Fast and automatic identification of particle tilt pairs based on Delaunay triangulation

Advances in Xmipp for Cryo-Electron Microscopy: From Xmipp to Scipion

Xmipp is an open-source software package consisting of multiple programs for processing data originating from electron microscopy and electron tomography, designed and managed by the Biocomputing Unit of the Spanish National Center for Biotechnology, although with contributions from many other developers over the world. During its 25 years of existence, Xmipp underwent multiple changes and updates. While there were many publications related to new programs and functionality added to Xmipp, there is no single publication on the Xmipp as a package since 2013. In this article, we give an overview of the changes and new work since 2013, describe technologies and techniques used during the development, and take a peek at the future of the package.

Robust and ultrafast fiducial marker correspondence in electron tomography by a two-stage algorithm considering local constraints

Motivation

Electron tomography (ET) has become an indispensable tool for structural biology studies. In ET, the tilt series alignment and the projection parameter calibration are the key steps toward high-resolution ultrastructure analysis. Usually, fiducial markers are embedded in the sample to aid the alignment. Despite the advances in developing algorithms to find correspondence of fiducial markers from different tilted micrographs, the error rate of the existing methods is still high such that manual correction has to be conducted. In addition, existing algorithms do not work well when the number of fiducial markers is high.

Results

In this article, we try to completely solve the fiducial marker correspondence problem. We propose to divide the workflow of fiducial marker correspondence into two stages: (i) initial transformation determination, and (ii) local correspondence refinement. In the first stage, we model the transform estimation as a correspondence pair inquiry and verification problem. The local geometric constraints and invariant features are used to reduce the complexity of the problem. In the second stage, we encode the geometric distribution of the fiducial markers by a weighted Gaussian mixture model and introduce drift parameters to correct the effects of beam-induced motion and sample deformation. Comprehensive experiments on real-world datasets demonstrate the robustness, efficiency and effectiveness of the proposed algorithm. Especially, the proposed two-stage algorithm is able to produce an accurate tracking within an average of  ⩽ 100 ms per image, even for micrographs with hundreds of fiducial markers, which makes the real-time ET data processing possible.

Availability and implementation

The code is available at https://github.com/icthrm/auto-tilt-pair. Additionally, the detailed original figures demonstrated in the experiments can be accessed at https://rb.gy/6adtk4.

Supplementary information

Supplementary data are available at Bioinformatics online.

Structural basis for cooperativity of human monoclonal antibodies to meningococcal factor H-binding protein

Monoclonal antibody (mAb) cooperativity is a phenomenon triggered when mAbs couples promote increased bactericidal killing compared to individual partners. Cooperativity has been deeply investigated among mAbs elicited by factor H-binding protein (fHbp), a Neisseria meningitidis surface-exposed lipoprotein and one of the key antigens included in both serogroup B meningococcus vaccine Bexsero and Trumenba. Here we report the structural and functional characterization of two cooperative mAbs pairs isolated from Bexsero vaccines. The 3D electron microscopy structures of the human mAb-fHbp-mAb cooperative complexes indicate that the angle formed between the antigen binding fragments (fAbs) assume regular angle and that fHbp is able to bind simultaneously and stably the cooperative mAbs pairs and human factor H (fH) in vitro. These findings shed light on molecular basis of the antibody-based mechanism of protection driven by simultaneous recognition of the different epitopes of the fHbp and underline that cooperativity is crucial in vaccine efficacy.

Advances in image processing for single-particle analysis by electron cryomicroscopy and challenges ahead

Electron cryomicroscopy (cryoEM) is essential for the study and functional understanding of non-crystalline macromolecules such as proteins. These molecules cannot be imaged using X-ray crystallography or other popular methods. CryoEM has been successfully used to visualize macromolecular complexes such as ribosomes, viruses, and ion channels. Determination of structural models of these at various conformational states leads to insight on how these molecules function. Recent advances in imaging technology have given cryoEM a scientific rebirth. As a result of these technological advances image processing and analysis have yielded molecular structures at atomic resolution. Nevertheless there continue to be challenges in image processing, and in this article we will touch on the most essential in order to derive an accurate three-dimensional model from noisy projection images. Traditional approaches, such as k-means clustering for class averaging, will be provided as background. We will then highlight new approaches for each image processing subproblem, including a 3D reconstruction method for asymmetric molecules using just two projection images and deep learning algorithms for automated particle picking.