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Calculating the Consequences of Left-Shifted Nav Channel Activity in Sick Excitable Cells

  • Bela Joos
  • Benjamin M. Barlow
  • Catherine E. Morris
Chapter
Part of the Handbook of Experimental Pharmacology book series (HEP, volume 246)

Abstract

Two features common to diverse sick excitable cells are “leaky” Nav channels and bleb damage-damaged membranes. The bleb damage, we have argued, causes a channel kinetics based “leakiness.” Recombinant (node of Ranvier type) Nav1.6 channels voltage-clamped in mechanically-blebbed cell-attached patches undergo a damage intensity dependent kinetic change. Specifically, they experience a coupled hyperpolarizing (left) shift of the activation and inactivation processes. The biophysical observations on Nav1.6 currents formed the basis of Nav-Coupled Left Shift (Nav-CLS) theory. Node of Ranvier excitability can be modeled with Nav-CLS imposed at varying LS intensities and with varying fractions of total nodal membrane affected. Mild damage from which sick excitable cells might recover is of most interest pathologically. Accordingly, Na+/K+ ATPase (pump) activity was included in the modeling. As we described more fully in our other recent reviews, Nav-CLS in nodes with pumps proves sufficient to predict many of the pathological excitability phenomena reported for sick excitable cells. This review explains how the model came about and outlines how we have used it. Briefly, we direct the reader to studies in which Nav-CLS is being implemented in larger scale models of damaged excitable tissue. For those who might find it useful for teaching or research purposes, we coded the Nav-CLS/node of Ranvier model (with pumps) in NEURON. We include, here, the resulting “Regimes” plot of classes of excitability dysfunction.

Keywords

Bleb Ectopic Excitability Hyperpolarizing shift Leaky sodium channels Left shift Membrane damage Mild injury Modeling 

References

  1. Banderali U, Juranka PF, Clark RB, Giles WR, Morris CE (2010) Impaired stretch modulation in potentially lethal cardiac sodium channel mutants. Channels 4:12–21CrossRefGoogle Scholar
  2. Barreto E, Cressman JR (2011) Ion concentration dynamics as a mechanism for neuronal bursting. J Biol Phys 37:361–373CrossRefGoogle Scholar
  3. Boucher PA, Joós B, Morris CE (2012) Coupled left-shift of Nav channels: modeling the Na+-loading and dysfunctional excitability of damaged axons. J Comput Neurosci 33:301–319CrossRefGoogle Scholar
  4. Choi JS, Waxman SG (2011) Physiological interactions between Na(v)1.7 and Na(v)1.8 sodium channels: a computer simulation study. J Neurophysiol 106(6):3173–3184CrossRefGoogle Scholar
  5. Coggan JS, Prescott SA, Bartol TM, Sejnowski TJ (2010) Imbalance of ionic conductances contributes to diverse symptoms of demyelination. Proc Natl Acad Sci U S A 107:20602–20609CrossRefGoogle Scholar
  6. Coggan JS, Ocker G, Sejnowski TJ, Prescott SA (2011) Explaining pathological changes in axonal excitability through dynamical analysis of conductance-based models. J Neural Eng 8:065002CrossRefGoogle Scholar
  7. Cressman JR Jr, Ullah G, Ziburkus J, Schiff SJ, Barreto E (2009) The influence of sodium and potassium dynamics on excitability, seizures, and the stability of persistent states: I. Single neuron dynamics. J Comput Neurosci 26:159–170. Erratum in (2011) 30: 781CrossRefGoogle Scholar
  8. Duménieu M, Oulé M, Kreutz MR, Lopez-Rojas J (2017) The segregated expression of voltage-gated potassium and sodium channels in neuronal membranes: functional implications and regulatory mechanisms. Front Cell Neurosci 11:115CrossRefGoogle Scholar
  9. Finol-Urdaneta RK, McArthur JR, Juranka PF, French RJ, Morris CE (2010) Modulation of KvAP unitary conductance and gating by 1-alkanols and other surface active agents. Biophys J 98:762–772CrossRefGoogle Scholar
  10. Hodgkin AL, Huxley AF (1952) A quantitative description of membrane current and its application to conduction and excitation in nerve. J Physiol 117:500–544CrossRefGoogle Scholar
  11. Hübel N, Dahlem MA (2014) Dynamics from seconds to hours in hodgkin-huxley model with time-dependent ion concentrations and buffer reservoirs. PLoS Comput Biol 10(12):e1003941CrossRefGoogle Scholar
  12. Hübel N, Ullah G (2016) Anions govern cell volume: a case study of relative astrocytic and neuronal swelling in spreading depolarization. PLoS One 11(3):e0147060CrossRefGoogle Scholar
  13. Jérusalem A, García-Grajales JA, Merchán-Pérez A, Peña JM (2013) A computational model coupling mechanics and electrophysiology in spinal cord injury. Biomech Model Mechanobiol 14:1–14Google Scholar
  14. Käger H, Wadman W, Somjen G (2000) Simulated seizures and spreading depression in a neuron model incorporating interstitial space and ion concentrations. J Neurophysiol 84:495–512CrossRefGoogle Scholar
  15. Kovalsky Y, Amir R, Devor M (2009) Simulation in sensory neurons reveals a key role for delayed Na+ current in subthreshold oscillations and ectopic discharge: implications for neuropathic pain. J Neurophysiol 102:1430–1442.CrossRefGoogle Scholar
  16. Lachance M, Longtin A, Morris CE, Yu N, Joós B (2014) Stimulation-induced ectopicity and propagation windows in model damaged axons. J Comput Neurosci 37:523–531CrossRefGoogle Scholar
  17. Läuger P (1991) Electrogenic ion pumps, distinguished lecture series of the society of general physiologists. Sinauer Associates, Sunderland, MA, p 313Google Scholar
  18. Ma QX, Arneodo A, Ding GH, Argoul F (2017) Dynamical study of Nav channel excitability under mechanical stress. Biol Cybern 111(2):129–148CrossRefGoogle Scholar
  19. Morris CE, Joós B (2016) Channels in damaged membranes. In: French RJ, Noskov SY (eds) Na channels from phyla to function. Currents topics in membranes, vol 18. Elsevier, Amsterdam, pp 561–597CrossRefGoogle Scholar
  20. Morris CE, Juranka PF (2007) Nav channel mechanosensitivity: activation and inactivation accelerate reversibly with stretch. Biophys J 93:822–833CrossRefGoogle Scholar
  21. Morris CE, Boucher PA, Joós B (2012a) Left-shifted Nav channels in injured bilayer: primary targets for neuroprotective Nav antagonists? Front Pharmacol 3:19CrossRefGoogle Scholar
  22. Morris CE, Juranka PF, Joós B (2012b) Perturbed voltage-gated channel activity in perturbed bilayers: implications for ectopic arrhythmias arising from damaged membrane. Prog Biophys Mol Biol 110:245–256CrossRefGoogle Scholar
  23. Ng LJ, Volman V, Gibbons MM, Phohomsiri P, Cui J, Swenson DJ, Stuhmiller JH (2017) A mechanistic end-to-end concussion model that translates head kinematics to neurologic injury. Front Neurol 8:269CrossRefGoogle Scholar
  24. Ochab-Marcinek A, Schmid G, Goychuk I, Hänggi P (2009) Noise-assisted spike propagation in myelinated neurons. Phys Rev. E 79(1):011904CrossRefGoogle Scholar
  25. Prescott SA, Sejnowski TJ, De Koninck Y (2006) Reduction of anion reversal potential subverts the inhibitory control of firing rate in spinal lamina I neurons: towards a biophysical basis for neuropathic pain. Mol Pain 2:32–51CrossRefGoogle Scholar
  26. Rotstein HG, Oppermann T, White JA, Kopell N (2006) The dynamic structure underlying subthreshold oscillatory activity and the onset of spikes in a model of medial entorhinal cortex stellate cells. J Comput Neurosci 21:271–292CrossRefGoogle Scholar
  27. Shcherbatko A, Ono F, Mandel G, Brehm P (1999) Voltage-dependent sodium channel function is regulated through membrane mechanics. Biophys J 77:1945–1959CrossRefGoogle Scholar
  28. Sheetz MP, Sable JE, Döbereiner HG (2006) Continuous membrane cytoskeleton adhesion requires continuous accommodation to lipid and cytoskeleton dynamics. Annu Rev. Biophys Biomol Struct 35:417–434CrossRefGoogle Scholar
  29. Sterratt D, Graham B, Gillies A, Willshaw D (2011) Principles of computational modelling in neuroscience. Cambridge Univ Press, CambridgeCrossRefGoogle Scholar
  30. Tabarean IV, Juranka P, Morris CE (1999) Membrane stretch affects gating modes of a skeletal muscle sodium channel. Biophys J 77:758–774CrossRefGoogle Scholar
  31. Volman V, Ng LJ (2013) Computer modeling of mild axonal injury: implications for axonal signal transmission. Neural Comput 25:2646–2681CrossRefGoogle Scholar
  32. Volman V, Ng LJ (2014) Primary paranode demyelination modulates slowly developing axonal depolarization in a model of axonal injury. J Comput Neurosci 37:439–457CrossRefGoogle Scholar
  33. Volman V, Ng LJ (2016) Perinodal glial swelling mitigates axonal degradation in a model of axonal injury. J Neurophysiol 115:1003–1017CrossRefGoogle Scholar
  34. Wang JA, Lin W, Morris T, Banderali U, Juranka PF, Morris CE (2009) Membrane trauma and Na + leak from Nav1.6 channels. Am J Physiol Cell Physiol 297:C823–C834CrossRefGoogle Scholar
  35. Yu N, Morris CE, Joós B, Longtin A (2012) Spontaneous excitation patterns computed for axons with injury-like impairments of sodium channels and Na/K pumps. PLoS Comput Biol 8:e1002664CrossRefGoogle Scholar
  36. Zou S, Chisholm R, Tauskela JS, Mealing GA, Johnston LJ, Morris CE (2013) Force spectroscopy measurements show that cortical neurons exposed to excitotoxic agonists stiffen before showing evidence of bleb damage. PLoS One 8:e73499CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Bela Joos
    • 1
  • Benjamin M. Barlow
    • 1
  • Catherine E. Morris
    • 2
  1. 1.Department of PhysicsUniversity of OttawaOttawaCanada
  2. 2.NeurosciencesOttawa Hospital Research InstituteOttawaCanada

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