# papers

email: rwilfong@purdue.edu
table_name: testing
doi: 10.1016/j.jmb.2023.168068
pmid: 37003470
scikit_keywords: structures, approaches, cellular, complexes, data
nltk_keywords: accessibility presented, artifacts missing, automated structural, biases often, complex densities
time: 2023-05-05 02:57:25
title:
  Computational Methods Toward Unbiased Pattern Mining and Structure Determination in Cryo-Electron Tomography Data.

abstract:
  Cryo-electron tomography can uniquely probe the native cellular environment for macromolecular structures. Tomograms feature complex data with densities of diverse, densely crowded macromolecular complexes, low signal-to-noise, and artifacts such as the missing wedge effect. Post-processing of this data generally involves isolating regions or particles of interest from tomograms, organizing them into related groups, and rendering final structures through subtomogram averaging. Template-matching and reference-based structure determination are popular analysis methods but are vulnerable to biases and can often require significant user input. Most importantly, these approaches cannot identify novel complexes that reside within the imaged cellular environment. To reliably extract and resolve structures of interest, efficient and unbiased approaches are therefore of great value. This review highlights notable computational software and discusses how they contribute to making automated structural pattern discovery a possibility. Perspectives emphasizing the importance of features for user-friendliness and accessibility are also presented.

summary:
  Summary 1: To reliably extract and resolve structures of interest, efficient and unbiased approaches are therefore of great value. Perspectives emphasizing the importance of features for user-friendliness and accessibility are also presented. Summary 2: Post-processing of this data generally involves isolating regions or particles of interest from tomograms, organizing them into related groups, and rendering final structures through subtomogram averaging. Tomograms feature complex data with densities of diverse, densely crowded macromolecular complexes, low signal-to-noise, and artifacts such as the missing wedge effect.


email: rwilfong@purdue.edu
table_name: testing
doi: 10.1016/j.ultramic.2014.01.010
pmid: 24566042
scikit_keywords: dose, electron, high, resolution, ac
nltk_keywords: ac-hrtem image, achieve highest, dependence signal-to-noise, determine optimum, doses required
time: 2023-05-05 02:59:24
title:
  Electron dose dependence of signal-to-noise ratio, atom contrast and resolution in transmission electron microscope images.

abstract:
  In order to achieve the highest resolution in aberration-corrected (AC) high-resolution transmission electron microscopy (HRTEM) images, high electron doses are required which only a few samples can withstand. In this paper we perform dose-dependent AC-HRTEM image calculations, and study the dependence of the signal-to-noise ratio, atom contrast and resolution on electron dose and sampling. We introduce dose-dependent contrast, which can be used to evaluate the visibility of objects under different dose conditions. Based on our calculations, we determine optimum samplings for high and low electron dose imaging conditions.

summary:
  Summary 1: In this paper we perform dose-dependent AC-HRTEM image calculations, and study the dependence of the signal-to-noise ratio, atom contrast and resolution on electron dose and sampling. We introduce dose-dependent contrast, which can be used to evaluate the visibility of objects under different dose conditions. Summary 2: In order to achieve the highest resolution in aberration-corrected (AC) high-resolution transmission electron microscopy (HRTEM) images, high electron doses are required which only a few samples can withstand. In this paper we perform dose-dependent AC-HRTEM image calculations, and study the dependence of the signal-to-noise ratio, atom contrast and resolution on electron dose and sampling.


email: rwilfong@purdue.edu
table_name: testing
doi: 10.1016/j.jsb.2017.07.007
pmid: 28743638
scikit_keywords: ctf, 3d, correction, resolution, averaging
time: 2023-05-05 03:00:20
title:
  Efficient 3D-CTF correction for cryo-electron tomography using NovaCTF improves subtomogram averaging resolution to 3.4Å.

abstract:
  Cryo-electron tomography (cryo-ET) allows cellular ultrastructures and macromolecular complexes to be imaged in three-dimensions in their native environments. Cryo-electron tomograms are reconstructed from projection images taken at defined tilt-angles. In order to recover high-resolution information from cryo-electron tomograms, it is necessary to measure and correct for the contrast transfer function (CTF) of the microscope. Most commonly, this is performed using protocols that approximate the sample as a two-dimensional (2D) plane. This approximation accounts for differences in defocus and therefore CTF across the tilted sample. It does not account for differences in defocus of objects at different heights within the sample; instead, a 3D approach is required. Currently available approaches for 3D-CTF correction are computationally expensive and have not been widely implemented. Here we simulate the benefits of 3D-CTF correction for high-resolution subtomogram averaging, and present a user-friendly, computationally-efficient 3D-CTF correction tool, NovaCTF, that is compatible with standard tomogram reconstruction workflows in IMOD. We validate the approach on synthetic data and test it using subtomogram averaging of real data. Consistent with our simulations, we find that 3D-CTF correction allows high-resolution structures to be obtained with much smaller subtomogram averaging datasets than are required using 2D-CTF. We also show that using equivalent dataset sizes, 3D-CTF correction can be used to obtain higher-resolution structures. We present a 3.4Å resolution structure determined by subtomogram averaging.

summary:
  Summary 1: In order to recover high-resolution information from cryo-electron tomograms, it is necessary to measure and correct for the contrast transfer function (CTF) of the microscope. Here we simulate the benefits of 3D-CTF correction for high-resolution subtomogram averaging, and present a user-friendly, computationally-efficient 3D-CTF correction tool, NovaCTF, that is compatible with standard tomogram reconstruction workflows in IMOD. Summary 2: Consistent with our simulations, we find that 3D-CTF correction allows high-resolution structures to be obtained with much smaller subtomogram averaging datasets than are required using 2D-CTF. We validate the approach on synthetic data and test it using subtomogram averaging of real data.

mesh_terms:
  Capsid Proteins, Cryoelectron Microscopy, HIV-1, Image Processing, Computer-Assisted, Reproducibility of Results, Software, Workflow

nltk_keywords:
  3.4å resolution, cellular ultrastructures, compatible standard, complexes imaged, computationally expensive


