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José María Carazo BioComputing Unit Centro Nacional de Biotecnología

Three-dimensional Electron Tomography of Macromolecules (3D-EM) and GRID Overview and Challenges ahead. José María Carazo BioComputing Unit Centro Nacional de Biotecnología. 3D-EM Conceptual bases (1). “Similar” to X-ray or NMR medical tomography, but on the nanometer scale.

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José María Carazo BioComputing Unit Centro Nacional de Biotecnología

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  1. Three-dimensional Electron Tomography of Macromolecules (3D-EM) and GRID Overview and Challenges ahead José María Carazo BioComputing Unit Centro Nacional de Biotecnología

  2. 3D-EM Conceptual bases (1) • “Similar” to X-ray or NMR medical tomography, but on the nanometer scale

  3. 3D-EM Conceptual bases (2) • Experimental situation in Electron Tomography

  4. Analogy: Data adquisition for CT

  5. Experimental situation: Original specimen • Limited number of projections • Single image noise • And…. • Partial lack of control over particle homogeneicity • Partical lack of control over data collection geometry Projection images Reconstruction algorithms Three-dimensional reconstruction

  6. Data adquisition for 3D-EM (II) Barcena et al., EMBO J., 2001 • pH 7.6 • 0.1 mM ATP

  7. Reconstruction as a linear set of equations

  8. x ...  An example of a reconstruction algorithm: ART, the “basics” Conceptual schema Proyectar Retroproyectar Iterar (n veces) - Sanchez-Sorzano et al, 1999, 2000, 2001, 2002, 2003, 2004, 2005

  9. protein ribosome virus mitochondria 10 nm. 100 nm. 1 mm. 1 m. Range of macromolecular structures studied by three-dimensional EM

  10. One of 3DEM “promises” • 3DEM especially suited to study large macromolecules. • 3DEM holds the possibility/promise to work with macromolecular machines in a mixture of conformational states…… coming closer to the study of functional states. • Because we do want to deal with “conformational mixtures” in states closer to functional ones, or because we do not know how to “freeze” them without inducing potential artifacts.

  11. CRYO MICROSCOPY ADVANTAGES: The apparent “paradox” Native state No spatial restrictions Conformational changes Structure-function relationships Resolution Conformational changes Heterogeneity Synchronization Image classification Homogeneous groups Paradox: Polimorphism vs resolution

  12. An analogy to “conformational changes” • pH 7.6 • 0.1 mM ATP

  13. alignment & classification are strongly intertwined! (and very robust algorithms are needed to deal with the noise) The actual situation(“single particles”, no tilt –high resolution-) • The 3D reconstruction process requires: • To know the orientation of the projections • Need of an a posteriori angular assignment step (=determination of the image projection geometry) • The existence of (only) ONE underlying 3D structure • Structural homogeneity is implicit in most reconstructions algorithms • In practice: • unknown orientations • assemblies in distinct states • very noisy projections

  14. Likelihood • Find a model Q that optimizes the log-likelihood of observing the entire dataset: integrate over all unknowns! Q comprises: estimates for 3D objects, s, … Optimization algorithm: Expectation Maximization

  15. Two test cases • 70S E.coli Ribosome +tRNA(fMet) + tRNA(Ile) + EF-G + GDPNP • discrete heterogeneity(non-stoichiometric ligand binding + associated conformational changes) • Large T-antigen double hexamers + dsDNA • continuous heterogeneity(flexible domain movements)

  16. Preliminary reconstruction 91,114 particles; 9.9 Å resolution fragmented (depicted at a lower threshold) blurred

  17. Seed generation 80 Å filter 4 random subsets; 1 iter ML

  18. ML optimization • 4 references • 91,114 particles • 64x64 pix (6.2Å/pix) • 25 iterations • 10° angular sampling 6 CPU-months

  19. no ratcheting; no EF-G; 3 tRNAs differences: overall rotations ratcheting, EF-G, 1 tRNA ML-derived classes

  20. Our Software Biocomputing Unit. CNB(http:www.biocomp.cnb.uam.es) XMIPP (X-Windows Image Processing Package)

  21. The Biocomputing “cluster”J.M.Carazo (CNB) • Structural biology of helicases • Dr.Mikel Valle (CNB) **(CIC Biogune) • Roberto Melero (CNB) • Dr.Carmen San Martín (CNB) • Yacob Gómez (CNB) • Marta Rajkiewicz (CNB) • Dr. Rafael Núñez (CNB) • Dr. Isabel Cuesta (CNB) Methods development in 3DEM • Dr. Sjors Scheres (CNB) • Dr. Javier Velázquez (CNB) ** (UCSF) • Dr. Roberto Marabini (UAM) • Ignacio Arganda (UAM) • Javier Rodriguez Falces (CNB) • Ana Iriarte (CNB) • Dr. Carlos Oscar Sánchez (CEU) • Dr. José Jesús Fernández (UAL) • José Román Bilbao Castro (UAL) • Computational and Data Grid • Dr. Natalia Jimézez-Lozano (PCM/INB) • Dr. José Ramón Macías (CNB)) • Eng. Alfredo Solano (CNB) • Eng. Enrique de Andrés (PCM/INB) • Eng. Germán Carrera (CNB) • Eng. David García • Dr. José Ramón Valverde • Eng. Jesus Cuenca (CNB) • Functional genomics: Dr. Alberto Pascual (UCM-CNB) • Dr. Monica Chagoyen (CNB) • Pedro Carmona (CNB) • Javier Díaz (CNB) • Federico Abascal • UCM TEAM • Main external collaborators • Prof. Gabor Herman (NYU) • Prof. Ellen Fanning (Vanderbilt) • Prof. Xiojiang Cheng (UCLA) • Prof. Claudia Gruss (Konstanz) • Prof. Willy Wrigger (Houston MC) • Proaf. Juan Carlos Alonso (CNB) • Prof. J. Frank (Albany) • Integromics spin-off • ….. • My right organizing arm…. • Ms. Blanca Benítez.

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