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Identification of the central intermediate in the extra-embryonic to embryonic endoderm transition through single-cell transcriptomics

Nature Cell Biology volume 24, pages 833–844 (2022)Cite this article

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Abstract

High-resolution maps of embryonic development suggest that acquisition of cell identity is not limited to canonical germ layers but proceeds via alternative routes. Despite evidence that visceral organs are formed via embryonic and extra-embryonic trajectories, the production of organ-specific cell types in vitro focuses on the embryonic one. Here we resolve these differentiation routes using massively parallel single-cell RNA sequencing to generate datasets from FOXA2Venus reporter mouse embryos and embryonic stem cell differentiation towards endoderm. To relate cell types in these datasets, we develop a single-parameter computational approach and identify an intermediate en route from extra-embryonic identity to embryonic endoderm, which we localize spatially in embryos at embryonic day 7.5. While there is little evidence for this cell type in embryonic stem cell differentiation, by following the extra-embryonic trajectory starting with naïve extra-embryonic endoderm stem cells we can generate embryonic gut spheroids. Exploiting developmental plasticity therefore offers alternatives to pluripotent cells and opens alternative avenues for in vitro differentiation.

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Fig. 1: Single-cell sequencing and analysis of embryonic Foxa2POS lineages.
Fig. 2: CAT and identification of the InterVE cluster as an intermediate population between VE and DE.
Fig. 3: Functional properties of VE in the transition to DE.
Fig. 4: ST reveals InterVE in E7.5 embryos.
Fig. 5: In vitro differentiation of endoderm lineages.
Fig. 6: An in vitro model for generating gut spheroids (nEnd spheroids) from extra-embryonic endoderm.

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Data availability

The single-cell RNA-seq data used in this study is in the Gene Expression Omnibus under accession number GSE164464. Previously published Nowotschin-2019 data that were re-analysed here are available under accession code GSE123046. Source data are provided with this study. All other data supporting the findings of this study are available from the corresponding author on reasonable request.

Code availability

All analyses, package versions as well as development environments for reproducibility purposes are publicly available at https://github.com/brickmanlab/rothova-et-al-2022. Implementation of CAT and the related pre-processed datasets are publicly available at https://github.com/brickmanlab/CAT. The interactive CAT app is available at https://align-clusters.com.

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Acknowledgements

We thank H. Lickert for the kind gift of the FOXA2Venus reporter mice, the DanStem Genomics Platform (H. Neil, M. Michaut and H. Wollmann), DanStem Flow Cytometry Platform (G. dela Cruz and P. van Dieken), Stem Cell Culture Platform (A. Meligkova, E. F. Rebollo and M. Paulsen), DanStem Imaging Platform (J. Bulkescher and A. Shrestha) for technical expertise, support and the use of instruments, M.S. Paulsen for facilitating ST, Brickman laboratory members for critical discussions, K. J. Won for comments and T. Machet for graphical advice and help. Raw sequencing data were converted from bcl to fastq using the DeiC National Life Science Supercomputer at DTU (www.computerome.dk).

Work in our groups was supported by grants from the Lundbeck Foundation (R198-2015-412), J.M.B.; Independent Research Fund Denmark (8020-00100B and 6110-00009), J.M.B.; the Novo Nordisk Foundation (NNF17OC0028218), J.M.B.; the Danish National Research Foundation (DNRF116), J.M.B. and A.T. The Novo Nordisk Foundation Center for Stem Cell Medicine is supported by Novo Nordisk Foundation (NNF21CC0073729), and its predecessor The Novo Nordisk Foundation Center for Stem Cell Biology was also supported by the Novo Nordisk Foundation (NNF17CC0027852).

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Author notes

  1. These authors contributed equally: Michaela Mrugala Rothová, Alexander Valentin Nielsen, Martin Proks.

Authors and Affiliations

  1. Novo Nordisk Foundation Center for Stem Cell Medicine (reNEW), University of Copenhagen, Copenhagen, Denmark

    Michaela Mrugala Rothová, Martin Proks, Yan Fung Wong, Alba Redo Riveiro, Madeleine Linneberg-Agerholm & Joshua Mark Brickman

  2. Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark

    Alexander Valentin Nielsen & Ala Trusina

  3. Department of Immunology, Weizmann Institute of Science, Rehovot, Israel

    Eyal David & Ido Amit

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  1. Michaela Mrugala Rothová
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Contributions

M.M.R., J.M.B. and A.T. conceived the study. M.M.R., J.M.B., A.T., A.V.N., A.R.R., M.L-A. and Y.F.W. designed and interpreted experiments. M.M.R. performed all experiments, Y.F.W, A.R.R. and M.L.-A. contributed to the nEnd-spheroid experiments. The pre-processing and initial filtering of the raw sequencing data was done by E.D. All subsequent data analysis was carried out by A.V.N. and M.P. with input from I.A. M.M.R., J.M.B. and A.T. wrote the manuscript with input from all other authors.

Corresponding authors

Correspondence to Ala Trusina or Joshua Mark Brickman.

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Extended data

Extended Data Fig. 1 Reproducibility and gene expression in Foxa2-Venus populations.

(a) Sample representation within each developmental stage. The samples are evenly distributed across the appropriate clusters. (b) Expression of known lineage markers agrees with the assigned cluster identities. aDE – anterior definitive endoderm, AVE – anterior visceral endoderm, DE1- early definitive endoderm, DE2 – later definitive endoderm, EmVE – embryonic visceral endoderm, ExVE – extra-embryonic endoderm, FG – foregut, FP – floorplate, HG – hindgut, InterVE – intermediate visceral endoderm, MG – midgut, PE – parietal endoderm, PS1 – early primitive streak, PS2 – later primitive streak.

Extended Data Fig. 2 Foxa2-Venus populations.

(a) Single cell FACS strategy. The sorted cells were consecutively gated in order to remove cell debris, to select singlet from multiplet cells and to select live cells. A general gate was created in the FSC-A vs SSC-A plot to include the population of interest and minimize low FSC and high SSC events. The events in this gate were then gated for single cells based on FSC-W to exclude doublets and aggregates. The single cells were then gated for DAPI exclusion. Single-color controls were used to determine the gates for the different fluorophores. The FOXA2POS cells were mixed with pre-labelled carrier cells (labelled with CellVue Maroon) and the FOXA2POS cells (negative for CellVue Maroon staining) were used for the final index single cell sort. Each cell specifications (such as forward scatter - cell size and FOXA2-Venus protein levels) were recorded and linked to a specific sorted cell. (b) Bar plot representation of samples per cluster. Each colour represents a time point between E6.5 and E9.5. (c) Images of E6.5 - E9.5 FOXA2POS embryos, the E8.5 and E9.5 embryos were dissected as illustrated. (d) Re-clustered UMAP dimensional embedding of gastrulation stage lineages. Here, the Node segregates into two clusters. (e) FACS and cell cycle chart for gastrulation stage lineages representing the cell size (radius of circles), Foxa2 mRNA level (X-axis), FOXA2 protein level (Y-axis) and cell cycle phase (colour of pie charts, G1-phase in red, G2M-phase in green, and S-phase in blue) for specific clusters. The Node is represented by a proliferative and non-proliferative cell populations. AVE – anterior visceral endoderm, DE1- early definitive endoderm, DE2 – later definitive endoderm, EmVE – embryonic visceral endoderm, ExVE – extra-embryonic endoderm, InterVE – intermediate visceral endoderm, PS1 – early primitive streak, PS2 – later primitive streak.

Source data

Extended Data Fig. 3 CAT analysis of different endoderm populations.

(a) A heatmap of Euclidean distances between the clusters in our in vivo and Now-2019 dataset. (b) An example of bootstrapped distance histograms illustrating that our InterVE cluster aligns to Now-EmVE2 (in green) and not other clusters in Now-2019 dataset (red). (c-e) Sankey diagrams representing alignments between clusters in: (c) our in vivo to Now-2019 dataset (before sub-clustering); (d) Now-2019 to our in vivo dataset; (e) our in vivo dataset aligned to itself. (c-e) Thickness of the line is inversely proportional to the pairwise distance. (f) PCA of all FOXA2POS cells places the InterVE between the extra-embryonic VE and embryonic DE lineages. AVE – anterior visceral endoderm, DE1- early definitive endoderm, DE2 – later definitive endoderm, EmVE – embryonic visceral endoderm, ExVE – extra-embryonic endoderm, FP – floorplate, InterVE – intermediate visceral endoderm, PE – parietal endoderm, PS1 – early primitive streak, PS2 – later primitive streak.

Extended Data Fig. 4 PAGA trajectory inference on DE and VE lineages.

(a-b) Partition-based graph abstraction (PAGA) of VE and DE FOXA2POS lineages. Similar to PCA, the PAGA trajectory inference highlights the position of InterVE in between the VE and DE lineages. AVE – anterior visceral endoderm, DE1- early definitive endoderm, DE2 – later definitive endoderm, EmVE – embryonic visceral endoderm, ExVE – extra-embryonic endoderm, InterVE – intermediate visceral endoderm.

Extended Data Fig. 5 Molecular basis for VE-InterVE-DE transition.

(a) Heatmap representing DEGs in the InterVE cluster. Gene expression in this heatmap includes both DE-expressed genes (first part of the heatmap) and VE-expressed genes (the second part of heatmap), which are co-expressed in the InterVE cluster. Genes are hierarchically clustered. (b) Cumulative gene expression of Smoothened GO-FC. Boxplots show median value, bordered by upper/lower (75/25) percentile, whiskers showing max/min value in 1.5 * IQR (interquartile range) and outliers as black dots. Two-sided Mann-Whitney U test was used to determine the significance between AVE and InterVE as well as DE2 and InterVE; *=<0.05; **=<0.01; ***=<0.001; ns=non-significant. (c) CAT networks representing examples of GO-FC, where InterVE is fully separated from VE-lineages and aligned with DE-lineages. The VE-lineages are in yellow, DE-lineages in blue, InterVE in green, and other lineages in pink. (d) CAT networks representing examples of GO-FC, where InterVE is aligned with VE-lineages and separated from DE-lineages. The VE-lineages are in yellow, DE-lineages in blue, InterVE in green, and other lineages in pink. AVE – anterior visceral endoderm, DE1- early definitive endoderm, DE2 – later definitive endoderm, EmVE – embryonic visceral endoderm, ExVE – extra-embryonic endoderm, FG – foregut, FP – floorplate, HG – hindgut, InterVE – intermediate visceral endoderm, LIV – liver, MG – midgut, NOTO – notochord, PE – parietal endoderm, PS1 – early primitive streak, PS2 – later primitive streak.

Extended Data Fig. 6 Spatial transcriptomics revealing InterVE in E7.5 embryos.

(a) Feature importance plot generated by decision tree showing the most important genes to enable the identification of the InterVE population. (b) Heatmap representing InterVE cells and 25 genes used for spatial transcriptomics. (c) Similar pattern as in (b) is obtained when the same 25 genes are projected in a heatmap of the identified InterVE cells in the embryo section in Fig. 4d. (d) Multiple sections of E7.5 embryos showing InterVE cells (in red, probability>0.5) identified by the decision tree. The InterVE cells are present on both anterior and posterior sides of the embryo but at this stage they are found predominantly in the anterior side. Colour-code represents the probability of a cell being InterVE. (e) PAGA trajectory inference of selected clusters in Nowotschin-2019 dataset. EmVE2 (corresponding to our InterVE) connects to various gut clusters along the anterior posterior axis of the developing gut. (f) Dotplot of AVE markers in the subclustered Nowotchin-2019 dataset. Based on CAT alignment (Fig. 2c), embryonic stage (Supplementary Dataset 4) and markers shown here, EmVE0 represents AVE at E6.5, EmVE3 and EmVE4 represent AVE at E5.5. (g) Sankey diagram representing alignments in between the Now-EmVE sub-clusters. EmVE2 (equivalent to our InterVE, Fig. 2c) is aligning with EmVE0 (equivalent to our AVE) suggesting a link between InterVE and AVE. DE - definitive endoderm, VE – visceral endoderm.

Extended Data Fig. 7 Differentiation of ESCs in vitro to generate distinct in vivo-like populations.

(a) Violin plots represent gene expression of the four most common genes used to purify DE in vitro. Two-sided Mann-Whitney U was used to determine the significance between VE clusters (AVE, EmVE, ExVE1 and ExVE2) and DE clusters (DE1 and DE2); *=<0.05; **=<0.01; ***=<0.001; ns=non-significant. (b) FACS plots showing the sorting strategy for isolating specific cell populations at various stages of 2D-ESC differentiation using the Gsc-GFP/Hhex-RedStar double reporter. (c) Sample representation within each differentiation protocol. Samples distribute evenly across the appropriate clusters. (d) Expression of known lineage markers agrees with the assigned cluster identities. DE- definitive endoderm, PrE – primitive endoderm, PS- primitive streak, VE –visceral endoderm.

Extended Data Fig. 8 Comparison of ESC in vitro differentiation protocols to in vivo populations.

(a) UMAP dimensional embedding of 2D-ESC and 2D-ESC-Pi3ki datasets. (b-c) Sankey diagrams representing significant alignments between clusters from 2D-ESC + PI3Ki protocols and our in vivo dataset. The alignments to DE2 and hindgut lineages are highlighted in red in (b) for fraction of 2D-ESC cells and in (c) for fraction of 2D-ESC-PI3Ki cells. The height of the cluster-bars to the left represents the proportion of cells in each cluster from (b) 2D-protocol and (c) PI3Ki-protocol. The width of the lines is given by the cluster-height divided by the number of alignments. D4 – Day 4, D5 – Day 5, D6 – Day 6. (d) UMAP dimensional embedding of 2D-ESC and 3D-ESC protocol highlighting that even when 2 different cell lines are used, the 2D and 3D protocols cluster together. (e) Scheme of calculating similarity measure S = 1-n_DE/N_E (1-n_EE/(n_DE (n_DE-1))). In this example, the total number of in vivo lineages, N_E = 5; in the bottom right panel, number of alignments, n_DE = 4 (red and green arrows); number of alignments among the four in vivo lineages n_EE = 2. DE1- early definitive endoderm, DE – definitive endoderm, DE2 – later definitive endoderm, FP – floorplate progenitors, PS2 – later primitive streak.

Extended Data Fig. 9 Characterization of nEnd and nEnd vs ESC differentiation.

(a) Full heatmap representing differentially expressed PrE genes from Now-2019 dataset. All clusters besides nEnd1 and nEnd2 are from Now-2019 dataset. The nEnd1, nEnd2, Now-PrE and Now-ParE form a hierarchal cluster. (b) Immuno-fluorescence staining of nEnd-spheroids for CDX2, FOXA2 and E-CAD. Results are representative of 4 independent experiments. (c) RT-qPCR of InterVE, nEnd and gut markers during the nEnd spheroid differentiation. The bars represent standard error of the mean over n = 4 biologically independent experiments. Unpaired t-test was used to determine the significance; * = <0.05; **=<0.01; ***=<0.001; ****=<0.0001. (d) Dotplot showing nEnd, InterVE and gut markers in MARS-seq dataset consisting of nEnd cells differentiating into nEnd spheroids. (e) RNA velocity on nEnd differentiation into nEnd spheroids. (f) RNA velocity on ESC differentiation using the 2D protocol. (g) Sankey diagram representing alignments between the spheroid gut differentiation and our in vivo dataset. DE - definitive endoderm, InterVE – intermediate visceral endoderm, nEnd – naïve extra-embryonic endoderm, PS – primitive streak. AVE – anterior visceral endoderm, DE2 – later definitive endoderm, EmVE – embryonic visceral endoderm, ExVE – extra-embryonic endoderm, InterVE – Intermediate visceral endoderm, PE – parietal endoderm.

Source data

Supplementary information

Reporting Summary

Supplementary Data 1

List of in vivo DEGs for all defined cell types. Gene significance and fold-change (log10 base) was determined using Mann–Whitney U test, followed by Bonferroni correction for multiple testing. List of markers were filtered as follows: average log fold change >0.5 and adjusted P value <0.05.

Supplementary Data 2

Distribution of individual samples across each cluster in the in vivo dataset.

Supplementary Data 3

DEGs of subclustered in vivo dataset including PS, DE, node and visceral endoderm. Gene significance and fold-change (log10 base) was determined using Mann–Whitney U test, followed by Bonferroni correction for multiple testing. List of markers were filtered as follows: average log fold change >0.5 and adjusted P value <0.05.

Supplementary Data 4

Distribution of E5.5–E7.5 samples across EmVE clusters in Nowotschin-2019 dataset.

Supplementary Data 5

DEGs between E7.5 and E8.5 DE clusters in the in vivo dataset.

Supplementary Data 6

GO analysis of DEGs between InterVE and other VE clusters and between InterVE and DE2.

Supplementary Data 7

List of genes included in each GO-FC.

Supplementary Data 8

Overview of in vitro protocols used in this study.

Supplementary Data 9

Number of cells FACS-sorted for each in vitro protocol used in this study.

Supplementary Data 10

Overview of genes contributing to the low similarity measure for each GO-FC.

Supplementary Data 11

List of antibodies used in this study.

Supplementary Data 12

List of primers and UPL probes used in this study.

Supplementary Data 13

Details for single-cell resolution including barcodes, reads, mapping and genes.

Supplementary Data 14

Gene names and catalogue numbers for the specific probes designed by Resolve BioSciences.

Source data

Source Data Fig. 2

Statistical source data for bar plots in Fig. 2e.

Source Data Fig. 3

Source data for Fig. 3b.

Source Data Fig. 5

Source data for Fig. 5f.

Source Data Extended Data Fig. 2

Source data for Extended Data Fig. 2b.

Source Data Extended Data Fig. 9

Statistical source data for RT–qPCR in Extended Data Fig. 9c.

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Rothová, M.M., Nielsen, A.V., Proks, M. et al. Identification of the central intermediate in the extra-embryonic to embryonic endoderm transition through single-cell transcriptomics. Nat Cell Biol 24, 833–844 (2022). https://doi.org/10.1038/s41556-022-00923-x

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