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Meta-Analysis
. 2011;6(10):e25584.
doi: 10.1371/journal.pone.0025584. Epub 2011 Oct 25.

An integrated transcriptomic and meta-analysis of hepatoma cells reveals factors that influence susceptibility to HCV infection

Jamie I MacPherson  1 , Ben Sidders, Stefan Wieland, Jin Zhong, Paul Targett-Adams, Volker Lohmann, Perdita Backes, Oona Delpuech-Adams, Francis Chisari, Marilyn Lewis, Tanya Parkinson, David L Robertson
Affiliations
Meta-Analysis

An integrated transcriptomic and meta-analysis of hepatoma cells reveals factors that influence susceptibility to HCV infection

Jamie I MacPherson et al. PLoS One. 2011.

Abstract

Hepatitis C virus (HCV) is a global problem. To better understand HCV infection researchers employ in vitro HCV cell-culture (HCVcc) systems that use Huh-7 derived hepatoma cells that are particularly permissive to HCV infection. A variety of hyper-permissive cells have been subcloned for this purpose. In addition, subclones of Huh-7 which have evolved resistance to HCV are available. However, the mechanisms of susceptibility or resistance to infection among these cells have not been fully determined. In order to elucidate mechanisms by which hepatoma cells are susceptible or resistant to HCV infection we performed genome-wide expression analyses of six Huh-7 derived cell cultures that have different levels of permissiveness to infection. A great number of genes, representing a wide spectrum of functions are differentially expressed between cells. To focus our investigation, we identify host proteins from HCV replicase complexes, perform gene expression analysis of three HCV infected cells and conduct a detailed analysis of differentially expressed host factors by integrating a variety of data sources. Our results demonstrate that changes relating to susceptibility to HCV infection in hepatoma cells are linked to the innate immune response, secreted signal peptides and host factors that have a role in virus entry and replication. This work identifies both known and novel host factors that may influence HCV infection. Our findings build upon current knowledge of the complex interplay between HCV and the host cell, which could aid development of new antiviral strategies.

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Conflict of interest statement

Competing Interests: BS, PTA, ODA, ML and TP are employees of Pfizer. JIM received a contribution to his PhD funding from Pfizer. This does not alter the authors' adherence to all the PLoS ONE policies on sharing data and materials.

Figures

Figure 1
Figure 1. Tree of hepatoma cell cultures.
Cell cultures are joined by arrows, going from the parent to the descendent, that indicate a subcloning event (or in the case of Huh-7 to Huh-7.5.1 a series of subcloning events). (A) The relative susceptibility of these cells to HCV infection where “+” represents susceptibility and “-” represents resistance and more symbols represent greater susceptibility or resistance. (B) Differential expressed genes between subclones. Differentially expressed genes were assigned to this tree either directly from expression comparison between cells or indirectly using a parsimony method. On each arrow, the first number indicates the total number of differentially expressed genes that have been attributed to the subcloning event. Below in brackets are the number of these genes that are (i) downregulated or (ii) upregulated following subclononing.
Figure 2
Figure 2. Hierarchical clustering plot displaying differentially expressed genes from infected and control cells.
Genes are represented by horizontal bands and cells by columns. Infected cells are denoted with an asterisk (*). Bands are coloured blue if the gene is downregulated and yellow if it is upregulated compared with the mean expression level for that gene. Greater colour intensity signifies greater fold change. Infected cells cluster with one another and gene clustering shows a clear pattern that corresponds to HCV infection-induced regulation of gene expression.
Figure 3
Figure 3. Venn diagram showing the overlap in genes differentially expressed due to HCV infection among susceptible cells.
The absolute numbers of significantly differentially expressed genes are given for Huh-7, Huh-7.5.1 and Huh-7.5.1c2 cells. The numbers in brackets refer to those genes that share the same direction of regulation (up- or downregulated) following infection, across multiple comparisons.
Figure 4
Figure 4. Hierarchical clustering plots showing the expression levels of differentially expressed genes between hepatoma cells.
Genes are represented by horizontal bands and cells by columns. Bands are coloured blue if the gene is downregulated and yellow if they are upregulated relative to their expression in Huh-7.5.1. Greater colour intensity relates to a greater fold change. Black bands represent genes whose expression is a similar level to Huh-7.5.1. (A) Comparison of gene expression levels between susceptible cells. Here, the Huh-7.5.1c2 cell line is clearly more similar in gene expression to Huh-7.5.1 than Huh-7. (B) Comparison of gene expression levels between resistant cells and Huh-7.5.1. The R2.1 cell line is more divergent from Huh-7.5.1 than either R.109 or R1.10 in terms of gene expression. R1.09 and R1.10 show similar patterns of gene expression.
Figure 5
Figure 5. Functional annotation cluster networks from differentially expressed genes and other HCV-related data sources.
These networks highlight areas of shared enriched function between gene sets that we identify as differentially expressed between hepatoma cells and also gene sets that relate to HCV infection. Nodes represent annotation clusters from the data source denoted by the node colour. Edges represent shared annotation terms between clusters. Only nodes that share at least 1/4 of annotating terms are connected by an edge. Node diameter is proportional to the level of enrichment of the biological function in the gene set. Edge width is proportional to the proportion of annotating terms shared between two clusters. Subnetworks A–D are those with >6 nodes, subnetworks shown in E have between 3 and 6 nodes. Annotation clusters from two PPI data sources are shown: PPI (1) from reference and PPI (2) from reference .
Figure 6
Figure 6. Hierarchical clustering plots showing the expression levels of differentially expressed HCV-linked cellular receptors and lipoproteins.
Genes are represented by horizontal bands and cells by columns. Bands are coloured blue if the gene is downregulated and yellow if they are upregulated, relative to their expression in Huh-7.5.1. Greater colour intensity relates to a greater fold change. Black bands represent genes whose expression is a similar level to Huh-7.5.1. (A) Comparison of gene expression levels between susceptible cells. All genes shown are linked to HCV cell entry except for MTTP and APOB that are associated with release of HCV from the cell. The majority of these host factors that undergo a significant change in expression are found at a higher level in Huh-7 than either of the Huh-7.5.1 derived cells. (B) Comparison of gene expression levels between resistant cells and Huh-7.5.1. R1.09 and R1.10 cells have have a lower level of expression of CD81 than Huh-7.5.1. Though R2.1 cells have a relatively high level of CD81 expression relative to Huh-7.5.1, other cell entry factors are expressed at lower levels.
Figure 7
Figure 7. Protein interaction neighbourhoods of HCV proteins.
HCV proteins are denoted by yellow nodes. Host proteins encoded by genes from either the high-scorer set or from significant antiviral and proviral biological functions are denoted by orange or blue nodes, indicating proviral or antiviral expression profiles, respectively. Other HCV interacting host proteins are denoted by grey nodes. Edges represent interactions between these proteins.
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