Targeting the cytoskeleton to direct pancreatic differentiation of human pluripotent stem cells

Last updated: 03-11-2020

Read original article here

Targeting the cytoskeleton to direct pancreatic differentiation of human pluripotent stem cells

Targeting the cytoskeleton to direct pancreatic differentiation of human pluripotent stem cells
Pluripotent stem cells
Abstract
Generation of pancreatic β cells from human pluripotent stem cells (hPSCs) holds promise as a cell replacement therapy for diabetes. In this study, we establish a link between the state of the actin cytoskeleton and the expression of pancreatic transcription factors that drive pancreatic lineage specification. Bulk and single-cell RNA sequencing demonstrated that different degrees of actin polymerization biased cells toward various endodermal lineages and that conditions favoring a polymerized cytoskeleton strongly inhibited neurogenin 3-induced endocrine differentiation. Using latrunculin A to depolymerize the cytoskeleton during endocrine induction, we developed a two-dimensional differentiation protocol for generating human pluripotent stem-cell-derived β (SC-β) cells with improved in vitro and in vivo function. SC-β cells differentiated from four hPSC lines exhibited first- and second-phase dynamic glucose-stimulated insulin secretion. Transplantation of islet-sized aggregates of these cells rapidly reversed severe preexisting diabetes in mice at a rate close to that of human islets and maintained normoglycemia for at least 9 months.
Get full journal access for 1 year
$250.00
All prices are NET prices.
VAT will be added later in the checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
from$8.99
All prices are NET prices.
Additional access options:
Fig. 1: The state of the cytoskeleton controls expression of the transcription factors NEUROG3 and NKX6-1 in pancreatic progenitors.
Fig. 2: Single-cell RNA sequencing demonstrates that cytoskeletal state directs pancreatic progenitor fate.
Fig. 3: Latrunculin A treatment during stage 5 increases the efficiency of SC-β cell specification for plated pancreatic progenitors.
Fig. 4: SC-β cells differentiated with the new planar protocol express β cell markers and function in vitro.
Fig. 5: SC-β cells generated with the new planar protocol can rapidly cure preexisting diabetes in mice.
Fig. 6: The state of the cytoskeleton influences endodermal cell fate.
Data availability
All single-cell and bulk RNA sequencing data have been deposited in the Gene Expression Omnibus under accession number GSE137659 . Any other data and protocol information used in the manuscript are available from the corresponding author upon reasonable request.
References
1.
Millman, J. R. & Pagliuca, F. W. Autologous pluripotent stem cell-derived β-like cells for diabetes cellular therapy. Diabetes 66, 1111–1120 (2017).
Google Scholar
2.
Tomei, A. A., Villa, C. & Ricordi, C. Development of an encapsulated stem cell-based therapy for diabetes. Expert Opin. Biol. Ther. 15, 1321–1336 (2015).
Google Scholar
3.
Jennings, R. E., Berry, A. A., Strutt, J. P., Gerrard, D. T. & Hanley, N. A. Human pancreas development. Development 142, 3126–3137 (2015).
Google Scholar
4.
Pagliuca, F. W. et al. Generation of functional human pancreatic β cells in vitro. Cell 159, 428–439 (2014).
Google Scholar
5.
Velazco-Cruz, L. et al. Acquisition of dynamic function in human stem cell-derived β cells. Stem Cell Reports 12, 351–365 (2019).
Google Scholar
6.
Rezania, A. et al. Reversal of diabetes with insulin-producing cells derived in vitro from human pluripotent stem cells. Nat. Biotechnol. 32, 1121–1133 (2014).
Google Scholar
7.
Russ, H. A. et al. Controlled induction of human pancreatic progenitors produces functional β-like cells in vitro. EMBO J. 34, 1759–1772 (2015).
Google Scholar
8.
Nair, G. G. et al. Recapitulating endocrine cell clustering in culture promotes maturation of human stem-cell-derived β cells. Nat. Cell Biol. 21, 263–274 (2019).
Google Scholar
9.
Sui, L. et al. β-cell replacement in mice using human type 1 diabetes nuclear transfer embryonic stem cells. Diabetes 67, 26–35 (2018).
Google Scholar
10.
Ghazizadeh, Z. et al. ROCKII inhibition promotes the maturation of human pancreatic β-like cells. Nat. Commun. 8, 298 (2017).
Google Scholar
11.
Nostro, M. C. et al. Efficient generation of NKX6-1+ pancreatic progenitors from multiple human pluripotent stem cell lines. Stem Cell Reports 4, 591–604 (2015).
Google Scholar
12.
Rezania, A. et al. Maturation of human embryonic stem cell-derived pancreatic progenitors into functional islets capable of treating pre-existing diabetes in mice. Diabetes 61, 2016–2029 (2012).
Google Scholar
13.
D’Amour, K. A. et al. Efficient differentiation of human embryonic stem cells to definitive endoderm. Nat. Biotechnol. 23, 1534–1541 (2005).
Google Scholar
14.
Amour, K. A. D. et al. Production of pancreatic hormone-expressing endocrine cells from human embryonic stem cells. Nat. Biotechnol. 24, 1392–1401 (2006).
Google Scholar
15.
Kroon, E. et al. Pancreatic endoderm derived from human embryonic stem cells generates glucose-responsive insulin-secreting cells in vivo. Nat. Biotechnol. 26, 443–452 (2008).
Google Scholar
16.
Spence, J. R. et al. Directed differentiation of human pluripotent stem cells into intestinal tissue in vitro. Nature 470, 105–110 (2011).
Google Scholar
17.
Cheng, X. et al. Self-renewing endodermal progenitor lines generated from human pluripotent stem cells. Cell Stem Cell 10, 371–384 (2012).
Google Scholar
18.
Gu, G., Dubauskaite, J. & Melton, D. A. Direct evidence for the pancreatic lineage: NGN3+ cells are islet progenitors and are distinct from duct progenitors. Development 129, 2447–2457 (2002).
Google Scholar
19.
Johansson, K. A. et al. Temporal control of Neurogenin3 activity in pancreas progenitors reveals competence windows for the generation of different endocrine cell types. Dev. Cell 12, 457–465 (2007).
Google Scholar
20.
Nelson, S. B., Schaffer, A. E. & Sander, M. The transcription factors Nkx6.1 and Nkx6.2 possess equivalent activities in promoting β-cell fate specification in Pdx1+ pancreatic progenitor cells. Development 134, 2491–2500 (2007).
Google Scholar
21.
Schulz, T. C. et al. A scalable system for production of functional pancreatic progenitors from human embryonic stem cells. PLoS One 7, e37004 (2012).
Google Scholar
22.
Engler, A. J., Sen, S., Sweeney, H. L. & Discher, D. E. Matrix elasticity directs stem cell lineage specification. Cell 126, 677–689 (2006).
Google Scholar
23.
Hogrebe, N. J. & Gooch, K. J. Direct influence of culture dimensionality on hMSC differentiation at various matrix stiffnesses using a fibrous self-assembling peptide hydrogel. J. Biomed. Mater. Res. Part A 104, 2356–2368 (2016).
Google Scholar
24.
Kilian, K. A., Bugarija, B., Lahn, B. T. & Mrksich, M. Geometric cues for directing the differentiation of mesenchymal stem cells. Proc. Natl Acad. Sci. USA 107, 4872–4877 (2010).
Google Scholar
25.
McBeath, R., Pirone, D. M., Nelson, C. M., Bhadriraju, K. & Chen, C. S. Cell shape, cytoskeletal tension, and RhoA regulate stem cell lineage commitment. Dev. Cell 6, 483–495 (2004).
Google Scholar
26.
Ahn, E. H. et al. Spatial control of adult stem cell fate using nanotopographic cues. Biomaterials 35, 2401–2410 (2014).
Google Scholar
27.
Frith, J. E., Mills, R. J. & Cooper-White, J. J. Lateral spacing of adhesion peptides influences human mesenchymal stem cell behaviour. J. Cell Sci. 125, 317–327 (2012).
Google Scholar
28.
Hogrebe, N. J. et al. Independent control of matrix adhesiveness and stiffness within a 3D self-assembling peptide hydrogel. Acta Biomater. 70, 110–119 (2018).
Google Scholar
29.
Janmey, P. A. & Miller, R. T. Mechanisms of mechanical signaling in development and disease. J. Cell Sci. 124, 9–18 (2011).
Google Scholar
30.
Swift, J. et al. Nuclear lamin-A scales with tissue stiffness and enhances matrix-directed differentiation. Science 341, 1240104 (2013).
Google Scholar
32.
Olson, E. N. & Nordheim, A. Linking actin dynamics and gene transcription to drive cellular motile functions. Nat. Rev. Mol. Cell Biol. 11, 353–365 (2010).
Google Scholar
33.
Sharon, N. et al. Wnt signaling separates the progenitor and endocrine compartments during pancreas development. Cell Rep. 27, 2281–2291 (2019).
Google Scholar
34.
Veres, A. et al. Charting cellular identity during human in vitro β-cell differentiation. Nature 569, 368–373 (2019).
Google Scholar
35.
Leong, W. S. et al. Thickness sensing of hMSCs on collagen gel directs stem cell fate. Biochem. Biophys. Res. Commun. 401, 287–292 (2010).
Google Scholar
36.
Peng, G. E., Wilson, S. R. & Weiner, O. D. A pharmacological cocktail for arresting actin dynamics in living cells. Mol. Biol. Cell 22, 3986–3994 (2011).
Google Scholar
37.
Brenner, S. L. & Korn, D. Inhibition of actin polymerization by latrunculin A. FEBS Lett. 2, 316–318 (1987).
Google Scholar
38.
Chang, Y. C. et al. GEF-H1 couples nocodazole-induced microtubule disassembly to cell contractility via RhoA. Mol. Biol. Cell 19, 2147–2153 (2008).
Google Scholar
39.
Adkar, S. S. et al. Step-wise chondrogenesis of human induced pluripotent stem cells and purification via a reporter allele generated by CRISPR–Cas9 genome editing. Stem Cells 37, 65–76 (2018).
Google Scholar
40.
Hohwieler, M. et al. Human pluripotent stem cell-derived acinar/ductal organoids generate human pancreas upon orthotopic transplantation and allow disease modelling. Gut 66, 473–486 (2017).
Google Scholar
41.
McCracken, K. W., Howell, J. C., Wells, J. M. & Spence, J. R. Generating human intestinal tissue from pluripotent stem cells in vitro. Nat. Protoc. 6, 1920–1928 (2011).
Google Scholar
42.
Ang, L. T. et al. A roadmap for human liver differentiation from pluripotent stem cells. Cell Rep. 22, 2190–2205 (2018).
Google Scholar
43.
Yin, X. et al. Niche-independent high-purity cultures of Lgr5+ intestinal stem cells and their progeny. Nat. Methods 11, 106–112 (2014).
Google Scholar
44.
Wang, X. et al. Point mutations in the PDX1 transactivation domain impair human β-cell development and function. Mol. Metab. 24, 80–97 (2019).
Google Scholar
45.
Balboa, D. et al. Insulin mutations impair β-cell development in a patient-derived iPSC model of neonatal diabetes. eLife 7, 1–35 (2018).
Google Scholar
46.
Ma, S. et al. β cell replacement after gene editing of a neonatal diabetes-causing mutation at the insulin locus. Stem Cell Reports 11, 1407–1415 (2018).
Google Scholar
47.
Chen, K. G., Mallon, B. S., McKay, R. D. G. & Robey, P. G. Human pluripotent stem cell culture: considerations for maintenance, expansion, and therapeutics. Cell Stem Cell 14, 13–26 (2014).
Google Scholar
48.
Kesavan, G. et al. Cdc42/N-WASP signaling links actin dynamics to pancreatic cell delamination and differentiation. J. Cell Sci. 127, 685–694 (2014).
Google Scholar
49.
Seymour, P. A. Sox9: a master regulator of the pancreatic program. Rev. Diabet. Stud. 11, 51–83 (2014).
Google Scholar
50.
Mamidi, A. et al. Mechanosignalling via integrins directs fate decisions of pancreatic progenitors. Nature 564, 114–118 (2018).
Google Scholar
51.
Butler, A., Hoffman, P., Smibert, P., Papalexi, E. & Satija, R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat. Biotechnol. 36, 411–420 (2018).
Google Scholar
52.
McCarthy, D. J., Chen, Y. & Smyth, G. K. Differential expression analysis of multifactor RNA-seq experiments with respect to biological variation. Nucleic Acids Res. 40, 4288–4297 (2012).
Google Scholar
53.
Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2009).
Google Scholar
54.
Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005).
Google Scholar
55.
Mootha, V. K. et al. PGC-1α-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat. Genet. 34, 267–273 (2003).
Google Scholar
57.
Liberzon, A. et al. The Molecular Signatures Database (MSigDB) hallmark gene set collection. Cell Syst. 1, 417–425 (2015).
Google Scholar
59.
Takebe, T. et al. Vascularized and functional human liver from an iPSC-derived organ bud transplant. Nature 499, 481–484 (2013).
Google Scholar
60.
Finkbeiner, S. R. et al. Transcriptome-wide analysis reveals hallmarks of human intestine development and maturation in vitro and in vivo. Stem Cell Reports 4, 1140–1155 (2015).
Google Scholar
61.
McCracken, K. W. et al. Modelling human development and disease in pluripotent stem-cell-derived gastric organoids. Nature 516, 400–404 (2014).
Google Scholar
62.
Rosekrans, S. L., Baan, B., Muncan, V. & van den Brink, G. R. Esophageal development and epithelial homeostasis. Am. J. Physiol. Liver Physiol. 309, G216–G228 (2015).
Google Scholar
63.
Trisno, S. L. et al. Esophageal organoids from human pluripotent stem cells delineate Sox2 functions during esophageal specification. Cell Stem Cell 23, 501–515 (2018).
Google Scholar
64.
Willet, S. G. & Mills, J. C. Stomach organ and cell lineage differentiation: from embryogenesis to adult homeostasis. Cell Mol. Gastroenterol. Hepatol. 2, 546–559 (2016).
Download references
Acknowledgements
This work was supported by the JDRF Career Development Award (5-CDA-2017-391-A-N), the National Institutes of Health (NIH) (5R01DK114233) and startup funds from the Washington University School of Medicine Department of Medicine. N.J.H. was supported by the NIH (T32DK007120). K.G.M. was supported by the NIH (T32DK108742). L.V.C. was supported by the NIH (R25GM103757). Microscopy was performed through the Washington University Center for Cellular Imaging, which is supported by the Washington University School of Medicine, the Childrenʼs Discovery Institute (CDI-CORE-2015-505) and the Foundation for Barnes-Jewish Hospital (3770). Microscopy was supported by the Washington University Diabetes Research Center (P30DK020579). Sequencing work was performed by the Washington University Genome Technology Access Center in the Department of Genetics (NIH P30CA91842 and UL1TR000448) and supported by the Washington University Institute of Clinical and Translational Sciences (NIH UL1TR002345). We thank M. Kim for technical assistance.
Author information
Affiliations
Division of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine, St. Louis, MO, USA
Nathaniel J. Hogrebe
Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA
Punn Augsornworawat
Google Scholar
Contributions
N.J.H. and J.R.M. conceived of the experimental design. N.J.H., P.A., K.G.M., L.V.C. and J.R.M. contributed to in vitro experiments. P.A., K.G.M. and J.R.M. performed all in vivo experiments. N.J.H. and J.R.M. wrote the manuscript. All authors edited and reviewed the manuscript.
Corresponding author
Ethics declarations
Competing interests
N.J.H., L.V.C. and J.R.M. are inventors on patents and patent applications related to SC-β cell differentiation approaches described in this manuscript.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Integrated supplementary information
Supplementary Figure 1 Plating pancreatic progenitors on ECM-coated tissue culture polystyrene prevents NEUROG3 expression.
(a) Images of pancreatic progenitors plated at the beginning of stage 4 onto ECM-coated tissue culture polystyrene as per Fig. 1a. Scale bar = 200 µm. (b) A colorimetric antibody-based integrin adhesion assay at the beginning and end of stage 4 confirmed high expression of integrin subunits that bind to collagens I and IV (α1, α2, β1), fibronectin (αV, β1, α5β1), vitronectin (αV, β1, αVβ5) and some but not all laminin isoforms (α3, β1) (n = 3). Data is normalized to an isotype control. (c) Immunostaining confirmed that cells at the beginning of stage 4 lack expression of both NKX6-1 and NEUROG3. Scale bar = 25 µm. (d) qRT-PCR of plated cells at the end of stage 4 (n = 4). All data was generated with HUES8. All data is represented as the mean, and all error bars represent SEM. Individual data points are shown for all bar graphs.
Supplementary Figure 2 Latrunculin treatment induces NEUROG3 expression in plated pancreatic progenitors.
(a) qRT-PCR of pancreatic gene expression at the end of stage 4 in response to different concentrations of latrunculin A added during stage 4 to plated pancreatic progenitors from the 1013-4FA and 1016SeVA iPSC lines (n = 4). (b) qRT-PCR of pancreatic gene expression at the end of stage 4 in response to latrunculin B dosing during stage 4 on plated HUES8 (ANOVA, n = 4). (c) qRT-PCR at the end of stage 4 of untreated HUES8 plated cells, untreated reaggregated clusters, and reaggregated clusters treated with the actin polymerizer jasplakinolide (unpaired two-sided t-tests, n = 4). (d) Western blots of the G/F actin ratio within cells under different culture formats and treated with latrunculin A are shown with the corresponding protein ladder (n = 3). All data was generated by plating down suspension clusters at the beginning of stage 4 and culturing the cells on collagen 1 coated plates throughout stage 4. All data is represented as the mean, and all error bars represent SEM. Individual data points are shown for all bar graphs. ns = not significant, * = p < 0.05, ** = p < 0.01, *** = p < 0.001.
Supplementary Figure 3 Single-cell RNA sequencing demonstrates that the state of the cytoskeleton influences gene expression in pancreatic progenitors.
(a) Immunostaining of F-actin in plated stage 4 PDX1-expressing pancreatic progenitors with and without a 5 µM nocodazole treatment for 24 hours. (b) tSNE plots generated from single-cell RNA sequencing data of plated HUES8 pancreatic progenitors showing expression of pancreatic and off-target genes. Red indicates increased gene expression levels (n = 1,062 total cells). All data was generated by plating down HUES8 suspension clusters at the beginning of stage 4 and culturing the cells on collagen 1 coated plates throughout stage 4.
Supplementary Figure 4 Latrunculin A treatment enables a planar protocol for making SC-β cells.
(a)qRT-PCR of HUES8 cells differentiated with the new planar protocol to the end of stage 4, untreated or treated throughout stage 4 with 0.5 µM latrunculin A (unpaired two-sided t-tests, n = 4). (b-d) qRT-PCR of HUES8 cells differentiated with the planar protocol to stage 6 with or without a 24 hour 1 µM latrunculin A treatment at the beginning of stage 5, (b, c) showing expression of islet and β cell genes and (d) non-endocrine genes (unpaired two-sided t-tests, n = 4). (e, f) Immunostaining of aggregates generated from the planar protocol with (e) 1013-4FA and (f) 1016SeVA iPSC lines. (g) MAFB immunostaining of stage 6 cells generated with the planar protocol from HUES8. MAFB is shown in both planar cells and in histological sections of clusters aggregated from planar cells. All data is represented as the mean, and all error bars represent SEM. Individual data points are shown for all bar graphs. Scale bars = 50 µm.
Supplementary Figure 5 SC-β cells generated with the planar protocol demonstrate high levels of functionality.
(a, b) Static GSIS of SC-β cells generated with the planar protocol from HUES8 in response to (a) sequential glucose challenges (paired two-sided t-test, n = 4) and (b) various secretagogues (paired two-sided t-test, n = 4). (c) Electron microscopy image of SC-β cells generated with the planar protocol from HUES8 demonstrating the presence of insulin granules. (d) Calcium flux of SC-β cells generated with the planar protocol from HUES8 and human islets in response to high glucose and KCL (n = 10 clusters). (e) Quantified cumulative population doublings of stem cells cultured in suspension bioreactors comparing the BJFF.6 iPSC line with HUES8. (f) Stage 6 clusters generated from the BJFF.6 iPSC line with the planar differentiation methodology. Scale bar = 250 µm. (g) Dynamic GSIS of stage 6 clusters generated from the BJFF.6 iPSC line with the planar differentiation methodology. (h) Dynamic (n = 2) and (i) static (paired two-sided t-test, n = 6) GSIS of SC-β cells generated from HUES8 with the planar protocol in a T-75 flask. (j) Quantification of mouse c-peptide with ELISA of serum from mice (untreated control, n = 5; STZ no transplant, n = 3; STZ planar transplant, n = 12). (k) Quantification of human insulin in the serum of mice without a transplant (untreated control, n = 5; STZ no transplant, n = 3) (l) A heatmap of genes associated with insulin processing and secretion was generated from the bulk RNA sequencing data in Figures 6a-d, comparing stage 6 cells produced with the suspension protocol to those of plated cells receiving the optimal stage 5 latrunculin A treatment. All data is represented as the mean, and all error bars represent SEM. Individual data points are shown for all bar graphs. ns = not significant, * = p < 0.05, ** = p < 0.01, *** = p < 0.001.
Supplementary Figure 6 SC-β cells generated from the planar and suspension protocols with the HUES8 line have similar gene expression and functionality.
(a) qRT-PCR of islet and disallowed (LDHA, SLC16A1) genes for stage 6 cells generated with the planar protocol compared to those generated with the suspension protocol and to human islets (Dunnett’s multiple comparisons test; planar, n = 4; suspension, n = 6; human islets, n = 3). (b) Insulin content of planar stage 6 cells compared to those generated with the suspension protocol (planar, n = 5; suspension, n = 4). (c) Proinsulin/insulin content ratio for planar stage 6 cells compared to those generated with the suspension protocol (planar, n = 5; suspension, n = 4). (d) Static GSIS for planar stage 6 cells compared to those generated with the suspension protocol (paired two-sided t-tests; planar, n = 11; suspension, n = 8). All data was generated with HUES8. All data is represented as the mean, and all error bars represent SEM. Individual data points are shown for all bar graphs. ns = not significant, * = p < 0.05, ** = p < 0.01, *** = p < 0.001.


Read the rest of this article here