1 Identification of CD177/NB1+ specified anterior definitive endoderm improves human

2 pancreatic and β-like cell differentiation in vitro

3

4 Pallavi U. Mahaddalkar1,2#, Katharina Scheibner1#, Sandra Pfluger1§, Ansarullah1§,

5 Michael Sterr1,2, Julia Beckenbauer1, Martin Irmler4, Johannes Beckers4,5,7, Sebastian

6 Knöbel3 & Heiko Lickert1,2,6,7*

7 1. Institute of Diabetes and Regeneration Research, Helmholtz Diabetes Center,

8 Helmholtz Zentrum München, 85764 Neuherberg, Germany

9 2. Institute of Stem Cell Research, Helmholtz Zentrum München, 85764 Neuherberg,

10 Germany

11 3. Miltenyi Biotec, 51429 Bergisch Gladbach, Germany

12 4. Institute of Experimental Genetics, Helmholtz Zentrum München, 85764

13 Neuherberg, Germany

14 5. Chair of Experimental Genetics, School of Life Sciences Weihenstephan,

15 Technische Universität München, 85354 Freising, Germany

16 6. Chair of -Cell Biology, Technical University of Munich, School of Medicine,

17 Klinikum Rechts der Isar, Ismaningerstraße 22, 81675 München, Germany

18 7. German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany

19 # contribute equally to this work

20 § contribute equally to this work

21 *Corresponding author: Tel. no.: +49 89 3187 3760

22 E-mail: [email protected]

23 1

24 Abstract

25 Morphogen gradients pattern the endoderm and specify liver and pancreatic progenitors in vivo.

26 However, if specified organ progenitors can be identified and isolated during human pluripotent

27 stem cell (hPSC) differentiation is unknown. Here, we report the identification of two novel

28 surface markers, CD177/NB1 glycoprotein and inducible T cell co-stimulatory ligand

29 CD275/ICOSL, that isolate specified organ progenitors from seemingly homogenous endoderm

30 differentiations in vitro. These markers allow assessing anterior definitive endoderm (ADE)

31 patterning and specification in human revealing different morphogen requirements and

32 induction efficiencies for the generation of specified pancreatic and liver progenitors using

33 known and novel differentiation paradigms. Furthermore, molecular profiling and

34 characterisation of CD177+ and CD275+ ADE subpopulations identified differential expression

35 of signalling components and inverse activation of canonical and non-canonical WNT

36 signalling. This signalling milieu specifies CD275+ ADE progenitors towards the liver fate. In

37 contrast, CD177+ ADE progenitors express and synthesize the secreted WNT, NODAL and

38 BMP antagonist CERBERUS1 and are specified towards the pancreatic fate. Strikingly,

39 isolated CD177+ ADE progenitors differentiate more homogenously into pancreatic progenitors

40 as well as into functionally, more mature and glucose-responsive β-like cells in vitro, when

41 compared to bulk endoderm differentiations. Overall, the identification of novel surface

42 markers allowed us to isolate, monitor and understand human organ progenitor formation for

43 the improved differentiation of β-like cells from hPSC.

44

45 Keywords: endoderm patterning, progenitors, pancreas differentiation, stem cell-

46 derived β-like cell differentiation, Wnt signalling, surface marker, CD177, CD275 and

47 CXCR4

2

48 Introduction

49 Endoderm patterning in the mouse embryo directly translates into formation of endoderm-

50 derived organs along the anterior-posterior (A-P) axis, including the thymus, thyroid, lungs,

51 liver, pancreas and gastro-intestinal tract1-3. High Nodal and Wnt signalling during embryonic

52 patterning and germ layer formation activates the endoderm transcription factors FoxA2,

53 Sox17, Eomes and Gata4/6 which leads to the execution of an endoderm program4. A series of

54 morphogenetic events promotes the transformation of naïve endoderm into the primitive gut

55 tube. During this period, the primitive gut tube is patterned along the A-P and dorso-ventral (D-

56 V) axis and is divided into fore-, mid- and hindgut domains1. Fate mapping studies have

57 revealed the fate of endoderm-derived organs is specified already shortly after gastrulation5,6.

58 It is thought that liver and pancreas progenitors are specified and originate from a multipotent

59 population of anterior definitive endoderm (ADE) depending on the inductive cues of Fgf, Bmp

60 and Wnt received from neighbouring tissues7. Moderate doses of Fgf signalling induces

61 albumin (Alb) expression and liver bud formation, whereas low levels of Fgf promotes Pdx1

62 expression and the formation of the ventral pancreatic bud8. Similarly, a gradient of Bmp and

63 retinoic acid (RA) signalling further specifies liver versus pancreatic fate. High Bmp signalling

64 promotes hepatic differentiation and represses pancreatic fate, while lack of RA fails to induce

65 the dorsal pancreatic bud and generates impaired liver growth7,9. Likewise, the presence of non-

66 canonical Wnt signalling in the foregut endoderm and pancreatic progenitors but not in liver

67 progenitors suggested cell type-specific activation of the non-canonical Wnt signalling for

68 progenitor specification and determination10. However, if human endoderm derived organ

69 progenitors can be identified in culture is not known. Furthermore, the upstream signals that

70 direct these progenitors into the PDX1+ pancreatic lineage remain elusive, especially in human

71 development which is not accessible at this stage11.

3

72 Translation of knowledge gained from in vivo studies of endoderm and pancreas development

73 have guided the in vitro differentiation of hPSCs towards glucose-responsive and insulin-

74 secreting β-like cells12,13. Over the years, the differentiation protocols were steadily improved

75 and recently up to 50% of insulin-producing β-like cells can be generated routinely14-16.

76 However, many β-like cells still remain immature and their response to static glucose-

77 stimulated insulin secretion (GSIS) is not comparable to β cells in human islets14. One common

78 problem of bulk stem cell differentiation is the remarkable heterogeneity of both

79 undifferentiated and differentiated hPSCs17,18. Enrichment of correct populations can enhance

80 the differentiation towards a desired lineage and reduce unwanted differentiation towards other

81 lineages19,20. Previous surface marker screens at pancreatic endoderm stage showed that

82 enrichment of pancreatic endoderm and endocrine cells can enhance pancreatic progenitor

83 differentiation towards hormone-positive and glucose-responsive cells21-23. Thus, we

84 hypothesize that cellular heterogeneity has a significant impact on endoderm patterning and

85 pancreatic differentiation.

86 To resolve endoderm heterogeneity we aimed to ascertain novel surface markers for the

87 identification and characterisation of endoderm subpopulations with the aim of detecting

88 endoderm-derived organ progenitors in culture. The recognition of CD177 and CD275 as

89 specific surface markers for ADE subpopulations allowed us to confirm that bulk endoderm

90 differentiation cultures from human induced pluripotent stem cells (hiPSCs) and human

91 embryonic stem cells (hESC) are very heterogeneous in nature. Detailed analysis of the CD177+

92 and CD275+ ADE progenitors during early differentiation further allowed us to understand the

93 signals and factors that induce ADE subpopulations and guide liver and pancreatic

94 differentiations in human. The enrichment of CD177+ ADE permitted for more homogenous

95 pancreatic differentiation which resulted in improved maturation and function of insulin-

96 producing β-like cells.

4

97 Results

98 Identification of novel surface markers to distinguish specified ADE subpopulations

99 Self-organisation and spatial patterning has been recently studied using hESCs24. Current hESC

100 differentiation protocols induce a seemingly homogenous population of definitive endoderm

101 (DE) when measured by specific marker genes, i.e. CXCR4, CXCR4/CD117 or

102 FOXA2/SOX17 at day 4 of differentiation (D4) (Fig. 1a-c). To investigate whether endoderm

103 differentiation is homogenous we used fluorescent activated cell sorting (FACS) based on

104 CXCR4 (CD184) and c-KIT (CD117) marker expression and analysed the induced endoderm

105 by quantitative PCR (qPCR) (Fig. 1b and 1d-g). Surprisingly, CD117 marks only a subset of

106 CXCR4+ endoderm (63.3%) and the CXCR4+/CD117+ double positive population can be

107 divided into CXCR4high/CD117high (21.3%), CXCR4mid/CD117mid (15.4%),

108 CXCR4low/CD117low (26.6%) and CXCR4+/CD117- (15.3%) subpopulations (Fig. 1b). We

109 found inverse expression levels of FOXA2 and SOX17 in the sorted CXCR4high/CD117high to

110 CXCR4low/CD117low subpopulations (Fig. 1d, e) and increased expression of the ADE markers

111 CERBERUS1 (CER1) and hematopoietically expressed homeobox (HHEX) in

112 CXCR4+/CD117- and CXCR4high/CD117high subpopulations, respectively (Fig. 1f, g). FoxA2

113 and Sox17 are expressed along opposite A-P gradients in the endoderm during mouse

114 gastrulation25. These results suggest that the endoderm is molecular heterogeneous and receives

115 some kind of pattern information in culture, likely through neighbouring cell-type

116 interactions24, similar to the endoderm in vivo26.

117 We speculated that the heterogeneity in endoderm can be a result of specified organ progenitors

118 generated in the culture. Endoderm fate mapping studies in mouse embryos have presented

119 already specified liver, pancreas and intestinal progenitors shortly after gastrulation5,27. To

120 resolve endoderm heterogeneity and isolate different endoderm organ progenitors in vitro, we

121 performed a screen to find novel surface markers that distinguish specified endoderm 5

122 subpopulations. We screened a library of 330 monoclonal antibodies (mAbs) directed against

123 surface epitopes to identify mAbs that detect subpopulations of DE (FOXA2+/CXCR4+) in H9

124 hESC at D4 (Fig. 1h, Supplementary Fig. 1a,b). These antibodies included known cluster of

125 differentiation markers, integrins and other cell surface markers. In general, CXCR4 marks the

126 entire DE in mouse and humans and is commonly used as a standard marker for quantifying

127 DE during in vitro differentiations13,28. The use of FOXA2 not only allowed us to identify novel

128 antibodies that identify DE (FOXA2high/CXCR4+), but also exclude mesendoderm progenitors

129 (FOXA2low/CXCR4-) present in differentiation cultures (Supplementary Fig. 1b). From the

130 initial screen, we discovered 30 mAbs which marked distinct subpopulations of the DE

131 (Supplementary Table 1, Supplementary Fig. 1a). These markers were selected based on mean

132 intensity of expression in the FOXA2high/CXCR4high population, while being preferentially

133 lower expressed in the FOXA2low and FOXA2-/CXCR4- populations. As we were specifically

134 interested in ADE-derived organ progenitors, the secondary screen was focused on mAbs that

135 identify ADE subpopulations and partially co-express the ADE marker CER1 (Supplementary

136 Fig. 1e). This identified glycoprotein CD177/NB1, a molecule required for activation of

137 neutrophils29, as a candidate marker due to its highly dynamic expression range within the DE

138 population (FOXA2high/CXCR4high) and marking ~49% of CER1+ ADE subpopulation in

139 CXCR4+ DE (Supplementary Fig. 1c, f). Additionally, CD275/ICOSL, a factor required for T

140 cell generation30, showed a somewhat broader distribution marking a major subpopulation of

141 CXCR4+ cells and ~24% of the CER1+ ADE subpopulation in CXCR4+ DE (Supplementary

142 Fig. 1d, f). mRNA quantification of the enriched CD177+ and CD275+ subpopulations by

143 magnetic activated cell sorting (MACS) revealed high expression of the endoderm marker

144 genes FOXA2 and SOX17, when compared to the CXCR4+ sorted DE population

145 (Supplementary Fig. 1g). Interestingly, the CD177+-enriched subpopulation showed higher

146 levels of the ADE marker CER1, while the CD275+-enriched subpopulation showed higher

147 levels of the ADE and liver marker HHEX, suggesting that these are distinct ADE 6

148 subpopulations (Supplementary Fig. 1h)26. Furthermore, in DE cells that are >90% CXCR4+,

149 CD177 marks ~37% and CD275 marks ~20% of cells in H9 hESC differentiation at D4 (Fig.

150 1h,i). Analysis of several hiPSC and hESC lines affirm that the induction efficiency of pan-

151 endoderm marker CXCR4 reaches up to ~90% in all cell lines making it seemingly homogenous

152 endoderm (Supplementary Fig. 2a,b). However, further measuring of CD177 or CD275 ADE

153 markers in CXCR4+ DE revealed marked differences, suggesting that different ratios of ADE

154 subpopulations are generated in different hiPSC and hESC lines (Supplementary Fig. 2c). When

155 we compared three previously established endoderm differentiation schemes14,15,31, we

156 observed differences in the efficiencies of the two ADE subpopulations at almost identical

157 levels of CXCR4+ DE expression in the H9 hESC and HMGUi001-A hiPSC (Supplementary

158 Fig. 3). Taken together, these results suggest that we discovered two novel surface markers that

159 identify distinct ADE subpopulations in the bulk endoderm population, which are induced to

160 different extend depending on cell line and differentiation protocol.

161 CD177 and CD275 mark molecular distinct ADE subpopulations

162 To further characterize CD177+-, CD275+-, and CXCR4+- ADE subpopulations we used MACS

163 followed by global gene expression profiling and qPCR (Fig. 2a). Gene expression profiles

164 followed by principal component analysis (PCA) revealed that the enriched CD177+ and

165 CD275+ ADE subpopulations were not only different from each other, but also different to the

166 CXCR4+ DE, demonstrating heterogeneity in endoderm differentiation at D4 (Fig. 2b). Gene

167 ontology (GO) and differential gene expression analysis in three-way comparisons of CD177+,

168 CD275+ and CXCR4+ populations identified genes related to pathways regulating endoderm

169 patterning and proliferation as well as pancreatic cell-fate specification (Fig. 2c-e). These

170 included positive regulation of TGF-β32, downstream signalling of activated FGFR1 pathway7,

171 positive regulation of MAPK cascades33, retinoic acid (RA)-mediated signalling9 and regulation

172 of canonical and non-canonical WNT/planar cell polarity (PCP) signalling10.

7

173 Non-canonical and canonical Wnt signalling were described to be differentially regulated in

174 mouse pancreas vs liver progenitors, respectively10. Due to differential expression of CER1

175 (Supplementary Fig. 1), a Wnt, Bmp and Nodal signalling antagonist34 and other WNT

176 signalling components enriched in ADE subpopulations (Fig. 2d-e), we tested whether the

177 CD177+ and CD275+ ADE subpopulations receive differential WNT signalling. Specifically,

178 components of the non-canonical WNT/PCP pathway, such as DVL2, CELSR1, and JNK as

179 well as WNT/PCP ligands, i.e. WNT5A and WNT4 were upregulated in the CD177+ ADE

180 subpopulation (Fig. 2f). In contrast, the expression of canonical ligand WNT3A and its target

181 gene AXIN2 were upregulated in the CD275+ ADE subpopulation (Fig. 2g). Western blot

182 analysis showed increased DVL2 and phospho-JNK levels proposing signalling activation of

183 the WNT/PCP pathway in the CD177+ ADE subpopulation (Fig. 2h, i). Nuclear translocation

184 of β-catenin is a hallmark of canonical WNT activation35, thus we tested for the distribution of

185 β-catenin in the nucleus and cytoplasm by immunofluorescence in the isolated subpopulations.

186 Remarkably, β-catenin was highly enriched in adherens junctions of CD177+ ADE progenitors,

187 suggesting degradation in the cytoplasm. Conversely, β-catenin accumulation was observed in

188 the nucleus and cytoplasm of CD275+ and CXCR4+ populations (Fig. 2j). These results suggest

189 that CD275+ ADE progenitors receive canonical WNT/β-catenin signalling and might be

190 specified towards the liver fate, while CD177+ ADE progenitors receive non-canonical

191 WNT/PCP signalling and might be specified towards the pancreatic fate5,10.

192 CD177 identifies specified pancreatic progenitors in hPSC differentiation

193 Next, we studied in detail the surface marker expression of CXCR4, CD177 and CD275 during

194 hiPSC-derived pancreatic and endocrine differentiation in vitro. The expression of CD177 and

195 CD275 peaked during ADE formation and patterning and gradually decreased during gut tube

196 and liver and pancreatic progenitor formation, where the expression of CD177 and CD275 was

197 almost negligible (Supplementary Fig. 4a). In contrast, we observed high expression of CXCR4

8

198 during pancreatic and endocrine differentiation until the formation of hiPSC-derived β-like

199 cells. To test whether the differential activation of cell fate specification pathways in CD177+

200 and CD275+ ADE subpopulations (Fig. 2) leads to preferential lineage allocation, we explored

201 the in vitro differentiation potential towards the liver and pancreatic fate. To test for liver

202 potency we differentiated the MACS sorted cells towards hepatocytes36 and tested the

203 expression of early liver progenitor genes AFP, TTR and HHEX (Supplementary Fig. 4b, c).

204 Remarkably, the expression of mRNA transcripts for HHEX, AFP and TTR were upregulated

205 in CXCR4+- and CD275+-derived early hepatic progenitors, when compared to CD177+-derived

206 progenitors (Supplementary Fig. 4c). On the other hand, when we tested for pancreatic

207 differentiation potency (Fig. 3a), we noticed more uniform expression of GATA6, an important

208 regulator for pancreatic development37-39, and PDX1 in CD177+-derived pancreatic progenitors

209 at stage 3 (CD177-PP1) when compared to CXCR4+- and CD275+-derived PP1 (Supplementary

210 Fig. 4d). We also observed that CD177+-derived pancreatic progenitors at stage 4 (CD177-PP2)

211 expressed very high mRNA levels of PDX1 and NKX6.1 (Fig. 3b). Immunofluorescence (Fig.

212 3c) and FACS analysis (Fig. 3d-e) substantiated these findings, suggesting that sorting of the

213 specified CD177+ ADE subpopulations can enhance the differentiation potential towards the

214 pancreatic lineage. To exclude the undirected generation of other endoderm-derived organ

215 progenitors we tested lung (SOX2+) and gut (CDX2+) markers, which were not expressed in

216 any of the sorted subpopulations at S4 (Supplementary Fig. 4e). Moreover, bulk endoderm

217 differentiation of several hiPSC and hESC lines consistently showed a positive correlation of

218 CD177+ ADE at S1 with pancreatic differentiation efficiency at S3 (Supplementary Fig. 5). For

219 further analyses we used the H1 hESC and HMGUI001-A hiPSC cell lines due to their superior

220 pancreatic differentiation efficiencies (Supplementary Fig. 5). Taken together, these results

221 suggest that CD177 not only predicts pancreatic differentiation efficiency at DE stage, but also

222 shows that CD177-sorted ADE subpopulation differentiates more efficiently into pancreatic

223 progenitors. 9

224 Canonical WNT inhibits, whereas non-canonical WNT signalling promotes the pancreatic

225 fate

226 CD275+ ADE receives canonical WNT signalling and is biased towards liver differentiation,

227 whereas CD177+ ADE receives non-canonical WNT signalling and is biased towards the

228 pancreatic fate, consistent with in vivo data from mouse liver and pancreas development10. To

229 directly test whether modulation of WNT signalling has an impact on pancreatic in vitro

230 differentiation from hiPSCs, we added IWP2, a Porcupine inhibitor that selectively inhibits

231 palmitoylation and secretion of Wnt ligands,40 to our differentiation cultures. We modulated

232 WNT signalling during primitive gut tube (PGT) formation and patterning at S2, when the

233 expression of CD177 and CD275 reach peak levels (Supplementary Fig. 4), and then further

234 differentiated towards PP2 stage (Fig. 4a). Under standard differentiation conditions without

235 IWP2, FACS analysis for PDX1+/NKX6.1+ showed ~75% PP2 cells derived from CD177+-

236 ADE, whereas ~23% were generated from CD275+-ADE and ~45% from CXCR4+-DE (Fig.

237 4b, Supplementary Table 2). After the addition of IWP2, the percentages of PDX1+/NKX6.1+

238 PP2 cells derived from CXCR4+-DE (~70%) and CD275+-ADE (~50%) increased drastically,

239 suggesting that the inhibition of WNT ligand secretion promotes pancreatic differentiation (Fig.

240 4b, c). No differences were observed in the percentages of PDX1+/NKX6.1+ cells in CD177+-

241 PP2s, suggesting that CD177+ADE progenitors, which express CER1, are already shielded from

242 WNT signalling activation, consistent with our previous results (Fig. 2). In addition, CD177+-

243 PP2 showed significantly higher percentages of PDX1+/NKX6.1+ pancreatic progenitors when

244 compared with previously published protocols (Supplementary Table 2).

245 As IWP2 impedes overall WNT secretion including canonical and non-canonical WNT ligands,

246 we decided to directly analyse the impact of canonical and non-canonical WNT signalling on

247 pancreatic differentiation using signalling specific ligands and small molecules (Fig. 4d).

248 Therefore, we added the canonical WNT ligand WNT3A (20 ng/ml) and the GSK3β inhibitor

10

249 CHIR (3 µM) to activate canonical WNT signalling and WNT5A (400 ng/ml) to stimulate non-

250 canonical WNT signalling pathways. Addition of IWP2 increased the percentages of

+ + 251 PDX1 /NKX6.1 PP2 cells from ~30% to ~60% (Fig. 4e-g). In contrast, addition of CHIR

252 (~10%) and WNT3A (~20%) stalled the generation of PP2 cells, while exposure to WNT5A

253 ligand (~40%) improved PP2 differentiation (Fig. 4d-g). These results together suggest that

254 canonical WNT signalling inhibits, whereas non-canonical WNT signalling promotes

255 pancreatic differentiation.

256 Another hallmark of canonical WNT signalling is the activation of cell-cycle regulators

257 triggering cell proliferation41 and of non-canonical WNT signalling to promote cell-cycle exit42.

258 Cell proliferation assessment in CD177+-, CD275+- and CXCR4+-PP2s by EdU pulse labelling

259 revealed ~15% of CD177+-PP2s were EdU+ compared to ~50% of CD275+- and ~60% of

260 CXCR4+-PP2s (Fig. 4h, i). Suppression of NGN3 during the early stages of pancreatic

261 differentiation is vital to reduce the generation of polyhormonal cells expressing insulin and

262 glucagon43 and cell-cycle lengthening is essential to induce NGN3 expression44. Hence, we

263 tested for the induction of NGN3 mRNA in CD177+-, CD275+- and CXCR4+-PP2s at S4 and in

264 endocrine progenitors (EPs) at S5. NGN3 mRNA was tightly regulated in CD177+-PP2s and

265 very efficiently induced in CD177+-EPs at S5, when compared to CXCR4+- and CD275+-PP2s

266 and -EPs (Fig. 4j).

267 CD177+ specified ADE generates efficiently stem cell-derived β-like cells (SC-β-cells)

268 To determine whether hiPSC-derived CD177+-ADE not only generates more efficiently

269 pancreatic and endocrine progenitors, but also SC-β-cells we differentiated MACS-enriched

270 DE and ADE towards INS+/NKX6.1+ cells at S7 (Fig. 5a). Since CXCR4+-DE represents the

271 bulk endoderm population, we decided to compare CD177+-ADE to CXCR4+-DE and

272 additionally used unsorted (US) heterogeneous endoderm differentiations to benchmark the

273 state-of-the art differentiation protocols. We added IWP2 to our cultures to optimize the overall 11

274 pancreatic differentiation efficiencies. In average, ~62% of CD177+- and ~46% of CXCR4+-β-

275 cells synthesized both INS and NKX6.1 protein (Fig. 5b-d). We also observed similar

276 percentages of INS+/NKX6.1+ cells (~45%) in the US-derived β-like cells (US-β-cells) after the

277 treatment with IWP2 (Fig. 5b-d). Immunostaining and FACS of sectioned clusters revealed

278 most of the cells to be INS+ and only a small subset of cells (~10%) of CD177+-β-cells and

279 (~20%) of US-β-cells were polyhormonal (INS+/GCG+) cells (Fig. 5d, f, g, Supplementary

280 Table 2). We observed only a small population of polyhormonal INS+/SST+ cells in the US-β-

281 cells and CD177+-β-cells (Fig. 5e-g). Finally, we repeated these experiments with the H1 hESC

282 line and confirmed that CD177+-ADE as compared to bulk differentiations shows more

283 homogenous and efficient pancreatic and β-like cell differentiation (Supplementary Fig. 6a-c,

284 f-g).

285 CD177+ specified ADE generates more mature and functional SC-β-cells

286 Subsequently, we determined whether enrichment of ADE progenitors during early stages of

287 differentiation not only improved SC-β-cell differentiation efficiency, but also maturation and

288 function. As the establishment of polarity and compaction plays an important role in maturation

289 of β-cells42,45, we decided to test if 2D vs 3D culture of the sorted cells influences the induction

290 and expression of PDX1 and NKX6.1 during pancreatic differentiation. Therefore, we sorted

291 CD177+ and CXCR4+ DE/ADE and further differentiated these into pancreatic progenitors

292 either in 2D adherent cultures or after re-aggregation in 3D clusters (Supplementary Fig. 7a).

293 We observed a slight increase in the amount of PDX1+/NKX6.1+ double positive PP2s in 3D

294 culture (Supplementary Fig. 7b). Interestingly, we noticed the formation of dense and compact

295 aggregates with defined E-CAD+ adherens junctions in CD177+-β-cells (Supplementary Fig.

296 7c), in line with the enrichment of the cell-cell adhesion molecule -catenin in CD177+ ADE

297 progenitors (Fig. 2l). Next, we analysed the expression of maturation markers in SC-β-cells and

298 found elevated levels of MAFA and GLUT1 mRNA transcripts in CD177+-β-cells compared to

12

299 US-β-cells, but still significant lower expression when compared to human islets (Fig. 6b).

300 Immunocytochemistry data showed the presence of MAFA in nuclei (Fig. 6c) and GLUT1 in

301 both membrane and cytoplasm (Fig. 6e) in higher percentages in CD177+-β-cells at S7.

302 Quantification by FACS revealed that CD177+-ADE generates more SC-β-cells co-expressing

303 INS and MAFA (~42%) as well as co-expressing INS and GLUT1 (~38%) (Fig. 6d, f). In line

304 with this, H1-derived CD177+-β-cells showed higher percentages of β-cells expressing INS and

305 GLUT1 (~31%) and INS and MAFA (~17%) compared to US-β-cells (Supplementary. Fig. 6d-

306 h). The increased maturation state was further supported by the comparison to previous

307 published protocols14,15 (Supplementary Table 2), implicating that the isolation of pancreatic

308 specified ADE promotes more homogenous differentiation towards β-like cells when compared

309 to heterogeneous bulk DE (Fig. 6f).

310 Finally, we tested the functionality of US-β-cells and CD177+-β-cells by assessing their

311 response to glucose stimulation in sequential static and dynamic challenges. At S7, the US- and

312 CD177+-β-cells in 3D clusters strongly stained red for dithizone (DTZ), a zinc chelating reagent

313 that stains the insulin granules (Fig. 7a). In line with the increased number and maturation status

314 (Fig. 6), we recorded significant more insulin content in H1- and hiPSC-derived CD177+-β-

315 cells (Fig. 7b, Supplementary Fig. 8a). Upon exposure to increasing concentrations of glucose

316 (5.6, 11.1 and 20 mM), US-and CD177+-β-cells showed glucose-stimulated insulin secretion

317 (GSIS), but US-β-cells failed to prolong the response with 20 mM glucose (Fig. 7c), implying

318 exhaustion of insulin granules with repeated higher glucose stimuli. Low glucose stimulus of

319 2.8 mM glucose drastically reduced GSIS in CD177+-β-cells almost to the basal levels (dashed

320 line) pinpointing tight sensation and glucose regulation compared to US-β-cells (Fig. 7c). Next,

321 we performed sequential static GSIS with both hiPSC and H1 hESC lines. We observed that

322 CD177-β-cells were capable of sensing repeated low and high glucose impulses, thus regulating

323 the insulin release depending upon glucose stimulation in both cell lines (Fig. 7d,

13

324 Supplementary Fig. 8b). Though hiPSC-derived US-β-cells could regulate the initial shift from

325 2.8 mM to 20 mM glucose, they failed to show increase GSIS in the 2nd glucose challenge (Fig.

326 7d). H1 hESC-derived US-β-cells completely failed to regulate insulin release upon different

327 glucose stimulations (Supplementary Fig. 8b).

328 Ultimately, we supplemented our static assays with dynamic GSIS in two different cell lines;

329 hiPSC and H1 hESC. We thus tested the response of US-β-cells and CD177+-β-cells to

330 secretagogues, such as 20 mM glucose, 10 nM Exendin-4 (Ex-4) and 25 mM KCl in a perifusion

331 system. Upon exposure to 20 mM glucose, CD177+-β-cells consistently displayed a rapid first-

332 phase insulin release as well as a secretory response to the secretagogues Ex-4 and KCl similar

333 to human islets in both cell lines (Fig. 7e, g, Supplementary Fig. 8d). However, after Ex-4

334 stimulation SC-β-cells were not capable of shutting off the insulin release rapidly in the low

335 glucose condition, indicating either a still immature β-cell status or lacking inhibitory - and/or

336 -cells, when compared to human islets. In agreement with the insulin content of CD177+-β-

337 cells (Fig. 7b, Supplementary Fig. 8a), we consistently observed less insulin secretion compared

338 to human islets in SC-β-cells (Fig. 7e, g, Supplementary Fig. 8d). In comparison, we did not

339 observe a first-phase insulin release in US-β-cells on 20 mM glucose stimulation, but a reliable

340 response to additional Ex-4 induction in the presence of high glucose and KCl hyperpolarization

341 (Fig. 7f, Supplementary Fig.8c). This data collectively suggests that CD177+-β-cells are

342 significantly more mature and functional than SC-β-cells derived by bulk differentiation using

343 hiPSC and hESC cell lines.

344

345

346

347 14

348 Discussion

349 In this study, by means of novel surface markers (CD177 and CD275), we report remarkable

350 functional heterogeneity of the ADE in vitro, the signalling requirements for pancreatic

351 progenitor specification and how sorting of specified organ progenitors at the endoderm stage

352 can improve the differentiation, maturation and function of SC-derived β-like cells in vitro.

353 Although cellular heterogeneity is an obvious origin for uncontrolled pluripotent stem cell

354 differentiations resulting in low numbers of terminally differentiated cell types, it has not been

355 addressed systematically before. We resolved this endoderm heterogeneity by identifying 30

356 mAbs directed against surface epitopes. Here, we specifically focused on CD177+ and CD275+

357 ADE subpopulations. This revealed very different quality and quantity of endoderm generated

358 in vitro using several hiPSC and hESC lines and different published protocols14,15,31, suggesting

359 that quality control at early steps of differentiation is warranted to direct ADE and further

360 endoderm-derived organ differentiation. In vivo, high TGF-β/Nodal activity promotes the

361 anterior fate, while lower Nodal signalling strength, Bmp signalling from the extra-embryonic

362 region and high canonical Wnt/β-catenin signalling at the posterior side specifies posterior

363 fates1,46-48. Interestingly, we observed higher expression of CER1, a Nodal, Bmp and Wnt

364 signalling antagonist49, in CD177+ ADE progenitors, suggesting an active auto-regulatory

365 feedback loop modulating ligand-receptor interactions in these cells and thus fine-tuning the

366 morphogen requirements to maintain the anterior characteristic and fate specification of the

367 CD177+ ADE progenitors1,50,51. Hence, we propose that the endoderm is inherently

368 heterogeneous and depending upon the signalling it receives, the endoderm is patterned by

369 intrinsic and extrinsic cues which translate into the formation of distinct organ progenitors. In

370 the future it will be interesting to explore the nature of the other endoderm subpopulations that

371 can be marked by one of our 30 mAbs to identify organ progenitors for the lung, thymus and

372 thyroid and the related signalling cues to induce fate specification and allocation.

15

373 Endoderm patterning in mice leads to fate specification of organ progenitors5. In human,

374 gastrulation and very early lineage commitment cannot be studied as it has happened already

375 before pregnancy can be confirmed11. Our study has helped to get first insights into how fine

376 tuning of morphogen gradients lead to patterning and fate specification during human endoderm

377 development in vitro. The secretion of the extracellular WNT, BMP and NODAL inhibitor

378 CER1, positive regulation of TGF-β signalling, regulation of canonical and non-canonical

379 Wnt/planar cell polarity prompted the specification of CD177+ ADE progenitors towards the

380 pancreatic fate. On the other hand, upregulation of transcription factor HHEX and activation of

381 canonical WNT signalling specified CD275+ ADE subpopulations towards the liver fate.

382 Interestingly, blocking the secretion of WNT ligands promoted, whereas activation of the

383 canonical WNT pathway inhibited the pancreatic fate, thus underpinning the role of canonical

384 WNT inhibition during pancreatic fate specification10. The efficient generation of CD177+

385 ADE-derived pancreatic progenitors showed that depleting cell populations that are not

386 specified towards the pancreatic fate can help in increasing the homogeneity of organ

387 progenitors and improve directed differentiation. This is an important consideration when

388 choosing an 2D adherent or 3D cluster differentiation paradigm. For example, even if endoderm

389 induction efficiency is >90%, dragging along mesoderm (contaminating) cells in bulk

390 differentiations can vastly influence the specification and identity of endoderm-derived organ

391 progenitors. Priming of sorted CD177+ ADE progenitors towards pancreatic fate by non-

392 canonical WNT/PCP signalling further translated into efficient pancreatic and endocrine

393 specification of these cells. In mice, loss of Celsr2 and Celsr3, two principle components of

394 WNT/PCP signalling reduced endocrine specification, β cell differentiation and glucose

395 homeostasis52.

396 Islet architecture and compaction as well as the WNT/PCP pathway trigger β cell maturation

397 and function42,45. Recently published protocols for the generation of β-like cells in vitro used

16

398 an air-liquid interface (ALI) system to maintain apical-basal polarity to generate glucose-

399 responsive β-like cells14,53. The pancreatic progenitors generated from CD177+ ADE were more

400 polarised and formed tighter and compact clusters likely due to the high expression and activity

401 of the Wnt/PCP pathway and increased cell-cell adhesion. This together with the enrichment of

402 specified pancreatic progenitors potentially explains the more homogenous pancreatic and

403 endocrine differentiation. The evident increased expression of β cell maturation marker MAFA

404 and GLUT1 in CD177+ ADE-derived β-like cells suggested that cluster architecture and

405 polarisation have an impact on maturation and functionality. Another striking result was the

406 expression of glucose transporter GLUT1 by CD177+ ADE generated β-like cells. In mouse β

407 cells, the presence of GLUT2 during maturation of β cells is necessary for the proper uptake

408 and sensing of glucose to initiate insulin secretion45. Upon static glucose stimulation, the insulin

409 secretion of the in vitro generated β-like cells using previously published protocols is ~1.5-2

410 fold14,15,38,54,55. The β-like cells generated from enriched CD177+ ADE, however, showed

411 increased insulin content and improved sequential static and dynamic GSIS with a rapid first-

412 phase response. Nevertheless, in the light of recent publications the link between classical

413 maturation markers (MAFA and GLUT1) and functionality of SC-β-cells needs to be

414 revisited56,57. In both studies the authors failed to detect MAFA and GLUT1 expression in the

415 SC-β-cells, but both studies showed dynamic GSIS. One study showed rapid first-56 and the

416 other rapid first- and second-phase insulin secretion57 after glucose stimulation. Contrary to

417 these findings, ours and other studies show co-expression of INS and MAFA in SC-β-

418 cells14,23. A combined approach of enriching CD177-ADE progenitors and improved

419 differentiation protocols56,57 will further enhance the maturation and functionality of SC-β-

420 cells. This points towards the actuality that hESC and hiPSC genetic background,

421 differentiation protocols, methods and antibodies, as well as functional read-outs are

422 inherently different and need to be harmonized for standardized quality control of SC-β-

423 cells. 17

424 Recent publications also point to the fact that enrichment of certain subpopulations of cells (e.g.

425 CD177+ ADE or GP2+ PP)22,23 at different stages during differentiations can enhance the

426 efficiency of the terminally differentiated phenotypes and increases the purity and safety of the

427 differentiation product. Isolation of CD177+-specified ADE progenitors will help in controlling

428 the differentiation at early stages even before PDX1 can be measured thereby maintaining

429 homogeneity at later stages of differentiation. Testing CD177 induction at DE/ADE stage at S1

430 can be used as an estimate to determine the differentiation potential of genetically different

431 hiPSC and hESC lines towards the pancreatic lineage. This can be important for upscaling the

432 differentiation process and generate large number of pancreatic progenitors for β-cell

433 replacement therapy. Encouraging results on self-expanding endoderm have shown the capacity

434 to enhance homogenous differentiation to hormone producing cell types by synchronizing the

435 differentiation speed and reducing cellular heterogeneity28.

436 Taken together, our results do not only broaden the understanding of human pancreatic

437 development but also provides insights into how the translation of certain developmental cues

438 can contribute to generation of mature β-like cells in vitro. CD177+ and CD275+ serve as tools

439 to standardise early differentiations in terms of generation of specified organ progenitors before

440 moving on with expensive and time-consuming long-term differentiation paradigms. In light of

441 these recent findings, our study will help to globally accelerate upscaling the production of

442 clinically relevant cells for disease modelling, drug testing and cell-replacement therapy.

443

444

445

446

447 18

448 Materials and Methods

449 450 Cell sources

451 Human islets were obtained from the Rudbecklaboratoriet C11 (Uppsala, Sweden) and islet

452 core facility (Edmonton, Canada) with informed consent. The H9, H1 and HUES8 hESC lines

453 was received from WiCell Research Institute, Inc. (Madison, WI). The Mel1-NKX6.1-GFP

454 were obtained from Australian Stem Cell Centre (Clayton, Victoria). An episomal

455 reprogrammed HMGUi-001 iPSC line was generated in lab from control group of MODY-4

456 patients58 (Gibco Human Episomal iPSC, Cat#A18945, Life Technologies, CA). All cell lines

457 have been authenticated by Cell Line Genetics (Madison, WI) and confirmed to be

458 mycoplasma-free by using the Lonza MycoAlert Mycoplasma Detection Kit (Lonza,

459 Cat#LT07-418). The hESC lines were used under the permission of Robert Koch Institute.

460 In vitro differentiation of human pluripotent stem cells towards pancreatic β-like cells.

461 H9, H1, Mel1-NKX6.1-GFP, HUES8 and HMGUi-001 iPSCs were cultured on 1:30 diluted

462 Geltrex (Invitogen, U.K, Cat#A1413302) in StemMACS iPS-Brew medium (Miltenyi Biotec,

463 Germany, Cat#130-104-368). At ~70% confluency, cultures were rinsed with 1× DPBS without

464 Mg2+ and Ca2+ (Invitrogen, Cat#14190) followed by incubation with 0.5 mM EDTA

465 (Applichem, Cat#12604-021) for 2–3 min at 37°C. Single cells were rinsed with iPS-Brew, and

466 spun at 1300 r.p.m. for 3 min. The resulting cell pellet was suspended in iPS-Brew medium

467 supplemented with Y-27632 (10 μM; Sigma-Aldrich; MO, Cat#Y0503) and the single cell

468 suspension was seeded at ~1.5–2×105 cells/cm2 on Geltrex-coated surfaces. Cultures were fed

469 every day with iPS-Brew medium and differentiation was initiated 24 h following seeding,

470 resulting in ~90% starting confluency. This confluency is a key factor to getting proper

471 patterning of endoderm.

19

472 The cells were differentiated towards definitive endoderm using MCDB131 medium

473 supplemented with 0.5% BSA (Sigma, Cat#10775835001), 100 ng/ml Activin A (Peprotech,

474 Cat#120-14-300) and 25 ng/ml WNT3A (Peprotech, Cat#315-20) or 3 µM CHIR-99021

475 (Miltenyi Biotec, Cat#130-103-926) for the first day. For the next 2 days, the cells were treated

476 with MCDB131 supplemented with 0.5% BSA and 100ng/ml Activin A.

477 For differentiation towards β cells, Rezania et al. 2014 β-cell differentiation protocol was

478 used14. In nutshell, the cells were differentiated towards primitive gut tube with MCDB131

479 supplemented with 0.5 % BSA, 50 ng/ml of FGF7 (Peprotech, Cat#100-19-100) 0.25 mM

480 ascorbic acid (Sigma, Cat#120-14-300) and 1.25 µM IWP2 (Tocris, Cat#3533-10) for 2 days.

481 For the WNT signalling activation experiments only, 20 ng/ml of WNT3A or 3 µM CHIR was

482 added to the cultures along with the S2 medium without IWP2. For differentiation towards

483 posterior foregut, the cells were further exposed to MCDB131 medium supplemented with

484 1xGlutamax (Gibco, Cat#A12860-01), 2% BSA (Cat#10775835001), 0.25 mM ascorbic acid

485 (Sigma, Cat#A4544-25G), 50 ng/ml FGF7, 0.25 µM SANT-1 (Sigma, Cat#S4572-5MG), 1 µM

486 retinoic acid (Sigma, Cat#R2625-50MG), 100 nM LDN193189 (Sigma, Cat#04-0074), 1:200

487 ITS-X (Gibco, Cat#51500-056) and 200 nM TPB (Merk Millipore, Cat#565740-1MG) for 2

488 days. The cells were then further differentiated towards pancreatic endoderm using MCDB131

489 supplemented with 1xGlutamax, 10 mM final glucose concentration, 2% BSA, 0.25 mM

490 ascorbic acid, 2 ng/ml FGF7, 0.25 µM SANT-1, 0.1 µM retinoic acid, 200 nM LDN193189,

491 1:200 ITS-X and 100 nM TPB for 3 days. For induction of pancreatic endocrine precursors, the

492 cells were next exposed to MCDB131 medium supplemented with 1xGlutamax, 20 mM final

493 glucose concentration, 2% BSA, 0.25 µM SANT-1, 0.05 µM retinoic acid, 100 nM

494 LDN193189, 1:200 ITS-X, 1 µM T3 (Sigma, Cat#T6397-100MG), 10 µM ALK5 Inhibitor II

495 (Enzo life sciences, Cat#ALX-270-445-M005), 10 µM zinc sulphate (Sigma, Cat#SI Z0251-

496 100G) and 10 µg/ml heparin (Sigma, Cat#H3149) for 3 days. Hormone positive cells were

20

497 generated by exposing the endocrine progenitors from last step with MCDB131 supplemented

498 with 1xGlutamax, 20 mM final glucose concentration, 2% BSA, 100 nM LDN193189, 1:200

499 ITS-X, 1µM T3, 10 mM ALK5 Inhibitor II, 10 µM zinc sulphate and 100 nM gamma secretase

500 inhibitor XX (Merck, Cat#565789) for the first 7 days. For maturation of β-like cells, the cells

501 from previous stage were treated with 2% BSA, 1:200 ITS-X, 1 µM T3, 10 µM ALK5 inhibitor

502 II, 10 µM zinc sulphate, 1 mM N-acetyl cysteine (Sigma, Cat#A9165), 10 µM Trolox (EMD,

503 Cat#648471), 2 µM R428 (SelleckChem, Cat# S2841) and 10 mg/ml of heparin for 15 days.

504 Hepatic lineage commitment protocol

505 For generation of hepatic progenitors from DE, cells were sorted for CD177, CD275 and

506 CXCR4 at day 4 and were then seeded on Geltrex coated ibidi chambers at the cell density of

507 2x105 cells per well. Briefly, the cells were washed the next day and culture medium was

508 changed to hepatic commitment medium KO-DMEM (Knockout serum replacement medium)

509 supplemented with 1 mM L-glutamine, 1% nonessential amino acids, 0.1 mM 2-

510 mercaptoethanol, and 1% dimethyl sulfoxide for 3 days. For the maturation, the cells were then

511 cultured in Iscove’s modified Dulbecco’s medium (IMDM) supplemented with 20 ng/mL

512 Oncostatin M (Peprotech, Cat#300-10T), 0.5 μM dexamethasone (Sigma, Cat#D1756-1G) and

513 1:200 ITS-X supplement for 8 more days.

514 Sorting ADE subpopulations

515 On day 4 of differentiation (DE/ADE), the differentiated samples were collected and stained

516 for surface markers CD177, CXCR4 and CD275. For staining of the surface markers, 10 µl Ab

517 (conjugated to APC) was added per 1x106 cells in 100 µl volume of MCDB1+0.5% BSA. The

518 cells were stained in dark for 15 min on ice. For magnetic labelling of the antibody the stained

519 cells were washed 3x with PBS to remove the antibody and then suspended in 80 µl of

520 MCDB131+0.5% BSA medium with 20 µL of Anti-APC Microbeads per 10x106 of total cells.

21

521 The cells were incubated for 15 min at 4°C. The cells were washed with 1-2 ml of PBS and

522 then suspended up to 20x106 cells in 500 µL of MCDB131+0.5% BSA and proceeded with

523 magnetic sorting. For magnetic sorting of the ADE subpopulations, the LS column was placed

524 in magnetic sorter. The column was rinsed with 3 ml of PBS. Cell suspension was applied to

525 the column and the flow through containing unlabelled cells was discarded. The column was

526 then washed 3x with 3 ml of PBS. The antibody positive cells were collected by removing the

527 column from the separator and flushing it with 5 ml of medium. The cells were then seeded in

528 iPS-Brew medium supplemented with 10 µM Y-compound at the seeding density of 2-10x103

529 cells in 1 well of ultra-low attachment round bottom 96 well plates to form an aggregate or

530 4x105 cells in one well of ibidi chamber for further differentiation and staining.

531 Quantitative qPCR analysis and gene profiling

532 Gene expression was assessed in differentiated cells by Taqman Arrays (Applied Biosystems).

533 Data were analysed using Expression Suite Software (Applied Biosystems) and normalized to

534 undifferentiated hESCs using ΔΔCt method. Refer to Supplementary Table 3 for primer details.

535 Immunofluorescence staining and Western blotting

536 For immunocytochemistry, the cells or aggregates were dissociated using Accutase and fixed

537 in 4% PFA. The cells were then permeabilised using 0.5% Triton-X in blocking buffer for 30

538 minutes at room temperature. The cells were blocked for 1 h using donkey block and stained

539 for interested markers at 4°C overnight. Secondary antibody staining was performed for 2 h at

540 room temperature. the following day. DAPI staining was used to define nucleus. List of primary

541 antibodies used for immunostaining are mentioned in Supplementary Table 4.

542 Nuclear fractionation was done from sorted cells using Subcellular protein Fractionation Kit

543 for cultured cells from Thermo Scientific (Cat#78840). For Western blotting, cells were

544 dissociated in RIPA buffer directly after sorting. Cell lysates were resolved by SDS-PAGE,

22

545 transferred to PVDF membrane (Biorad) and incubated with the antibodies (Primary antibody:

546 o/n, 4°C; Secondary antibody 1 h, room temperature). Protein bands were visualized using HRP

547 conjugated antibodies and chemiluminescence reagent (Millipore). The bands were quantified

548 with ImageJ. Refer to Supplementary Table 4 for the dilutions and list of antibodies.

549 Flow cytometry analysis

550 hESCs, hiPSCs and differentiated cells were dissociated and single cell suspension was

551 prepared. The cells were fixed, permeablilised and stained for DE, pancreatic endoderm,

552 pancreatic progenitors and hormone positive markers. FACS gating was determined using

553 isotype antibodies. Cells were analysed using BD FACS Aria III. The list of all the FACS

554 antibodies and isotype controls are mentioned in Supplementary Table 4.

555 Sequential static glucose stimulated insulin secretion

556 Sequential static glucose stimulated insulin secretion (seqGSIS) of the generated β-like cells

557 was performed based on previous described protocols14,59. Briefly, 5 aggregates (6,000-10,000

558 cells in total) (n=4-5, biological replicates) were picked and rinsed three times with KRBH

559 buffer (129 mM NaCl, 4.8 mM KCl, 2.5 mM CaCl2, 1.2 mM MgSO2, 1 mM Na2HPO4, 1.2 mM

560 KH2PO4, 5 mM NaHCO3, 10 mM HEPES and 0.1% BSA in deionized water and sterile filtered)

561 and then equilibrated in KRBH buffer at 37°C for 30 min. Aggregates then were incubated in

562 KRBH buffer spiked with 2.8 mM glucose for 30 min at room temperature. Supernatants were

563 collected and the aggregates were transferred to KRBH buffer spiked with 20 mM glucose for

564 30 min. Supernatants were collected again. The aggregates were then washed to remove left

565 over high glucose with KRBH and another round of low glucose and high glucose stimulus was

566 performed. At the end of the experiment, cell aggregates were dissociated into single cells and

567 the cell numbers were counted to normalize the GSIS. Mercodia Human Insulin ELISA kit

23

568 (Mercodia, Cat#10-1113-01) was used to measure the insulin content in supernatant sample

569 following manufacturer’s protocol.

570 Dynamic glucose stimulated insulin secretion

571 Briefly, 25 SC-derived β-cells (iPSC (n=3), H1 hESC (n=5) biological replicates) or human

572 islets from healthy donors (n=4 biological replicates) were pre-incubated in KRBH buffer (115

573 mM NaCl, 5 mM KCl, 2.5 mM CaCl2, 1 mM MgCl2, 24 mM NaHCO3,10 mM HEPES and

574 0.1% BSA, pH 7.4) containing 2.8 mM Glucose for 30 min and then loaded on a nylon filter in

575 a plastic perfusion chamber containing acrylamide-based microbead slurry (Bio-Gel P-4, Bio-

576 Rad Laboratories). The SC-derived β-cells or human islets were then sequentially perifused

577 with low glucose (2.8 mM) for 12 min, followed by high-glucose (20 mM) for 24 min, Exendin-

578 4 (10 nM) + high glucose (20 mM) for 24 min, low glucose (2.8 mM) for 12 min and a final

579 step with 25 mM KCl for 12 min at a constant flow rate of 100 µl/180 sec using the BioRep

580 perifusion system (Model No. PERI-4.2) maintained at 37°C in a temperature controlled

581 chamber. Flow through fractions were collected on a 96-well plate maintained at 4°C and

582 quantified for insulin content using Human Insulin ELISA (Mercodia, Cat#10-1113-01) as per

583 manufacturer’s instruction. After the completion of run, SC-derived β-cells or human islets

584 were recovered from perifusion chambers and assayed for DNA contents and quantified using

585 Quant-IT PicoGreen dsDNA kit, (Thermo Fischer, Cat# P7581).

586

587

588

589

590

24

591 Table 1: Demographic information and characteristics of healthy human islet donors

Donor Age Gender BMI HLA Islet HbA1c

ID (Years) Purity (%)

(%)

R301 18 M 19 A:2, - B:65, 49 BW: 6, 4 75 5

CW:7, 8 DRB1: DR:11, 13

DQB1: 7, 6 DQA1:5, 1

DPA1: 1, -DPB1:02;01, 04;01

Other: DRW - 52, 52

R305 60 M 21 A:11, 31 B:8, 44 BW: 6, 4 80 5.6

CW:5, 7 DRB1:17, 4 DR:

DQB1: 2, 7 DQA1: 5, 3

DPA1: 1, 2 DPB1: 1, 04;01

Other: DR52present DR53

present

R306 22 M 21.1 A:1, 3 B:8, 65 BW:6, 6

CW: 7, 8 DRB1:15, 15

DR:51, -- DQB1:6, 6

DQA1: 1, 1 DPA1: 1, 1

DPB1: 1, 01;02

R309 47 F 27.4 A:2 ,3 B:7, 60 BW:6, 6

CW:10, 7 DRB1:

DR:5, 15 DQB1:8, 6

DQA1: 1, 3 DPA1:1, 1

25

DPB1: 04;01, 04;01

Other: DRW - 53, 51

R310 25 M 26.4 A:02, 31 B:7, 60 BW:

CW:10, 7 DRB1:13, 15 DR:

DQB1: 6, 6 DQA1:1, 1

DPA1: 1, 2 DPB1:0401, 5

Other: DRB3 - 52, --

592 Human islets were obtained from the University of Alberta Diabetes Institute Islet Core

593 (Edmonton, Alberta, Canada). Islets from healthy donors R305, R306, R309, R310 were used

594 for dynamic GSIS, whereas R301, R305, R306, R309, R310 were used for insulin content.

595 Insulin content

596 S7 clusters from CD177, unsorted differentiations and human islets were washed with PBS and

597 dissociated using Accutase. Cells were counted and 1000 cells were collected for measuring

598 insulin content. The cells were resuspended in Acid-EtOH solution (1.5% HCL and 70% EtOH)

599 and kept on a shaker at 4°C overnight. The tubes were centrifuged at 2100 g for 15 min and

600 supernatant was collected and neutralised with an equal volume of 1 M Tris (pH 7.5). Human

601 insulin was measured using Mercodia Human Insulin ELISA kit (Mercodia, Cat#10-1113-01).

602 DTZ staining

603 S7 clusters were washed with PBS and then suspended into DTZ staining for 2 min at RT. The

604 cells were then washed with PBS and pictures were taken with Leica Stereoscope.

605 Affymetrix microarray analysis

26

606 For gene profiling, total RNA was extracted using miRNeasy Mini kit (Qiagen, Cat#217004),

607 RNA integrity was checked using Agilent 2100 Bioanalyzer (Agilent RNA 6000 Pico Kit) and

608 only high quality RNA (RIN>7) was used for microarray analysis. Total RNA (5 ng) was

609 amplified using the Ovation Pico WTA System V2 in combination with the Encore Biotin

610 Module (Nugen). Amplified cDNA was hybridised on Affymetrix Human Gene ST 2.0 arrays

611 (Affymetrix, 902113). Staining and scanning (GeneChip Scanner 3000 7G) was done according

612 to the Affymetrix expression protocol including minor modifications as suggested in the Encore

613 Biotin protocol. Expression console (v.1.4.1.46, Affymetrix) was used for quality control. All

614 subsequent computational analysis was performed in R using Bioconductor packages.

615 Expression data were RMA normalised using the oligo package (version 1.42.0) and probe sets

616 were annotated using the package hugene20sttranscriptcluster.db (version 8.7.0). Differential

617 expression analyses were performed using the limma package (version 3.34.9) and P-values

618 were adjusted for multiple testing by Benjamini-Hochberg correction. A gene was considered

619 as differentially expressed if the raw P-value was below a threshold of 0.01 and the fold-change

620 was greater than or equal to 1.5. Functional enrichments were conducted using HOMER60. All

621 microarray data is available at GEO under the accession number GSE113791

622 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE113791).

623 Image analysis

624 Images were acquired with Leica SP5 confocal microscope and Zeiss LSM 880 Airy Scan

625 confocal microscope. Images taken by Leica confocal were analysed using Leica LAS AF Lite.

626 Images taken by Zeiss confocal microscope were analysed using Zeiss Zen Blue software.

627 Statistical analysis and reproducibility

628 All values are depicted as means ±s.e.m. All statistical tests performed are mentioned in figure

629 legends for each data set. In brief, statistical significance is defined as P<0.05. Sample sizes are

27

630 provided in the figure legends. Comparison of 3 or more data sets were performed using

631 ordinary one way ANOVA with Bonferroni’s multiple comparison test for Figs. 1d-g, 2f-g,

632 3b/e, 4b/e/i, 6b, 7b and Supplementary Figs. 1g-h, 3e and 4c. Two tailed unpaired t-tests

633 (Student’s t-test) with Welch’s correction was used in Fig. 4j, 5d/e, 6f, 7d and Supplementary

634 Fig. 6g/h, 8a. Two tailed unpaired t-tests (Student’s t-test) assuming equal standard deviation

635 in Supplementary Fig. 8b. All statistics were performed using GraphPad Prism software 8

636 (GraphPad Software Inc., La Jolla, CA). No statistical methods were used to determine

637 sample size. All P values are displayed in the figures.

638 Acknowledgements

639 We would like to thank Alireza Rezania for providing hMAFA and hGLUT1 antibodies. The

640 authors are grateful to Ingo Burtscher, Aimée Bastidas-Ponce, Ciro Salinno and Marta Medina

641 Tarquis for their invaluable inputs and technical assistance. We would like to thank Donna

642 Marie Thomson and Mara Catani for reading and correction of the manuscript. This work was

643 supported by the HumEN consortium funded by European Union's Seventh Framework

644 Programme for Research, Technological Development and Demonstration under grant

645 agreement no.602587 (http://www.hum-en.eu/). This work was also funded in part by the

646 German Center for Diabetes Research (DZD e.V.) and the Helmholtz Alliance ‘Aging and

647 Metabolic Programming, AMPro’. P.U.M is funded by postdoctoral grant from HumEN

648 consortium, EU. M.S, S.P and K.S are supported by Helena graduate school and Technische

649 Universität München (TUM). S.K is an employee of Miltenyi Biotec GmbH, Bergisch

650 Gladbach , Germany.

651

652

653

28

654 Author Contributions

655 P.U.M and H.L wrote the manuscript. P.U.M and K.S contributed equally to this work. P.U.M

656 and H.L designed experiments, analysed and interpreted the results. K.S, S.P and A.A.

657 performed experiments and analysed data. M.S provided bioinformatics assistance and

658 analysed the results. J.B provided technical assistance. S.K designed, performed and analysed

659 the antibody screen. M.I performed the microarray chips and analysed them. P.U.M and H.L

660 conceived the project.

661 Competing financial interests

662 The authors declare competing financial interests. Helmholtz Zentrum München and Miltenyi

663 Biotec own the patent (#PLA16A13, Luxembourg patent application No.: 100320:

664 “"METHODS FOR PURIFYING ENDODERM AND PANCREATIC ENDODERM CELLS

665 DERIVED FROM HUMAN EMBRYONIC STEM CELLS" for the use of CD177 and CD275

666 antibodies in pancreatic and liver differentiation protocols.

667

668

669

670

671

672

673

674

29

675 References and Bibliography

676 1 Zorn, A. M. & Wells, J. M. Vertebrate Endoderm Development and Organ Formation. Annual 677 review of cell and developmental biology 25, 221-251, 678 doi:10.1146/annurev.cellbio.042308.113344 (2009). 679 2 Spence, J. R. & Wells, J. M. Translational embryology: Using embryonic principles to generate 680 pancreatic endocrine cells from embryonic stem cells. Developmental Dynamics 236, 3218- 681 3227, doi:10.1002/dvdy.21366 (2007). 682 3 Beddington, R. S. P. & Robertson, E. J. Axis Development and Early Asymmetry in Mammals. 683 Cell 96, 195-209, doi:10.1016/S0092-8674(00)80560-7. 684 4 Stainier, D. Y. R. A glimpse into the molecular entrails of endoderm formation. Genes & 685 Development 16, 893-907, doi:10.1101/gad.974902 (2002). 686 5 Tremblay, K. D. & Zaret, K. S. Distinct populations of endoderm cells converge to generate 687 the embryonic liver bud and ventral foregut tissues. Dev Biol 280, 87-99, 688 doi:10.1016/j.ydbio.2005.01.003 (2005). 689 6 Tam, P. P. L. et al. Sequential allocation and global pattern of movement of the definitive 690 endoderm in the mouse embryo during gastrulation. Development 134, 251-260, 691 doi:10.1242/dev.02724 (2007). 692 7 Zaret, K. S. Genetic programming of liver and pancreas progenitors: lessons for stem-cell 693 differentiation. Nat Rev Genet 9, 329-340 (2008). 694 8 Serls, A. E., Doherty, S., Parvatiyar, P., Wells, J. M. & Deutsch, G. H. Different thresholds of 695 fibroblast growth factors pattern the ventral foregut into liver and lung. Development 132, 696 35-47, doi:10.1242/dev.01570 (2005). 697 9 Wang, Z., Dollé, P., Cardoso, W. V. & Niederreither, K. Retinoic acid regulates morphogenesis 698 and patterning of posterior foregut derivatives. Dev Biol 297, 433-445, 699 doi:https://doi.org/10.1016/j.ydbio.2006.05.019 (2006). 700 10 Rodríguez-Seguel, E. et al. Mutually exclusive signaling signatures define the hepatic and 701 pancreatic progenitor cell lineage divergence. Genes & Development 27, 1932-1946, 702 doi:10.1101/gad.220244.113 (2013). 703 11 Jennings, R. E. et al. Development of the Human Pancreas From Foregut to Endocrine 704 Commitment. Diabetes 62, 3514-3522, doi:10.2337/db12-1479 (2013). 705 12 Madsen, O. D. & Serup, P. Towards cell therapy for diabetes. Nature Biotechnology 24, 1481, 706 doi:10.1038/nbt1206-1481 (2006). 707 13 D'Amour, K. A., Agulnick, A. D., Eliazer, S., Kelly, O. G. & Kroon, E. Efficient differentiation of 708 human embryonic stem cells to definitive endoderm. Nat Biotechnol 23, 709 doi:10.1038/nbt1163 (2005). 710 14 Rezania, A. et al. Reversal of diabetes with insulin-producing cells derived in vitro from 711 human pluripotent stem cells. Nat Biotech 32, 1121-1133, doi:10.1038/nbt.3033 712 http://www.nature.com/nbt/journal/v32/n11/abs/nbt.3033.html#supplementary- 713 information (2014). 714 15 Pagliuca, Felicia W. et al. Generation of Functional Human Pancreatic β Cells In Vitro. Cell 715 159, 428-439, doi:https://doi.org/10.1016/j.cell.2014.09.040 (2014). 716 16 Russ, H. A. et al. Controlled induction of human pancreatic progenitors produces functional 717 beta-like cells in vitro. The EMBO Journal 34, 1759-1772, doi:10.15252/embj.201591058 718 (2015). 719 17 Canham, M. A., Sharov, A. A., Ko, M. S. H. & Brickman, J. M. Functional Heterogeneity of 720 Embryonic Stem Cells Revealed through Translational Amplification of an Early Endodermal 721 Transcript. PLOS Biology 8, e1000379, doi:10.1371/journal.pbio.1000379 (2010). 722 18 Morrison, G. M. et al. Anterior Definitive Endoderm from ESCs Reveals a Role for FGF 723 Signaling. Cell Stem Cell 3, 402-415, doi:https://doi.org/10.1016/j.stem.2008.07.021 (2008).

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724 19 Gadue, P. et al. Generation of Monoclonal Antibodies Specific for Cell Surface Molecules 725 Expressed on Early Mouse Endoderm. STEM CELLS 27, 2103-2113, doi:doi:10.1002/stem.147 726 (2009). 727 20 Holtzinger, A. et al. New markers for tracking endoderm induction and hepatocyte 728 differentiation from human pluripotent stem cells. Development (Cambridge, England) 142, 729 4253-4265, doi:10.1242/dev.121020 (2015). 730 21 Kelly, O. G. et al. Cell-surface markers for the isolation of pancreatic cell types derived from 731 human embryonic stem cells. Nat Biotech 29, 750-756, 732 doi:http://www.nature.com/nbt/journal/v29/n8/abs/nbt.1931.html#supplementary- 733 information (2011). 734 22 Ameri, J. et al. Efficient Generation of Glucose-Responsive Beta Cells from Isolated 735 GP2⁺ Human Pancreatic Progenitors. Cell Reports 19, 36-49, 736 doi:10.1016/j.celrep.2017.03.032. 737 23 Cogger, K. F. et al. Glycoprotein 2 is a specific cell surface marker of human pancreatic 738 progenitors. Nature Communications 8, 331, doi:10.1038/s41467-017-00561-0 (2017). 739 24 Deglincerti, A. et al. Self-organization of the in vitro attached human embryo. Nature 533, 740 251, doi:10.1038/nature17948 741 https://www.nature.com/articles/nature17948#supplementary-information (2016). 742 25 Burtscher, I. & Lickert, H. Foxa2 regulates polarity and epithelialization in the endoderm germ 743 layer of the mouse embryo. Development 136, 1029-1038, doi:10.1242/dev.028415 (2009). 744 26 Hoshino, H., Shioi, G. & Aizawa, S. AVE protein expression and visceral endoderm cell 745 behavior during anterior–posterior axis formation in mouse embryos: Asymmetry in OTX2 746 and DKK1 expression. Dev Biol 402, 175-191, 747 doi:https://doi.org/10.1016/j.ydbio.2015.03.023 (2015). 748 27 Franklin, V. et al. Regionalisation of the endoderm progenitors and morphogenesis of the gut 749 portals of the mouse embryo. Mechanisms of Development 125, 587-600, 750 doi:https://doi.org/10.1016/j.mod.2008.04.001 (2008). 751 28 Cheng, X. et al. Self-Renewing Endodermal Progenitor Lines Generated from Human 752 Pluripotent Stem Cells. Cell stem cell 10, 371-384, doi:10.1016/j.stem.2012.02.024 (2012). 753 29 Stroncek, D. F. Neutrophil-specific antigen HNA-2a, NB1 glycoprotein, and CD177. Current 754 opinion in hematology 14, 688-693, doi:10.1097/MOH.0b013e3282efed9e (2007). 755 30 Hu, H. et al. Noncanonical NF-κB regulates inducible costimulator (ICOS) ligand expression 756 and T follicular helper cell development. Proceedings of the National Academy of Sciences 757 108, 12827-12832, doi:10.1073/pnas.1105774108 (2011). 758 31 Rezania, A. et al. Enrichment of human embryonic stem cell‐derived NKX6.1‐expressing 759 pancreatic progenitor cells accelerates the maturation of insulin‐secreting cells in vivo. STEM 760 CELLS 31, 2432-2442, doi:doi:10.1002/stem.1489 (2013). 761 32 Xu, X., Browning, V. & Odorico, J. Activin, BMP and FGF pathways cooperate to promote 762 endoderm and pancreatic lineage cell differentiation from human embryonic stem cells. 763 Mechanisms of development 128, 412-427, doi:10.1016/j.mod.2011.08.001 (2011). 764 33 Yap, C., Goh, H. N., Familari, M., Rathjen, P. D. & Rathjen, J. The formation of proximal and 765 distal definitive endoderm populations in culture requires p38 MAPK activity. Journal of Cell 766 Science 127, 2204-2216, doi:10.1242/jcs.134502 (2014). 767 34 Piccolo, S. et al. The head inducer Cerberus is a multifunctional antagonist of Nodal, BMP and 768 Wnt signals. Nature 397, 707-710, doi:10.1038/17820 (1999). 769 35 MacDonald, B. T., Tamai, K. & He, X. Wnt/β-catenin signaling: components, mechanisms, and 770 diseases. Developmental cell 17, 9-26, doi:10.1016/j.devcel.2009.06.016 (2009). 771 36 Chen, Y.-F. et al. Rapid Generation of Mature Hepatocyte-Like Cells from Human Induced 772 Pluripotent Stem Cells by an Efficient Three-Step Protocol. Hepatology (Baltimore, Md.) 55, 773 1193-1203, doi:10.1002/hep.24790 (2012). 774 37 Decker, K., Goldman, D. C., Grasch, C. L. & Sussel, L. Gata6 is an important regulator of mouse 775 pancreas development. Dev Biol 298, 415-429, doi:10.1016/j.ydbio.2006.06.046 (2006).

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776 38 Shi, Z.-D. et al. Genome Editing in hPSCs Reveals GATA6 Haploinsufficiency and a Genetic 777 Interaction with GATA4 in Human Pancreatic Development. Cell Stem Cell 20, 675-688.e676, 778 doi:https://doi.org/10.1016/j.stem.2017.01.001 (2017). 779 39 Tiyaboonchai, A. et al. GATA6 Plays an Important Role in the Induction of Human Definitive 780 Endoderm, Development of the Pancreas, and Functionality of Pancreatic 781 β Cells. Stem Cell Reports 8, 589-604, doi:10.1016/j.stemcr.2016.12.026 (2017). 782 40 Chen, B. et al. Small molecule-mediated disruption of Wnt-dependent signaling in tissue 783 regeneration and cancer. Nature chemical biology 5, 100-107, doi:10.1038/nchembio.137 784 (2009). 785 41 Pei, Y. et al. WNT signaling increases proliferation and impairs differentiation of stem cells in 786 the developing cerebellum. Development 139, 1724-1733, doi:10.1242/dev.050104 (2012). 787 42 Bader, E. et al. Identification of proliferative and mature β-cells in the islets of Langerhans. 788 Nature 535, 430-434, doi:10.1038/nature18624 789 http://www.nature.com/nature/journal/v535/n7612/abs/nature18624.html#supplementary 790 -information (2016). 791 43 Johansson, K. A. et al. Temporal Control of Neurogenin3 Activity in Pancreas Progenitors 792 Reveals Competence Windows for the Generation of Different Endocrine Cell Types. 793 Developmental Cell 12, 457-465, doi:https://doi.org/10.1016/j.devcel.2007.02.010 (2007). 794 44 Krentz, N. A. J. et al. Phosphorylation of NEUROG3 Links Endocrine Differentiation to the Cell 795 Cycle in Pancreatic Progenitors. Dev Cell 41, 129-142 e126, doi:10.1016/j.devcel.2017.02.006 796 (2017). 797 45 Roscioni, S. S., Migliorini, A., Gegg, M. & Lickert, H. Impact of islet architecture on [beta]-cell 798 heterogeneity, plasticity and function. Nat Rev Endocrinol 12, 695-709, 799 doi:10.1038/nrendo.2016.147 (2016). 800 46 Vincent, S. D., Dunn, N. R., Hayashi, S., Norris, D. P. & Robertson, E. J. Cell fate decisions 801 within the mouse organizer are governed by graded Nodal signals. Genes & Development 17, 802 1646-1662, doi:10.1101/gad.1100503 (2003). 803 47 Perea-Gomez, A. et al. Nodal Antagonists in the Anterior Visceral Endoderm Prevent the 804 Formation of Multiple Primitive Streaks. Developmental Cell 3, 745-756, 805 doi:https://doi.org/10.1016/S1534-5807(02)00321-0 (2002). 806 48 Robertson, E. J., Norris, D. P., Brennan, J. & Bikoff, E. K. Control of early anterior-posterior 807 patterning in the mouse embryo by TGF-β signalling. Philosophical Transactions of the Royal 808 Society of London. Series B: Biological Sciences 358, 1351-1358, doi:10.1098/rstb.2003.1332 809 (2003). 810 49 Brennan, J. et al. Nodal signalling in the epiblast patterns the early mouse embryo. Nature 811 411, 965doi:10.1038/35082103https://www.nature.com/articles/35082103#supplementary- 812 information (2001). 813 50 Arnold, S. J. & Robertson, E. J. Making a commitment: cell lineage allocation and axis 814 patterning in the early mouse embryo. Nature Reviews Molecular Cell Biology 10, 91, 815 doi:10.1038/nrm2618 (2009). 816 51 Aykul, S., Ni, W., Mutatu, W. & Martinez-Hackert, E. Human Cerberus Prevents Nodal- 817 Receptor Binding, Inhibits Nodal Signaling, and Suppresses Nodal-Mediated Phenotypes. 818 PLOS ONE 10, e0114954, doi:10.1371/journal.pone.0114954 (2015). 819 52 Cortijo, C., Gouzi, M., Tissir, F. & Grapin-Botton, A. Planar Cell Polarity Controls Pancreatic 820 Beta Cell Differentiation and Glucose Homeostasis. Cell Reports 2, 1593-1606, 821 doi:10.1016/j.celrep.2012.10.016. 822 53 Pezzulo, A. A. et al. The air-liquid interface and use of primary cell cultures are important to 823 recapitulate the transcriptional profile of in vivo airway epithelia. American Journal of 824 Physiology - Lung Cellular and Molecular Physiology 300, L25-L31, 825 doi:10.1152/ajplung.00256.2010 (2011).

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826 54 Kim, Y. et al. Islet-like organoids derived from human pluripotent stem cells efficiently 827 function in the glucose responsiveness in vitro and in vivo. 6, 35145, doi:10.1038/srep35145 828 https://www.nature.com/articles/srep35145#supplementary-information (2016). 829 55 Millman, J. R. et al. Generation of stem cell-derived β-cells from patients with type 1 830 diabetes. 7, 11463, doi:10.1038/ncomms11463 831 https://www.nature.com/articles/ncomms11463#supplementary-information (2016). 832 56 Nair, G. G. et al. Recapitulating endocrine cell clustering in culture promotes maturation of 833 human stem-cell-derived β cells. Nature Cell Biology 21, 263-274, doi:10.1038/s41556-018- 834 0271-4 (2019). 835 57 Velazco-Cruz, L. et al. Acquisition of Dynamic Function in Human Stem Cell-Derived β Cells. 836 Stem Cell Reports 12, 351-365, doi:https://doi.org/10.1016/j.stemcr.2018.12.012 (2019). 837 58 Wang, X. et al. Generation of a human induced pluripotent stem cell (iPSC) line from a 838 patient with family history of diabetes carrying a C18R mutation in the PDX1 gene. Stem Cell 839 Research 17, 292-295, doi:https://doi.org/10.1016/j.scr.2016.08.005 (2016). 840 59 Shi, Z.-D. et al. Genome Editing in hPSCs Reveals GATA6 Haploinsufficiency and a 841 Genetic Interaction with GATA4 in Human Pancreatic Development. Cell Stem 842 Cell 20, 675-688.e676, doi:10.1016/j.stem.2017.01.001. 843 60 Heinz, S. et al. Simple Combinations of Lineage-Determining Transcription Factors Prime cis- 844 Regulatory Elements Required for Macrophage and B Cell Identities. Molecular Cell 38, 576- 845 589, doi:https://doi.org/10.1016/j.molcel.2010.05.004 (2010).

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860 Main Figure Legends:

861 Figure 1. Identification of novel CD177+ and CD275+ ADE subpopulations (a) Schematic 862 representation of hESCs differentiation towards DE showing the growth factors and small 863 molecules added. (b-c) Representative FACS plot of CXCR4+/CD117+ cells (b) showing a 864 heterogeneous population and apparent homogenous FOXA2+/SOX17+ (c) DE. (d-e) Gene 865 expression profiles of CXCR4+/CD117-, CXCR4high/CD117high, CXCR4mid/CD117mid and 866 CXCR4low/CD117low cells for FOXA2 and SOX17. (f-g) Gene expression profiles of 867 CXCR4+/CD117-, CXCR4high/CD117high, CXCR4mid/CD117mid and CXCR4low/CD117low cells 868 for CER1 and HHEX (Fig. 1b-g n=3, biological replicates). Mean ±s.e.m, P<0.05 and P<0.01 869 is determined using ordinary one way ANOVA with Bonferroni’s test for multiple analysis. (h) 870 Summary of the antibody screen identifying and isolating CD177+ and CD275+ as novel 871 markers to identify ADE subpopulations. CXCR4 and FOXA2 are used as controls to identify 872 the whole DE. (i) hPSCs and hPSC-derived DE stained for CXCR4, CD177 and CD275 as 873 shown by live cell FACS.

874 Figure 2. Molecular profiling of CD177+, CD275+ and CXCR4+ DE subpopulations reveal 875 distinct signatures (a) Summary of differentiation protocol towards DE/ADE followed by 876 MACS sorting to enrich for CD177 and CD275 subpopulation. CXCR4 represents the non- 877 enriched DE/ADE population. (b) PCA analysis showing mRNA derived transcriptome profiles 878 are characteristic of different DE/ADE subpopulations. (c-e) Bar graphs of selected and 879 significantly enriched gene ontology (GO) terms in CD275+ versus CXCR4+ (c), CD177+ versus 880 CD275+ (d) and CD177+ versus CXCR4+ (e) DE populations. (f-g) Validation of the microarray 881 analysis by real-time qPCR for non-canonical WNT/PCP components and ligands (f) and 882 canonical WNT components and ligands (g) (n=3, biological replicates). Error bar represents 883 ±s.e.m; P<0.05 and P<0.01 is determined using ordinary one way ANOVA with Bonferroni’s 884 test for multiple analysis. Data were normalized to 18S. (h, i) Western blot analysis (h) and 885 quantification (i) of WNT/PCP components such as p-JNK and DVL2 in ADE subpopulations. 886 GAPDH is used as a loading control. (j-k) Nuclear fractionation (j) and quantification (k) of β- 887 CATENIN in cytoplasm (C) and nucleus (N) of enriched ADE subpopulations. (l) 888 Immunofluorescence analysis validated the exclusive localization of β-catenin in the membrane 889 in CD177+ ADE cells and in the cytoplasm and nucleus in CD275+ ADE and CXCR4+ DE cells. 890 FOXA2 is used as a nuclear marker. Scale bars 50 µm and 20 µm in inset.

891 Figure 3. CD177+ ADE efficiently differentiates into PDX1+/NKX6.1+ pancreatic 892 progenitors (a) Summary of pancreatic differentiation protocol after the enrichment of 34

893 CD177+, CD275+ and CXCR4+ at DE stage. (b) mRNA quantification of PDX1 and NKX6.1 in 894 S4 cells generated from enriched subpopulations. Data is represented as ±s.e.m; P<0.05 and 895 P<0.01 is determined using ordinary one-way ANOVA with Bonferroni’s test for multiple 896 analysis. Data were normalized to CXCR4-PP2. GAPDH was used as a control. (c) 897 Immunofluorescence staining of CD177+-, CD275+- and CXCR4+-PP2s for PDX1 and NKX6.1 898 showing most of the CD177-PP2 positive for PDX1/NKX6.1. Scale bars 50 µm. (d) 899 PDX1/NKX6.1 intracellular FACS analysis and quantification (e) of CD177+-, CD275+- and 900 CXCR4+-PP2 showing percentage of PDX1+/NKX6.1+ cells. Data is represented as ±s.e.m; 901 P<0.05 and P<0.01 is determined using ordinary one-way ANOVA with Bonferroni’s test for 902 multiple analysis. Exact P values are mentioned in the figure.

903 Figure 4. Inhibition of canonical WNT secretion promotes pancreatic differentiation (a) 904 Overview of differentiation protocol towards pancreatic progenitors (PP2) where inhibition of 905 WNT secretion is performed at S2 stage in CD177+-, CD275+- and CXCR4+-DE using IWP2. 906 (b-c) FACS quantification (b) and immunocytochemistry (c) for the percentage of cells 907 expressing PDX1+/NKX6.1+ generated from CD177+-, CD275+- and CXCR4+-ADE. Scale 908 bars, 20 µm. (d-g) Protocol for activation of canonical and non-canonical WNT pathway using 909 20 ng/ml WNT3A or 3 µM CHIR and 400 ng/ml of WNT5A at S2 stage. (e-g) Analysis (e) of 910 representative FACS plots (f) and immunofluorescent images (g) for PDX1/NKX6.1 at S4 stage 911 showing activation of canonical WNT pathway hampering PP2 induction. Data in (b,e,i) is 912 represented as ±s.e.m; P<0.05 and P<0.01 is determined using ordinary one-way ANOVA with 913 Bonferroni’s test for multiple analysis. Exact P values are mentioned in the figure. Scale bars, 914 50µm. (h) EdU staining (h) and quantification (i) for EdU+ cells in different ADE subsets 915 revealing the exit of cells from the cell cycle. Scale bars, 80 µm. (j) mRNA analysis of NGN3 916 at S4 and S5 stage in different ADE subpopulations. (n=3, biological replicates). Error bar 917 represents ±s.e.m; P<0.05, P<0.01, two-sided unpaired t-test. Data were normalized to 18S.

918 Figure 5. CD177+- ADE efficiently differentiates into NKX6.1+/INS+ β-like cells (a) 919 Schematic representation of adapted Rezania et al. 2014 protocol for differentiation towards 920 pancreatic β cells. (b, f) Representative immunofluorescent staining for CD177-β-cells, 921 CXCR4-β-cells and unsorted (US-β-cells) for: (b) NKX6.1 (red) and C-peptide (green) and (f) 922 GCG (red), INS (green) and SST (magenta). Nuclear DAPI staining is shown in blue. Scale 923 bars, 20 µm (b) and 50 µm (f). (c, g) Representative FACS plots for CD177-β-cells, CXCR4- 924 β-cells and US-β-cells for expression of INS and NKX6.1 (c) and INS, GCG and SST (g). (d- 925 e) FACS quantification of the cells at S7 stage for the percentage of cells expressing INS,

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926 NKX6.1 and GCG (d) and INS and SST (e). 4 biological independent experiments were used. 927 Data is represented as ±s.e.m; P<0.05 and P<0.01 is determined using ordinary one-way 928 ANOVA with Bonferroni’s test for multiple analysis (d) and two-sided unpaired t-test (e). Exact 929 P values are mentioned in the figure.

930 Figure 6. CD177+- enriched ADE generates more mature β-like cells in vitro (a) Outline of 931 the differentiation protocol. (b) Gene expression profile of β-like cells for maturation markers 932 MAFA and GLUT1. Data are expressed as the fold change relative to US-β-cells. Data is 933 represented as ±s.e.m; P<0.05 and P<0.01 is determined using ordinary one-way ANOVA with 934 Bonferroni’s test for multiple analysis. Exact P values are mentioned in the figure. Data were 935 normalized to 18S. (c, e) Immunohistochemistry for the expression of MAFA (red) and INS 936 (green) and (e) INS (green) and GLUT1 (red) in US-β-cells and CD177-β-cells. DAPI is shown 937 in blue. Insets show higher magnification images. For MAFA, staining was performed on 938 monolayer due to antibody issues in PFA fixed sections. GLUT1 staining was performed on 939 sectioned aggregates. Scale bars, in low magnification images, 50 µm (c) and high 940 magnification images 5 µm (c) and 20 µm (e) and inset 80 µm (e). (d, f) FACS analysis (d) and 941 quantification (f) of cells expressing MAFA and GLUT1 in differentiation at S7. Each point is 942 a biological independent replicate. Data is represented as ±s.e.m; P<0.05 and P<0.01 is 943 determined using non-parametric Student’s t test. Exact P values are mentioned in the figure.

944 Figure 7. Functional characterization of the US-β-cells and CD177-β-cells (a) Images of 945 US-β-cells and CD177-β-cells stained with DTZ (b) Comparison of insulin content in 1000 946 cells between US-β-cells (n=9), CD177-β-cells (n=9) and human islets (n=5). (c) Sequential 947 static GSIS assay comparing the insulin secretion of US-β-cells and CD177-β-cells when 948 subjected to 2.8, 5.6, 11.1, 20 and 2.8 mM glucose stimulations in the interval of 30 minutes 949 (n=4, biological replicates) (d) Insulin secretion in static GSIS on 5 aggregates collected from 950 US-β-cells (n=4; biologically independent experiments) and CD177-β-cells (n=5; biologically 951 independent experiments) in response to multiple challenges with 30 min of 2.8 and 20 mM 952 glucose. (e-g) Insulin secretion in response to dynamic glucose, Ex-4 and KCl challenges in a 953 perifusion system on US-β-cells (f) and CD177-β-cells (n=3, biological replicates) (g) cells in 954 comparison to human islets (n=4, biological replicates) (e). Data is represented as ±s.e.m; 955 P<0.05 and P<0.01 is determined using ordinary one-way ANOVA with Bonferroni’s test for 956 multiple analysis (b) and non-parametric Student’s t test (d).

957

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958 Supplementary Figure legends:

959 Supplementary Fig. 1. Screening strategy for the identification of endoderm 960 subpopulations (a) Screening work flow for the initial screen. (b-d) Representative FACS plots 961 for CD177 and CD275 (b) labelling of differentiated day 4 DE cells with known endoderm 962 markers (FOXA2 and CXCR4) revealed definitive endoderm (FOXA2+/CXCR4+) and mes- 963 endoderm (FOXA2low/CXCR4-) subpopulations (c-d) CD177 and CD275 expression profiles 964 reveal different endoderm subpopulations. (e) Immunofluorescent staining for CER1 (green) 965 with FOXA2 (red) in DE cultures. Scale bar, 50 µm. (f) FACS analysis for CD275+/CER1+ and 966 CD177+/CER1+ ADE cell populations in day 4 DE. (g-h) qPCR quantification for the mRNA 967 expression of FOXA2 and SOX17 (g), CER1 and HHEX (h) in enriched CD177+ and CD275+ 968 ADE subpopulations. Data is represented as ±s.e.m; P<0.05 and P<0.01 is determined using 969 ordinary one-way ANOVA with Bonferroni’s test for multiple analysis.

970 Supplementary Fig. 2. Percentage of CD177+ and CD275+ ADE subpopulations induced 971 in different hESC and hiPSC lines (a-b) Endoderm differentiation scheme from hESCs 972 towards DE/ADE. (b) FACS plots represent the percentage of CXCR4+/CD177+ and 973 CXCR4+/CD275+ subpopulations in hH1, hMEL1-NKX6.1, HMGUi001-A hiPSC, HUES8 974 and H9 at DE/ADE stage. (c) Quantification of flow cytometry data from (b). Each point 975 represents a biologically independent experiment.

976 Supplementary Fig. 3. Induction efficiency of CD177+ and CD275+ ADE shows variation 977 using different protocols (a-c) Adaptation of previously published endoderm differentiation 978 protocols from hESCs. (d) FACS quantification for the percentage of total population 979 expressing CXCR4 in DE cells derived from HMGUi001-A hiPSC using 3 different endoderm 980 induction protocols (n=3 biological replicates). (e) FACS quantification for the percentage of 981 cells expressing CXCR4+/CD177+ and CXCR4+/CD275+ in DE generated using previously 982 published protocols.

983 Supplementary Fig. 4. Differentiation of enriched CD177+ , CD275+ and CXCR4+ ADE 984 subpopulations towards liver and pancreas fate (a) Expression of CD177+-, CD275+-, and 985 CXCR4+ during differentiation of hESCs towards pancreatic β-like cells. (b) Liver 986 differentiation protocol. (c) qPCR quantification of the expression of early liver progenitor 987 markers HHEX, TTR and AFP in enriched ADE subpopulations. Data is represented as ±s.e.m; 988 P<0.05 and P<0.01 is determined using ordinary one-way ANOVA with Bonferroni’s test for 989 multiple analysis. (d) Immunofluorescent staining of pancreatic progenitor cells derived from

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990 enriched ADE subpopulations for the co-expression of posterior foregut marker GATA6 and 991 PDX1. Scale bars, 50µm. e) Immunofluorescent staining of pancreatic progenitor cells derived 992 from enriched ADE subpopulations for the co-expression of lung marker SOX2, intestinal 993 marker CDX2 and PDX1. Scale bars, 50µm.

994 Supplementary Fig. 5. CD177+ ADE positively correlates with PP1 induction (a) Pancreatic 995 induction protocol. (b) FACS analysis of H1, HMGUi001-A hiPSC, HUES8 and MEL1- 996 NKX6.1 for PDX1 at S3 stage. (c) Quantification of CD177+ cells generated at S1 and PDX1+ 997 cells generated at S3 stage showing correlation between CD177 and PDX1 induction. Each 998 point on the graph depicts a biologically independent data set.

999 Supplementary Fig. 6. H1 hESC pancreatic and endocrine differentiations of CD177+ and 1000 US-DE (a) Overview of differentiation protocol used to generate CD177/US-β-cells. (b-e) 1001 Immunostainings for INS and NKX6.1 (b), GCG, INS and SST (c) and C-peptide and GLUT1 1002 (d), INS, MAFA and NKX6.1 (e) in CD177- and US-β-cells. Scale bars, 50 µm. (f) 1003 Representative flow cytometry contour plots of S4 and S7 cells generated from CD177- and 1004 US-ADE/DE cells on H1 line and stained for indicated markers. (g,h) Percentage of cells 1005 expressing indicated markers. Data is represented as ±s.e.m; P<0.05 and P<0.01 is determined 1006 using non-parametric Student’s t test. Exact P values are mentioned in the figure.

1007 Supplementary Fig. 7. Comparison of 2D and 3D culture system on pancreatic 1008 differentiation (a) Overview of differentiation protocol used. (b) Comparison of 1009 PDX1+/NKX6.1+ generated from CD177+- and CXCR4+-ADE in 2D and 3D settings. (c) 1010 Morphology of CD177 and CXCR4-β-cells; DAPI (blue) and E-CAD (green). Scale bars, 20 1011 µm. Graph represents the size of the aggregates in µm. Mean ±s.e.m, P<0.05 determined using 1012 non-parametric Student’s t test. Exact P value is mentioned in the graph.

1013 Supplementary Fig. 8. H1 hESC-derived CD177-ADE generates more functional -like 1014 cells in vitro. (a) Insulin content of US-β-cells and CD177-β-cells (n=10, biological replicates). 1015 (b) Comparison of insulin secretion of US-β-cells and CD177-β-cells in sequential static GSIS 1016 (n= 5, biological replicates). (c,d) Insulin secretion in response to dynamic glucose, Ex-4 and 1017 KCl challenges in a perifusion system on US-β-cells (c) and CD177-β-cells (d) (n=5, biological 1018 replicates). Data is represented as ±s.e.m; P<0.05 and P<0.01 is determined using non- 1019 parametric Student’s t test. Exact P values are mentioned in the figure.

1020

38

1021 Supplementary Table 1: List of antibodies selected for secondary screen

No Antibody Isotype

1 Mouse IgG1-isotype control

2 Mouse IgG2a-isotype control

3 Mouse IgG2b-isotype control

4 Mouse IgM-isotype control

5 Rat IgG2a-isotype control

6 Rat IgG2b- isotype control

7 CD44 Mouse IgG1

8 CD90 Mouse IgG1

9 CD111 Mouse IgG1

10 CD133/1 (AC133) Mouse IgG1

11 CD146 Mouse IgG1

12 CD262 Mouse IgG1

13 CD275 (B7-H2) Mouse IgG1

14 Anti-PTK7 (CCK-4) Mouse IgG2a

15 CD133/2 (293C3) Mouse IgG2b

16 Anti-PSA-NCAM Mouse IgM

17 CD15 Mouse IgM

18 CD49f Rat IgG2a

19 ANTI CX3CR1 Rat IgG2b

20 Anti CCR10 Recombinant human IgG1

21 Anti HLA-DQ Recombinant human IgG1

22 Anti-SSEA1 Recombinant human IgG1

23 Anti- SSEA4 Recombinant human IgG1

24 CD46 Recombinant human IgG1

39

25 CD47 Recombinant human IgG1

26 CD49b Recombinant human IgG1

27 CD51 Recombinant human IgG1

28 CD82 Recombinant human IgG1

29 CD131 Recombinant human IgG1

30 CD138 (44F9) Recombinant human IgG1

31 CD171 (LCAM) Recombinant human IgG1

32 CD177 Recombinant human IgG1

33 CD244 (2B4) Recombinant human IgG1

34 CD270 (HVEM) Recombinant human IgG1

35 CD184 Mouse IgG2a

36 DCIR Recombinant human IgG1

37 CD234 Recombinant human IgG1

38 Anti- LGR5 Rat IgG2b

39 CD166 Recombinant human IgG1

40 CD195 CCR5 Recombinant human IgG1

41 Anti SSEA-5 Mouse IgG1κ

42 Anti-NOTCH1 Recombinant human IgG1

43 CD41a (ITGA2b) Recombinant human IgG1

44 CD49c (ITGA3) Recombinant human IgG1

45 CD140b Recombinant human IgG1

46 CD181 (CXCR1) Mouse IgG2bκ

1022

1023

1024

1025

40

1026 Supplementary Table 2: Stage-wise comparison of pancreatic progenitors and β-like 1027 cells (S3-S7) generated from enriched CD177+ ADE and CXCR4+ ADE vs already 1028 published protocols*.

Bulk differentiati CD177+ CXCR4+ onaccordin Bulk differentiation Stage derived derived g to according to Pagliuca (% of cells from pancreatic pancreatic Rezania et.al., 2014 (as total population) precursors precursors et.al., 2014 published) (as published)

S3: PDX1+ cells >70% >50% >89% >85%

S4: >60% >50% >62% >55% PDX1+/NKX6.1+

S6: C-peptide+/NKX6.1+: INS+/NKX6.1+ >60% >50% >44% >38% GCG+/INS+ >13% >10% >20% GCG+/C-peptide+: >8%

S7: INS+/MAFA+ >30% >20% NA NA INS+/GLUT1+ >30% >20% NA NA

1029

1030 * NA: not available

1031 A direct comparison between GLUT1+/INS+ β-like cells derived from CXCR4+-, CD177+-ADE 1032 compared to already published protocols at S7 stage was not possible as both the protocols did 1033 not check for the expression of GLUT1.

1034

1035

1036

41

1037 Supplementary Table 3: List of primers for qPCR

1038 Primer Sequence/TaqMan id 1039 GAPDH Hs02758991_g1

18S Hs99999901_s1 1040

FOXA2 Hs00232764_m1 1041

SOX17 Hs00751752_s1 1042

CER1 For: CCCATCAAAAGCCATGAAGT 1043 Rev: TTTCCCAAAGCAAAGGTTGT 1044 HHEX For: ACGGTGAACGACTACACGC 1045 Rev: CTTCTCCAGCTCGATGGTCT 1046 CELSR1 Hs00947712_m1 1047 WNT4 Hs01573504_m1 1048 WNT5A Hs01086864_m1

DVL2 Hs00182901_m1 1049

WNT3A Hs00263977_m1 1050

AXIN2 Hs00610344_m1 1051

NGN3 Hs01875204_s1 1052

PDX1 Hs00236830_m1 1053 NKX6.1 Hs01055914_m1 1054 NEUROD1 Hs01922995_s1 1055 MAFA Hs01651425_s1/Hs04186804_s1 1056 GLUT1 Hs00892681_m1 1057 UCN3 Hs00846499_s1 1058 TTR For: ACTTGGCATCTCCCCATTC

Rev:TAGGAGTAGGGGCTCAGCAG 1059

AFP Hs00173490_m1 1060

NKX2.2 Hs00159616_m1 1061

INS Hs02741908_m1 1062

GCG Hs01031536_m1 1063

1064 42

1065 Supplementary Table 4: List of Antibodies for Immunohistochemistry, FACS and 1066 Western blotting

1067 Conjugated antibodies:

Antibody Company Catalogue No Dilution FACS

Miltenyi Biotec 130-098-354 Human CXCR4-PE Miltenyi Biotec 120-010-802 1:40 Human CXCR4-APC

Miltenyi Biotec 130-091-733 Human CD117-APC Miltenyi Biotec 130-091-734 1:40 Human CD117-PE

R and D IC2400G FOXA2 1:10

R and D IC1924A SOX17 1:10

Miltenyi Biotec 120-017-498 Human CD177-APC 1:20

Human CD275-APC Miltenyi Biotec 120-012-112 1:20

BD Pharmingen™ 562161 PE Mouse anti-PDX1 1:40

Alexa Fluor® 647 BD Pharmingen™ 563338 1:40 Mouse anti-Nkx6.1

Alexa Fluor® 647 BD Pharmingen™ 563023 Mouse IgG1 κ Isotype 1:40 Control

1068

1069

43

1070 Unconjugated antibodies:

Antibody Company Catalogue No Dilution FACS Dilution IF

Rabbit FOXA2 Cell signalling 8186 1:1000 1:1000

Goat SOX17 Acris/Novus GT15094 1:1000 1:1000

Goat CER1 R&D Systems AF1075 1:1000 1:1000

Mouse β- BD 610154 1:1000 1:1000 catenin

Guinea pig Thermo PA1-26938 1:100 1:100 INSULIN Schientific

Guinea pig C- Abcam ab30477 1:300 1:300 peptide

Rabbit MAFA Betalogics LP9872 1:100 1:100

Rabbit GLUT1 Thermo Fisher PA1-37782 1:100 1:100

Goat GATA6 R&D Systems AF1700 1:1000 1:1000

Abgent / Bio Mouse SOX2 AM2048 1:1000 1:1000 Cat

Rabbit CDX2 Santa Cruz sc-134468 1:1000 1:1000

Goat PTF1A NCBI AB2153 1:1000 1:1000

Mouse GCG Sigma G2654-.2ML 1:300 1:300

Goat PDX1 R&D Systems AF2419 1:100 1:500

Novus Rabbit NKX6.1 NBP1-49672 1:2000 1:5000 biologicals Goat NKX6.1 AF5857 1:300 1:300 R&D systems

1071

1072 Unconjugated antibodies:

Antibody Company Catalogue No Dilution

Rabbit p-JNK Cell signalling 4668 1:1000

Rabbit DVL2 Cell signalling 3216 1:1000

Mouse β-catenin BD 610154 1:2000

Mouse GAPDH Merck Biosciences CB1001 1:6000

1073 44

Figure 1. Identification of novel CD177+ and CD275+ ADE subpopulations

a) b) c) CXCR4high/ CXCR4mid/ CD117high 80.1% CD117mid 21.3% 15.4% 100 ng/ml AA+ CXCR4low/ 20 ng/ml WNT3A (D1); CD117low 26.6%

100 ng/ml AA (D2-D4) CD117 hESCs DE/ADE FOXA2 D0 D4 CXCR4+/ CD117- 15.3%

CXCR4 SOX17

d) FOXA2 e) SOX17 f) CER1 g) HHEX 80 30 p=0.0325 p=0.0030 2500 p=0.0008 p=0.0278 6 p=0.0037 60 2000 20 1500 4 40 1000 10 2 Gene expression 20 Gene expression Gene expression Gene expression 500

0 0 0 0

low mid high low mid high low mid high low mid high

/CD117 /CD117 /CD117 /CD117 /CD117 /CD117 /CD117/CD117 /CD117 /CD117/CD117/CD117 low mid low mid low mid low mid high high high high CXCR4+/CD117- CXCR4+/CD117- CXCR4+/CD117- CXCR4+/CD117- CXCR4 CXCR4 CXCR4 CXCR4 CXCR4 CXCR4 CXCR4CXCR4 CXCR4 CXCR4 CXCR4CXCR4 h) i) CXCR4 CD177 CD275 0.85 1.86 1.93 CXCR4+/ FOXA2+ CD177+ CXCR4+ hPSC (day 0) CD275+ 330 surface

marker mAbs hESCs DE/ADE DE/ADE 94.2 37.2 19.9 Endoderm (day 4) Figure 2. Molecular profiling of CD177+, CD275+ and CXCR4+ DE subpopulations reveal distinct signatures Selected terms a) CD177+ b) PCA c) CD275 vs CXCR4 Up 20 PPAR signaling pathway S1 CXCR4+ PID_RXR_VDR_Pathway 3d MACS sorting 0 on D4 RA receptors−mediated signaling

hiPSCs DE/ADE PC2 −20 MAPK (JNK) signaling OCT4 FOXA2 CXCR4 Signaling by Retinoic Acid NANOG SOX17 CD275+ −40 CD177 SOX2 AA AA CXCR4 cell development WNT3A CD275 developmental cell growth −25 0 25 PC1 positive regulation of MAPK cascade

−4 −2 0 d) e) log(p value) Selected terms Selected terms CD177 vs CD275 Up CD177 vs CXCR4 Up cell development positive regulation of developmental process positive regulation of TGF-β production positive regulation of TGF-β production cell differentiation regulation of TGF-β production positive regulation of MAPK cascade Signaling events mediated by c−Kit EphrinB−EPHB pathway hallmark TGF-β signaling developmental process Signalling to ERKs positive regulation of MAPK cascade Ras signaling pathway regulation of cell proliferation TGF-β signaling pathway cell morphogenesis involved in differentiation regulation of establishment of planar polarity regulation of cell proliferation regulation of non−canonical Wnt signaling pathway response to transforming growth factor beta Downstream signaling of activated FGFR1 regulation of MAPK cascade PI3K−Akt signaling pathway developmental maturation Rap1 signaling pathway Wnt signaling pathway p38 MAPK signaling pathway cell differentiation −10.0 −7.5 −5.0 −2.5 0 −4 −3 −2 −1 0 log(p value) log(p value) f) g) CELSR1 DVL2 WNT4 WNT5A WNT3A AXIN2 p= 0.0070 3 p= 0.0185 3 p=0.0309 p=0.0015 2.0 p= 0.0059 2.0 p=0.0086 5 4 p=0.0012

4 1.5 3 1.5 2 2 3 p=0.0049 1.0 2 1.0 2 1 1 0.5 1 0.5 1

0 0.0 0 0 0 0.0 Fold change relative to CXCR4-DE Fold change relative to CXCR4-DE Fold change relative to CXCR4-DE Fold change relative to CXCR4-DE Fold change relative to CXCR4-DE Fold change relative to CXCR4-DE E E E E E E E E E E E E E E E E E E -D D D -D D D D D D D D D - -D D D -D D D - 177- 275- CR4 CR4 177- 275- CR4 177- 275- 177- 275- 177- 275- CR4 177- 275- X D D X D D X D D CR4 D D CR4 D D C C C C C C C X X D D X C C C C C C C C C C C non-canonical WNT/PCP genes canonical WNT genes h) i) j) β-CATENIN/FOXA2 4 DVL2

WNT/PCP signalling H

D 3 P A

G 2 / 2 L

CXCR4-DE

V 1 D

0 E E E -D D D

CXCR4-DE CD177-DE CD275-DE CR4 177- 275- X D D C C C 95 kDa DVL2 3 pJNK GAPDH CD177-DE 37 kDa H D

P 2 54 kDa p-JNK 46 kDa 1 NK /G A

37 kDa GAPDH p J 0 CD275-DE E E E -D D D

CR4 177- 275- X D D C C C Figure 3. CD177+ ADE efficiently differentiates into pancreatic progenitors a) d) S1 CD177+ S2 S3 S4 CXCR4+ Isotype CXCR4-PP2 3d MACS Sorting on D4 2d 2d 3d 0.0 1.46 25.2 49.2 CD275, CD177, CXCR4 hESCs DE/ADE CD275+ PGT PP1 PP2 OCT4 FOXA2 FOXA2 FOXA2 FOXA2 NANOG SOX17 HNF1A PDX1 PDX1 SOX2 CXCR4 HNF4A NKX6.1 AA AA FGF7 FGF7 FGF7 WNT3A VitC VitC VitC RA RA TPB TPB SANT-1 SANT-1 97.5 1.04 20.3 5.32 b) LDN LDN PDX1 NKX6.1 2.5 2.5

p= 0.0027 p=0.0005 PDX1 p=0.0286 p=0.0019 CD177-PP2 CD275-PP2 2.0 2.0 25.1 59.8 25.4 22.9

1.5 1.5 3.89 1.0 1.0

0.5 0.5 Fold change relative to CXCR4-PP2 Fold change relative to CXCR4-PP2 0.0 0.0 2 2 12.8 2.31 47.8 3.81 2 2 2 2 P P P P P P P P P P - -P P 177- 275- 177- 275- CR4 D D CR4 NKX6.1 X C C X D D C C C C c) e) PDX1 NKX6.1 DAPI/MERGE FACS analysis 100

p=0.0168 80

CXCR4-PP2 60 29.4 40

20

CD177-PP2 % of PDX1+/NKX6.1+ cells 0 2 2 2 P P P -P P P

CR4 177- 275- X D D C C C

CD275-PP2 Figure 4. Inhibition of canonical WNT secretion promotes pancreatic differentiation

a) S1 CD177+ S2 S3 S4 b) p=0.0036 p=0.0038 CXCR4+ CXCR4-PP2 + 100 p= 0.0001 3d 2d 2d 3d 1 CD177-PP2 MACS Sorting on D4 . 6 80 CD275-PP2

CD275, CD177, CXCR4 X K hESCs DE/ADE CD275+ PGT PP1 PP2

N 60 FOXA2 /

OCT4 FOXA2 FOXA2 FOXA2 +

NANOG SOX17 HNF1A PDX1 PDX1 1 40

SOX2 CXCR4 HNF4A NKX6.1 X AA AA FGF7 FGF7 FGF7 D 20 WNT3A VitC VitC VitC P f

+/- IWP2 RA RA o 0 TPB TPB

% -IWP2 +IWP2 SANT-1 SANT-1 LDN LDN

c) DAPI PDX1 NKX6.1 MERGE h) CXCR4-PP2 CD177-PP2 CD275-PP2

CXCR4-PP2

DAPI / EdU

i) j) 100 NGN3 4000 S4 S5 s l l

CD177-PP2 80 p=0.0023 0.0001 e p=

c 3000 60 + p=0.0029 2000

d U 40 E

f 1000

o 20 Gene expression % CD275-PP2 0 0 2 2 2 P P P EP EP EP -P P P PP2 PP2 PP2 CXCR4 CD177 CD275 177- 275- CR4 D D C X C C d) S1 S2 S3 S4 f) g) NKX6.1 PDX1 DAPI/MERGE

5 Q152.4 44.8Q2 3d 2d 2d 3d 10 52.4 44.8

-IWP2 4 10 PE-A 3 hESCs DE/ADE PGT PP1 PP2 10 OCT4 FOXA2 FOXA2 FOXA2 FOXA2 0 Q4 Q3 3 NANOG SOX17 HNF1A PDX1 PDX1 -10 2.42 0.390.39 3 3 4 5 NKX6.1 -10 0 10 10 10 SOX2 CXCR4 HNF4A Alexa Fluor 488-A 5 Q134.3 62.5Q2 AA AA FGF7 FGF7 FGF7 10 34.3 62.5

WNT3A VitC VitC VitC s4 pdx1 555 nkx61 488_sp p36 - IWP2.fcs +IWP2 4 10 Single Cells +/-IWP2/ RA RA 13170 PE-A 3 +CHIR/ TPB TPB 10

+WNT3A/ SANT-1 SANT-1 0 Q4 Q3 3 +WNT5A LDN LDN -10 3.06 0.130.13

3 3 4 5 -10 0 10 10 10

Alexa Fluor 488-A 5 74.2Q1 17.6Q2 10 74.2 17.6

+WNT3A

s4 pdx1 555 nkx61 488_sp p36 +IWP2.fcs 4 10 Single Cells e) FACS analysis 14982 p=0.0406 PE-A 3 10

0 p=0.0001 PDX1

Q4 Q3 3 s 0.0033 -10 7.82 0.380.38

l 80 p= 3 3 4 5 p=0.0003 p=0.0186 -10 0 10 10 10 Alexa Fluor 488-A 5 Q1 Q2 10 68 12.7 ce l p= 0.0018 68.0 12.7 s4 pdx1 555 nkx61 488_sp p41 +wnt3a.fcs +CHIR + 4 Single Cells 10 18676 1 60 . PE-A 6 3 10 X

0 K

Q4 Q3 3 N -10 17.6 1.59

/ 40 17.6 1.59 3 3 4 5 -10 0 10 10 10 +

Alexa Fluor 488-A 1

5 +WNT5A 10 44,4 46,0 X nkx61 488 pdx1 555_iPSCKS p30 +chir.fcs

D Single Cells 4 20 10 11665 P

3 10 o f

0 % 3 0 -10 9,32 0,27 3 3 4 5 -10 0 10 10 10 2 2 A R A P P 3 I 5 NKX6.1 T H T IW IW C - + N + N W W + + Figure 5. CD177+ ADE efficiently differentiates into β-like cells

S1 CD177+ S2 S3 S4 S5 S6 S7 a) CXCR4+ 2d 3d MACS Sorting on D4 2d 3d 3d 7d 15d

CD177, CXCR4, Unsorted Immature Mature Unsorted hESCs DE/ADE PGT PP1 PP2 EN SC-β SC-β OCT4 FOXA2 FOXA2 FOXA2 FOXA2 FOXA2 INS INS NANOG SOX17 HNF1A PDX1 PDX1 NGN3 PDX1 MAFA SOX2 CXCR4 HNF4A NKX6.1 NKX2.2 NKX6.1 GLUT1 AA AA FGF7 FGF7 FGF7 T3 T3 T3 UCN3 WNT3A VitC VitC VitC Alk5 Inh II Alk5 Inh II Alk5 Inh II IWP2 RA RA RA GS Inh XX N-CYS TPB TPB SANT-1 LDN AXL Inh SANT-1 SANT-1 LDN Heparin TROLOX LDN LDN b) NKX6.1 c) C-peptide DAPI/MERGE Isotype US-β-cells

5 5 10 6.2 0.28 10 0.28 55.0

4 4 10 10 APC-A APC-A 3 3 10 10

0 0 US- β-cells

3 3 -10 93.5 0 -10 23.4 21.4

3 3 4 5 3 3 4 5 -10 0 10 10 10 -10 0 10 10 10 PE-A CXCR4-PE-A β-cells

0.29 1.63 9.24 60.0 INS

96.1 1.95 19.1 11.6 CXCR4- β-cells CD177-β-cells 0.32 1.88 8.13 73.4

CD177- β-cells 95.8 2.04 10.9 7.6 NKX6.1 d) FACS analysis e) FACS analysis 100 100 US-β-cells CXCR4-β-cells CD177-β-cells US-β-cells CD177-β-cells p=0.02 n n o

p=0.03 i o t 80 i t 80 a a pu l pu l 60 60 p o p o l l a a 40 40 o t o t t t o f o f 20 20 % % 0 0 INS+/NKX6.1+ NKX6.1+ INS+/GCG+ INS+ INS+/SST+ INS+ f) INS GCG SST DAPI/MERGE g) US-β-cells CD177-β-cells 43.6 12.21 48.1 14.9

US- β -cells 44.2 0 37.0 0 INS INS GCG GCG

5 5 10 34.4 6.22 10 49.8 4.43

4 4 10 10

3 3 10 10

2 2 10 10

0 0

2 2 -10 58.3 1.08 -10 44.9 0.89 3 4 5 3 4 5 0 10 10 10 0 10 10 10 CD177- β-cells SST SST Figure 6. CD177+ ADE generates more mature β-like cells in vitro a) S1 CD177+ S2 S3 S4 S5 S6 S7 2d 3d MACS Sorting on D4 2d 3d 3d 15d 15d

CD177, Unsorted Unsorted Immature Mature hESCs DE/ADE 3D PGT PP1 PP2 EN SC-β SC-β OCT4 FOXA2 FOXA2 FOXA2 FOXA2 FOXA2 INS INS NANOG SOX17 HNF1A PDX1 PDX1 NGN3 PDX1 MAFA SOX2 CXCR4 HNF4A NKX6.1 NKX2.2 NKX6.1 GLUT1 UCN3 AA AA FGF7 FGF7 FGF7 T3 T3 T3 WNT3A VitC VitC VitC Alk5 Inh II Alk5 Inh II Alk5 Inh II IWP2 RA RA RA GS Inh XX N-CYS TPB TPB SANT-1 LDN AXL Inh SANT-1 SANT-1 LDN Heparin TROLOX LDN LDN b) c) d) MAFA MAFA INS MERGE US-β-cells CD177-β-cells p=0.0002 30.9 24.8 48.3 28.1 p=0.0004 β-cells 25

20 INS 15 10 44.8 0.28 22.5 1.07 5 US- β-cells MAFA 48.1 17.3 33.1 26.5

0

Fold change relative to US- INS

US-β-cells 34.6 0.0 38.2 2.25 human islets

CD177-β-cells CD177- β-cells GLUT1 e) f) GLUT1 GLUT1 INS MERGE FACS analysis p=0.0055 p=0.0310 β-cells 4 US-β-cells CD177-β-cells 100

n p=0.0436 o i

3 t 80 a

US- β-cells 0.0091 2 pu l p=

o 60 p l

1 a t 40 o t f o Fold change relative to US- 0 20 % 0 US-β-cells human islets MAFA+/ GLUT1+/ INS+

CD177-β-cells CD177- β-cells INS+ INS+ Figure 7. CD177+ ADE generates more functional β-like cells in vitro a) b) c) DTZ US-β-cells CD177-β-cells ) p=0.0003 3 s 20 l l e

c p=0.0022 15

100 0 2 ng / ( 10 en t t

Phase contrast US-β-cells n

o 1 c 5 n i l u s n I 0 Fold change C-peptide secretion 0 M M M M M m m m m m .8 .6 .1 0 .8 2 5 1 2 2 1 US-β-cells CD177-β-cells human islets Glucose stimulation CD177-β-cells d) e) Human islets 6 US-β-cells CD177-β-cells

n 2.8 mM 20 mM 20 mM Glu+ 2.8 mM 25 mM KCl o )

i 40000 t A

e Glu Glu 10nM Ex-4 Glu r N ) c p=0.0183 D e M s 4 g 30000 m µ n / i l 8 g . u p 2 ( s n n i

i 20000 l n u mM / i

2 s n i 20 (

n 10000 ang e a h m c u d H l 0 0 F o 2.8 mM 20 mM 2.8 mM 20 mM 0 9 18 27 36 45 54 63 72 81 Time (min) 1st stimulation 2nd stimulation f) US-β-cells g) CD177-β-cells

2.8 mM 20 mM 20 mM Glu+ 2.8 mM 25 mM KCl 2.8 mM 20 mM 20 mM Glu+ 2.8 mM 25 mM KCl 1500 2500 ) ) A Glu Glu 10nM Ex-4 Glu A Glu Glu 10nM Ex-4 Glu N N D D 2000 g g µ µ / 1000 / g g 1500 p p ( ( n n i i l l u u 1000 s 500 s n n i i n n a

a 500 m m u u H 0 H 0 0 9 18 27 36 45 54 63 72 81 0 9 18 27 36 45 54 63 72 81 Time (min) Time (min) Supplementary Fig. 1. Screening strategy for the identification of endoderm subpopulations a) Characterisation Primary Screen Hits selection Secondary Screen of CD177 and CD275 • 30 Abs screened • • 330 Abs against Microarray • 30 Abs selected for their human surface profiling based on their efficiency to • markers Signalling efficiency to detect detect ADE (integrins and requirements DE subpopulations (CER1+) • Differentiation cluster of + + (FOXA2 /CXCR4 ) • Final hits: CD177 differentiation potential & CD275 • markers Ability to produce • Control: CXCR4 β mature -like cells

DEFINITIVE b) ENDODERM c) Gating Strategy (FOXA2 high/CXCR4+) CD177/NB1

SSC-A MES-

ENDODERM FOXA2-488

FSC-A (FOXA2+/CXCR4-) CD177-APC

FOXA2-488

FOXA2-488

FSC-A CXCR4-PE

CXCR4-PE CD177-APC CXCR4-PE FSC-H GATING STRATEGY

CD177-APC MOI-APC d) CD275/ICOSL e) DAPI FOXA2 f)

12.4 48.9 FOXA2-488 CD275-APC CD177

30.3 8.50 FOXA2-488

CER1 MERGE CER1 CXCR4-PE 2.45 24.3

CD275-APC CXCR4-PE CD275

44.5 28.7 CD275-APC CER1 g) h) FOXA2 SOX17 CER1 HHEX 2.5 5 2.5 1.5 p=0.0301 p=0.0138 p=0.0221 p=0.0048 2.0 4 2.0 1.0 1.5 3 1.5

1.0 2 1.0 0.5 0.5 1 0.5

Fold change relative to CXCR4-DE 0.0 Fold change relative to CXCR4-DE 0 Fold change relative to CXCR4-DE 0.0 Fold change relative to CXCR4-DE 0.0

CD177-DE CD275-DE CD177-DE CD275-DE CD177-DE CD275-DE CD177-DECD275-DE CXCR4-DE CXCR4-DE CXCR4-DE CXCR4-DE Supplementary Fig. 2. Percentage of CD177+ and CD275+ ADE subpopulations induced in different hESC and hiPSC lines a) 100 ng/ml AA+ 20 ng/ml WNT3A (D1); FACS analysis:

100 ng/ml AA (D2-D4) CXCR4/CD177 CXCR4/CD275 hESCs DE/ADE D0 D4 b) 1.32 8.53 45.6 51.4 17.8 41.5

H1 hESC

87.4 2.78 1.42 1.59 39.6 1.14

0.0 1.73 62.7 26.0 24.9 53.2

MEL1- NKX6.1 eGFP hESC 94.7 3.59 11.3 0.0 5.75 16.1

1.81 4.73 49.5 37.5 50.6 25.8

HMGUi001-A +

4 hiPSC

R

C X C 92.5 0.94 7.73 4.87 23.3 0.23

0.36 1.62 44.5 52.2 72.2 23.8

HUES8 hESC 97.0 1.03 2.9 0.49 3.8 0.28

1.13 1.78 52.8 39.9 72.8 17.4

H9 hESC 96.2 0.87 7.05 0.22 9.67 0.17

Isotype CD177+ CD275+ c) 80 H1 n o i

t MEL1-NKX6.1

a 60 HMGUi001-A pu l

p o 40 HuES8 l

a H9 o t t 20 o f % 0

177+275+ 177+275+ 177+275+ 177+275+ 177+275+ D D D D D D D D D D /C /C /C /C /C /C /C /C /C /C + + + + + + + + + +

CR4CR4 CR4CR4 CR4CR4 CR4CR4 CR4CR4 X X X X X X X X X X C C C C C C C C C C Supplementary Fig. 3. Induction efficiency of CD177+ and CD275+ ADE shows variation using different protocols a) b)

MCDB131+ 0.5% BSA+ 1x Glutamax MCDB131+ 0.5% BSA+ 1x Glutamax

100 ng/ml AA+ 20 ng/ml WNT3A (D1); 100 ng/ml AA+ 1 µM CHIR99021 (D1); 100 ng/ml AA (D2-D4) 100 ng/ml AA (D2-D3) hiPSCs DE/ADE hiPSCs DE/ADE D0 D4 D0 D4 Adapted from Rezania et al. 2013 Adapted from Rezania et al. 2014 c)

MCDB131+ 0.5% BSA+ 1x Glutamax

100 ng/ml AA+ 3 µM CHIR99021 (D1); 100 ng/ml AA (D2-D3) hiPSCs DE/ADE D0 D4 Adapted from Pagliuca et al. 2014

d) e) H9 (hESC) HMGUi001-A (hiPSC) 100 s s l l

l 80 l e e c c + +

4 60 4 R R C C

X 40 X C C f f o o 20 % %

0

Rezania et al. 2014 al. et Rezania Rezania et al. 2013 al. et Rezania

Rezania et al. 2014 al. et Rezania Rezania et al. 2013 al. et Rezania

Pagliuca et al. 2014 al. et Pagliuca Pagliuca et al. 2014 al. et Pagliuca

H9 (hESC) HMGUi001-A (hiPSC) CXCR4+/CD177+ 50 CXCR4+/CD177+ 50 CXCR4+/CD275+

n CXCR4+/CD275+ n o 40 i

o 40 t i t a a

pu l 30

pu l 30 p o p o l l a 20 a 20 o t t o t t o f 10 o f 10 % %

0 0

Rezania et al. 2014 al. et Rezania

Rezania et al. 2014 al. et Rezania Rezania et al. 2013 al. et Rezania

Rezania et al. 2013 al. et Rezania

Rezania et al. 2014 al. et Rezania

Rezania et al. 2014 al. et Rezania Rezania et al. 2013 al. et Rezania

Rezania et al. 2013 al. et Rezania

Pagliuca et al. 2014 al. et Pagliuca

Pagliuca et al. 2014 al. et Pagliuca

Pagliuca et al. 2014 al. et Pagliuca Pagliuca et al. 2014 al. et Pagliuca Supplementary Fig. 4. Differentiation of enriched CD177+ , CD275+ and CXCR4+ DE subpopulations towards liver fate a) b) Liver progenitor protocol CD177+ 100 CXCR4+ CD275 3d MACS on D4 3d s l l 80 CD177 e

c CXCR4 CD275, CD177, Hepatic lineage commitment + r 60 hESCs DE/ADE CXCR4 FOXA2 e CD275+ k r OCT4 FOXA2 TTR a 40 m NANOG SOX17 AFP f

o SOX2 CXCR4 20 NEAA

% AA WNT3A L-Glutamine 0 HGF DMSO 0 2 4 6 8 0 3 0 D D D D D 1 1 2 β-MER D D D ADE PGT PP1 PP2 EP Immature β cells c) HHEX AFP TTR

P P p=0.0030 P H H H

- - p=0.0027 - 10 40 2.0 p=0.0463 CR 4 CR 4 CR 4

X X 30 X

C 8 C C

o o 20 o 1.5 t t t

e e 10 e

v 6 v v i i i t t t a a a

l l l 1.0 2.0 e e e

r 4 r r 1.5 g e g e g e

n n n 0.5 2 1.0 h a h a h a

c c 0.5 c d d d l 0 l 0.0 l 0.0

F o P P P F o F o P P P P P P H H H -H -H -H H -H -H - - - 7 5 - 7 5 4 7 5 7 7 7 7 R 7 7

CD1 CD2 CD1 CD2 CD1 CD2 CXCR4 CXCR4 CXC d) GATA6 PDX1 MERGE e) PDX1 SOX2 CDX2 MERGE

CXCR4-PP1

CXCR4-PP2

CD177-PP2

CD177-PP1

CD275-PP2

CD275-PP1 Supplementary Fig. 5.CD177+ ADE positively correlates with PP1 induction

a) S1 S2 S3

2d 2d 2d

hESCs DE/ADE PGT PP1 OCT4 FOXA2 FOXA2 FOXA2 NANOG SOX17 HNF1A PDX1 SOX2 AA AA CXCR4 FGF7 HNF4A FGF7 WNT3A VitC VitC RA TPB SANT-1 b) LDN

H1 MEL1-NKX6.1 61.4 43.4 Count

HUES8 H9 55.1 35.1

PDX1 c) HMGUi001-A 100

n H1 o i 40.4 t 80

a MEL1-NKX6.1

pu l 60 HMGUi001-A

p o HuES8 l a 40 H9 o t t

o f 20 % 0

+PP1 +PP1 +PP1 +PP1 +PP1 1 1 1 1 1 177+DEX 177+DEX 177+DEX 177+DEX 177+DEX D D D D D D D D D D P P P PDX1 C P C P C C C Supplementary Fig.6. H1 hESC pancreatic and endocrine differentiations in CD177+ ADE and US-DE

a) S1 CD177+ S2 S3 S4 S5 S6 S7

3d MACS Sorting on D4 2d 2d 3d 3d 15d 15d CD177, Unsorted Unsorted Immature Mature hESCs DE/ADE 3D PGT PP1 PP2 EN SC-β SC-β OCT4 FOXA2 FOXA2 FOXA2 FOXA2 FOXA2 INS INS NANOG SOX17 HNF1A PDX1 PDX1 NGN3 PDX1 MAFA SOX2 CXCR4 HNF4A NKX6.1 NKX2.2 NKX6.1 GLUT1 AA AA FGF7 FGF7 FGF7 T3 T3 T3 UCN3 WNT3A VitC VitC VitC Alk5 Inh II Alk5 Inh II Alk5 Inh II IWP2 RA RA RA GS Inh XX N-CYS TPB TPB SANT-1 LDN AXL Inh SANT-1 SANT-1 LDN Heparin TROLOX LDN LDN

b) c) INS NKX6.1 MERGE GCG INS SST MERGE US- β -cells US- β -cells CD177- β -cells CD177- β -cells

d) C-peptide GLUT1 MERGE e) INS MAFA NKX6.1 MERGE US- β -cells US- β -cells CD177- β -cells CD177- β -cells

f) g) FACS analysis p=0.0211 80 US-β-cells US-β-cells CD177-β-cells US-β-cells CD177-β-cells

n p=0.0125 CD177-β-cells

5 5 o 0.20 46.7 2.66 61.4 10 25,9 16.2 10 28,3 25.2 i t 60 a

4 4 10 10 pu l o p

l 40 3 3 10 10

a

INS INS t

o

NKX6.1 NKX6.1

0 0 t f

3 3 o 20 3.32 49.8 19.8 16.1 -10 54,3 3,56 -10 43,2 3,27

3 3 4 5 3 3 4 5 % -10 0 10 10 10 -10 0 10 10 10 PDX1 PDX1 GLUT1 GLUT1 0

5 5 5 5 10 37.1 41.5 10 37.2 52.0 10 68,6 12,9 10 51,9 26,8 PDX1+/ INS+/ INS+/ NKX6.1+ NKX6.1+ GCG 4 4 4 4 10 10 10 10

3 3

10 10

INS INS INS INS FACS analysis 3 3 10 10 h)

2 2 0 0 US-β-cells CD177-β-cells 10 10 100 0 0 3 3 0.0354 2 2 -10 -10 p= -10 16.6 4.78 -10 8.70 2.11 18,2 0,34 19,9 1,46 n 3 4 5 0 10 10 10 3 4 5 3 3 4 5 3 3 4 5

0 10 10 10 -10 0 10 10 10 -10 0 10 10 10 o i

t 80

NKX6.1 NKX6.1 MAFA MAFA a

pu l p=0.0022 p=0.0084

o 60 5 5 10 10 1.36 7.23 0 16.9 p l

4 4 a 10 10 t 40 o t

3 3 f 10 10

o

GCG GCG 2 2 20 10 10 %

1 1 10 10 0 0 0 10 50.4 41.0 10 18.0 65.1 0 1 2 3 4 5 0 1 2 3 4 5 MAFA+/ GLUT1+/ INS+ 10 10 10 10 10 10 10 10 10 10 10 10 INS INS INS+ INS+ Supplementary Fig. 7. Comparison of 2D and 3D cell culture system on pancreatic differentiation a) b) 2D 3D 2D p=0.086630 +

S1 CD177+ S2 S3 S4 1 p=0.293005 . 60 6 X

3d MACS Sorting on D4 2d 2d 3d K N CXCR4+ /

CD177, CXCR4 +

1 50

hESCs DE/ADE PGT PP1 PP2 X D

OCT4 FOXA2 FOXA2 FOXA2 FOXA2 P

NANOG SOX17 HNF1A PDX1 PDX1 f SOX2 CXCR4 3D HNF4A NKX6.1 o 40 AA AA FGF7 FGF7 FGF7 % WNT3A VitC VitC VitC RA RA 2 2 P P TPB TPB P P + + SANT-1 SANT-1 4 7 LDN LDN R 7 CXC CD1 c) DAPI/E-CAD p= 0.0068 ) 250 m µ ( 200 z e i

s 150 e t

g a 100 CXCR4- β -cells

ggr e 50 a

0 CD177- β -cells

CXCR4-β-cellsCD177-β-cells Supplementary Figure 8. H1 hESC CD177+ ADE generates more functional β-like cells in vitro a) b) 0.0001

p= n

) 15 o i s t l US-β-cells CD177-β-cells 0.0424

l p= e e r 6 c c ) e s M p=0.0204 n m 10 i l 100 0 8 u .

s 4 2 ng / n i ( n i mM / en t t

n 5 20 o 2 ( c ang e h n i l c u d s l n I 0 0 F o US-β-cells CD177-β-cells 2.8 mM 20 mM 2.8 mM 20 mM 1st stimulation 2nd stimulation c) d) US-β-cells CD177-β-cells ) ) 2.8 mM 20 mM 20 mM Glu+ 2.8 mM 25 mM KCl 2.8 mM 20 mM 20 mM Glu+ 2.8 mM 25 mM KCl A A 2000 N N Glu Glu 10 nM Ex-4 Glu Glu Glu 10nM Ex-4 Glu D D g g 1000 µ µ / / 1500 g g p p ( ( n n i i l l 1000 u u 500 s s n n i i n n 500 a a m m u u H H 0 0 0 9 18 27 36 45 54 63 72 81 0 9 18 27 36 45 54 63 72 81 Time (min) Time (min)