Deconvolution of pro- and antiviral genomic responses in Zika virus-infected and bystander macrophages

Abstract

Genome-wide investigations of host-pathogen interactions are often limited by analyses of mixed populations of infected and uninfected cells, which lower sensitivity and accuracy. To overcome these obstacles and identify key mechanisms by which Zika virus (ZIKV) manipulates host responses, we developed a system that enables simultaneous characterization of genome-wide transcriptional and epigenetic changes in ZIKV-infected and neighboring uninfected primary human macrophages. We demonstrate that transcriptional responses in ZIKV-infected macrophages differed radically from those in uninfected neighbors and that studying the cell population as a whole produces misleading results. Notably, the uninfected population of macrophages exhibits the most rapid and extensive changes in gene expression, related to type I IFN signaling. In contrast, infected macrophages exhibit a delayed and attenuated transcriptional response distinguished by preferential expression of IFNB1 at late time points. Biochemical and genomic studies of infected macrophages indicate that ZIKV infection causes both a targeted defect in the type I IFN response due to degradation of STAT2 and reduces RNA polymerase II protein levels and DNA occupancy, particularly at genes required for macrophage identity. Simultaneous evaluation of transcriptomic and epigenetic features of infected and uninfected macrophages thereby reveals the coincident evolution of dominant proviral or antiviral mechanisms, respectively, that determine the outcome of ZIKV exposure.

Keywords: Zika virus; genomics; immune evasion; macrophage; transcription.

Fig. 1.

ZIKV modulates macrophage transcription during infection. (A) Diagram depicting the infection model. HMDMs are infected with ZIKV and stained for ZIKV group antigen followed by FACS isolation of live, productively infected ZIKV⁺ and bystander (ZIKV⁻) macrophages. (B) Percent of RNA-seq reads aligning to the ZIKV genome in FACS-isolated ZIKV⁺ and ZIKV⁻ macrophages at the indicated time points PI. Percent was calculated as the total reads aligning to ZIKV alone vs. human + ZIKV genomes. Each data point (mean ± SEM) represents results from HMDMs derived from different human donors. All categories were compared using ANOVA with correction for multiple comparisons. (C) PCA biplot of the first two principal component dimensions comparing RNA-seq of FACS-isolated ZIKV⁺ or ZIKV⁻ HMDMs from three (12 h and 18 h) or five (mock-infected and 24 h) individual donors. (D) Calculated loss of sensitivity in detecting ZIKV-regulated gene expression. Gene-expression levels were calculated using data from ZIKV⁺, ZIKV⁻, and mock-infected macrophage RNA-seq experiments 24 h PI performed with macrophages from five different donors. (E and F) Individual gene expression calculated by RNA-seq in pure populations of mock-infected, ZIKV⁺, and ZIKV⁻ macrophages (24 h PI). Mean (± SEM) IL1A (E) and CCR1 (F) expressions of pure populations (black bars) were calculated based on RNA-seq from five different donors. Mean (± SEM) expression of a 36% mixed population (white bar) was calculated computationally based on mixing 36% ZIKV⁺ macrophages with 64% ZIKV⁻ macrophages from each of those five independent RNA-seq experiments. (G) Calculated number of genes expected to be falsely attributed to ZIKV-dependent regulation based on percent infectivity. Calculations were performed as in D. (H) Mean (± SEM) EIF2AK2 and IL6 expression of pure populations (black bars) and a 36% mixed population (white bar) calculated as described in E and F.

Fig. 2.

Degradation of STAT2 by ZIKV impairs ISG activation. (A) Heat maps of the top enriched functional annotations of genes significantly up-regulated (fold change >2, FDR < 0.01) in ZIKV⁺ and ZIKV⁻ macrophages compared with mock-infected macrophages at the indicated time points. (B) Heat map of the relative expression of selected genes involved in cytokine signaling and antigen presentation in mock-infected, ZIKV⁺ and ZIKV⁻ macrophages 24 h PI. Data are the average of five experiments. (C) Venn diagrams showing the numbers of unique and shared up-regulated genes in ZIKV⁺ and ZIKV⁻ macrophages compared with mock-infected macrophages at 12, 18, and 24 h PI. The top significantly enriched functional category for genes uniquely induced in ZIKV⁺ cells (red) at each time point is shown with examples of genes from that category. (D) Heat map depicting relative transcription of type I and III IFN genes and ISG in ZIKV⁻ and ZIKV⁺ macrophages vs. control (Mock) over time. Data are the average of three experiments (12 h and 18 h) or five experiments (24 h). (E) Western blot of STAT1, phosphorylated-STAT1, STAT2, phosphorylated STAT2, ZIKV NS2B, and β-actin levels in equivalent numbers of mock-infected, ZIKV⁻, and ZIKV⁺ cells at 24 h PI. (F) Relative quantitation of Western blot STAT2 levels in ZIKV⁻ and ZIKV⁺ cells treated with MG132 or vehicle control (Mock). STAT2 density is relative to β-actin. Data shown (mean ± SEM) are from three infections performed in HMDMs derived from three different individuals at 24 h PI. Data were analyzed by ANOVA with MG132 treatment groups compared with vehicle with correction for multiple comparisons. (G) Relative gene expression in ZIKV⁻ and ZIKV⁺ cells treated with MG132 compared with DMSO. Data (mean ± SEM) show the relative gene expression by qRT-PCR in at least three independent experiments performed with FACS HMDMs derived from different donors at 24 h PI. Data for each gene were analyzed by ANOVA with MG132-treatment groups compared with vehicle with correction for multiple comparisons. Asterisks indicate statistically significant differences (*P < 0.05).

Fig. 3.

ZIKV suppresses the activation of genomic regions containing ISRE/IRF motifs. (A) Diagram depicting the infection model for H3K27ac ChIP-seq. HMDMs are infected with ZIKV and stained for ZIKV group antigen followed by FACS isolation of productively infected ZIKV⁺ and bystander (ZIKV⁻) macrophages and then followed by H3K27ac ChIP-seq. (B) The number of regions with significantly increased or decreased H3K27ac (fold change >2 and FDR < 0.01) in ZIKV⁺ or ZIKV⁻ cells compared with mock-infected cells. (C) Scatter plot of H3K27ac tag counts at genomic regions marked by significant H3K27ac in ZIKV⁺ vs. ZIKV⁻ macrophages 24 h PI. Regions with significantly elevated levels of H3K27ac in ZIKV⁺ (red) and ZIKV⁻ (blue) are colored. (D) UCSC browser visualization of H3K27ac near the IFITM gene locus in control, ZIKV⁺, and ZIKV⁻ cells. The upper panel displays transcription as defined by RNA-seq. The lower panel displays H3K27ac abundance in control (Mock, black), ZIKV⁻ (blue), or ZIKV⁺ (red) macrophages. Regions with significantly up-regulated H3K27ac in ZIKV⁻ cells are marked with blue shading. (E) Comparative motif enrichment at promoter-distal active regulatory regions as defined by H3K27ac in ZIKV⁻ (blue bars) vs. ZIKV⁺ (red bars) HMDMs.

Fig. 4.

ZIKV suppresses RNApol2 recruitment. (A) Scatter plot of log₂ FPKM RNApol2 tag counts at genomic regions marked by significant RNApol2 in ZIKV⁺ vs. ZIKV⁻ macrophages at 24 h PI. Color coding: gray, all genomic regions; blue, protein-coding regions; red, snRNA-coding regions. (B) UCSC browser visualization of RNA-seq (first panel), RNApol2 (second panel), H3K27ac (third panel), and CTCF (fourth panel) near the CEBPB gene locus in control (Mock, black), ZIKV⁻ (blue), or ZIKV⁺ (red) macrophages. (C) UCSC browser visualization of RNApol2 (Upper) and H3K27ac (Lower) near two snRNA genes, RNU4-2 and RNU4-1, in control (Mock, black), ZIKV⁻ (blue), or ZIKV⁺ (red) macrophages. (D) Heat map depicting relative RNApol2 levels at core macrophage genes in ZIKV⁻ and ZIKV⁺ macrophages compared with control macrophages (mock). Genes associated with SEs are shown in bold type. Data are the average from three independent experiments. (E) Relationship between changes in RNApol2 and the presence of SEs. Shown is the log2 ratio of RNApol2 reads at individual genes in ZIKV⁺ cells compared with control cells (Mock). The orange trace shows the total number of genes associated with each ratio of RNApol2 change. The blue trace shows the fraction of genes overlapping SE as a function of their change in RNApol2. (F) Western blot of RPB1, β-actin, and ZIKV-NS2B levels extracted from FACS-isolated equivalent numbers of mock-infected, ZIKV⁻, and ZIKV⁺ cells at 24 h PI. (G) Relative quantitation of Western blot RPB1 levels. RPB1 density is relative to β-actin with control samples set to 1. Relative levels (mean ± SEM) of RPB1 in control (Mock), ZIKV⁻, and ZIKV⁺ cells are shown for three infections in different individuals at 24 h PI. (H) Log₂-transformed FPKM RNA-seq counts for POLR2A in control (Mock), ZIKV⁻, and ZIKV⁺ cells 24 h PI. Data represent expression from RNA-seq performed in five different individuals. Data for G and H were analyzed by ANOVA with all-group comparison with correction for multiple comparisons. Asterisks indicate statistically significant differences (****P < 0.0001; **P < 0.01).