Project description:Finding the 3D structure of proteins and their complexes has several applications, such as developing vaccines that target viral proteins effectively. Methods such as cryogenic electron microscopy (cryo-EM) have improved in their ability to capture high-resolution images, and when applied to a purified sample containing copies of a macromolecule, they can be used to produce a high-quality snapshot of different 2D orientations of the macromolecule, which can be combined to reconstruct its 3D structure. Instead of purifying a sample so that it contains only one macromolecule, a process that can be difficult, time-consuming, and expensive, a cell sample containing multiple particles can be photographed directly and separated into its constituent particles using computational methods. Previous work, SLICEM, has separated 2D projection images of different particles into their respective groups using 2 methods, clustering a graph with edges weighted by pairwise similarities of common lines of the 2D projections. In this work, we develop DeepSLICEM, a pipeline that clusters rich representations of 2D projections, obtained by combining graphical features from a similarity graph based on common lines, with additional image features extracted from a convolutional neural network. DeepSLICEM explores 6 pretrained convolutional neural networks and one supervised Siamese CNN for image representation, 10 pretrained deep graph neural networks for similarity graph node representations, and 4 methods for clustering, along with 8 methods for directly clustering the similarity graph. On 6 synthetic and experimental datasets, the DeepSLICEM pipeline finds 92 method combinations achieving better clustering accuracy than previous methods from SLICEM. Thus, in this paper, we demonstrate that deep neural networks have great potential for accurately separating mixtures of 2D projections of different macromolecules computationally.
Project description:Cryo-electron microscopy reconstruction methods are uniquely able to reveal structures of many important macromolecules and macromolecular complexes. EMDataBank.org, a joint effort of the Protein Data Bank in Europe (PDBe), the Research Collaboratory for Structural Bioinformatics (RCSB) and the National Center for Macromolecular Imaging (NCMI), is a global 'one-stop shop' resource for deposition and retrieval of cryoEM maps, models and associated metadata. The resource unifies public access to the two major archives containing EM-based structural data: EM Data Bank (EMDB) and Protein Data Bank (PDB), and facilitates use of EM structural data of macromolecules and macromolecular complexes by the wider scientific community.
Project description:The growing body of work in the epidemiology literature focused on G-computation includes theoretical explanations of the method but very few simulations or examples of application. The small number of G-computation analyses in the epidemiology literature relative to other causal inference approaches may be partially due to a lack of didactic explanations of the method targeted toward an epidemiology audience. The authors provide a step-by-step demonstration of G-computation that is intended to familiarize the reader with this procedure. The authors simulate a data set and then demonstrate both G-computation and traditional regression to draw connections and illustrate contrasts between their implementation and interpretation relative to the truth of the simulation protocol. A marginal structural model is used for effect estimation in the G-computation example. The authors conclude by answering a series of questions to emphasize the key characteristics of causal inference techniques and the G-computation procedure in particular.
Project description:In January 2020, a workshop was held at EMBL-EBI (Hinxton, UK) to discuss data requirements for deposition and validation of cryoEM structures, with a focus on single-particle analysis. The meeting was attended by 47 experts in data processing, model building and refinement, validation, and archiving of such structures. This report describes the workshop's motivation and history, the topics discussed, and consensus recommendations resulting from the workshop. Some challenges for future methods-development efforts in this area are also highlighted, as is the implementation to date of some of the recommendations.
Project description:In January 2020, a workshop was held at EMBL-EBI (Hinxton, UK) to discuss data requirements for the deposition and validation of cryoEM structures, with a focus on single-particle analysis. The meeting was attended by 47 experts in data processing, model building and refinement, validation, and archiving of such structures. This report describes the workshop's motivation and history, the topics discussed, and the resulting consensus recommendations. Some challenges for future methods-development efforts in this area are also highlighted, as is the implementation to date of some of the recommendations.
Project description:With larger, higher speed detectors and improved automation, individual CryoEM instruments are capable of producing a prodigious amount of data each day, which must then be stored, processed and archived. While it has become routine to use lossless compression on raw counting-mode movies, the averages which result after correcting these movies no longer compress well. These averages could be considered sufficient for long term archival, yet they are conventionally stored with 32 bits of precision, despite high noise levels. Derived images are similarly stored with excess precision, providing an opportunity to decrease project sizes and improve processing speed. We present a simple argument based on propagation of uncertainty for safe bit truncation of flat-fielded images combined with lossless compression. The same method can be used for most derived images throughout the processing pipeline. We test the proposed strategy on two standard, data-limited CryoEM data sets, demonstrating that these limits are safe for real-world use. We find that 5 bits of precision is sufficient for virtually any raw CryoEM data and that 8-12 bits is sufficient for intermediate averages or final 3-D structures. Additionally, we detail and recommend specific rules for discretization of data as well as a practical compressed data representation that is tuned to the specific needs of CryoEM.
Project description:BackgroundLow-density lipoprotein (LDL) particles, the major carriers of cholesterol in the human circulation, have a key role in cholesterol physiology and in the development of atherosclerosis. The most prominent structural components in LDL are the core-forming cholesteryl esters (CE) and the particle-encircling single copy of a huge, non-exchangeable protein, the apolipoprotein B-100 (apoB-100). The shape of native LDL particles and the conformation of native apoB-100 on the particles remain incompletely characterized at the physiological human body temperature (37 °C).Methodology/principal findingsTo study native LDL particles, we applied cryo-electron microscopy to calculate 3D reconstructions of LDL particles in their hydrated state. Images of the particles vitrified at 6 °C and 37 °C resulted in reconstructions at ~16 Å resolution at both temperatures. 3D variance map analysis revealed rigid and flexible domains of lipids and apoB-100 at both temperatures. The reconstructions showed less variability at 6 °C than at 37 °C, which reflected increased order of the core CE molecules, rather than decreased mobility of the apoB-100. Compact molecular packing of the core and order in a lipid-binding domain of apoB-100 were observed at 6 °C, but not at 37 °C. At 37 °C we were able to highlight features in the LDL particles that are not clearly separable in 3D maps at 6 °C. Segmentation of apoB-100 density, fitting of lipovitellin X-ray structure, and antibody mapping, jointly revealed the approximate locations of the individual domains of apoB-100 on the surface of native LDL particles.Conclusions/significanceOur study provides molecular background for further understanding of the link between structure and function of native LDL particles at physiological body temperature.
Project description:Sweet potato feathery mottle virus (SPFMV) and Sweet potato mild mottle virus (SPMMV) are members of the genera Potyvirus and Ipomovirus, family Potyviridae, sharing Ipomoea batatas as common host, but transmitted, respectively, by aphids and whiteflies. Virions of family members consist of flexuous rods with multiple copies of a single coat protein (CP) surrounding the RNA genome. Here we report the generation of virus-like particles (VLPs) by transient expression of the CPs of SPFMV and SPMMV in the presence of a replicating RNA in Nicotiana benthamiana. Analysis of the purified VLPs by cryo-electron microscopy, gave structures with resolutions of 2.6 and 3.0 Å, respectively, showing a similar left-handed helical arrangement of 8.8 CP subunits per turn with the C-terminus at the inner surface and a binding pocket for the encapsidated ssRNA. Despite their similar architecture, thermal stability studies reveal that SPMMV VLPs are more stable than those of SPFMV.
Project description:Black carbon (BC) plays an important role in climate and health sciences. Using the combination of a year real-time BC observation (photoacoustic extinctiometer) and data for PM2.5 and selected co-pollutants, we herein show that annual BC Mass concentration has a bi-modal distribution, in a cold-climate city of Montreal. In addition to the summer peak, a winter BC peak was observed (up to 0.433 μg/m3), lasting over 3 months. A comparative study between two air pollution hotspots, downtown and Montreal international airport indicated that airborne average BC Mass concentration in downtown was 0.344 μg/m3, whereas in the residential areas around Montreal airport BC Mass values were over 400% higher (1.487 μg/m3). During the numerous snowfall events, airborne BC Mass concentration decreased. High-resolution scanning/transmission electron microscopy with energy dispersive X-ray spectroscopy analysis of the snow samples provided evidence that airborne BC particles or carbon nanomaterials were indeed transferred from polluted air to snow. During the COVID-19 lockdown, the BC concentration and selected co-pollutants, decreased up to 72%, confirming the predominance of anthropogenic activities in BC emission. This first cold-climate BC data set can be essential for more accurate air quality and climate modeling. About one-third of the Earth's land surface receive snow annually, the impact of this study on air quality, health and climate change is discussed.