Is muscle hypertrophy following resistance exercise regulated by truncated splice variants of PGC-1<i>α</i>?
Bibliographic record
Abstract
In this issue, the investigation by Lundberg et al. revisited a classic question of how muscle hypertrophy occurs following resistance exercise but not endurance exercise in human skeletal muscle. A recent study suggested the master transcriptional co-activator PGC-1α, known for regulating multiple transcriptional programs encoding mitochondrial and other metabolic proteins following endurance exercise, may also regulate muscle hypertrophy after resistance exercise through a truncated variant termed PGC-1α4 (Ruas et al. 2012). Based on these findings, Lundberg and colleagues reasoned this model would predict a greater expression of this splice variant following resistance exercise vs endurance exercise in human skeletal muscle. In contrast to this model, their results demonstrate similar responses in the expression of truncated splice variants to both modalities. Collectively, these findings suggest a single splice variant of PGC-1α may not be unique in its role in regulating muscle hypertrophy and that control of hypertrophy following resistance exercise may be distributed across a broader array of mechanisms in humans than previously demonstrated in rodent and cell culture models (Ruas et al. 2012). There are limitations to our understanding of the distinct signalling mechanisms regulating muscle hypertrophy vs metabolic adaptations to resistance and endurance exercise respectively. This is an intriguing topic given both types of exercises would seemingly generate many of the same stimuli for adaptation (calcium transients, energy deprivation, catecholamine responses, etc.) albeit to differing degrees. Furthermore, identifying the unique manner in which hypertrophy is dissociated from improved metabolic regulation with either modality may have impact on understanding their utility in maintaining muscle health throughout the lifespan, as well as explaining exercise intolerances in specific diseased populations. Various signalling mechanisms have been attributed to hypertrophy following resistance exercise that may be distinctly regulated from metabolic adaptations to endurance-type exercise (see Egan & Zierath 2013 for review). As noted by Lundberg and colleagues, Ruas et al. (2012) suggest an additional level of control of hypertrophy may exist through truncated variants of the master transcriptional co-activator PGC-1α. PGC-1α regulates numerous transcriptional programs encoding oxidative metabolic pathways and has been linked to the expansion of the mitochondrial reticulum following endurance exercise (see Russell et al. 2014 for review). Early reports of truncated PGC-1α proteins in skeletal muscle (Kakuma et al. 2000, Baar et al. 2002) were followed by identification of splice variants of the PGC-1α mRNA transcript stemming from two promoters (Miura et al. 2008, Chinsomboon et al. 2009, Yoshioka et al. 2009, Zhang et al. 2009). The physiological relevance of truncated PGC-1α proteins instantly came to question. Recently, Norrbom et al. (2011) were the first to demonstrate exercise upregulates PGC-1α splice variants from both promoters in human skeletal muscle. Later, Ruas et al. (2012) suggested one truncated splice variant – in particular PGC-1α4 – played a unique role in regulating skeletal muscle mass following resistance exercise. Indeed, over-expression and knockdown of PGC-1α4 splice variant increased and decreased muscle mass respectively in cell culture and rodent models. Furthermore, they showed PGC-1α4 mRNA was elevated in response to resistance exercise in human skeletal muscle. The authors suggested PGC-1α4 may be unique from the other splice variants by contributing to the regulation of hypertrophy following resistance exercise. The similar responses of splice variants to acute (Ydfors et al. 2013, Lundberg et al. 2014) and chronic (Lundberg et al. 2014) exercise of both modalities in human skeletal muscle challenge this idea of splice variant-specific regulation of adaptation to exercise. Hence, these studies offer two different perspectives. Ruas et al. imply a truncated PGC-1α protein may have a unique reactivity with factors regulating transcriptional programs determining muscle mass as opposed to metabolic capacities, whereas the full length PGC-1α may be distinct in its reactivity with promoters linked to mitochondrial content. In contrast, Lundberg et al. argue the lack of a relationship between exercise modality and truncated or non-truncated PGC-1α transcripts underscores the complexity of muscle adaptation to exercise and suggests the somewhat reductionist model of a single splice variant-controlling muscle mass might not represent a significant mechanism of regulating muscle hypertrophy to chronic resistance exercise in humans. Adding to the discrepant findings, specific truncated splice variants were suggested to be regulated distinctly by two different promoters (Ruas et al. 2012), whereas reports focusing on human skeletal muscle demonstrated both exercise modalities upregulate truncated splice variants from both promoters (Norrbom et al. 2011, Ydfors et al. 2013, Lundberg in this issue). It was suggested that the disparate findings might be traced to the use of primers in the Ruas study that do not distinguish between both promoters (discussed in Ydfors et al. 2013). The Lundberg and Ydfors studies used primers that capture pooled truncated transcripts from both promoters, whilst the Ruas study may not have been able to distinguish between either promoter for PGC-1α (discussed in Ydfors et al. 2013). Lundberg and Ydfors emphasize that all truncated and non-truncated splice variants, which includes PGC-1α4, responded similarly to both exercise modalities in humans which was not predicted based on the clear effect of PGC-1α4 on regulating muscle mass in non-exercised rodent and cell culture models (Ruas et al. 2012). Collectively, comparing the Lundberg paper to the preceding literature highlights the difficulty in translating mechanistic discoveries in cell culture and rodent models to human adaptation. Indeed, determining mechanisms in humans pose obvious challenges particularly with hypotheses related to genetic regulatory processes. This fact clearly underscores the importance of establishing mechanism in cell culture and rodent models (Ruas et al. 2012). Nevertheless, comparative approaches (exercise modalities, subject populations, etc.) are often the main design in human-based exercise physiology research due to a clear lack of pharmacological/genomic approaches to isolate the effect of specific transcripts during exercise adaptation. Working within these constraints of human research, many investigations have adopted designs that encompass a time-course or examine the effects of chronic training on acute responses to exercise. These approaches relate the transcriptional responses following one exercise bout to the eventual change in phenotype and generally posit that muscle adaptation to exercise is a product of repeated accumulation of mRNA transcripts that eventually expand the proteome responsible for muscle fitness (Williams & Neufer 1996, Pilegaard et al. 2000, Fluck & Hoppeler 2003, Booth & Neufer 2006, Perry et al. 2010). Lundberg et al. adopted a strong design comparing the response of splice variants to acute exercise as muscle fitness improved over 5 weeks from an ‘un-trained’ to ‘trained’ state. However, they still observed similar responses in truncated splice variants to both exercise types rather than greater-truncated variants post-resistance exercise as predicted from the Ruas study (2012). In an attempt to reconcile these apparent discrepant findings of Ruas, Lundberg and Ydfors, it may be possible that the responses of all splice variants to resistance exercise reflect the need for simultaneous improvements in both muscle mass and metabolic capacities. However, hypertrophy is not necessarily expected following endurance exercise, suggesting the similar responses in all splice variants to both modalities may have little to do with increasing muscle mass and are more related to the known role of PGC-1α in regulating metabolic capacities. The search continues for a unified conceptual model that explains how muscle mass vs. metabolic capacities are differentially regulated by exercise depending on whether the challenge is endurance or resistance. Should PGC-1α splice variant-specific control be added to the current list of candidate mechanisms differentiating hypertrophy vs. metabolic adaptations to exercise in human skeletal muscle (see Egan & Zierath 2012 for review)? The findings of Lundberg (this issue) and Ydfors et al. (2013) do not support the proposal that skeletal muscle hypertrophy following resistance exercise is mediated primarily through PGC-1α4. Nevertheless, the clear effect of a truncated splice variant in regulating muscle mass in non-exercise models (Ruas et al. 2012) justifies additional investigation into whether it plays a greater role in non-exercise challenges to muscle (hormonal regulation during development, nutritional influences, etc.). Whether truncated forms of PGC-1α are dedicated specifically to endurance or resistance exercise-induced adaptations remains to be determined, but this will remain a difficult task in humans given the similar splice variant responses and indeed the plethora of signalling networks activated in both modalities. None.
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Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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