Antagonistic regulation of type I collagen gene expression by interferon-gamma and transforming growth factor-beta. Integration at the level of p300/CBP transcriptional coactivators.

Among the extracellular signals that modulate the synthesis of collagen, transforming growth factor-beta (TGF-beta) and interferon-gamma (IFN-gamma) are preeminent. These two cytokines exert antagonistic effects on fibroblasts, and play important roles in the physiologic regulation of extracellular matrix turnover. We have shown previously that in normal skin fibroblasts, TGF-beta positively regulates alpha2(I) procollagen gene (COL1A2) promoter activity through the cellular Smad signal transduction pathway. In contrast, IFN-gamma activates Stat1alpha, down-regulates COL1A2 transcription, and abrogates its stimulation induced by TGF-beta. The level of integration of the two pathways mediating antagonistic collagen regulation is unknown. We now report that IFN-gamma abrogates TGF-beta-stimulated COL1A2 transcription in fibroblasts by inhibiting Smad activities. IFN-gamma appears to induce competition between activated Stat1alpha and Smad3 for interaction with limiting amounts of cellular p300/CBP. Overexpression of p300 restored COL1A2 stimulation by TGF-beta in the presence of IFN-gamma, and potentiated IFN-gamma-dependent positive transcriptional responses. In contrast to fibroblasts, in U4A cells lacking Jak1 and consequently unable to activate Stat1alpha-mediated responses, IFN-gamma failed to repress TGF-beta-induced transcription. These results indicate that as essential coactivators for both Smad3 and Stat1alpha, nuclear p300/CBP integrate signals that positively or negatively regulate COL1A2 transcription. The findings implicate a novel mechanism to account for antagonistic interaction of Smad and Jak-Stat pathways in regulation of target genes. In fibroblasts responding to cytokines with opposing effects on collagen transcription, the relative levels of cellular coactivators, and their interaction with regulated transcription factors, may govern the net effect.