Cellular and Molecular Bioengineering

, Volume 8, Issue 2, pp 237–246 | Cite as

Increased Cell Membrane Capacitance is the Dominant Mechanism of Stretch-Dependent Conduction Slowing in the Rabbit Heart: A Computational Study

  • Bernardo L. de Oliveira
  • Emily R. Pfeiffer
  • Joakim SundnesEmail author
  • Samuel T. Wall
  • Andrew D. McCulloch


Volume loading of the cardiac ventricles is known to slow electrical conduction in the rabbit heart, but the mechanisms remain unclear. Previous experimental and modeling studies have investigated some of these mechanisms, including stretch-activated membrane currents, reduced gap junctional conductance, and altered cell membrane capacitance. In order to quantify the relative contributions of these mechanisms, we combined a monomain model of rabbit ventricular electrophysiology with a hyperelastic model of passive ventricular mechanics. First, a simplified geometric model with prescribed homogeneous deformation was used to fit model parameters and characterize individual MEF mechanisms, and showed good qualitative agreement with experimentally measured strain-CV relations. A 3D model of the rabbit left and right ventricles was then compared with experimental measurements from optical electrical mapping studies in the isolated rabbit heart. The model was inflated to an end-diastolic pressure of 30 mmHg, resulting in epicardial strains comparable to those measured in the anterior left ventricular free wall. While the effects of stretch activated channels did alter epicardial conduction velocity (CV), an increase in cellular capacitance was required to explain previously reported experimental results. The new results suggest that for large strains, various mechanisms can combine and produce a biphasic relationship between strain and CV. However, at the moderate strains generated by high end-diastolic pressure, a stretch-induced increase in myocyte membrane capacitance is the dominant driver of conduction slowing during ventricular volume loading.


Mechano-electric feedback Stretch-activated currents Cell membrane Bidomain model Tissue conductivity Multiscale model Pressure loaded heart 



Supported by The Research Council of Norway through a grant from the eVITA program and a Centre of Excellence grant to the Center for Biomedical Computing at Simula Research Laboratory, and by NIH Grants 8 P41 GM1034268, P50 GM094503, 1 R01 HL105242, and 1 R01 HL96544.

Conflict of interest

Bernardo L. de Oliveira, Emily R. Pfeiffer, Joakim Sundnes, Samuel T. Wall, and Andrew D. McCulloch declare that they have no conflicts of interest.

Ethical standards

No human studies or animal studies were carried out by the authors for this article. Studies were conducted on murine myocytes, which were isolated and cultured according to institutional, national, and international guidelines, and approved by the UCSD Animal Subjects Committee.


  1. 1.
    Bayer, J., R. Blake, G. Plank, and N. Trayanova. A novel rule-based algorithm for assigning myocardial fiber orientation to computational heart models. Ann. Biomed. Eng., 40:2243–54, 2010.CrossRefGoogle Scholar
  2. 2.
    Bayly, P. V., B. H. KenKnight, J. M. Rogers, R. E. Hillsley, R. E. Ideker, and W. M. Smith. Estimation of conduction velocity vector fields from epicardial mapping data.IEEE Trans. Biomed. Eng., 45:563–571, 1998.CrossRefGoogle Scholar
  3. 3.
    Belus, A. and E. White. Streptomycin and intracellular calcium modulate the response of single guinea-pig ventricular myocytes to axial stretch. J. Physiol., 546:501–509, 2003.CrossRefGoogle Scholar
  4. 4.
    Camelliti, P., A. D. McCulloch, and P. Kohl. Microstructured cocultures of cardiac myocytes and fibroblasts: a two-dimensional in vitro model of cardiac tissue. Microsc. Microanal., 11(3):249–259, 2005.CrossRefGoogle Scholar
  5. 5.
    Camelliti, P., J. O. Gallagher, P. Kohl, and A. D. McCulloch. Micropatterned cell cultures on elastic membranes as an in vitro model of myocardium. Nat. Protoc., 1(3):1379–1391, 2006.CrossRefGoogle Scholar
  6. 6.
    Franz, M. R.. Mechano-electrical feedback in ventricular myocardium. Cardiovasc. Res., 32:15–24, 1996.CrossRefGoogle Scholar
  7. 7.
    Healy, S. N. and A. D. McCulloch. An ionic model of stretch-activated and stretch-modulated currents in rabbit ventricular myocytes. Europace, 7:S128–S134, 2005.CrossRefGoogle Scholar
  8. 8.
    Hu, H. and F. Sachs. Stretch-activated ion channels in the heart. J. Mol. Cell. Cardiol., 29:1511–1523, 1997.CrossRefGoogle Scholar
  9. 9.
    Kohl, P., P. J. Cooper, and H. Holloway. Effects of acute ventricular volume manipulation on in situ cardiomyocyte cell membrane configuration. Prog. Biophys. Mol. Biol., 82:221–227, 2003.CrossRefGoogle Scholar
  10. 10.
    Kuijpers, N., H. T. Eikelder, P. Bovendeerd, S. Verheule, and T. A. P. Hilbers. Mechano-electric feedback leads to conduction slowing and block in acutely dilated atria: a modeling study of cardiac electromechanics. Am. J. Physiol. Heart Circ. Physiol., 292(6):H2832–H2853, 2007.CrossRefGoogle Scholar
  11. 11.
    Lee, A. A., T. Delhaas, L. Waldman, D. A. MacKenna, F. J. Villarreal, and A. D. McCulloch. An equibiaxial strain system for cultured cells. Am. J. Physiol., 271(4):1400–1408, 1996.Google Scholar
  12. 12.
    Li, W., V. Gurev, A. D. McCulloch, and N. A. Trayanova. The role of mechanoelectric feedback in vulnerability to electric shock. Prog. Biophys. Mol. Biol., 97(2–3):461–78, 2008.CrossRefGoogle Scholar
  13. 13.
    Mahajan, A., Y. Shiferaw, D. Sato, A. Baher, R. Olcese, L.-H. Xie, M.-J. Yang, P.-S. Chen, J. G. Restrepo, A. Karma, A. Garfinkel, Z. Qu, and J. N. Weiss. A rabbit ventricular action potential model replicating cardiac dynamics at rapid heart rates. Biophys. J., 94:392–410, 2008.CrossRefGoogle Scholar
  14. 14.
    McNary, T. G., K. Sohn, B. Taccardi, and F. B. Sachse. Experimental and computational studies of strain-conduction velocity relationships in cardiac tissue. Prog. Biophys. Mol. Biol., 97:383–400, 2008.CrossRefGoogle Scholar
  15. 15.
    Mills, R. W., S. M. Narayan, and A. D. McCulloch. Mechanisms of conduction slowing during myocardial stretch by ventricular volume loading in the rabbit. Am. J. Physiol. Heart Circ. Physiol., 295:H1270–H1278, 2008.CrossRefGoogle Scholar
  16. 16.
    Niederer, S. A., E. Kerfoot, A. P. Benson, M. O. Bernabeu, O. Bernus, C. Bradley, E. M. Cherry, R. Clayton, F. H. Fenton, A. Garny, E. Heidenreich, S. Land, M. Maleckar, P. Pathmanathan, G. Plank, J. F. Rodrguez, I. Roy, F. B. Sachse, G. Seemann, O. Skavhaug, and N. P. Smith. Verification of cardiac tissue electrophysiology simulators using an n-version benchmark. Philos. Trans. R. Soc. A, 369:4331–4351, 2011.CrossRefGoogle Scholar
  17. 17.
    Niederer, S., L. Mitchell, N. Smith, and G. Plank. Simulating human cardiac electrophysiology on clinical time-scales. Fronti. Physiol., 2:14, 2011.Google Scholar
  18. 18.
    Pfeiffer, E. R., A. T. Wright, A. G. Edwards, J. C. Stowe, K. McNall, J. Tan, I. Niesman, H. H. Patel, D. M. Roth, J. H. Omens, and A. D. McCulloch. Caveolae in ventricular myocytes are required for stretch-dependent conduction slowing. J. Mol. Cell. Cardiol., 76:265–274, 2014.CrossRefGoogle Scholar
  19. 19.
    Reed, A., P. Kohl, and R. Peyronnet. Molecular candidates for cardiac stretch-activated ion channels. Global Cardiol. Sci. Pract., 2014(2):9–25, 2014.Google Scholar
  20. 20.
    Roth, B. J. Electrical conductivity values used with the bidomain model of cardiac tissue. IEEE Trans. Biomed. Eng., 44(4):326–328, 1997.CrossRefGoogle Scholar
  21. 21.
    Sachse, F., G. Seemann, and C. Riedel. Modeling of cardiac excitation propagation taking deformation into account. Proceedings of BIOMAG, pp. 839–841, 2002.Google Scholar
  22. 22.
    Sachse, F., B. Steadman, J. Bridge, B. Punske, and B. Taccardi. Conduction velocity in myocardium modulated by strain: measurement instrumentation and initial results. Conf. Proc. IEEE Eng. Med. Biol. Soc., 5:3593–3596, 2004.Google Scholar
  23. 23.
    Sinha, B., D. Kster, R. Ruez, P. Gonnord, M. Bastiani, D. Abankwa, R. V. Stan, G. Butler-Browne, B. Vedie, L. Johannes, N. Morone, R. G. Parton, G. Raposo, P. Sens, C. Lamaze, and P. Nassoy. Cells respond to mechanical stress by rapid disassembly of caveolae. Cell, 144(3):402–413, 2011.CrossRefGoogle Scholar
  24. 24.
    Sokabe, M., F. Sachs, and Z. Jing. Quantitative video microscopy of patch clamped membranes stress, strain, capacitance, and stretch channel activation. Biophys. J., 59:722–728, 1991.CrossRefGoogle Scholar
  25. 25.
    Spear, J. F. and E. N. Moore. Stretch-induced excitation and conduction disturbances in the isolated rat myocardium. J. Electrocardiol., 5 (1):15–24, 1972.CrossRefGoogle Scholar
  26. 26.
    Sreejit, P., S. Kumar, and R. S. Verma. An improved protocol for primary culture of cardiomyocyte from neonatal mice. In Vitro Cell. Dev. Biol. Anim., 44(3–4):45–50, 2008.CrossRefGoogle Scholar
  27. 27.
    Sundnes, J., G. T. Lines, and A. Tveito. An operator splitting method for solving the bidomain equations coupled to a volume conductor model for the torso. Math. Biosci., 194:233–248, 2005.CrossRefzbMATHMathSciNetGoogle Scholar
  28. 28.
    Sundnes, J., S. Wall, H. Osnes, T. Thorvaldsen, and A. McCulloch. Improved discretisation and linearisation of active tension in strongly coupled cardiac electro-mechanics simulations. Comput. Methods Biomech. Biomed. Eng., 17(6):604–615, 2014.CrossRefGoogle Scholar
  29. 29.
    Sung, D., R. Mills, J. Schettler, S. M. Narayan, J. H. Omens, and A. D. McCulloch. Ventricular filling slows epicardial conduction and increases action potential duration in an optical mapping study of the isolated rabbit heart. J. Cardiovasc. Electrophysiol., 14(7):739–749, 2003.CrossRefGoogle Scholar
  30. 30.
    Taggart, P. and P. M. Sutton. Cardiac mechano-electric feedback in man: clinical relevance. Prog. Biophys. Mol. Biol., 71:139–154, 1999.CrossRefGoogle Scholar
  31. 31.
    Tavi, P. and M. L. M. Weckstrom. Effect of gadolinium on stretch-induced changes in contraction and intracellularly recorded action- and after potentials of rat isolated atrium. Br. J. Pharmacol., 118:407–413, 1996.CrossRefGoogle Scholar
  32. 32.
    Usyk, T. P., I. J. LeGrice, and A. D. McCulloch. Computational model of three-dimensional cardiac electromechanics. Comput. Vis. Sci., 4:249–257, 2002.CrossRefzbMATHGoogle Scholar
  33. 33.
    Vetter, F. J. and A. D. McCulloch. Mechanoelectric feedback in a model of the passively inflated left ventricle. Ann. Biomed. Eng., 29:414–426, 1998.CrossRefGoogle Scholar
  34. 34.
    Wall, S. T., J. M. Guccione, M. B. Ratcliffe, and J. Sundnes. Electromechanical feedback with reduced cellular connectivity alters electrical activity in an infarct injured left ventricle: a finite element model study. AJP: Heart Circ. Physiol., 302(1):H206–H214, Dec. 2011.Google Scholar
  35. 35.
    Zhang, Y., R. B. Sekar, A. D. McCulloch, and L. Tung. Cell cultures as models of cardiac mechanoelectric feedback. Prog. Biophys. Mol. Biol., 97(2–3):367–382, 2008.CrossRefGoogle Scholar
  36. 36.
    Zhu, W. X., S. B. Johnson, R. Brandt, and J. B. D. L. Packer. Impact of volume loading and load reduction on ventricular refractoriness and conduction properties in canine congestive heart failure. J. Am. Coll. Cardiol., 30(3):825–833, 1997.CrossRefGoogle Scholar

Copyright information

© Biomedical Engineering Society 2015

Authors and Affiliations

  • Bernardo L. de Oliveira
    • 1
  • Emily R. Pfeiffer
    • 3
  • Joakim Sundnes
    • 1
    • 2
    Email author
  • Samuel T. Wall
    • 1
  • Andrew D. McCulloch
    • 3
  1. 1.Simula Research LaboratoryLysakerNorway
  2. 2.Department of InformaticsUniversity of OsloOsloNorway
  3. 3.Bioengineering DepartmentUniversity of CaliforniaSan DiegoUSA

Personalised recommendations