1. Structural description of the biological membrane. Physical property of biological membrane

2. Transfer of water soluble molecules across cell membranes by transport proteins

3. Two classes of membran proteins

5. Comparison of passive and active transport

6. Examples of sbubstances transported across cell membranes by carrier proteins

7. Bacteriorhodopsin: A carrier protein

8. Conformational change in protein to passively carry glucose

9. Two components of an electrochemical gradient

10. Three ways of driving active transport

11. Three types of transport by carrier proteins

12. Two types of glucose carriers for transfer of glucose across the gut lining

13. The Na-K pump

14. cycle

15. Osmosis

16. Avoiding osmotic swelling

17. Carrier mediated solute transport in animal and plant cells

18. The structure of an ion channel

19. Patch-clamp recording

20. Current through a single ion channel

21. Gated ion channels

22. Stress activated ion channels allow us to hear

23. Distribution of ions gives rise to membrane potential

24. K + is responsible for generating a membrane potential Nernst equation: V = 62log 10 (C o /C i )

25. Neurons

26. Action Potenetial

27. Three conformations of the voltage gated Na channel ----- +++++

28. Ion Flows and the Action Potential

29. The propogation of an action potential along an axon

30. The Action Potential

31. Synapses

34. Excitatory vs. Inhibitory Synapse

35. Synapses

36. Ion Channels

37. Lecture 2 Membrane potentials Ion channels Hodgkin-Huxley model

38. Cell membranes

39. Lipid bilayer, 3-4 nm thick  capacitance c = C/A ~ 10 nF/mm 2

40. Cell membranes Lipid bilayer, 3-4 nm thick  capacitance c = C/A ~ 10 nF/mm 2 Ion channels  conductance

41. Cell membranes Lipid bilayer, 3-4 nm thick  capacitance c = C/A ~ 10 nF/mm 2 Ion channels  conductance Typical A =.01 -.1 mm 2  C ~.1 – 1 nF

42. Cell membranes Lipid bilayer, 3-4 nm thick  capacitance c = C/A ~ 10 nF/mm 2 Ion channels  conductance Typical A =.01 -.1 mm 2  C ~.1 – 1 nF Q=CV, Q= 10 9 ions  |V| ~ 65 mV

43. Membrane potential Fixed potential  concentration gradient

44. Membrane potential Fixed potential  concentration gradient Concentration difference  Potential difference Concentration difference maintained by ion pumps, which are transmembrane proteins

45. Nernst potential Concentration ratio for a specific ion (inside/outside):  = 1/k B T  ( q = proton charge, z = ionic charge in units of q )

46. Nernst potential Concentration ratio for a specific ion (inside/outside):  = 1/k B T  ( q = proton charge, z = ionic charge in units of q ) No flow at this potential difference Called Nernst potential or reversal potential for that ion

47. Reversal potentials Note: V T = k B T/q = (for chemists) RT/F ~ 25 mv Some reversal potentials: K: -70 - -90 mV Na: +50 mV Cl: -60 - -65 mV Ca: 150 mV Rest potential: ~ -65 mV ~2.5 V T

48. Effective circuit model for cell membrane

49. ( C, g i, I ext all per unit area) (“point model”: ignores spatial structure)

50. Effective circuit model for cell membrane ( C, g i, I ext all per unit area) (“point model”: ignores spatial structure) g i can depend on V, Ca concentration, synaptic transmitter binding, …

51. Ohmic model One g i = g = const or

52. Ohmic model One g i = g = const or membrane time const

53. Ohmic model One g i = g = const or Start at rest: V= V 0 at t=0 membrane time const

54. Ohmic model One g i = g = const or Final state: Start at rest: V= V 0 at t=0 membrane time const

55. Ohmic model One g i = g = const or Final state: Start at rest: V= V 0 at t=0 Solution: membrane time const

56. channels are stochastic

57. Many channels: effective g = g open * (prob to be open) * N

58. Voltage-dependent channels

59. K channel Open probability: 4 independent, equivalent, conformational changes

60. K channel Open probability: 4 independent, equivalent, conformational changes Kinetic equation:

61. K channel Open probability: 4 independent, equivalent, conformational changes Kinetic equation: Rearrange:

62. K channel Open probability: 4 independent, equivalent, conformational changes Kinetic equation: Rearrange: relaxation time: asymptotic value

63. Thermal rates: u 1, u 2 : barriers

64. Thermal rates: u 1, u 2 : barriers Assume linear in V :

65. Thermal rates: u 1, u 2 : barriers Assume linear in V : 

66. Thermal rates: u 1, u 2 : barriers Assume linear in V :  Simple model: a n =b n, c 1 =c 2

67. Thermal rates: u 1, u 2 : barriers Assume linear in V :  Simple model: a n =b n, c 1 =c 2 Similarly,

68. Hodgkin-Huxley K channel

69. (solid: exponential model for both  and  Dashed: HH fit)

70. Transient conductance: HH Na channel 4 independent conformational changes, 3 alike, 1 different (see picture)

71. Transient conductance: HH Na channel 4 independent conformational changes, 3 alike, 1 different (see picture) HH fits:

72. Transient conductance: HH Na channel 4 independent conformational changes, 3 alike, 1 different (see picture) HH fits:

73. Transient conductance: HH Na channel 4 independent conformational changes, 3 alike, 1 different (see picture) HH fits: m is fast (~.5 ms) h,n are slow (~5 ms)

74. Hodgkin-Huxley model

75. Parameters: g L = 0.003 mS/mm 2 g K = 0.36 mS/mm 2 g Na = 1.2 ms/mm 2 V L = -54.387 mV V K = -77 V Na = 50 mV

76. Spike generation Current flows in, raises V  m increases (h slower to react)  g Na increases  more Na current flows in  …  V rises rapidly toward V Na Then h starts to decrease  g Na shrinks  V falls, aided by n opening for K current Overshoot, recovery

77. Spike generation Current flows in, raises V  m increases (h slower to react)  g Na increases  more Na current flows in  …  V rises rapidly toward V Na Then h starts to decrease  g Na shrinks  V falls, aided by n opening for K current Overshoot, recovery Threshold effect

78. Spike generation (2)

79. Regular firing, rate vs I ext

80. Step increase in current

81. Noisy input current, refractoriness