Your browser doesn't support javascript.
loading
nextPYP: a comprehensive and scalable platform for characterizing protein variability in situ using single-particle cryo-electron tomography.
Liu, Hsuan-Fu; Zhou, Ye; Huang, Qinwen; Piland, Jonathan; Jin, Weisheng; Mandel, Justin; Du, Xiaochen; Martin, Jeffrey; Bartesaghi, Alberto.
Affiliation
  • Liu HF; Department of Biochemistry, Duke University, Durham, NC, USA.
  • Zhou Y; Department of Computer Science, Duke University, Durham, NC, USA.
  • Huang Q; Department of Computer Science, Duke University, Durham, NC, USA.
  • Piland J; Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA.
  • Jin W; Department of Computer Science, Duke University, Durham, NC, USA.
  • Mandel J; Department of Computer Science, Duke University, Durham, NC, USA.
  • Du X; Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Martin J; Department of Computer Science, Duke University, Durham, NC, USA.
  • Bartesaghi A; Department of Biochemistry, Duke University, Durham, NC, USA. alberto.bartesaghi@duke.edu.
Nat Methods ; 20(12): 1909-1919, 2023 Dec.
Article in En | MEDLINE | ID: mdl-37884796
Single-particle cryo-electron tomography is an emerging technique capable of determining the structure of proteins imaged within the native context of cells at molecular resolution. While high-throughput techniques for sample preparation and tilt-series acquisition are beginning to provide sufficient data to allow structural studies of proteins at physiological concentrations, the complex data analysis pipeline and the demanding storage and computational requirements pose major barriers for the development and broader adoption of this technology. Here, we present a scalable, end-to-end framework for single-particle cryo-electron tomography data analysis from on-the-fly pre-processing of tilt series to high-resolution refinement and classification, which allows efficient analysis and visualization of datasets with hundreds of tilt series and hundreds of thousands of particles. We validate our approach using in vitro and cellular datasets, demonstrating its effectiveness at achieving high-resolution and revealing conformational heterogeneity in situ. The framework is made available through an intuitive and easy-to-use computer application, nextPYP ( http://nextpyp.app ).
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / Electron Microscope Tomography Language: En Journal: Nat Methods Journal subject: TECNICAS E PROCEDIMENTOS DE LABORATORIO Year: 2023 Type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / Electron Microscope Tomography Language: En Journal: Nat Methods Journal subject: TECNICAS E PROCEDIMENTOS DE LABORATORIO Year: 2023 Type: Article Affiliation country: United States