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Galaxy is a mature, browser accessible workbench for scientific computing. It enables scientists to share, analyze and visualize their own data, with minimal technical impediments. A thriving global community continues to use, maintain and contribute to the project, with support from multiple national infrastructure providers that enable freely accessible analysis and training services. The Galaxy Training Network supports free, self-directed, virtual training with >230 integrated tutorials. Project engagement metrics have continued to grow over the last 2 years, including source code contributions, publications, software packages wrapped as tools, registered users and their daily analysis jobs, and new independent specialized servers. Key Galaxy technical developments include an improved user interface for launching large-scale analyses with many files, interactive tools for exploratory data analysis, and a complete suite of machine learning tools. Important scientific developments enabled by Galaxy include Vertebrate Genome Project (VGP) assembly workflows and global SARS-CoV-2 collaborations.

Metabolomic and lipidomic studies measure and discover metabolic and lipid profiles in biological samples, enabling a better understanding of the metabolism of specific biological phenotypes. Accurate biological interpretations require high analytical reproducibility and sensitivity, and standardized and transparent data processing. Here we describe a complete workflow for nanoelectrospray ionization (nESI) direct-infusion mass spectrometry (DIMS) metabolomics and lipidomics. After metabolite and lipid extraction from tissues and biofluids, samples are directly infused into a high-resolution mass spectrometer (e.g., Orbitrap) using a chip-based nESI sample delivery system. nESI functions to minimize ionization suppression or enhancement effects as compared with standard electrospray ionization (ESI). Our analytical technique-named spectral stitching-measures data as several overlapping mass-to-charge (m/z) windows that are subsequently 'stitched' together, creating a complete mass spectrum. This considerably increases the dynamic range and detection sensitivity-about a fivefold increase in peak detection-as compared with the collection of DIMS data as a single wide mass-to-charge (m/z ratio) window. Data processing, statistical analysis and metabolite annotation are executed as a workflow within the user-friendly, transparent and freely available Galaxy platform (galaxyproject.org). Generated data have high mass accuracy that enables molecular formulae peak annotations. The workflow is compatible with any sample-extraction method; in this protocol, the examples are extracted using a biphasic method, with methanol, chloroform and water as the solvents. The complete workflow is reproducible, rapid and automated, which enables cost-effective analysis of >10,000 samples per year, making it ideal for high-throughput metabolomics and lipidomics screening-e.g., for clinical phenotyping, drug screening and toxicity testing.

Metabolomics is a widely used technology in academic research, yet its application to regulatory science has been limited. The most commonly cited barrier to its translation is lack of performance and reporting standards. The MEtabolomics standaRds Initiative in Toxicology (MERIT) project brings together international experts from multiple sectors to address this need. Here, we identify the most relevant applications for metabolomics in regulatory toxicology and develop best practice guidelines, performance and reporting standards for acquiring and analysing untargeted metabolomics and targeted metabolite data. We recommend that these guidelines are evaluated and implemented for several regulatory use cases.

Currently there is a surge of interest in exploiting toxicogenomics to screen the toxicity of chemicals, enabling rapid and accurate categorisation into classes of defined mode-of-action (MOA), and prioritising chemicals for further testing. Direct infusion FT-ICR mass spectrometry-based metabolomics can provide a sensitive and unbiased analysis of metabolites in only 15 mins and therefore has considerable potential for chemical screening. The water flea, Daphnia magna, is an OECD test species and is utilised internationally for toxicity testing. However, no metabolomics studies of this species have been reported.Here we optimised and evaluated the effectiveness of FT-ICR mass spectrometry metabolomics for toxicity testing in D. magna. We confirmed that high-quality mass spectra can be recorded from as few as 30 neonates (\24 h old; 224 lg dry mass) or a single adult daphnid (301 lg dry mass). An OECD 24 h acute toxicity test was conducted with neonates at copper concentrations of 0, 5, 10, 25, 50 lg l -1 . A total of 5447 unique peaks were detected reproducibly, of which 4768 were assigned at least one empirical formula and 1017 were putatively identified based upon accurate mass measurements. Significant copper-induced changes to the daphnid metabolome, consistent with the documented MOA of copper, were detected thereby validating the approach. In addition, Nacetylspermidine was putatively identified as a novel biomarker of copper toxicity. Collectively, our results highlight the excellent sensitivity, reproducibility and mass accuracy of FT-ICR mass spectrometry, and provide strong evidence for its applicability to high-throughput screening of chemical toxicity in D. magna.