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International Symposium on Computer Methods in Biomechanics and Biomedical Engineering

CMBBE 2019: Computer Methods, Imaging and Visualization in Biomechanics and Biomedical Engineering pp 142–157Cite as

Mechano-Physiological Modeling to Probe the Role of Satellite Cells and Fibroblasts in Cerebral Palsy Muscle Degeneration

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Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB,volume 36)

Abstract

Cerebral palsy (CP) is a neural disorder that greatly affects the musculoskeletal system, but the causes and progression of muscle degeneration are poorly understood. The CP muscle environment is altered compared to typical, particularly with the presence of fibrosis and fewer satellite cells (SCs). Healthy regeneration of muscle requires both SCs—a progenitor cell population for muscle cells—and fibroblasts—the primary instigators of extracellular matrix (ECM) remodeling. SCs and fibroblasts interact, but their dynamics at the muscle level are complex and nonlinear; nevertheless, detailed knowledge of these dynamics is necessary for a thorough understanding of muscle degeneration in CP and as a precursor to the development of novel clinical interventions. In this work, computational agent-based modeling (ABM) was used to investigate muscle regeneration by representing muscle tissue adaptation at the cellular level following injury. We used an ABM to vary SC levels in simulated muscle regeneration, which showed that muscle fiber recovery was impaired when SC levels were decreased, whereas fibroblast activity was enhanced. Complete recovery of damaged muscle tissue was sensitive to the level of injury. Coupling of this ABM with finite element modeling will contribute to the development of a mechano-physiological model to probe muscle injury and regeneration in CP.

Keywords

  • Cerebral palsy
  • Agent based modeling
  • Muscle regeneration

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References

  1. Graham, H.K., Rosenbaum, P., Paneth, N., Dan, B., Lin, J.P., Damiano, Di.L., Becher, J.G., Gaebler-Spira, D., Colver, A., Reddihough, Di.S., Crompton, K.E., Lieber, R.L.: Cerebral palsy. Nat. Rev. Dis. Prim. 2, 19–20 (2016). https://doi.org/10.1038/nrdp.2015.82

  2. Kinney, M.C., Dayanidhi, S., Dykstra, P.B., McCarthy, J.J., Peterson, C.A., Lieber, R.L.: Reduced skeletal muscle satellite cell number alters muscle morphology after chronic stretch but allows limited serial sarcomere addition. Muscle Nerve 55, 384–392 (2017). https://doi.org/10.1002/mus.25227

    CrossRef  Google Scholar 

  3. Fahey, M.C., Maclennan, A.H., Kretzschmar, D., Gecz, J., Kruer, M.C.: The genetic basis of cerebral palsy. Dev. Med. Child Neurol. 59, 462–469 (2017). https://doi.org/10.1111/dmcn.13363

    CrossRef  Google Scholar 

  4. Norton, N.S.: Cerebral palsy. xPharm Compr. Pharmacol. Ref. 1–5 (2007). https://doi.org/10.1016/b978-008055232-3.60641-5

  5. Lieber, R.L., Runesson, E., Einarsson, F., Fridén, J.: Inferior mechanical properties of spastic muscle bundles due to hypertrophic but compromised extracellular matrix material. Muscle Nerve 28, 464–471 (2003). https://doi.org/10.1002/mus.10446

    CrossRef  Google Scholar 

  6. Kerr Graham, H., Selber, P.: Musculoskeletal aspects of cerebral palsy. J. Bone Jt. Surg. 85, 157–166 (2003). https://doi.org/10.1302/0301-620X.85B2.14066

    CrossRef  Google Scholar 

  7. Friden, J., Lieber, R.L.: Spastic muscle cells are shorter and stiffer than normal cells. Muscle Nerve. 26, 157–164 (2003). https://doi.org/10.1002/mus.10247

    CrossRef  Google Scholar 

  8. Mathewson, M.A., Lieber, R.L.: Pathophysiology of muscle contractures in cerebral palsy. Phys. Med. Rehabil. Clin. N. Am. 26, 57–67 (2015). https://doi.org/10.1016/j.pmr.2014.09.005

    CrossRef  Google Scholar 

  9. Smith, L.R., Lee, K.S., Ward, S.R., Chambers, H.G., Lieber, R.L.: Hamstring contractures in children with spastic cerebral palsy result from a stiffer extracellular matrix and increased in vivo sarcomere length. J. Physiol. 589, 2625–2639 (2011). https://doi.org/10.1113/jphysiol.2010.203364

    CrossRef  Google Scholar 

  10. Willerslev-Olsen, M., Choe Lund, M., Lorentzen, J., Barber, L., Kofoed-Hansen, M., Nielsen, J.B.: Impaired muscle growth precedes development of increased stiffness of the triceps surae musculotendinous unit in children with cerebral palsy. Dev. Med. Child Neurol. 60, 672–679 (2018). https://doi.org/10.1111/dmcn.13729

    CrossRef  Google Scholar 

  11. Proske, U., Morgan, D.L.: Muscle damage from eccentric exercise: mechanism, mechanical signs, adaptation and clinical applications. J. Physiol. 537, 333–345 (2001)

    CrossRef  Google Scholar 

  12. Chargé, S.B.P., Rudnicki, M.A.: Cellular and molecular regulation of muscle regeneration. 209–238 (2009). https://doi.org/10.1152/physrev.00019.2003

  13. Sciorati, C., Rigamonti, E., Manfredi, A.A., Rovere-Querini, P.: Cell death, clearance and immunity in the skeletal muscle. Cell Death Differ. 23, 927–937 (2016). https://doi.org/10.1038/cdd.2015.171

    CrossRef  Google Scholar 

  14. Tidball, J.G., Villalta, S.A.: Regulatory interactions between muscle and the immune system during muscle regeneration. Am. J. Physiol. Regul. Integr. Comp. Physiol. 298, R1173–R1187 (2010). https://doi.org/10.1152/ajpregu.00735.2009

    CrossRef  Google Scholar 

  15. Ten Broek, R.W., Grefte, S., Von Den Hoff, J.W.: Regulatory factors and cell populations involved in skeletal muscle regeneration. J. Cell. Physiol. 224, 7–16 (2010). https://doi.org/10.1002/jcp.22127

    CrossRef  Google Scholar 

  16. Arnold, L., Henry, A., Poron, F., Baba-Amer, Y., van Rooijen, N., Plonquet, A., Gherardi, R.K., Chazaud, B.: Inflammatory monocytes recruited after skeletal muscle injury switch into antiinflammatory macrophages to support myogenesis. J. Exp. Med. 204, 1057–1069 (2007). https://doi.org/10.1084/jem.20070075

    CrossRef  Google Scholar 

  17. Järvinen, T.A., Kääriäinen, M., Äärimaa, V., Järvinen, M., Kalimo, H.: Skeletal muscle repair after exercise-induced injury. In: Schiaffino, S., Partridge, T. (eds.) Skeletal Muscle Repair and Regeneration, pp. 217–242. Springer, Heidelberg (2008)

    CrossRef  Google Scholar 

  18. Lu, P., Takai, K., Weaver, V.M., Werb, Z.: Extracellular matrix degradation and remodeling in development and disease. Cold Spring Harb. Perspect. Biol. 3, a005058–a005058 (2011). https://doi.org/10.1101/cshperspect.a005058

    CrossRef  Google Scholar 

  19. Lepper, C., Conway, S.J., Fan, C.M.: Adult satellite cells and embryonic muscle progenitors have distinct genetic requirements. Nature 460, 627–631 (2009). https://doi.org/10.1038/nature08209

    CrossRef  Google Scholar 

  20. Yin, H., Price, F., Rudnicki, M.A.: Satellite cells and the muscle stem cell niche. Physiol. Rev. 93, 23–67 (2013). https://doi.org/10.1152/physrev.00043.2011

    CrossRef  Google Scholar 

  21. Wang, Y.X., Rudnicki, M.A.: Satellite cells, the engines of muscle repair. Nat. Rev. Mol. Cell Biol. 13, 127–133 (2012). https://doi.org/10.1038/nrm3265

    CrossRef  Google Scholar 

  22. Snijders, T., Nederveen, J.P., McKay, B.R., Joanisse, S., Verdijk, L.B., van Loon, L.J.C., Parise, G.: Satellite cells in human skeletal muscle plasticity. Front. Physiol. 6, 283 (2015). https://doi.org/10.3389/fphys.2015.00283

    CrossRef  Google Scholar 

  23. Charge, S.B.P., Rudnicki, M.A.: Cellular and molecular regulation of muscle regeneration. Physiol. Rev. 84, 209 (2004). https://doi.org/10.1152/physrev.00019.2003

    CrossRef  Google Scholar 

  24. Ambrosio, F., Kadi, F., Lexell, J., Kelley Fitzgerald, G., Boninger, M.L., Huard, J.: The effect of muscle loading on skeletal muscle regenerative potential: an update of current research findings relating to aging and neuromuscular pathology. Am. J. Phys. Med. Rehabil. 88, 145–155 (2009). https://doi.org/10.1097/PHM.0b013e3181951fc5

    CrossRef  Google Scholar 

  25. Chapman, M.A., Meza, R., Lieber, R.L.: Skeletal muscle fibroblasts in health and disease. Differentiation 92, 108–115 (2016). https://doi.org/10.1016/j.diff.2016.05.007

    CrossRef  Google Scholar 

  26. Mendias, C.L.: Fibroblasts take the centre stage in human skeletal muscle regeneration. J. Physiol. 595, 5005 (2017). https://doi.org/10.1113/JP274403

    CrossRef  Google Scholar 

  27. Mackey, A.L., Magnan, M., Chazaud, B., Kjaer, M.: Human skeletal muscle fibroblasts stimulate in vitro myogenesis and in vivo muscle regeneration. J. Physiol. 595, 5115–5127 (2017). https://doi.org/10.1113/JP273997

    CrossRef  Google Scholar 

  28. Smith, L.R., Pontén, E., Hedström, Y., Ward, S.R., Chambers, H.G., Subramaniam, S., Lieber, R.L.: Novel transcriptional profile in wrist muscles from cerebral palsy patients. BMC Med. Genom. 2, 44 (2009). https://doi.org/10.1186/1755-8794-2-44

    CrossRef  Google Scholar 

  29. De Bruin, M., Smeulders, M.J., Kreulen, M., Huijing, P.A., Jaspers, R.T.: Intramuscular connective tissue differences in spastic and control muscle: a mechanical and histological study. PLoS One. 9 (2014). https://doi.org/10.1371/journal.pone.0101038

  30. Booth, C.M., Cortina-Borja, M.J.F., Theologis, T.N.: Collagen accumulation in muscles of children with cerebral palsy and correlation with severity of spasticity. Dev. Med. Child Neurol. 43, 314–320 (2001). https://doi.org/10.1111/j.1469-8749.2001.tb00211.x

    CrossRef  Google Scholar 

  31. Foran, J.R.H., Steinman, S., Barash, I., Chambers, H.G., Lieber, R.L.: Structural and mechanical alterations in spastic skeletal muscle. Dev. Med. Child Neurol. 47, 713–717 (2005). https://doi.org/10.1017/S0012162205001465

    CrossRef  Google Scholar 

  32. Smith, L.R., Chambers, H.G., Lieber, R.L.: Reduced satellite cell population may lead to contractures in children with cerebral palsy. Dev. Med. Child Neurol. 55, 264–270 (2013). https://doi.org/10.1111/dmcn.12027

    CrossRef  Google Scholar 

  33. Wilensky, U., Rand, B.: An Introduction to Agent-based Modelling: Modelling Natural, Social and Engineered Complex Systems with NetLogo. The MIT Press, Cambridge (2015)

    Google Scholar 

  34. Abar, S., Theodoropoulos, G.K., Lemarinier, P., O’Hare, G.M.P.: Agent Based Modelling and Simulation tools: a review of the state-of-art software. Comput. Sci. Rev. 24, 13–33 (2017). https://doi.org/10.1016/j.cosrev.2017.03.001

    CrossRef  Google Scholar 

  35. Borgiani, E., Duda, G.N., Checa, S.: Multiscale modeling of bone healing: toward a systems biology approach. Front. Physiol. 8, 287 (2017). https://doi.org/10.3389/fphys.2017.00287

    CrossRef  Google Scholar 

  36. Rouillard, A.D., Holmes, J.W.: Coupled agent-based and finite-element models for predicting scar structure following myocardial infarction. Prog. Biophys. Mol. Biol. 115, 235–243 (2014). https://doi.org/10.1016/j.pbiomolbio.2014.06.010

    CrossRef  Google Scholar 

  37. Zhuan, X., Luo, X., Gao, H., Ogden, R.W.: Coupled agent-based and hyperelastic modelling of the left ventricle post-myocardial infarction. Int. J. Numer. Method. Biomed. Eng. 35, e3155 (2018). https://doi.org/10.1002/cnm.3155

    CrossRef  Google Scholar 

  38. Virgilio, K.M., Martin, K.S., Peirce, S.M., Blemker, S.S.: Agent-based model illustrates the role of the microenvironment in regeneration in healthy and mdx skeletal muscle. J. Appl. Physiol. 125, 1424–1439 (2018). https://doi.org/10.1152/japplphysiol.00379.2018

    CrossRef  Google Scholar 

  39. Martin, K.S., Blemker, S.S., Peirce, S.M.: Agent-based computational model investigates muscle-specific responses to disuse-induced atrophy. J. Appl. Physiol. 118, 1299–1309 (2015). https://doi.org/10.1152/japplphysiol.01150.2014

    CrossRef  Google Scholar 

  40. Thorne, B.C., Bailey, A.M., Peirce, S.M.: Combining experiments with multi-cell agent-based modeling to study biological tissue patterning. Brief. Bioinform. 8, 245–257 (2007). https://doi.org/10.1093/bib/bbm024

    CrossRef  Google Scholar 

  41. Macal, C.M., North, M.J.: Tutorial on agent-based modelling and simulation. J. Simul. 4, 151–162 (2010). https://doi.org/10.1057/jos.2010.3

    CrossRef  Google Scholar 

  42. Gorochowski, T.E.: Agent-based modelling in synthetic biology. Essays Biochem. 60, 325–336 (2016). https://doi.org/10.1042/EBC20160037

    CrossRef  Google Scholar 

  43. An, G.: Integrating physiology across scales and formalizing hypothesis exploration with agent-based modeling. J. Appl. Physiol. 118, 1191–1192 (2015). https://doi.org/10.1152/japplphysiol.00243.2015

    CrossRef  Google Scholar 

  44. Bonabeau, E.: Agent-based modeling: methods and techniques for simulating human systems. Proc. Natl. Acad. Sci. 99, 7280–7287 (2002). https://doi.org/10.1073/pnas.082080899

    CrossRef  Google Scholar 

  45. Mackey, A.L., Kjaer, M.: The breaking and making of healthy adult human skeletal muscle in vivo. Skelet. Muscle 7, 1–18 (2017). https://doi.org/10.1186/s13395-017-0142-x

    CrossRef  Google Scholar 

  46. Miller, K.J., Thaloor, D., Matteson, S., Pavlath, G.K.: Hepatocyte growth factor affects satellite cell activation and differentiation in regenerating skeletal muscle. Am. J. Physiol. Cell Physiol. 278, C174–C181 (2000). https://doi.org/10.1152/ajpcell.2000.278.1.C174

    CrossRef  Google Scholar 

  47. Siegel, A.L., Kuhlmann, P.K., Cornelison, D.D.W.: Muscle satellite cell proliferation and association: new insights from myofiber time-lapse imaging. Skelet. Muscle 1, 1–7 (2011). https://doi.org/10.1186/2044-5040-1-7

    CrossRef  Google Scholar 

  48. Pawlikowski, B., Vogler, T.O., Gadek, K., Olwin, B.B.: Regulation of skeletal muscle stem cells by fibroblast growth factors. Dev. Dyn. 246, 359–367 (2017). https://doi.org/10.1002/dvdy.24495

    CrossRef  Google Scholar 

  49. Rangel-Huerta, E., Maldonado, E.: Transit-amplifying cells in the fast lane from stem cells towards differentiation. Stem Cells Int. 2017, 1–10 (2017). https://doi.org/10.1155/2017/7602951

    CrossRef  Google Scholar 

  50. Kuang, S., Gillespie, M.A., Rudnicki, M.A.: Niche regulation of muscle satellite cell self-renewal and differentiation. Cell Stem Cell 2, 22–31 (2008). https://doi.org/10.1016/j.stem.2007.12.012

    CrossRef  Google Scholar 

  51. Murphy, M.M., Lawson, J.A., Mathew, S.J., Hutcheson, D.A., Kardon, G.: Satellite cells, connective tissue fibroblasts and their interactions are crucial for muscle regeneration. Development 138, 3625–3637 (2011). https://doi.org/10.1242/dev.064162

    CrossRef  Google Scholar 

  52. Delaney, K., Kasprzycka, P., Ciemerych, M.A., Zimowska, M.: The role of TGF-β1 during skeletal muscle regeneration. Cell Biol. Int. 41, 706–715 (2017). https://doi.org/10.1002/cbin.10725

    CrossRef  Google Scholar 

  53. Tipping, P.G., Hancock, W.W.: Production of tumor necrosis factor and interleukin-1 by macrophages from human atheromatous plaques. Am. J. Pathol. 142, 1721–1728 (1993)

    Google Scholar 

  54. Vignola, A.M., Chanez, P., Chiappara, G., Merendino, A., Zinnanti, E., Bousquet, J., Bellia, V., Bonsignore, G.: Release of transforming growth factor-beta (TGF-β) and fibronectin by alveolar macrophages in airway diseases. Clin. Exp. Immunol. 106, 114–119 (1996). https://doi.org/10.1046/j.1365-2249.1996.d01-811.x

    CrossRef  Google Scholar 

  55. McCarthy, J.J., Mula, J., Miyazaki, M., Erfani, R., Garrison, K., Farooqui, A.B., Srikuea, R., Lawson, B.A., Grimes, B., Keller, C., Van Zant, G., Campbell, K.S., Esser, K.A., Dupont-Versteegden, E.E., Peterson, C.A.: Effective fiber hypertrophy in satellite cell-depleted skeletal muscle. Development 138, 3657–3666 (2011). https://doi.org/10.1242/dev.068858

    CrossRef  Google Scholar 

  56. Dayanidhi, S., Lieber, R.L.: Skeletal muscle satellite cells: mediators of muscle growth during development and implications for developmental disorders. Muscle Nerve 48, 153–154 (2013). https://doi.org/10.1002/mus.23878

    CrossRef  Google Scholar 

  57. Mockford, M., Caulton, J.M.: The pathophysiological basis of weakness in children with cerebral palsy. Pediatr. Phys. Ther. 22, 222–233 (2010). https://doi.org/10.1097/pep.0b013e3181dbaf96

    CrossRef  Google Scholar 

  58. Cholok, D., Lee, E., Lisiecki, J., Agarwal, S., Loder, S., Ranganathan, K., Qureshi, A.T., Davis, T.A., Levi, B.: Traumatic muscle fibrosis: from pathway to prevention. J. Trauma Acute Care Surg. 82, 174–184 (2017). https://doi.org/10.1097/TA.0000000000001290

    CrossRef  Google Scholar 

  59. Novak, M.L., Koh, T.J.: Phenotypic transitions of macrophages orchestrate tissue repair. Am. J. Pathol. 183, 1352–1363 (2013). https://doi.org/10.1016/j.ajpath.2013.06.034

    CrossRef  Google Scholar 

  60. Wynn, T.A., Vannella, K.M.: Macrophages in tissue repair, regeneration, and fibrosis. Immunity 44, 450–462 (2016). https://doi.org/10.1016/j.immuni.2016.02.015

    CrossRef  Google Scholar 

  61. Kirk, S., Oldham, J., Kambadur, R., Sharma, M., Dobbie, P., Bass, J.: Myostatin regulation during skeletal muscle regeneration. J. Cell. Physiol. 184, 356–363 (2000). https://doi.org/10.1002/1097-4652(200009)184:3%3c356:AID-JCP10%3e3.0.CO;2-R

    CrossRef  Google Scholar 

  62. Goetsch, S.C., Hawke, T.J., Gallardo, T.D., Richardson, J.A., Garry, D.J.: Transcriptional profiling and regulation of the extracellular matrix during muscle regeneration. Physiol. Genomics 14, 261–271 (2015). https://doi.org/10.1152/physiolgenomics.00056.2003

    CrossRef  Google Scholar 

  63. Blemker, S.S., Pinsky, P.M., Delp, S.L.: A 3D model of muscle reveals the causes of nonuniform strains in the biceps brachii. J. Biomech. 38, 657–665 (2005). https://doi.org/10.1016/j.jbiomech.2004.04.009

    CrossRef  Google Scholar 

  64. Sharafi, B., Blemker, S.S.: A mathematical model of force transmission from intrafascicularly terminating muscle fibers. J. Biomech. 44, 2031–2039 (2011). https://doi.org/10.1016/j.jbiomech.2011.04.038

    CrossRef  Google Scholar 

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Authors and Affiliations

  1. Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand

    Stephanie Khuu, Justin W. Fernandez & Geoffrey G. Handsfield

  2. Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA

    Kelley M. Virgilio

  3. Department of Engineering Science, University of Auckland, Auckland, New Zealand

    Justin W. Fernandez

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  1. Stephanie Khuu
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  2. Kelley M. Virgilio
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  3. Justin W. Fernandez
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  4. Geoffrey G. Handsfield
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Correspondence to Geoffrey G. Handsfield .

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Editors and Affiliations

  1. Andrew Walz Professor of Mechanical Engineering and Professor of Biomedical Engineering, Columbia University, New York, NY, USA

    Prof. Dr. Gerard A. Ateshian

  2. Department of Mechanical Engineering, Columbia University, New York, NY, USA

    Ph.D. Kristin M. Myers

  3. Department of Mechanical Engineering, University of Porto, Porto, Portugal

    Dr. João Manuel R. S. Tavares

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Khuu, S., Virgilio, K.M., Fernandez, J.W., Handsfield, G.G. (2020). Mechano-Physiological Modeling to Probe the Role of Satellite Cells and Fibroblasts in Cerebral Palsy Muscle Degeneration. In: Ateshian, G., Myers, K., Tavares, J. (eds) Computer Methods, Imaging and Visualization in Biomechanics and Biomedical Engineering. CMBBE 2019. Lecture Notes in Computational Vision and Biomechanics, vol 36. Springer, Cham. https://doi.org/10.1007/978-3-030-43195-2_11

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