West Nile Virus Poster FINAL

Understanding West Nile Virus Infection:
The QIAGEN Bioinformatics Solution: Biomedical Genomics Workbench + Ingenuity Pathway Analysis (IPA).
Jean-Noel Billaud, PhD and Stuart Tugendreich, PhD; QIAGEN Silicon Valley (Redwood City, CA)
Top Canonical Pathways and their predicted activation state:
No approved therapy for humans
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Immune response-related pathways are induced by WNV infection. Note that interferon signaling (right panel) is predicted to be
activated, promoting an increase antiviral response and a decrease of replication of Flaviviridae (WNV family).
Mosquito-transmitted virus
Worldwide public health concern
Viral pathogenesis is incompletely understood
In 2012: highest number of human WNV cases
in the U.S. since 2003 (CDC)
West Nile Virus Infection
• Infection in healthy humans is asymptomatic, but can be severe in elderly and
immunocompromised
• Neuroinvasive forms of WNV infection:
 Characterized both by neuronal death and infiltration of mononuclear
effector cells
 Whose activities promote both viral clearance and neuronal injury
 Life-threatening neurological disease (meningitis and encephalitis)
• Immune Response:
 Induction of type-1 IFNs and humoral immunity provide front-line
defense against WNV pathogenesis,
 Cellular immunity (γδ T cells, CD4+, and CD8+ αβ T cells) for host
recovery from WNV infection.
Downstream Effects Analysis: Biological
Splicing Variant of interest: The isoforms (yellow
processes associated with WNV infection indicate a strong
immune response (innate immune response, antibody response,
cell movement of dendritic cells). These biological processes are
all predicted to be increased and they participate in the antiviral
response.
halo) are differentially expressed. One of them, ZAPS (short form
of ZC3HAV1) is of interest. ZAPS is upregulated in the infected
macrophages (red filled circle) and is a stimulator of signaling
mediated by the RNA helicase RIG-I during antiviral responses.
Some Key questions to be asked with transcriptomics
using IPA
• What are the signaling or metabolic pathways present, are they activated or
inhibited?
• What are the underlying transcriptional programs?
• What biological processes are involved and in what way?
• Are there any splicing variants of interest?
Splicing Variants
are involved in
the inhibition of
virus: Specific
Study GSE40718:
Identification of Genes Critical for Resistance to
Infection by West Nile Virus using RNA-Seq Analysis.
• Infection of primary macrophages from healthy human donors (10 individuals,
MOI=1, 24 hrs).
• PolyA+ RNA was prepared from uninfected and WNV-infected primary
macrophages, fragmented, and subjected to sequencing using the Illumina
Genome Analyzer 2.
• Processing the RNA-seq data in Biomedical Genomics Workbench
isoforms of ZC3HAV1,
Causal Network: CLEC7A might be a useful therapeutic
target to decrease WNV-associated encephalitis (orange circle).
CLEC7A is a master regulator (Upstream Analysis) and has
already been described as Host Susceptibility Factor required by WNV
to infect cells.
 Download the FASTQ files from European Nucleotide Archive (or
binary files from SRA)
 Import and process FASTQ files using Biomedical Genomics
Workbench (BXWB)
o Set up the RNA-seq Analysis in BXWB
o Select Reference Genome (human Ensembl)
o Select Mapping options
o Select Expression Level Options
 Set Up the Experiment at Gene Level (GE) or Transcripts Level (TE):
Infected vs. control
SP100, CFLAR, MX1 as
well IL27 participate in the
antiviral response and lead
to inhibition of virus.
This Causal Network allows to set a new hypothesis in
conjunction with MAP (Molecule Activity Predictor). MAP
simulates the inhibition of CLEC7A and the impact on the
encephalitis. When CLEC7A is inhibited or downregulated, the
encephalitis is decreased (blue circle). This hypothesis is ready
to be tested and validated.
• Send dataset to IPA using Plugin IPA from BXWB (Fold Change, p-value, FDR)
• Analyze the processed dataset in IPA
 Dataset: 3285 isoforms with >10 RPKM in either mock or infected,
|fold change|>1, p<0.05
 Analysis: 976 genes with |fold change| >2 and p-value <0.01
Conclusion
Using Biomedical Genomics Workbench, we have been able to:
Upload RNA-seq data (FASTQ files from SRA).
Align to the genome of interest (human Ensembl)
Quantitate and obtain differential expression between samples
Seamlessly send data directly into IPA for biological
interpretation
Using IPA, we have been able to:
Understand signaling pathways involved in antiviral immune
response
Discover potential transcriptional program(s) (CLEC7A)
Visualize differentially expressed splicing variants (view of ZAPS)
Discover biological processes participating in antiviral response
Highlight new hypotheses (CLEC7A inhibition).