MicroRNAs (miRNA) are small non-coding RNAs that function as post-transcriptional repressors of gene expression. MicroRNAs silence mRNA translation by direct repression and/or mRNA decay, ultimately influencing protein abundance. However, a single miRNA can target multiple genes; likewise, multiple miRNAs can impact a single transcript, complicating a relatively simple process. MicroRNA research is likely to be clinically relevant since miRNAs regulate nearly two-thirds, if not all, of the mammalian genome (Friedman et al. 2009), highlighting miRNAs as a novel target to manipulate gene expression and perhaps control disease. Since the discovery of miRNAs in 1993 in C. elegans (Lee et al. 1993), interest in miRNA biology has been on the rise. A quick search on Pubmed indicates that ∼9000 articles have been published in this area prior to mid-2010, with a peak increase in 2009. The miRNA research in human skeletal muscle is incredibly limited and that involving exercise is nearly non-existent.
MicroRNAs are ubiquitously expressed in a broad range of tissues while some miRNAs are tissue-specific. Muscle-specific miRNAs (myomiRs), miR-1, -133a, -133b and -206, are appropriately termed because elevated expression is limited primarily to striated muscle (Beuvink et al. 2007), indicating that they may regulate tissue specificity and function. Unfortunately, little is known of the biological role of myomiRs in skeletal muscle or their specific gene targets. At a minimum, it appears that myomiRs may be associated with muscle growth and regeneration (Chen et al. 2006; Nakasa et al. 2009), implicating a potential role in skeletal muscle adaptation to exercise. Indeed, myomiR expression is acutely altered during post-exercise recovery in humans and rats (Drummond et al. 2008; Safdar et al. 2009) while models of muscle overload can significantly alter myomiR expression to new steady state levels (McCarthy & Esser, 2007).
In an article in this issue of The Journal of Physiology, Nielsen et al. (2010) provide intriguing data in skeletal muscle of young men that myomiR expression levels transiently increased 1 h after a bout of endurance exercise while myomiR expression at rest decreased to a new steady state level following 12 weeks of aerobic training, returning to pre-exercise levels following a period of inactivity. Interestingly, muscle-specific miRNA expression levels not only change with exercise but the expression patterns are different following an acute bout of exercise versus at rest following repeated exercise or inactivity. But what do these alterations in miRNA expression mean in light of how the muscle adapts to the demands of physical activity?
As highlighted by Nielsen et al. (2010), making associations between specific miRNAs and a predicted downstream target can be very difficult. In fact, inverse relationships between individual myomiRs and predicted targets, Cdc42 and ERK1/2, could not be determined. This raises some uncertainty or complexity of one-to-one relationships between miRNAs and their targets. Is it possible that miRNAs function collectively to regulate expression of a predicted gene target? As appropriately coined in a recent review, miRNAs may ‘hunt in packs’ (Lanceta et al. 2010). Thus, even modest changes in a group of miRNAs may impact the expression of several (or hundreds) of genes perhaps with a goal of regulating a specific signalling network (e.g. cell cycle control). The complexity of miRNA biology makes it incredibly difficult to deduce relationships between miRNAs and their targets (especially in human models). The use of miRNA and gene arrays complimented by bioinformatics prediction software to indentify groups of miRNAs, related signalling networks, and gene targets may help us make sense of the biological relevance of miRNAs. Furthermore, paralleling human studies with mechanistic cell experiments (functional assays) may significantly aid in validating miRNA targets following exercise.
Future perspective
The novel work of Nielsen et al. (2010) clearly indicates that myomiR expression can be modulated following acute and chronic endurance exercise in humans. This study opens a new and exciting vista to increase our understanding of the role of miRNAs in muscle biology. For example, are other miRNAs involved in muscle adaptation to endurance exercise? Aerobic training is notably characterized by alterations in metabolic and contractile properties of muscle. Following an acute bout of endurance exercise in mice, Safdar et al. (2009) noted changes in the expression level not only of miR-1 but also of miR-23, a miRNA tightly correlated with PGC-1α expression. Additionally, emerging evidence suggests that slow myosin heavy chain expression is regulated by miR-499 and -208b (McCarthy et al. 2009), newly identified members of the myomiR family, while overexpression of miR-499 remarkably increased muscle endurance (van Rooij et al. 2009). In light of the findings of Nielsen et al. it is likely that other miRNAs are involved in the exercise-induced muscle adaptations following endurance-type training.
Finally, what is regulating myomiR transcription? Could it be myogenic regulatory factors (Rao et al. 2006), hormones, or another miRNA(s)? Is there a role of neuronal input? What about the function of miR-486 in muscle development (Small et al. 2010)? What is the effect of ageing on myomiR expression? For example, Nielsen et al. (2010) found no differences in myomiR expression following an insulin infusion, in contrast to the results of Granjon et al. (2009) following a similar insulin infusion protocol in older men. None would argue that what we currently know of the biological role of miRNAs following exercise and their gene targets is defined by the name of the molecule: ‘micro’. The data from Nielsen et al. (2010) form just the tip of the iceberg of our collective miRNA knowledge and are important for enabling us to push forward to better elucidate the role of miRNAs in exercise. This should excite many, as this area of research in muscle adaptation to exercise is wide open for investigation.
References
- Beuvink I, Kolb FA, Budach W, Garnier A, Lange J, Natt F, Dengler U, Hall J, Filipowicz W, Weiler J. Nucleic Acids Res. 2007;35:e52. doi: 10.1093/nar/gkl1118. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Chen JF, Mandel EM, Thomson JM, Wu Q, Callis TE, Hammond SM, Conlon FL, Wang DZ. Nat Genet. 2006;38:228–233. doi: 10.1038/ng1725. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Drummond MJ, McCarthy JJ, Fry CS, Esser KA, Rasmussen BB. Am J Physiol Endocrinol Metab. 2008;295:E1333–E1340. doi: 10.1152/ajpendo.90562.2008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Friedman RC, Farh KK, Burge CB, Bartel DP. Genome Res. 2009;19:92–105. doi: 10.1101/gr.082701.108. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Granjon A, Gustin MP, Rieusset J, Lefai E, Meugnier E, Guller I, Cerutti C, Paultre C, Disse E, Rabasa-Lhoret R, Laville M, Vidal H, Rome S. Diabetes. 2009;58:2555–2564. doi: 10.2337/db09-0165. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Lanceta J, Prough RA, Liang R, Wang E. Exp Gerontol. 2010;45:269–278. doi: 10.1016/j.exger.2009.12.009. [DOI] [PubMed] [Google Scholar]
- Lee RC, Feinbaum RL, Ambros V. Cell. 1993;75:843–854. doi: 10.1016/0092-8674(93)90529-y. [DOI] [PubMed] [Google Scholar]
- McCarthy JJ, Esser KA. J Appl Physiol. 2007;102:306–313. doi: 10.1152/japplphysiol.00932.2006. [DOI] [PubMed] [Google Scholar]
- McCarthy JJ, Esser KA, Peterson CA, Dupont-Versteegden EE. Physiol Genomics. 2009;39:219–226. doi: 10.1152/physiolgenomics.00042.2009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Nakasa T, Ishikawa M, Shi M, Shibuya H, Adachi N, Ochi M. J Cell Mol Med. 2009 doi: 10.1111/j.1582-4934.2009.00898.x. in press. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Nielsen S, Scheele C, Yfanti C, Åkerstrom T, Nielsen AR, Pedersen BK, Laye M. J Physiol. 2010;588:4029–4037. doi: 10.1113/jphysiol.2010.189860. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Rao PK, Kumar RM, Farkhondeh M, Baskerville S, Lodish HF. Proc Natl Acad Sci U S A. 2006;103:8721–8726. doi: 10.1073/pnas.0602831103. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Safdar A, Abadi A, Akhtar M, Hettinga BP, Tarnopolsky MA. PLoS ONE. 2009;4:e5610. doi: 10.1371/journal.pone.0005610. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Small EM, O’Rourke JR, Moresi V, Sutherland LB, McAnally J, Gerard RD, Richardson JA, Olson EN. Proc Natl Acad Sci U S A. 2010;107:4218–4223. doi: 10.1073/pnas.1000300107. [DOI] [PMC free article] [PubMed] [Google Scholar]
- van Rooij E, Quiat D, Johnson BA, Sutherland LB, Qi X, Richardson JA, Kelm RJ, Jr, Olson EN. Dev Cell. 2009;17:662–673. doi: 10.1016/j.devcel.2009.10.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
