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SCIENCE CHINA Life Sciences, https://doi.org/10.1007/s11427-021-1990-5

Genome-wide CRISPR activation screen identifies candidate receptors for SARS-CoV-2 entry

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  • ReceivedMay 28, 2021
  • AcceptedAug 6, 2021
  • PublishedAug 20, 2021

Abstract


Funded by

funds from the National Key R&D Program of China(2020YFA0707800,to,W.W.,2020YFA0707600,to,Z.Z.)

Beijing Municipal Science & Technology Commission(Z181100001318009)

the National Natural Science Foundation of China(31930016)

Beijing Advanced Innovation Center for Genomics at Peking University and the Peking-Tsinghua Center for Life Sciences(to,W.W.)

the National Natural Science Foundation of China(31870893)

the National Major Science & Technology Project for Control and Prevention of Major Infectious Diseases in China(2018ZX10301401,to,Z.Z.)

and China Postdoctoral Science Foundation(2020M670031,to,Y.L.)


Acknowledgment

We acknowledge the National Center for Protein Sciences (Beijing) at Peking University for their assistance with fluorescence-activated cell sorting and SPR measurements, particularly Dr. Jia Luo, Ms Huan Yang, Ms Liying Du and Ms Hui Li for their technical help. We acknowledge Dr. Ying Yu (Peking University) for her assistance in preparing the NGS library. This project was supported by funds from the National Key R&D Program of China (2020YFA0707800 to W.W., 2020YFA0707600 to Z.Z.), Beijing Municipal Science & Technology Commission (Z181100001318009), the National Natural Science Foundation of China (31930016), Beijing Advanced Innovation Center for Genomics at Peking University and the Peking-Tsinghua Center for Life Sciences (to W.W.), the National Natural Science Foundation of China (31870893), the National Major Science & Technology Project for Control and Prevention of Major Infectious Diseases in China (2018ZX10301401 to Z.Z.), and China Postdoctoral Science Foundation (2020M670031 to Y.L.).


Interest statement

The author(s) declare that they have no conflict of interest.


Supplement

SUPPORTING INFORMATION

The supporting information is available online at https://doi.org/10.1007/s11427-021-1990-5. The supporting materials are published as submitted, without typesetting or editing. The responsibility for scientific accuracy and content remains entirely with the authors.


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  • Figure 1

    Identification of candidate factors for SARS-CoV-2 entry by a genome-wide CRISPRa gain-of-function screen in HEK293T cells. A, Detection of the pseudovirus infection in HEK293T-CRISPRa cells transfected with different sgRNAs targeting ACE2. The infection rate of SARS-CoV-2 pseudovirus is indicated by the percentage of EGFP-positive cells. Wild type/cDNAACE2 represents the wild type HEK293T cells transfected with ACE2 cDNA as a positive control. B, Schematic diagram of an sgRNA with an external barcode (eBAR). Three 4-nt eBARs were respectively embedded outside of the sgRNA scaffold after the poly-U signal. C, Schematic of the CRISPRa screen in HEK293T cells using the SARS-CoV-2 pseudotyped virus. D, FACS selection of EGFP+ cells grouping based on different fluorescence intensities after SARS-CoV-2 pseudovirus infection. Left indicates the total EGFP intensity of HEK293T-CRISPRa library cells after the second round of pseudovirus infection. Right indicates three additional sorting gates including the top 10%–20%, top 10% and top 2% of the total EGFP+ cells. E–H, Robust rank aggregation (RRA) scores of all genes from the total EGFP+ (E), top 10%–20% (F), top 10% (G) and top 2% (H) of the total EGFP+ cells. RRA scores were used to evaluate the enrichment of candidate genes, which were calculated by binomial P-values of sgRNAseBAR targeting each gene. Membrane proteins were labelled as red dots, proteases were labelled as blue dots, the genes that are both membrane protein and proteases were labelled as purple dots. Grey and black dots represent other types of genes and negative controls.

  • Figure 2

    Host factors identified from CRISPRa library screening. A, Gene Ontology (GO) enrichment analysis was conducted using all the significant candidates (RRA score <0.001) identified in the four groups. Hypergeometric test was used to calculate all the P-values. The top-enriched GO terms were selected for visualization. The x axis represents the number of genes identified in the specific GO terms. A complete list of genes in each GO term is in Table S3 in Supporting Information. B, The performance of all the significant hits in four screening groups (top 2%, top 10%, top 10%–20% of EGFP intensity and total EGFP+). The gene with a smaller value of normalized rank (in redder colour) represented a higher enrichment in the relevant groups. C, Expression patterns of identified candidates within human tissues. The data used for analysis were retrieved from the Human Protein Atlas normalized expression.

  • Figure 3

    Validation of candidate genes identified from CRISPRa library screening. A and B, Effects of identified genes on the infection of SARS-CoV-2. A, 51 individual cDNAs and an empty vector were transfected into HEK293T cells. Then the cells were treated with luciferase-labelled SARS-CoV-2 pseudotyped virus. The entry of SARS-CoV-2 pseudotyped virus was quantified through measuring luciferase activity 48 h later. The luciferase activities were normalized by the empty vector. Data are presented as the mean±SD (n=2). B, The cDNAs of candidate genes were introduced into HEK293T cells lentivirally labelled with an mCherry marker. The mCherry-positive cells were enriched through FACS followed by infection with authentic SARS-CoV-2 virus at an MOI of 0.5. SARS-CoV-2 RNAs were quantified by real-time qPCR and normalized by GAPDH. Data were presented as the mean±SD (n=3). C and D, Effects of identified genes on the infection of SARS-CoV-2 in ACE2–/– cells. C, The cDNAs were transfected into HEK293T ACE2–/– cells. Then the cells were treated with 10-fold concentrated SARS-CoV-2 pseudotyped virus. The entry of pseudotyped virus was quantified through measuring luciferase activity and was normalized by the empty vector. D, The cDNAs of candidate genes were introduced into HEK293T ACE2–/– cells lentivirally. Cells were enriched through FACS followed by infection with authentic SARS-CoV-2 virus at an MOI of 0.5. SARS-CoV-2 RNAs were quantified by real-time qPCR and normalized by GAPDH. Data were presented as the mean±SD (n=3). P values were calculated using Student’s t test, *P<0.05; **P<0.01; ***P<0.001; ns, not significant.

  • Figure 4

    Direct binding of LDLRAD3, CLEC4G and TMEM30A to SARS-CoV-2 S. A, Co-IP of SARS-CoV-2 S6P spike with FLAG-tagged proteins in HEK293T cells transfected with Flag-cDNA constructs and SARS-CoV-2 S. Immunoblot analysis was conducted using anti-Flag and anti-spike antibodies. B, In vitro pull-down assay of purified ACE2, CLEC4G and LDLRAD3 to SARS-CoV-2 S. Strep-tagged SARS-CoV-2 S and FLAG-tagged full-length candidate receptors were expressed in HEK293T cells and affinity-purified. Immunoblot analysis was conducted using anti-Flag and anti-Strep antibodies. C and D, In vitro pull-down assay of purified ACE2, CLEC4G, LDLRAD3 and TMEM30A to the NTD (C) or RBD (D) of SARS-CoV-2 S. Immunoblot analysis was conducted using anti-Flag and anti-His antibodies. E, Surface plasmon resonance (SPR) measurements for the dynamic binding between candidate receptors and SARS-CoV-2 S. Purified extracellular domain of ACE2, full-length of LDLRAD3 and CLEC4G (0.03125, 0.0625, 0.125, 0.25, 0.5 and 1 μmol L–1) were tested.

  • Figure 5

    Inhibition of soluble proteins on SARS-CoV-2 infection. A and B, Effects of purified ACE2 on SARS-CoV-2 infection in SH-SY5Y (A) and SK-N-SH (B) cells. C and D, Effects of purified LDLRAD3 on SARS-CoV-2 infection in SH-SY5Y (C) and SK-N-SH (D) cells. E and F, Effects of purified ACE2 (E) and CLEC4G (F) on SARS-CoV-2 infection in Huh7.5 cells. The soluble proteins (0, 12.5, 25, 50 and 100 μg mL–1) were incubated with authentic SARS-CoV-2 virus for 1 h. Infection was performed at an MOI of 0.5. SARS-CoV-2 RNAs were quantified by real-time qPCR and normalized by GAPDH. Data were presented as the mean±SD (n=3). P values were calculated using Student’s t test, *P<0.05; **P<0.01; ***P<0.001; ns, not significant.

  • Figure 6

    Examination of the interaction between SARS-CoV-2 S protein and candidate receptors by syncytium formation assay. Spike-EGFP represents the HEK293T cells transfected with SARS-CoV-2 S protein and an EGFP marker. Receptor-mCherry represents the HEK293T cells stably overexpressed with the known and candidate receptors labelled with an mCherry marker, labeled as HEK293T-ACE2, HEK293T-CLEC4G, HEK293T-LDLRAD3 and HEK293T-TMEM30A. HEK293T cells infected with the cDNA-expressing vector, labelled as HEK293T-vector, was served as the control. Merge indicates the co-localization of the two categories of cells through merging the EGFP and mCherry fluorescence channels by ImageJ. The images were taken 40 h after co-culturing the two categories of cells. Scale bar, 100 μm.

  • Figure 7

    Loss-of-function effects of identified receptors on SARS-CoV-2 infection. A, Expression of identified host factors relative to ACE2 in SH-SY5Y cells. B–D, Suppression of ACE2 (B), LDLRAD3 (C) and TMEM30A (D) by siRNAs in SH-SY5Y cells. E, Effects of suppression of candidate receptors by siRNAs on SARS-CoV-2 infection in SH-SY5Y cells. Infection was performed at an MOI of 0.5. F, Expression of identified host genes relative to ACE2 in SK-N-SH cells. G and H, Suppression of LDLRAD3 (G) and TMEM30A (H) by siRNAs in in SK-N-SH cells. I, Effects of suppression of candidate genes by siRNAs on SARS-CoV-2 infection in SK-N-SH cells. Infection was performed at an MOI of 0.5. J, Expression of identified host genes relative to ACE2 in Huh7.5 cells. K and L, Suppression of ACE2 (K) and CLEC4G (L) by siRNAs in in Huh7.5 cells. M, Effects of suppression of candidate genes by siRNAs on SARS-CoV-2 infection in Huh7.5 cells. Infection was performed at an MOI of 0.5. For all these experiments, a total of 20 pmol for each siRNA was transfected into cells. The relative mRNA abundance was quantified 48 h post transfection. Ctrl RNA: Random non-targeting siRNA. RNA abundance of host factors and SARS-CoV-2 were quantified by real-time qPCR and normalized by GAPDH. Data were presented as the mean±SD (n=3). P values were calculated using Student’s t test, *P<0.05; **P<0.01; ***P<0.001; ns, not significant. All siRNAs used for gene suppression are listed in Table S4 in Supporting Information, and primers used for real-time qPCR are listed in Table S5 in Supporting Information.

  • Figure 8

    Expression of candidate receptors in nasopharyngeal samples from COVID-19 patients correlates with SARS-CoV-2 infection. A–D, Evaluation of the co-expression between SARS-CoV-2 and ACE2 (A), LDLRAD3 (B), CLEC4G (C) or TMEM30A (D) from COVID-19 patients at the single-cell level. E, The percentage of SARS-CoV-2 entry in single cells with/without expression of each candidate gene. F, Evaluation of the co-expression between SARS-CoV-2 and each candidate gene in different cell types from COVID-19 patients at the single-cell level. The P value shown in each figure (A–D, F) was calculated by the Fisher test to evaluate the significance of co-expression between SARS-CoV-2 and each candidate receptor.

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