(350f) Transcriptional Regulatory Network Dynamics In the Early Regenerative Response of Rat Liver

Liver regeneration is a complex, yet remarkably coordinated, process characterized by system-wide gene expression changes underlying the response of the liver tissue to acute damage through mechanical, chemical or viral mechanisms (Taub, 2004 review). This response involves a variety of growth factors, cytokines, hormones, matrix components and other factors. Following the signals that mark the recognition of tissue damage after partial hepatectomy (PHx) and the onset of regeneration, hepatocytes are primed to enter the pre-replicative phase of the cell cycle (G1) and respond to the mitogenic effect of growth factors. The priming phase is controlled by several cytokines that activate a variety of normally latent transcription factors (TFs) important during the initial stages of liver regeneration before the onset of de novo protein synthesis and entry into the cell cycle. In recent years, the use of microarray technology has considerably expanded the list of identified changes in early gene expression and started bringing new insight into regulatory processes in the course of liver regeneration. A notable observation in these studies is the broad range of cellular processes that appears to be represented among these genes. However, our understanding of the temporal patterns of gene expression and of the upstream regulatory signals responsible for these patterns is still limited. Our goal is to obtain a detailed perspective on the time course of early responses and to gain insight into the network of intracellular signaling and transcriptional/translational events that drive the functional response of the liver tissue.

In this study we used cDNA microarrays to monitor changes in gene expression at 1, 2, 4, 6 h after PHx in remnant livers in the rat. We adopted a novel approach to analyze the microarray data that extends beyond the list of differentially expressed genes and focuses on the characterization of their transcriptional regulation. Candidate TFs responsible for differential expression profiles of the immediate early genes were characterized using the Promoter Analysis and Interaction Network Toolset (PAINT) software (Vadigepalli et al., 2003). Analysis of the gene expression time series data using ANOVA resulted in a total of 309 genes significantly up- or down-regulated at any of the four time points at ~20% false discovery rate (FDR) threshold. The 309 differentially regulated genes were clustered according their expression profiles. Six clusters provided maximum information on distinct temporal patterns and were well distinguishable from randomized data partitioning. We validated these results using qRT-PCR on a total of 17 genes that represent the response profiles in the different clusters.

PAINT analysis identified 22 TF binding sites enriched (FDR<30%) in individual clusters with distinct temporal gene expression patterns. Some of these TFs, e.g., NFкB, HNF1, C/EBP, CREB, ATF, GATA, are known to be involved in the early phase of liver regeneration from previous studies, whereas others (AP2α, LEF1, PAX6) are novel predictions. and are known to contribute to the regulation of cellular processes related to proliferation and differentiation in many tissues. In order to corroborate the PAINT analysis, we obtained time series data on the DNA binding activity detected in nuclear extracts from remnant livers for several of the transcription factors implicated by our PAINT analysis. The regulatory dynamics we observe is generally consistent with the differential gene expression pattern between 1h and 6h post PHx. In particular, the temporal patterns of NFκB and GATA-1 activity are consistent with the expression pattern of Cluster 4 in which the NFκB and GATA binding sites were found to be enriched in our computational analysis. The early changes in PAX-6 activity also confirmed the potential role of this TF in regulation of some of the immediate-early gene expression (Cluster 2 genes). It is notable that for many of the TFs analyzed that show an early transient increase, we observed a significant resurgence in the DNA-binding activity between 4h and 6h. The resurgence phase coincides with the gene expression profile that suggests a broad range of functional changes occurring between 4 and 6 hrs after PHx.

Our study highlights significant candidate mechanisms for transcriptional control of specific genes and gene clusters in the onset of liver regeneration. These findings also emphasize the fact that the study of any individual factor will not capture the systemic nature of the regulatory machinery that drives the regenerative response of the liver to PHx. We are actively pursuing chromatin immunoprecipitation and related methodologies to identify the functional role of each TF in individual gene responses. Our study points not only to the complexity of the transcriptional control of the early response to PHx, but also suggests that there is a clear underlying organization to the temporal response of genes in different functional categories that is driven by transcriptional regulation. The data reported here should provide a basis for a more detailed analysis of the role of each of these TFs to the regulation of individual genes and gene categories.

REFERENCES:

1. Taub R. (2004). Liver regeneration: from myth to mechanism. NatRev 5: 836–847.
2. Vadigepalli R, Chakravarthula P, Zak DE, Schwaber JS,Gonye GE (2003) PAINT: a promoter analysis and interaction network generation tool for gene regulatory network identification. Omics 7:235-252.