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Furthering our understanding of microtubule dynamic instability by CryoEM Gabriel Lander Postdoc, Eva Nogales Lab UC Berkeley/Lawrence Berkeley National Lab Greg Alushin The Microtubule Microtubules are among most important components of


  1. Furthering our understanding of microtubule dynamic instability by CryoEM Gabriel Lander Postdoc, Eva Nogales Lab UC Berkeley/Lawrence Berkeley National Lab

  2. Greg Alushin

  3. The Microtubule • Microtubules are among most important components of the cytoskeleton • Fundamental part of many physiological processes: • intracellular transport • cell motility • cell polarization • cell division

  4. The Tubulin Dimer - The Microtubule Building Block Beta Subunit Alpha Subunit

  5. Tubulin dimers assemble longitudinally Protofilament

  6. Microtubule

  7. Microtubule Seam Breaks Helical Symmetry Microtubules are not static structures - their ability to assemble & depolymerize is essential to cellular function.

  8. The Nucleotide Binding Pocket GTP Exchangeable site Beta Subunit (E-site) (GDP) Free tubulin can exchange GDP for GTP Non-exchangeable site (N-site) Alpha Subunit (GTP)

  9. The Nucleotide Binding Pocket GTP is required at Beta Subunit beta subunit for MT (GTP) polymerization, creating strong inter- tubulin contacts Alpha Subunit (GTP)

  10. The Nucleotide Binding Pocket Beta Subunit GTP hydrolysis to (GDP) GDP weakens the inter-tubulin contacts Alpha Subunit (GTP)

  11. Microtubule Dynamic Instability GTP “Cap” {

  12. Microtubule Dynamic Instability

  13. Microtubule Dynamic Instability Mechanism relating GTP hydrolysis to dynamic instability still unknown

  14. Atomic-Resolution Structures X-ray Electron Crystallography Crystallography X-ray X-ray (1FFX,1SA0,1Z2B, (1TUB,1JFF,1TVK) Crystallography Crystallography 3DU7,3HKB,3N2G,3RYC, Zinc-induced antiparallel (4DRX,4F6R) (4FFB) 4F61,4UT5) tubulin sheets + DARPin-bound dimer TOG-bound dimer Polymers bound to stabilizing ligand stathmin-like domains

  15. CryoEM of Microtubules

  16. Subnanometer-Resolution CryoEM Structures Kikkawa and Hirokawa Sindelar and Downing Li et al . Structure 2002 (9Å resolution) EMBO J 2006 (9.5Å resolution) PNAS 2010 (8.5Å resolution) Are microtubules only ordered to 8Å resolution? Fourniol et al. JCB 2010 Alushin et al . Nature 2010 Maurer et al . Cell 2012 Yajima et al . JCB 2012 (8Å resolution) (8.6Å resolution) (8Å resolution) (9Å resolution)

  17. FEI Titan EM (aka “The Beast”) • C3 active, parallel illumination • 300keV • 2K CCD, no DD = film collection • No Leginon = Tecnai Low Dose • Side-entry holder • “Weird State” feature!

  18. Microtubule Distortions Bending Flattening

  19. Distinguishing Alpha from Beta In an EM micrograph, alpha tubulin is indistinguishable from beta tubulin

  20. Human Kinesin Monomer Rice et al. Nature, Dec 1999 Mutation in switch II region inhibits ATP hydrolysis, stably binds to microtubules (plasmid from Vale lab, UCSF)

  21. Heterogeneous Protofilament Symmetries & Seam 12pf 13pf 14pf 15pf

  22. 72000X (0.87Å/pixel) 25e - /Å 2 8Å

  23. Ice ring at ~3.6Å

  24. Remove images with drift/ beam induced motion

  25. Pick MT Filaments Box out at every 80Å 768x768 pixels, binned by 2 for processing

  26. 2D classification (IMAGIC MSA/MRA) 5Å 10Å 20Å 40Å 80Å Layer lines visible out to ~5Å resolution 5Å 10Å 20Å 40Å 80Å

  27. 2D classification (IMAGIC MSA/MRA) 5Å 10Å 20Å 40Å 80Å Remove low resolution particles

  28. 2D classification (IMAGIC MSA/MRA) 5Å 10Å 20Å 40Å 80Å Remove particles missing kinesin, also 12pf & 15pf

  29. Refinement Scheme (EMAN2/SPARX Libs) Masked particle segments with mixed protofilament numbers (13 & 14pfs)

  30. Refinement Scheme (EMAN2/SPARX Libs) Masked particle segments with mixed protofilament numbers (13 & 14pfs) 13 & 14pf initial models

  31. Refinement Scheme (EMAN2/SPARX Libs) Masked particle segments with mixed protofilament numbers (13 & 14pfs) Particles are sorted by multi- model projection matching using 13pf and 14pf models Asymmetric back projection of each pf symmetry

  32. Low-resolution asymmetric densities Determine helical symmetry of each pf number using only monomer density (Egelman’s hsearch_lorentz)

  33. Applying Pseudo-Symmetry 13 protofilament 14 protofilament turn = -27.67º turn = -25.75º rise = 9.51Å rise = 8.89Å

  34. Applying Pseudo-Symmetry Average symmetry mates in Fourier space during back projection

  35. Applying Pseudo-Symmetry (14pf example) 1x For each protofilament density, use the helical parameters to symmetrize the density with pf-1 symmetry mates

  36. Applying Pseudo-Symmetry (14pf example) 2x For each protofilament density, use the helical parameters to symmetrize the density with pf-1 symmetry mates

  37. Applying Pseudo-Symmetry (14pf example) 3x For each protofilament density, use the helical parameters to symmetrize the density with pf-1 symmetry mates

  38. Applying Pseudo-Symmetry (14pf example) 13x For each protofilament density, use the helical parameters to symmetrize the density with pf-1 symmetry mates

  39. Applying Pseudo-Symmetry Extract protofilament containing symmetrized tubulin dimers

  40. Generating Seamed Density 14 protofilament turn = -25.75º rise = 8.89Å Regenerate 13 or 14-fold microtubule with seam

  41. Pseudo-Helical Microtubule Reconstruction Particle segments with mixed protofilament #’s Projection matching & back projection using multiple pf models For each, find helical parameters iterate (Ed Egelman’s hsearch_lorentz) iterate Over symmetrize using helical parameters (real space) Extract the “good” protofilaments & create new models using helical params Final refinement in FREALIGN with same averaging & pf extraction

  42. Assessing alignment with the seam X X X X X X

  43. Removing “bad” microtubules

  44. FREALIGN refinement

  45. FREALIGN refinement

  46. GMPCPP MTs + Kinesin 1.4-3.5um underfocus 25e - /Å 2 (1sec exposure) 311 Films acquired 252 used for processing 92,581 segments (40:60 ratio 13:14pfs)

  47. Microtubule at 4.7Å Resolution (FSC=0.143)

  48. Microtubule at 4.7Å Resolution (FSC=0.143)

  49. Acknowledgements Atomic modeling Greg Alushin (UCB) Paul Adams & Jeff Head (LBNL) \ Eva Nogales (UCB/LBNL)

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