genomic data combined with strong visualization and second-level analysis capabilities. The paper aims at bridging the gap between the potency of SOM-machine learning to reduce dimension of high-dimensional data on one hand and practical applications with special emphasis on gene expression analysis on the other hand.ResultsThe method was applied to generate a SOM characterizing the whole genome expression profiles of 67 healthy human tissues selected from ten tissue categories (adipose, endocrine, homeostasis, digestion, exocrine, epithelium, sexual reproduction, muscle, immune system and nervous tissues). SOM mapping reduces the dimension of expression data from ten of thousands of genes to a few thousand metagenes, each representing a minicluster of co-regulated single genes. Tissue-specific and common properties shared between groups of tissues emerge as a handful of localized spots in the tissue maps collecting groups of co-regulated and co-expressed metagenes. The functional context of the spots was discovered using overrepresentation analysis with respect to pre-defined gene sets of known functional impact. We found that tissue related spots typically contain enriched populations of genes related to specific molecular processes in the respective tissue. Analysis techniques normally used at the gene-level such as two-way hierarchical clustering are better represented and provide better signal-to-noise ratios if applied to the metagenes. Metagene-based clustering analyses aggregate the tissues broadly into three clusters containing nervous, immune system and the remaining tissues.ConclusionsThe SOM technique provides a more intuitive and informative global view of the behavior of a few well-defined modules of correlated and differentially expressed genes than the separate discovery of the expression levels of hundreds or thousands of individual genes. The program is available as R-package 'oposSOM'.

Dataset Information

Self-organization of the human embryo in the absence of maternal tissues.

Publications

Self-organization of the human embryo in the absence of maternal tissues.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets