title: Progressive Stochastic Reconstruction Technique (PSRT) for cryo electron tomography.
abstract: Cryo Electron Tomography (cryoET) plays an essential role in Structural Biology, as it is the only technique that allows to study the structure of large macromolecular complexes in their close to native environment in situ. The reconstruction methods currently in use, such as Weighted Back Projection (WBP) or Simultaneous Iterative Reconstruction Technique (SIRT), deliver noisy and low-contrast reconstructions, which complicates the application of high-resolution protocols, such as Subtomogram Averaging (SA). We propose a Progressive Stochastic Reconstruction Technique (PSRT) - a novel iterative approach to tomographic reconstruction in cryoET based on Monte Carlo random walks guided by Metropolis-Hastings sampling strategy. We design a progressive reconstruction scheme to suit the conditions present in cryoET and apply it successfully to reconstructions of macromolecular complexes from both synthetic and experimental datasets. We show how to integrate PSRT into SA, where it provides an elegant solution to the region-of-interest problem and delivers high-contrast reconstructions that significantly improve template-based localization without any loss of high-resolution structural information. Furthermore, the locality of SA is exploited to design an importance sampling scheme which significantly speeds up the otherwise slow Monte Carlo approach. Finally, we design a new memory efficient solution for the specimen-level interior problem of cryoET, removing all associated artifacts.
authors: Saarland University, Campus E 1.1, 66123 Saarbrücken, Germany; IMPRS-CS, Max-Planck Institute for Informatics, Campus E 1.4, 66123 Saarbrücken, Germany. Electronic address: turonova@cs.uni-saarland.de.
authors: Beata
authors: B
authors: Turoňová
authors: Saarland University, Campus E 1.1, 66123 Saarbrücken, Germany; Agents and Simulated Reality Group, DFKI GmbH, Campus E 3.4, 66123 Saarbrücken, Germany; Eyen SE, Na Nivách 1043/16, 14100 Prague, Czech Republic.
authors: Lukas
authors: L
authors: Marsalek
authors: Saarland University, Campus E 1.1, 66123 Saarbrücken, Germany; Intel VCI, Campus E 1.1, 66123 Saarbrücken, Germany.
authors: Tomáš
authors: T
authors: Davidovič
authors: Saarland University, Campus E 1.1, 66123 Saarbrücken, Germany; Agents and Simulated Reality Group, DFKI GmbH, Campus E 3.4, 66123 Saarbrücken, Germany; Intel VCI, Campus E 1.1, 66123 Saarbrücken, Germany.
authors: Philipp
authors: P
authors: Slusallek
mesh_terms: D000465:Algorithms; D020285:Cryoelectron Microscopy / Q000379:methods; D055032:Electron Microscope Tomography / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods; D046911:Macromolecular Substances / Q000737:chemistry; D009010:Monte Carlo Method; D015203:Reproducibility of Results; D012270:Ribosomes / Q000737:chemistry; D013269:Stochastic Processes
chemical_list: D046911:Macromolecular Substances
keywords: 3D reconstruction; Cryo electron tomography; Metropolis–Hastings; Monte Carlo; Stochastic reconstruction; Subtomogram averaging