Cell Motility: Dynamic Networks And Flexible Membranes

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Cell Motility: Dynamic Networks And Flexible Membranes

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1. Cell Motility: Dynamic Networks And Flexible Membranes How to describe this complex systeHow to describe this complex syste

2. Cells move First thing to note: Cells are motile objects. Self propel – moving around on a surface, or through tissue. cell motion carries out important biological function fibroblasts cells make connective tissue Cells get Mechanical and biochemical cues for their motion: Here focus on dynamic load bearing biopolymer network inside cell That is also thought to generate forces that allow a cell to move Note: transport of material on the insideFirst thing to note: Cells are motile objects. Self propel – moving around on a surface, or through tissue. cell motion carries out important biological function fibroblasts cells make connective tissue Cells get Mechanical and biochemical cues for their motion: Here focus on dynamic load bearing biopolymer network inside cell That is also thought to generate forces that allow a cell to move Note: transport of material on the inside

3. Motion guided by chemical or mechanical cues Let me give you an exampleLet me give you an example

4. Chemotaxis – from receptor activation to cell movement How does this work?How does this work?

5. Direct observation of the signaling molecules one can directly image the signaling pathway. but as you may imagine, the combination of motion and biochemical signals is hard to analyze (moving boundary problem...) so one ouw like to decouple biochemical response from the motion of the cell. Indeed one can directly image the signaling pathway. but as you may imagine, the combination of motion and biochemical signals is hard to analyze (moving boundary problem...) so one ouw like to decouple biochemical response from the motion of the cell. Indeed

7. several models have been developed in the past few years. one of the models developed by one of my students at NIH (Ron Skupsky) how do you distinguish such signaling pathways quite general problem in biophysics and cell biology first tell you a bit more about our modelseveral models have been developed in the past few years. one of the models developed by one of my students at NIH (Ron Skupsky) how do you distinguish such signaling pathways quite general problem in biophysics and cell biology first tell you a bit more about our model

8. Perturbing the chemical signal – Colin McCann

10. Cells Zigzag Cells zigzag in a gradient Preferred turning angle Preferred anglePreferred angle

11. Perturb the mechanical “system” Cell size, membrane, load bearing scaffolding. Scaffolding: biopolymer filaments: Cell size, membrane, load bearing scaffolding. Scaffolding: biopolymer filaments:

13. Applying forces comparable to a moving cell

14. Deforming membranes with multipoint Laser Tweezers

15. Vesicle Contour extraction and Fourier Analysis

18. Other shapes

19. Actin filaments dynamic Actin filaments: double stranded chain (persistence length o(mm) )

20. Local mechanical probe of network: microspheres Particle tracking with ~10nm accuracy In water: beads of this size diffuse around randomly due to brownian motionIn water: beads of this size diffuse around randomly due to brownian motion

21. Deforming the actin network

25. Next step: crosslinked network Scaffolding not just filaments, filaments are connected in a controlled way through actin binding proteins (a whole zoo of them). Here I show three important ones: Again network dynamically changing – since actin associated proteins come on and off with characteristic timescales.Scaffolding not just filaments, filaments are connected in a controlled way through actin binding proteins (a whole zoo of them). Here I show three important ones: Again network dynamically changing – since actin associated proteins come on and off with characteristic timescales.

26. Actin network crosslinked with alpha-actinin

27. Next step 2: Two-point local forcing Use laser tweezer to force two beads simultaneously Measure response of surrounding beads Does superposition hold?

28. Two-Point Forcing (cont.)

29. Deformation of Vesicles by Polymerization of Actin on the Inside

30. Even Modes vs Odd Modes

31. Cell Motility: Dynamic Networks and Flexible Membranes How do components of the cell motility machinery respond to perturbations? Biochemical signal perturbations: Bias in the gradient sensing response. (Skupsky, McCann, Nossal, Losert) Mechanical perturbations of membrane: Arbitrary deformation of vesicles achieved w/ tweezer array Second Fourier Mode least stable Actin network deformations Direct visualization of deformation field achieved Above a threshold, deformations are irreversible Complex addition of forces Developed experimental tools Developed experimental tools

32. Acknowledgments Postdoc: Erin Rericha Grad Students: Andrew Pomerance, Cory Poole, Ron Skupsky, Colin McCann Undergraduates: Joe Meszaros, Kumar Senthil Collaborators: Jeff Urbach (Georgetown), Jack Douglas, Kris Helmerson, Jim Warren (NIST), Ralph Nossal, Carole Parent (NIH) Funding: NIH, NIST, NSF-MRSEC, NSF-MRI

34. Acknowledgements Funding: NSF, NASA, NIH, NIST www.ireap.umd.edu/losertlab

35. The cell scaffolding: dynamic, spatially heterogeneous ATP hydrolysis about 10^-18 J per molecule ~100kT Network is thought to exert forces on the leading edge of the cell. Not known exactly how this occurs physically, several competing models.ATP hydrolysis about 10^-18 J per molecule ~100kT Network is thought to exert forces on the leading edge of the cell. Not known exactly how this occurs physically, several competing models.

36. Next step: Biochemical gradients e.g. Gradient in actin severing proteins (Gelsolin)

38. upside: fast downside: in the "shop" this fallupside: fast downside: in the "shop" this fall

39. Deformations (cont.)

40. Large forces: Controlled fluid flow Ultrasound driven air bubbles (with Sascha Hilgenfeld, Northwestern Univ.) Generate streaming flow if air bubble close to ultrasound resonance

41. How are signals translated into actin polymerization and membrane deformation? What is the cause of the shape instability? Which biochemical signal leads, and which lags mechanical membrane deformations? -> need model of signaling pathway

43. Additional connection between mechanics and chemical signaling pathways several models have been developed in the past few years. one of the models developed by one of my students at NIH (Ron Skupsky) how do you distinguish such signaling pathways quite general problem in biophysics and cell biology first tell you a bit more about our modelseveral models have been developed in the past few years. one of the models developed by one of my students at NIH (Ron Skupsky) how do you distinguish such signaling pathways quite general problem in biophysics and cell biology first tell you a bit more about our model

44. 15 seconds between frames15 seconds between frames

45. More of these + a streaming cell trackMore of these + a streaming cell track

46. Onset of cell motion

48. Embedded particles drift at ~0.1 mm/s in actin network gradient (omit:Speeds comparable to the speed of some motile cells) Energy comes from either ATP hydrolysis during actin polymerization or energy flux due to the thermal gradient(omit:Speeds comparable to the speed of some motile cells) Energy comes from either ATP hydrolysis during actin polymerization or energy flux due to the thermal gradient

49. Dynamic response of signaling pathways Complicated system – signal pathwaysComplicated system – signal pathways

50. Calculate viscous and elastic properties of actin networks from particle tracks (microrheology) Note: Water 1 cPoise = 1 mPa sec -> exactly as predicted by green curve on left. Note: Water 1 cPoise = 1 mPa sec -> exactly as predicted by green curve on left.

51. Models generally agree with steady state experiment Label graphLabel graph

52. Characterize motion: Diffusive exponent g Brownian motion: g=1 In actin gel: g< 1 use g as measure of polymerization Particle motion in a polymer network Free diffusion In gel: Not simply slower diffusion, but harder and harder to move larger distances. Use as measure of the polymerizationFree diffusion In gel: Not simply slower diffusion, but harder and harder to move larger distances. Use as measure of the polymerization

53. Mechanical properties of actin networks close to the polymerization transition At energies of several kT the actin network actually can be broken. So when we move a 2 micron sphere Through the actin network by moving a laser tweezer along the path indicated here. The bead actually Follows the tweezer and breaks through the network, but eventually actin filaments appear to build up ahead of the bead and the Bead falls out of the trap and recoils due to the elastic part of the response of the actin network. At energies of several kT the actin network actually can be broken. So when we move a 2 micron sphere Through the actin network by moving a laser tweezer along the path indicated here. The bead actually Follows the tweezer and breaks through the network, but eventually actin filaments appear to build up ahead of the bead and the Bead falls out of the trap and recoils due to the elastic part of the response of the actin network.

54. Local characterization of the polymerization transition of actin Increase temperature: entropic transition These are one of the first microrheology measurements on a dynamic actin network Though several groups are also starting to look at dynamic networks now. In addition, we also started to look at the role of gradients, there are no data on gradients of actin to our knowledge. Gradient from polymerized to non-polymerized: temperature gradient. Increase temperature: entropic transition These are one of the first microrheology measurements on a dynamic actin network Though several groups are also starting to look at dynamic networks now. In addition, we also started to look at the role of gradients, there are no data on gradients of actin to our knowledge. Gradient from polymerized to non-polymerized: temperature gradient.

55. Spatial polymerization gradients First step toward generating gradients in the actin network that mimik the gradients present at the leading edge of cells.First step toward generating gradients in the actin network that mimik the gradients present at the leading edge of cells.

56. t=An

57. Note: Network is dynamic – though it looks frozen here About one micron total length – though length not given in paper Want to measure local mechanical properties of such heterogeneous network. Cannot visualize dynamics of network directly -> filaments too close together. Instead track the motion of tracer particles that are pushed and pulled by network. Now it is time to go to model systems: what are the key features that allow front to generate forces and That transport material to the leading edge? actin network that is dynamic – i.e constantly growing and rearranging, and contains gradients. Note: Network is dynamic – though it looks frozen here About one micron total length – though length not given in paper Want to measure local mechanical properties of such heterogeneous network. Cannot visualize dynamics of network directly -> filaments too close together. Instead track the motion of tracer particles that are pushed and pulled by network. Now it is time to go to model systems: what are the key features that allow front to generate forces and That transport material to the leading edge? actin network that is dynamic – i.e constantly growing and rearranging, and contains gradients.

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