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.

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.

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.

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.

Small molecules enhance the potency of natural antimicrobial peptides.

The skin-associated microbiome plays an important role in general well-being and in a variety of treatable skin conditions. In this regard, endogenous antimicrobial peptides have both a direct and indirect role in determining the composition of the microbiota. We demonstrate here that certain small molecular species can amplify the antimicrobial potency of naturally occurring antimicrobial peptides. In this study, we have used niacinamide, a form of vitamin B3 naturally found in foods and widely used in cosmetic skincare products, and two of its structural analogs, to investigate their cooperativity with the human antimicrobial peptide LL37 on the bacterium Staphylococcus aureus. We observed a clear synergistic effect of niacinamide and, to some extent, N-methylnicotinamide, whereas isonicotinamide showed no significant cooperativity with LL37. Adaptively biased molecular dynamics simulations using simplified model membrane substrates and single peptides revealed that these molecules partition into the headgroup region of an anionic bilayer used to mimic the bacterial membrane. The simulated effects on the physical properties of the simulated model membrane are well correlated with experimental activity observed in real biological assays despite the simplicity of the model. In contrast, these molecules have little effect on zwitterionic bilayers that mimic a mammalian membrane. We conclude that niacinamide and N-methylnicotinamide can therefore potentiate the activity of host peptides by modulating the physical properties of the bacterial membrane, and to a lesser extent through direct interactions with the peptide. The level of cooperativity is strongly dependent on the detailed chemistry of the additive, suggesting an opportunity to fine-tune the behavior of host peptides.

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.

Explainable AI reveals changes in skin microbiome composition linked to phenotypic differences.

Alterations in the human microbiome have been observed in a variety of conditions such as asthma, gingivitis, dermatitis and cancer, and much remains to be learned about the links between the microbiome and human health. The fusion of artificial intelligence with rich microbiome datasets can offer an improved understanding of the microbiome's role in human health. To gain actionable insights it is essential to consider both the predictive power and the transparency of the models by providing explanations for the predictions. We combine the collection of leg skin microbiome samples from two healthy cohorts of women with the application of an explainable artificial intelligence (EAI) approach that provides accurate predictions of phenotypes with explanations. The explanations are expressed in terms of variations in the relative abundance of key microbes that drive the predictions. We predict skin hydration, subject's age, pre/post-menopausal status and smoking status from the leg skin microbiome. The changes in microbial composition linked to skin hydration can accelerate the development of personalized treatments for healthy skin, while those associated with age may offer insights into the skin aging process. The leg microbiome signatures associated with smoking and menopausal status are consistent with previous findings from oral/respiratory tract microbiomes and vaginal/gut microbiomes respectively. This suggests that easily accessible microbiome samples could be used to investigate health-related phenotypes, offering potential for non-invasive diagnosis and condition monitoring. Our EAI approach sets the stage for new work focused on understanding the complex relationships between microbial communities and phenotypes. Our approach can be applied to predict any condition from microbiome samples and has the potential to accelerate the development of microbiome-based personalized therapeutics and non-invasive diagnostics.

Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge.

This paper describes outcomes of the 2019 Cryo-EM Model Challenge. The goals were to (1) assess the quality of models that can be produced from cryogenic electron microscopy (cryo-EM) maps using current modeling software, (2) evaluate reproducibility of modeling results from different software developers and users and (3) compare performance of current metrics used for model evaluation, particularly Fit-to-Map metrics, with focus on near-atomic resolution. Our findings demonstrate the relatively high accuracy and reproducibility of cryo-EM models derived by 13 participating teams from four benchmark maps, including three forming a resolution series (1.8 to 3.1 Å). The results permit specific recommendations to be made about validating near-atomic cryo-EM structures both in the context of individual experiments and structure data archives such as the Protein Data Bank. We recommend the adoption of multiple scoring parameters to provide full and objective annotation and assessment of the model, reflective of the observed cryo-EM map density.

Comparing Cryo-EM Reconstructions and Validating Atomic Model Fit Using Difference Maps.

Cryogenic electron microscopy (cryo-EM) is a powerful technique for determining structures of multiple conformational or compositional states of macromolecular assemblies involved in cellular processes. Recent technological developments have led to a leap in the resolution of many cryo-EM data sets, making atomic model building more common for data interpretation. We present a method for calculating differences between two cryo-EM maps or a map and a fitted atomic model. The proposed approach works by scaling the maps using amplitude matching in resolution shells. To account for variability in local resolution of cryo-EM data, we include a procedure for local amplitude scaling that enables appropriate scaling of local map contrast. The approach is implemented as a user-friendly tool in the CCP-EM software package. To obtain clean and interpretable differences, we propose a protocol involving steps to process the input maps and output differences. We demonstrate the utility of the method for identifying conformational and compositional differences including ligands. We also highlight the use of difference maps for evaluating atomic model fit in cryo-EM maps.

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.

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 ).

West-Life: A Virtual Research Environment for structural biology.

The West-Life project (https://about.west-life.eu/) is a Horizon 2020 project funded by the European Commission to provide data processing and data management services for the international community of structural biologists, and in particular to support integrative experimental approaches within the field of structural biology. It has developed enhancements to existing web services for structure solution and analysis, created new pipelines to link these services into more complex higher-level workflows, and added new data management facilities. Through this work it has striven to make the benefits of European e-Infrastructures more accessible to life-science researchers in general and structural biologists in particular.

Author Correction: Tuneable poration: host defense peptides as sequence probes for antimicrobial mechanisms.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Tuneable poration: host defense peptides as sequence probes for antimicrobial mechanisms.

The spread of antimicrobial resistance stimulates discovery strategies that place emphasis on mechanisms circumventing the drawbacks of traditional antibiotics and on agents that hit multiple targets. Host defense peptides (HDPs) are promising candidates in this regard. Here we demonstrate that a given HDP sequence intrinsically encodes for tuneable mechanisms of membrane disruption. Using an archetypal HDP (cecropin B) we show that subtle structural alterations convert antimicrobial mechanisms from native carpet-like scenarios to poration and non-porating membrane exfoliation. Such distinct mechanisms, studied using low- and high-resolution spectroscopy, nanoscale imaging and molecular dynamics simulations, all maintain strong antimicrobial effects, albeit with diminished activity against pathogens resistant to HDPs. The strategy offers an effective search paradigm for the sequence probing of discrete antimicrobial mechanisms within a single HDP.

Accelerating molecular discovery through data and physical sciences: Applications to peptide-membrane interactions.

Simulation and data analysis have evolved into powerful methods for discovering and understanding molecular modes of action and designing new compounds to exploit these modes. The combination provides a strong impetus to create and exploit new tools and techniques at the interfaces between physics, biology, and data science as a pathway to new scientific insight and accelerated discovery. In this context, we explore the rational design of novel antimicrobial peptides (short protein sequences exhibiting broad activity against multiple species of bacteria). We show how datasets can be harvested to reveal features which inform new design concepts. We introduce new analysis and visualization tools: a graphical representation of the k-mer spectrum as a fundamental property encoded in antimicrobial peptide databases and a data-driven representation to illustrate membrane binding and permeation of helical peptides.

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.

Cooperative Modes of Action of Antimicrobial Peptides Characterized with Atomistic Simulations: A Study on Cecropin B.

Antimicrobial peptides (AMPs) are widely occurring host defense agents of interest as one route for addressing the growing problem of multidrug-resistant pathogens. Understanding the mechanisms behind their antipathogen activity is instrumental in designing new AMPs. Herein, we present an all-atom molecular dynamics and free energy study on cecropin B (CB) and its constituent domains. We find a cooperative mechanism in which CB inserts into an anionic model membrane with its amphipathic N-terminal segment, supported by the hydrophobic C-terminal segment of a second peptide. The two peptides interact via a Glu···Lys salt bridge and together sustain a pore in the membrane. Using a modified membrane composition, we demonstrate that when the lower leaflet is overall neutral, insertion of the cationic segment is retarded and thus this mode of action is membrane specific. The observed mode of action utilizes a flexible hinge, a common structural motif among AMPs, which allows CB to insert into the membrane using either or both termini. Data from both unbiased trajectories and enhanced sampling simulations indicate that a requirement for CB to be an effective AMP is the interaction of its hydrophobic C-terminal segment with the membrane. Simulations of these segments in isolation reveal their aggregation in the membrane and a different mechanism of supporting pore formation. Together, our results show the complex interaction of different structural motifs of AMPs and, in particular, a potential role for electronegative side chains in an overall cationic AMP.

Recent developments in MrBUMP: better search-model preparation, graphical interaction with search models, and solution improvement and assessment.

Increasing sophistication in molecular-replacement (MR) software and the rapid expansion of the PDB in recent years have allowed the technique to become the dominant method for determining the phases of a target structure in macromolecular X-ray crystallography. In addition, improvements in bioinformatic techniques for finding suitable homologous structures for use as MR search models, combined with developments in refinement and model-building techniques, have pushed the applicability of MR to lower sequence identities and made weak MR solutions more amenable to refinement and improvement. MrBUMP is a CCP4 pipeline which automates all stages of the MR procedure. Its scope covers everything from the sourcing and preparation of suitable search models right through to rebuilding of the positioned search model. Recent improvements to the pipeline include the adoption of more sensitive bioinformatic tools for sourcing search models, enhanced model-preparation techniques including better ensembling of homologues, and the use of phase improvement and model building on the resulting solution. The pipeline has also been deployed as an online service through CCP4 online, which allows its users to exploit large bioinformatic databases and coarse-grained parallelism to speed up the determination of a possible solution. Finally, the molecular-graphics application CCP4mg has been combined with MrBUMP to provide an interactive visual aid to the user during the process of selecting and manipulating search models for use in MR. Here, these developments in MrBUMP are described with a case study to explore how some of the enhancements to the pipeline and to CCP4mg can help to solve a difficult case.