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Dntt expression reveals developmental hierarchy and lineage specification of hematopoietic progenitors

Nature Immunology volume 23, pages 505–517 (2022)Cite this article

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Abstract

Intrinsic and extrinsic cues determine developmental trajectories of hematopoietic stem cells (HSCs) towards erythroid, myeloid and lymphoid lineages. Using two newly generated transgenic mice that report and trace the expression of terminal deoxynucleotidyl transferase (TdT), transient induction of TdT was detected on a newly identified multipotent progenitor (MPP) subset that lacked self-renewal capacity but maintained multilineage differentiation potential. TdT induction on MPPs reflected a transcriptionally dynamic but uncommitted stage, characterized by low expression of lineage-associated genes. Single-cell CITE-seq indicated that multipotency in the TdT+ MPPs is associated with expression of the endothelial cell adhesion molecule ESAM. Stable and progressive upregulation of TdT defined the lymphoid developmental trajectory. Collectively, we here identify a new multipotent progenitor within the MPP4 compartment. Specification and commitment are defined by downregulation of ESAM which marks the progressive loss of alternative fates along all lineages.

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Fig. 1: TdT reporter and lineage tracing expression in T and B cells.
Fig. 2: TdT expression and tracing across mature cells and progenitors.
Fig. 3: Functional heterogeneity of MPPs by TdT lineage tracing.
Fig. 4: CITE-seq reveals heterogeneity and lineage bias within LSKs.
Fig. 5: Plasticity and multilineage potential of MPP4s.
Fig. 6: ESAM expression defines developmental hierarchy in MPPs.
Fig. 7: Irradiation pauses the lymphoid program in MPPs.

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Acknowledgements

We dedicate this work to the memory of T. Rolink, who has been a great mentor and a friend to all of us. His vision and passion for research will remain. We acknowledge C. Engdahl, G. Capoferri, M. Burgunder and S. Sikanjic for their contributions. We thank A. Offinger and L. Davidson and both teams of animal caretakers at the DBM Basel and NIDCR USA for constant support. Further we would like to acknowledge the Genomics Facility Basel (D-BSSE ETH Zürich) for generating the CITE-seq dataset. Calculations were performed at sciCORE (http://scicore.unibas.ch/) scientific computing center at the University of Basel. We also thank Y. Belkaid, G. Trinchieri, A. Bhandoola and C. Dunbar for their inputs and discussion. This work was in part supported by the SNF grants PP00P3_179056, 310030_185193 and by the Research Fund of the University of Basel for the promotion of excellent junior researchers (FK). This research was in part supported by the Intramural Research Program of the NIH, NIDCR (ZIADE000752-02).

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Authors and Affiliations

  1. Department of Biomedicine, University of Basel, Basel, Switzerland

    Fabian Klein, Julien Roux, Grozdan Cvijetic, Patrick Fernandes Rodrigues, Lilly von Muenchow, Panagiotis Tsapogas & Roxane Tussiwand

  2. Swiss Institute of Bioinformatics, Basel, Switzerland

    Julien Roux

  3. National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, USA

    Grozdan Cvijetic & Roxane Tussiwand

  4. Bucher Biotec AG, Basel, Switzerland

    Lilly von Muenchow

  5. The Institute of Biomedical and Oral Research, Hebrew University, Jerusalem, Israel

    Ruth Lubin & Simon Yona

  6. Center for Transgenic Models, University of Basel, Basel, Switzerland

    Pawel Pelczar

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Contributions

F.K., G.C., P.F.R., L.v.M., P.T., S.Y., R.L., P.P. and R.T. designed and performed experiments; F.K., G.C. and P.P. generated the TdThCD4 and TdTiCre mouse lines; F.K., P.F.R., J.R. and R.T. analyzed data; F.K. and R.T. conceived the project and wrote the manuscript.

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Correspondence to Roxane Tussiwand.

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Extended data

Extended Data Fig. 1 Generation of TdThCD4 and TdTicre mice.

(a) Schematic Fig. illustrating the generation of TdThCD4 and TdTiCre mouse lines. First Cas9, guided by a specific crRNA and the common trcrRNA, introduced a double-strand break before the stop-codon of the Dntt gene. Homology directed repair resulted in the integration of ssDNA repair templates containing 200 base-pair homology regions and the P2A self-cleaving peptide followed by either the hCD4 or iCre coding sequence. Small arrows spanning the final constructs indicate primers used in (b). (b) LSK cells isolated from the BM of 6-8 weeks old TdThCD4/YFP mice were sorted based on the expression of hCD4 as indicated. Shown are bar graphs depicting the relative mRNA expression of Dntt, hCD4, iCre as well as inter-spanning transcripts of Dntt-hCD4 and Dntt iCre using primer pair combinations shown in (a) Error bars indicate s.e.m. (n=5-6). (c-d) LSK cells subdivided based on the expression of hCD4 as indicated were analyzed for intracellular TdT expression. Shown are representative histograms (c) and cumulative bar graphs of the mean fluorescence intensities (d) depicting intracellular TdT (left, n=5) and surface hCD4 (right, n=6) in TdThCD4 BM LSK. Error bars indicate s.e.m. (e) Shown is the gating strategy used to identify Ly6D+ EPLMs in the BM.

Extended Data Fig. 2 Gating strategies to identify progenitors and mature cells.

(a-d) Shown are representative FACS plots depicting the gating strategies used to identify (a) lymphocytes as B cells, CD4/CD8 T cells, gd-T cells and NK cells in the spleen; (b) pro-erythrocytes in the BM; (c) platelets in peripheral blood; (d) pDC, pDC-like, cDC1, cDC2, monocytes and granulocytes in the spleen. (e) Shown is a representative FACS plots depicting the expression of CD150 and CD48 on MPP4s gated as shown in Fig. 2c. (f, g) Shown are representative FACS plots depicting the gating strategies used to identify (f) MkPs, CFU-Es, GMPs and (g) cMoPs, MDPs and CDPs in the BM. (h-i) Shown are representative FACS plots depicting the expression of (h) intracellular TdT against hCD4 (h) and surface hCD4 plotted against CD150 (i) on the indicated progenitor subsets gated as shown in Fig. 2c.

Extended Data Fig. 3 Reduced self-renewal capacity of YFP−MPP4s.

(a-d) Shown is the distribution of Tomato+ and GFP+ in TdTmTmG mice on the indicated progenitor subsets gated as in Fig. 2c. Data are derived from 2 independent experiments (n=3). Error bars indicate s.e.m. (a) Shown is the distribution of Tomato+ (red), Double positive (orange) and GFP+ single positive (green) cells within each subset as indicated. (b) Shown is the percent distribution of GFP+Tomatohigh, GFP+Tomatoint and GFP+Tomatolow as indicated. (c) Shown is the percent distribution of cells that are Tomatohigh, Tomatoint and Tomatolow within GFP+ progenitor subsets as indicated. (d) Shown is the expression of Tomato and GFP for the indicated subsets. (e) Shown is the expression of CD150 and CD48 on IL7R+ cells pre-gated as LSK (Lin-FLT3-CD117+ Sca1+). (f-h) Shown are the gating strategies to identify and quantify (f) donor derived B cells, (g) myeloid cells, (h) and platelets in peripheral blood of recipient mice. (i) 4000 GFP+ MPP4, GFP+ or GFP- were transferred into sub-lethally irradiated WT recipients. Shown are percent reconstitution in the bone marrow of recipient animals of Tomato+ (red bars) and GFP+ (green bars) MPP2s, MPP3s and MPP4s after 2 and 4 weeks. Cumulative from 2-3 independent experiments for each timepoint (n=4-8). Error bars indicate s.e.m. (j-k) 1500 LT- (j) and ST-HSCs (k) were sorted from the BM of 6-8 weeks old WT mice and transferred i.v. in competition with 1500 YFP- MPP4s sorted from the BM of 6-8 weeks old TdTYFPCD45.1/2 mice into lethally irradiated WT CD45.1 recipient mice. 3x105 WT CD45.1 BM cells were co-injected as support cells. Shown is the percent peripheral blood reconstitution for CD11b+CD3-NK1.1- myeloid and CD19+CD11b- B cells at the indicated timepoints after transfer. Data were collected from 2 independent experiments ((j) n=7; (k) n=8). Error bars indicate s.e.m.

Extended Data Fig. 4 HSC and MPP transcriptional profiling using a posteriori gating.

LSK cells isolated from BM of four 6–8 weeks old TdThCD4/YFP double reporter mice were used for single-cell RNA sequencing in combination with CITE-Seq labelling as described in the methods. (a-c) Hierarchical clustering analysis was performed and projected in a 2-dimensional space using UMAP as explained in the methods. Each color represents a specific cluster as indicated. (a) Hierarchical clustering identified 12 clusters. (b) Cell-cycle phase, represented by the colors yellow (G1), orange (S) and red (G2), of each cell was determined as described in the methods. (c) Unique molecular identifiers (UMIs) coming from the mitochondrial (MT) genome were quantified across cells, reflected by the color intensity. Contour lines display the 2D cell density on the UMAP space. (d) Shown is a bar plot distribution indicating the frequency of cells in the different phases of the cell cycle across subsets obtained for the “a posteriori gating defined as in Fig. 4b. (e) UMAP and bar graphs illustrating the scaled expression of the Flt3, Slamf1, and Cd48 mRNA (left panels), as well as the expression of their corresponding surface markers used for CITE-Seq (right panels). The colors represent cells from the different clusters. Dot size and color intensity indicate expression levels. Bar height in bar graphs indicate the average expression across cells from each biological replicate across clusters. (f) A posteriori gating strategy used to define HSC and MPP populations within the CITE-Seq data. For MPP4: Flt3 > 2.5, CD135 > 3.5, and CD150 < 4. For MPP3: Flt3 < 2, CD135 < 3, CD150 < 4, and CD48 > 7. For MPP2: Flt3 < 2.5, CD135 < 3.5, CD150 > 5.5, and CD48 > 7. For LT-HSC: Flt3 < 2.5, CD135 < 3.5, CD150 > 5.5, and CD48 < 6.5. For ST-HSC: Flt3 < 2, CD135 < 3, CD150 < 4, and CD48 < 6.5. The colors represent cells from the different clusters. (g) Heatmap displaying the centered and scaled expression of the top differentially expressed genes between the gated populations defined as in (e), resulting in a list of 96 markers. Cells were ordered following the hierarchical clustering tree. Cluster assignment and similarity score of each cell to reference ImmGen RNA-seq samples is shown on top of the heatmap. (g) Shown is the UMAP distribution of our single cell dataset assigned using the previously published bulk RNA-Seq obtained from sorted progenitors (see gates below) from ref. 29. (i) Shown is the UMAP distribution for the integrated analysis of our dataset with the previously published scRNA-Seq obtained from ref. 34 obtained using the Seurat package (findIntegrationAnchors function)35. On the left the overlay of the two data sets on the right the scRNA-Seq obtained from ref. 34.

Extended Data Fig. 5 Single-cell gene expression profiling of LSKs.

(a-d) UMAP and bar graphs illustrating the scaled expression for selected (a) stem cell-related markers and surface receptors (Cd34, CD48, CD9, ESAM); (b) erythroid (Gata1, Klf1, Vwf, and Pf4), (c) myeloid (Mpo, Irf8, Ctsg, Elane), (d) lymphoid (Ighm, Ighd, Notch1, Lck). The colors represent cells from the different clusters. Dot size and color intensity indicate expression levels. Below is the distribution across clusters where bar height indicates the average expression across cells from each biological replicate across clusters.

Extended Data Fig. 6 Single cell profiling and functional characterization of MPP3s.

(a) UMAP and bar graphs illustrating the scaled expression of the Dntt mRNA, hCD4 surface marker, and YFP. The colors represent cells from the different clusters. Dot size and color intensity indicate expression level. Bar height in bar graph indicate the average expression across cells from each biological replicate across clusters. (b) Compiled data showing hCD4−YFP−, hCD4+YFP−, hCD4+YFP+, and hCD4−YFP+ MPP3s, annotated based on a posteriori gating as in Fig. 4b, in relation to their cluster distribution defined as in Fig. 4a; the similarity score to reference samples from the ImmGen dataset defined as in Fig. 4c; centered and scaled expression for the top 26 markers differentially expressed between subsets. (c) UMAP plot illustrating the distribution of hCD4−YFP−(grey), hCD4+YFP− (blue), hCD4+YFP+ (green), and hCD4−YFP+ (orange) MPP3 cells. (d) Bar graph showing the distribution of the subsets as in (c) across clusters defined as in Fig. 4a. The colors represent the different clusters. (e) hCD4−YFP−, hCD4+YFP+, and hCD4−YFP+ MPP3s were sorted from the BM of 6–8 weeks old TdThCD4/YFP mice and 1500 cells were transferred i.v. in competition with 1500 ST-HSCs sorted from the BM of 6–8 weeks old WT-CD45.1/2 mice into sub−lethally irradiated WT-CD45.1 recipients. Shown are the percent peripheral blood reconstitutions for B cells (CD19+CD11b-) and myeloid cells (CD11b+, CD3−, NK1.1-) at the indicated timepoints after transfer. Data were collected from 2 independent experiments (hCD4−YFP− MPP3 n = 5; hCD4+YFP+ MPP3 n = 6; hCD4−YFP+ MPP3 n = 6). A multiple two-tailed unpaired Student’s t test was performed. (Myeloid cells: hCD4−YFP− and hCD4+YFP+ day 10 P = 0.026, day 14 P = 0.03, day 18 P = 0.049; hCD4−YFP− and hCD4−YFP+ day 10 P = 0.005, day 14 P = 0.026; hCD4+YFP+ and hCD4−YFP+ day 10 P = 0.004). *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001. Error bars indicate s.e.m. (f) UMAP plot illustrating the distribution of hCD4−YFP−(grey), hCD4+YFP− (blue), hCD4+YFP+ (green), and hCD4−YFP+ (orange) MPP4 cells. (g) Bar graph showing the distribution of the subsets as in (f) across clusters defined as in Fig. 4a. The colors represent the different clusters. (h) hCD4−YFP−, hCD4+YFP+, and hCD4−YFP+ MPP4s were sorted from the BM of 6–8 weeks old TdThCD4/YFP mice and 1500 cells were transferred i.v. in competition with 1500 ST-HSCs sorted from the BM of 6–8 weeks old WT-CD45.1/2 mice into sub−lethally irradiated WT-CD45.1 recipients. Shown are the percent peripheral blood reconstitutions for B cells (CD19+CD11b-) and myeloid cells (CD11b+, CD3−, NK1.1-) at the indicated timepoints after transfer. Data were collected from 2 independent experiments (hCD4−YFP− MPP4 n = 5; hCD4+YFP+ MPP4 n = 6; hCD4−YFP+ MPP4 n = 7). A multiple two-tailed unpaired Student’s t test was performed (B cells: hCD4−YFP− and hCD4+YFP+ day 14 P = 0.008; hCD4+YFP+ and hCD4−YFP+ day 14 P = 0.002, day 18 P = 0.03; Myeloid cells: hCD4−YFP− and hCD4−YFP+ day 10 P = 0.011, day 14 P = 0.00003, day 18 P = 0.000004; hCD4+YFP+ and hCD4−YFP+ day 10 P = 0.00021, day 14 P = 0.0012, day 18 P = 0.002). *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001. Error bars indicate s.e.m.

Extended Data Fig. 7 ESAM defines the developmental hierarchy of MPPs.

(a) Two color histograms depicting the expression of YFP and ESAM from BM cells of 6–8 weeks old TdThCD4/YFP mice. Cells are pre-gated as shown in Fig. 2c. (b-c) Progenitors were defined using the “a posteriori” gating (Extended Data Fig. 4f) as ESAM negative and positive MPP2s (top) MPP3s (middle) and MPP4s (bottom). (b) Shown is the distribution with the frequency across clusters for each subset. (c) Shown are volcano plots projecting the difference in gene expression for each subset. Genes downregulated in the ESAM− fractions with an FDR < 0.01 are marked in blue and genes upregulated in the ESAM+ fractions are marked in red. Genes with an abs log2 FC > 1 are labeled. (d) 4000 ESAM negative and positive MPP2s (top) MPP3s (middle) and MPP4s (bottom) were isolated from the BM of 6–8 weeks old Rosa26mTmG mice and transferred i.v. into sub-lethally irradiated WT recipients. Shown are cumulative data with percent reconstitution of recipient animals for mature subsets (gated as shown in Extended Data Fig. 2a-d) after four weeks in the bone marrow (pro-Erythrocytes), peripheral blood (platelets) and spleen (all other subsets). Data were collected from 3 independent experiments. A multiple two-tailed unpaired Student’s t test was performed (MPP4: B cells P = 0.003, CD4+ T cells P = 0.0097, CD8+ T cells P = 0.005, pDCs P = 0.000005, monocytes P = 0.000001, pro-erythrocytes P = 0.006). **, P < 0.01; ****, P < 0.0001. Error bars indicate s.e.m. (e) Compiled data showing ESAM+hCD4−, ESAM+hCD4+, ESAM−hCD4+, and ESAM−hCD4−MPP4s, annotated based on the “a posteriori” gating as in (Extended Data Fig. 4f), in relation to their cluster distribution defined as in Fig. 4a; the similarity score to reference samples from the ImmGen dataset defined as in Fig. 4c; The top 38 differentially expressed markers and genes between subsets is centered and scaled. (f) Representative histograms illustrating the expression levels of hCD4 within LT-HSCs, ESAM+ and ESAM−MPP4s, and CLPs isolated from the BM of 6–8 weeks old TdThCD4 mice. (g) Shown is the expression of Sca-1 and ESAM for LT- and ST-HSCs (Left plot) gated as shown in Fig. 2c. LT- (in black) and ST-HSCs (color scale) are projected into a t-SNE plot. ST-HSCs are projected indicating the expression of ESAM. (h-k) CD48+ LSKs isolated from the BM of 6–8 weeks old TdThCD4 mice were sorted based on the expression of hCD4 as indicated. (h) 2000 cells were analyzed for erythroid colony forming potential (BFU-E). Shown are the number of colonies obtained. Data were collected from 3 independent experiments (n = 6). Statistical analysis was done with two-tailed unpaired Student’s t test (hCD4-neg and hCD4-int P = 0.002). *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001. Error bars indicate s.e.m. (i) Myeloid precursor frequency was determined for the indicated subsets by in vitro limiting dilution analysis, as described in methods. Shown is one representative experiment (n = 3). Error bars indicate s.e.m. (j, k) 4000 cells were transferred i.v. into sub-lethally irradiated WT-CD45.1 recipients in competition with 4000 hCD4-neg CD48+ LSK cells sorted from TdThCD4-CD45.1/2 mice. Shown is the percent peripheral blood reconstitution for CD11b+CD3−NK1.1- myeloid (j) and CD19+CD11b− B cells (k) at the indicated timepoints after transfer. Data were collected from 3 independent experiments. Error bars indicate s.e.m.

Extended Data Fig. 8 A new functional classification of early hematopoietic progenitors.

(a,b) Shown is the improved gating strategy depicting the use of ESAM to identify LT-, ST-HSCs, bona fide MPPs and oligopotent progenitors (OPP) with prominent myeloid and limited erythroid OPP-Me or prominent erythroid and limited myeloid OPP-Em potential. Lin− progenitors are pre-gated as IL-7R− and referred as LEKs (Lineage−ESAM+cKit+). LEKs are further subdivided based on FLT3 expression as bona fide MPPs (FLT3+ LEK), ST-HSCs (FLT3−CD48−CD150− LEK), LT-HSCs (FLT3−CD48−CD150+ LEK), Oligopotent Progenitors with prominent Myeloid- and limited erythroid (OPP-Me, FLT3−CD48+CD150− LEK) or prominent Erythroid and limited myeloid potential (OPP-Em, FLT3−CD48+CD150+ LEK) (c). Progenitors pre-gated as IL-7R−and referred as LSK (lineage−Sca1+ckit+) can be further subdivided based on FLT3 expression as MPP4s (FLT3+). Within this MPP4 subset the expression of ESAM in C57BL/6 mice identifies bona fide MPPs (FLT3+ESAM+ LSK), whereas the combined use of ESAM and hCD4 in TdThCD4 reporter mice allows for the identification of Lymphoid Progenitors (LP, FLT3+hCD4highESAM− LSK), and Oligopotent Progenitors with Llymphoid- and Myeloid potential (OPP-LM) (FLT3+hCD4int/lowESAM− LSK) besides MPPs (FLT3+ESAM+ LSK). FLT3−LSK can be further subdivided as shown into ST-HSCs (FLT3−ESAM+CD48−CD150− LSK), LT-HSCs (FLT3−CD48−CD150+ LSK), OPP-Me (FLT3−ESAM+CD48+CD150− LSK), OPP-Em (FLT3−ESAM+CD48+CD150+ LSK), Myeloid Progenitors (MP, FLT3−ESAM−CD48+CD150− LSK) and Erythroid Progenitors (EP, FLT3−ESAM−CD48+CD150+ LSK) as shown (d). Highlighted are the newly identified subsets. (c) Each pregated subset as obtained from Extended Data Fig. 8a,b is color coded according to their transcriptionally most similar cluster as defined in Fig. 4a and gated using selected markers (upper panel) or projected in a two-dimensional t-SNE (lower panel) plot. (d,e) Schematic model of steady state (d) and emergency (e) hematopoiesis illustrating the proposed hierarchy as observed for HSCs and MPPs in TdT-reporter and lineage tracer mice. Progenitors are labeled for hCD4, YFP, ESAM and FLT3 expression allowing for the new subset’s definition: OPP-LM, OPP-Me, OPP-Em, LP, MP and EP.

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Reagents and primers.

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DEG clusters.

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Klein, F., Roux, J., Cvijetic, G. et al. Dntt expression reveals developmental hierarchy and lineage specification of hematopoietic progenitors. Nat Immunol 23, 505–517 (2022). https://doi.org/10.1038/s41590-022-01167-5

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