Determination of host proteins composing the microenvironment of coronavirus replicase complexes by proximity-labeling
Identifieur interne : 001230 ( Pmc/Curation ); précédent : 001229; suivant : 001231Determination of host proteins composing the microenvironment of coronavirus replicase complexes by proximity-labeling
Auteurs : Philip V'Kovski [Suisse] ; Markus Gerber [Suisse] ; Jenna Kelly [Suisse] ; Stephanie Pfaender [Suisse] ; Nadine Ebert [Suisse] ; Sophie Braga Lagache [Suisse] ; Cedric Simillion [Suisse] ; Jasmine Portmann [Suisse] ; Hanspeter Stalder [Suisse] ; Véronique Gaschen [Suisse] ; Rémy Bruggmann [Suisse] ; Michael H. Stoffel [Suisse] ; Manfred Heller [Suisse] ; Ronald Dijkman [Suisse] ; Volker Thiel [Suisse]Source :
- eLife [ 2050-084X ] ; ????.
Abstract
Positive-sense RNA viruses hijack intracellular membranes that provide niches for viral RNA synthesis and a platform for interactions with host proteins. However, little is known about host factors at the interface between replicase complexes and the host cytoplasm. We engineered a biotin ligase into a coronaviral replication/transcription complex (RTC) and identified >500 host proteins constituting the RTC microenvironment. siRNA-silencing of each RTC-proximal host factor demonstrated importance of vesicular trafficking pathways, ubiquitin-dependent and autophagy-related processes, and translation initiation factors. Notably, detection of translation initiation factors at the RTC was instrumental to visualize and demonstrate active translation proximal to replication complexes of several coronaviruses. Collectively, we establish a spatial link between viral RNA synthesis and diverse host factors of unprecedented breadth. Our data may serve as a paradigm for other positive-strand RNA viruses and provide a starting point for a comprehensive analysis of critical virus-host interactions that represent targets for therapeutic intervention.
Url:
DOI: 10.7554/eLife.42037
PubMed: 30632963
PubMed Central: 6372286
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PMC:6372286Le document en format XML
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</author>
<author><name sortKey="Gaschen, Veronique" sort="Gaschen, Veronique" uniqKey="Gaschen V" first="Véronique" last="Gaschen">Véronique Gaschen</name>
<affiliation wicri:level="1"><nlm:aff id="aff7"><institution content-type="dept">Division of Veterinary Anatomy, Vetsuisse Faculty</institution>
<institution>University of Bern</institution>
<addr-line>Bern</addr-line>
<country>Switzerland</country>
</nlm:aff>
<country xml:lang="fr">Suisse</country>
<wicri:regionArea># see nlm:aff country strict</wicri:regionArea>
</affiliation>
</author>
<author><name sortKey="Bruggmann, Remy" sort="Bruggmann, Remy" uniqKey="Bruggmann R" first="Rémy" last="Bruggmann">Rémy Bruggmann</name>
<affiliation wicri:level="1"><nlm:aff id="aff4"><institution content-type="dept">Interfaculty Bioinformatics Unit, SIB Swiss Institute of Bioinformatics</institution>
<institution>University of Bern</institution>
<addr-line>Bern</addr-line>
<country>Switzerland</country>
</nlm:aff>
<country xml:lang="fr">Suisse</country>
<wicri:regionArea># see nlm:aff country strict</wicri:regionArea>
</affiliation>
</author>
<author><name sortKey="Stoffel, Michael H" sort="Stoffel, Michael H" uniqKey="Stoffel M" first="Michael H" last="Stoffel">Michael H. Stoffel</name>
<affiliation wicri:level="1"><nlm:aff id="aff7"><institution content-type="dept">Division of Veterinary Anatomy, Vetsuisse Faculty</institution>
<institution>University of Bern</institution>
<addr-line>Bern</addr-line>
<country>Switzerland</country>
</nlm:aff>
<country xml:lang="fr">Suisse</country>
<wicri:regionArea># see nlm:aff country strict</wicri:regionArea>
</affiliation>
</author>
<author><name sortKey="Heller, Manfred" sort="Heller, Manfred" uniqKey="Heller M" first="Manfred" last="Heller">Manfred Heller</name>
<affiliation wicri:level="1"><nlm:aff id="aff5"><institution content-type="dept">Mass Spectrometry and Proteomics Core Facility, Department for BioMedical Research (DBMR)</institution>
<institution>University of Bern</institution>
<addr-line>Bern</addr-line>
<country>Switzerland</country>
</nlm:aff>
<country xml:lang="fr">Suisse</country>
<wicri:regionArea># see nlm:aff country strict</wicri:regionArea>
</affiliation>
</author>
<author><name sortKey="Dijkman, Ronald" sort="Dijkman, Ronald" uniqKey="Dijkman R" first="Ronald" last="Dijkman">Ronald Dijkman</name>
<affiliation wicri:level="1"><nlm:aff id="aff1"><institution>Institute of Virology and Immunology IVI</institution>
<addr-line>Bern</addr-line>
<country>Switzerland</country>
</nlm:aff>
<country xml:lang="fr">Suisse</country>
<wicri:regionArea># see nlm:aff country strict</wicri:regionArea>
</affiliation>
<affiliation wicri:level="1"><nlm:aff id="aff2"><institution content-type="dept">Department of Infectious Diseases and Pathobiology, Vetsuisse Faculty</institution>
<institution>University of Bern</institution>
<addr-line>Bern</addr-line>
<country>Switzerland</country>
</nlm:aff>
<country xml:lang="fr">Suisse</country>
<wicri:regionArea># see nlm:aff country strict</wicri:regionArea>
</affiliation>
</author>
<author><name sortKey="Thiel, Volker" sort="Thiel, Volker" uniqKey="Thiel V" first="Volker" last="Thiel">Volker Thiel</name>
<affiliation wicri:level="1"><nlm:aff id="aff1"><institution>Institute of Virology and Immunology IVI</institution>
<addr-line>Bern</addr-line>
<country>Switzerland</country>
</nlm:aff>
<country xml:lang="fr">Suisse</country>
<wicri:regionArea># see nlm:aff country strict</wicri:regionArea>
</affiliation>
<affiliation wicri:level="1"><nlm:aff id="aff2"><institution content-type="dept">Department of Infectious Diseases and Pathobiology, Vetsuisse Faculty</institution>
<institution>University of Bern</institution>
<addr-line>Bern</addr-line>
<country>Switzerland</country>
</nlm:aff>
<country xml:lang="fr">Suisse</country>
<wicri:regionArea># see nlm:aff country strict</wicri:regionArea>
</affiliation>
</author>
</analytic>
<series><title level="j">eLife</title>
<idno type="eISSN">2050-084X</idno>
<imprint><date when="????">????</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
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</teiHeader>
<front><div type="abstract" xml:lang="en"><p>Positive-sense RNA viruses hijack intracellular membranes that provide niches for viral RNA synthesis and a platform for interactions with host proteins. However, little is known about host factors at the interface between replicase complexes and the host cytoplasm. We engineered a biotin ligase into a coronaviral replication/transcription complex (RTC) and identified >500 host proteins constituting the RTC microenvironment. siRNA-silencing of each RTC-proximal host factor demonstrated importance of vesicular trafficking pathways, ubiquitin-dependent and autophagy-related processes, and translation initiation factors. Notably, detection of translation initiation factors at the RTC was instrumental to visualize and demonstrate active translation proximal to replication complexes of several coronaviruses. Collectively, we establish a spatial link between viral RNA synthesis and diverse host factors of unprecedented breadth. Our data may serve as a paradigm for other positive-strand RNA viruses and provide a starting point for a comprehensive analysis of critical virus-host interactions that represent targets for therapeutic intervention.</p>
</div>
</front>
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<article-id pub-id-type="pmc">6372286</article-id>
<article-id pub-id-type="publisher-id">42037</article-id>
<article-id pub-id-type="doi">10.7554/eLife.42037</article-id>
<article-categories><subj-group subj-group-type="display-channel"><subject>Research Article</subject>
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<subj-group subj-group-type="heading"><subject>Microbiology and Infectious Disease</subject>
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<title-group><article-title>Determination of host proteins composing the microenvironment of coronavirus replicase complexes by proximity-labeling</article-title>
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<contrib id="author-51510" contrib-type="author"><name><surname>Dijkman</surname>
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<given-names>Volker</given-names>
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<email>volker.thiel@vetsuisse.unibe.ch</email>
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<aff id="aff1"><label>1</label>
<institution>Institute of Virology and Immunology IVI</institution>
<addr-line>Bern</addr-line>
<country>Switzerland</country>
</aff>
<aff id="aff2"><label>2</label>
<institution content-type="dept">Department of Infectious Diseases and Pathobiology, Vetsuisse Faculty</institution>
<institution>University of Bern</institution>
<addr-line>Bern</addr-line>
<country>Switzerland</country>
</aff>
<aff id="aff3"><label>3</label>
<institution content-type="dept">Graduate School for Biomedical Science</institution>
<institution>University of Bern</institution>
<addr-line>Bern</addr-line>
<country>Switzerland</country>
</aff>
<aff id="aff4"><label>4</label>
<institution content-type="dept">Interfaculty Bioinformatics Unit, SIB Swiss Institute of Bioinformatics</institution>
<institution>University of Bern</institution>
<addr-line>Bern</addr-line>
<country>Switzerland</country>
</aff>
<aff id="aff5"><label>5</label>
<institution content-type="dept">Mass Spectrometry and Proteomics Core Facility, Department for BioMedical Research (DBMR)</institution>
<institution>University of Bern</institution>
<addr-line>Bern</addr-line>
<country>Switzerland</country>
</aff>
<aff id="aff6"><label>6</label>
<institution content-type="dept">Department of Clinical Research</institution>
<institution>University of Bern</institution>
<addr-line>Bern</addr-line>
<country>Switzerland</country>
</aff>
<aff id="aff7"><label>7</label>
<institution content-type="dept">Division of Veterinary Anatomy, Vetsuisse Faculty</institution>
<institution>University of Bern</institution>
<addr-line>Bern</addr-line>
<country>Switzerland</country>
</aff>
</contrib-group>
<contrib-group><contrib contrib-type="editor"><name><surname>Kirkegaard</surname>
<given-names>Karla</given-names>
</name>
<role>Reviewing Editor</role>
<aff><institution>Stanford University School of Medicine</institution>
<country>United States</country>
</aff>
</contrib>
<contrib contrib-type="editor"><name><surname>Dikic</surname>
<given-names>Ivan</given-names>
</name>
<role>Senior Editor</role>
<aff><institution>Goethe University Frankfurt</institution>
<country>Germany</country>
</aff>
</contrib>
</contrib-group>
<pub-date date-type="pub" publication-format="electronic"><day>11</day>
<month>1</month>
<year>2019</year>
</pub-date>
<pub-date pub-type="collection"><year>2019</year>
</pub-date>
<volume>8</volume>
<elocation-id>e42037</elocation-id>
<history><date date-type="received" iso-8601-date="2018-09-14"><day>14</day>
<month>9</month>
<year>2018</year>
</date>
<date date-type="accepted" iso-8601-date="2019-01-11"><day>11</day>
<month>1</month>
<year>2019</year>
</date>
</history>
<permissions><copyright-statement>© 2019, V'kovski et al</copyright-statement>
<copyright-year>2019</copyright-year>
<copyright-holder>V'kovski et al</copyright-holder>
<ali:free_to_read></ali:free_to_read>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/"><ali:license_ref>http://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This article is distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License</ext-link>
, which permits unrestricted use and redistribution provided that the original author and source are credited.</license-p>
</license>
</permissions>
<self-uri content-type="pdf" xlink:href="elife-42037.pdf"></self-uri>
<abstract><p>Positive-sense RNA viruses hijack intracellular membranes that provide niches for viral RNA synthesis and a platform for interactions with host proteins. However, little is known about host factors at the interface between replicase complexes and the host cytoplasm. We engineered a biotin ligase into a coronaviral replication/transcription complex (RTC) and identified >500 host proteins constituting the RTC microenvironment. siRNA-silencing of each RTC-proximal host factor demonstrated importance of vesicular trafficking pathways, ubiquitin-dependent and autophagy-related processes, and translation initiation factors. Notably, detection of translation initiation factors at the RTC was instrumental to visualize and demonstrate active translation proximal to replication complexes of several coronaviruses. Collectively, we establish a spatial link between viral RNA synthesis and diverse host factors of unprecedented breadth. Our data may serve as a paradigm for other positive-strand RNA viruses and provide a starting point for a comprehensive analysis of critical virus-host interactions that represent targets for therapeutic intervention.</p>
</abstract>
<abstract abstract-type="executive-summary"><title>eLife digest</title>
<p>Coronaviruses can infect the nose and throat and are a main cause of the common cold. Infections are usually mild and short-lived, but sometimes they can turn nasty. In 2002 and 2012, two dangerous new coronaviruses emerged and caused diseases known as SARS and MERS. These viruses caused much more serious symptoms and in some cases proved deadly. The question is, why are some coronaviruses more dangerous than others? Scientists know that the body's response to virus infection can make a difference to whether someone had mild or severe disease. So, to understand why some coronaviruses cause a cold and others kill, they also need to learn how people react to virus infection.</p>
<p>Coronaviruses hijack membranes inside cells and turn them into virus factories. Within these factories, the viruses build molecular machinery called replicase complexes to copy their genetic code, which is needed for the next generation of virus particles. The viruses steal and repurpose proteins from their host cell that will assist in the copying process. However, scientists do not yet know which host proteins are essential for the virus to multiply. So, to find out, V’kovski et al. developed a way to tag any host protein that came near the virus factories.</p>
<p>The new technique involved attaching an enzyme called a biotin ligase to the replicase complex. This enzyme acts as a molecular label gun, attaching a chemical tag to any protein that comes within ten nanometres. The label gun revealed that more than 500 different proteins come into contact with the replicase complex. To find out what these proteins were doing, the next step was to switch off their genes one by one. This revealed the key cell machinery that coronaviruses hijack when they are replicating. It included the cell's cargo transport system, the waste disposal system, and the protein production system. Using these systems allows the viruses to copy their genetic code next to machines that can turn it straight into viral proteins.</p>
<p>These new results provide clues about which proteins viruses actually need from their host cells. They also do not just apply to coronaviruses. Other viruses use similar strategies to complete their infection cycle. These findings could help researchers to understand more generally about how viruses multiply. In the future, this knowledge could lead to new ways to combat virus infections.</p>
</abstract>
<kwd-group kwd-group-type="author-keywords"><kwd>coronavirus</kwd>
<kwd>replicase complex</kwd>
<kwd>proximity labeling</kwd>
<kwd>virus-host interaction</kwd>
<kwd>translation</kwd>
<kwd>vesicular transport</kwd>
</kwd-group>
<kwd-group kwd-group-type="research-organism"><title>Research organism</title>
<kwd>Human</kwd>
<kwd>Mouse</kwd>
<kwd>Virus</kwd>
</kwd-group>
<funding-group><award-group id="fund1"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/501100001711</institution-id>
<institution>Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung</institution>
</institution-wrap>
</funding-source>
<award-id>173085</award-id>
<principal-award-recipient><name><surname>V'kovski</surname>
<given-names>Philip</given-names>
</name>
<name><surname>Thiel</surname>
<given-names>Volker</given-names>
</name>
</principal-award-recipient>
</award-group>
<award-group id="fund2"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/501100000780</institution-id>
<institution>European Commission</institution>
</institution-wrap>
</funding-source>
<award-id>748627</award-id>
<principal-award-recipient><name><surname>Pfaender</surname>
<given-names>Stephanie</given-names>
</name>
<name><surname>Thiel</surname>
<given-names>Volker</given-names>
</name>
</principal-award-recipient>
</award-group>
<award-group id="fund3"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/501100001711</institution-id>
<institution>Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung</institution>
</institution-wrap>
</funding-source>
<award-id>160780</award-id>
<principal-award-recipient><name><surname>Kelly</surname>
<given-names>Jenna</given-names>
</name>
<name><surname>Ebert</surname>
<given-names>Nadine</given-names>
</name>
<name><surname>Thiel</surname>
<given-names>Volker</given-names>
</name>
</principal-award-recipient>
</award-group>
<funding-statement>The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.</funding-statement>
</funding-group>
<custom-meta-group><custom-meta specific-use="meta-only"><meta-name>Author impact statement</meta-name>
<meta-value>The molecular microenvironment of coronaviral replicase complexes provides functional and spatial links between conserved cellular processes and viral RNA synthesis, and highlights potential targets for the development of novel antivirals.</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<sub-article id="SA1" article-type="decision-letter"><front-stub><article-id pub-id-type="doi">10.7554/eLife.42037.024</article-id>
<title-group><article-title>Decision letter</article-title>
</title-group>
<contrib-group><contrib contrib-type="editor"><name><surname>Kirkegaard</surname>
<given-names>Karla</given-names>
</name>
<role>Reviewing Editor</role>
<aff><institution>Stanford University School of Medicine</institution>
<country>United States</country>
</aff>
</contrib>
</contrib-group>
</front-stub>
<body><boxed-text position="float" orientation="portrait"><p>In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.</p>
</boxed-text>
<p>Thank you for submitting your article "Determination of host proteins composing the microenvironment of coronavirus replicase complexes by proximity-labeling" for consideration by <italic>eLife</italic>
. Your article has been reviewed by two peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Ivan Dikic as the Senior Editor. The reviewers have opted to remain anonymous.</p>
<p>The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.</p>
<p>Summary:</p>
<p>In this manuscript, V'kovski and colleagues described the use of proximity labeling in an attempt to define the complete proteome of replication complexes within the cytoplasm of coronavirus infected cells. For this study, the authors mainly focused on mouse hepatitis virus (MHV), but they also confirmed a subset of their findings with human coronavirus 229E and MERS-coronavirus. They used very well controlled experimental conditions at one time point during MHV infection of L929 cells in culture. The authors engineered a biotin ligase into the coding region of nsp2 and demonstrated that this virus, as well as a control GFP virus, had replication kinetics and growth properties similar to those of WT MHV. Five hundred proteins were identified, roughly 50 of which had proviral effects, as surmised from the decrease in viral RNA replication when the abundance of their mRNAs was reduced by siRNA treatment.</p>
<p>This is a well-crafted study that has generated a wealth of data regarding the composition of membrane bound replication complexes in coronavirus-infected mouse cells. It has the potential for uncovering the mechanistic details of how RNA replication complexes are assembled, how those complexes change during infection, and how viral non-structural proteins interact with a large array of host proteins to produce viral mRNAs and RNA replication intermediates. Given the already ambitious scope of the current study, all these mechanistic questions could not be addressed in this manuscript, but it is anticipated that data reported in this paper will be a springboard for many future studies. Here, the authors focused on translation factors and used a puromycin incorporation assay to show that active viral translation occurred near sites of viral RNA synthesis, providing evidence for the spatial coupling of viral translation and RNA synthesis functions and likely dependence of nascent protein synthesis for the proper topology of membrane association.</p>
<p>A small amount of additional protein work is needed to demonstrate the integrity of the BirA<sub>R118G</sub>
-nsp2 fusion protein during infection and the reduction in ribosomal proteins following siRNA treatment.</p>
<p>Essential revisions:</p>
<p>1) Figure 1A and 1B. Given the propensity of viral proteins to be cleaved by viral and host proteinases, it is necessary to test whether all BirA<sub>R118G</sub>
remains fused to nsp2 in infected cells.</p>
<p>2) The data and their interpretation presented in the subsection “Active translation near sites of viral mRNA synthesis”, are problematic. It seems unlikely that knocking down canonical factors required for cap-dependent translation would dramatically impact viral translation but not host translation. The authors are using RT-PCR to verify knockdowns, but this would not account for the fact that some of these proteins may be very stable, especially if they are in translation initiation or elongation complexes. To deal with this possibility, it is essential for the authors to carry out Western blots following siRNA knockdowns of Rpl13a, eIF3i, eIF3f, eIF3e, and eIF4G1. The real readout here is protein levels, and this needs to be shown directly.</p>
<p>3) Subsection "Functional classification of the RTC-proximal host factors." This subsection contains a lengthy analysis of what emerged from the GO analysis, and how these observations could be connected with the literature. This is very interesting, but it would be good if the more speculative parts were moved to the Discussion. There, they could be combined with discussion of the 50 that emerged as being proviral following the siRNA screen. As it is, one is confused about what ideas were derived from the 500 candidates and what survived further investigation.</p>
<p>4) All discussion of the 500 proteins analyzed is based on the idea that they facilitate viral infection, or not. Surely there is a possibility that some of them are antiviral, and thus viral RNA replication will increase in their absence? Some acknowledgement of this possibility should be included.</p>
</body>
</sub-article>
<sub-article id="SA2" article-type="reply"><front-stub><article-id pub-id-type="doi">10.7554/eLife.42037.025</article-id>
<title-group><article-title>Author response</article-title>
</title-group>
</front-stub>
<body><disp-quote content-type="editor-comment"><p>Essential revisions:</p>
<p>1) Figure 1A and 1B. Given the propensity of viral proteins to be cleaved by viral and host proteinases, it is necessary to test whether all BirA<sub>R118G</sub>
remains fused to nsp2 in infected cells.</p>
</disp-quote>
<p>The reviewers raised an important point. In order to assess whether BirA<sub>R118G</sub>
remains fused to nsp2 during infection, we performed a western blot analysis of mock-infected, MHV-WT and MHV-BirA<sub>R118G</sub>
-nsp2-infected cells, using an anti-myc monoclonal antibody.</p>
<p>As shown in the new Figure 1—figure supplement 1, a specific band at the expected molecular weight of 102.2 kDa was detected specifically in MHV-BirA<sub>R118G</sub>
-nsp2 lysates. Additionally, a band largely exceeding the size of the reference protein ladder likely represents polyprotein precursors. Importantly, no specific bands were detected at 36.7 kDa, which represents the expected molecular weight of myc-BirA<sub>R118G</sub>
. Moreover, immunofluorescence analysis of MHV-BirA<sub>R118G</sub>
-nsp2-infected cells further demonstrates the association of BirA<sub>R118G</sub>
with nsp2/3 and nsp8-labelled RTCs at all investigated time points (9, 12, 15 hours post infection) (Figure 1C and Figure 1—figure supplement 2, Figure 1—figure supplement 3). We included the immunofluorescence data from time points 9h and 15h post infection in the new supplementary Figure 1—figure supplement 2. Altogether, these data strongly suggest that BirA<sub>R118G</sub>
remains fused to nsp2 during the entire course of MHV-BirA<sub>R118G</sub>
-nsp2 infection and is not cleaved by viral proteinases.</p>
<p>These results were included in the manuscript as two new supplementary figures (Figure 1—figure supplement 1 and Figure 1—figure supplement 2) and in the second paragraph of the subsection “Engineering the BirA<sub>R118G</sub>
-biotin ligase into the MHV replicase transcriptase complex”.</p>
<disp-quote content-type="editor-comment"><p>2) The data and their interpretation presented in the subsection “Active translation near sites of viral mRNA synthesis”, are problematic. It seems unlikely that knocking down canonical factors required for cap-dependent translation would dramatically impact viral translation but not host translation. The authors are using RT-PCR to verify knockdowns, but this would not account for the fact that some of these proteins may be very stable, especially if they are in translation initiation or elongation complexes. To deal with this possibility, it is essential for the authors to carry out Western blots following siRNA knockdowns of Rpl13a, eIF3i, eIF3f, eIF3e, and eIF4G1. The real readout here is protein levels, and this needs to be shown directly.</p>
</disp-quote>
<p>We thank the reviewers for this comment, to which we entirely agree. In order to address this question, we ordered a deconvolved siRNA library containing target-specific, single siRNAs to silence eIF3e, eIF3f and eIF3i as well as eIF4G1 and Rpl13a. Next, we assessed protein levels by western blot after siRNA-mediated silencing of these factors (48h). For Rpl13a, we did not find suitable commercial antibodies, and western blots using both a polyclonal rabbit anti-eIF4G1 as well as a monoclonal rabbit anti-eIF4G1 (cell signalling 2858 and 8701) did not result in western blots of acceptable quality to allow quantification.</p>
<p>However, we could find suitable monoclonal antibodies for eIF3e, eIF3f and eIF3i, and we show in a new figure (Figure 5) that the knockdown of eIF3e, eIF3f and eIF3i, using 4 distinct siRNAs, resulted in a significant decrease of protein levels when normalized to an actin loading control. These data were performed in three independent siRNA knockdown followed by western blot experiments. Correspondingly, assessing viral replication using MHV-Gluc in the same knockdown conditions was consistent with previous results and confirmed that the knockdown of eIF3e, eIF3f and eIF3i significantly impairs viral replication.</p>
<p>These results are displayed in a new figure (Figure 5) and in the first paragraph of the subsection “Active translation near sites of viral mRNA synthesis”.</p>
<disp-quote content-type="editor-comment"><p>3) Subsection "Functional classification of the RTC-proximal host factors." This subsection contains a lengthy analysis of what emerged from the GO analysis, and how these observations could be connected with the literature. This is very interesting, but it would be good if the more speculative parts were moved to the Discussion. There, they could be combined with discussion of the 50 that emerged as being proviral following the siRNA screen. As it is, one is confused about what ideas were derived from the 500 candidates and what survived further investigation.</p>
</disp-quote>
<p>We thank the reviewers for this constructive remark. We adapted the subsection "Functional classification of the RTC-proximal host factors" accordingly and discussed parallels between published studies and our results in the Discussion section of the manuscript.</p>
<p>Statements referring to previously published work were removed from the Results section.</p>
<p>Accordingly, in the Discussion section, we discussed similarities between our results and other published studies using both coronaviruses and other positive-sense viruses. These changes are found in the third, fourth and fifth paragraph of the Discussion.</p>
<disp-quote content-type="editor-comment"><p>4) All discussion of the 500 proteins analyzed is based on the idea that they facilitate viral infection, or not. Surely there is a possibility that some of them are antiviral, and thus viral RNA replication will increase in their absence? Some acknowledgement of this possibility should be included.</p>
</disp-quote>
<p>We thank the reviewers for raising this point. Indeed, within the coronavirus RTC microenvironment, we expect to detect both proviral host factors that are required and support viral replication, as well as antiviral factors responsible for detecting viral replication intermediates. However since this study was performed in a L929 mouse fibroblast cell line, it is not surprising that the results are skewed towards highlighting proviral factors. To detect antiviral factors, other cell lines/types, e.g. primary macrophages, that are better equipped in eliciting antiviral responses, would be preferable.</p>
<p>Accordingly, we included the following sentence in the manuscript: “In contrast, we did not find antiviral factors that resulted in significant enhancement of viral replication upon siRNA knockdown. While this work was performed in a murine fibroblast cell line, the identification of antiviral proteins may be anticipated in a similar siRNA-mediated knockdown screen using primary target cells such as macrophages, that are better equipped in eliciting antiviral responses upon virus infection.”</p>
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