Signalome-wide assessment of host cell response to hepatitis C virus
Identifieur interne : 000092 ( Pmc/Checkpoint ); précédent : 000091; suivant : 000093Signalome-wide assessment of host cell response to hepatitis C virus
Auteurs : Gholamreza Haqshenas [Australie] ; Jianmin Wu [Australie, République populaire de Chine] ; Kaylene J. Simpson [Australie] ; Roger J. Daly [Australie] ; Hans J. Netter [Australie] ; Thomas F. Baumert [France] ; Christian Doerig [Australie]Source :
- Nature Communications [ 2041-1723 ] ; 2017.
Abstract
Host cell signalling during infection with intracellular pathogens remains poorly understood. Here we report on the use of antibody microarray technology to detect variations in the expression levels and phosphorylation status of host cell signalling proteins during hepatitis C virus (HCV) replication. Following transfection with HCV RNA, the JNK and NF-κB pathways are suppressed, while the JAK/STAT5 pathway is activated; furthermore, components of the apoptosis and cell cycle control machineries are affected in the expression and/or phosphorylation status. RNAi-based hit validation identifies components of the JAK/STAT, NF-κB, MAPK and calcium-induced pathways as modulators of HCV replication. Selective chemical inhibition of one of the identified targets, the JNK activator kinase MAP4K2, does impair HCV replication. Thus this study provides a comprehensive picture of host cell pathway mobilization by HCV and uncovers potential therapeutic targets. The strategy of identifying targets for anti-infective intervention within the host cell signalome can be applied to any intracellular pathogen.
Url:
DOI: 10.1038/ncomms15158
PubMed: 28480889
PubMed Central: 5424167
Affiliations:
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Simpson</name><affiliation wicri:level="1"><nlm:aff id="a5"><institution>Victorian Centre for Functional Genomics, The Peter MacCallum Cancer Centre</institution>, St Andrews Place, East Melbourne, Victoria 3002,<country>Australia</country></nlm:aff><country xml:lang="fr">Australie</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="a6"><institution>Sir Peter MacCallum Department of Oncology, The University of Melbourne</institution>, Parkville, Victoria 3052,<country>Australia</country></nlm:aff><country xml:lang="fr">Australie</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Daly, Roger J" sort="Daly, Roger J" uniqKey="Daly R" first="Roger J." last="Daly">Roger J. Daly</name><affiliation wicri:level="1"><nlm:aff id="a7"><institution>Cancer Program, Monash Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University</institution>, Clayton Victoria 3800,<country>Australia</country></nlm:aff><country xml:lang="fr">Australie</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Netter, Hans J" sort="Netter, Hans J" uniqKey="Netter H" first="Hans J." last="Netter">Hans J. Netter</name><affiliation wicri:level="1"><nlm:aff id="a1"><institution>Infection & Immunity Program, Monash Biomedicine Discovery Institute and Department of Microbiology, Monash University</institution>, Clayton Victoria 3800,<country>Australia</country></nlm:aff><country xml:lang="fr">Australie</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="a8"><institution>Victorian Infectious Diseases Reference Laboratory, The Peter Doherty Institute, Melbourne Health</institution>, Victoria 3000,<country>Australia</country></nlm:aff><country xml:lang="fr">Australie</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Baumert, Thomas F" sort="Baumert, Thomas F" uniqKey="Baumert T" first="Thomas F." last="Baumert">Thomas F. Baumert</name><affiliation wicri:level="1"><nlm:aff id="a9"><institution>Inserm U1110, Institut de Recherche sur les Maladies Virales et Hépatiques, Université de Strasbourg</institution>, 67091 Strasbourg,<country>France</country></nlm:aff><country xml:lang="fr">France</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="a10"><institution>Institut Hospitalo-Universitaire, Pôle Hépato-digestif, Hôpitaux Universitaires de Strasbourg</institution>, 67091 Strasbourg,<country>France</country></nlm:aff><country xml:lang="fr">France</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author><author><name sortKey="Doerig, Christian" sort="Doerig, Christian" uniqKey="Doerig C" first="Christian" last="Doerig">Christian Doerig</name><affiliation wicri:level="1"><nlm:aff id="a1"><institution>Infection & Immunity Program, Monash Biomedicine Discovery Institute and Department of Microbiology, Monash University</institution>, Clayton Victoria 3800,<country>Australia</country></nlm:aff><country xml:lang="fr">Australie</country><wicri:regionArea># see nlm:aff country strict</wicri:regionArea></affiliation></author></analytic><series><title level="j">Nature Communications</title><idno type="eISSN">2041-1723</idno><imprint><date when="2017">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Host cell signalling during infection with intracellular pathogens remains poorly understood. Here we report on the use of antibody microarray technology to detect variations in the expression levels and phosphorylation status of host cell signalling proteins during hepatitis C virus (HCV) replication. Following transfection with HCV RNA, the JNK and NF-κB pathways are suppressed, while the JAK/STAT5 pathway is activated; furthermore, components of the apoptosis and cell cycle control machineries are affected in the expression and/or phosphorylation status. RNAi-based hit validation identifies components of the JAK/STAT, NF-κB, MAPK and calcium-induced pathways as modulators of HCV replication. Selective chemical inhibition of one of the identified targets, the JNK activator kinase MAP4K2, does impair HCV replication. Thus this study provides a comprehensive picture of host cell pathway mobilization by HCV and uncovers potential therapeutic targets. The strategy of identifying targets for anti-infective intervention within the host cell signalome can be applied to any intracellular pathogen.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Mehta, S H" uniqKey="Mehta S">S. H. Mehta</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Schuppan, D" uniqKey="Schuppan D">D. Schuppan</name></author><author><name sortKey="Krebs, A" uniqKey="Krebs A">A. Krebs</name></author><author><name sortKey="Bauer, M" uniqKey="Bauer M">M. Bauer</name></author><author><name sortKey="Hahn, E G" uniqKey="Hahn E">E. G. Hahn</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Gower, E" uniqKey="Gower E">E. Gower</name></author><author><name sortKey="Estes, C" uniqKey="Estes C">C. Estes</name></author><author><name sortKey="Blach, S" uniqKey="Blach S">S. 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Nat Commun</journal-id><journal-id journal-id-type="iso-abbrev">Nat Commun</journal-id><journal-title-group><journal-title>Nature Communications</journal-title></journal-title-group><issn pub-type="epub">2041-1723</issn><publisher><publisher-name>Nature Publishing Group</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">28480889</article-id><article-id pub-id-type="pmc">5424167</article-id><article-id pub-id-type="pii">ncomms15158</article-id><article-id pub-id-type="doi">10.1038/ncomms15158</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Signalome-wide assessment of host cell response to hepatitis C virus</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Haqshenas</surname><given-names>Gholamreza</given-names></name><xref ref-type="corresp" rid="c1">a</xref><xref ref-type="aff" rid="a1">1</xref></contrib><contrib contrib-type="author"><name><surname>Wu</surname><given-names>Jianmin</given-names></name><xref ref-type="aff" rid="a2">2</xref><xref ref-type="aff" rid="a3">3</xref><xref ref-type="aff" rid="a4">4</xref><contrib-id contrib-id-type="orcid">http://orcid.org/0000-0002-8876-128X</contrib-id></contrib><contrib contrib-type="author"><name><surname>Simpson</surname><given-names>Kaylene J.</given-names></name><xref ref-type="aff" rid="a5">5</xref><xref ref-type="aff" rid="a6">6</xref></contrib><contrib contrib-type="author"><name><surname>Daly</surname><given-names>Roger J.</given-names></name><xref ref-type="aff" rid="a7">7</xref></contrib><contrib contrib-type="author"><name><surname>Netter</surname><given-names>Hans J.</given-names></name><xref ref-type="aff" rid="a1">1</xref><xref ref-type="aff" rid="a8">8</xref></contrib><contrib contrib-type="author"><name><surname>Baumert</surname><given-names>Thomas F.</given-names></name><xref ref-type="aff" rid="a9">9</xref><xref ref-type="aff" rid="a10">10</xref></contrib><contrib contrib-type="author"><name><surname>Doerig</surname><given-names>Christian</given-names></name><xref ref-type="corresp" rid="c2">b</xref><xref ref-type="aff" rid="a1">1</xref></contrib><aff id="a1"><label>1</label><institution>Infection & Immunity Program, Monash Biomedicine Discovery Institute and Department of Microbiology, Monash University</institution>, Clayton Victoria 3800,<country>Australia</country></aff><aff id="a2"><label>2</label><institution>Kinghorn Cancer Centre & Cancer Division, Garvan Institute of Medical Research</institution>, Sydney, New South Wales 2010,<country>Australia</country></aff><aff id="a3"><label>3</label><institution>St Vincent's Clinical School, University of New South Wales</institution>, Sydney, New South Wales 2010,<country>Australia</country></aff><aff id="a4"><label>4</label><institution>Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Centre for Cancer Bioinformatics, Peking University Cancer Hospital & Institute</institution>, Beijing 100142,<country>China</country></aff><aff id="a5"><label>5</label><institution>Victorian Centre for Functional Genomics, The Peter MacCallum Cancer Centre</institution>, St Andrews Place, East Melbourne, Victoria 3002,<country>Australia</country></aff><aff id="a6"><label>6</label><institution>Sir Peter MacCallum Department of Oncology, The University of Melbourne</institution>, Parkville, Victoria 3052,<country>Australia</country></aff><aff id="a7"><label>7</label><institution>Cancer Program, Monash Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University</institution>, Clayton Victoria 3800,<country>Australia</country></aff><aff id="a8"><label>8</label><institution>Victorian Infectious Diseases Reference Laboratory, The Peter Doherty Institute, Melbourne Health</institution>, Victoria 3000,<country>Australia</country></aff><aff id="a9"><label>9</label><institution>Inserm U1110, Institut de Recherche sur les Maladies Virales et Hépatiques, Université de Strasbourg</institution>, 67091 Strasbourg,<country>France</country></aff><aff id="a10"><label>10</label><institution>Institut Hospitalo-Universitaire, Pôle Hépato-digestif, Hôpitaux Universitaires de Strasbourg</institution>, 67091 Strasbourg,<country>France</country></aff></contrib-group><author-notes><corresp id="c1"><label>a</label><email>gholamreza.haqshenas@monash.edu</email></corresp><corresp id="c2"><label>b</label><email>christian.doerig@monash.edu</email></corresp></author-notes><pub-date pub-type="epub"><day>08</day><month>05</month><year>2017</year></pub-date><pub-date pub-type="collection"><year>2017</year></pub-date><volume>8</volume><elocation-id>15158</elocation-id><history><date date-type="received"><day>23</day><month>05</month><year>2016</year></date><date date-type="accepted"><day>06</day><month>03</month><year>2017</year></date></history><permissions><copyright-statement>Copyright © 2017, The Author(s)</copyright-statement><copyright-year>2017</copyright-year><copyright-holder>The Author(s)</copyright-holder><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/4.0/"><pmc-comment>author-paid</pmc-comment>
<license-p>This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</ext-link></license-p></license></permissions><abstract><p>Host cell signalling during infection with intracellular pathogens remains poorly understood. Here we report on the use of antibody microarray technology to detect variations in the expression levels and phosphorylation status of host cell signalling proteins during hepatitis C virus (HCV) replication. Following transfection with HCV RNA, the JNK and NF-κB pathways are suppressed, while the JAK/STAT5 pathway is activated; furthermore, components of the apoptosis and cell cycle control machineries are affected in the expression and/or phosphorylation status. RNAi-based hit validation identifies components of the JAK/STAT, NF-κB, MAPK and calcium-induced pathways as modulators of HCV replication. Selective chemical inhibition of one of the identified targets, the JNK activator kinase MAP4K2, does impair HCV replication. Thus this study provides a comprehensive picture of host cell pathway mobilization by HCV and uncovers potential therapeutic targets. The strategy of identifying targets for anti-infective intervention within the host cell signalome can be applied to any intracellular pathogen.</p></abstract><abstract abstract-type="web-summary"><p>Development of antiviral strategies depends on an understanding of virus–host interactions. Here, using HCV, Haqshenas <italic>et al</italic>. show that antibody microarray combined with a targeted siRNA screen can be a powerful tool to identify cellular signalling pathways that are important for virus replication.</p></abstract></article-meta></front><floats-group><fig id="f1"><label>Figure 1</label><caption><title>Flowchart of the Kinexus antibody microarray methodology.</title><p>(<bold>a</bold>) <italic>In vitro</italic> synthesized transcripts of HCV deletion mutant (ΔE1E2) were transfected into Huh7.5.1 cells using transfection lipid reagent DMRIE-C. Negative control cells (Controls) were transfected with the transfection mixture lacking viral genome. At given time points post-transfection (PT), cells were harvested and lysed, and the extracts were incubated onto the antibody microarray. (<bold>b</bold>,<bold>c</bold>) Number of total and phosphorylated forms of signalling molecules across three time points. (<bold>d</bold>) Venn diagram of the 103 identified genes across different time points (6, 12 and 24 h post-transfection) (see <xref ref-type="supplementary-material" rid="S1">Supplementary Data 1–3</xref>). (<bold>e</bold>) Effects of silencing of the genes identified by antibody microarray on virus replication. The graph shows the top 20 factors that had most profound effect on virus replication. Following silencing of the genes for 43 h, cells were infected with a reporter virus containing a Renilla luciferase gene. The luciferase activity of each well was measured and normalized to its viability and negative control si-OTP-NT set at 100%. The error bars represent s.d. of at least three wells. <italic>P</italic> values were calculated with the unequal variance <italic>t</italic>-test embedded in Excel; significant variations (<italic>P</italic><0.05) are depicted by an asterisk.</p></caption><graphic xlink:href="ncomms15158-f1"></graphic></fig><fig id="f2"><label>Figure 2</label><caption><title>JAK/STAT5A pathway.</title><p>(<bold>a</bold>) Upregulation and downregulation of cell factors determined by antibody microarray experiment. Factors with a <italic>Z</italic> ratio >1.25 are considered significant (see Methods section). (<bold>b</bold>) A schematic figure of simplified JAK/STAT5A pathway. Colour boxes represent factors shortlisted for siRNA validation following the microarray experiment. (<bold>c</bold>) Effect of silencing of the JAK/STAT5A pathway components on HCV replication. Following silencing the target genes for 43 h, cells were infected with a reporter virus containing a Renilla luciferase gene. Solid bars, luciferase readout: Luciferase activity in each well, normalized to viability and negative control (si-OTP-NT) set at 100%. Hatched bars, qRT–PCR readout, normalized to two housekeeping genes. The error bars represent s.d. of at least three wells. <italic>P</italic> values were calculated with the unequal variance <italic>t</italic>-test embedded in Excel; significant variations (<italic>P</italic><0.05) are depicted by an asterisk.</p></caption><graphic xlink:href="ncomms15158-f2"></graphic></fig><fig id="f3"><label>Figure 3</label><caption><title>Non-canonical NF-κB pathway.</title><p>(<bold>a</bold>) Upregulation and downregulation of cell factors determined by antibody microarray experiment. Factors with a <italic>Z</italic> ratio >1.25 are considered significant (see Methods section). (<bold>b</bold>) A schematic figure of the (simplified) NF-κB pathway. Colour boxes represent factors shortlisted for siRNA validation following the microarray experiment. (<bold>c</bold>) Effect of silencing of the NF-κB pathway components on HCV replication. Following silencing the target genes for 43 h, cells were infected with a reporter virus containing a Renilla luciferase gene. Solid bars, luciferase readout: Luciferase activity in each well, normalized to viability and negative control (si-OTP-NT) set at 100%. Hatched bars, qRT–PCR readout, normalized to two housekeeping genes. The error bars represent s.d. of three independent experiments. <italic>P</italic> values were calculated with the unequal variance <italic>t</italic>-test embedded in Excel; significant variations (<italic>P</italic><0.05) are depicted by an asterisk. IκBα and IκBβ are referred to as NFKBIA and NFKBIB in the Kinexus microarray data set.</p></caption><graphic xlink:href="ncomms15158-f3"></graphic></fig><fig id="f4"><label>Figure 4</label><caption><title>Calcium-dependent signalling.</title><p>(<bold>a</bold>) Upregulation and downregulation of cell factors determined by antibody microarray experiment. Factors with a <italic>Z</italic> ratio >1.25 are considered significant (see Methods section). (<bold>b</bold>) Effect of gene silencing on HCV replication. Following silencing the target genes for 43 h, cells were infected with a reporter virus containing a Renilla luciferase gene. Solid bars, luciferase readout: Luciferase activity in each well, normalized to viability and negative control (si-OTP-NT) set at 100%. Hatched bars, qRT–PCR readout, normalized to two housekeeping genes. The error bars represent s.d. of at least three wells. <italic>P</italic> values were calculated with the unequal variance <italic>t</italic>-test embedded in Excel; significant variations (<italic>P</italic><0.05) are depicted by an asterisk.</p></caption><graphic xlink:href="ncomms15158-f4"></graphic></fig><fig id="f5"><label>Figure 5</label><caption><title>MAPK pathways.</title><p>(<bold>a</bold>) Upregulation and downregulation of cell factors determined by antibody microarray experiment. Factors with a <italic>Z</italic> ratio >1.25 are considered significant (see Methods section). (<bold>b</bold>) A schematic figure of the simplified MAPK pathway. Colour boxes represent factors shortlisted for siRNA validation following the microarray experiment. (<bold>c</bold>) Effect of silencing of the MAPK pathway components on HCV replication. Following silencing the target genes for 43 h, cells were infected with a reporter virus containing a Renilla luciferase gene. Solid bars, luciferase readout: Luciferase activity in each well, normalized to viability and negative control (si-OTP-NT) set at 100%. Hatched bars, qRT–PCR readout, normalized to two house keeping genes. The error bars represent s.d. of three independent experiments. <italic>P</italic> values were calculated with the unequal variance <italic>t</italic>-test embedded in Excel; significant variations (<italic>P</italic><0.05) are depicted by an asterisk.</p></caption><graphic xlink:href="ncomms15158-f5"></graphic></fig><fig id="f6"><label>Figure 6</label><caption><title>Effects of MAP4K2 silencing and chemical inhibition on HCV replication.</title><p>Huh7.5.1 cells were infected with a reporter virus after silencing MAP4K2 using SMARTpool and individual siRNA (si-MAP4K2 P1-4). The luciferase activity of (<bold>a</bold>) supernatant fluids was measured 15 and 43 h post-infection and (<bold>b</bold>) viral RNA quantity at 72 h post-infection. Cell viability was assessed using the PrestoBlue reagent (see Methods section) after the 43 h samples were collected. (<bold>c</bold>) Effects of TL4-12 on HCV replication. Huh7.5.1 cells were treated with TL4-12 for 5 h before the virus inoculum was added. At 6 h post-infection, cells were washed and the fresh medium containing TL4-12 were added. Samples were collected at given time points post-infection. DMSO-treated samples acted as mock-treated cells. The luciferase activity of (<bold>c</bold>) TL4-12 and mock-treated cultures and (<bold>d</bold>) viral RNA levels were normalized to non-treated cells. The viability was assessed using the PrestoBlue reagent. (<bold>e</bold>) Schematic representation of HCV replicon (Jc1ΔE1E2) lacking E1 and E2 genes. (<bold>f</bold>) Effect of MAP4K2 silencing on Jc1ΔE1E2 replication. (<bold>g</bold>) Effect of TL4-12 on Jc1ΔE1E2 replication. The error bars represent s.d. of three replicates. RLU: relative luciferase units; RFU: relative fluorescence units.</p></caption><graphic xlink:href="ncomms15158-f6"></graphic></fig></floats-group></pmc><affiliations><list><country><li>Australie</li><li>France</li><li>République populaire de Chine</li></country></list><tree><country name="Australie"><noRegion><name sortKey="Haqshenas, Gholamreza" sort="Haqshenas, Gholamreza" uniqKey="Haqshenas G" first="Gholamreza" last="Haqshenas">Gholamreza Haqshenas</name></noRegion><name sortKey="Daly, Roger J" sort="Daly, Roger J" uniqKey="Daly R" first="Roger J." last="Daly">Roger J. Daly</name><name sortKey="Doerig, Christian" sort="Doerig, Christian" uniqKey="Doerig C" first="Christian" last="Doerig">Christian Doerig</name><name sortKey="Netter, Hans J" sort="Netter, Hans J" uniqKey="Netter H" first="Hans J." last="Netter">Hans J. Netter</name><name sortKey="Netter, Hans J" sort="Netter, Hans J" uniqKey="Netter H" first="Hans J." last="Netter">Hans J. Netter</name><name sortKey="Simpson, Kaylene J" sort="Simpson, Kaylene J" uniqKey="Simpson K" first="Kaylene J." last="Simpson">Kaylene J. Simpson</name><name sortKey="Simpson, Kaylene J" sort="Simpson, Kaylene J" uniqKey="Simpson K" first="Kaylene J." last="Simpson">Kaylene J. Simpson</name><name sortKey="Wu, Jianmin" sort="Wu, Jianmin" uniqKey="Wu J" first="Jianmin" last="Wu">Jianmin Wu</name><name sortKey="Wu, Jianmin" sort="Wu, Jianmin" uniqKey="Wu J" first="Jianmin" last="Wu">Jianmin Wu</name></country><country name="République populaire de Chine"><noRegion><name sortKey="Wu, Jianmin" sort="Wu, Jianmin" uniqKey="Wu J" first="Jianmin" last="Wu">Jianmin Wu</name></noRegion></country><country name="France"><noRegion><name sortKey="Baumert, Thomas F" sort="Baumert, Thomas F" uniqKey="Baumert T" first="Thomas F." last="Baumert">Thomas F. Baumert</name></noRegion><name sortKey="Baumert, Thomas F" sort="Baumert, Thomas F" uniqKey="Baumert T" first="Thomas F." last="Baumert">Thomas F. 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