Fluorescein-based sensors to purify human α-cells for functional and transcriptomic analyses

  1. Sevim Kahraman
  2. Kimitaka Shibue
  3. Dario F De Jesus
  4. Hyunki Kim
  5. Jiang Hu
  6. Debasish Manna
  7. Bridget Wagner
  8. Amit Choudhary
  9. Rohit N Kulkarni  Is a corresponding author
  1. Islet Cell and Regenerative Biology, Joslin Diabetes Center, United States
  2. Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, United States
  3. Harvard Stem Cell Institute, Harvard Medical School, United States
  4. Chemical Biology and Therapeutics Science Program, Broad Institute of MIT and Harvard, United States
  5. Divisions of Renal Medicine and Engineering, Brigham and Women’s Hospital, United States
5 figures, 1 table and 10 additional files

Figures

Figure 1 with 1 supplement
Isolation of live human pancreatic α-cells after staining with diacetylated Zinpyr1 (DA-ZP1) by fluorescence activated cell sorting (FACS).

(a) Experimental outline. (b) Representative FACS plot showing three cell populations with low, intermediate, or bright fluorescence. The plot represents the data collected from Donor-1 islets. Unstained (left) vs DA-ZP1-treated (right) human islets. Gating strategy and the data collected from the other donors (n=4) are given in Figure 1—figure supplement 1. (c) The DA-ZP1 derived green fluorescence is maintained in the next day of sorting in the sorted islet cells. The cells were plated in Matrigel-coated flat-bottom plates. Scale bar, 100 μm. See also Figure 1—figure supplement 1. (d) Representative images of human islet cells after FACS showing C-peptide (green) and glucagon (red) expressing islet cells. Nuclei were stained with DAPI (blue). Scale bar, 50 μm. (e) Quantification of percentage of CPEP+, GCG+, and other cells (CPEP- GCG-) in each cell population. Data are presented as mean values ± s.e.m. n=3 donors. (f) Heatmap showing expression of genes in different cell subsets. n=3 donors. (g) Comparison of other zinc-based dyes with DA-ZP1 by FACS.

Figure 1—figure supplement 1
Gating strategy for isolation of live human pancreatic α-cells.

(a) Starting cell population was determined by SSC-A/FSC-A gating. Single human islet cells were gated according to FSC-A/FSC-W gating. Treatment of the single cells with diacetylated Zinpyr1 (DA-ZP1) resulted in three cell populations with different fluorescence intensity (low, intermediate, and bright). n=5 human islet donors. Donor information is given in Supplementary file 9. (b) Number of live cells collected by fluorescence activated cell sorting (FACS) using 15,000 islet equivalent determined by trypan blue staining. (c) The DA-ZP1 derived green fluorescence is maintained in the next day of sorting in the sorted islet cells. Scale bar, 100 μm.

Figure 1—figure supplement 1—source data 1

Number of live cells collected by FACS using 15,000 islet equivalents (IEQs) determined by trypan blue staining.

https://cdn.elifesciences.org/articles/85056/elife-85056-fig1-figsupp1-data1-v3.xlsx
Figure 2 with 1 supplement
α-Pseudoislets are viable and able to proliferate in vitro post-sorting.

(a) The single islet cells were seeded in round-bottom wells (1k cells per well) after sorting to allow re-aggregation. (b, c) Bright-field images of intermediate (sorted α-cells) (b) and unsorted pseudoislets (c) post-sorting. 1k (top panel) or 2k (bottom panel) single cells were seeded per well. Scale bar, 100 μm. See also Figure 2—figure supplement 1. (d) Cell viability was quantified by luminescence reflecting intracellular ATP levels on days 5 and 10 following fluorescence activated cell sorting (FACS). Fold-change relative to blank control. n=7–9 replicates using islet cells from two donors. (e) Representative immunostaining images of α-pseudoislets, unsorted pseudoislets, and native islets on days 5 and day 10 showing INS (red), GCG (green). Nuclei stained with DAPI are blue. For top and bottom images, scale bar, 100 μm. (f) Percentage of INS+, GCG+, and other (INS-GCG-) islet cells. n=3 donors. (g) Representative immunostaining images of α-pseudoislets, unsorted pseudoislets, and native islets on day 5 and day 10 showing GCG (red), TUNEL (green). Nuclei stained with DAPI are blue. Scale bar, 100 μm. Boxes show apoptotic α-cells. (h) Percentage of TUNEL+GCG+ cells. n=3 donors. (i) Representative immunostaining images of α-pseudoislets, unsorted pseudoislets, and native islets on day 5 and day 10 showing GCG (red), Ki67 (green). Nuclei stained with DAPI are blue. Scale bar, 50 μm. Boxes show proliferating α-cells. (j) Percentage of Ki67+GCG+ cells. n=3 donors. Data are presented as mean values ± s.e.m (b–j). n=3 donors. Two-way ANOVA followed by Sidak’s multiple comparison test (d, h, j).

Figure 2—figure supplement 1
α-Pseudoislets tended to form tighter clusters.

Bright-field images of α-pseudoislets (a) and unsorted pseudoislets (b) 5 days post-sorting. 1k (top panel) or 2k (bottom panel) single cells were seeded per well. Scale bar, 100 μm. n=3 biological replicates using islet cells from a single donor (a, b).

Glucagon secretion in response to glucose challenge.

(a) α-Pseudoislets, unsorted pseudoislets, or native islets were preincubated in Krebs-Ringer bicarbonate (KRB) buffer with 16.7 mM glucose followed by the incubation in KRB buffer with 3.3 mM glucose and 16.7 mM glucose on day 5 post-sorting. (b) Glucagon secretion in response to glucose challenge (3.3 mM vs 16.7 mM). One-tailed Student’s t-test. (c) Ratio of glucagon released by each groups of cells at 16.7 mM glucose versus that at 3.3 mM glucose. (d) Glucagon content measured in each well containing ~8000 cells (eight α-pseudoislets, eight unsorted pseudoislets, and eight native islets). Data are presented as mean values ± s.e.m. (b–d). n=5 replicates using islet cells from two donors (b–d). One-way ANOVA corrected for Tukey applied to (c, d).

Figure 4 with 1 supplement
Changes in gene expression levels driven by dissociation and re-aggregation of human islet cells.

(a) Heatmap showing expression levels of α-cell enriched and β-cell enriched genes in α-pseudoislets, unsorted pseudoislets, and native islets on days 0, 5, and 10. Asterisks show genes associated with α-cell identity and function (GCG, ARX, IRX2, TTR). (b) Pie charts showing percentage of α-cell enriched (top panel) and β-cell enriched (bottom panel) genes that alter in α-pseudoislets, unsorted pseudoislets, and native islets on day 5 or day 10 compared to day 0. See also Figure 4—figure supplement 1. (c) Transcriptome of unsorted pseudoislets was compared with native islets on days 0, 5, 10. Venn diagram shows number of differentially expressed genes (DEGs) between unsorted pseudoislets and native islets on different days. (d–f) Volcano plots showing genes downregulated (blue) or upregulated (orange) significantly (FC < –2 or FC > 2, respectively, FDR < 0.1) on day 0 (d), day 5 (e), and day 10 (f). Gray shows non-significant genes with FDR > 0.1 and –2 < FC < 2. (g) Top 10 pathways downregulated in unsorted pseudoislets on day 5 and day 10 compared to native islets. n=4 donors; α-pseudoislets d0, d5, d10, unsorted pseudoislets d5, native islets d5, d10, and n=3 donors; unsorted pseudoislets d0, d10, native islets d0 (a–g).

Figure 4—figure supplement 1
Changes in expression levels of α-cell enriched and β-cell enriched genes in α-pseudoislets, unsorted pseudoislets, and native islets on days 0, 5, 10.

Pie charts show percentage of genes altered on day 5 or 10 compared to day 0 (FDR < 0.1; FC > 2 upregulated or FC < –2 downregulated). n=4; α-pseudoislets d0, d5, d10, unsorted pseudoislets d5, native islets d5, d10, and n=3; unsorted pseudoislets d0, d10, native islets d0.

Time-dependent changes in transcriptome of α-pseudoislets.

(a) Venn diagram shows number of genes that progressively up- or downregulated in α-pseudoislets, unsorted pseudoislets, and native islets in culture over the period from day 0 to day 5 to day 10. (b, c) Pathway analysis showing altered pathways in α-pseudoislets or in unsorted pseudoislets except native islets (b), and altered pathways only in α-pseudoislets with time (c). (d) Heatmap showing expression levels of genes significantly change with time only in α-pseudoislets. n=4 donors; α-pseudoislets d0, d5, d10, unsorted pseudoislets d5, native islets d5, d10, and n=3 donors; unsorted pseudoislets d0, d10, native islets d0 (a–d). (e) Representative immunostaining images of α-pseudoislets on day 0, 5, and 10 showing GCG (red), DLK1, GSN, and SMIM24 (green). Nuclei stained with DAPI are blue. Scale bar, 50 μm. (f) Expression level of each protein in α-pseudoislets on days 0, 5, 10. Data are presented as mean values ± s.e.m. Two-way ANOVA followed by Dunnett’s multiple comparison test compared to d0. n=3 donors (e, f).

Tables

Key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
AntibodyAnti-C-peptide (Rat monoclonal)Developmental Studies Hybridoma BankCat# GN-ID4, RRID: AB_2255626IF (1:200)
AntibodyAnti-Ki67 (Mouse monoclonal)BD BiosciencesCat# BD550609, RRID: AB_393778IF (1:100)
AntibodyAnti-Insulin (Guinea Pig polyclonal)AbcamCat# ab7842, RRID: AB_306130IF (1:400)
AntibodyAnti-Glucagon (Mouse monoclonal)MilliporeSigmaCat# G2654, RRID: AB_259852IF (1:10,000)
AntibodyAnti-Glucagon (Rabbit monoclonal)AbcamCat# ab92517, RRID: AB_10561971IF (1:5000)
AntibodyAnti-DLK1 (Rabbit polyclonal)AbcamCat# ab21682, RRID: AB_731965IF (1:1000)
AntibodyAnti-GSN (Rabbit polyclonal)MilliporeSigmaCat# HPA054026, RRID: AB_2682347IF (1:50)
AntibodyAnti-SMIM24 (Rabbit polyclonal)MilliporeSigmaCat# HPA045046, RRID: AB_10964444IF (1:50)
AntibodyAnti-Guinea Pig AF594 (Donkey polyclonal)Jackson ImmunoResearchCat# 706-586-148, RRID: AB_2340475IF (1:400)
AntibodyAnti-Rat AF488 (Donkey polyclonal)Jackson ImmunoResearchCat# 712-546-153, RRID: AB_2340686IF (1:400)
AntibodyAnti-Mouse AF594 (Donkey polyclonal)Jackson ImmunoResearchCat# 715-586-150, RRID: AB_2340857IF (1:400)
AntibodyAnti-Mouse AF488 (Donkey polyclonal)Jackson ImmunoResearchCat# 715-545-150, RRID: AB_2340846IF (1:400)
AntibodyAnti-Rabbit AF594 (Donkey polyclonal)Jackson ImmunoResearchCat# 711-586-152, RRID: AB_2340622IF (1:400)
AntibodyAnti-Rabbit AF488 (Donkey polyclonal)Jackson ImmunoResearchCat# 711-545-152, RRID: AB_2313584IF (1:400)
Biological sample (Homo sapiens)Primary human pancreatic isletsIntegrated Islet Distribution Program (IIDP), Prodo Laboratories Inc, ADI Islet Corehttp://iidp.coh.org; RRID: SCR_014387, https://prodolabs.com/Freshly isolated
Chemical compoundDA-ZP1Laboratory of Amit ChoudharyBroad Institute of MIT and Harvard
Chemical compoundZIGIRLaboratory of Wen-hong LiUniversity of Texas, Dallas
Chemical compoundNPGThermoN7991
OtherDAPI, dilactateSigmaD9564IF (1:6600)
OtherMiami Media #1ACellgro98-021-CVIslet cell culture
OtherTrypLEThermo Fisher Scientific12604-013Islet cell dissociation
OtherFBSThermo Fisher Scientific10437028Islet cell dissociation
OtherDPBSThermo Fisher Scientific14190250Islet cell dissociation
OtherD-GlucoseSigma-AldrichG8769Glucagon secretion assay
OtherFFA-BSASigma-Aldrich3117057001Glucagon secretion assay
OtherDMSOSigma-AldrichD2650-100FACS
OtherPenicillin-streptomycinCorning30-002-ClIslet cell culture
Other4% PFAWako163-20145Embedding islets in agar
OtherAntibody diluentAbcamAb64211IF
OtherLow melting agaroseScientific Laboratory SuppliesNAT1030Embedding islets in agar
OtherTRIzol reagentInvitrogen15596026RNA isolation
Commercial assay or kitGlucagon ELISA kitMercodia10-1271-01
Commercial assay or kitMycoAlert Mycoplasma Test KitLonzaLT07-318
Commercial assay or kitCellTiter-Glo Luminescent Cell Viability Assay KitPromegaG7570
Commercial assay or kitApopTag Peroxidase In Situ Apoptosis Detection KitMilliporeSigmaS7100: RRID:AB_2661855
Commercial assay or kitQIAGEN RNeasy micro kitQIAGEN74004
Software, algorithmPrism v.7.0GraphPad Softwarehttp://www.graphpad.com; RRID: SCR_002798
Software, algorithmFlowjo-v10FlowJo Softwarehttp://www.flowjo.com; RRID: SCR_008520
Software, algorithmImageJImageJ Softwarehttps://imagej.net: RRID:SCR_003070
Software, algorithmR version 4.1.0R Softwarehttps://www.r-project.org/

Additional files

Supplementary file 1

Single-cell RNA-sequencing (scRNA-seq) analysis of GSE84133 dataset revealed genes that are differentially expressed between islet α-cells and β-cells.

https://cdn.elifesciences.org/articles/85056/elife-85056-supp1-v3.xlsx
Supplementary file 2

Changes in expression levels of α-cell enriched and β-cell enriched genes in sorted α-cells on day 0.

https://cdn.elifesciences.org/articles/85056/elife-85056-supp2-v3.xlsx
Supplementary file 3

Changes in expression levels of α-cell enriched and β-cell enriched genes in α-pseudoislets, unsorted pseudoislets, and native islets on day 5 and day 10 vs day 0.

https://cdn.elifesciences.org/articles/85056/elife-85056-supp3-v3.xlsx
Supplementary file 4

Differentially expressed genes between unsorted pseudoislets versus native islets with fold change >2 and <–2 (log2 FC >1 and <–1) and false discovery rate (FDR)<0.1.

https://cdn.elifesciences.org/articles/85056/elife-85056-supp4-v3.xlsx
Supplementary file 5

Pathway analysis of commonly downregulated genes on days 5 and 10 in the unsorted pseudoislets compared to native islets.

https://cdn.elifesciences.org/articles/85056/elife-85056-supp5-v3.xlsx
Supplementary file 6

Progressively up- or downregulated genes over the period from day 0 to day 10.

https://cdn.elifesciences.org/articles/85056/elife-85056-supp6-v3.xlsx
Supplementary file 7

Altered pathways in α-pseudoislets and unsorted pseudoislets except native islets with time.

https://cdn.elifesciences.org/articles/85056/elife-85056-supp7-v3.xlsx
Supplementary file 8

Altered pathways exclusively in α-pseudoislets with time.

https://cdn.elifesciences.org/articles/85056/elife-85056-supp8-v3.xlsx
Supplementary file 9

Donor information.

https://cdn.elifesciences.org/articles/85056/elife-85056-supp9-v3.xlsx
MDAR checklist
https://cdn.elifesciences.org/articles/85056/elife-85056-mdarchecklist1-v3.docx

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  1. Sevim Kahraman
  2. Kimitaka Shibue
  3. Dario F De Jesus
  4. Hyunki Kim
  5. Jiang Hu
  6. Debasish Manna
  7. Bridget Wagner
  8. Amit Choudhary
  9. Rohit N Kulkarni
(2023)
Fluorescein-based sensors to purify human α-cells for functional and transcriptomic analyses
eLife 12:e85056.
https://doi.org/10.7554/eLife.85056