. 2018 Dec 13;175(7):1931-1945.e18.

doi: 10.1016/j.cell.2018.11.028.

Comparative Flavivirus-Host Protein Interaction Mapping Reveals Mechanisms of Dengue and Zika Virus Pathogenesis

Priya S Shah¹, Nichole Link², Gwendolyn M Jang³, Phillip P Sharp⁴, Tongtong Zhu⁵, Danielle L Swaney³, Jeffrey R Johnson³, John Von Dollen³, Holly R Ramage⁶, Laura Satkamp³, Billy Newton³, Ruth Hüttenhain³, Marine J Petit⁷, Tierney Baum⁸, Amanda Everitt⁸, Orly Laufman⁹, Michel Tassetto⁹, Michael Shales³, Erica Stevenson³, Gabriel N Iglesias¹⁰, Leila Shokat³, Shashank Tripathi¹¹, Vinod Balasubramaniam¹², Laurence G Webb⁵, Sebastian Aguirre¹¹, A Jeremy Willsey¹³, Adolfo Garcia-Sastre¹⁴, Katherine S Pollard¹⁵, Sara Cherry⁶, Andrea V Gamarnik¹⁰, Ivan Marazzi¹⁶, Jack Taunton¹⁷, Ana Fernandez-Sesma¹⁸, Hugo J Bellen¹⁹, Raul Andino²⁰, Nevan J Krogan²¹

Affiliations

¹ Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, USA; Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA, USA; Quantitative Biosciences Institute (QBI), University of California San Francisco, San Francisco, CA, USA; The J. David Gladstone Institutes, San Francisco, CA, USA.
² Department of Molecular and Human Genetics, and Program in Developmental Biology, Baylor College of Medicine, Houston, TX, USA; Jan and Dan Duncan Neurological Research Institute, Houston, TX, USA; Howard Hughes Medical Institute, Baylor College of Medicine, Houston, TX, USA.
³ Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, USA; Quantitative Biosciences Institute (QBI), University of California San Francisco, San Francisco, CA, USA; The J. David Gladstone Institutes, San Francisco, CA, USA.
⁴ Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, USA.
⁵ Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
⁶ Department of Microbiology, University of Pennsylvania, Philadelphia, PA, USA.
⁷ Department of Chemical Engineering, Department of Microbiology and Molecular Genetics, University of California Davis, Davis, CA, USA.
⁸ Institute for Neurodegenerative Diseases, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA.
⁹ Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA, USA.
¹⁰ Fundación Instituto Leloir-CONICET, Buenos Aires, Argentina.
¹¹ Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
¹² Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Selangor, Malaysia.
¹³ Quantitative Biosciences Institute (QBI), University of California San Francisco, San Francisco, CA, USA; Institute for Neurodegenerative Diseases, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA; Department of Psychiatry, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA.
¹⁴ Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Medicine, Division of Infectious Diseases, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
¹⁵ Quantitative Biosciences Institute (QBI), University of California San Francisco, San Francisco, CA, USA; The J. David Gladstone Institutes, San Francisco, CA, USA; Department of Epidemiology and Biostatistics, Institute for Human Genetics, and Institute for Computational Health Sciences, University of California San Francisco, San Francisco, CA, USA; Chan-Zuckerberg Biohub, San Francisco, CA, USA.
¹⁶ Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
¹⁷ Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, USA; Quantitative Biosciences Institute (QBI), University of California San Francisco, San Francisco, CA, USA.
¹⁸ Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Medicine, Division of Infectious Diseases, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
¹⁹ Department of Molecular and Human Genetics, and Program in Developmental Biology, Baylor College of Medicine, Houston, TX, USA; Jan and Dan Duncan Neurological Research Institute, Houston, TX, USA; Howard Hughes Medical Institute, Baylor College of Medicine, Houston, TX, USA. Electronic address: hbellen@bcm.edu.
²⁰ Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA, USA. Electronic address: raul.andino@ucsf.edu.
²¹ Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, USA; Quantitative Biosciences Institute (QBI), University of California San Francisco, San Francisco, CA, USA; The J. David Gladstone Institutes, San Francisco, CA, USA. Electronic address: nevan.krogan@ucsf.edu.

PMID: 30550790
PMCID: PMC6474419
DOI: 10.1016/j.cell.2018.11.028

Comparative Flavivirus-Host Protein Interaction Mapping Reveals Mechanisms of Dengue and Zika Virus Pathogenesis

Priya S Shah et al. Cell. 2018.

. 2018 Dec 13;175(7):1931-1945.e18.

doi: 10.1016/j.cell.2018.11.028.

Authors

Affiliations

¹ Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, USA; Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA, USA; Quantitative Biosciences Institute (QBI), University of California San Francisco, San Francisco, CA, USA; The J. David Gladstone Institutes, San Francisco, CA, USA.
² Department of Molecular and Human Genetics, and Program in Developmental Biology, Baylor College of Medicine, Houston, TX, USA; Jan and Dan Duncan Neurological Research Institute, Houston, TX, USA; Howard Hughes Medical Institute, Baylor College of Medicine, Houston, TX, USA.
³ Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, USA; Quantitative Biosciences Institute (QBI), University of California San Francisco, San Francisco, CA, USA; The J. David Gladstone Institutes, San Francisco, CA, USA.
⁴ Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, USA.
⁵ Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
⁶ Department of Microbiology, University of Pennsylvania, Philadelphia, PA, USA.
⁷ Department of Chemical Engineering, Department of Microbiology and Molecular Genetics, University of California Davis, Davis, CA, USA.
⁸ Institute for Neurodegenerative Diseases, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA.
⁹ Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA, USA.
¹⁰ Fundación Instituto Leloir-CONICET, Buenos Aires, Argentina.
¹¹ Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
¹² Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Selangor, Malaysia.
¹³ Quantitative Biosciences Institute (QBI), University of California San Francisco, San Francisco, CA, USA; Institute for Neurodegenerative Diseases, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA; Department of Psychiatry, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA.
¹⁴ Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Medicine, Division of Infectious Diseases, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
¹⁵ Quantitative Biosciences Institute (QBI), University of California San Francisco, San Francisco, CA, USA; The J. David Gladstone Institutes, San Francisco, CA, USA; Department of Epidemiology and Biostatistics, Institute for Human Genetics, and Institute for Computational Health Sciences, University of California San Francisco, San Francisco, CA, USA; Chan-Zuckerberg Biohub, San Francisco, CA, USA.
¹⁶ Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
¹⁷ Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, USA; Quantitative Biosciences Institute (QBI), University of California San Francisco, San Francisco, CA, USA.
¹⁸ Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Medicine, Division of Infectious Diseases, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
¹⁹ Department of Molecular and Human Genetics, and Program in Developmental Biology, Baylor College of Medicine, Houston, TX, USA; Jan and Dan Duncan Neurological Research Institute, Houston, TX, USA; Howard Hughes Medical Institute, Baylor College of Medicine, Houston, TX, USA. Electronic address: hbellen@bcm.edu.
²⁰ Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA, USA. Electronic address: raul.andino@ucsf.edu.
²¹ Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, USA; Quantitative Biosciences Institute (QBI), University of California San Francisco, San Francisco, CA, USA; The J. David Gladstone Institutes, San Francisco, CA, USA. Electronic address: nevan.krogan@ucsf.edu.

PMID: 30550790
PMCID: PMC6474419
DOI: 10.1016/j.cell.2018.11.028

Abstract

Mosquito-borne flaviviruses, including dengue virus (DENV) and Zika virus (ZIKV), are a growing public health concern. Systems-level analysis of how flaviviruses hijack cellular processes through virus-host protein-protein interactions (PPIs) provides information about their replication and pathogenic mechanisms. We used affinity purification-mass spectrometry (AP-MS) to compare flavivirus-host interactions for two viruses (DENV and ZIKV) in two hosts (human and mosquito). Conserved virus-host PPIs revealed that the flavivirus NS5 protein suppresses interferon stimulated genes by inhibiting recruitment of the transcription complex PAF1C and that chemical modulation of SEC61 inhibits DENV and ZIKV replication in human and mosquito cells. Finally, we identified a ZIKV-specific interaction between NS4A and ANKLE2, a gene linked to hereditary microcephaly, and showed that ZIKV NS4A causes microcephaly in Drosophila in an ANKLE2-dependent manner. Thus, comparative flavivirus-host PPI mapping provides biological insights and, when coupled with in vivo models, can be used to unravel pathogenic mechanisms.

Keywords: ANKLE2; Drosophila; PAF1C; Sec61; Zika virus; dengue virus; endoplasmic reticulum; flavivirus; interferon stimulated genes; microcephaly; proteomics.

PubMed Disclaimer

Conflict of interest statement

Declaration of Interests

J.T. is a cofounder and shareholder of Global Blood Therapeutics, Principia Biopharma, Kezar Life Sciences, and Cedilla Therapeutics. J.T. and P.P.S. are listed as inventors on a provisional patent application describing PS3061. All other authors declare no conflicts of interest.

Figures

**Figure 1:. Summary of the DENV-human protein-protein interaction network.**
(A) Overall pipeline for the integrated AP-MS and RNAi approach to define DENV-human PPIs. (B) Schematic of RNAi screening approach. (C) RNAi knockdown efficiency for 37 genes measured by RT-qPCR. (D) Summary of RNAi screening of 350 host factors using quadruplicate measurements. (E) ROC analysis of MiST training using RNAi data, and additional filtering by CompPASS. (F) Functional enrichment analysis by bait. Highly similar categories with significant enrichment (false discovery rate (FDR) corrected q value < 0.05) were combined (Table S4), and the most conservative q values of combined terms are plotted. (*) indicates established role in flavivirus biology. (G) Overlap of DENV-human network with *Flaviviridae* protein interaction datasets. (H) Overlap of DENV-human network with *Flaviviridae* genetic datasets.

**Figure 2:. The DENV-human protein-protein interaction network.**
198 high confidence DENV-human PPIs are shown. Viral baits (grey squares), human prey (blue circles), benchmark interactions used for MiST training (dark blue circles), previously reported *Flaviviridae* replication phenotype (thick black border), virus-host interactions (solid grey lines), host-host interactions (dashed blue lines).

**Figure 3:. Comparative proteomics reveals that flavivirus NS5 antagonizes host restriction factor PAF1C.**
(A) DENV-human (blue) and ZIKV-human (pink) data were compared using gene ontology biological process and cellular compartment categories. Highly similar categories with significant enrichment (FDR corrected q value < 0.05) were combined (Table S5), and median q values of combined terms are plotted. Individual interactions detected in DENV (blue) and ZIKV (pink) datasets are shown for a subset of NS5 enrichment categories. (B) NS5 interaction with PAF1C subunits is conserved across flaviviruses. 2xStrep II tagged NS5 constructs were subjected to AP and Western blot. Stat2 is a positive control for NS5 AP, DENV Cap (Capsid), HIV Tat and EGFP are negative controls. Red triangles indicate band corresponding to bait. (C) Knockdown of PAF1C subunits leads to increased infectivity by DENV and ZIKV. Error bars reflect standard deviation of four replicates. P values were calculated using a paired, one tailed student’s t-test. (D) Knockdown of PAF1C components was confirmed by Western blot. (E) Mean LEO1 occupancy for 67 DENV-induced genes plotted for ChIP-seq triplicates. Error bars reflect standard deviation. P values were calculated using paired, two-tailed Mann-Whitney U-test. (F) NS5 inhibition of LEO1 recruitment is specific to ISGs. (G) Quantitative comparison of genes expressed in NS5- and GFP-expressing cells after immunostimulation. Left side: genome-wide (11,364 genes); Middle: 64 genes differentially regulated by polyIC; Right: Overlap of genes from set of 64 genes in middle panel and the genes whose binding of LEO1 is affected by NS5 (18 genes). (H) Model of NS5 effect on immune response gene expression through interaction with PAF1C.

**Figure 4:. Pharmacological modulation of SEC61 translocon inhibits DENV and ZIKV replication in human and mosquito cells.**
(A) Overlap between DENV-human (blue), ZIKV-human (pink), and DENV-mosquito (orange) NS4A interactions. Left panel: Enrichment analysis using gene ontology biological process categories. Highly similar categories with significant enrichment (FDR corrected q value < 0.05) were combined (Table S5), and median q values of combined terms are plotted. Right panel: individual interactions for a subset of enrichment categories. (B) Targeted proteomic analysis of flavivirus NS4A interaction with SEC61 translocon subunits and SRPR. Error bars reflect standard deviation from triplicates. (C) and (D) Inhibition of viral replication by 500nM CT8 and 1000 nM PS3061. DENV (blue) and ZIKV (pink) replication measured by plaque assay (C) and RT-qPCR of viral RNA (D) in human and mosquito cells. Error bars reflect standard deviation from triplicates. (E) CT8 (500 nM) inhibits DENV viral protein production in HEK 293T cells (MOI = 1). (F) CT8 (500 nM) inhibits DENV viral protein production in HEK 293T cells when added to cells post infection (MOI = 1). (G) Proposed model of cotransin inhibition of flavivirus replication.

**Figure 5:. ZIKV NS4A expression induces microcephaly in an ANKLE2-dependent manner.**
(A) Diagram of *D. melanogaster* 3^rd instar larva brain. (B) Bright field images of 3^rd instar brains expressing indicated proteins in a wild type or *Ankle2*^A/+ background (two lower right images). Colored square matches color of corresponding box plot in (C). Scale bar 100 μm. (C) Brain volumes quantified from animals corresponding to panel (A). P values were calculated using one-way ANOVA, Sidak’s multiple comparisons test. (D) Targeted proteomic analysis of ANKLE2 interaction with DENV and ZIKV NS4A. NS2B was used as a negative control. Error bars reflect standard deviation from triplicates. (E) Cell death quantified in 5 brains expressing the indicated proteins using a TUNEL assay. P values were calculated using one-way ANOVA, Tukey’s multiple comparisons test. (F-G) Cell type specific cell death was analyzed using TUNEL followed by immunostaining to identify neurons, glia, and neuroblasts. A single slice was analyzed in each set of images. Scale bar 40 μm. (F) Merged signals for neurons (Elav, purple), glia (Repo, light gray) and TUNEL (green). (G) Merged signals for neuroblasts (Dpn, red), ganglion mother cells and early neuronal lineages (Pros, cyan), and TUNEL (green) from a region of the brain at the surface (left panel) and from a deeper region of the brain (right panel).

**Figure 6:. ZIKV NS4A interacts with Ankle2 and affects neuroblasts**
(A) 3^rd instar larval brains from animals expressing the indicated proteins ubiquitously (driven by *Act*-GAL4), and stained for neuroblasts (Dpn, green) and neuronal lineages (Pros, purple) in control animals (CD8-GFP in *Ankle2*^A/+), *Ankle2*^A/Y males, NS4A, or NS4A in *Ankle2*^A/+ animals. The CD8-GFP in control animals was not imaged. Scale bar 50 βm. (B) and (C) Quantification of neuroblasts in brains expressing the indicated proteins using total number of Dpn positive cells in the central brain (B) and medulla (C). (D) Central brain neuroblast proliferation was quantified in brains expressing the indicated proteins based on EdU incorporation in Dpn positive cells. (E) Brain volumes quantified from animals expressing the indicated construct with the indicated driver to test cell type specificity. P values were calculated using one-way ANOVA, Sidak’s multiple comparisons test. Act-NS4A was also shown in Figure 5C. (F) Model of ZIKV NS4A impact on ANKLE2 function and brain development.

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Comment in

Deception through Mimicry: A Cellular Antiviral Strategy.
Wu NC, Ward AB. Wu NC, et al. Cell. 2018 Dec 13;175(7):1728-1729. doi: 10.1016/j.cell.2018.11.033. Cell. 2018. PMID: 30550784

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Comparative Flavivirus-Host Protein Interaction Mapping Reveals Mechanisms of Dengue and Zika Virus Pathogenesis

Affiliations

Comparative Flavivirus-Host Protein Interaction Mapping Reveals Mechanisms of Dengue and Zika Virus Pathogenesis

Authors

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Abstract

Conflict of interest statement

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Comment in

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