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Progenitor T-cell differentiation from hematopoietic stem cells using Delta-like-4 and VCAM-1

Nature Methods volume 14, pages 531–538 (2017)Cite this article

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Abstract

The molecular and cellular signals that guide T-cell development from hematopoietic stem and progenitor cells (HSPCs) remain poorly understood. The thymic microenvironment integrates multiple niche molecules to potentiate T-cell development in vivo. Recapitulating these signals in vitro in a stromal cell-free system has been challenging and limits T-cell generation technologies. Here, we describe a fully defined engineered in vitro niche capable of guiding T-lineage development from HSPCs. Synergistic interactions between Notch ligand Delta-like 4 and vascular cell adhesion molecule 1 (VCAM-1) were leveraged to enhance Notch signaling and progenitor T-cell differentiation rates. The engineered thymus-like niche enables in vitro production of mouse Sca-1+cKit+ and human CD34+ HSPC-derived CD7+ progenitor T-cells capable of in vivo thymus colonization and maturation into cytokine-producing CD3+ T-cells. This engineered thymic-like niche provides a platform for in vitro analysis of human T-cell development as well as clinical-scale cell production for future development of immunotherapeutic applications.

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Figure 1: Optimization of T-cell differentiation in defined medium.
Figure 2: VCAM-1 enhances committed DN3 proT-cell yield in the engineered thymic-like niche.
Figure 3: Human HSPCs generate proT-cells in the engineered thymic-like niche.
Figure 4: Human proT-cells home and mature in vivo.

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Acknowledgements

The authors thank the donors and the Research Centre for Women's and Infants' Health BioBank of Mount Sinai Hospital for the human specimens used in this study and all the operators at the Sick Kids-University Health Network Flow Cytometry Facility for their technical support in cell sorting. The authors thank W. Wang and E. Piccinini for their assistance in processing fetal liver samples, T. Usenko for assistance in processing umbilical cord blood samples, J. Östblom for providing training in computational programming, C. Bauwens for assistance in editing the manuscript, J. Ma for illustrating the summary cartoon figure, and all members of the P.W.Z. laboratory for their helpful discussion. This work was supported by the Leukemia and Lymphoma Society of Canada (grant no. 493946 to P.W.Z.), the Canadian Institutes for Health Research (CIHR) (grant no. MOP-119538 to J.C.Z.-P.; grant no. 489401 and 452750 to P.W.Z.), Medicine by Design, a Canada First Research Excellence Program at the University of Toronto (grant no. C1TPA-2016-20 to J.C.Z.-P.; grant no. 499470 to P.W.Z.), and the Krembil Foundation (to J.C.Z.-P.). S.S. was supported by the CIHR Vanier Canada Graduate Scholarship and the NSERC CREATE M3 Scholarship. J.C.Z.-P. is the Canada Research Chair in Developmental Immunology. P.W.Z. is the Canada Research Chair in Stem Cell Bioengineering.

Author information

Author notes

  1. Matthew A Langley and Jastaranpreet Singh: These authors contributed equally to this work.

Authors and Affiliations

  1. Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada

    Shreya Shukla, Matthew A Langley, John M Edgar & Peter W Zandstra

  2. Department of Immunology, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada

    Jastaranpreet Singh, Mahmood Mohtashami & Juan Carlos Zúñiga-Pflücker

  3. Medicine by Design, a Canada First Research Excellence Program at the University of Toronto, Toronto, Ontario, Canada

    Juan Carlos Zúñiga-Pflücker & Peter W Zandstra

  4. Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Ontario, Canada

    Peter W Zandstra

  5. Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada

    Peter W Zandstra

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Contributions

S.S. designed and performed experiments, analyzed data, and wrote the manuscript. M.A.L. performed live imaging and PCR analyses. J.S. performed in vivo experiments. J.M.E. performed certain flow cytometry experiments. M.M. provided vital reagents and feedback. J.C.Z.-P. provided critical experimental advice and edited the manuscript. P.W.Z. designed experiments and edited the manuscript.

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Correspondence to Peter W Zandstra.

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Integrated supplementary information

Supplementary Figure 1 Representative flow cytometry plots on day 7 of differentiation in IMDM+BIT serum-free medium.

Flow cytometry plots depict differentiation in IMDM+BIT serum-free medium on 10 μg/mL adsorbed DL4 ligand. Data represents mean ± SD (n = 3).

Supplementary Figure 2 Quantification of progenitor cell expansion in IMDM+BIT or αMEM+BIT serum-free medium vs. OP9 serum medium control.

(a) Total fold expansion (cell yield on day 7 of CD45+7AAD− live cells normalized to input sorted HSPCs on day 0) in the presence or absence of 10 μg/mL adsorbed DL4 in OP9 serum medium (αMEM+16% FBS) vs. serum-free media compositions (αMEM+BIT and IMDM+BIT) (n = 3). All media compositions contained the same amount of cytokines (25 ng/mL SCF, 5 ng/mL Flt3L and 1 ng/mL IL-7 in 200 μL medium/well) with a 50% medium exchange step at day 4. (b) CD11b+ myeloid cell expansion on day 7 normalized to input sorted HSPCs on day 0 in the different media compositions in the presence or absence of DL4 (n = 3). (c) CD19+ B cell expansion on day 7 normalized to input sorted HSPCs on day 0 in the different media compositions in the presence or absence of DL4 (n = 3). (d) CD25+CD90+ proT-cell expansion on day 7 normalized to input sorted HSPCs on day 0 in the different media compositions in the presence or absence of DL4 (n = 3). Data represent mean ± 95% CI. * P < 0.05; ** P < 0.01; *** P < 0.001.

Supplementary Figure 3 Quantification of frequency and yield of DN1, DN2 and DN3 proT-cell populations in IMDM+BIT or αMEM+BIT serum-free medium vs. OP9 serum medium control.

(a) Quantification of total CD45+7AAD− live cell yield at day 7 vs. frequency of DN1 (CD25−CD44+CD45+) proT-cells in OP9 serum medium (αMEM+16% FBS) vs. serum-free media compositions (αMEM+BIT and IMDM+BIT). (b) Quantification of yield of CD25+CD90+ proT-cells at day 7 vs. frequency of DN2 (CD25+CD44+CD45+) cells or (c) frequency of DN3 (CD25+CD44−CD45+) cells in different serum-free media compositions compared to OP9 serum medium control. Shaded areas were plotted using a bivariate kernel density estimate function. All data points are depicted for n = 3 independent replicates.

Supplementary Figure 4 Optimization of key assay design parameter – Notch ligand choice.

(a) Quantification of DN1, DN2, DN3, CD19+ B cell, CD11b+ myeloid and CD25+CD90+ proT-cell subset frequencies on day 7 obtained on increasing coating concentrations of DL1 ligand (n = 3). (b) Notch pathway Cbf-1 Firefly activation normalized to constitutively active Renilla plasmid after 24 hours on 0 μg/mL DL4 (no ligand; negative control) and 10 μg/mL DL4 (positive control) to test activity of DL1 at 10 and 20 μg/mL (n = 3). Data represent mean ± 95% CI. * P < 0.05; ** P < 0.01; *** P < 0.001.

Supplementary Figure 5 Optimization of key assay design parameter - HSPC seeding density.

(a) Quantification of total CD45+7AAD− live cell expansion at day 7 normalized to increasing input day 0 sorted HSPC seeding densities per cm2 (n = 3). (b) Quantification of DN1, DN2, DN3, CD19+ B cell, CD11b+ myeloid and CD25+CD90+ proT-cell subset frequencies on day 7 with increasing input day 0 sorted HSPC seeding densities per cm2 (n = 3). Data represent mean ± 95% CI. * P < 0.05; ** P < 0.01; *** P < 0.001.

Supplementary Figure 6 Optimization of key assay design parameter – well shape.

Quantification of DN1, DN2, DN3, CD19+ B cell, CD11b+ myeloid and CD25+CD90+ proT-cell subset frequencies at day 7 in U-bottom (U bot) vs. flat-bottom plates (flat bot) with no coating (- DL4) or 10 μg/ml DL4 (+ DL4) on day 0 (n = 3). Data represent mean ± 95% CI. * P < 0.05; ** P < 0.01; *** P < 0.001.

Supplementary Figure 7 Design of Experiment (DOE) in silico modeling to optimize cytokine concentrations and eliminate re-feeding.

(a) DOE response surface method was implemented to optimize the concentrations of SCF, Flt3L and IL-7 for the “no-feed” differentiation strategy. The design cube depicts the range of concentrations tested in the DOE model. (b) Schematic for elimination of day 4 medium exchange while reducing medium consumption. Baseline “re-feed” differentiation strategy involved seeding cells in 200 μL medium/well with 50% media exchange at day 4 with double the cytokine concentration at day 0 to maintain the same concentration. Our baseline control used 25 ng/mL SCF, 5 ng/mL Flt3L and 1 ng/mL IL-7 in 200μL medium/well (25-5-1 re-feed condition) based on previously published OP9 stromal co-culture. The optimized “no-feed” differentiation strategy involved seeding cells in 50 μL medium/well with higher cytokine concentrations and no medium exchange at day 4. (c) Surface response curve depicting desirability of varying SCF and IL-7 test concentrations at the optimal constant Flt3L concentration to maximize committed DN3 proT-cell frequency. (d) In vitro testing of the top predicted cytokine concentration hits from the in silico DOE model. Quantification of CD25+CD90+ proT-cell yield vs. DN2 frequency at day 7 with the positive control (25-5-1 re-feed condition) vs. the optimized no-feed process. By simply increasing the IL-7 concentration from 2 to 10 ng/mL (50-10-10 no-feed condition), the cells produced a significantly higher yield of DN2 and higher frequency and yield of T lineage-committed DN3 cells than the control (Fig. 1f). Shaded areas were plotted using a bivariate kernel density estimate function. All data points are depicted for n = 3 independent replicates.

Supplementary Figure 8 Increasing concentrations of VCAM-1 and not fibronectin enhance DN3 proT-cell commitment and yield.

(a) A screening study was performed to assess the effect of different concentrations of several cytokines (IL-6, soluble IL-6R (sIL6R), IL-11, IL-7, leukemia inhibitory factor (LIF)), chemokines (CCL25, SDF1α) and matrix protein (VCAM-1) on T-lineage committed DN3 cell frequency on day 7 of culture (n = 3). (b) Sorted HSPCs were cultured on 10 μg/mL DL4 alone or 10 μg/mL DL4 with increasing concentrations of fibronectin (0.5, 1.0 and 5.0 μg/mL). The concentrations of fibronectin are equivalent in molar concentrations to VCAM-1 tested in these dose titration experiments. DN1, DN2, DN3, CD19+ B cell, CD11b+ myeloid and CD25+CD90+ proT-cell frequencies were quantified on day 7 (n = 3). (c) Quantification on day 7 of total DN3 proT-cell yield on 10 μg/mL DL4 alone or 10 μg/mL DL4 with increasing concentrations of VCAM-1 (0.24, 0.47 and 2.32 μg/mL) (n = 4). Data represent mean ± 95% CI. * P < 0.05; ** P < 0.01; *** P < 0.001.

Supplementary Figure 9 Live imaging of differentiating proT-cells in the serum-free and feeder-free engineered thymic niche.

Representative still image from live imaging of differentiating day 7 proT-cells in the DL4+VCAM-1 engineered thymic niche. Cells were stained for CD25 (magenta) and CD44 (green) and merged with bright-field. Scale bar, 100μm.

Supplementary Figure 10 VCAM-1 synergizes with DL4 to enhance proT-cell differentiation and Notch pathway activation.

(a) Sorted HSPCs were cultured on sub-optimal 5 μg/mL DL4 alone or 5 μg/mL DL4 with increasing concentrations of VCAM-1 (0.24, 0.47 and 2.32 μg/mL). DN1, DN2, DN3, CD19+ B cell, CD11b+ myeloid and CD25+CD90+ proT-cell frequencies were quantified on day 7 (n = 3). (b) Notch pathway Cbf-1 Firefly activation normalized to constitutively active Renilla plasmid after 24 hours on no ligand (negative control), 2.32 μg/mL VCAM-1, 10 μg/mL DL4 (positive control) and 10 μg/mL DL4 with 2.32 μg/mL VCAM-1 (n = 4). Data represent mean ± 95% CI. * P < 0.05; ** P < 0.01; *** P < 0.001.

Supplementary Figure 11 Rapid DN2 and DN3 proT-cell differentiation within first two days of culture on DL4+VCAM-1 than DL4 alone.

Representative flow plots of HSPCs 24 and 48 hours after culture on DL4 vs. DL4+VCAM-1 (n = 4).

Supplementary Figure 12 Input CD34+ frequency of human HSPCs.

The purity of the input umbilical cord blood-derived HSPCs was verified to be greater than 95% CD34+ prior to initiation of each culture. CD34+ frequency was assessed on 7AAD− live cell population (n = 3).

Supplementary Figure 13 qRT-PCR gene expression in human HSPCs after 24 hours of culture.

qRT-PCR gene expression of downstream Notch pathway genes (HES1, DELTEX, NOTCH1, BCL11B, GATA3, TCF7), a HSPC gene (E2A) and a myeloid lineage gene (PU.1) on no coating, 2.32 μg/mL VCAM-1, 10 μg/mL DL4, or DL4+VCAM-1 after 24 hours of culture with human CD34+ HSPCs (n = 5). Data represent mean ± SE. * P < 0.05; ** P < 0.01; *** P < 0.001.

Supplementary Figure 14 Comparison of day 14 proT-cell frequencies from OP9-DL4 co-culture or DL4+VCAM-1 engineered thymic niche.

Quantification of CD7+CD34+, CD7+CD34− and CD7+CD5+ populations after 14 days of OP9-DL4 co-culture or on the engineered thymic niche (n = 6). Data represent mean ± 95% CI. * P < 0.05; ** P < 0.01; *** P < 0.001.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–14 and Supplementary Tables 1–32 (PDF 2609 kb)

Live cell time-lapse imaging of proT-cells on DL4

Transmitted light, 10-minute frame interval. (MOV 5149 kb)

Live cell time-lapse imaging of proT-cells on DL4+VCAM-1

Transmitted light, 10-minute frame interval. (MOV 5754 kb)

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Shukla, S., Langley, M., Singh, J. et al. Progenitor T-cell differentiation from hematopoietic stem cells using Delta-like-4 and VCAM-1. Nat Methods 14, 531–538 (2017). https://doi.org/10.1038/nmeth.4258

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