Bioengineered human myobundles mimic clinical responses of skeletal muscle to drugs

  • Madden L
  • Juhas M
  • Kraus W
  • et al.
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Abstract

Existing in vitro models of human skeletal muscle cannot recapitulate the organization and function of native muscle, limiting their use in physiological and pharmacological studies. Here, we demonstrate engineering of electrically and chemically responsive, contractile human muscle tissues (‘myobundles’) using primary myogenic cells. These biomimetic constructs exhibit aligned architecture, multinucleated and striated myofibers, and a Pax7+ cell pool. They contract spontaneously and respond to electrical stimuli with twitch and tetanic contractions. Positive correlation between contractile force and GCaMP6-reported calcium responses enables non-invasive tracking of myobundle function and drug response. During culture, myobundles maintain functional acetylcholine receptors and structurally and functionally mature, evidenced by increased myofiber diameter and improved calcium handling and contractile strength. In response to diversely acting drugs, myobundles undergo dose-dependent hypertrophy or toxic myopathy similar to clinical outcomes. Human myobundles provide an enabling platform for predictive drug and toxicology screening and development of novel therapeutics for muscle-related disorders.Scientists have developed realistic models of the human liver, lung, and heart that allow them to observe living tissue in the laboratory. These models have helped us to better understand how these organs work and what goes wrong in diseases that affect these organs. The models can also be used to test how new drugs may affect a particular organ without the risk of exposing patients to the drug.Efforts to develop a realistic laboratory model of human muscle tissues that can contract like real muscles have not been as successful to date. This shortcoming has potentially hindered the development of drugs to treat numerous disorders that affect muscles and movement in humans—such as muscular dystrophies, which are diseases in which people progressively lose muscle strength.Some important drugs, like cholesterol-lowering statins, have detrimental effects on muscle tissue; one statin was so harmful to muscles that it had to be withdrawn from the market. As such, it would be useful to have experimental models that would allow scientists to test whether potential drugs damage or treat muscle tissue.Madden et al. have now bioengineered a three-dimensional laboratory model of living muscle tissue made of cells taken from biopsies of several different human patients. These tissues were grown into bundles of muscle fibers on special polymer frames in the laboratory. The bioengineered muscle bundles respond to electrical and chemical signals and contract just like normal muscle. They also exhibit the same structure and signaling as healthy muscle tissue in humans.Madden et al. exposed the muscle tissue bundles to three drugs known to affect muscles to determine if the model could be used to test whether drugs have harmful effects. This revealed that the bundles had weaker contractions in response to statins and the malaria drug chloroquine, just like normal muscles do—and that this effect worsened if more of each drug was used. Madden et al. also found that a drug that strengthens muscle contractions at low doses and damages muscle at high doses in humans has similar effects in the model.As well as this model being used to screen for harmful effects of drugs before clinical trials, the technique used to create the model could be used to grow muscle tissue from patients with muscle diseases. This would help researchers and doctors to better understand the patient's condition and potentially develop more efficient therapies. Also, the technique could be eventually developed to grow healthy muscle tissue to implant in patients who have been injured.

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Madden, L., Juhas, M., Kraus, W. E., Truskey, G. A., & Bursac, N. (2015). Bioengineered human myobundles mimic clinical responses of skeletal muscle to drugs. ELife, 4. https://doi.org/10.7554/elife.04885

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