STAT5: A target of antagonism by neurotropic flaviviruses

Flaviviruses are a diverse group of arthropod-borne viruses responsible for numerous significant public health threats; therefore, understanding the interactions between these viruses and the human immune response remains vital. West Nile virus (WNV) and Zika virus (ZIKV) infect human dendritic cells (DCs) and can block antiviral immune responses in DCs. Previously, we used mRNA sequencing and weighted gene coexpression network analysis (WGCNA) to define molecular signatures of antiviral DC responses following activation of innate immune signaling (RIG-I, MDA5, or type I interferon [IFN] signaling) or infection with WNV. Using this approach, we found that several genes involved in T cell cosignaling and antigen processing were not enriched in DCs during WNV infection. Using cis-regulatory sequence analysis, STAT5 was identified as a regulator of DC activation and immune responses downstream of innate immune signaling that was not activated during either WNV or ZIKV infection. Mechanistically, WNV and ZIKV actively blocked STAT5 phosphorylation downstream of RIG-I, IFN-β, and interleukin-4 (IL-4), but not granulocyte-macrophage colony-stimulating factor (GM-CSF), signaling. Unexpectedly, dengue virus serotypes 1 to 4 (DENV1 to DENV4) and the yellow fever 17D vaccine strain (YFV-17D) did not antagonize STAT5 phosphorylation. In contrast to WNV, ZIKV inhibited JAK1 and TYK2 phosphorylation following type I IFN treatment, suggesting divergent mechanisms used by these viruses to inhibit STAT5 activation. Combined, these findings identify STAT5 as a target of antagonism by specific pathogenic flaviviruses to subvert the immune response in infected DCs. IMPORTANCE Flaviviruses are a diverse group of insect-borne viruses responsible for numerous significant public health threats. Previously, we used a computational biology approach to define molecular signatures of antiviral DC responses following activation of innate immune signaling or infection with West Nile virus (WNV). In this work, we identify STAT5 as a regulator of DC activation and antiviral immune responses downstream of innate immune signaling that was not activated during either WNV or Zika virus (ZIKV) infection. WNV and ZIKV actively blocked STAT5 phosphorylation downstream of RIG-I, IFN-β, and IL-4, but not GM-CSF, signaling. However, other related flaviviruses, dengue virus serotypes 1 to 4 and the yellow fever 17D vaccine strain, did not antagonize STAT5 phosphorylation. Mechanistically, WNV and ZIKV showed differential inhibition of Jak kinases upstream of STAT5, suggesting divergent countermeasures to inhibit STAT5 activation. Combined, these findings identify STAT5 as a target of antagonism by specific pathogenic flaviviruses to subvert antiviral immune responses in human DCs

Zika Virus Antagonizes Type I Interferon Responses during Infection of Human Dendritic Cells

<div><p>Zika virus (ZIKV) is an emerging mosquito-borne flavivirus that is causally linked to severe neonatal birth defects, including microcephaly, and is associated with Guillain-Barre syndrome in adults. Dendritic cells (DCs) are an important cell type during infection by multiple mosquito-borne flaviviruses, including dengue virus, West Nile virus, Japanese encephalitis virus, and yellow fever virus. Despite this, the interplay between ZIKV and DCs remains poorly defined. Here, we found human DCs supported productive infection by a contemporary Puerto Rican isolate with considerable variability in viral replication, but not viral binding, between DCs from different donors. Historic isolates from Africa and Asia also infected DCs with distinct viral replication kinetics between strains. African lineage viruses displayed more rapid replication kinetics and infection magnitude as compared to Asian lineage viruses, and uniquely induced cell death. Infection of DCs with both contemporary and historic ZIKV isolates led to minimal up-regulation of T cell co-stimulatory and MHC molecules, along with limited secretion of inflammatory cytokines. Inhibition of type I interferon (IFN) protein translation was observed during ZIKV infection, despite strong induction at the RNA transcript level and up-regulation of other host antiviral proteins. Treatment of human DCs with RIG-I agonist potently restricted ZIKV replication, while type I IFN had only modest effects. Mechanistically, we found all strains of ZIKV antagonized type I IFN-mediated phosphorylation of STAT1 and STAT2. Combined, our findings show that ZIKV subverts DC immunogenicity during infection, in part through evasion of type I IFN responses, but that the RLR signaling pathway is still capable of inducing an antiviral state, and therefore may serve as an antiviral therapeutic target.</p></div

The Effect of Anticoagulants, Temperature, and Time on the Human Plasma Metabolome and Lipidome from Healthy Donors as Determined by Liquid Chromatography-Mass Spectrometry

Liquid-chromatography mass spectrometry is commonly used to identify and quantify metabolites from biological samples to gain insight into human physiology and pathology. Metabolites and their abundance in biological samples are labile and sensitive to variations in collection conditions, handling and processing. Variations in sample handling could influence metabolite levels in ways not related to biology, ultimately leading to the misinterpretation of results. For example, anticoagulants and preservatives modulate enzyme activity and metabolite oxidization. Temperature may alter both enzymatic and non-enzymatic chemistry. The potential for variation induced by collection conditions is particularly important when samples are collected in remote locations without immediate access to specimen processing. Data are needed regarding the variation introduced by clinical sample collection processes to avoid introducing artifact biases. In this study, we used metabolomics and lipidomics approaches paired with univariate and multivariate statistical analyses to assess the effects of anticoagulant, temperature, and time on healthy human plasma samples collected to provide guidelines on sample collection, handling, and processing for vaccinology. Principal component analyses demonstrated clustering by sample collection procedure and that anticoagulant type had the greatest effect on sample metabolite variation. Lipids such as glycerophospholipids, acylcarnitines, sphingolipids, diacylglycerols, triacylglycerols, and cholesteryl esters are significantly affected by anticoagulant type as are amino acids such as aspartate, histidine, and glutamine. Most plasma metabolites and lipids were unaffected by storage time and temperature. Based on this study, we recommend samples be collected using a single anticoagulant (preferably EDTA) with sample processing at &lt;24 h at 4 &#176;C

ZIKV infection induces an antiviral state within human DCs.

<p>moDCs were infected with ZIKV PR-2015, P6-1966, MR-1947, or Dak-1984 at MOI of 1 (n = 6–8 donors). Cells were collected at indicated hours post-infection and antiviral gene expression was determined by qRT-PCR. Gene expression was normalized to <i>GAPDH</i> transcript levels in each respective sample and represented as the averaged log₂ normalized fold increase above donor and time-point matched uninfected cells. The averaged log₁₀ normalized levels of infectious virus (FFU/mL) at each time point is depicted beneath the gene expression heat map. <b>(A)</b> RLR gene expression. <b>(B)</b> Antiviral effector gene expression. <b>(C)</b> moDCs were left untreated (“Mock”), treated with RIG-I agonist (10ng/1e5 cells), or infected with ZIKV PR-2015 (MOIs of 1 and 10) or MR-1947 (MOI 1). After 18hrs of agonist treatment or at 48hpi with ZIKV, whole-cell lysates were collected for western blot analysis of host antiviral effector protein expression. Western blots are shown for a single donor and are representative of data obtained from two donors. See also <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1006164#ppat.1006164.s005" target="_blank">S5 Fig</a>.</p

Differential infection of human DCs by evolutionarily distinct ZIKV strains.

<p>moDCs were infected with PR-2015, P6-1966, MR-1947, or Dak-1984 at MOI of 1 and assessed for viral replication at the indicated hours post-infection. <b>(A)</b> Infectious virus release into the supernatant was determined by FFA. Shown as the mean +/- SEM from 6–9 donors. <b>(B)</b> Infectious virus release for 6 of the individual donors summarized in panel A. <b>(C)</b> Percent infected cells assessed by ZIKV E protein staining and flow cytometry. Shown as the mean +/- SEM from 6–9 donors. <b>(D)</b> Percent infected cells in 6 of the individual donors summarized in panel C. <b>(E)</b> Cell viability of infected moDCs assessed by Ghost Red 780 (Tonbo) viability staining and flow cytometry. Shown as the mean +/- SEM from 6–9 donors. Statistical significance (p< 0.05) was determined using a two-way ANOVA with comparisons made to mock-infected cells. See also <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1006164#ppat.1006164.s007" target="_blank">S1 Table</a>.</p

Innate immune signaling restricts ZIKV viral replication within human DCs.

<p><b>(A)</b> moDCs were infected with PR-2015, P6-1966, MR-1947, or Dak-1984 at MOI of 1 (n = 4 donors). After viral attachment and entry at 1hpi, cells were treated with RIG-I agonist (10ng/1e5 cells), human IFNβ (100 IU/mL), or left untreated. <b>(B)</b> Supernatants were collected at 48hpi and assessed for infectious virus release by FFA. Values for each individual donor are shown with the mean +/- SD. Statistical significance (p< 0.05) was determined using a Friedman test with comparisons made to donor-paired, untreated, ZIKV-infected cells. The assay limit of detection is indicated with a dashed line.</p

ZIKV infection minimally activates human DCs.

<p><b>(A)</b> moDCs were left uninfected (“Mock”) or infected with PR-2015, P6-1966, MR-1947, or Dak-1984 at MOI of 1 (n = 6–8 donors). Cells were collected at 48hpi and labeled for ZIKV E protein and indicated DC activation markers. Cells were categorized as being viral E protein- or viral E protein+ and activation marker surface expression quantitated by flow cytometry. Values are represented as median fluorescence intensity (MFI) for each individual donor with uninfected and ZIKV infected samples from the same donor connected with a line. Statistical significance (p< 0.05) was determined using a Friedman test with comparisons made to donor-paired, uninfected cells. <b>(B)</b> moDCs infected with PR-2015 at MOI of 1 were stratified into “low” (n = 3 donors) and “high” (n = 5 donors) infection on the basis of viral E protein staining. MFIs are shown as the mean +/- SD. See also <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1006164#ppat.1006164.s003" target="_blank">S3 Fig</a>.</p