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Journal of Virology, October 2006, p. 10248-10252, Vol. 80, No. 20
0022-538X/06/$08.00+0     doi:10.1128/JVI.01384-06
Copyright © 2006, American Society for Microbiology. All Rights Reserved.

Differential Signaling Networks Induced by Mild and Lethal Hemorrhagic Fever Virus Infections

Gavin C. Bowick,^1,2 Susan M. Fennewald,^1,2 Barry L. Elsom,^1,2 Judith F. Aronson,^1,2 Bruce A. Luxon,^2,3,4 David G. Gorenstein,^2,3 and Norbert K. Herzog^1,2*

Department of Pathology,¹ Center for Biodefense and Emerging Infectious Diseases,² Department of Biochemistry and Molecular Biology,³ Bioinformatics Program, University of Texas Medical Branch, Galveston, Texas 77555⁴

Received 30 June 2006/ Accepted 2 August 2006

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The family Arenaviridae includes several National Institutes of Allergy and Infections Diseases category A select agents which cause hemorrhagic fever. There are few vaccines available, and treatment is limited to ribavirin, which varies in efficacy. Development of new antiviral compounds has been hindered by a lack of understanding of the molecular basis of pathogenesis. We used two variants of Pichinde virus, one attenuated and one virulent in the guinea pig model, to delineate the host determinants which lead to either viral clearance or lethal disease. By analyzing protein level changes using pathway analysis, we have identified key intermediates which may be targets for therapeutic intervention.

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The family Arenaviridae includes several National Institutes of Allergy and Infections Diseases (NIAID) category A biothreat agents, such as Lassa fever virus. Little is known about the molecular determinants of disease, and this has hindered the design of antivirals. Variants of Pichinde virus—a biosafety level 2 model for arenavirus hemorrhagic fever disease—cause either a self-limiting infection or lethal disease in guinea pigs that can be used to delineate the host cell signaling events associated with these different outcomes. We have previously shown that infection of macrophages with P2 (attenuated) or P18 (virulent) viruses induces differential responses of the transcription factors NF-B and RBP-J (4). By understanding the signaling events which lead to these differential responses, we hope to identify the key regulators responsible for determining host fate and determine which may be targets for antiviral therapies.

To investigate the host response to hemorrhagic fever virus infection, we used a high-throughput immunoblotting approach to assay the levels of over 700 proteins in macrophages which were either mock infected or infected with P2 or P18 Pichinde virus. Murine monocyte-like P388D1 cells were maintained in RPMI medium (Invitrogen) supplemented with 2 mM glutamine (Invitrogen) and 5% fetal bovine serum (Whittaker Bioproducts). Cells were maintained in the absence of antibiotics to monitor any potential contamination which could cause signaling pathway activation. Cells were infected with PEG-purified P2 or P18 Pichinde virus at a multiplicity of infection of 0.1. PEG-purified virus was used in order to remove contaminating cytokines and other factors which may influence cell signaling. Mock-infected cells were treated with PEG purification medium alone. Cells were harvested 3 days postinfection in denaturing buffer.

The BD Biosciences PowerBlot service was used to assay the total protein levels in the whole-cell extracts described above. Samples were resolved on 5-to-15% gradient sodium dodecyl sulfate-polyacrylamide gels (Bio-Rad). A 300-µg sample of protein was loaded into a single lane which spans the width of the gel. Following electrophoresis, proteins were transferred onto an Immobilon-P nylon membrane (Millipore) and blocked for 20 min in 5% milk. The membrane was clamped in a manifold to isolate 40 channels across the membrane and antibody cocktail was added to each channel and incubated for 45 min. The blot was removed from the manifold, washed, and incubated for 30 min with horseradish peroxidase-conjugated goat anti-mouse immunoglobulin. The membrane was washed and developed by chemiluminescence using the SuperSignal West Dura extended-duration substrate (Pierce). Immunoblotting was performed in triplicate. Images were captured and digitally matched using PDQuest software (Bio-Rad). Blot images and raw and normalized data were supplied for analysis.

We observed 98 significant changes between mock and P2 infection, 86 changes between mock and P18 infection, and 44 changes between P2 and P18 infection (Table S1 in the supplemental material). Figure 1 shows the degree of commonality between the observed changes, presented as a Venn diagram. To place these observations in biological context, we utilized the Ingenuity pathway analysis knowledge base. Proteins which differed in expression between treatments in duplicate (over 2-fold) or triplicate (over 1.5-fold) with high-quality signals were compiled into a data set and analyzed with the Ingenuity Pathways Analysis software (Ingenuity Systems, Redwood City, CA). The Ingenuity Pathways Analysis Knowledge Base has been described in detail (3). Briefly, functions of, and interactions between, cellular proteins are mined from peer-reviewed literature and encoded into an ontology by postdoctoral-level scientists. A network analysis of the knowledge base is used to construct interaction-based relationships between proteins in the knowledge base.

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FIG. 1. Commonality between P2- and P18-induced changes in cellular protein levels presented as a Venn diagram. Numbers represent the differences between virus-infected and mock-infected cells and correspond to protein level changes shown in the first two columns of Table S1 in the supplemental material. The degree of overlap represents commonality in P2- and P18-induced changes relative to mock infection rather than a P2-versus-P18 pairwise comparison.

A data set containing SWISS-PROT protein identifiers and their corresponding "fold-change" values was uploaded as an Excel spreadsheet using the template provided in the application. Each protein identifier was mapped to its corresponding object in the Ingenuity pathways knowledge base. A cutoff of 2 was set to identify proteins whose expression was significantly differentially regulated between infected and mock-infected cells; a cutoff of 1.5 was used to compare effects between P2 and P18 infection. These proteins were then used as the starting point for generating biological networks, i.e., integrated systems of several canonical signaling pathways which reveal cross talk between signaling intermediates. Networks were constructed using direct interactions only. Biological functions were assigned to each protein network using the findings that were extracted from the scientific literature and stored in the Ingenuity pathways knowledge base. The biological functions assigned to each network were ranked according to the significance of that biological function to the network. A Fischer's exact test was used to calculate a P value determining the probability that the biological function assigned to that network is explained by chance alone. Pathways were designated as significant if they had a score of 4 or higher; a score of x represents a P value of 10^–x. Proteins present in signaling networks are functionally classified according to the symbol key in Fig. S1 in the supplemental material.

Comparing differences between mock-infected and P2-infected cells identified five signaling networks with significance scores ranging from 5 to 72; in comparison, mock-infection-versus-P18-infection analysis produced four networks, with scores from 5 to 75. Common changes associated with both viruses included the identification of p53, STATs 1 and 3, and RelA as significantly involved nodes in activated signaling networks. The integrated networks produced after merging these pathways are shown in Fig. 2.

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FIG. 2. Cell-signaling networks induced by Pichinde virus infection as analyzed using the Ingenuity pathway analysis knowledge base. Significant pathways were merged to produce networks representing induction following infection with the attenuated P2 variant (A) and the lethal P18 variant (B). Nodes in red are up-regulated following virus infection; nodes in green are down-regulated. Reprinted with permission from Ingenuity Systems.

As the host is able to effectively clear P2, but not P18, infection, we hypothesize that P18 suppresses the signaling events which lead to a protective immune response. By modulating these networks pharmacologically to alter P18 signaling to resemble a P2-type induced response, we may be able to either induce an effective host response or prevent the rapid onset of shock, allowing the host further time to mount an effective immune response. In order to identify the signaling intermediates that are regulated differentially between P2 and P18 infection, we created networks from proteins expressed differentially between these two infections (Table S1, column 3). Analysis produced three signaling networks with significance scores of 27, 14, and 12, revealing p53, c-Myc, and Akt as central nodes. These individual networks were merged and displayed according to subcellular location to reveal logical upstream-to-downstream signaling pathways (Fig. 3). A number of differences were identified, including IB kinase, IB epsilon, phospholipase C (which has been shown to be involved in RANKL-induced NF-B activation [8]), and protein kinase C-iota (involved in a number of pathways, including NF-B signaling [1, 6]).

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FIG. 3. Differentially expressed proteins following P2 or P18 Pichinde virus infection. Significant pathways were merged to produce a cellular signaling network which is regulated differentially between attenuated and virulent arenavirus infections. Nodes shown in red are up-regulated following P2 infection compared to P18; nodes in green are down-regulated. Reprinted with permission from Ingenuity Systems.

Of particular interest is the fourfold increase in the expression of the cholinergic receptor following P2 infection compared to P18 infection. The parasympathetic nervous system is involved in inflammatory response attenuation (reviewed in reference 10); the lack of effective attenuation of this response in P18 infection may be fundamental in the development of the proinflammatory cytokine-induced shock commonly seen in hemorrhagic fever virus infections. However, P2 infection leads to a reduced level of glycogen synthase-3-kinase-ß. Glycogen synthase-3-kinase-ß phosphorylates and activates p53 (11), which has been shown to be anti-inflammatory (5). This result suggests that there may be reduced p53-mediated suppression of inflammation following P2 infection compared to P18 infection. These findings illustrate the importance of dissecting the signaling mechanisms important for inflammatory responses, rather than merely determining whether the overall outcome is pro- or anti-inflammatory, as the delicate balance between pathways of activation and repression may have a significant bearing on potential therapeutic intervention.

Our findings suggest that the lethal P18 variant of Pichinde virus does not induce as broad a host-signaling response as the mild form of the virus. As arenaviruses are not likely to activate cell signaling pathways to enhance viral replication, it is likely that this is the result of active suppression of host cell signaling by the P18 virus. These results are consistent with those seen with other arenaviruses. The nonpathogenic Mopeia virus activates macrophages following infection, but the hemorrhagic fever-causing Lassa virus does not (2, 9). It has also been shown that Ebola and Lassa virus-infected dendritic cells are inhibited in their immunoregulatory function (7). In summary, we have identified key proteins involved in signaling networks that are differentially regulated in attenuated and lethal arenavirus disease. These proteins provide useful targets for future development of antiviral agents, which may be effective against a number of hemorrhagic fever virus infections.

 
We thank Stephen Higgs for critical reading of the manuscript.

These studies were supported by grants from DARPA (DAAD19011037), DTRA (DAAD17-01-D0001), and NIH (N01-HV-28184, U01 AI054827, R01 A127744) and by a grant from NIAID to N.K.H. through the Western Regional Center of Excellence for Biodefense and Emerging Infectious Disease Research, NIH grant number U54 AI057156.

 
* Corresponding author. Mailing address: University of Texas Medical Branch, 201 University Blvd., Galveston, TX 77555. Phone: (409) 772-3938. Fax: (409) 747-2400. E-mail: nherzog{at}utmb.edu.

Supplemental material for this article may be found at http://jvi.asm.org/.

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Journal of Virology, October 2006, p. 10248-10252, Vol. 80, No. 20
0022-538X/06/$08.00+0     doi:10.1128/JVI.01384-06
Copyright © 2006, American Society for Microbiology. All Rights Reserved.

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This Article Abstract Full Text (PDF) Supplemental material Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Reprints and Permissions Copyright Information Books from ASM Press MicrobeWorld Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Bowick, G. C. Articles by Herzog, N. K. Search for Related Content PubMed PubMed Citation Articles by Bowick, G. C. Articles by Herzog, N. K.