Overview and applications of map and model validation tools in the CCP-EM software suite.

Cryogenic electron microscopy (cryo-EM) has recently been established as a powerful technique for solving macromolecular structures. Although the best resolutions achievable are improving, a significant majority of data are still resolved at resolutions worse than 3 Å, where it is non-trivial to build or fit atomic models. The map reconstructions and atomic models derived from the maps are also prone to errors accumulated through the different stages of data processing. Here, we highlight the need to evaluate both model geometry and fit to data at different resolutions. Assessment of cryo-EM structures from SARS-CoV-2 highlights a bias towards optimising the model geometry to agree with the most common conformations, compared to the agreement with data. We present the CoVal web service which provides multiple validation metrics to reflect the quality of atomic models derived from cryo-EM data of structures from SARS-CoV-2. We demonstrate that further refinement can lead to improvement of the agreement with data without the loss of geometric quality. We also discuss the recent CCP-EM developments aimed at addressing some of the current shortcomings.

Indexed variation graphs for efficient and accurate resistome profiling.

Motivation: Antimicrobial resistance (AMR) remains a major threat to global health. Profiling the collective AMR genes within a metagenome (the 'resistome') facilitates greater understanding of AMR gene diversity and dynamics. In turn, this can allow for gene surveillance, individualized treatment of bacterial infections and more sustainable use of antimicrobials. However, resistome profiling can be complicated by high similarity between reference genes, as well as the sheer volume of sequencing data and the complexity of analysis workflows. We have developed an efficient and accurate method for resistome profiling that addresses these complications and improves upon currently available tools. Results: Our method combines a variation graph representation of gene sets with a locality-sensitive hashing Forest indexing scheme to allow for fast classification of metagenomic sequence reads using similarity-search queries. Subsequent hierarchical local alignment of classified reads against graph traversals enables accurate reconstruction of full-length gene sequences using a scoring scheme. We provide our implementation, graphing Resistance Out Of meTagenomes (GROOT), and show it to be both faster and more accurate than a current reference-dependent tool for resistome profiling. GROOT runs on a laptop and can process a typical 2 gigabyte metagenome in 2 min using a single CPU. Our method is not restricted to resistome profiling and has the potential to improve current metagenomic workflows. Availability and implementation: GROOT is written in Go and is available at https://github.com/will-rowe/groot (MIT license). Supplementary information: Supplementary data are available at Bioinformatics online.

Modulation of Antimicrobial Peptide Potency in Stressed Lipid Bilayers.

It is shown that the tendency of an archetypal antimicrobial peptide to insert into and perforate a simple lipid bilayer is strongly modulated by tensile stress in the membrane. The results, obtained through molecular dynamics simulations, have been demonstrated with several lipid compositions and appear to be general, although quantitative details differ. The findings imply that the potency of antimicrobial peptides may not be a purely intrinsic chemical property and, instead, depends on the mechanical state of the target membrane.

K-mer clustering algorithm using a MapReduce framework: application to the parallelization of the Inchworm module of Trinity.

BACKGROUND: De novo transcriptome assembly is an important technique for understanding gene expression in non-model organisms. Many de novo assemblers using the de Bruijn graph of a set of the RNA sequences rely on in-memory representation of this graph. However, current methods analyse the complete set of read-derived k-mer sequence at once, resulting in the need for computer hardware with large shared memory. RESULTS: We introduce a novel approach that clusters k-mers as the first step. The clusters correspond to small sets of gene products, which can be processed quickly to give candidate transcripts. We implement the clustering step using the MapReduce approach for parallelising the analysis of large datasets, which enables the use of compute clusters. The computational task is distributed across the compute system using the industry-standard MPI protocol, and no specialised hardware is required. Using this approach, we have re-implemented the Inchworm module from the widely used Trinity pipeline, and tested the method in the context of the full Trinity pipeline. Validation tests on a range of real datasets show large reductions in the runtime and per-node memory requirements, when making use of a compute cluster. CONCLUSIONS: Our study shows that MapReduce-based clustering has great potential for distributing challenging sequencing problems, without loss of accuracy. Although we have focussed on the Trinity package, we propose that such clustering is a useful initial step for other assembly pipelines.

Exploring the speed and performance of molecular replacement with AMPLE using QUARK ab initio protein models.

AMPLE clusters and truncates ab initio protein structure predictions, producing search models for molecular replacement. Here, an interesting degree of complementarity is shown between targets solved using the different ab initio modelling programs QUARK and ROSETTA. Search models derived from either program collectively solve almost all of the all-helical targets in the test set. Initial solutions produced by Phaser after only 5 min perform surprisingly well, improving the prospects for in situ structure solution by AMPLE during synchrotron visits. Taken together, the results show the potential for AMPLE to run more quickly and successfully solve more targets than previously suspected.

Conversion of a disulfide bond into a thioacetal group during echinomycin biosynthesis.

Echinomycin is a nonribosomal depsipeptide natural product with a range of interesting bioactivities that make it an important target for drug discovery and development. It contains a thioacetal bridge, a unique chemical motif derived from the disulfide bond of its precursor antibiotic triostin A by the action of an S-adenosyl-L-methionine-dependent methyltransferase, Ecm18. The crystal structure of Ecm18 in complex with its reaction products S-adenosyl-L-homocysteine and echinomycin was determined at 1.50 Å resolution. Phasing was achieved using a new molecular replacement package called AMPLE, which automatically derives search models from structure predictions based on ab initio protein modelling. Structural analysis indicates that a combination of proximity effects, medium effects, and catalysis by strain drives the unique transformation of the disulfide bond into the thioacetal linkage.

Community recommendations on cryoEM data archiving and validation: Outcomes of a wwPDB/EMDB workshop on cryoEM data management, deposition and validation.

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.

Community recommendations on cryoEM data archiving and validation.

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.

Ligand binding and dynamics of the monomeric epidermal growth factor receptor ectodomain.

The ectodomain of the human epidermal growth factor receptor (hEGFR) controls input to several cell signalling networks via binding with extracellular growth factors. To gain insight into the dynamics and ligand binding of the ectodomain, the hEGFR monomer was subjected to molecular dynamics simulation. The monomer was found to be substantially more flexible than the ectodomain dimer studied previously. Simulations where the endogeneous ligand EGF binds to either Subdomain I or Subdomain III, or where hEGFR is unbound, show significant differences in dynamics. The molecular mechanics Poisson-Boltzmann surface area method has been used to derive relative free energies of ligand binding, and we find that the ligand is capable of binding either subdomain with a slight preference for III. Alanine-scanning calculations for the effect of selected ligand mutants on binding reproduce the trends of affinity measurements. Taken together, these results emphasize the possible role of the ectodomain monomer in the initial step of ligand binding, and add details to the static picture obtained from crystal structures.

Application of the AMPLE cluster-and-truncate approach to NMR structures for molecular replacement.

AMPLE is a program developed for clustering and truncating ab initio protein structure predictions into search models for molecular replacement. Here, it is shown that its core cluster-and-truncate methods also work well for processing NMR ensembles into search models. Rosetta remodelling helps to extend success to NMR structures bearing low sequence identity or high structural divergence from the target protein. Potential future routes to improved performance are considered and practical, general guidelines on using AMPLE are provided.

AMPLE: a cluster-and-truncate approach to solve the crystal structures of small proteins using rapidly computed ab initio models.

Protein ab initio models predicted from sequence data alone can enable the elucidation of crystal structures by molecular replacement. However, the calculation of such ab initio models is typically computationally expensive. Here, a computational pipeline based on the clustering and truncation of cheaply obtained ab initio models for the preparation of structure ensembles is described. Clustering is used to select models and to quantitatively predict their local accuracy, allowing rational truncation of predicted inaccurate regions. The resulting ensembles, with or without rapidly added side chains, solved 43% of all test cases, with an 80% success rate for all-α proteins. A program implementing this approach, AMPLE, is included in the CCP4 suite of programs. It only requires the input of a FASTA sequence file and a diffraction data file. It carries out the modelling using locally installed Rosetta, creates search ensembles and automatically performs molecular replacement and model rebuilding.

Atomic model validation using the CCP-EM software suite.

Recently, there has been a dramatic improvement in the quality and quantity of data derived using cryogenic electron microscopy (cryo-EM). This is also associated with a large increase in the number of atomic models built. Although the best resolutions that are achievable are improving, often the local resolution is variable, and a significant majority of data are still resolved at resolutions worse than 3 Å. Model building and refinement is often challenging at these resolutions, and hence atomic model validation becomes even more crucial to identify less reliable regions of the model. Here, a graphical user interface for atomic model validation, implemented in the CCP-EM software suite, is presented. It is aimed to develop this into a platform where users can access multiple complementary validation metrics that work across a range of resolutions and obtain a summary of evaluations. Based on the validation estimates from atomic models associated with cryo-EM structures from SARS-CoV-2, it was observed that models typically favor adopting the most common conformations over fitting the observations when compared with the model agreement with data. At low resolutions, the stereochemical quality may be favored over data fit, but care should be taken to ensure that the model agrees with the data in terms of resolvable features. It is demonstrated that further re-refinement can lead to improvement of the agreement with data without the loss of geometric quality. This also highlights the need for improved resolution-dependent weight optimization in model refinement and an effective test for overfitting that would help to guide the refinement process.

Evaluating the solution from MrBUMP and BALBES.

Molecular replacement is one of the key methods used to solve the problem of determining the phases of structure factors in protein structure solution from X-ray image diffraction data. Its success rate has been steadily improving with the development of improved software methods and the increasing number of structures available in the PDB for use as search models. Despite this, in cases where there is low sequence identity between the target-structure sequence and that of its set of possible homologues it can be a difficult and time-consuming chore to isolate and prepare the best search model for molecular replacement. MrBUMP and BALBES are two recent developments from CCP4 that have been designed to automate and speed up the process of determining and preparing the best search models and putting them through molecular replacement. Their intention is to provide the user with a broad set of results using many search models and to highlight the best of these for further processing. An overview of both programs is presented along with a description of how best to use them, citing case studies and the results of large-scale testing of the software.

REFMAC5 for the refinement of macromolecular crystal structures.

This paper describes various components of the macromolecular crystallographic refinement program REFMAC5, which is distributed as part of the CCP4 suite. REFMAC5 utilizes different likelihood functions depending on the diffraction data employed (amplitudes or intensities), the presence of twinning and the availability of SAD/SIRAS experimental diffraction data. To ensure chemical and structural integrity of the refined model, REFMAC5 offers several classes of restraints and choices of model parameterization. Reliable models at resolutions at least as low as 4 Šcan be achieved thanks to low-resolution refinement tools such as secondary-structure restraints, restraints to known homologous structures, automatic global and local NCS restraints, `jelly-body' restraints and the use of novel long-range restraints on atomic displacement parameters (ADPs) based on the Kullback-Leibler divergence. REFMAC5 additionally offers TLS parameterization and, when high-resolution data are available, fast refinement of anisotropic ADPs. Refinement in the presence of twinning is performed in a fully automated fashion. REFMAC5 is a flexible and highly optimized refinement package that is ideally suited for refinement across the entire resolution spectrum encountered in macromolecular crystallography.

Overview of the CCP4 suite and current developments.

The CCP4 (Collaborative Computational Project, Number 4) software suite is a collection of programs and associated data and software libraries which can be used for macromolecular structure determination by X-ray crystallography. The suite is designed to be flexible, allowing users a number of methods of achieving their aims. The programs are from a wide variety of sources but are connected by a common infrastructure provided by standard file formats, data objects and graphical interfaces. Structure solution by macromolecular crystallography is becoming increasingly automated and the CCP4 suite includes several automation pipelines. After giving a brief description of the evolution of CCP4 over the last 30 years, an overview of the current suite is given. While detailed descriptions are given in the accompanying articles, here it is shown how the individual programs contribute to a complete software package.

Redeployment of automated MrBUMP search-model identification for map fitting in cryo-EM.

In crystallography, the phase problem can often be addressed by the careful preparation of molecular-replacement search models. This has led to the development of pipelines such as MrBUMP that can automatically identify homologous proteins from an input sequence and edit them to focus on the areas that are most conserved. Many of these approaches can be applied directly to cryo-EM to help discover, prepare and correctly place models (here called cryo-EM search models) into electrostatic potential maps. This can significantly reduce the amount of manual model building that is required for structure determination. Here, MrBUMP is repurposed to fit automatically obtained PDB-derived chains and domains into cryo-EM maps. MrBUMP was successfully able to identify and place cryo-EM search models across a range of resolutions. Methods such as map segmentation are also explored as potential routes to improved performance. Map segmentation was also found to improve the effectiveness of the pipeline for higher resolution (<8 Å) data sets.

Structural analysis of a glycoside hydrolase family 43 arabinoxylan arabinofuranohydrolase in complex with xylotetraose reveals a different binding mechanism compared with other members of the same family.

AXHs (arabinoxylan arabinofuranohydrolases) are alpha-L-arabinofuranosidases that specifically hydrolyse the glycosidic bond between arabinofuranosyl substituents and xylopyranosyl backbone residues of arabinoxylan. Bacillus subtilis was recently shown to produce an AXH that cleaves arabinose units from O-2- or O-3-mono-substituted xylose residues: BsAXH-m2,3 (B. subtilis AXH-m2,3). Crystallographic analysis reveals a two-domain structure for this enzyme: a catalytic domain displaying a five-bladed beta-propeller fold characteristic of GH (glycoside hydrolase) family 43 and a CBM (carbohydrate-binding module) with a beta-sandwich fold belonging to CBM family 6. Binding of substrate to BsAXH-m2,3 is largely based on hydrophobic stacking interactions, which probably allow the positional flexibility needed to hydrolyse both arabinose substituents at the O-2 or O-3 position of the xylose unit. Superposition of the BsAXH-m2,3 structure with known structures of the GH family 43 exo-acting enzymes, beta-xylosidase and alpha-L-arabinanase, each in complex with their substrate, reveals a different orientation of the sugar backbone.

Ectodomain orientation, conformational plasticity and oligomerization of ErbB1 receptors investigated by molecular dynamics.

Epidermal growth factor receptor (EGFR; ErbB1, HER1 in humans) is a receptor tyrosine kinase triggering signals across the plasma membranes of cells to determine cell fate. We have used molecular dynamics simulations to investigate structural models of ErbB1 ectodomains. We show that, with minor rearrangements, the ErbB1 back-to-back dimer can align almost flat on the cell membrane. This is in contrast to the traditional picture of ErbB1 dimers standing proud of the membrane, but in line with recent FRET and EM experiments. Interaction with the membrane leads to conformational changes in the dimer, which further stabilize the back-to-back interface. On the membrane, two dimers can associate forming a tetramer. This is enabled by a head-to-head interface, involving the ligand binding side of the ectodomain, and which significantly enhances ligand binding. A weak head-to-head interface has been seen in crystal structures, but is found to stabilise appreciably in our simulation. We also find that the domains IV, connecting the receptor to the membrane, weakly interact with each other. These simulations illustrate some of the flexibility of the ErbB1 ectodomains, and may help to explain recent experimental results.

Streaming histogram sketching for rapid microbiome analytics.

BACKGROUND: The growth in publically available microbiome data in recent years has yielded an invaluable resource for genomic research, allowing for the design of new studies, augmentation of novel datasets and reanalysis of published works. This vast amount of microbiome data, as well as the widespread proliferation of microbiome research and the looming era of clinical metagenomics, means there is an urgent need to develop analytics that can process huge amounts of data in a short amount of time. To address this need, we propose a new method for tyrhe compact representation of microbiome sequencing data using similarity-preserving sketches of streaming k-mer spectra. These sketches allow for dissimilarity estimation, rapid microbiome catalogue searching and classification of microbiome samples in near real time. RESULTS: We apply streaming histogram sketching to microbiome samples as a form of dimensionality reduction, creating a compressed 'histosketch' that can efficiently represent microbiome k-mer spectra. Using public microbiome datasets, we show that histosketches can be clustered by sample type using the pairwise Jaccard similarity estimation, consequently allowing for rapid microbiome similarity searches via a locality sensitive hashing indexing scheme. Furthermore, we use a 'real life' example to show that histosketches can train machine learning classifiers to accurately label microbiome samples. Specifically, using a collection of 108 novel microbiome samples from a cohort of premature neonates, we trained and tested a random forest classifier that could accurately predict whether the neonate had received antibiotic treatment (97% accuracy, 96% precision) and could subsequently be used to classify microbiome data streams in less than 3 s. CONCLUSIONS: Our method offers a new approach to rapidly process microbiome data streams, allowing samples to be rapidly clustered, indexed and classified. We also provide our implementation, Histosketching Using Little K-mers (HULK), which can histosketch a typical 2 GB microbiome in 50 s on a standard laptop using four cores, with the sketch occupying 3000 bytes of disk space. ( https://github.com/will-rowe/hulk ).

Single-molecule imaging and fluorescence lifetime imaging microscopy show different structures for high- and low-affinity epidermal growth factor receptors in A431 cells.

Epidermal growth factor (EGF) receptor (EGFR) modulates mitosis and apoptosis through signaling by its high-affinity (HA) and low-affinity (LA) EGF-binding states. The prevailing model of EGFR activation-derived from x-ray crystallography-involves the transition from tethered ectodomain monomers to extended back-to-back dimers and cannot explain these EGFR affinities or their different functions. Here, we use single-molecule Förster resonant energy transfer analysis in combination with ensemble fluorescence lifetime imaging microscopy to investigate the three-dimensional architecture of HA and LA EGFR-EGF complexes in cells by measuring the inter-EGF distances within discrete EGF pairs and the vertical distance from EGF to the plasma membrane. Our results show that EGFR ectodomains form interfaces resulting in two inter-EGF distances ( approximately 8 nm and < 5.5 nm), different from the back-to-back EGFR ectodomain interface ( approximately 11 nm). Distance measurements from EGF to the plasma membrane show that HA EGFR ectodomains are oriented flat on the membrane, whereas LA ectodomains stand proud from it. Their flat orientation confers on HA EGFR ectodomains the exclusive ability to interact via asymmetric interfaces, head-to-head with respect to the EGF-binding site, whereas LA EGFRs must interact only side-by-side. Our results support a structural model in which asymmetric EGFR head-to-head interfaces may be relevant for HA EGFR oligomerization.