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Cryo-Electron Microscopy

James Conway University of Pittsburgh School of Medicine. Cryo-Electron Microscopy. 1. Making images image formation contrast function detectors – film & scanning, CCD, DED energy filters phase plates

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Cryo-Electron Microscopy

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  1. James Conway University of Pittsburgh School of Medicine Cryo-Electron Microscopy 1. Making imagesimage formationcontrast functiondetectors – film & scanning, CCD, DEDenergy filtersphase plates 2. Making density maps (AUTO3DEM)calculating 3D density maps from 2D projectionsestimating resolutionmodelling Penn State Med School – Friday, 4-Oct-2013

  2. • Images are 2D projections of the 3D structure • Simple approach is to back-project into a 3D volume • More computationally efficient is to perform the equivalent operation in Fourier (reciprocal) space • Easier to demonstrate back-projection using1D projections from a 2D object 1. How does 3D reconstruction work anyway? Penn State Med School – Friday, 4-Oct-2013

  3. Reconstructions - Central Section Theorem center of Fourier volume Fourier Transform (inverse) Projection onto 2D plane (microscopy) Fit through center of 3D volume Reconstruction pathways Fourier Transform Raw images center of Fourier plane Need many images at different orientations to fill Fourier volume or Real Space volume

  4. Back-Projection in 2D - 1. Projection images Object

  5. Back-Projection in 2D - 2. Projecting backwards Object

  6. Back-Projection in 2D - 3. Finer sampling Object 30° 10° 5° 1°

  7. Back-Projection in 2D - 4. Details 1° R-weighted Object 10° 1°

  8. Back-Projection in 2D - 5. Another Example Object 1° R-weighted

  9. Reconstructions - Central Section Theorem center of Fourier volume Fourier Transform (inverse) Projection onto 2D plane (microscopy) Fit through center of 3D volume Reconstruction pathways Fourier Transform Raw images center of Fourier plane Need many images at different orientations to fill Fourier volume or Real Space volume

  10. a. Particle Picking b. CTF estimation c. RMC – initial model search d. Auto3Dem e. Resolution f. Interpretation & modelling 2. Reconstruction Process Tim Baker Purdue/UCSD Penn State Med School – Friday, 4-Oct-2013

  11. 2a. Particle Picking 500Å 1000Å Penn State Med School – Friday, 4-Oct-2013

  12. 2a. Particle Picking Penn State Med School – Friday, 4-Oct-2013

  13. 579 capsids 21 capsids 2a. Particle Picking 451 x 451 pixels Penn State Med School – Friday, 4-Oct-2013

  14. micrograph 2b. CTF Estimation Penn State Med School – Friday, 4-Oct-2013

  15. power spectrum 2b. CTF Estimation Penn State Med School – Friday, 4-Oct-2013

  16. power spectrum 2b. CTF Estimation Penn State Med School – Friday, 4-Oct-2013

  17. • Picked 579 biggies & 21 smallies from 1 micrograph (2134) • Repeat for other micrographs: ugraphBig Small total 2134 579 21 600 2135 508 17 525 2136 528 30 558 2137 490 8 498 2138 540 12 552 Total 2645 88 2733 Mean 529 17 546 • Defocus estimates ugraph defocus 2134 2.77 2135 2.85 2136 3.08 2137 3.20 2138 2.87 • Continue with analysis of biggies… 2a & b. Summary Penn State Med School – Friday, 4-Oct-2013

  18. 2c. RMC – initial model search • Iterate search with new model for 10 rounds • Repeat whole procedure several times with different starting orientations – look for acceptable and consistent results. Penn State Med School – Friday, 4-Oct-2013

  19. conway% setup_rmc ------ SETUP_RMC version v4.03.1 ------ NAME setup_rmc - script for setting up random model calculation EXAMPLE setup_rmc -ncpu 4 -seed 123 -list listfile setup_rmc -usedefaults DESCRIPTION All input specified using the syntax -key value. Defaults values are shown in brackets following descriptions. To use all default values, use the -usedefaults flag. 'n' = integer, 'f' = float, 's' = string -boxrad n image box size [obtained from image file] -fsc_nbins n number of bins for FSC calculation [50] -fsc_res_min f minimum resolution (A) for FSC calculation [60] -fsc_res_max f maximum resolution (A) for FSC calculation [30] -list s file or expression listing particle parameter files If not specified, then setup_rmc looks for (1) file named 'list' or (2) *00n files in rundir -multi run multiple RMCs in parallel -ncpu n number of CPUs for each RMC computation[4] -nimages n number of images to use in constructing model [150] -nmodels n number of random models [10] -noctf turn off CTF corrections -nodefile s file containing list of compute nodes -res f highest resolution used in constructing map -rmax n maximum capsid radius -rmin n minimum capsid radius -rundir s directory containing particle parameter files [dat] -seed n seed for random number generator. Use an integer for reproducible result or -seed=time for seed based on seconds since 1/1/1970 [1] -symm_code n symmetry of reconstruction [532] -trad traditional RMC calculation (best map chosen using FSC) 2c. RMC – initial model search Penn State Med School – Friday, 4-Oct-2013

  20. conway% setup_rmc –nmodels 5 --- setup_rmc starting --- setup_rmc parameters: Default rundir = dat Default maximum map resolution = 29 list not specified - setup_rmc will first check for file 'list', then look for files dat/*00n Default ncpu = 4 Default fsc_nbins = 50 Default fsc_res_min = 60.0 Default fsc_res_max = 30.0 Default nimages = 150 User specified nmodels = 5 Default symm_code = 532 Default seed = 1 Parameter files in dat considered for model construction: all5.dat_000 Box radius from PIF/MRC file = 112 Instructions: Run RMC_run to construct starting model Run RMC_cleanup to remove temporary files after calculations complete Starting model will be found at dat/rmc.pif auto3dem input file auto-bin2_master automatically generated --- setup_rmc done --- conway% RMC_run 2c. RMC – initial model search Note – 150 particles only Penn State Med School – Friday, 4-Oct-2013

  21. Trial 1 Iteration 0 0 1 2 3 4 2c. RMC – initial model search 5 6 7 8 9 10 Penn State Med School – Friday, 4-Oct-2013

  22. Trial 5 Trial 1 Trial 2 Trial 3 Trial 4 2c. RMC – initial model search “Best” Not precise, but accurate Penn State Med School – Friday, 4-Oct-2013

  23. 2d. Auto3Dem i. Initial orientation search– we have a model (RMC)– but no orientations ii. Refinement– improve orientations– improve resolution global refine local refine auto mode search Uses PPFT auto mode refine Uses POR po2r mode global po2r mode local Penn State Med School – Friday, 4-Oct-2013

  24. PPFT 2d. Auto3Dem POR Penn State Med School – Friday, 4-Oct-2013

  25. 2d. Auto3Demi. Initial orientation search (PPFT) vs. • I usually run 10 iterations to ensure the model is decent and particle orientations have a chance to sample their correct values • Use coarse angle steps – want a quick answer, rough but accuratee.g. ppftdelta_theta 2ppftbin_factor 2 Penn State Med School – Friday, 4-Oct-2013

  26. Projection from RMC map 2d. Auto3Demi. Initial orientation search (PPFT) auto mode search ... ppftannulus_high 110 ppftannulus_low 33 ppftbin_factor 2 ppftctfmode 3 ppftdelta_theta 2 ppft filter_factor_1 0.1 ppftinput_mode 2 ppftpftrad_hi 112 ppftpftrad_lo 1 ppftpftrad_step 1 ppftresolution_high 30 ppftresolution_low 124.2 ppfttemperature_factor 0 Penn State Med School – Friday, 4-Oct-2013

  27. delta map map itr mode estres angle undamp damp time cpunptlesntotnmg defocus --- ---- ------ ------ ------ ------ ----- --- ------ ------ --- --------- # cycle 1. Start with RMC model (5), 5 iterations 1 s(2) 18.48 2.00 15.60 13.49 35 8 2639 2645 5 2.77-3.20 2 s(2) 13.07 2.00 11.56 10.36 35 8 2638 2645 5 2.77-3.20 3 s(2) 12.58 2.00 11.17 10.05 36 8 2638 2645 5 2.77-3.20 4 s(2) 12.64 2.00 11.22 10.09 36 8 2638 2645 5 2.77-3.20 5 s(2) 13.59 2.00 11.97 10.69 36 8 2639 2645 5 2.77-3.20 2d. Auto3Demi. Initial orientation search (PPFT) RMC iter 1 iter 2 iter 3 iter 4 iter 5 150p 2639p 2638p 2638p 2638p 2639p Penn State Med School – Friday, 4-Oct-2013

  28. delta map map itr mode estres angle undamp damp time cpunptlesntotnmg defocus --- ---- ------ ------ ------ ------ ----- --- ------ ------ --- --------- # cycle 1. Start with RMC model (5), 5 iterations 1 s(2) 18.48 2.00 15.60 13.49 35 8 2639 2645 5 2.77-3.20 2 s(2) 13.07 2.00 11.56 10.36 35 8 2638 2645 5 2.77-3.20 3 s(2) 12.58 2.00 11.17 10.05 36 8 2638 2645 5 2.77-3.20 4 s(2) 12.64 2.00 11.22 10.09 36 8 2638 2645 5 2.77-3.20 5 s(2) 13.59 2.00 11.97 10.69 36 8 2639 2645 5 2.77-3.20 2d. Auto3Demi. Initial orientation search (PPFT) iter 1 1 5 iter 2 Penn State Med School – Friday, 4-Oct-2013

  29. delta map map itr mode estres angle undamp damp time cpunptlesntotnmg defocus --- ---- ------ ------ ------ ------ ----- --- ------ ------ --- --------- # cycle 1. Start with RMC model (5), 5 iterations 1 s(2) 18.48 2.00 15.60 13.49 35 8 2639 2645 5 2.77-3.20 2 s(2) 13.07 2.00 11.56 10.36 35 8 2638 2645 5 2.77-3.20 3 s(2) 12.58 2.00 11.17 10.05 36 8 2638 2645 5 2.77-3.20 4 s(2) 12.64 2.00 11.22 10.09 36 8 2638 2645 5 2.77-3.20 5 s(2) 13.59 2.00 11.97 10.69 36 8 2639 2645 5 2.77-3.20 2d. Auto3Demi. Initial orientation search (PPFT) 5 4 Penn State Med School – Friday, 4-Oct-2013

  30. RMC iter 5 RMC iter 5 2d. Auto3Demi. Initial orientation search (PPFT) Penn State Med School – Friday, 4-Oct-2013

  31. • Better model, starting orientations for all particles • POR/global generally does a better job than PPFT • But…very slow • After PPFT, do 1 iteration of POR/global, coarse steps 2d. Auto3Demii. Global orientation refine (POR mode global) auto mode refine ... # Iteration parameters auto iter_start 6 auto niter 1 ... po2rctfmode 2 po2r dangle 2 po2r dcenter 3 po2rgangle 3 po2r mode global po2r nangle4 po2r ncenter4 po2rres_max 12.65 po2r res_min 124.2 po2rtempfac0 delta map map itr mode estres angle undamp damp time cpunptlesntotnmg defocus --- ---- ------ ------ ------ ------ ----- --- ------ ------ --- --------- # cycle 1. Start with RMC model (5), 5 iterations 1 s(2) 18.48 2.00 15.60 13.49 35 8 2639 2645 5 2.77-3.20 2 s(2) 13.07 2.00 11.56 10.36 35 8 2638 2645 5 2.77-3.20 3 s(2) 12.58 2.00 11.17 10.05 36 8 2638 2645 5 2.77-3.20 4 s(2) 12.64 2.00 11.22 10.09 36 8 2638 2645 5 2.77-3.20 5 s(2) 13.59 2.00 11.97 10.69 36 8 2639 2645 5 2.77-3.20 # cycle 2. Global POR, 1 iteration 6 r(g) 11.34 3.00 10.18 9.24 1766 4 1984 2645 5 2.77-3.20 auto score_fraction 0.75 Penn State Med School – Friday, 4-Oct-2013

  32. delta map map itr mode estres angle undamp damp time cpunptlesntotnmg defocus --- ---- ------ ------ ------ ------ ----- --- ------ ------ --- --------- # cycle 1. Start with RMC model (5), 5 iterations 1 s(2) 18.48 2.00 15.60 13.49 35 8 2639 2645 5 2.77-3.20 2 s(2) 13.07 2.00 11.56 10.36 35 8 2638 2645 5 2.77-3.20 3 s(2) 12.58 2.00 11.17 10.05 36 8 2638 2645 5 2.77-3.20 4 s(2) 12.64 2.00 11.22 10.09 36 8 2638 2645 5 2.77-3.20 5 s(2) 13.59 2.00 11.97 10.69 36 8 2639 2645 5 2.77-3.20 # cycle 2. Global POR, 1 iteration 6 r(g) 11.34 3.00 10.18 9.24 1766 4 1984 2645 5 2.77-3.20 2d. Auto3Demii. Global orientation refine (POR mode global) iter 5 iter 6 2639p 1766p Penn State Med School – Friday, 4-Oct-2013

  33. delta map map itr mode estres angle undamp damp time cpunptlesntotnmg defocus --- ---- ------ ------ ------ ------ ----- --- ------ ------ --- --------- # cycle 1. Start with RMC model (5), 5 iterations 1 s(2) 18.48 2.00 15.60 13.49 35 8 2639 2645 5 2.77-3.20 2 s(2) 13.07 2.00 11.56 10.36 35 8 2638 2645 5 2.77-3.20 3 s(2) 12.58 2.00 11.17 10.05 36 8 2638 2645 5 2.77-3.20 4 s(2) 12.64 2.00 11.22 10.09 36 8 2638 2645 5 2.77-3.20 5 s(2) 13.59 2.00 11.97 10.69 36 8 2639 2645 5 2.77-3.20 # cycle 2. Global POR, 1 iteration 6 r(g) 11.34 3.00 10.18 9.24 1766 4 1984 2645 5 2.77-3.20 2d. Auto3Demii. Global orientation refine (POR mode global) iter 1 18.5Å iter 5 13.6Å iter 6 11.3Å Penn State Med School – Friday, 4-Oct-2013

  34. delta map map itr mode estres angle undamp damp time cpunptlesntotnmg defocus --- ---- ------ ------ ------ ------ ----- --- ------ ------ --- --------- # cycle 1. Start with RMC model (5), 5 iterations 1 s(2) 18.48 2.00 15.60 13.49 35 8 2639 2645 5 2.77-3.20 2 s(2) 13.07 2.00 11.56 10.36 35 8 2638 2645 5 2.77-3.20 3 s(2) 12.58 2.00 11.17 10.05 36 8 2638 2645 5 2.77-3.20 4 s(2) 12.64 2.00 11.22 10.09 36 8 2638 2645 5 2.77-3.20 5 s(2) 13.59 2.00 11.97 10.69 36 8 2639 2645 5 2.77-3.20 # cycle 2. Global POR, 1 iteration 6 r(g) 11.34 3.00 10.18 9.24 1766 4 1984 2645 5 2.77-3.20 6 r(g) 11.62 2.00 10.41 9.43 5174 4 1984 2645 5 2.77-3.20 2d. Auto3Demii. Global orientation refine (POR mode global) •Iteration 6 repeated with a smaller angle (2° instead of 3°) • No significant change in resolution • Took 3 times longer to run (86 mins vs. 29 mins) • Don’t make your angle or center steps too small!! Penn State Med School – Friday, 4-Oct-2013

  35. • Better model, better orientations • POR/local is faster by inspecting a local window of orientations • Do cycles of 5 iterations, reducing angle& center steps 2d. Auto3Demii. Local orientation refine (POR mode local) delta map map itr mode estres angle undamp damp time cpunptlesntotnmg defocus --- ---- ------ ------ ------ ------ ----- --- ------ ------ --- --------- ... # cycle 2. Global POR, 1 iteration 6 r(g) 11.34 3.00 10.18 9.24 1766 4 1984 2645 5 2.77-3.20 # cycle 3. Local POR, 5 iterations 7 r(l) 10.56 2.00 9.55 8.72 70 4 1984 2645 5 2.77-3.20 8 r(l) 10.63 2.00 9.61 8.77 38 4 1983 2645 5 2.77-3.20 9 r(l) 10.59 2.00 9.58 8.74 38 4 1984 2645 5 2.77-3.20 10 r(l) 10.59 2.00 9.58 8.74 37 4 1983 2645 5 2.77-3.20 11 r(l) 10.59 2.00 9.58 8.74 38 4 1983 2645 5 2.77-3.20 auto mode refine ... # Iteration parameters auto iter_start7 auto niter 5 ... po2rctfmode 2 po2r dangle 2 po2r dcenter 3 po2rgangle 3 po2r mode local po2r nangle4 po2r ncenter4 po2rres_max11.34 po2r res_min 124.2 po2rtempfac0 . . . . +8° . . . . . . . . +6° . . . . . . . . +4° . . . . . . . . +2° . . . . -8° -6°-4° -2° 0° +2° +4° +6° +8° (Φ) . . . . -2° . . . . . . . . -4° . . . . . . . . -6° . . . . . . . . -8° . . . . (θ) Penn State Med School – Friday, 4-Oct-2013

  36. delta map map itr mode estres angle undamp damp time cpunptlesntotnmg defocus --- ---- ------ ------ ------ ------ ----- --- ------ ------ --- --------- ... # cycle 2. Global POR, 1 iteration 6 r(g) 11.34 3.00 10.18 9.24 1766 4 1984 2645 5 2.77-3.20 # cycle 3. Local POR, 5 iterations 7 r(l) 10.56 2.00 9.55 8.72 70 4 1984 2645 5 2.77-3.20 8 r(l) 10.63 2.00 9.61 8.77 38 4 1983 2645 5 2.77-3.20 9 r(l) 10.59 2.00 9.58 8.74 38 4 1984 2645 5 2.77-3.20 10 r(l) 10.59 2.00 9.58 8.74 37 4 1983 2645 5 2.77-3.20 11 r(l) 10.59 2.00 9.58 8.74 38 4 1983 2645 5 2.77-3.20 2d. Auto3Demii. Local orientation refine (POR mode local) iter 6 iter 11 Penn State Med School – Friday, 4-Oct-2013

  37. delta map map itr mode estres angle undamp damp time cpunptlesntotnmg defocus --- ---- ------ ------ ------ ------ ----- --- ------ ------ --- --------- ... # cycle 2. Global POR, 1 iteration 6 r(g) 11.34 3.00 10.18 9.24 1766 4 1984 2645 5 2.77-3.20 # cycle 3. Local POR, 5 iterations 7 r(l) 10.56 2.00 9.55 8.72 70 4 1984 2645 5 2.77-3.20 8 r(l) 10.63 2.00 9.61 8.77 38 4 1983 2645 5 2.77-3.20 9 r(l) 10.59 2.00 9.58 8.74 38 4 1984 2645 5 2.77-3.20 10 r(l) 10.59 2.00 9.58 8.74 37 4 1983 2645 5 2.77-3.20 11 r(l) 10.59 2.00 9.58 8.74 38 4 1983 2645 5 2.77-3.20 2d. Auto3Demii. Global orientation refine (POR mode global) iter 6 11.3Å iter 11 10.6Å Penn State Med School – Friday, 4-Oct-2013

  38. delta map map itr mode estres angle undamp damp time cpunptlesntotnmg defocus --- ---- ------ ------ ------ ------ ----- --- ------ ------ --- --------- ... 11 r(l) 10.59 2.00 9.58 8.74 38 4 1983 2645 5 2.77-3.20 # 4. Local POR, 5 iterations 16 r(l) 10.06 1.00 9.14 8.38 39 4 1983 2645 5 2.77-3.20 # 5. Local POR, 5 iterations 21 r(l) 9.91 0.50 9.02 8.27 40 4 1985 2645 5 2.77-3.20 # 6. Local POR, 5 iterations 26 r(l) 9.62 0.30 8.77 8.06 42 4 1983 2645 5 2.77-3.20 # 7. Try some deconvolution in P3DR 31 r(l) 9.46 0.30 8.64 7.95 45 4 1983 2645 5 2.77-3.20 # 8. Try some deconvolution in P3DR 36 r(l) 9.35 0.20 8.55 7.88 48 4 1983 2645 5 2.77-3.20 # 9. Last round 41 r(l) 9.13 0.10 8.37 7.72 63 4 1983 2645 5 2.77-3.20 2d. Auto3Demii. Global orientation refine (POR mode global) iter 6 11.3Å iter11 10.6Å iter 41 9.1Å Penn State Med School – Friday, 4-Oct-2013

  39. iter 11 iter 41 2d. Auto3Demii. Global orientation refine (POR mode global) • Needs more particles: - reduce noise - increase resolution Penn State Med School – Friday, 4-Oct-2013

  40. •Previously bin-by-2 data (2.76Å/pixel) • Un-binned data (1.38Å/pixel) • FSC(0.5) = 7.0Å; 0.26°; 11598 / 23248p 50 µgraphs 2d. Auto3Demii. Global orientation refine (POR mode global) 100Å Penn State Med School – Friday, 4-Oct-2013

  41. •Previously bin-by-2 data (2.76Å/pixel) • Un-binned data (1.38Å/pixel) • FSC(0.5) = 7.0Å; 0.26°; 11598 / 23248p 50 µgraphs 2d. Auto3Demii. Global orientation refine (POR mode global) iter 6 11.3Å iter11 10.6Å iter 41 9.1Å no-bin 7.0Å Penn State Med School – Friday, 4-Oct-2013

  42. FSC = Fourier Shell Correlation • Correlation between two ½-dataset density maps in Fourier (reciprocal) space • Measure of consistencyvs spatial frequency (spacing) • Consistency breaks down when common signal stops Problems • ½-dataset density maps inferior to full dataset map • Correlation limit – which? 0.5, 0.3, 0.143,… • Consistency may be extended by systematic error including model bias “Gold Standard” (Henderson et al, Structure 20, 2012) • ½-datasets analysed independently (RMC onwards) • Correlation limit of 0.143 DPR SSNR 2d. Resolution Penn State Med School – Friday, 4-Oct-2013

  43. Over-fitting 2d. Resolution Solid – ½ datasets Dashed – full dataset vsxtal map Black – “gold standard” Grey – “classic” Penn State Med School – Friday, 4-Oct-2013

  44. 2e. Interpretation & Modelling Penn State Med School – Friday, 4-Oct-2013

  45. Recipe for RMC/Auto3Dem • RMC, check sections • Auto3Dem – search, 10 iterations: ppftdelta_theta 2 (or 3) • Auto3Dem – refine (g), 1 iteration: po2r gangle 2 (or 3) • Auto3Dem – refine (l), 5 iterations: po2r dangle 1.2po2rdcenter2 – 5 • Match dangle and dcenter to current resolutioneg: 300Å radius particle, 1° ≈ 1°*pi/180*300  5 Å at edgeSo at 20Å, refine at 1° angle steps 5 Å center steps (change to pixels) • Repeat refine (local) and adjust dangle and dcenter down to match new resolution • Use a realistic fraction of particles • Use phase flipping (ctfmode 2) especially in po2r • Use deconvolution (ctfmode1) with modest tempfac in p3dr • Run p3dr “by hand” to optimize data limits & tempfac Summary Penn State Med School – Friday, 4-Oct-2013

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