Single-cell Transcriptomic Analyses of Mouse Pancreatic Endocrine Cells

* These authors contributed equally
Developmental Biology

Your institution must subscribe to JoVE's Developmental Biology section to access this content.

Fill out the form below to receive a free trial or learn more about access:

 

Summary

We describe a method for the isolation of endocrine cells from embryonic, neonatal and postnatal pancreases followed by single-cell RNA sequencing. This method allows analyses of pancreatic endocrine lineage development, cell heterogeneity and transcriptomic dynamics.

Cite this Article

Copy Citation | Download Citations

Li, L. C., Yu, X. X., Zhang, Y. W., Feng, Y., Qiu, W. L., Xu, C. R. Single-cell Transcriptomic Analyses of Mouse Pancreatic Endocrine Cells. J. Vis. Exp. (139), e58000, doi:10.3791/58000 (2018).

Abstract

Pancreatic endocrine cells, which are clustered in islets, regulate blood glucose stability and energy metabolism. The distinct cell types in islets, including insulin-secreting β cells, are differentiated from common endocrine progenitors during the embryonic stage. Immature endocrine cells expand via cell proliferation and mature during a long postnatal developmental period. However, the mechanisms underlying these processes are not clearly defined. Single-cell RNA-sequencing is a promising approach for the characterization of distinct cell populations and tracing cell lineage differentiation pathways. Here, we describe a method for the single-cell RNA-sequencing of isolated pancreatic β cells from embryonic, neonatal and postnatal pancreases.

Introduction

The pancreas is a vital metabolic organ in mammals. The pancreas is comprised of endocrine and exocrine compartments. Pancreatic endocrine cells, including insulin-producing β cells and glucagon-producing α cells, cluster together in the islets of Langerhans and coordinately regulate systemic glucose homeostasis. Dysfunction of the endocrine cells results in diabetes mellitus, which has become a major public health issue worldwide.

Pancreatic endocrine cells are derived from Ngn3+ progenitors during embryogenesis1. Later, during the perinatal period, the endocrine cells proliferate to form immature islets. These immature cells continue to develop and gradually become mature islets, which become richly vascularized to regulate blood glucose homeostasis in adults2.

Although a group of transcriptional factors has been identified that regulate β cell differentiation, the precise maturation pathway of β cells is still unclear. Moreover, the β cell maturation process also involves the regulation of cell number expansion3,4 and the generation of cellular heterogeneity5,6. However, the regulatory mechanisms of these processes have not been well studied.

Single-cell RNA-sequencing is a powerful approach that can profile cell subpopulations and trace cell lineage developmental pathways7. Taking advantage of this technology, the key events that occur during pancreatic islet development can be deciphered at the single-cell level8. Among the single-cell RNA-sequencing protocols, Smart-seq2 allows the generation of full-length cDNA with improved sensitivity and accuracy, and the use of standard reagents at lower cost9. Smart-seq2 takes approximately two days to construct a cDNA library for sequencing10.

Here, we propose a method for the isolation of fluorescence-labeled β cells from the pancreases of fetal to adult Ins1-RFP transgenic mice11, using fluorescence-activated cell sorting (FACS), and the performance of transcriptomic analyses at the single-cell level, using Smart-seq2 technology (Figure 1).This protocol can be extended to analyze the transcriptomes of all pancreatic endocrine cell types in normal, pathological and aging states.

Subscription Required. Please recommend JoVE to your librarian.

Protocol

All methods described here have been approved by the Institutional Animal Care and Use Committee (IACUC) of Peking University.

1. Pancreas Isolation

  1. For E17.5 (embryonic day 17.5) embryos:
    1. Estimate embryonic day 0.5 based on the time point when the vaginal plug appears.
    2. Sacrifice the pregnant mice by CO2 administration. Spray the abdominal fur with 70% alcohol.
    3. Make a V-shaped incision with scissors from the genital area extending to the ribs. This process will completely open the abdominal cavity.
    4. Dissect the uterus out of the abdominal cavity and place it in a 10 cm dish containing cold PBS.
    5. Dissect the embryos from the uterus with thin-tipped forceps under a stereomicroscope, removing other tissues, such as the placenta and umbilical cord. Place all embryos in a 10 cm dish containing cold PBS.
    6. Tear open the embryos’ abdominal cavity and dig out the visceral tissue with elbow tweezers. Transfer the visceral tissue into a 6 cm black-bottom dish containing cold PBS.
    7. The pancreas is located in the upper left part of the abdomen and attaches to the stomach, spleen and duodenum (yellow dotted line in Figure 2A)12. Detach the pancreases from the visceral tissue using forceps and pool the pancreatic tissue together into a 20 mL vial containing 5 mL of 0.5 mg/mL cold collagenase solution: 0.5 mg/mL collagenase P in isolation buffer (HBSS containing 10 mM HEPES, 1 mM MgCl2, 5 mM Glucose, pH 7.4).
  2. For P0-P15 (postnatal day 0-15) mice:
    1. Sacrifice and fix the mouse by adhering the limbs to a piece of benchtop protector with tape. Spray the abdominal fur with 70% alcohol.
    2. Completely open the abdominal cavity as described in step 1.1.3. Pull the bowel out and to the left side of the mouse. This procedure will expose the duodenal, gastric, and splenic lobes of the pancreas. Carefully dissect all lobes of the pancreas (Figure 2B)12 and pool the pancreatic tissue together into a 20 mL vial containing 5 mL of 0.5 mg/mL cold collagenase solution.
  3. For P18-P60 (postnatal day 18-60) mice:
    1. Prepare the collagenase solution. Keep on ice until ready for use.
    2. Sacrifice the mouse and open the abdominal cavity as mentioned above (step 1.1.2 and 1.1.3).
      NOTE: Do not hurt the liver, any wound to the liver will reduce the flow pressure into the bile duct and reduce the perfusion efficiency of the following step.
    3. Remove the xiphoid. Pull the bowel out and to the right side of the mouse, and push the left and right medial lobes of the liver to each side to expose the gallbladder (white arrow in Figure 2C) and the common bile duct.
    4. Clamp the duodenum with a pair of small vessel clamps at the upper and lower position, flanking the site where the bile duct enters the duodenum (Figure 2D).
      NOTE: Do not clamp the gastric or splenic lobes of the pancreas. The collagenase solution will not flow into the gastric and splenic lobe of the pancreas in the next step if clamped.
    5. Fill a syringe with 5 mL of 0.5 mg/mL cold collagenase solution and insert a 30 G needle into the gallbladder. Carefully and smoothly, manipulate the needle through the common bile duct.
    6. Perfuse the pancreas by injecting 1–5 mL of 0.5 mg/mL cold collagenase solution, depending on the size of the mouse. The injection should be slow and constant to prevent the needle from slipping out of the duct and to prevent the intestine from bursting under high liquid pressure. The injection is complete when the pancreas is fully expanded.
    7. Dissect the pancreas (The yellow dotted line in Figure 2D) out of the abdominal cavity using forceps immediately after perfusion. Place the tissue in a 20 mL vial containing 5 mL of 0.5 mg/mL cold collagenase solution. If manipulating more than one mouse at a time, perfuse the mice one by one and pool the tissues into cold collagenase solution in a 20 mL vial until all mice have been dissected.

2. Collagenase Digestion and Islet Isolation

  1. Place the 20 mL vial containing the pancreatic tissue into a 37 °C water bath and incubate for 3 min to equilibrate the temperature.
  2. Gently shake the tube for another 3 to 5 min. If the pancreatic tissue is fully inflated, it will gradually dissociate into small tissue pieces until it is finally dispersed uniformly. The digestion time varies depending on the pancreas size and the perfusion efficiency.
  3. Filter the digested product through a 0.25 mm nylon strainer into a new 50 mL centrifuge tube. Throughly wash the strainer using a 20 mL syringe containing ice-cold PBS.
  4. For E17.5-P15 pancreases, skip to step 3.1.
  5. For P18-P60 pancreases, centrifuge at 200 x g for 1 min and discard the supernatant. Re-suspend the tissue with cold PBS.
  6. Pour 5 mL of the tissue suspension into a 6 cm black-bottom dish. The pancreatic islets are small, compact, milky white structures and acinar tissue is loose and translucent white. Pick islets with a 200 μL pipette and transfer them into a 1.5 mL tube containing a small amount of cold PBS.

3. Trypsin Digestion of Pancreatic Tissue or Islets

  1. Centrifuge the tube containing pancreatic tissue or islets at 200 x g for 1 min at 4 °C and discard the supernatant without disturbing the pellet.
  2. Re-suspend the pellet with 0.25% trypsin-EDTA and incubate in a 37 °C water bath. After 4 min of incubation, gently and occasionally aspirate (pipette) for 1 min using 200 μL tips.
    NOTE: For E17.5-P3 pancreases, add 1 mL trypsin-EDTA. For P4-P15 pancreases, add 3 mL trypsin-EDTA. For 100-300 islets, add 1 mL trypsin-EDTA. Adjust the volume of trypsin-EDTA according to the amount of tissue.
  3. Stop the digestion by adding 0.4x volume of cold fetal bovine serum (FBS) and mix by gentle vortex.
  4. Centrifuge at 250 x g for 3 min at 4 °C. Discard the supernatant without disturbing the pellet.
  5. Re-suspend the cells with 200 μL cold FACS buffer (HBSS containing 1% FBS, pH 7.4). Transfer cells to a 5 mL FACS tube.
  6. Quickly spin the FACS tube to allow the cell suspension to pass through the filter to remove undigested large tissue debris. The single cell suspension in the tube is now ready for FACS sorting.

4. Single-cell Lysis

  1. Prepare cell lysis buffer.
    NOTE: Perform all experiments under a UV-sterilized hood with laminar flow. All tubes, plates and pipette tips should be RNase-/DNase-free. Decontaminate the hood and pipettes with RNase away solution before use.
    1. Thaw the reagents on ice: dNTP (10 mM), oligo-dT primer (10 μM), and ERCC stock solution (1:20).
    2. Dilute the ERCC to 1:5 x 105 with nuclease-free water.
    3. Calculate the volume of cell lysis buffer needed. Add 0.1 μL of RNase inhibitor (40 U/μL), 1.9 μL of 0.2% (vol/vol) Triton X-100, 1 μL of dNTP, 1 μL of oligo-dT primer, and 0.05 μL of diluted ERCC to a final volume of 4.05 μL for each cell.
    4. Aliquot the cell lysis buffer into 0.2 mL thin-wall 8-stripe PCR tubes or 96-well plates. Centrifuge the tubes or plates for 30 s at 4 °C.
      Note: Centrifuge 0.2 mL thin-wall 8-stripe PCR tubes at 7500 x g and 96-well plates at 800 x g in the following steps.
  2. Single-cell picking and lysis.
    1. Manually pick FACS sorted Ins1-RFP+ single cells in FACS buffer into 8-strip PCR tubes using a 30–40 µm capillary pipette, or directly sort Ins1-RFP+ single cells into 96-well plates. The volume containing a single cell is considered to be less than 0.3 μL.
      Note: Use forward scatter height (FSC-H) vs forward scatter area (FSC-A) gating strategy for doublet discrimination, FSC-H vs side scatter area (SSC-A) for debris and fluorescence gating for Ins1-RFP+ cell (Figure 3A-3C) sorting. For the picking method, sort the target cells into a 1.5 mL tube containing 300 μL FACS buffer. The appropriate final concentration is 5–10 cells/μL. Adjust the buffer volume accordingly. For the plate collection method, sort a single-cell into each well of a 96-well plate following the manual of instrument.7,13
    2. Vortex the tubes or plates to lyse the cells and release the RNA. Centrifuge the tubes or plates for 30 s at 4 °C and immediately place them on ice.
      Note: The cells can be stored at -80 °C for one week.

5. Single-cell cDNA Amplification

  1. Reverse transcription (RT).
    1. Thaw the RT reagents (Table 1) on ice.
    2. Incubate the samples at 72 °C for 3 min and immediately put the tubes or plates on ice for at least 1 min. Briefly centrifuge the tubes or plates for 30 s at 4 °C.
      Note: Use a thermal cycler with a 105 °C heated lid for all incubations.
    3. Prepare the RT mix for all reactions, as described in Table 1.
    4. Dispense 5.7 μL of RT mix to each sample to bring the volume to a total of 10 μL. Gently vortex the mix and centrifuge for 30 s at 4 °C.
    5. Place the samples into a thermal cycler and start the RT program as follows: 42 °C for 90 min, 10 cycles (50 °C for 2 min, 42 °C for 2 min), 70 °C for 15 min and hold at 4 °C.
  2. PCR pre-amplification.
    1. Thaw the PCR reagents (Table 2) on ice.
    2. Prepare the PCR mix for all reactions, as described in Table 2.
    3. Dispense 15 μL of PCR mix to each sample, which contains the first-strand reactions. Gently vortex the mix and centrifuge for 30 s at 4 °C.
    4. Place the samples into a thermal cycler and start the following PCR program: 98 °C for 3 min, 18 cycles (98 °C for 20 s, 67 °C for 15 s, 72 °C for 6 min), 72 °C for 5 min and hold at 4 °C.
      NOTE: The PCR product can be stored at 4 °C for less than one week or at -20 °C / -80 °C for up to 6 months.
  3. PCR purification.
    1. Add 25 μL of re-suspended DNA purification beads (1x) to each sample from the previous step and mix well by vortex. Then, quickly spin the tube or plates at room temperature to collect the liquid but avoid the settlement of beads.
      NOTE: Equilibrate DNA purification beads to room temperature for 15 min and vortex thoroughly before use.
    2. Incubate for 5 min at room temperature.
    3. Place the tube or plate on an appropriate magnetic stand until the solution is clear, then carefully remove and discard the supernatant.
    4. Add 200 μL of freshly prepared 80% ethanol to wash the beads while in the magnetic stand, incubate for 30 s, then carefully remove and discard the ethanol solution.
      NOTE: The 80% (vol/vol) ethanol solution should be freshly prepared each time.
    5. Repeat step 5.3.4 for a total of two washes.
    6. Carefully remove and discard the remaining ethanol solution and air dry the beads while the tube or plate is on the magnetic stand.
      NOTE: Avoid over-drying the beads to ensure the maximum elution efficiency.
    7. Add 11 μL of nuclease-free water to elute the DNA target from the beads and mix well by vortex. Then, quickly spin the tube or plate and place it on a magnetic stand until the solution is clear. Transfer 10 μL of the sample to a new PCR tube.
      Note: If dimers exist after a single round of purification, based on cDNA size distribution detection, purify again to remove the dimers completely. The dimers can influence the cDNA yield calculation if allowed to remain in the sample.
  4. Quality check of cDNA.
    1. Randomly choose samples to detect the cDNA total yield using a fluorometer.
    2. Evaluate the marker gene expression levels by real-time PCR (qPCR) (Figure 4E). Remove 1 μL of the sample to dilute 40 times and perform qPCR using a 384-well plate. Prepare the qPCR mix as described in Table 3. Cycling conditions: 95 °C for 10 min, 45 cycles (95 °C for 10 s, 60 °C for 15 s, 72 °C for 15 s).
    3. Randomly choose samples to detect the size distribution using a parallel capillary electrophoresis instrument.

6. cDNA Library Construction

  1. Tagmentation reaction by the Tn5 transposase.
    1. Detect the cDNA total yield of qPCR-selected cells from step 5.4.2 using a fluorometer. Use 2 ng of cDNA as the starting material.
    2. Thaw the tagmentation reaction reagents (Table 4) on ice.
    3. Prepare the tagmentation reaction in a 0.2 mL thin-wall 8-stripe PCR tube, as described in Table 4, and mix carefully by vortex. Then, quickly spin down the solution at room temperature.
    4. Incubate the samples at 55 °C for 10 min and hold at 4 °C.
    5. Immediately add 2 μL of 5x TS to each sample containing the tagmented DNA to stop the reaction. Mix carefully by vortex, and then quickly spin down the solution at room temperature.
    6. Incubate the mixture for 5 min at room temperature. The DNA should be processed for the final enrichment PCR immediately.
  2. Amplification of adapter-ligated fragments.
    1. Thaw the PCR reagents (Table 5) on ice.
    2. Prepare the enrichment PCR mix, as described in Table 5, and mix carefully by vortex. Then, quickly spin down the solution at room temperature.
    3. Perform the PCR by using the following program: 72 °C for 10 min, 98 °C for 30 s, 8 cycles (98 °C for 15 s, 60 °C for 30 s, 72 °C for 3 min), 72 °C for 5 min and hold at 4 °C.
      NOTE: The number of cycles depends on the expected library DNA amount.
  3. PCR purification with size selection.
    1. Add 14 μL of re-suspended DNA purification beads (0.7 x) to each sample from the previous step and mix well by vortex. Then, quickly spin the tube at room temperature to collect the liquid but avoid the settlement of beads.
      NOTE: Equilibrate DNA purification beads to room temperature for 15 min and vortex thoroughly before use.
    2. Incubate for 5 min at room temperature.
    3. Place the tube on an appropriate magnetic stand until the solution is clear, carefully transfer the supernatant to a new tube strip and discard the previous tube stripe.
    4. Add 3 μL of re-suspended DNA purification beads (0.15x) to each sample in the tube stripe and mix well by vortex. Then, quickly spin the tube at room temperature.
    5. Incubate for 5 min at room temperature.
    6. Place the tube or plate on an appropriate magnetic stand until the solution is clear, then carefully remove and discard the supernatant.
    7. Add 200 μL of freshly prepared 80% ethanol to wash the beads while in the magnetic stand, incubate for 30 s, then carefully remove and discard the ethanol solution.
      NOTE: The 80% (vol/vol) ethanol solution should be freshly prepared each time.
    8. Repeat step 6.3.7 for a total of two washes.
    9. Carefully remove and discard the remaining ethanol solution and air dry the beads while the tube or plate is on the magnetic stand.
      NOTE: Avoid over-drying the beads to ensure the maximum elution efficiency.
    10. Add 11 μL of nuclease-free water to elute the DNA target from the beads and mix well by vortex. Then, quickly spin the tube or plate and place it on a magnetic stand until the solution is clear. Transfer 10 μL of the sample to a new tube stripe.
  4. Quality check of final cDNA library.
    1. Measure the concentration of each library using a fluorometer and check the size distribution using a parallel capillary electrophoresis instrument.
      Note: The DNA yield is typically between 15–25 ng for each library. The fragments ranging from 250 bp to 450 bp will be observed. If dimers remain after purification, as confirmed by the size distribution check, purify with 1 x DNA purification beads one more time.
  5. Library pooling
    1. Based on the approximate fragment size, pool equal amounts of DNA from each sample, ensuring that none of them contain the same combinations of N6XX and N8XX adapters.

7. DNA Sequencing

  1. Subject barcoded libraries to 51 bp single-end sequencing using a high-throughput sequencing system. Perform the sequencing following the manufacturer's protocol. The sequencing depth of each cell is about 1 million reads on average8, at least 0.5 million reads per cell14.

8. Bioinformatics Analyses

  1. Sequencing quality evaluation and alignment.
    1. Evaluate the quality of sequenced reads using FastQC (v0.11.3)15 with the following parameters: “fastqc --extract -o output_dir input_fastq”.
    2. Merge the mouse genome with the ERCC sequences using the command “cat mm10.fa ERCC.fa >mm10_ERCC.fa”.
    3. Build bowtie2 (v2.2.5)16 index with the following parameters: “bowtie2-build mm10_ERCC.fa mm10_ERCC”.
    4. Align reads using tophat2 (v2.1.0)17 with the following parameters: “tophat2 -o output_dir -G gene.gtf --transcriptome-index trans_index mm10_ERCC input_fastq”.
  2. Quantify gene expression levels.
    1. Count mapped reads for each gene using HTSeq (v 0.6.0)18 with the following parameters: ‘‘htseq-count -f bam -r pos -s no -a 30 accepted_hits.bam gene.gtf > read_count.txt’’.
    2. Normalize the gene expression levels to transcripts per million (TPM)19.
  3. Quality control of cells.
    1. Exclude cells with fewer than 0.5 million mapped reads or fewer than 4,000 genes (TPM > 1).
      NOTE: the criterion of exclusion depends on the cell types and sequence depth.
    2. Retain cells expressing endocrine markers (e.g., Ins1 for β cells, Gcg for α cells), and exclude cells expressing non-endocrine markers (e.g., Spi1 for leukocytes).
  4. Principal component analysis (PCA)
    1. Identify highly variable genes according to ERCC spike-ins, as previously described20.
    2. Perform PCA using the function “PCA” in the R package FactoMineR (v1.31.4)21, with log2(TPM + 0.1) of highly variable genes.
    3. Visualize the PCA results with ggplot2 (v2.0.0)22.
  5. Hierarchical clustering.
    1. Identify genes with the highest principal component (PC) loadings using the “dimdesc” function FactoMineR (v1.31.4)21.
    2. Perform hierarchical clustering using the function “heatmap.2“ in the R package gplots (v3.0.1)23, with log2 (TPM + 1) relative values of high PC loading genes.

Subscription Required. Please recommend JoVE to your librarian.

Representative Results

Pancreases were dissected from embryonic, neonatal and postnatal mice (Figure 2A and 2B). For mice older than postnatal day 18, the digestive effect depends on the degree of perfusion; therefore, the injection is the most important step for islet isolation (Figure 2C-2E and Table 6). As much collagenase was injected as was possible to fill the pancreas during this step. The fully inflated pancreas is shown in Figure 2D. If the perfusion is not successful (Figure 2E), but the sample is precious, the pancreas can be torn into small pieces for sufficient digestion later.

After perfusion, the pancreatic tissue was digested into small pieces to release islets (Figure 2F). To shorten the FACS sorting time, we enriched the endocrine cells by picking the islets in advance. The size of the islets may vary depending on the mouse age and the digestion intensity. Occasionally, the islets are not round in shape. Islets should be selected according to color and compact state (Figure 2G and Table 6). If the transgenic mouse strain has a reporter gene, such as GFP or RFP for endocrine cells, the islets could also be picked under a fluorescence microscope.

Ins1-RFP+ cells were purified by FACS sorting (Figure 3A-3C), and then single cells were picked using a capillary pipette for single-cell RNA-seq (Figure 3D). Successfully amplified cDNA should have a full length above 500 bp and be enriched from 1.5 kb to 2 kb. Moreover, there is usually a 500-600 bp enrichment of cDNA observed in the Ins1-RFP+ cells, which may represent the insulin transcripts (Figure 4A). However, there have been some abnormal situations observed10 (Table 6). For example, the cDNA fragments near 100 bp are primer dimers (Figure 4B), which are usually caused by the excessive primers, that must be removed by repeating the DNA purification step. The existence of primer dimers may influence the calculations of total cDNA yields, which are used for the following library construction. The cDNA fragments between 100 bp and 500 bp usually represent degraded cDNA (Figure 4C), which is caused by bad cell status or reagent problems, such as RNase contamination. Under this condition, we should identify the cause of DNA degradation and exclude the disturbance. For instance, to ensure good cell status, tissues should be digested and cells should be sorted quickly and gently, and operations should be performed cautiously to avoid any type of pollutants.

After the purification of the cDNA libraries for sequencing, we obtained cDNA fragments of different sizes by following the instructions for adding different ratios of DNA purification beads to the sample. For example, we can obtain cDNA ranging from 250 bp to 450 bp by adding 0.7x and 0.15x DNA purification beads to the first and second rounds of purification, respectively (Figure 4D). This step has a high success rate. However, if there are fragments of approximately 100 bp, it is suggested to purify the libraries again with 1x DNA purification beads to remove dimers (Table 6). Unremoved dimers will skew the DNA quantification and will influence the sample pooling results, which results in the uneven data acquisition from each sample.

We analyzed the sequencing data with bioinformatics approaches (Figure 5A). The sequencing quality scores should be greater than 30 during sequencing quality evaluation (Figure 5B). After alignment, 80-90% of reads are expected to be mapped to the reference genome. To obtain high quality cells for downstream analyses, we excluded cells with fewer than 0.5 million mapped reads or with fewer than 4,000 detected genes (Figure 5C and 5D). After PCA and hierarchical clustering, we characterized different groups of cells and identified the genes that were heterogeneously expressed in different groups8.

Figure 1
Figure 1: Schematic overview for single-cell RNA-seq of mouse pancreatic endocrine cells. Please click here to view a larger version of this figure.

Figure 2
Figure 2: Pancreas dissection, perfusion and islet picking. (A) Dissection of embryonic pancreatic tissue (lower) from an E17.5 embryo (upper). The yellow dotted line demarcates the pancreatic tissue. Scale bar = 1,000 µm. (B) Dissection of postnatal pancreatic tissue (right) from a P10 mouse (left). Scale bar = 1,000 µm. (C-D) The pancreatic tissue of a P60 mouse before (C) and after (D) perfusion. The yellow dotted line demarcates the pancreatic tissue. White arrow indicates gallbladder. (E) The partially perfused pancreatic tissue of a P60 mouse. Red arrow indicates the well perfused area of the pancreas. Blue arrows indicates the poorly perfused areas of the pancreas. (F) The pancreatic tissue before (upper) and after (lower) collagenase digestion. (G) Arrows point to the islets that were released from collagenase digested pancreatic tissue. Scale bar = 200 µm. Please click here to view a larger version of this figure.

Figure 3
Figure 3: Manually picking cells with a 30–40 µm capillary pipette under a microscope. (A-C) Step-wise FACS gating for sorting Ins1-RFP+ cells. (D) The bright circles indicate cells and the tube is a capillary pipette. Pick the cells with better morphology (Arrow) and ignore the clustered cells (Arrowhead). Scale bar = 200 µm. Please click here to view a larger version of this figure.

Figure 4
Figure 4: Quality detection of cDNA and library size distribution of Ins1-RFP+ cells by a parallel capillary electrophoresis instrument. (A) The representative result of successfully pre-amplified cDNA. Normally, the cDNA profile should be above 500 bp with an ~1.5–2 kb peak. (B) The representative result of pre-amplified cDNA with a primer dimer peak. The primer dimer peak is approximately 100 bp. (C) The profile of pre-amplified cDNA with fragments between 100 bp and 500 bp indicates the possibility of cDNA degradation. (D) The size distribution of cDNA library ranging between 250 bp and 450 bp following the purification steps mentioned in this protocol. (E) The expression levels of Ins2 in cDNA libraries by qPCR (left) and relative sequencing data (right). The x-axes represent distinct 8 single cell samples. The y-axis (left) represents normalized ΔCt relative to Gapdh (CtGapdh- CtIns2 + 6) and the y-axis (right) represents normalized expression level of Ins2 relative to Gapdh (log2(TPMIns2 / TPMGapdh)). Please click here to view a larger version of this figure.

Figure 5
Figure 5: Bioinformatics analyses of single-cell transcriptome data. (A) Pipeline of bioinformatics analyses. (B) Sequencing quality scores across all bases of reads. (C) Distribution of mapped read count. (D) Distribution of detected gene count. Please click here to view a larger version of this figure.

Component Volume (µL)
Reverse transcriptase (200 U/µL) 0.5
RNase inhibitor 0.25
First-strand buffer (5x) 2
DTT (100 mM) 0.5
Betaine (5 M) 2
MgCl2 (1 M) 0.06
TSO (100 µM) 0.1
Nuclease-free water 0.29
Total 5.7

Table 1: RT reagent mix components in a 5.7 µL reaction for each sample.

Component Volume (µL)
First-strand reaction 10
DNA Polymerase (2x ReadyMix) 12.5
IS PCR primers (10 µM) 0.25
Nuclease-free water 2.25
Total 25

Table 2: PCR pre-amplification reagent mix components in a 25 µL reaction for each sample

Component Volume (µL)
SYBR Green Master Mix 5
Primers (5 µM) 0.5
Nuclease-free water 2.5
cDNA 2
Total 10

Table 3: qPCR reagent mix components in a 10 µL reaction using a standard 384-well plate.

Component Volume (µL)
5x TTBL 1.6
2 ng cDNA Variable
ddH2O Variable
TTE Mix V5 2
Total 8

Table 4: Tagmentation reagent mix components in an 8 µL reaction for each sample.

Component Volume (µL)
ddH2O 1.6
Product of previous step 10
5x TAB 4
N6XX 2
N8XX 2
TAE 0.4
Total 20

Table 5: Enrichment PCR reagent mix components in a 20 µL reaction for each sample.

Step Problem Possibility Solution
1.3.4 Slipping of the clamps The outer surface of the intestine is wet caused by the existence of the small amount of interstitial fluid and collegenase leakness Gently swap the duodenum wall and other organ walls in the abdominal cavity with cotton swabs
1.3.6 Intestine burst Liquid pressure is too high in the intestine Slow down the injection speed
2.6 Islets stick to exocrine tissue when picking islets Insufficent digestion Prolong the digestion duration and shaking strength
5.3 The cDNA yield is low after PCR amplification The cells are in bad condition Keep cells fresh and in good condition
5.4 or 6.4 Primer dimers can be seen Excessive primers Purify the cDNA one more time with DNA purification beads (0.8:1 or 1:1 ratio)
5.4 Degraded cDNA after PCR amplification Poor quality of cells or contaminated reagents Keep cells in good condition or change reagents
6.3 The amount of DNA is low after library construction Too few PCR cycles or the quality of cDNA is not good Increase the number of cycles or ensure cDNA quality before library construction

Table 6: Troubleshooting.

Subscription Required. Please recommend JoVE to your librarian.

Discussion

In this protocol, we demonstrated an effective and easy-to-use method for studying the single-cell expression profiles of pancreatic β cells. This method could be used to isolate endocrine cells from embryonic, neonatal and postnatal pancreases and to perform single-cell transcriptomic analyses.

The most critical step is the isolation of single β cells in good condition. Fully perfused pancreases respond better to subsequent digestion. Insufficient perfusion, which usually occurs in the dorsal pancreas, will result in a low islet yield. After perfusion, the digestion time and shaking intensity require special attention. Over-digestion, resulting from long incubation times and vigorous shaking, can break the islets into pieces. Insufficient digestion will not completely separate the islets from adjacent tissues. After digestion of the pancreas, the islets were purified by hand picking rather than by density gradient centrifugation. Although density gradient centrifugation can enrich islets, many small islets or islets connected with acinar tissue are mistakenly discarded. Try to avoid picking acinar tissue, which may cause inefficient trypsin digestion and reduce the purity of the β cells.

Independent biological replicates are necessary for distinguishing biological variability and batch effects. If two biological replicates have a similar pattern in PCA and include similar sub-groups in clustering results, these samples might reveal reliable biological variability. Otherwise, additional biological replicates are required to confirm the results. For a metabolic organ such as the pancreas, the cell state associated with the circadian clock24 may account for batch differences. To solve this problem, we recommend collecting all samples at the same time of day.

The limitation of this approach is low throughput because we have to construct a library for each cell. Due to the excessive primers in the reaction, the cDNA before and after library construction generally should be purified twice to completely remove the primer dimers. These processes are time-consuming. Recently, a modified protocol25 was reported that could solve this problem to some extent. In this protocol, the cell-specific barcode labels cDNA fragments during the reverse transcription step. Therefore, the cDNA of each cell can be pooled together and then be purified, followed by library construction. This modification significantly increases the throughput of library construction. However, this modified method is less sensitive and detects fewer genes per cell. In addition, this method is a 3' counting method with reduced read coverage. Therefore, Smart-seq2 is still the most suitable method for pancreatic development.

The pancreatic preparation from other species may be different. For human pancreas, the islets can be isolated following previous protocols26,27. Then, the isolated islets can be dissociated into single cells28 and perform single-cell analyses using this method. This method can be widely applied to the research of mammalian pancreatic development, diseases and regeneration.

Subscription Required. Please recommend JoVE to your librarian.

Disclosures

The authors have nothing to disclose.

Acknowledgements

We thank the National Center for Protein Sciences, Beijing (Peking University) and the Peking-Tsinghua Center for the Life Science Computing Platform. This work was supported by the Ministry of Science and Technology of China (2015CB942800), the National Natural Science Foundation of China (31521004, 31471358, and 31522036), and funding from Peking-Tsinghua Center for Life Sciences to C.-R.X.

Materials

Name Company Catalog Number Comments
Collagenase P Roche 11213873001
Trypsin-EDTA (0.25 %), phenol red Thermo Fisher Scientific 25200114
Fetal bovine serum (FBS) Hyclone SH30071.03
Dumont #4 Forceps Roboz RS-4904
Dumont #5 Forceps Roboz RS-5058
30 G BD Needle 1/2" Length BD 305106
Stereo Microscope Zeiss Stemi DV4
Stereo Fluorescence microscope Zeiss Stereo Lumar V12
Centrifuge Eppendorf 5810R
Centrifuge Eppendorf 5424R
Polystyrene Round-Bottom Tube with Cell-Strainer Cap BD-Falcon 352235
96-Well PCR Microplate Axygen PCR-96-C
Silicone Sealing Mat Axygen AM-96-PCR-RD
Thin Well PCR Tube Extragene P-02X8-CF
Cell sorter BD Biosciences BD FACSAria
Capillary pipette Sutter B100-58-10
RNaseZap Ambion AM9780
ERCC RNA Spike-In Mix Life Technologies 4456740
Distilled water Gibco 10977
Triton X-100 Sigma-Aldrich T9284
dNTP mix New England Biolabs N0447
Recombinant RNase Inhibitor Takara 2313
Superscript II reverse transcriptase Invitrogen 18064-014
First-strand buffer (5x) Invitrogen 18064-014
DTT Invitrogen 18064-014
Betaine Sigma-Aldrich 107-43-7
MgCl2 Sigma-Aldrich 7786-30-3
Nuclease-free water Invitrogen AM9932
KAPA HiFi HotStart ReadyMix (2x) KAPA Biosystems KK2601
VAHTS DNA Clean Beads XP beads Vazyme N411-03
Qubit dsDNA HS Assay Kit Invitrogen Q32854
AceQ qPCR SYBR Green Master Mix Vazyme Q121-02
TruePrep DNA Library Prep Kit V2 for Illumina Vazyme TD502 Include 5x TTBL, 5x TTE, 5x TS, 5x TAB, TAE
TruePrep Index Kit V3 for Illumina Vazyme TD203 Include 16 N6XX and 24 N8XX
High Sensitivity NGS Fragment Analysis Kit Advanced Analytical Technologies DNF-474
1x HBSS without Ca2+ and Mg2+ 138 mM NaCl; 5.34 mM KCl
4.17 mM NaHCO3; 0.34 mM Na2HPO4
0.44 mM KH2PO4
Isolation buffer 1 × HBSS containing 10 mM HEPES, 1 mM MgCl2, 5 mM Glucose, pH 7.4
FACS buffer 1 × HBSS containing 15 mM HEPES, 5.6 mM Glucose, 1% FBS, pH 7.4
NaCl Sigma-Aldrich S5886
KCl Sigma-Aldrich P9541
NaHCO3 Sigma-Aldrich S6297
Na2HPO4 Sigma-Aldrich S5136
KH2PO4 Sigma-Aldrich P5655
D-(+)-Glucose Sigma-Aldrich G5767
HEPES Sigma-Aldrich H4034
MgCl2 Sigma-Aldrich M2393
Oligo-dT30VN primer 5'-AAGCAGTGGTATCAA
CGCAGAGTACT30VN-3'
TSO 5'-AAGCAGTGGTATCAAC
GCAGAGTACATrGrG+G-3'
ISPCR primers 5'-AAGCAGTGGTAT
CAACGCAGAGT-3'
Gapdh Forward primer 5'-ATGGTGAAGGTC
GGTGTGAAC-3'
Gapdh Reverse primer 5'-GCCTTGACT
GTGCCGTTGAAT-3'
Ins2 Forward primer 5'-TGGCTTCTTC
TACACACCCA-3'
Ins2 Reverse primer 5'-TCTAGTTGCA
GTAGTTCTCCA-3'

DOWNLOAD MATERIALS LIST

References

  1. Gu, G., Dubauskaite, J., Melton, D. A. Direct evidence for the pancreatic lineage: NGN3+ cells are islet progenitors and are distinct from duct progenitors. Development. 129, (10), 2447-2457 (2002).
  2. Oliver-Krasinski, J. M., Stoffers, D. A. On the origin of the beta cell. Genes & Development. 22, (15), 1998-2021 (1998).
  3. Dor, Y., Brown, J., Martinez, O. I., Melton, D. A. Adult pancreatic beta-cells are formed by self-duplication rather than stem-cell differentiation. Nature. 429, (6987), 41-46 (2004).
  4. Smukler, S. R., et al. The adult mouse and human pancreas contain rare multipotent stem cells that express insulin. Cell Stem Cell. 8, (3), 281-293 (2011).
  5. Dorrell, C., et al. Human islets contain four distinct subtypes of beta cells. Nature Communications. 7, 11756 (2016).
  6. Bader, E., et al. Identification of proliferative and mature beta-cells in the islets of Langerhans. Nature. 535, (7612), 430-434 (2016).
  7. Saliba, A. E., Westermann, A. J., Gorski, S. A., Vogel, J. Single-cell RNA-seq: Advances and future challenges. Nucleic Acids Research. 42, (14), 8845-8860 (2014).
  8. Qiu, W. L., et al. Deciphering pancreatic islet beta cell and alpha cell maturation pathways and characteristic features at the single-cell level. Cell Metabolism. 25, (5), 1194-1205 (2017).
  9. Picelli, S., et al. Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nature Methods. 10, (11), 1096-1098 (2013).
  10. Picelli, S., et al. Full-length RNA-seq from single cells using Smart-seq2. Nature Protocols. 9, (1), 171-181 (2014).
  11. Piccand, J., et al. Pak3 promotes cell cycle exit and differentiation of beta-cells in the embryonic pancreas and is necessary to maintain glucose homeostasis in adult mice. Diabetes. 63, (1), 203-215 (2014).
  12. Veite-Schmahl, M. J., Regan, D. P., Rivers, A. C., Nowatzke, J. F., Kennedy, M. A. Dissection of the mouse pancreas for histological analysis and metabolic profiling. Journal of Visualized Experiments. (126), (2017).
  13. Hu, P., Zhang, W., Xin, H., Deng, G. Single cell isolation and analysis. Frontiers in Cell and Developmental Biology. 4, 116 (2016).
  14. Haque, A., Engel, J., Teichmann, S. A., Lonnberg, T. A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications. Genome Medicine. 9, (1), 75 (2017).
  15. Andrews, S. FastQC: A quality control tool for high throughput sequence data. Available from: https://www.bioinformatics.babraham.ac.uk/projects/fastqc/ (2010).
  16. Langmead, B., Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nature Methods. 9, (4), 357-359 (2012).
  17. Kim, D., et al. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biology. 14, (4), (2013).
  18. Anders, S., Pyl, P. T., Huber, W. HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics. 31, (2), Oxford, England. 166-169 (2015).
  19. Wagner, G. P., Kin, K., Lynch, V. J. Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples. Theory in Biosciences. 131, (4), 281-285 (2012).
  20. Brennecke, P., et al. Accounting for technical noise in single-cell RNA-seq experiments. Nature Methods. 10, (11), 1093-1095 (2013).
  21. Le, S., Josse, J., Husson, F. FactoMineR: An R package for multivariate analysis. Journal of Statistical Software. 25, (1), (2008).
  22. Hadley, W. ggplot2: Elegant graphics for data analysis. Springer Science & Business Media. (2009).
  23. Warnes, G., Bolker, B., Bonebakker, L., Gentleman, R., Huber, W., Liaw, A., Lumley, T., Mächler, M., Magnusson, A., Möller, S. gplots: Various R Programming Tools for Plotting Data. Available from: https://cran.r-project.org/package=gplots (2016).
  24. Marcheva, B., et al. Disruption of the clock components CLOCK and BMAL1 leads to hypoinsulinaemia and diabetes. Nature. 466, (7306), 627-631 (2010).
  25. Li, L., et al. Single-cell RNA-seq analysis maps development of human germline cells and gonadal niche interactions. Cell Stem Cell. (2017).
  26. Qi, M., et al. Human pancreatic islet isolation: Part I: Digestion and collection of pancreatic tissue. Journal of Visualized Experiments. (27), (2009).
  27. Qi, M., et al. Human pancreatic islet isolation: Part II: Purification and culture of human islets. Journal of Visualized Experiments. (27), (2009).
  28. Teo, A. K. K., et al. Single-cell analyses of human islet cells reveal de-differentiation signatures. Cell Death Discovery. 4, (14), (2018).

Comments

0 Comments


    Post a Question / Comment / Request

    You must be signed in to post a comment. Please or create an account.

    Usage Statistics