Glass reinforced plastic (GRP) boats and the impact on coastal environment - Evidence of fibreglass ingestion by marine bivalves from natural populations.

Classified as marine debris, man made materials are polluting the world's oceans. Recently, glass reinforced plastic (GRP) has been shown to degrade and contaminate the coasts. In this pioneering study, fibreglass particles have been detected in the soft parts of oysters and mussels collected from natural populations, in front of an active boatyard. The presence of particulate glass, with concentrations up to 11,220 particles/kg ww in Ostrea edulis and 2740 particles/kg ww in Mytilus edulis, was confirmed by micro Raman spectroscopy. The results showed higher accumulation during the winter months, when boat maintenance activities are peaking and, through repair work, the release of glass fibres in the environment is more likely. Bivalves are considered high risk species due to their sessile nature and extensive filter feeding behaviour. The microparticle inclusion may contribute to adverse impacts on physiological processes and eventually to a decline in the overall health and subsequent death of the animal. The high costs involved in the proper GRP disposal and the lack of recycling facilities worldwide lead to boat abandonement and further contamination of the coasts. For the first time this study presents the extensive fibreglass contamination of natural bivalve populations, in a popular South England sailing harbour, designated a biological and geological site of specific scientific interest (SSRI).

The Planemo toolkit for developing, deploying, and executing scientific data analyses in Galaxy and beyond.

There are thousands of well-maintained high-quality open-source software utilities for all aspects of scientific data analysis. For more than a decade, the Galaxy Project has been providing computational infrastructure and a unified user interface for these tools to make them accessible to a wide range of researchers. To streamline the process of integrating tools and constructing workflows as much as possible, we have developed Planemo, a software development kit for tool and workflow developers and Galaxy power users. Here we outline Planemo's implementation and describe its broad range of functionality for designing, testing, and executing Galaxy tools, workflows, and training material. In addition, we discuss the philosophy underlying Galaxy tool and workflow development, and how Planemo encourages the use of development best practices, such as test-driven development, by its users, including those who are not professional software developers.

Ligand Unbinding Pathway and Mechanism Analysis Assisted by Machine Learning and Graph Methods.

We present two methods to reveal protein-ligand unbinding mechanisms in biased unbinding simulations by clustering trajectories into ensembles representing unbinding paths. The first approach is based on a contact principal component analysis for reducing the dimensionality of the input data, followed by identification of unbinding paths and training a machine learning model for trajectory clustering. The second approach clusters trajectories according to their pairwise mean Euclidean distance employing the neighbor-net algorithm, which takes into account input data bias in the distances set and is superior to dendrogram construction. Finally, we describe a more complex case where the reaction coordinate relevant for path identification is a single intraligand hydrogen bond, highlighting the challenges involved in unbinding path reaction coordinate detection.

Galaxy workflows for fragment-based virtual screening: a case study on the SARS-CoV-2 main protease.

We present several workflows for protein-ligand docking and free energy calculation for use in the workflow management system Galaxy. The workflows are composed of several widely used open-source tools, including rDock and GROMACS, and can be executed on public infrastructure using either Galaxy's graphical interface or the command line. We demonstrate the utility of the workflows by running a high-throughput virtual screening of around 50000 compounds against the SARS-CoV-2 main protease, a system which has been the subject of intense study in the last year.

Galaxy-ML: An accessible, reproducible, and scalable machine learning toolkit for biomedicine.

Supervised machine learning is an essential but difficult to use approach in biomedical data analysis. The Galaxy-ML toolkit (https://galaxyproject.org/community/machine-learning/) makes supervised machine learning more accessible to biomedical scientists by enabling them to perform end-to-end reproducible machine learning analyses at large scale using only a web browser. Galaxy-ML extends Galaxy (https://galaxyproject.org), a biomedical computational workbench used by tens of thousands of scientists across the world, with a suite of tools for all aspects of supervised machine learning.

Observation of microstructure evolution during inertia friction welding using in-situ synchrotron X-ray diffraction.

The widespread use and development of inertia friction welding is currently restricted by an incomplete understanding of the deformation mechanisms and microstructure evolution during the process. Understanding phase transformations and lattice strains during inertia friction welding is essential for the development of robust numerical models capable of determining optimized process parameters and reducing the requirement for costly experimental trials. A unique compact rig has been designed and used in-situ with a high-speed synchrotron X-ray diffraction instrument to investigate the microstructure evolution during inertia friction welding of a high-carbon steel (BS1407). At the contact interface, the transformation from ferrite to austenite was captured in great detail, allowing for analysis of the phase fractions during the process. Measurement of the thermal response of the weld reveals that the transformation to austenite occurs 230 °C below the equilibrium start temperature of 725 °C. It is concluded that the localization of large strains around the contact interface produced as the specimens deform assists this non-equilibrium phase transformation.

Freely accessible ready to use global infrastructure for SARS-CoV-2 monitoring.

The COVID-19 pandemic is the first global health crisis to occur in the age of big genomic data.Although data generation capacity is well established and sufficiently standardized, analytical capacity is not. To establish analytical capacity it is necessary to pull together global computational resources and deliver the best open source tools and analysis workflows within a ready to use, universally accessible resource. Such a resource should not be controlled by a single research group, institution, or country. Instead it should be maintained by a community of users and developers who ensure that the system remains operational and populated with current tools. A community is also essential for facilitating the types of discourse needed to establish best analytical practices. Bringing together public computational research infrastructure from the USA, Europe, and Australia, we developed a distributed data analysis platform that accomplishes these goals. It is immediately accessible to anyone in the world and is designed for the analysis of rapidly growing collections of deep sequencing datasets. We demonstrate its utility by detecting allelic variants in high-quality existing SARS-CoV-2 sequencing datasets and by continuous reanalysis of COG-UK data. All workflows, data, and documentation is available at https://covid19.galaxyproject.org .

Data on elemental concentrations in marine sediments from the South and South West of England.

The present Data In Brief methodological paper details the acquisition, mining and pre-processing of elemental concentration data in marine sediments (coastal and open sea) of Southern England, presented and discussed in the co-submitted Environment International paper entitled: "Three decades of trace element sediment contamination: the mining of governmental databases and the need to address hidden sources for clean and healthy seas" [1]. Elemental sediment concentration data were obtained from the two main UK environmental sources, i.e. the Environment Agency (EA) and the Marine Environment Monitoring and Assessment National (MERMAN) database managed by the British Oceanographic Data Centre (BODC). The merged database is the result of a rigorous data selection-validation process and provides spatially and temporally extensive records of arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), iron (Fe), mercury (Hg), nickel (Ni), lead (Pb) and zinc (Zn) concentrations for hundreds of sites over 31 years (1983-2013). Additional records of manganese (Mn), aluminium (Al), lithium (Li), tin (Sn) [and tributyltin (TBT)], barium (Ba), antimony (Sb), boron (B), calcium (Ca), molybdenum (Mo), cobalt (Co), selenium (Se), potassium (K), magnesium (Mg), beryllium (Be), vanadium (V), titanium (Ti), sodium (Na), silver (Ag), thallium (Tl) and strontium (Sr) are also included. The full secondary database is hosted in the Mendeley Data repository and the geo-spatial information to map sites is given in supplementary files to the paper. To provide end-users with the relevant context on spatial and temporal coverage, monitoring statistics are given for the nine trace elements (TEs). Site-specific statistics include: the first and last year of sediment monitoring, the number of years monitored, and minimum, maximum, mean and median numbers of years monitored. Also given are summary data on the number of sites monitored each year, from the first records from 1983 to 2013. For the nine TEs (total and strong acid digestion techniques are considered separately for Cr and Fe), monitoring statistics are presented separately for coastal and open sea sites. Data are relevant to diverse end-users to assess the local and regional contaminant loads and to contextualize anthropogenic threats to benthic systems in multiple locations from the French/English Channel, southern North and Celtic Seas.

Three decades of trace element sediment contamination: The mining of governmental databases and the need to address hidden sources for clean and healthy seas.

Trace elements (TEs) frequently contaminate coastal marine sediments with many included in priority chemical lists or control legislation. These, improved waste treatment and increased recycling have fostered the belief that TE pollution is declining. Nevertheless, there is a paucity of long-term robust datasets to support this confidence. By mining UK datasets (100s of sites, 31 years), we assess sediment concentrations of arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), iron (Fe), mercury (Hg), nickel (Ni), lead (Pb) and zinc (Zn) and use indices (PI [Pollution], TEPI [Trace Element Pollution] and Igeo [Geoaccumulation]) to assess TE pollution evolution. PI and TEPI show reductions of overall TE pollution in the 1980s then incremental improvements followed by a distinct increase (2010-13). Zn, As and Pb Igeo scores show low pollution, whilst Cd and Hg are moderate, but with all remaining temporally stable. Igeo scores are low for Ni, Fe and Cr, but increasing for Ni and Fe. A moderate pollution Igeo score for Cu has also steadily increased since the mid-1990s. Increasing site trends are not universal and, conversely, minimal temporal change masks some site-specific increases and decreases. To capture this variability we strongly advocate embedding sufficient sentinel sites within observation networks. Decreasing sediment pollution levels (e.g. Pb and Hg) have been achieved, but stabilizing Igeo and recently increasing TEPI and PI scores require continued global vigilance. Increasing Ni and Fe Igeo scores necessitate source identification, but this is a priority for Cu. Local, regional and world analyses indicate substantial 'hidden' inputs from anti-fouling paints (Cu, Zn), ship scrubbers (Cu, Zn, Ni) and sacrificial anodes (Zn) that are also predicted to increase markedly. Accurate TE input assessments and targeted legislation are, therefore, urgently required, especially in the context of rapid blue economic growth (e.g. shipping).

Multisecond ligand dissociation dynamics from atomistic simulations.

Coarse-graining of fully atomistic molecular dynamics simulations is a long-standing goal in order to allow the description of processes occurring on biologically relevant timescales. For example, the prediction of pathways, rates and rate-limiting steps in protein-ligand unbinding is crucial for modern drug discovery. To achieve the enhanced sampling, we perform dissipation-corrected targeted molecular dynamics simulations, which yield free energy and friction profiles of molecular processes under consideration. Subsequently, we use these fields to perform temperature-boosted Langevin simulations which account for the desired kinetics occurring on multisecond timescales and beyond. Adopting the dissociation of solvated sodium chloride, trypsin-benzamidine and Hsp90-inhibitor protein-ligand complexes as test problems, we reproduce rates from molecular dynamics simulation and experiments within a factor of 2-20, and dissociation constants within a factor of 1-4. Analysis of friction profiles reveals that binding and unbinding dynamics are mediated by changes of the surrounding hydration shells in all investigated systems.

The ChemicalToolbox: reproducible, user-friendly cheminformatics analysis on the Galaxy platform.

Here, we introduce the ChemicalToolbox, a publicly available web server for performing cheminformatics analysis. The ChemicalToolbox provides an intuitive, graphical interface for common tools for downloading, filtering, visualizing and simulating small molecules and proteins. The ChemicalToolbox is based on Galaxy, an open-source web-based platform which enables accessible and reproducible data analysis. There is already an active Galaxy cheminformatics community using and developing tools. Based on their work, we provide four example workflows which illustrate the capabilities of the ChemicalToolbox, covering assembly of a compound library, hole filling, protein-ligand docking, and construction of a quantitative structure-activity relationship (QSAR) model. These workflows may be modified and combined flexibly, together with the many other tools available, to fit the needs of a particular project. The ChemicalToolbox is hosted on the European Galaxy server and may be accessed via https://cheminformatics.usegalaxy.eu .

Intuitive, reproducible high-throughput molecular dynamics in Galaxy: a tutorial.

This paper is a tutorial developed for the data analysis platform Galaxy. The purpose of Galaxy is to make high-throughput computational data analysis, such as molecular dynamics, a structured, reproducible and transparent process. In this tutorial we focus on 3 questions: How are protein-ligand systems parameterized for molecular dynamics simulation? What kind of analysis can be carried out on molecular trajectories? How can high-throughput MD be used to study multiple ligands? After finishing you will have learned about force-fields and MD parameterization, how to conduct MD simulation and analysis for a protein-ligand system, and understand how different molecular interactions contribute to the binding affinity of ligands to the Hsp90 protein.

Biomolecular Reaction and Interaction Dynamics Global Environment (BRIDGE).

MOTIVATION: The pathway from genomics through proteomics and onto a molecular description of biochemical processes makes the discovery of drugs and biomaterials possible. A research framework common to genomics and proteomics is needed to conduct biomolecular simulations that will connect biological data to the dynamic molecular mechanisms of enzymes and proteins. Novice biomolecular modelers are faced with the daunting task of complex setups and a myriad of possible choices preventing their use of molecular simulations and their ability to conduct reliable and reproducible computations that can be shared with collaborators and verified for procedural accuracy. RESULTS: We present the foundations of Biomolecular Reaction and Interaction Dynamics Global Environment (BRIDGE) developed on the Galaxy platform that makes possible fundamental molecular dynamics of proteins through workflows and pipelines via commonly used packages, such as NAMD, GROMACS and CHARMM. BRIDGE can be used to set up and simulate biological macromolecules, perform conformational analysis from trajectory data and conduct data analytics of large scale protein motions using statistical rigor. We illustrate the basic BRIDGE simulation and analytics capabilities on a previously reported CBH1 protein simulation. AVAILABILITY AND IMPLEMENTATION: Publicly available at https://github.com/scientificomputing/BRIDGE and https://usegalaxy.eu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Intertidal mudflat and saltmarsh conservation and sustainable use in the UK: a review.

The adoption of the Convention on Wetlands of International Importance in Ramsar, Iran in 1971 committed the UK to conserve and sustainably use intertidal mudflats and saltmarshes for the benefit of present and future generations. Through consideration of their importance and value, current status, the characteristics, causes and consequences of their loss, and the associated responses to loss, this paper reviews the UK progress towards the conservation and sustainable use of intertidal mudflats and saltmarshes. Uncertainties in their current status and trends make it difficult to assess the overall net change in extent across the UK. However, it is apparent that losses due to erosion continue to exceed gains from intertidal mudflat and saltmarsh reparation (IMSR) schemes in south-east and southern England. IMSR schemes in the UK have been generally limited to relatively small-scale trials in comparison to elsewhere in Europe and in the USA. No research to date has unequivocally identified the causes of erosion. Regardless of the cause, the loss of intertidal mudflats and saltmarshes has adverse impacts on the provision of ecosystem services upon which humans and other species depend. The evidence presented in this paper suggests that alongside further science-based research, there is a need to develop a decision-making process capable of accommodating complexity, uncertainty and multiple diverse perspectives, through which more informed, timely decisions and more effective, concerted actions to conserve and sustainably use intertidal mudflats and saltmarshes can be taken.