Plasticity of cells, tissues, and organs is controlled by the coordinated transcription of biological programs. However, the mechanisms orchestrating such context-specific transcriptional networks mediated by the dynamic interplay of transcription factors and coregulators are poorly understood. The peroxisome proliferator–activated receptor γ coactivator 1α (PGC-1α) is a prototypical master regulator of adaptive transcription in various cell types. We now uncovered a central function of the C-terminal domain of PGC-1α to bind RNAs and assemble multiprotein complexes including proteins that control gene transcription and RNA processing. These interactions are important for PGC-1α recruitment to chromatin in transcriptionally active liquid-like nuclear condensates. Notably, such a compartmentalization of active transcription mediated by liquid–liquid phase separation was observed in mouse and human skeletal muscle, revealing a mechanism by which PGC-1α regulates complex transcriptional networks. These findings provide a broad conceptual framework for context-dependent transcriptional control of phenotypic adaptations in metabolically active tissues.
Background Interventions to preserve functional capacities at advanced age are becoming increasingly important. So far, exercise provides the only means to counteract age‐related decrements in physical performance and muscle function. Unfortunately, the effectiveness of exercise interventions in elderly populations is hampered by reduced acceptance and compliance as well as disuse complications. We therefore studied whether application of interleukin‐6 (IL‐6), a pleiotropic myokine that is induced by skeletal muscle activity and exerts broad systemic effects in response to exercise, affects physical performance and muscle function alone or in combination with training in aged mice. Methods Sedentary old male mice (Sed+Saline, n = 15) were compared with animals that received recombinant IL‐6 (rIL‐6) in an exercise‐mimicking pulsatile manner (Sed+IL‐6, n = 16), were trained with a moderate‐intensity, low‐volume endurance exercise regimen (Ex+Saline, n = 13), or were exposed to a combination of these two interventions (Ex+IL‐6, n = 16) for 12 weeks. Before and at the end of the intervention, mice underwent a battery of tests to quantify endurance performance, muscle contractility in situ, motor coordination, and gait and metabolic parameters. Results Mice exposed to enhanced levels of IL‐6 during endurance exercise bouts showed superior improvements in endurance performance (33% more work and 12% greater peak power compared with baseline), fatigue resistance in situ (P = 0.0014 vs. Sed+Saline; P = 0.0199 vs. Sed+IL‐6; and P = 0.0342 vs. Ex+Saline), motor coordination (rotarod performance, P = 0.0428), and gait (gait speed, P = 0.0053) following training. Pulsatile rIL‐6 treatment in sedentary mice had only marginal effects on glucose tolerance and some gait parameters. No increase in adverse events or mortality related to rIL‐6 treatment was observed. Conclusions Administration of rIL‐6 paired with treadmill running bouts potentiates the adaptive response to a moderate‐intensity low‐volume endurance exercise regimen in old mice, while being safe and well tolerated.
The peroxisome-proliferator-activated receptor-γ coactivator-1α (PGC-1α) integrates environmental cues by controlling complex transcriptional networks in various metabolically active tissues. However, it is unclear how a transcriptional coregulator coordinates dynamic biological programs in response to multifaceted stimuli such as endurance training or fasting. Here, we discovered a central function of the poorly understood C-terminal domain (CTD) of PGC-1α to bind RNAs and assemble multi-protein complexes. Surprisingly, in addition to controlling the coupling of transcription and processing of target genes, RNA binding is indispensable for the recruitment of PGC-1α to chromatin into liquid-like nuclear condensates, which compartmentalize and regulate active transcription. These results demonstrate a hitherto unsuspected molecular mechanism by which complexity in the regulation of large transcriptional networks by PGC-1α is achieved. These findings are not only essential for the basic understanding of transcriptional coregulator-driven control of biological programs, but will also help to devise new strategies to modulate these processes in pathological contexts in which PGC-1α function is dysregulated, such as type 2 diabetes, cardiovascular diseases or skeletal muscle wasting.
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