Lecture 8: Tomography (part 1) 1. Principles of Electron Tomography 2. Sample Preparation 3. Data Acquisition 4. Tomogram Reconstruction 5. Tomogram Denoising Principles of EM Tomography Computer Tomography Electron Tomography Workflow in Electron Tomography Principles of Electron Tomography Aligned Tilt Series Reconstructed Tomogram Sample Preparation for CryoET BIOLOGICAL SAMPLE Purified particles Cellular samples VITRIFICATION Plunge-freezing in liquid ethane High-pressure freezing V i i Cryo-FIB milling Cryo-ultramicrotomy IMAGING CryoEM Cryo-electron tomography of thin specimen 3D RECONSTRUCTION & INTERPRETATION Acquisition of Tilt Series Eucentric height Acquisition of Tilt Series Tilt axis offset Acquisition of Tilt Series •••••••• ••••• 0 D 0 k«* xxxxx xxxxx xxxxx xxxxxxx x\\\\\\ xxxxxxx xxxxxxx \ \ \ \ \ \ \ Hi* I xxxxxxxx }{}}}{$} xxxxxxxx XXXXXXXX xxxxxxxx 0 0 Predictive Method Collect few initial tilt images Determine image shifts Fit shift to a model of tilt geometry Predict and apply beam/image shifts Collect further images, refine model -J / pata ; j 4 Acquisition Acquisition of Tilt Series 0 k«* •••••••• •••••••• •••••••• •••••••• •••••••• •••••••• 0 0 xxxxxxxx \\\\\\\\ \x\\\\\\ A Focus Position Method Move to Focus, focus and center Move to Record, collect image Tilt, move to Focus, focus, center Move to Record, collect image Refine model of beam/image shifts Automated Data Collection Identify the target area of interest Set parameters for data collection: Range of tilt angles: -60° to +60° Angular step: 1° or 2° Dose per image: 0.5-2.0 e/A2 Dose distribution: uniform vs. tilt-dependent Automated Data Collection Automated focusing Automated determination of the Eucentric height lens Magnified image Electron Tomography 5bt Data acquisition (tilt series) Reconstructed tomogram Seed fiducial markers (bshow, btrack) Refine a (bshow, lignment btrack) 1 f Reconstruct tomogram (bmgft, btomrec, bzfft, bpatch) Denoise tomogram (bmedian, bbif, bnad) Tomogram reconstruction workflow (IMOD, Bsoft, EMAN2, Xmipp) Image processing in Bsoft j □ Bsoft -> G Ä Ď lsbr.niams.nih.gov/bsoft/# :■■ Apps Q Noviny Q Radia D TV D Slovníky C3 Software Q Journals Q Vyhledavače D D.C. Q Dan CD CEITEC » CD Other bookmarks ■n Code Design Usage Developer Bernard's Software Package Bsoft is a collection of programs and a platform for development of software for unage and molecular processing in structural biology. Problems in structural biology are approached with a highly modular design, allowing fast development of new algorithms without the burden of issues such as file I O. It provides an easily accessible interface, a resource that can be and lias been used in other packages. The evolution of Bsoft is unique in the sense that it started from different aims and intentions than the typical image processing package. In stead of solving a particular image processing problem. Bsoft developed to deal with the disparities in approaches in other packages, as well as supporting efforts to handle large volumes of data and processing tasks in heterogeneous environments. As such, the layout and concepts within Bsoft are significantly different from other programs doing the same kind of processing. In the following sections I'm presenting the background and philosophies of Bsoft. which are still evolving, and may continue for some tune. Images are stored in pif/mrc/tif files as a set of 2D images or as slices of a 3D image. Parameters are stored in ASCII star files with predetermined organization for micrographs, reconstructions and models. Heymann et al.,7. Struct. ß/o/.(2008) 161, 232 Preprocessing of collected data bnorm -ver 7 -images -rescale 127,10 -data byte -out output.star input.mrc output.pif btomo -v 7 -sampling 8.05 -axis 78 -tilt -60,2 -gold 5 -out output.star input.star Finding fiducial markers for alignment of tilt series »928 «11 °678 c6I877 ■£77 06IO o477 "397 03353 03OI °558 c474 ■»43 =413 off? 0319 0171 o85 o346 °tf51 / / / / / 0343 =512 =■189 312333 °-=99 I m70 «93 ■zw "m: ,,o*-2U/ 02 02 9 =1926 ol980 ol953 ., ' • *0*4ooo '■197,7 Ol970 ol773 "1712 0I8 ol78! 1?44 ol834 801 1680 ol758l751 o!764 / ol761 =1849 018 ol699 oiEsas 0I6O6 01602 """S&fc °1626ol603 o1608 ____. 4 1516 01474 °47S ■*780 °2#9 0I6O »2112 Seed fiducial markers (bshow, btrack) Reconstr (b'ncft. blcrr Pgnoiao tomogram id) ] Tracking fiducial markers in all tilt images btrack -ver 1 -reset -axis 78 -exclude none -resol 15,300 -shift 1000 -update -track 5 -refine markers -out FV3tomo9_trk.star FV3tomo9_seed.star >& FV3tomo9_trk.log Refinement of fiducial marker positions © C ■ © © © FV3tomo9_norm.pif: FV3tomo9_ref4.star ^ JI 11Z» © © © Tomography Tomography x 969 y 820 Image type " Averaging mi value FOM Select Clear selection Update 1 1 654 0 619 1 - 2 e 905 0 362 1 3 l 785 0 493 1 4 l 932 0 564 1 5 2 B58 0 490 1 6 6 175 0 332 1 7 1 044 IJ 729 1 8 1 693 0 751 1 9 2 365 0 854 1 10 2 580 0 721 1 :: 2 057 0 818 1 3 452 0 800 1 :: 2 479 0 605 1 14 0 572 0 619 1 15 1 694 0 806 1 16 2 280 0 360 1 1 J 4 082 0 533 1 18 2 937 0 771 1 : 9 3 388 0 508 ; 2 9 3 785 0 638 : 21 0 482 0 536 : 22 1 589 0 817 : 23 1 860 0 668 : 25 1 364 0 475 l l< < > >l J< \ * v show markers Marker radius Markers Selected marker Residual Tilt axis FOM cutoff -1 Show errors 16165 27 Marker table Residual ,3.44361591; FOM 2.293715151 Update | 78.132583 ie w show 0.000 □J- Mg Tilt Axis Level OriginX OriginY ScaleX ScaleY 1 0 -60 21 77. 90 0 3 2 1015. 9 1030. 3 1 001 3 001 1 -58 18 77. 90 0 34 1023. 5 1018. 8 1 002 3 001 2 -56 22 77. 93 0 33 1015. 1 1030. 2 1 001 1 001 3 -54 26 77. 94 0 3 2 975. 1 1050. 9 2 000 3 001 4 -52 32 77. 92 0 3 3 1008. 2 1053. 0 999 . 000 5 -50 23 77. 90 0 3 4 994. 0 1059. 2 1 001 2 000 6 -48 26 77. 92 0 35 981. a 1048. 3 1 000 001 7 -46 18 77 . 95 0 J 4 979. 7 1039. 9 1 001 3 001 8 -44 15 77 . 92 0 34 982. 7 1056. E 1 002 . 000 9 -42 19 77. 5 9 0 32 993. 4 1026. 3 : 001 1 001 10 -40 25 77. 9 2 0 35 985. a 1025. E : O0D : 001 : i -38 19 77 . 93 0 3fi 980. 8 1034 . 2 : 001 1 000 12 -36 2 2 77. 92 0 37 972. 7 1026. i : 001 1 001 : 3 -34 29 78 . 9 1 0 35 984 . 1 1025. E D 999 1 000 14 -32 2 J 78. 03 D 36 951. 4 1039. 4 1 000 1 000 15 -30 23 77. 96 0 38 975. 5 1034. 9 1 000 2 000 :■; -28. 22 77. 99 : 38 974. 7 1031. 3 2 000 3 000 3- -26. 18 78 . 2 4 0 42 939. 6 1039. 4 2 000 2 000 2 3 -24 : j 78 . 07 D 37 985. 7 1035. 3. 0 999 _ 000 19 -22 2: 78 . 03 2 4: 991. 5 1020. 3 2 000 1 000 20 -20 23 78. 14 0 45 965. 3 1039. 1 0 999 1 000 21 -18. 22 3 S 0 42 1012. 6 1029. 8 1 000 : 999 22 -16. .2 78. :■ 6 Q 4^ 989. 7 1030. 5 2 000 000 2 3 -14. 14 78. 2 9 C 49 948. 2 1038. 7 2 000 999 btrack -ver 1 -reset -refine 10,z,o,v -image FV3tomo9_align.pif -Post FV3tomo9_err.ps -out FV3tomo9_refl.star FV3tomo9_ref0.star >& FV3tomo9_refl.log Refinement of fiducial marker positions btrack -ver 1 -reset -refine 10,z,o,v -image FV3tomo9_align.pif -Post FV3tomo9_err.ps -out FV3tomo9_refl.star FV3tomo9_ref0.star >& FV3tomo9_refl.log Tomogram reconstruction Tomogram reconstruction bmark -v 7 FV3tomo7_ref4.star tomrec_PBS.tcsh -rec output.pif -resol 20 -size 2048,2048,550 -remove 10 -thick 20 -scale 1 -out output.star input.star Tomogram reconstruction bmark -v 7 FV3tomo7_ref4.star tomrec_PBS.tcsh -rec output.pif -resol 20 -size 2048,2048,550 -remove 10 -thick 20 -scale 1 -out output.star input.star Denoising of reconstructed tomograms