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De novo construction of T cell compartment in humanized mice engrafted with iPSC-derived thymus organoids

Nature Methods volume 19, pages 1306–1319 (2022)Cite this article

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Abstract

Hematopoietic humanized (hu) mice are powerful tools for modeling the action of human immune system and are widely used for preclinical studies and drug discovery. However, generating a functional human T cell compartment in hu mice remains challenging, primarily due to the species-related differences between human and mouse thymus. While engrafting human fetal thymic tissues can support robust T cell development in hu mice, tissue scarcity and ethical concerns limit their wide use. Here, we describe the tissue engineering of human thymus organoids from inducible pluripotent stem cells (iPSC-thymus) that can support the de novo generation of a diverse population of functional human T cells. T cells of iPSC-thymus-engrafted hu mice could mediate both cellular and humoral immune responses, including mounting robust proinflammatory responses on T cell receptor engagement, inhibiting allogeneic tumor graft growth and facilitating efficient Ig class switching. Our findings indicate that hu mice engrafted with iPSC-thymus can serve as a new animal model to study human T cell-mediated immunity and accelerate the translation of findings from animal studies into the clinic.

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Fig. 1: Differentiation of human iPSCs into TEPCs in 3D alginate hydrogel capsule.
Fig. 2: scRNA-seq analysis of iPSC-TECs.
Fig. 3: iPSC-thymus organoids can support the progression of T cell program in vitro.
Fig. 4: Development of multiple hematopoietic lineages in hu.Thor mice.
Fig. 5: Development of functional human T cell subsets in hu.Thor mice.
Fig. 6: hu.Thor mice can effective reject allogeneic teratomas derived from iPSCs.

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Data availability

All the data and materials are available from corresponding authors on reasonable request. Single-cell datasets (2D iPSC-TECs and 3D iPSC-TECs) are deposited at the National Centre for Biotechology Information Gene Expression Omnibus repository with accession number GSE201675. Source data are provided with this paper.

Code availability

The software code used to analyze scRNA-seq data is modified from the Seurat package (https://satijalab.org/seurat/), and is included in the supplementary information.

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Acknowledgements

We thank E. Moravcikova for support with FCM, A. Sanguino for assistance with pathological assessment of teratomas, D. Graziano for assistance with HLA typing, H. Monroe and the University of Pittsburgh Genomics Research core for their expertise in scRNA preparation and analysis, and B. Phillips and W. Rudert for insightful suggestions and discussions of the project. Figure 3a was created with BioRender.com. This study was supported in part by the National Institutes of Health (grant nos. Y.F., R01 AI123392 and R21 AI126335), National Science Foundation (Y.F. and I.B., CBET, standard grant no. 1804728), PA Health Department research grant (M.T., SAP no. 4100079708). C.M. and H.G. were supported by Highmark Health Award (grant no. A023948-HIGHMARK-LANNI-FAN). We also thank the Center for Biologic imaging University of Pittsburgh for the use of imaging facilities under the grant no. 1S10OD019973-01.

Author information

Author notes

  1. These authors contributed equally: Connor Wiegand, Wen Liu, Catherine McCormick.

Authors and Affiliations

  1. Institute of Cellular Therapeutics, Allegheny Health Network, Pittsburgh, PA, USA

    Ann Zeleniak, Wen Liu, Suzanne Bertera, Robert Lakomy, Asako Tajima, Henry Cohen, Stephanie Wong, Massimo Trucco & Yong Fan

  2. Department of Chemical and Petroleum Engineering, University of Pittsburgh, Pittsburgh, PA, USA

    Connor Wiegand, Ravikumar K., Benjamin Mizerak & Ipsita Banerjee

  3. Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA, USA

    Catherine McCormick, Haonan Guan, Massimo Trucco & Yong Fan

  4. Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA

    Amir Alavi & Ziv Bar-Joseph

  5. Department of Pathology and Laboratory Medicine, Allegheny General Hospital, Pittsburgh, PA, USA

    Lame Balikani

  6. Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, USA

    Massimo Trucco & Yong Fan

  7. Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA

    Yong Fan

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Contributions

Y.F. and I.B. initiated the project. Y.F., I.B., M.T. and A.Z. designed the study. A.Z., C.W., W.L., C.M., A.T., H.C., H.G., R.K., S.W., S.B., R.L., R.K., L.B., B.M. and Y.F. performed experiments. A.A., C.M., Y.F. and Z.B.J. performed the computational analysis of scRNA-seq data. Y.F., A.Z. and I.B. wrote the manuscript. All authors reviewed and edited the manuscript.

Corresponding author

Correspondence to Yong Fan.

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Nature Methods thanks the anonymous reviewers for their contribution to the peer review of this work. Primary Handling Editor: Madhura Mukhopadhyay, in collaboration with the Nature Methods team.

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Extended data

Extended Data Fig. 1 RT-qPCR analysis of genes associated with TEC differentiation.

RNA samples were isolated from undifferentiated iPSCs (UD), 2D TECs (2D), and 3D TECs and were subjected to RT-qPCR analysis of expression of epithelium-associated cytokeratin genes (a), cortical TEC (cTEC)-specific genes (b), undifferentiated and early stem cell markers (c), early progenitors of the thymic epithelium (d), mTEC specific markers (e), and markers of the parathyroid (GCM and PTH), mesenchymal (TCF21 and PDGFRA), and cardiomyocyte lineages (NKX2-5 and TBX5) (f). Levels of gene expression were normalized to hGAPDH. Shown are results of triplicates from at least three independent isolations. Data are presented as mean values +/− SEM using a two-tailed unpaired t test. * p < 0.05; ** p < 0.01; *** p < 0.005. Exact p values are listed in the Supporting Information.

Source data

Extended Data Fig. 2 Immunofluorescence analysis of human FOXN1 expression in 3D iPSC-TECs.

Immunofluorescent images of 3D iPSC-TEC aggregates stained with antibodies against human FOXN1 (red) and counterstained with Hoechst 33342 for nucleus (blue). Primary human thymic epithelial cells and lymph node fibroblasts were used as positive and negative controls, respectively. White scale bar, 25um. Shown are representative images from three independent iPSC-TEC differentiations with similar results.

Extended Data Fig. 3 scRNA-seq analysis of iPSC-TECs.

a. Annotation of key human leukocyte antigen (HLA) gene expression on 2D and 3D iPSC-TEC Seurat clusters. 3D iPSC-TECs display higher levels of HLA gene expression compared with 2D iPSC-TECs. b. c. Annotation of EMT-associated gene expression in 2D and 3D iPSC-TEC clusters, highlighting the phenotypic similarity between 2D-1 and 3D-2 clusters (double arrows).

Extended Data Fig. 4 Pro-T/iPSC-TEC thymus organoids support progression of T cell development in vitro.

a. FCM analysis of CD4 and CD8 expression in cells of Pro-T/iPSC-TEC thymus organoids (lower panels) after one week of in vitro culture. Upper panels, cells dissociated from one week cultured decellularized scaffolds seeded with Pro-T cells alone (Pro-T scaffolds) as controls. Shown are representative FCM graphs from at least three independent experiments with similar results. b. FCM analysis of thymic output from Pro-T/iPSC-TEC thymus organoids (lower panels) and Pro-T scaffold controls (upper panels). hCD45+ cells were examined for key surface markers of T cell development (CD1a + CD3 + , left columns), TCRab (middle columns), and CD4 and CD8 (right columns). Shown are representative graphs of at least two independent experiments for the Pro-T control output and at least five independent experiments for Pro-T/iPSC-TEC thymus organoid output with similar results.

Extended Data Fig. 5 T cell development in hu.Thor mice generated from iPSC-TEC thymus engraftment.

a. Schematic of the timeline (upper panel) and treatments (lower panel) of four groups (G1-G4) of humanized mice. b. FCM analysis of hCD4+ and hCD8 + T cells (middle panels) in the hCD45 + mCD45-hCD3+ gate (left panels) and CD20 + B cells (right panels) of hu.Thor, hu.PBMC, and hu.SRC mice. Shown are representative FCM graphs from at least four mice of each type with similar results.

Extended Data Fig. 6 HPC/iPSC-TEC thymus-engrafted hu mice displayed increased human cell chimerisim over time.

a. FCM analysis of human CD45 + (hCD45+) versus mouse CD45 + (mCD45+) cells in peripheral blood of G1-G4 mice at 12-weeks post-transplantation. Left panel shows hu.PBMC blood as a positive control. Shown are representative graphs from at least five independent mice from each group with similar results. b. Dot plots showing percentages of hCD45+ cells in peripheral blood of four groups of hu mice (G1-G4) at 12-week post-transplantation. Data are shown as mean +/− SEM, analyzed by two-tailed, Mann-Whitney test. c-d. Cells were isolated from the bone marrow of G1-G4 hu mice (18-40 weeks post-transplantation) and analyzed with FCM for overall ratios of human cell chimerism (% of hCD45 in total CD45 + cells). c. Representative FCM graphs from at least five independent mice from each group. d. Dot plots showing the percentages of hCD45+ cells as mean +/− SEM, analyzed by two-tailed, Mann-Whitney test. e. Progression of hCD45+ cell chimerism in hu.Thor mice with time. Shown are % of hCD45+ cells (over total CD45 + cells) in peripheral blood of hu.Thor mice 4 (n = 9), 8 (n = 28), 12 (n = 25) and 24 (n = 10) weeks post iPSC-TEC thymus transplantation. Data are denoted as mean +/− SEM with two-tailed, unpaired Welch’s t test.

Source data

Extended Data Fig. 7 Multiple hematopoietic lineage development in hu.Thor mice after 4-weeks of iPSC-TEC thymus transplantation.

Gating strategy for characterization of hu.Thor splenocytes. Singlets were then gated on hCD45 versus mCD45, and only hCD45+ cells were used as the entry gate into lineage study. Staining was completed for T cells (CD4 and CD8, top right panel), B cells and dendritic cells (CD20 and CD11c, second from top right panel), myeloid and NK cells (CD33 and CD56, third from the top right panel), and monocyte cells (CD14, bottom panel). Shown are representative of three independent experiments with similar results.

Extended Data Fig. 8 Generation of CD4 + and CD8 + T cells in hu.Thor mice.

Splenocytes were harvested from hu.SRC (n = 10), hu.Thor at 4 weeks post-transplantation (4w), hu.Thor (n = 9, 16-weeks) and hu.PBMC mice and analyzed with FCM for CD4 + and CD8 + T cell populations. a and c. Total numbers of CD4 + T cells (a) and CD8 + T cells (c). b and d. Percentage of CD4 + T cells (b) and CD8 + T cells (d). Data are presented as bar graphs with mean values +/− SEM using a two-tailed Mann-Whitney test, where p < 0.05 is considered as significance.

Source data

Extended Data Fig. 9 CytoStim-mediated IL-2 and IFNg production in hu.Thor CD3 + T-cells.

Splenocytes and bone marrow cells were harvested and mixed at 1:1 ratio from hu.Thor (n = 4) and hu.PBMC (n = 3), and stimulated with CytoStim (a and c, lower panels) for 6 hours, and intracellularly stained for IL-2 (a and b) and IFNg (c and d). a and c. FCM analysis of IL2- (a) and IFNg- (c) producing cells in the hCD45 + CD3 + T cell populations. Shown are representative FCM graphs from three independent experiments with similar results. b and d. Percentages of IL2 + (b) and IFNg + (d) hCD3 + T cells before (blue dots) and after (red dots) CytoStim stimulation. Data were analyzed with paired, two-tailed t-test. p < 0.05 is considered as significance.

Source data

Extended Data Fig. 10 Generation of major human immunoglobulin classes in hu.Thor mice.

Sera were harvested from hu.Thor mice (n = 15) at 16-18 weeks post-transplantation. Isotypes of human immunoglobulin classes were quantified with Luminex isotyping kit. Upper rows show the primary classes of immunoglobulin. Lower rows show the IgG subclasses. Sera from hu.SRC mice (n = 8) at similar post-transplant ages were used as controls. Sera from untreated NSG mice (n = 8) were used as negative control to show the background of the assay. Data are shown as dot plots with mean (bar). Statistical analysis was performed between hu.SRC and hu.Thor samples with a two-tailed Mann-Whitney test. p < 0.05 is considered as significance.

Source data

Supplementary information

Supplementary Information

Supplementary Figs. 1–21 and Tables 1–3.

Reporting Summary

Supplementary Software

Single-cell datasets (2D iPSC-TECs and 3D iPSC-TECs) are deposited at the NCBI GEO repository (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE201675). The software codes folder contains two html files, with the software codes and the results (based on Seurat R packages). The main code is presented in the file entitled Software codes for comparison_with_Campinoti_and_Zeng.html. If running in R, it will call codes in the second file, entitled Zeng_TEC.html. The files can be opened in web browsers, such as Chrome. Reference datasets are from the two following references: Campinoti et al.21, Zeng et al. Single-cell RNA sequencing resolves spatiotemporal development of pre-thymic lymphoid progenitors and thymus organogenesis in human embryos. Immunity 51, 930–948 (2019). Reference datasets from Campinoti et al.21: CD205-EpCAMhi mTEC I. CD205-EpCAMhi mTEC II. CD205+EpCAMlow cTEC II. CD205+EpCAMlow cTEC I. Reference datasets from Zeng et al. (2019): GSM3905999_w8_w10_epi_UMI_data.txt.gz. GSM3905997_w8_early_epi_UMI_data.txt. GSM3905998_w9_epi_UMI_data.txt.

Source data

Source Data Fig. 1

Y1 iPSC-TEC thymus aggregate size distribution statistical source data.

Source Data Fig. 3

Statistical source data for in vitro T cell generation in Fig. 3d–g.

Source Data Fig. 4

Statistical source data for hCD45+ cells, CD3+ T cells and CD220+ B cells in spleens of hu.Thor mice.

Source Data Fig. 5

Statistical source of Fig. 5a TRBV and Fig. 5d,g,h for T cell activation analysis.

Source Data Extended Data Fig. 1

Statistical source for RT–qPCR analysis for Extended Data Fig. 1 and exact P values (including Supplementary Figs. 3 and 4).

Source Data Extended Data Fig. 6

Statistical source for Extended Data Fig. 6 blood and bone marrow hCD45+.

Source Data Extended Data Fig. 8

Statistical source for Extended Data Fig. 8 CD4-CD8 development.

Source Data Extended Data Fig. 9

Statistical source for Fig. 9 IFNg and IL2 activation.

Source Data Extended Data Fig. 10

Statistical source for hu.Thor Ig analysis.

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Zeleniak, A., Wiegand, C., Liu, W. et al. De novo construction of T cell compartment in humanized mice engrafted with iPSC-derived thymus organoids. Nat Methods 19, 1306–1319 (2022). https://doi.org/10.1038/s41592-022-01583-3

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