Project description:The peroxisome proliferator-activated receptor γ co-activator 1α (PGC-1α) coordinates the transcriptional network response to promote an improved endurance capacity in skeletal muscle, e.g. by co-activating the estrogen-related receptor α (ERRα) in the regulation of oxidative substrate metabolism. Despite a close functional relationship, the interaction between these two proteins has not been studied on a genomic level. We now mapped the genome-wide binding of ERRα to DNA in skeletal muscle cell line with elevated PGC-1α and linked the DNA recruitment to global PGC-1α target gene regulation. We found that, surprisingly, ERRα co-activation by PGC-1α is only observed in the minority of all PGC-1α recruitment sites. Nevertheless, a majority of PGC-1α target gene expression is dependent on ERRα. Intriguingly, the interaction between these two proteins is controlled by the genomic context of response elements, in particular the relative GC and CpG content, monomeric and dimeric repeat binding site configuration for ERRα, and adjacent recruitment of the transcription factor SP1. These findings thus not only reveal an unprecedented insight into the regulatory network underlying muscle cell plasticity, but also strongly link the genomic context of DNA response elements to control transcription factor - co-regulator interactions.
Project description:The peroxisome proliferator-activated receptor γ co-activator 1α (PGC-1α) coordinates the transcriptional network response to promote an improved endurance capacity in skeletal muscle, e.g. by co-activating the estrogen-related receptor α (ERRα) in the regulation of oxidative substrate metabolism. Despite a close functional relationship, the interaction between these two proteins has not been studied on a genomic level. We now mapped the genome-wide binding of ERRα to DNA in skeletal muscle cell line with elevated PGC-1α and linked the DNA recruitment to global PGC-1α target gene regulation. We found that, surprisingly, ERRα co-activation by PGC-1α is only observed in the minority of all PGC-1α recruitment sites. Nevertheless, a majority of PGC-1α target gene expression is dependent on ERRα. Intriguingly, the interaction between these two proteins is controlled by the genomic context of response elements, in particular the relative GC and CpG content, monomeric and dimeric repeat binding site configuration for ERRα, and adjacent recruitment of the transcription factor SP1. These findings thus not only reveal an unprecedented insight into the regulatory network underlying muscle cell plasticity, but also strongly link the genomic context of DNA response elements to control transcription factor - co-regulator interactions.
Project description:Skeletal muscle tissue shows an extraordinary cellular plasticity, but the underlying molecular mechanisms are still poorly understood. Here we use a combination of experimental and computational approaches to unravel the complex transcriptional network of muscle cell plasticity centered on the peroxisome proliferator-activated receptor γ coactivator 1α (PGC-1α), a regulatory nexus in endurance training adaptation. By integrating data on genome-wide binding of PGC-1α and gene expression upon PGC-1α over-expression with comprehensive computational prediction of transcription factor binding sites (TFBSs), we uncover a hitherto underestimated number of transcription factor partners involved in mediating PGC-1α action. In particular, principal component analysis of TFBSs at PGC-1α binding regions predicts that, besides the well-known role of the estrogen-related receptor α (ERRα), the activator protein-1 complex (AP-1) plays a major role in regulating the PGC-1α-controlled gene program of hypoxia response. Our findings thus reveal the complex transcriptional network of muscle cell plasticity controlled by PGC-1α.
Project description:Skeletal muscle tissue shows an extraordinary cellular plasticity, but the underlying molecular mechanisms are still poorly understood. Here we use a combination of experimental and computational approaches to unravel the complex transcriptional network of muscle cell plasticity centered on the peroxisome proliferator-activated receptor γ coactivator 1α (PGC-1α), a regulatory nexus in endurance training adaptation. By integrating data on genome-wide binding of PGC-1α and gene expression upon PGC-1α over-expression with comprehensive computational prediction of transcription factor binding sites (TFBSs), we uncover a hitherto underestimated number of transcription factor partners involved in mediating PGC-1α action. In particular, principal component analysis of TFBSs at PGC-1α binding regions predicts that, besides the well-known role of the estrogen-related receptor α (ERRα), the activator protein-1 complex (AP-1) plays a major role in regulating the PGC-1α-controlled gene program of hypoxia response. Our findings thus reveal the complex transcriptional network of muscle cell plasticity controlled by PGC-1α.
Project description:Skeletal muscle tissue shows an extraordinary cellular plasticity, but the underlying molecular mechanisms are still poorly understood. Here we use a combination of experimental and computational approaches to unravel the complex transcriptional network of muscle cell plasticity centered on the peroxisome proliferator-activated receptor γ coactivator 1α (PGC-1α), a regulatory nexus in endurance training adaptation. By integrating data on genome-wide binding of PGC-1α and gene expression upon PGC-1α over-expression with comprehensive computational prediction of transcription factor binding sites (TFBSs), we uncover a hitherto underestimated number of transcription factor partners involved in mediating PGC-1α action. In particular, principal component analysis of TFBSs at PGC-1α binding regions predicts that, besides the well-known role of the estrogen-related receptor α (ERRα), the activator protein-1 complex (AP-1) plays a major role in regulating the PGC-1α-controlled gene program of hypoxia response. Our findings thus reveal the complex transcriptional network of muscle cell plasticity controlled by PGC-1α.
Project description:Reprogramming of cellular metabolism plays a central role in fuelling malignant transformation, and AMPK as well as the PGC-1α/ERRα axis are key regulators of this process. Intersection of gene expression and binding event datasets in breast cancer cells shows that activation of AMPK significantly increases the expression of PGC-1α/ERRα and promotes the binding of ERRα to its cognate sites. Unexpectedly, the data also reveal that ERRα, in concert with PGC-1α, negatively regulates the expression of several one-carbon metabolism genes resulting in substantial perturbations in purine biosynthesis. This PGC-1α/ERRα-mediated repression of one-carbon metabolism promotes the sensitivity of breast cancer cells and tumors to the anti-folate drug methotrexate. These data implicate the PGC-1α/ERRα axis as a core regulatory node of folate cycle metabolism and further suggest that activators of AMPK could be used to modulate this pathway in cancer. We used microarrays to detail the global programme of gene expression following AMPK activation by AICAR in BT474 breast cancer cells.
Project description:Reprogramming of cellular metabolism plays a central role in fuelling malignant transformation, and AMPK as well as the PGC-1α/ERRα axis are key regulators of this process. Intersection of gene expression and binding event datasets in breast cancer cells shows that activation of AMPK significantly increases the expression of PGC-1α/ERRα and promotes the binding of ERRα to its cognate sites. Unexpectedly, the data also reveal that ERRα, in concert with PGC-1α, negatively regulates the expression of several one-carbon metabolism genes resulting in substantial perturbations in purine biosynthesis. This PGC-1α/ERRα-mediated repression of one-carbon metabolism promotes the sensitivity of breast cancer cells and tumors to the anti-folate drug methotrexate. These data implicate the PGC-1α/ERRα axis as a core regulatory node of folate cycle metabolism and further suggest that activators of AMPK could be used to modulate this pathway in cancer. We used microarrays to detail the global program of gene expression following AMPK activation by AICAR in BT474 breast cancer cells.