Totipotency is the ability of a single cell to give rise to all of the differentiated cell types that build the conceptus, yet how to capture this property in vitro remains incompletely understood. Defining totipotency relies on a variety of assays of variable stringency. Here, we describe criteria to define totipotency. We explain how distinct criteria of increasing stringency can be used to judge totipotency by evaluating candidate totipotent cell types in mice, including early blastomeres and expanded or extended pluripotent stem cells. Our data challenge the notion that expanded or extended pluripotent states harbour increased totipotent potential relative to conventional embryonic stem cells under in vitro and in vivo conditions.
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All raw and processed sequencing data, as well as .loom files for visualization in SCope, generated in this study, have been submitted to the NCBI GEO (http://www.ncbi.nlm.nih.gov/geo/) under the accession number GSE145609 and also with further instructions at GitHub (https://github.com/pasquelab/totipotency). Furthermore, published datasets were downloaded as provided by Deng et al.41 (GEO: GSE45719), Posfai et al.4 (GEO: GSE84892), Mohammed et al.42 (GEO: GSE100597), Chen et al.43 (GEO: GSE74155), Li et al.39 (GEO: GSE135289, GSE135701), Yang et al.35 (ENA: ERP005641), Yang et al.36 (GEO: GSE89303) Pijuan-Sala et al.49 (https://github.com/MarioniLab/EmbryoTimecourse2018), Janiszewski et al.77 (GEO: GSE126229), Sozen et al.40 (GEO: GSE134240). All other data supporting the findings of this study are available from the corresponding authors on reasonable request. Source data are provided with this paper.
Codes pertaining to important analyses in this study are available from the Pasque laboratory GitHub webpage (https://github.com/pasquelab/totipotency).
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We acknowledge the contribution of the Model Production Core staff at the Center for Phenogenomics for technical support. Single-cell sequencing was performed at National Genomics Infrastructure in Stockholm at the Science for Life Laboratory (funded by the Knut and Alice Wallenberg Foundation and the Swedish Research Council) with assistance from SNIC/Uppsala Multidisciplinary Center for Advanced Computational Science with massively parallel sequencing and access to the UPPMAX computational infrastructure. Bulk RNA-seq was performed at the KU Leuven Genomics Core. We thank S. Aerts, S. Aibar, C. Davie and C. Flerin for discussions and support; and J. Wu for the C1-12 tdTomato-expressing D-EPSCs. This work was funded by CIHR (FDN-143334), Genome Canada and Ontario Genomics (OGI-099), Programme de bourses de chercheur-boursier FRQS Junior 1 (FRQS 268829, 280187), the Swedish Research Council, Ragnar Söderberg Foundation, Ming Wai Lau Center for Reparative Medicine, Center for Innovative Medicine, Wallenberg Academy Fellow, NSERC (2014-04497). Research in the Pasque laboratory is supported by The Research Foundation–Flanders (FWO; Odysseus Return Grant G0F7716N to V.P.; FWO grants G0C9320N and G0B4420N to V.P.), the KU Leuven Research Fund (BOFZAP starting grant StG/15/021BF to V.P. C1 grant C14/16/077 to V.P. and project financing) and FWO PhD fellowships to A.Janiszewski (1158318N), I.T. (1S72719N) and S.K.T. (1S75720N).
The authors declare no competing interests.
Peer review information: Peer reviewer reports are available. Nature Cell Biology thanks the anonymous reviewers for their contribution to the peer review of this work.
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Scale bar 100 µ. At least 5 brightfield images were taken of cells in each culture condition.
a, Number of DEGs between 2iLif ESCs and L-EPSCs at different days of conversion. b, Gene expression comparison of pluripotency and somatic genes between 2iLif ESCs and L-EPSCs and mouse embryonic fibroblasts (MEFs) as control. 1 sample. c, Changes in expression levels between 2iLif ESCs and L-EPSCs for genes reported to change in Yang et al.35. 1 sample. d, GSEA analysis of 4-cell stage signature genes in bulk RNA-seq data of L-EPSCs generated in this study (2iLif n = 1, EPSC n = 5) and published bulk L-EPSCs RNA-seq data (Yang et al. 35, (2iLif n = 5, EPSC n = 5), Yang et al.36 (2iLif n = 2, EPSC n = 2)). e, UMAP from Fig. 1e showing the resource from which each cell was merged, and lists the number of cells used from each. f, FeaturePlots projecting expression of representative 2-cell, EPI, PE, and TE marker genes, overlaying Fig. 1e UMAP. g, GSEA analysis of 4-cell stage signature genes in scRNA-seq data of L-EPSCs and D-EPSCs generated in this study (2iLif n = 191, L-EPSCs n = 182, D-EPSCs n = 186) and published L-EPSCs scRNA-seq data (Yang et al.35 (2iLif n = 96, EPSC=96)). *: p-value 0,05-0,01, **: p-value 0,01-0,001. h, Heatmap of genes previously reported to be upregulated in D-EPSCs compared to ESCs cultured in Lif/serum conditions, which are similarly upregulated in D-EPSCs (generated in this study) when compared to naïve 2iLif ESCs. i, Violin plot using Module A & B from Yang Y. et al., 2017, Figure 7C36 Fig. 7c, showing significant upregulation in both L-EPSCs and D-EPSCs compared to 2i. N = number of cells in each condition.
Extended Data Fig. 3 Scattering of cells during single-cell integration and gene regulatory networks analysis, related to Fig. 1.
a, Cells are binned according to their position in the integration UMAP in Fig. 1e depending on whether they occupy a position defined as ICM, TE, PE, EPI E4.5, EPI E5.5 or EPI E6.75. ScRNAseq profiles of L-EPSCs generated in this study are merged with published EPSCs signatures from the Liu lab (Liu EPSCs)35. Modular scores are then presented for each subcluster of each stem cell type. The modular scores are based on the top100 differentially expressed gene signatures defined by the corresponding embryo data. The number of cells in each group can be found in Source data Extended Fig. 3. b, UMAP constructed based on the activity of gene regulatory networks in 2iLif ESCs, embryonic stages E3.5 ICM, E4.5 EPI, E5.5 EPI, L-EPSCs and D-EPSCs.
a, Displayed is an example of the gating strategy implemented to generate flow cytometry data. The data displayed uses the iCdx2 Elf5.2A.mCherry ESCs, which are eGFP+, contain the Elf5.2A.mCherry reporter, and are stained for both CD40 and Plet1.The plots are pseudo-colour plots and the x-axis labels state markers and fluorochromes used. Laser (V=violet; B=blue; G=green; R=red) and filter bandpass information is also included on x-axis in brackets. Ancestry plots are included to show how cells were gated: majority of cells were included in FSC/SSC gate due to size discrepancy between cells of interest and underlying feeder cells. Single cells were determined by FSC-W x FSC-H and SSC-W x SSC-H plots. Live cells were gated using dead cell stain Sytox blue. Cells of interest were discriminated from underlying feeder cells (EGFP negative) by expression of eGFP. Fluorescence minus one (FMO) controls were used to establish gates in order to separate positive and negative populations.
Extended Data Fig. 5 Re-analysis of transcriptional profiling data of blastoid cells related to Fig. 3.
a, UMAP from Fig. 3a identifying original datasets4,35,39,40,42,43,50 for each cell. b, UMAP from Fig. 3a, highlighting ZG-blastoid EPI, ZG-blastoid ZG, B-blastoid TE, and ZG-blastoid intermediate. c, UMAP from Fig. 3a, highlighting ZG-blastoid populations produced with 2i/Lif vs. EPSCs. d, UMAP from Fig. 3a, highlighting B-blastoid EPI, B-blastoid PE, B-blastoid TE, and B-blastoid intermediates. e, Pie chart showing percent of each cell type category based on our re-analysis of all B-blastoid cells.
Extended Data Fig. 6 Gene regulatory network atlas spanning mouse embryo stages from morula to gastrulation and in vitro blastoid models.
a, UMAP analysis based on the activity of gene regulatory networks. b, Heatmap representing the activity of selected regulons associated with lineage-specific TFs averaged across cells from each cluster. c, Dot plot showing expression levels of NANOG, GATA4, GATA3, T and CDX2 target genes derived from gene regulatory network analysis of selected cell types.
a–d, Stacked bar charts showing percent of E4.5 and E6.25 chimeric embryos with different lineage contributions (epiblast – EPI, trophoblast (ExE and ectoplacental cone) –TB, epiblast and trophoblast position – EPI + TB position). mScarlet-NLS expressing cells were cultured in either 2i/Lif (11 chimeras analyzed at E4.5 and 8 at E6.25) or L-EPSC (15 chimeras analyzed at E4.5 and 24 at E6.25) conditions and tdTomato expressing cells were cultured in 2i/Lif (9 chimeras analyzed at E6.25) or D-EPSC (26 chimeras analyzed at E4.5 and 6 chimeras analyzed at E6.25) conditions. The number of chimeras showing different lineage contributions is indicated withing the bar chart. e-h, Representative immunofluorescent stainings of E4.5 or E6.25 chimeric embryos generated using L-EPSCs (mScarlet-NLS) or D-EPSCs (tdTomato), stained for mScarlet (detected using an mCherry antibody), tdTomato (using a DsRed antibody), SOX2 (EPI), CDX2 (TE), or ELF5 (ExE). Whole embryo images show maximum intensity projections in panels e, g and h. Single planes shown in panel f and in all magnified views. Scale bar = 20 µ. Number of chimeras analyzed: 15 in panel E, 24 in panel F, 26 in panel G, and 6 in panel H.
Immunofluorescent stainings of E12.5 chimeric placentas generated with a single blastomere of an 8-cell stage embryo that expressed either H2B-GFP or DsRed and a wild-type host embryo. H2B-GFP expressing placentas were stained for TFAP2C, TPBPA, MCT4, CD31 and GFP (top panel). DsRed expressing placentas were stained for KRT8, MCT1, CDH3 and mCherry/RFP (bottom panel). Images shown at different magnifications. Scale bars: 500 µ (4x), 200 µ (7x), 50 µ (40x). Sections from 4 chimeric placentas were analyzed.
Extended Data Fig. 9 Full panel of chimeric E12.5 placentas generated using tetraploid complementation.
Immunofluorescent staining of E12.5 chimeric placentas generated with H2B-GFP expressing tetraploid host embryo and wild-type ESCs (left panel), wild-type tetraploid host embryo and H2B-GFP expressing ESCs (middle panel) and wild-type host embryo (diploid) and H2B-GFP expressing L-EPSCs. Placenta sections are immuno-stained for GFP and the following trophoblast markers: CDH3, TPBPA, and MCT4. A total of 14 H2B-GFP positive L-EPSCs placentas were collected from two females, and 3 to 4 placentas were analyzed for each marker. Images shown at different magnifications. Scale bars: 500 µ (4x), 200 µ (7x), 50 µ (40x). Sections from 4 chimeric placentas were analyzed.
Supplementary Fig. 1: SCENIC analysis in mouse embryo stages from morula to gastrulation and in vitro blastoid models.
Supplementary Table 1: differential gene expression analysis of bulk RNA-seq data. Supplementary Table 2: Gene Ontology analysis. Supplementary Table 3: Panther pathway enrichment analysis on differentially expressed genes between ESCs and EPSCs. Supplementary Table 4: four-cell stage signature associated with Fig.1d. Supplementary Table 5: GSEA signatures for each stage. Supplementary Table 6: List of all of the primers used. Supplementary Table 7: list of all of the antibodies used.
Source data Fig. 1f.
Statistical source data Fig. 2b and Fig. 2d,e.
Flow cytometry gating strategy related to Fig. 2.
Source data Fig. 3c.
Source data Fig. 4b,d.
Source data Fig. 5c.
Source data Fig. 6b,c.
Source data for the number of differentially expressed genes Extended Data Fig. 2a.
Source data for the number of cells per group Extended Data Fig. 3a.
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Posfai, E., Schell, J.P., Janiszewski, A. et al. Evaluating totipotency using criteria of increasing stringency. Nat Cell Biol 23, 49–60 (2021). https://doi.org/10.1038/s41556-020-00609-2
Nature Communications (2021)
Nature Reviews Molecular Cell Biology (2021)
Protein & Cell (2021)