Created By: Jasmit Dhaliwal, Cynthia Yuanxin Gu, Pavlo Navrota, Jasmine Soomal

In “A Human Pluripotent Stem Cell-based Platform to Study SARS-CoV-2 Tropism and Model Virus Infection in Human Cells and Organoids” by Yang et al., the authors aimed to discover a physiologically relevant human model to study SARS-CoV-2 infection. A library of cell and organoids was generated from hPSCs, which were then infected with the virus to evaluate permissiveness. Infection of these cells was then validated using various models, and transcript profiling was used to evaluate chemokine expression to reveal cells that offer a valuable model of SARS-CoV-2 infection (1).

Image 1: Shuibing Chen, Ph.D., principal investigator under which Dr. Liuliu Yang is currently a Postdoctoral Associate in Surgery at Weill Cornell Medical College.

Dr Liuliu Yang is a Postdoctoral Associate in the Department of Surgery under Dr Shuibing Chen’s stem cell lab at Weill Cornell Medical College as of 2019. He received his PhD from the Chinese Academy of Science in Beijing (China) in 2019 (2).

Dr Chen’s lab at Cornell Medicine studies high throughput screens using human pluripotent stem cells and human pluripotent stem cell-derived populations. With their in house chemical and protein libraries, they have so far identified a series of small molecules that control stem cell self-renewal, differentiation, and reprogramming. Currently, Dr Chen’s lab is focusing on identifying small molecules that direct human pluripotent stem cells (hPSC) differentiation into cell types like pancreatic endocrine cells, exocrine cells, and hepatocytes (3).

Yang et al. started off with the differentiation of hPSC into the 3 germ layers, followed by the commitment to the eight types of cells or organoids (Figure 1A). Each cell underwent directed differentiation where their cultures were sequentially supplemented with inducing factors and growth factors specific to their hPSC-derived cell (1).

Figure 1A: hPSC differentiation to eight types of cells or organoids.

For example, hESC line H1 was differentiated into endothelial cells by passing through different mediums and growth factors (Figure S1C). H1 then differentiated into the mesoderm, vascular progenitors, endothelial progenitors, and then finally, the endothelial cells. This process was completed specifically for each cell type (1).

Figure S1C: Directed differentiation of hPSCs to endothelial cells.

Fig 1B: Confocal imaging of hPSC-derived cells/organoids using antibodies against ACE2 and cell specific markers.

Immunostaining was then performed on the eight-cell or organoid types to examine the expression of the ACE2 receptor for SARS-CoV-2 infection. Confocal microscopy was used to pass light uniformly over the organoids stained with antibodies against certain cell markers, ACE2, and DAPI. In Figure 1B, red is indicative of ACE2 expression, which is detected in GCG+ alpha and beta-pancreatic endocrine cells, ALB+ hepatocytes in liver organoids, CD31+ endothelial cells, cardiomyocytes, CD206+ macrophages, microglia, and dopaminergic neurons. Cortical neurons expressed low levels, and no detection was found in hPSCs. The green displays the antibodies used against specific cell markers. For example, antibodies against ALB are used to determine the presence of liver cells. Finally, the blue demonstrates DAPI staining, which binds to the DNA in nuclei and simply indicates the presence of cells (1).

Each cell or organoid type was then infected with a mock-control and SARS-CoV-2 pseudo-entry virus, and their luciferase activity was examined 24 hours later as an indication of the infection's efficiency (Figure 1C). High luciferase activity (LUC) was detected in pancreatic endocrine cells, liver organoids, cardiomyocytes, and dopaminergic neurons. Relatively low or no LUC levels were found in the other cells. Time-course experiments showed that low LUC activity was not a delayed infection of the virus, as levels remained comparable at 48 hours post-infection (hpi) (1).

Figure 1C: Luciferase activity of eight types of organoids either mock or infected with SARS-CoV-2 pseudo-entry virus at 24 hpi.

Confocal imaging of the hPSC-derived cells showed that the same cell types that showed high LUC activity stained positively with a LUC antibody, which is shown in red. These include pancreatic endocrine cells (Fig. 1E), hepatocytes in liver organoids (Fig. 1F), sarcomeric α-Actinin+ cardiomyocytes (Fig. 1G), and MAP2+ and FOXA2+ dopaminergic neurons (Fig. 1K). LUC was rarely detected in IBA1+ microglial cells (Fig. 1H), CD31+ endothelial cells (1I), CD206+ macrophages (Fig. 1J), or beta III-tubulin+ cortical neurons (Fig. 1L). The green fluorescence is indicative of cell markers specific to each cell type, such as CS31 for the endothelial cells (1).

Figures 1E-L: Confocal imaging of hPSC derived cells (in respective order: endocrine cells, hepatocytes, cardiomyocytes, dopaminergic neurons, microglial cells, endothelial cells, macrophages, cortical neurons) with SARS-CoV-2 pseudo-entry virus using antibodies against luciferase (red), cell specific markers (green), and DAPI (blue).

Figure 2A: UMAP of nine cell types after single-cell RNA-seq. Figure 2B: UMAP of pancreatic cell markers, including PRSS1, KRT19, INS, GCG, COL1A1, PECAM1, TYROBP, SST, and PPY.

Before validating the permissiveness of primary human islets to SARS-CoV-2 virus, the authors used single-cell RNA-sequencing (scRNA-seq) to examine global transcript profiles. The nine-cell lineages were defined and categorized are acinar cells, ductal cells, beta cells, alpha cells, mesenchymal cells, delta cells, pp cells, endothelial cells and immune cells (Figure 2A) (1).

The expression of unique marker genes further confirmed each cell type (Figure 2B). PRSS1 indicated acinar cells, keratin19/KRT19 indicated ductal cells, COL1A1 indicated mesenchymal cells, PECAM1 indicated endothelial cells, TYROBP indicated immune cells, SST indicated delta cells, and PPY indicated PP cells. In particular, note the INS indicated beta cells and GCG indicated alpha cells (1).

To use scRNA-seq for examining global transcript profiles, the authors isolated individual cells. The most commonly used strategy for this is using flow activated cell sorting (FACS). FACS flags target cells with a fluorescent monoclonal antibody-based on a specific known surface marker and enables sorting of distinct populations. During the sorting, a laser is run through a single file of cells and sorted based on the detection of fluorescence. The authors then sequenced these cells using scRNA-seq, filtering cells with less than 300 or more than 6000 genes and ones with mitochondrial gene content greater than 15% (1).

The authors projected global transcript profiles retrieved from scRNA-seq using UMAP, or Uniform Manifold Approximation and Projection. UMAP simplifies the complex relationships and factors that play into the expression profiles of genes into a 2D graph. This is commonplace when identifying and characterizing proteins that act in a common pathway through whole-transcriptome profiling, while also preventing inference of physical and genetic interactions. UMAP condenses large data sets into a comprehensible graph while still maintaining the relationship between genes. By doing so, scientists can identify groups of genes that correspond to protein complexes and pathways (1,4).

Now that cell lineages are confirmed, the authors wanted to assess the correlation between the expression of two known receptors associated with SARS-CoV-2 infection and the permissiveness of each cell type to SARS-CoV-2 virus. The two factors being the putative receptor ACE2 and the effector protease TMPRSS2. ACE2 and TMPRSS2 were both expressed in acinar cells, ductal cells, mesenchymal cells, endothelial cells, and beta cells, alpha cells (Figures 2C and 2D) (1).

Figure 2C: UMAP of ACE2 and TMPRSS2. Figure 2D: Jitter plots of ACE2 and TMPRSS2.

Figure 2E: Confocal imaging of adult human islets stained with the antibodies against ACE2, INS, or GCG.

The authors show this expression using a jitter plot; similar to a scatter plot, jitter plots visualize data using single plots. The difference is that it graphs the relationship between a measurement variable, in this case gene expression on the y axis and a categorical variable seen here as cell type on the x-axis.

Immunohistochemistry further validated that primary human alpha and beta cells express ACE2 (Figure 2E). This is an image taken using confocal microscopy, where light is passed uniformly over tissue samples of adult human islets stained with antibodies against ACE2, INS, or GCG (1,5).

Image 2: Human pancreatic endocrine cells located in the islets of Langerhans in the pancreas. Alpha cells indicated as large light purple cells, delta cells indicated as small sickle-like light purple cells, and beta cells indicated as dark purple cells (7).

Human alpha and beta cells are pancreatic endocrine cells, or islands of cells of the pancreas that produce hormones. Alpha cells release glucagon, which elevates blood glucose, and beta cells produce insulin, which lowers blood glucose (6)

Based on previous research on the connection between SARS-CoV-2 and pancreatic endocrine cells, the authors wanted to take a closer look at how human pancreatic endocrine cells are affected by SARS-CoV-2 in an in vivo model. The authors transplanted hPSC-derived pancreatic endocrine cells under the kidney capsule of SCID-beige mice (1).

Two months following transplantation, the organoid xenograft was removed and the expression profiles of the cells were analyzed. Like with the in vitro cultures, ACE2 was also detected in hPSC-derived INS+ beta cells and GCG+ alpha cells. Yang et al. then inoculated the mice with a SARS-CoV-2 pseudo-entry virus. 24 hpi, the xenografts were removed and analyzed by immunohistochemistry. LUC was detected in the xenografts inoculated with the virus, but not in controls (1)

Image 3: In vivo SCID-beige mouse model of human pancreatic endocrine cells SARS-CoV-2 pseudo-entry virus infection. hPSC-derived pancreatic endocrine cells were transplanted under the kidney capsule of mice. Two months after transplantation, organoid xenograft was removed for analysis, and mice were inoculated with SARS-CoV-2 pseudo-entry virus. 24 hours after infection, the xenografts were removed and analyzed by immunohistochemistry.

Immunohistochemistry detected LUC in INS+ beta cells and GCG+ alpha cells (Figures 2I and 2J), further confirming that these two types of human pancreatic endocrine cells are permissive to SARS-CoV-2 pseudo-entry virus infection in vivo (1).

Figure 2I: Confocal imaging and quantification. Figure 2J: of human pancreatic endocrine xenografts against LUC, INS, or GCG, at 24 hpi of SARS-CoV-2 pseudo-entry virus infection.

Image 4: COVID-19 and T2D patients with well-controlled blood glucose regulation (upper limit ≤ 10 mmol/L) had better clinical outcomes than those with poorly controlled blood glucose (upper limit greater than 10 mmol/L), showing the connection between proper blood glucose control and improved outcomes in patients with COVID-19 (8)

The infection of human pancreatic beta cells by SARS-CoV-2 was of particular interest as it supports an existing hypothesis that viral infections contribute to the pathogenesis of Type 1 diabetes. This has been seen before with enteroviruses, coxsackievirus B, rotavirus, mumps virus, and cytomegalovirus. Enteroviruses in particular infected and induced the destruction of human islet cells in vitro (1). There has also been a recent clinical study showing a strong correlation between COVID-19 and type 2 diabetes, increasing the mortality risk of patients (8).

Yang et al. then decided to look at the infection response of hPSC derived pancreatic alpha and beta cells. They confirmed cellular infection using qRT-PCR (Figure 3A). Viral subgenomic RNA levels were higher compared to the control and increased in subsequent hours post-infection. Immunofluorescence staining showed spike protein in alpha (GCG+) and beta (INS+) cells (Figure 3B). Quantification of confocal imaging showed a substantial number of INS+ and GCG+ cells with spike protein (Figure 3C). RNA transcript profiles of infected cells showed viral RNA alignment to the SARS-CoV-2 genome (Figure 3D) (1)

Methods for confirming successful cell infection. Figure 3A: qRT-PCR analysis of relative viral N sgRNA expression in hPSC-derived pancreatic endocrine cells infected with SARS-CoV-2, carried out at increasing MOIs (virions per cell). Figure 3B: Confocal imaging and quantification (Figure C) of SARS-CoV-2-infected (MOI = 0.01, 24 hpi) hPSC-derived pancreatic endocrine cells stained for SARS-CoV-2 Spike protein, INS, or GCG. Scale bar represents 10 mm. Figure 3D: Read coverage of the SARS-CoV-2 genome in infected hPSC-derived pancreatic endocrine cells (MOI = 0.01, 24 hpi). Schematic denotes the SARS-CoV-2 genome.

Principal component analysis (PCA) showed that gene expression clustered differently between mock and infected cells (Figure 3E). KEGG Gene Set Enrichment (GSEA) showed upregulation of viral infection pathways such as those of HIV, herpes virus, Epstein Barr virus, hepatitis C, and cytomegalovirus. Concerningly, pathways related to metabolism and pancreatic endocrine function were downregulated, such as calcium signalling, glucagon signalling, and insulin resistance pathways (Figure 3F) (1).

Figure 3E: Using the R Seurat package, highly variable genes and their differential expression between mock and SARS-CoV-2-infection. Figure 3F: KEGG gene set enrichment analysis of differential gene expression profiles from SARS-CoV-2-infected hPSC-derived pancreatic endocrine cells compared to mock infection.

To determine if these changes were caused by dedifferentiation to a stem cell state, or cell apoptosis, immunostaining was carried out. CASP3 was an apoptotic marker that was found in both GCG+ and INS+ cells suggesting the pathway profiles are due to apoptosis (Figure S3C).

Figure S3C: Quantification of confocal imaging of SARS-CoV-2 infected (MOI = 0.1) hPSC-derived pancreatic endocrine cells at 24 hpi. Cells are stained for apoptotic marker CASP3 and either alpha cell maker GCG or beta cell marker INS.

This was further confirmed by the RNA sequencing data showing upregulation of apoptotic genes, and downregulation of cell survival genes. When this paper was released, there were no known studies that conducted RNA sequencing on COVID-19 patient pancreatic samples. Yang et al. decided to compare the RNA sequences of COVID-19 patient lung autopsy samples. An upregulation of chemokine and cytokine genes was seen (Figure 3H) (1). Overall, Similar to patient lung autopsy samples, chemokine and cytokine transcripts were elevated compared to the mock-infected conditions for hPSC derived pancreatic endocrine cells (9).

Figure 3H: Heatmap of chemokine transcript levels in SARS-CoV-2-infected hPSC-derived pancreatic endocrine cell cells compared to mock infection. n=3 independent biological replicates. Data were presented as mean ± SD. p values were calculated by unpaired two-tailed Student’s t test. ***p < 0.001.

Image 5: Cytokine profiles of COVID-19 patients. Sera of 24 COVID-19 patients and 24 SARS-CoV-2-negative controls were analyzed by ELISA for the protein levels of a broad panel of cytokines. The dotted line depicts the limit of detection. Statistical significance was calculated by Mann-Whitney non-parametric t test. NS, non-significant; ∗p < 0.05, ∗∗p < 0.005, ∗∗∗p < 0.0001 (9).

To further the research, it was found that adult liver hepatocyte and cholangiocyte organoids are permissive to SARS-CoV-2 pseudo-entry virus infection and showed similar chemokine responses for SARS-CoV-2 infection as the autopsy samples from COVID-19 patients (1).

In Figure S4A, the hepatocyte organoids were infected with SARS-CoV-2 pseudo-entry virus at a multiplicity of infection (MOI), or virions per cell, of 0.1. At 24 hpi, there was a significant increase in LUC activity in the infected samples. LUC expression was detected in SARS-CoV-2 pseudo-entry virus-infected ALB+ hepatocytes but not mock-infected hepatocytes (Figures S4B and S4C). The same results were seen for CK19+ cholangiocyte organoids (Figures S4D and S4E) (1).

Figure S4A: Luciferase activity in adult human hepatocyte organoids infected with SARS-CoV-2 pseudo-entry virus. Figures S4B and S4C: Luciferase activity in ALB+ hepatocytes. Figures S4D and S4E: Luciferase activity in CK19+ cholangiocytes.

In Figure 4A, adult primary human hepatocyte organoids were infected with SARS-CoV-2 and analyzed at 24 hpi via qRT-PCR, and it showed robust infected due to the high levels of viral sgRNA transcripts of the replicating viral RNA. Immunostaining of SARS-CoV-2 Spike protein expression was used to confirm the results seen above at the protein level (Figure 4B). There was also a higher amount of SARS-S+ cells seen in the infected hepatocyte organoids (Figure 4C) (1).

Figure 4A: qRT-PCR analysis of adult human hepatocyte organoids infected with SARS-CoV-2. Figure 4B and Figure 4C: Confocal imaging (B) and quantification (C) of human hepatocyte organoids.

Primary human organoids were created that consisted mostly of cholangiocytes. These organoids were also infected with SARS-CoV-2 and analyzed at 24 hpi via qRT-PCR, which showed robust SARS-CoV-2 infection (Figure 4D). This was also confirmed by immunostaining (Figure 4E). There was also a high amount of SARS-S+ cells in the infected cholangiocyte organoids (Figure 4F) (1).

Figure 4D: qRT-PCR analysis of adult human cholangiocyte organoids infected with SARS-CoV-2. Figure 4E and Figure 4F: Confocal imaging (E) and quantification (F) of human hcholagiocyte organoids.

Transcript profiles were compared between mock and SARS-CoV-2-infected human primary hepatocyte and cholangiocyte organoids. Alignment with the viral genome confirmed robust replication in both hepatocyte organoids (Figure 4G) and cholangiocyte organoids (Figure 4H). PCA was then used which showed the distinction between mock-infected and SARS-CoV-2-infected hepatocyte organoids (Figure 4I) (1).

Figure 4G: Read coverage of the SARS-CoV-2 genome in infected human hepatocyte organoids. Figure 4H: Read coverage of the SARS-CoV-2 genome in infected human cholangiocyte organoids. Figure 4I: PCA analysis of differential expressed genes in SARS-CoV-2 infected human hepatocyte organoids.

In Figure 4J and Figure S4F, volcano plots and heat-maps were created for differentially expressed genes in SARS-CoV-2 infected hepatocyte organoids compared to mock infection. These revealed robust induction of chemokines including CXCL1, CXCL3, CXCL5, CXCL6, and CCL20. There was downregulation of key hepatocyte metabolic markers, such as CYP7A1, CYP2A6, CYP1A2, and CYP2D6 (1).

Figure 4J: Volcano plot analysis of differential expressed genes in SARS-CoV-2-infected human hepatocyte organoids. Figure S4F: Heatmap of differential expressed genes in SARS-CoV-2 infected human hepatocyte organoids

After, mock-infected with SARS-CoV-2 infected hepatocyte organoids were compared via KEGG gene set enrichment analysis (GSEA) which revealed over-represented and upregulated pathways, including cytokine-cytokine receptor interaction, IL-17 signaling, chemokine signaling pathway, TNF signal, and NF-kB signaling pathways. However, cellular metabolism was downregulated (Figure 4K) (1).

Figure 4K: KEGG gene set enrichment analysis of transcript profiles from SARS-CoV-2 infected hepatocyte organoids.

PCA also showed that mock and SARS-CoV-2-infected cholangiocyte organoid transcript profiles clustered separately (Figures 4L and S4G). A robust induction of chemokines, including, CXCL1, CXCL2, CXCL3, and CCL2 was seen. Volcano plot and heatmap analysis of these changes in gene expression in SARS-CoV-2-infected cholangiocyte organoids was seen in Figure 4M and S4H (1).

Figures 4L and S4G: PCA analysis of differential expressed genes in SARS-CoV-2-infected human cholangiocyte organoids. Figures 4M and S4H: Volcano plot (M) and heat map (S4H) analysis of differential expressed genes in SARS-CoV-2-infected human cholangiocyte organoids.

In Figure 4N, KEGG GSEA was used to compare mock-infected with SARS-CoV-2-infected cholangiocyte organoids, which revealed the upregulation of inflammatory pathways, including cytokine-cytokine receptor interaction and IL-17 signaling. This is consistent with previous findings in COVID-19 lung autopsy samples (1).

Figure 4N: KEGG gene set enrichment analysis of transcript profiles from SARS-CoV-2 infected cholangiocyte organoids.

qRT-PCR analysis of SARS-CoV-2 infected hPSC-derived cardiomyocytes, dopaminergic neurons, macrophages, microglia, and cortical neurons showed high levels of viral sgRNA in cardiomyocytes (Figure S4I) and dopaminergic neurons (Figure S4J). In addition, low or no level of viral sgRNA was detected in cortical neurons (Figure S4K), microglia (Figure S4L), and macrophages (Figure S4M). This is all consistent with data from pseudo-entry virus infections (1).

Figures S4I to S4M: qRT-PCR analysis of sgRNA expression in hPSC-derived cardiomyocytes (I), dopaminergic neurons (J), cortical neurons (K), microglia (L), and macrophages (M), infected with SARS-CoV-2.

The authors also used adult liver organoids to confirm the permissiveness of hepatocytes and cholangiocytes to SARS-CoV-2 virus infection. The liver is of particular interest as it is susceptible to many viral pathogens such as hepatitis A, B, C, D, and E, herpes simplex virus family members, and cytomegalovirus. Half of the COVID-19 patients have evidence of viral hepatitis as SARS-CoV-2 virus was recently shown to infect liver ductal organoids which caused increased cell death (1).

In conclusion, the purpose of the paper, “A Human Pluripotent Stem Cell-based Platform to Study SARS-CoV-2 Tropism and Model Virus Infection in Human Cells and Organoids” by Yang et al., was to discover a physiologically relevant human model to study SARS-CoV-2 infection. A library of hPSC-derived cells/organoids was generated to evaluate their permissiveness to infection. A SARS-CoV-2 pseudo-entry virus was found to infect pancreatic endocrine cells, liver organoids, cardiomyocytes, and dopaminergic neurons. In particular, hepatic and pancreatic cells were highly permissive to infection, which was further validated using adult primary human islets, adult hepatic and cholangiocyte organoids, and a humanized mouse model. Transcript profiling of these cells revealed similar upregulation of chemokine expression as seen in primary human COVID-19 pulmonary autopsy samples. hPSC-derived cells/organoids offer a model for studying cell responses to infection and for diseases modelling of COVID-19 (1).

Organoid models are important for studying SARS-CoV-2 because organoid models have the potential to effectively recapitulate viral infection in live tissue. Common cell lineages lack components of the viral infection process. For example, Vero Cells, which are a common cell lineage isolated from monkey kidneys, do not secrete interferon-alpha or beta during viral infection. In addition, human cancer cell lineages have tumour-associated mutations with p53 that can affect viral replication differently from normal tissue. Overall, these differences can create difficulties in modeling SARS-CoV-2 infection. This would necessitate the use of a different model to identify disease-relevant tissues and their responses to infection. Thus, human embryonic or induced stem cells can be used to recreate the tissue needed to model the disease condition. These cells can be put through previously discovered differentiation protocols to be differentiated into stem cells and organoid structures. Since organoids have been used in the past to recreate disease processes, they can be used to understand the COVID-19 symptom complex, complications with comorbidity, and potential treatments (!).

Yang et al. showed permissiveness of multiple cell types to SARS-CoV-2 virus. However, whether or not some of these cells are major targets of viral infection in COVID-19 will not be clear without a more thorough analysis of primary patient-derived samples. In the paper, there was a focus on viral entry and to some extent replication, but there may be cell lineage differences for viral release and secondary infection that needs to be further explored. Cell and organoid-based models are a good first step towards modeling COVID-19, but these models are simplified compared to fully functioning and interacting adult human organs. In the future, more complex organoid models can be made, along with incorporating the analysis of immune system components that were missing in the paper (1).

There is an urgent need to create disease-relevant models to study SARS-CoV-2 pathology and facilitate drug screening. In particular, inhibitors to combat viral hepatitis as a result of SARS-CoV-2 virus using liver organoids could be further investigated.

It is also pertinent to study patients both at high risk for or have type 1 and type 2 diabetes previously infected with or are infected by COVID-19. This is necessary to evaluate the contribution of SARS-CoV-2 to progression toward type 1 or type 2 diabetes.

View slides here.

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(2) VIVO Project. Liuliu Yang Postdoctoral Associate in Surgery https://vivo.weill.cornell.edu/display/cwid-liy4003 (accessed Feb 28, 2021).

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(9) Blanco-Melo, D.; Nilsson-Payant, B. E.; Liu, W. C.; Uhl, S.; Hoagland, D.; Møller, R.; Jordan, T. X.; Oishi, K.; Panis, M.; Sachs, D.; et al. Imbalanced Host Response to SARS-CoV-2 Drives Development of COVID-19. Cell 2020, 181 (5), 1036-1045.e9. https://doi.org/10.1016/j.cell.2020.04.026.