Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Engineered signaling centers for the spatially controlled patterning of human pluripotent stem cells

Nature Methods volume 16, pages 640–648 (2019)Cite this article

Subjects

Abstract

Signaling centers, localized groups of cells that secrete morphogens, play a key role in early development and organogenesis by orchestrating spatial cell fate patterning. Here we present a microfluidic approach that exposes human pluripotent stem cell (hPSC) colonies to spatiotemporally controlled morphogen gradients generated from artificial signaling centers. In response to a localized source of bone morphogenetic protein 4 (BMP4), hPSC colonies reproducibly break their intrinsic radial symmetry to produce distinct, axially arranged differentiation domains. Counteracting sources of the BMP antagonist NOGGIN enhance this spatial control of cell fate patterning. We also show how morphogen concentration and cell density affect the BMP response and germ layer patterning. These results demonstrate that the intrinsic capacity of stem cells for self-organization can be extrinsically controlled through the use of engineered signaling centers.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Design and characterization of the microfluidic device.
Fig. 2: A localized source of BMP4 biases the positioning of hPSC-derived germ layers.
Fig. 3: Effects of the BMP4 source concentration on hPSC patterning.
Fig. 4: Effects of the BMP4 source concentration on hPSC patterning dynamics.
Fig. 5: The balance between cell density and BMP4 source concentration is relevant for the patterning outcome.
Fig. 6: Counteracting sources of BMP4 and its inhibitor NOGGIN reinforce the spatial control on hPSC patterning.

Similar content being viewed by others

Data availability

All relevant data are available from the corresponding author upon reasonable request.

References

  1. McCauley, H. A. & Wells, J. M. Pluripotent stem cell-derived organoids: using principles of developmental biology to grow human tissues in a dish. Development 144, 958–962 (2017).

    Article  CAS  Google Scholar 

  2. Simunovic, M. & Brivanlou, A. H. Embryoids, organoids and gastruloids: new approaches to understanding embryogenesis. Development 144, 976–985 (2017).

    Article  CAS  Google Scholar 

  3. Taniguchi, K., Heemskerk, I. & Gumucio, D. L. Opening the black box: stem cell-based modeling of human post-implantation development. J. Cell Biol. 218, 410–421 (2018).

    Article  Google Scholar 

  4. Rossi, G., Manfrin, A. & Lutolf, M. P. Progress and potential in organoid research. Nat. Rev. Genet. 19, 671–687 (2018).

    Article  CAS  Google Scholar 

  5. Warmflash, A., Sorre, B., Etoc, F., Siggia, E. D. & Brivanlou, A. H. A method to recapitulate early embryonic spatial patterning in human embryonic stem cells. Nat. Methods 11, 847–854 (2014).

    Article  CAS  Google Scholar 

  6. Tewary, M. et al. A stepwise model of reaction–diffusion and positional information governs self-organized human peri-gastrulation-like patterning. Development 144, 4298–4312 (2017).

    Article  CAS  Google Scholar 

  7. Martyn, I., Kanno, T. Y., Ruzo, A., Siggia, E. D. & Brivanlou, A. H. Self-organization of a human organizer by combined Wnt and Nodal signalling. Nature 558, 132–135 (2018).

    Article  CAS  Google Scholar 

  8. Tam, P. P. L. & Loebel, D. A. F. Gene function in mouse embryogenesis: get set for gastrulation. Nat. Rev. Genet. 8, 368–381 (2007).

    Article  CAS  Google Scholar 

  9. Arnold, S. J. & Robertson, E. J. Making a commitment: cell lineage allocation and axis patterning in the early mouse embryo. Nat. Rev. Mol. Cell Biol. 10, 91–103 (2009).

    Article  CAS  Google Scholar 

  10. Schoenwolf, G. C., Bleyl, S. B., Brauer, P. R. & Francis-West, P. H. Larsen’s Human Embriology (Elsevier/Churchill Livingstone, 2014).

  11. Briscoe, J. & Small, S. Morphogen rules: design principles of gradient-mediated embryo patterning. Development 142, 3996–4009 (2015).

    Article  CAS  Google Scholar 

  12. Gobaa, S. et al. Artificial niche microarrays for probing single stem cell fate in high throughput. Nat. Methods 8, 949–955 (2011).

    Article  CAS  Google Scholar 

  13. Keenan, T. M. & Folch, A. Biomolecular gradients in cell culture systems. Lab Chip 8, 34–57 (2008).

    Article  CAS  Google Scholar 

  14. Etoc, F. et al. A balance between secreted inhibitors and edge sensing controls gastruloid self-organization. Dev. Cell 39, 302–315 (2016).

    Article  CAS  Google Scholar 

  15. Morgani, S. M., Metzger, J. J., Nichols, J., Siggia, E. D. & Hadjantonakis, A.-K. Micropattern differentiation of mouse pluripotent stem cells recapitulates embryo regionalized cell fate patterning. eLife 7, e32839 (2018).

    Article  Google Scholar 

  16. Schulz, L. C. et al. Human embryonic stem cells as models for trophoblast differentiation. Placenta 29, 10–16 (2008).

    Article  Google Scholar 

  17. Wolpert, L. Positional information and the spatial pattern of cellular differentiation. J. Theor. Biol. 25, 1–47 (1969).

    Article  CAS  Google Scholar 

  18. Rogers, K. W. & Schier, A. F. Morphogen gradients: from generation to interpretation. Annu. Rev. Cell Dev. Biol. 27, 377–407 (2011).

    Article  CAS  Google Scholar 

  19. Kutejova, E., Briscoe, J. & Kicheva, A. Temporal dynamics of patterning by morphogen gradients. Curr. Opin. Genet. Dev. 19, 315–322 (2009).

    Article  CAS  Google Scholar 

  20. Muller, P., Rogers, K. W., Yu, S. R., Brand, M. & Schier, A. F. Morphogen transport. Development 140, 1621–1638 (2013).

    Article  CAS  Google Scholar 

  21. Piccolo, S., Sasai, Y., Bin, L. & De Robertis, E. M. Dorsoventral patterning in Xenopus: inhibition of ventral signals by direct binding of chordin to BMP-4. Cell 86, 589–598 (1996).

    Article  CAS  Google Scholar 

  22. Zimmerman, L. B., De Jesus-Escobar, J. M. & Harland, R. M. The Spemann organizer signal noggin binds and inactivates bone morphogenetic protein 4. Cell 86, 599–606 (1996).

    Article  CAS  Google Scholar 

  23. Winnier, G., Blessing, M., Labosky, P. A. & Hogan, B. L. M. Bone morphogenetic protein-4 is required for mesoderm formation and patterning in the mouse. Genes Dev. 9, 2105–2116 (1995).

    Article  CAS  Google Scholar 

  24. Ben-Haim, N. et al. The nodal precursor acting via activin receptors induces mesoderm by maintaining a source of its convertases and BMP4. Dev. Cell 11, 313–323 (2006).

    Article  CAS  Google Scholar 

  25. Bier, E. & De Robertis, E. M. BMP gradients: a paradigm for morphogen-mediated developmental patterning. Science 348, aaa5838 (2015).

    Article  Google Scholar 

  26. Schwank, G. et al. Formation of the long range Dpp morphogen gradient. PLoS Biol. 9, e1001111 (2011).

    Article  CAS  Google Scholar 

  27. Zhou, S. et al. Free extracellular diffusion creates the Dpp morphogen gradient of the Drosophila wing disc. Curr. Biol. 22, 668–675 (2012).

    Article  CAS  Google Scholar 

  28. Yu, S. R. et al. Fgf8 morphogen gradient forms by a source–sink mechanism with freely diffusing molecules. Nature 461, 533–536 (2009).

    Article  CAS  Google Scholar 

  29. Demers, C. J. et al. Development-on-chip: in vitro neural tube patterning with a microfluidic device. Development 143, 1884–1892 (2016).

    Article  CAS  Google Scholar 

  30. Kawada, J., Kimura, H., Akutsu, H., Sakai, Y. & Fujii, T. Spatiotemporally controlled delivery of soluble factors for stem cell differentiation. Lab Chip 12, 4508–4515 (2012).

    Article  CAS  Google Scholar 

  31. Titmarsh, D. M. et al. Microbioreactor arrays for full factorial screening of exogenous and paracrine factors in human embryonic stem cell differentiation. PLoS ONE 7, e52405 (2012).

    Article  CAS  Google Scholar 

  32. Uzel, S. G. M. et al. Simultaneous or sequential orthogonal gradient formation in a 3D cell culture microfluidic platform. Small 12, 612–622 (2016).

    Article  CAS  Google Scholar 

  33. Tabata, Y. & Lutolf, M. P. Multiscale microenvironmental perturbation of pluripotent stem cell fate and self-organization. Sci. Rep. 7, 44711 (2017).

    Article  CAS  Google Scholar 

  34. Ehrbar, M. et al. Enzymatic formation of modular cell-instructive fibrin analogs for tissue engineering. Biomaterials 28, 3856–3866 (2007).

    Article  CAS  Google Scholar 

  35. Ehrbar, M. et al. Biomolecular hydrogels formed and degraded via site-specific enzymatic reactions. Biomacromolecules 8, 3000–3007 (2007).

    Article  CAS  Google Scholar 

  36. Preibisch, S., Saalfeld, S. & Tomancak, P. Globally optimal stitching of tiled 3D microscopic image acquisitions. Bioinformatics 25, 1463–1465 (2009).

    Article  CAS  Google Scholar 

  37. Pau, G., Fuchs, F., Sklyar, O., Boutros, M. & Huber, W. EBImage—an R package for image processing with applications to cellular phenotypes. Bioinformatics 26, 979–981 (2010).

    Article  CAS  Google Scholar 

  38. Arrio-Dupont, M., Cribier, S., Foucault, G., Devaux, P. F. &. d’Albis, A. Diffusion of fluorescently labeled macromolecules in cultured muscle cells. Biophys. J. 70, 2327–2332 (1996).

    Article  CAS  Google Scholar 

  39. Brandenberg, N. & Lutolf, M. P. In situ patterning of microfluidic networks in 3D cell-laden hydrogels. Adv. Mater. 28, 7450–7456 (2016).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank A.G. Elefanty (The Royal Children Hospital) for providing the HES3 MIXL1GFP/+ hESC line and A.H. Brivanlou (The Rockefeller University) for providing the RUES2 hESC line. We thank N. Brandenberg (École Polytechnique Fédérale de Lausanne (EPFL)) for help with diffusion studies and O. Mashinchian (EPFL and Nestlé Institute of Health Sciences) for suggestions on HYS0103 hiPSC line culture. We thank L. Manfrin for helping with tools for the syringe pumps setup. We thank G. Rossi and all the members of the Laboratory of Stem Cell Bioengineering (EPFL) for helpful discussions. A.M. is supported by the EPFL Fellows program co-funded by the Marie Skłodowska-Curie and Horizon2020 (grant agreement 665667). E.R.P. was supported by a Canadian Institute of Health Research (CIHR 358808) and a SystemsX.ch Transition Postdoc Fellowship (51FSP0163584). A.R.V. and F.N. were supported by StoNets, a grant from the Swiss SystemsX.ch (https://www.systemsx.ch) initiative evaluated by the Swiss National Science Foundation. This work was funded by the EU Framework7 HEALTH research program Plurimes (http://plurimes.eu/), the European Union’s Horizon 2020 research and innovation program (INTENS 668294), the Swiss National Science Foundation (grant 310030_179447), the National Center of Competence in Research (NCCR) ‘Bio-Inspired Materials’, and the Personalized Health and Related Technologies Initiative from the ETH Board and EPFL.

Author information

Authors and Affiliations

  1. Laboratory of Stem Cell Bioengineering, Institute of Bioengineering, School of Life Sciences and School of Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Andrea Manfrin, Yoji Tabata, François R. Rivest & Matthias P. Lutolf

  2. Computational Systems Biology Lab, Institute of Bioengineering, School of Life Sciences and School of Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Eric R. Paquet, Ambroise R. Vuaridel & Felix Naef

  3. Institute of Chemical Sciences and Engineering, School of Basic Science, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Matthias P. Lutolf

Authors
  1. Andrea Manfrin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yoji Tabata
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Eric R. Paquet
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ambroise R. Vuaridel
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. François R. Rivest
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Felix Naef
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Matthias P. Lutolf
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

A.M. and M.P.L. conceived the study and designed the experiments; A.M. and Y.T. performed the experiments; Y.T. designed the original diffusion device; A.M., Y.T. and F.R.R. produced the PDMS microfluidic devices; M.P.L. and A.M. wrote the manuscript; E.R.P. performed the fluorescence-intensity-based image analysis; A.M. performed the image analysis for the percentage of marker-positive cells; A.R.V. and F.N. analyzed the mathematical model; and all authors read and approved the final manuscript.

Corresponding author

Correspondence to Matthias P. Lutolf.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information: Nina Vogt and Tal Nawy were the primary editors on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Integrated supplementary information

Supplementary Figure 1 Schemes and characterization of the microfluidic device.

(a) Detail of the two layers for the SU8 mold of the device. In the final device the white parts will be occupied by the PDMS and the colored parts will be empty. (b) Bright-field picture of the gel compartments loaded with colored ink to show how the liquid is retained by the phase-guiding features inside the compartments. (c) Schematic representation of the casting of the PEG-hydrogel (here represented in green) in the gel compartments. (d) Computational simulation of the diffusion of a reference molecule from the source side of the cell chamber. The graphs (right) is the calculated distribution at different time points of a reference molecule at the source edge of the chamber along the blue line reported in the left panel. (e) Computational simulation of the diffusion of a reference molecule from the source side of the cell chamber. The graphs (right) is the calculated distribution at different time points of a reference molecule at the sink edge of the chamber along the blue line reported in the left panel. (f) Schematic representation of the microfluidic device for alternating perfusion. By alternating perfusion through inlet A and inlet B it is possible to temporally control the composition at the source. Inlet C is perfused continuously. (g) Visualization of TexasRed-40kDa Dextran at the specified time points. The device has been perfused intermittently with “medium + TexasRed-40kDa Dextran” through inlet A (6hr), and “medium only” through inlet B (6hr). Inlet C has been perfused continuously with “medium only”. The scheme represents the period of perfusion through inlet A and inlet B. (h) Quantification of the fluorescent signal of TexasRed-40kDa Dextran within the red rectangles reported in “g” for different time-points. Repetition on eight samples showed similar results.

Supplementary Figure 2 Characterization of HES3 MIXL1GFP/+ cells exposed to uniform BMP4 concentration in the microfluidic device.

(a) Combined graph of the quantification of MIXL1, T, SOX17 and CDX2 after 48 hours of constant and uniform exposure of HES3 MIXL1GFP/+ cells to 50ng/ml BMP4 (from Fig. 1k). (b, c, d, e) Fluorescence pictures of indicated markers for HES3 MIXL1GFP/+ cells after 48hours of exposure to constant and uniform 50ng/ml BMP4 in the microfluidic device. These experiments were repeated independently two times (with eight samples per repetition) and showed similar results. (b) Red arrows indicate CDX2-positive MIXL1-negative cells located at the edges of the colony. White arrows indicate MIXL1/CDX2 double positive cells. (c) The vast majority of the SOX17-positive cells co-express CDX2. White arrows indicate CDX2-positive/SOX17-negative cells. Red arrows indicate SOX17-positive/CDX2-negative cells. (d) Red arrows indicate MIXL1/SOX17 double negative cells present in patches at the edges of the colony. White arrows indicate MIXL1/SOX17 double-positive cells. (e) White arrows indicate cells negative for MIXL1, T and SOX2 with wider internuclear distances located at the edges of the colony in patches of various sizes. (f) Scheme that approximates the distribution of markers in a colony of HES3 MIXL1GFP/+ cells after 48hours of constant and uniform exposure to 50ng/ml BMP4. (g) Computational simulation showing the local percentage of phospho-SMAD1 positive cells in a colony under a uniform and constant concentration of BMP4 at different time points. Top, distribution of exogenously provided BMP4. Bottom, local percentage of phospho-SMAD1 positive cells. Scale bar 200μm.

Supplementary Figure 3 Characterization of HES3 MIXL1GFP/+ cells exposed to a localized source of 50ng/ml BMP4.

(a) Time-points of computational simulation showing the local concentration of exogenously provided BMP4 diffusing from a 50ng/ml source located at the top of the colony. Refer to Fig. 2a for the associated simulated response of BMP signaling (local percentage of pSMAD1 in the colony). (b) Boxplots of the distribution of HES3 MIXL1GFP/+ cells positive for the reported markers along the axis of the cell chamber after 48 hours of exposure to a localized 50ng/ml BMP4 source (n=8 independent samples). (c) Combined graph of the quantification of MIXL1, T, SOX17 and CDX2 in HES3 MIXL1GFP/+ cells after 48 hours of exposure to a localized 50ng/ml BMP4 source (from Fig. 2e). In the boxplots the center line represents the median, the box limits represent the first and third quartiles, the whiskers represent the upper and lower extremes of the distribution, while white circles represent outliers (defined as a data point located more than 1.5 times outside the interquartile range above the upper quartile or below the lower quartile). Single data points are also shown in red. (d) Scheme that approximates the distribution of markers in a colony of HES3 MIXL1GFP/+ cells after 48 hours of exposure to a localized 50ng/ml source of BMP4.

Supplementary Figure 4 Characterization of H1, RUES2 and HYS0103 cells exposed to a localized source of 50ng/ml BMP4

(a) Representative fluorescence pictures for indicated markers in H1 cells after 48 hours of exposure to a localized 40ng/ml source of BMP4 in the microfluidic device. This experiment was repeated independently two times (with four samples per repetition) and showed similar results. (b) Fluorescence pictures for indicated markers in RUES2 cells after 48 hours of exposure to a localized 80ng/ml source of BMP4 in the microfluidic device. This experiment was repeated independently two times and showed similar results. (c) Mean (line) and standard error of the mean (light-colored area) of normalized fluorescence intensity for the indicated markers along the source-sink axis of multiple cell chambers of RUES2 cells after 48 hours of exposure to a localized 80ng/ml BMP4 source (n=7 independent samples). (d) Fluorescence pictures for indicated markers in HYS0103 hiPSC cells after 48 hours of exposure to a localized 20ng/ml source of BMP4 in the microfluidic device. This experiment was repeated independently two times and showed similar results. (e) Mean (line) and standard error of the mean (light-colored area) of normalized fluorescence intensity for the indicated markers along the source-sink axis of multiple cell chambers of HYS0103 hiPSC cells after 48 hours of exposure to a localized 20ng/ml BMP4 source (n=7 independent samples). Scale bar 200μm.

Supplementary Figure 5 Characterization of HES3 MIXL1GFP/+ cells exposed to a localized BMP4 source in a smaller cell chamber

(a) Design of the two layers for the SU8 mold of the device with 500μm-diameter cell chambers; detail of a single unit. In the final device the white parts will be occupied by the PDMS and the colored parts will be empty. (b) Computational simulation of the diffusion of a reference molecule from the source side of the 500μm-diameter cell chamber after 48 hours of perfusion. (c) Calculated distribution of the reference molecule along the red line reported in Supplementary Fig. 5b at the indicated time points. (d) Fluorescence pictures for indicated markers in HES3 MIXL1GFP/+ cells after 48 hours of exposure to a localized 40ng/ml source of BMP4 in the 500μm-diameter chambers microfluidic device. This experiment was repeated independently two times and showed similar results. (e) Mean (line) and standard error of the mean (light-colored area) of normalized fluorescence intensity for the indicated markers along the source-sink axis of multiple cell chambers of HES3 MIXL1GFP/+ cells after 48 hours of exposure to a localized 40ng/ml BMP4 source in 500μm-diameter chambers (n=8 independent samples).

Supplementary Figure 6 Characterization of HES3 MIXL1GFP/+ cells exposed to a localized source of 250ng/ml BMP4.

(a) Boxplots of the distribution of HES3 MIXL1GFP/+ cells positive for the reported markers along the axis of the cell chamber after 48 hours of exposure to a localized 250ng/ml BMP4 source (n=8 independent samples). In the boxplots the center line represents the median, the box limits represent the first and third quartiles, the whiskers represent the upper and lower extremes of the distribution, while white circles represent outliers (defined as a data point located more than 1.5 times outside the interquartile range above the upper quartile or below the lower quartile). Single data points are also shown in red. (b) Orthogonal projection of DAPI signal for HES3 MIXL1GFP/+ cells at the source side after 48 hours of exposure to a localized 250ng/ml BMP4 source. This experiment was repeated three times and showed similar results.

Supplementary Figure 7 Effect of cell density on the patterning of hESC induced by a localized BMP4 source.

(a) Computational simulation showing the local percentage of phospho-SMAD1 positive cells in a colony with an initially high cell density exposed to a localized BMP4 source of 50ng/ml. (b) Representative pictures (DAPI) of HES3 MIXL1GFP/+ cell suspensions at different concentrations 30 hours after the loading in the cell chambers. (c) Boxplots of the measured cell density for the different cell suspension concentrations (n=8 independent samples per condition). For simplicity the conditions are named “Low”, “Intermediate” and “High” density. ANOVA and subsequent multiple two-tailed t-test Benjamini-Hochberg corrected were performed. (d) Boxplots of the distribution of HES3 MIXL1GFP/+ cells positive for the reported markers along the axis of the cell chamber after 48 hours of exposure to a localized 50ng/ml BMP4 source starting with high cell density (n=8 independent samples). (e) Boxplots of the distribution of HES3 MIXL1GFP/+ cells positive for the reported markers along the axis of the chamber after 48 hours of exposure to a localized 250ng/ml BMP4 source starting with high cell density (n=6 independent samples). For all the boxplots the center line represents the median, the box limits represent the first and third quartiles, the whiskers represent the upper and lower extremes of the distribution, while white circles represent outliers. Single data points are also shown in red. (f) Time points from a computational simulation showing the local percentage of phospho-SMAD1 positive cells in a colony with an initially high cell density exposed to a localized BMP4 source of 250ng/ml. (g) Representative fluorescence pictures for indicated markers in HES3 MIXL1GFP/+ cells exposed 48 hours to a localized 50ng/ml source of BMP4 in the microfluidic device starting with low cell density. This experiment was repeated two times on a total of 8 samples and showed similar results. Scale bar 200μm.

Supplementary Figure 8 Effect of counteracting BMP4 and NOGGIN sources on the patterning of HES3 MIXL1GFP/+ cells.

(a) Boxplots of the distribution of HES3 MIXL1GFP/+ cells positive for the reported markers along the axis of the cell chamber after 48 hours of exposure to counteracting sources of 50ng/ml BMP4 and 200ng/ml NOGGIN (n=8 independent samples). In the boxplots the center line represents the median, the box limits represent the first and third quartiles, the whiskers represent the upper and lower extremes of the distribution, while white circles represent outliers (defined as a data point located more than 1.5 times outside the interquartile range above the upper quartile or below the lower quartile). Single data points are also shown in red. (b) Combined graph of the quantification of MIXL1, T, SOX17 and CDX2 for of HES3 MIXL1GFP/+ cells after 48 hours of exposure to counteracting sources of 50ng/ml BMP4 and 200ng/ml NOGGIN (from Fig. 6d). (c) Scheme that approximates the distribution of markers in a colony of HES3 MIXL1GFP/+ cells after 48 hours of exposure to counteracting sources of 50ng/ml BMP4 and 200ng/ml NOGGIN.

.

Supplementary Figure 9 Effect of counteracting BMP4 and NOGGIN sources on the patterning of H1, RUES2 and HYS0103 cells.

(a) Representative fluorescence pictures for indicated markers in H1 cells after 48 hours of exposure to counteracting sources of 40ng/ml BMP4 and 200ng/ml NOGGIN in the microfluidic device. This experiment was repeated independently two times (with four samples per repetition) and showed similar results. (b) Fluorescence pictures for indicated markers in RUES2 cells after 48 hours of exposure to counteracting sources of 80ng/ml BMP4 and 200ng/ml NOGGIN in the microfluidic device. This experiment was repeated independently two times and showed similar results. (c) Mean (line) and standard error of the mean (light-colored area) of normalized fluorescence intensity for the indicated markers along the source-sink axis of multiple cell chambers of RUES2 cells after 48 hours of exposure to counteracting sources of 80ng/ml BMP4 and 200ng/ml NOGGIN (n=7 independent samples). (d) Fluorescence pictures for indicated markers in HYS0103 hiPSC cells after 48 hours of exposure to counteracting sources of 20ng/ml BMP4 and 200ng/ml NOGGIN in the microfluidic device. This experiment was repeated independently two times and showed similar results. (e) Mean (line) and standard error of the mean (light-colored area) of normalized fluorescence intensity for the indicated markers along the source-sink axis of multiple cell chambers of HYS0103 hiPSC cells after 48 hours of exposure to counteracting sources of 20ng/ml BMP4 and 200ng/ml NOGGIN (n=6 independent samples). Scale bar 200μm.

Supplementary Figure 10 Effect of counteracting BMP4 and NOGGIN sources on the patterning of HES3 MIXL1GFP/+ cells in smaller chamber.

(a) Fluorescence pictures for indicated markers in HES3 MIXL1GFP/+ cells after 48 hours of exposure to counteracting sources of 40ng/ml BMP4 and 200ng/ml NOGGIN in the 500μm-diameter chambers microfluidic device. This experiment was repeated independently two times on a total of 8 samples and showed similar results. (b) Mean (line) and standard error of the mean (light-colored area) of normalized fluorescence intensity for the indicated markers along the source-sink axis of multiple cell chambers of HES3 MIXL1GFP/+ cells after 48 hours of exposure counteracting sources of 40ng/ml BMP4 and 200ng/ml NOGGIN in 500μm-diameter chambers (n=8 independent samples).

Supplementary information

Supplementary Information

Supplementary Figures 1–10

Reporting Summary

Supplementary Video 1

Dynamics of MIXL1 pattern formation upon 10 ng/ml BMP4 localizedsource (3–48 h). Time-lapse of HES3 MIXL1GFP/+ from 3 h until 48 h of exposure to localized BMP4 with a source concentration of 10 ng/ml. The source is at the top. BF on the left and GFP (MIXL1) is on the right. Pictures were acquired every hour. This experiment was performed on four samples that showed similar results.

Supplementary Video 2

Dynamics of MIXL1 pattern formation upon 10 ng/ml BMP4 localized source (24–65 h). Time-lapse of HES3 MIXL1GFP/+ from 24 h until 65 h of exposure tolocalized BMP4 with a source concentration of 10 ng/ml. The source is at the top. BF on the left and GFP (MIXL1) is on the right. Pictures were acquiredevery hour. This experiment was performed on four samples that showed similar results.

Supplementary Video 3

Supplementary Video 3 Dynamics of MIXL1 pattern formation upon 50 ng/ml BMP4 localized source (3–48 h). Time-lapse of HES3 MIXL1GFP/+ from 3 h until 48 h of exposure tolocalized BMP4 with a source concentration of 50 ng/ml. The source is at the top. BF on the left and GFP (MIXL1) is on the right. Pictures were acquired every hour. This experiment was performed on four samples that showed similar results.

Supplementary Video 4

Dynamics of MIXL1 pattern formation upon 50 ng/ml BMP4 localized source (24–65 h). Time-lapse of HES3 MIXL1GFP/+ from 24 h until 65 h of exposure to localized BMP4 with a source concentration of 50 ng/ml. The source is at the top. BF on the left and GFP (MIXL1) is on the right. Pictures were acquired every hour. This experiment was performed on four samples that showed similar results.

Supplementary Video 5

Dynamics of MIXL1 pattern formation upon 250 ng/ml BMP4 localized source (3–48 h). Time-lapse of HES3 MIXL1GFP/+ from 3 h until 48 h of exposure to localized BMP4 with a source concentration of 250 ng/ml. The source is at the top. BF on the left and GFP (MIXL1) is on the right. Pictures were acquired every hour. This experiment was performed on four samples that showed similar results.

Supplementary Video 6

Dynamics of MIXL1 pattern formation upon 250 ng/ml BMP4 localized source (24–65 h). Time-lapse of HES3 MIXL1GFP/+ from 24 h until 65 h of exposure to localized BMP4 with a source concentration of 250 ng/ml. The source is at the top. BF on the left and GFP (MIXL1) is on the right. Pictures were acquired every hour. This experiment was performed on four samples. A certain variability in the behavior of the four samples was observed: two of them showed MIXL1 expression extending at the center of the colony (as the one shown in this video), while the center of the colony was preserved from MIXL1 expression in the other two samples.

Supplementary Data

Layout of the design of the microfluidic devices used in this study for the production of the photolithography masks (.cif file format). The masks can be used to fabricate the two-layer SU8 mold for the production of the PDMS device.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Manfrin, A., Tabata, Y., Paquet, E.R. et al. Engineered signaling centers for the spatially controlled patterning of human pluripotent stem cells. Nat Methods 16, 640–648 (2019). https://doi.org/10.1038/s41592-019-0455-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41592-019-0455-2

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing