Genome-Scale Identification of SARS-CoV-2 and Pan-coronavirus Host Factor Networks

Abstract

The coronavirus disease 2019 (COVID-19) pandemic has claimed the lives of over one million people worldwide. The causative agent, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a member of the Coronaviridae family of viruses that can cause respiratory infections of varying severity. The cellular host factors and pathways co-opted during SARS-CoV-2 and related coronavirus life cycles remain ill defined. To address this gap, we performed genome-scale CRISPR knockout screens during infection by SARS-CoV-2 and three seasonal coronaviruses (HCoV-OC43, HCoV-NL63, and HCoV-229E). These screens uncovered host factors and pathways with pan-coronavirus and virus-specific functional roles, including major dependency on glycosaminoglycan biosynthesis, sterol regulatory element-binding protein (SREBP) signaling, bone morphogenetic protein (BMP) signaling, and glycosylphosphatidylinositol biosynthesis, as well as a requirement for several poorly characterized proteins. We identified an absolute requirement for the VMP1, TMEM41, and TMEM64 (VTT) domain-containing protein transmembrane protein 41B (TMEM41B) for infection by SARS-CoV-2 and three seasonal coronaviruses. This human coronavirus host factor compendium represents a rich resource to develop new therapeutic strategies for acute COVID-19 and potential future coronavirus pandemics.

Keywords: COVID-19; CRISPR; HCoV-229E; HCoV-NL63; HCoV-OC43; SARS-CoV-2; TMEM41B; coronavirus; genetic screens; host factors.

Graphical abstract

Figure 1

Genome-wide CRISPR Screens Identify Host Factors Required for SARS-CoV-2 Infection (A) Genome-wide CRISPR screening workflow. Cas9-expressing Huh-7.5 cells are transduced with the Brunello genome-wide CRISPR library, selected with puromycin, and infected with SARS-CoV-2 or one of three seasonal CoVs (HCoV-OC43, HCoV-NL63, or HCoV-229E). Surviving cells and mock controls are then harvested, and sgRNA abundance is determined using next-generation sequencing. (B) Bubble plot of data from SARS-CoV-2 screens at 37°C. Red lines denote z = ±2. (C) Bubble plot of data from SARS-CoV-2 screens at 33°C. Red lines denote z = ±2. (D) Scatterplot comparing Z scores from (B) and (C) for SARS-CoV-2 screens at 37°C and 33°C, respectively. (E) Subset of significantly enriched genes from SARS-CoV-2 screens at 37°C and 33°C.

Figure S1

Screen QC Data, Related to Figures 1 and 2 (A) Species accumulation curve for unique reads with ≥ 10 counts. (B) Heatmap for correlation coefficients between samples. (C) ROC curves for each screen. (D) Area under the curve (AUC) for each ROC curve in (C).

Figure S2

Analysis of Established and Putative CoV Host Factors and Gene-wise Fitness Scores for SARS-CoV-2 and 3 Seasonal CoVs, Related to Figures 1 and 2 (A) Heatmap of z-scores for known and putative coronavirus host factors. (B-D) Genewise fitness beta scatterplots comparing SARS-CoV-2 at 37°C versus mock (B), SARS-CoV-2 at 33°C versus mock (C), and SARS-CoV-2 at 33°C versus SARS-CoV-2 at 37°C (D). Non-targeting controls and essential control genes are highlighted in blue and red, respectively. (E) HCoV-OC43 versus mock infected. (F) HCoV-NL63 versus mock infected. (G) HCoV-229E versus mock infected.

Figure 2

Parallel Genome-wide CRISPR Screening against Multiple HCoVs Uncovers Host Factors and Pathways with Pan-CoV and Virus-Specific Functional Roles (A) Bubble plot of data from HCoV-OC43 screens at 33°C. Red lines denote z = ±2. (B) Bubble plot of data from HCoV-NL63 screens at 33°C. Red lines denote z = ±2. (C) Bubble plot of data from HCoV-229E screens at 33°C. Red lines denote z = ±2. (D) UpSet plot showing enriched hits overlapping in screens across all four viruses. Select genes for enriched sgRNAs are indicated.

Figure 3

CoVs Co-opt an Extensive Network of Human Proteins and Pathways to Complete Their Life Cycles (A) Network analysis of human CoV host factors for all significant screening hits using the STRING-db protein:protein interaction network. Nodes are subdivided by number of virus screens by color and size for which the node was significant. Highly interconnected and functionally related genes are further highlighted in gray. (B–G) Comparative pathway-focused heatmaps showing enriched and depleted sgRNAs across all CRISPR screens.

Figure S3

Expanded CoV-Specific Networks, Related to Figure 3 (A–D) Network diagram of all coronavirus screen hits and the next 100 adjacent interactors, shown in gray. Broad functional categories of highly interconnected gene neighborhoods are indicated. Diagrams are for SARS-CoV-2 (A), HCoV-OC43 (B), HCoV-NL63 (C) and HCoV-229E (D).

Figure S4

Additional Enriched Pathways and Subset Analysis of a High-Confidence SARS-CoV-2 Protein:Protein Interactome, Related to Figure 3 (A) Heatmap of z-scores for the cholesterol biosynthesis gene set. (B) Heatmap of z-scores for the mediator complex gene set. (C) Heatmap of z-scores for the endoplasmic reticulum membrane complex gene set. (D) Subset analysis of absolute z-scores for SARS-CoV-2 screen at 37°C for the Gordon et al. high-confidence interactome and the Hoffmann et al., functional interactome. Whiskers represent the range, bar represents median, box represents first and third quartiles. Significance tests are two-sided Wilcoxon rank sum test. (E) Heatmap of z-scores from functional interactome hits in Hoffmann et al. subsetted from genome-scale CRISPR screens.

Figure 4

Validation of High-Confidence Coronaviridae Host Factors (A) Candidate validation in Huh-7.5 cells with SARS-CoV-2 infection at 33°C. (B) Candidate validation in Huh-7.5 cells with HCoV-OC43 infection at 33°C. (C) Candidate validation in Huh-7.5 cells with HCoV-NL63 at 33°C. (D) Candidate validation in Huh-7.5 cells with HCoV-229E at 37°C. (E) Heatmap representation of data from (A)–(D). The SARS-CoV-2 and HCoV-NL-63 receptor (ACE2) and the HCoV-229E receptor (ANPEP) are shown separately.

Figure 5

TMEM41B Is a Pan-CoV Host Factor (A) Heatmap of genes from the autophagy pathway, ordered sequentially by function in the autophagy cascade. (B) Comparative analysis of Zika virus and SARS-CoV-2 screens by log2 fold change (LFC). (C) CoV infectivity assay in parental Huh-7.5 cells, clonal TMEM41B knockout cells, and TMEM41B knockout cells reconstituted with TMEM41B cDNA. (D) CoV infectivity assay in parental A549_ACE2/TMPRSS2 cells, clonal TMEM41B knockout cells, and TMEM41B knockout cells reconstituted with TMEM41B cDNA. (E) Quantitative PCR analysis of the levels of three SARS-CoV-2 RNA transcripts in parental Huh-7.5 cells, clonal TMEM41B knockout cells, and TMEM41B knockout cells reconstituted with TMEM41B cDNA. Error bars represent standard deviation (SD). (F) Measurement of SARS-CoV-2 replication in Huh-7.5 TMEM41B knockout cells and TMEM41B knockout cells reconstituted with TMEM41B cDNA electroporated with RNA of SARS-CoV-2 expressing NanoLuc. Measurements were performed 18 h post-electroporation and are expressed in relative luciferase units (RLUs) normalized to reconstituted knockout cells. (G) Fluorescence microscopy images of SARS-CoV-2 immunostaining (green), tagRFP-TMEM41B (red), and DNA (DAPI) in parental Huh-7.5 and A549_ACE2/TMPRSS2 cells, clonal TMEM41B knockout cells, and TMEM41B knockout cells reconstituted with TMEM41B cDNA. Scale bars, 30 μm.

Figure S5

A Majority of Functional CoV Host Factors Are Expressed in the Airway, Related to Figures 1, 2, and 3 (A–D) scRNaseq expression dotplot diagrams from select cells in the airway of the average expression and the percent of cells expressing coronavirus host factors for SARS-CoV-2 (A), HCoV-OC43 (B), HCoV-NL63 (C) and HCoV-229E (D). Rows for each diagram are ordered top to bottom from highest to lowest z-score. Data are from Chua et al. (2020).