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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.

Oceanic dissolved organic matter (DOM) is an assemblage of reduced carbon compounds, which results from biotic and abiotic processes. The biotic processes consist in either release or uptake of specific molecules by marine organisms. Heterotrophic bacteria have been mostly considered to influence the DOM composition by preferential uptake of certain compounds. However, they also secrete a variety of molecules depending on physiological state, environmental and growth conditions, but so far the full set of compounds secreted by these bacteria has never been investigated. In this study, we analyzed the exo-metabolome, metabolites secreted into the environment, of the heterotrophic marine bacterium Pseudovibrio sp. FO-BEG1 via ultra-high resolution mass spectrometry, comparing phosphate limited with phosphate surplus growth conditions. Bacteria belonging to the Pseudovibrio genus have been isolated worldwide, mainly from marine invertebrates and were described as metabolically versatile Alphaproteobacteria. We show that the exo-metabolome is unexpectedly large and diverse, consisting of hundreds of compounds that differ by their molecular formulae. It is characterized by a dynamic recycling of molecules, and it is drastically affected by the physiological state of the strain. Moreover, we show that phosphate limitation greatly influences both the amount and the composition of the secreted molecules. By assigning the detected masses to general chemical categories, we observed that under phosphate surplus conditions the secreted molecules were mainly peptides and highly unsaturated compounds. In contrast, under phosphate limitation the composition of the exo-metabolome changed during bacterial growth, showing an increase in highly unsaturated, phenolic, and polyphenolic compounds. Finally, we annotated the detected masses using multiple metabolite databases. These analyses suggested the presence of several masses analogue to masses of known bioactive compounds. However, the annotation was successful only for a minor part of the detected molecules, underlining the current gap in knowledge concerning the biosynthetic ability of marine heterotrophic bacteria.

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.

Prevailing knowledge gaps in linking specific molecular changes to apical outcomes and methodological uncertainties in the generation, storage, processing, and interpretation of ‘omics data limit the application of ‘omics technologies in regulatory toxicology. Against this background, the European Centre for Ecotoxicology and Toxicology of Chemicals (ECETOC) convened a workshop Applying ‘omics technologies in chemicals risk assessment that is reported herein. Ahead of the workshop, multi-expert teams drafted frameworks on best practices for (i) a Good-Laboratory Practice-like context for collecting, storing and curating ‘omics data; (ii) the processing of ‘omics data; and (iii) weight-of-evidence approaches for integrating ‘omics data. The workshop participants confirmed the relevance of these Frameworks to facilitate the regulatory applicability and use of ‘omics data, and the workshop discussions provided input for their further elaboration. Additionally, the key objective (iv) to establish approaches to connect ‘omics perturbations to phenotypic alterations was addressed. Generally, it was considered promising to strive to link gene expression changes and pathway perturbations to the phenotype by mapping them to specific adverse outcome pathways. While further work is necessary before gene expression changes can be used to establish safe levels of substance exposure, the ECETOC workshop provided important incentives towards achieving this goal.

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