Gene expression profiling and network analysis reveals lipid and steroid metabolism to be the most favored by TNFalpha in HepG2 cells

Abstract

Background: The proinflammatory cytokine, TNFalpha, is a crucial mediator of the pathogenesis of several diseases, more so in cases involving the liver wherein it is critical in maintaining liver homeostasis since it is a major determiner of hepatocyte life and death. Gene expression profiling serves as an appropriate strategy to unravel the underlying signatures to envisage such varied responses and considering this, gene transcription profiling was examined in control and TNFalpha treated HepG2 cells.

Methods and findings: Microarray experiments between control and TNFalpha treated HepG2 cells indicated that TNFalpha could significantly alter the expression profiling of 140 genes; among those up-regulated, several GO (Gene Ontology) terms related to lipid and fat metabolism were significantly (p<0.01) overrepresented indicating a global preference of fat metabolism within the hepatocyte and those within the down-regulated dataset included genes involved in several aspects of the immune response like immunoglobulin receptor activity and IgE binding thereby indicating a compromise in the immune defense mechanism(s). Conserved transcription factor binding sites were identified in identically clustered genes within a common GO term and SREBP-1 and FOXJ2 depicted increased occupation of their respective binding elements in the presence of TNFalpha. The interacting network of "lipid metabolism, small molecule biochemistry" was derived to be significantly overrepresented that correlated well with the top canonical pathway of "biosynthesis of steroids".

Conclusions: TNFalpha alters the transcriptome profiling within HepG2 cells with an interesting catalog of genes being affected and those involved in lipid and steroid metabolism to be the most favored. This study represents a composite analysis of the effects of TNFalpha in HepG2 cells that encompasses the altered transcriptome profiling, the functional analysis of the up- and down- regulated genes and the identification of conserved transcription factor binding sites. These could possibly determine TNFalpha mediated alterations mainly the phenotypes of hepatic steatosis and fatty liver associated with several hepatic pathological states.

Figure 1. A volcano plot of genes altered by TNFα in HepG2 cells.

Log₂ fold changes and their corresponding p-values of all genes in the microarray were taken for construction of the volcano plot. Genes up-regulated with more than 1.5 fold change with a p-value <0.05 are depicted in red boxes and those down regulated with identical fold change and p-value are in green boxes. All other genes in the array that were not found to be significantly altered are in black dots.

Figure 2. Validation of microarray gene expression data by Real Time PCR.

HepG2 cells were treated in the absence and presence of TNFα (0.5 nM, 12 h) and the isolated total RNA was subjected to Real time PCR with gene specific primers as listed in Table 2. Values of each gene were normalized to those of 18S rRNA and are plotted with respect to the control that has arbitrarily been taken as 1. Each value is the mean ± SEM of three independent experiments. *p<0.01 as compared to control. **p<0.05 as compared to control.

Figure 3. Classification of TNFα-regulated genes into functional groups.

HepG2 genes that were altered by TNFα were classified on the basis of molecular functions using the GO Tool Box. Fraction of genes and the corresponding GO terms from the up-regulated set are shown in A and the same from the down regulated set are depicted in B.

Figure 4. Electrophoretic mobility shift assay in control and TNFα-treated nuclear extracts using SREBP-1 and FOXJ2 oligonucleotide probes.

15 µg of nuclear extracts from control or TNFα-treated cells were incubated with labeled probes harboring the binding elements of either SREBP-1 (A) or FOXJ2 (C). On termination of incubation they were resolved in a non-denaturing polyarylamide gel and subjected to phosphorimager analysis. Mutated oligonucleotides with altered binding motifs of these two transcription factors were used to check the specificity of the DNA-protein complexes. All experiments were done in triplicate. B and D: Densitometric analyses of the binding of SREBP-1 (B) and FOXJ2 (D) respectively. Each point is the mean±SEM of three independent experiments. Lane 1: Labeled probe alone; Lane 2: Labeled probe incubated with nuclear extract from control cells; Lane 3: Labeled probe incubated with nuclear extract from TNFα-treated cells; Lane 4: Labeled mutated probe incubated with the nuclear extract from control cells. *p<0.05 as compared to Lane 1; **p<0.01 as compared to Lanes 1 and 2; ***p<0.001 as compared to Lanes 1 and 2.

Figure 5. Interacting network among genes altered by TNFα in HepG2 cells.

Functional interacting network among genes altered with a log₂ ratio of ±0.5 in HepG2 cells by TNFα. All such genes were uploaded in the Ingenuity Pathway Analysis tool and the network of “lipid metabolism, small molecule biochemistry, nervous system development and function” that was identified with a significant score is depicted. Genes from our dataset and falling in this network are shown in either red (up-regulated) or green (down regulated) with the intensity of the color being an indicator of the fold change.

Figure 6. “Biosynthesis of steroids” identified as the top canonical pathway altered by TNFα in HepG2 cells.

Significant positions of the pathway are occupied by genes from our dataset indicating that this pathway is invariably affected by TNFα in HepG2 cells. These positions have been marked with solid diamond boxes in the figure. All the genes clustered at this part of the complete “Biosynthesis of steroids” pathway and therefore are indicative of the role of TNFα in the regulation of this pathway within the hepatocyte. 1.14.99.7: Squalene Epoxidase; 5.3.3.5: Emopamil Binding Protein (sterol isomerase); 2.5.1.1, 2.5.1.10, 2.5.1.129: forms of Farnesyl Diphosphate Synthase.

Figure 7. Effect of TNFα on cholesterol synthesis in HepG2 cells.

A.HepG2 cells were incubated in the absence (C) or presence of TNFα (0.5 nM, 12 h) and cells were lysed and lipids were extracted by addition of 1.0 ml of chloroform: methanol (2:1). B. HepG2 cells were transfected with 50 nM of either control (Con siRNA) or SQLE or FDPS or EBP siRNAs. After 48 h, they were incubated either alone or in the presence of TNFα as in “A”. Cholesterol was estimated in the extracted lipid fraction as described in the Methods section. Results are expressed after normalization to the total protein content. Each value is the mean± SEM of three experiments. *p<0.05 as compared to control (C), determined using Student's t test (A). *p<0.001 as compared to ConsiRNA; **p<0.01 and ***p<0.05 as compared to the incubation of TNFα alone in the presence of ConsiRNA (B).