FragHub: A Mass Spectral Library Data Integration Workflow.

Open mass spectral libraries (OMSLs) are critical for metabolite annotation and machine learning, especially given the rising volume of untargeted metabolomic studies and the development of annotation pipelines. Despite their importance, the practical application of OMSLs is hampered by the lack of standardized file formats, metadata fields, and supporting ontology. Current libraries, often restricted to specific topics or matrices, such as natural products, lipids, or the human metabolome, may limit the discovery potential of untargeted studies. The goal of FragHub is to provide users with the capability to integrate various OMSLs into a single unified format, thereby enhancing the annotation accuracy and reliability. FragHub addresses these challenges by integrating multiple OMSLs into a single comprehensive database, supporting various data formats, and harmonizing metadata. It also proposes some generic filters for the mass spectrum using a graphical user interface. Additionally, a workflow to generate in-house libraries compatible with FragHub is proposed. FragHub dynamically segregates libraries based on ionization modes and chromatography techniques, thereby enhancing data utility in metabolomic research. The FragHub Python code is publicly available under a MIT license, at the following repository: https://github.com/eMetaboHUB/FragHub. Generated data can be accessed at 10.5281/zenodo.11057687.

Multi-omics analysis to evaluate the effects of solar exposure and a broad-spectrum SPF50+ sunscreen on markers of skin barrier function in a skin ecosystem model.

Sun exposure induces major skin alterations, but its effects on skin metabolites and lipids remain largely unknown. Using an original reconstructed human epidermis (RHE) model colonized with human microbiota and supplemented with human sebum, we previously showed that a single dose of simulated solar radiation (SSR) significantly impacted the skin metabolome and microbiota. In this article, we further analyzed SSR-induced changes on skin metabolites and lipids in the same RHE model. Among the significantly altered metabolites (log2-fold changes with p ≤ 0.05), we found several natural moisturizing factors (NMFs): amino acids, lactate, glycerol, urocanic acid, pyrrolidone carboxylic acid and derivatives. Analyses of the stratum corneum lipids also showed that SSR induced lower levels of free fatty acids and higher levels of ceramides, cholesterols and its derivatives. An imbalance in NMFs and ceramides combined to an increase of proinflammatory lipids may participate in skin permeability barrier impairment, dehydration and inflammatory reaction to the sun. Our skin model also allowed the evaluation of an innovative ultraviolet/blue light (UV/BL) broad-spectrum sunscreen with a high sun protection factor (SPF50+). We found that using this sunscreen prior to SSR exposure could in part prevent SSR-induced alterations in NMFs and lipids in the skin ecosystem RHE model.

Spatial metabolomics using mass-spectrometry imaging to decipher the impact of high red meat diet on the colon metabolome in rat.

Colorectal cancer (CRC) is the third most common cancer in the world with a higher prevalence in the developed countries, mainly caused by environmental and lifestyle factors such as diet, particularly red meat consumption. The metabolic impact of high red meat consumption on the epithelial part of the colon was investigated using Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MSI), to specifically analyze the epithelial substructure. Ten colons from rats fed for 100 days high red or white meat diet were subjected to untargeted MSI analyses using two spatial resolutions (100 µm and 10 µm) to evaluate metabolite changes in the epithelial part and to visualize the distribution of metabolites of interest within the epithelium crypts. Our results suggest a specific effect of red meat diet on the colonic epithelium metabolism, as evidenced by an increase of purine catabolism products or depletion in glutathione pool, reinforcing the hypothesis of increased oxidative stress with red meat diet. This study also highlighted cholesterol sulfate as another up-regulated metabolite, interestingly localized at the top of the crypts. Altogether, this study demonstrates the feasibility and the added value of using MSI to decipher the effect of high red meat diet on the colonic epithelium.

Innovative analytical methodologies for characterizing chemical exposure with a view to next-generation risk assessment.

The chemical burden on the environment and human population is increasing. Consequently, regulatory risk assessment must keep pace to manage, reduce, and prevent adverse impacts on human and environmental health associated with hazardous chemicals. Surveillance of chemicals of known, emerging, or potential future concern, entering the environment-food-human continuum is needed to document the reality of risks posed by chemicals on ecosystem and human health from a one health perspective, feed into early warning systems and support public policies for exposure mitigation provisions and safe and sustainable by design strategies. The use of less-conventional sampling strategies and integration of full-scan, high-resolution mass spectrometry and effect-directed analysis in environmental and human monitoring programmes have the potential to enhance the screening and identification of a wider range of chemicals of known, emerging or potential future concern. Here, we outline the key needs and recommendations identified within the European Partnership for Assessment of Risks from Chemicals (PARC) project for leveraging these innovative methodologies to support the development of next-generation chemical risk assessment.

Multi-omics approach to understand the impact of sun exposure on an in vitro skin ecosystem and evaluate a new broad-spectrum sunscreen.

A reconstructed human epidermal model (RHE) colonized with human microbiota and sebum was developed to reproduce the complexity of the skin ecosystem in vitro. The RHE model was exposed to simulated solar radiation (SSR) with or without SPF50+ sunscreen (with UVB, UVA, long-UVA, and visible light protection). Structural identification of discriminant metabolites was acquired by nuclear magnetic resonance and metabolomic fingerprints were identified using reverse phase-ultra high-performance liquid chromatography-high resolution mass spectrometry, followed by pathway enrichment analysis. Over 50 metabolites were significantly altered by SSR (p < 0.05, log2 values), showing high skin oxidative stress (glutathione and purine pathways, urea cycle) and altered skin microbiota (branched-chain amino acid cycle and tryptophan pathway). 16S and internal transcribed spacer rRNA sequencing showed the relative abundance of various bacteria and fungi altered by SSR. This study identified highly accurate metabolomic fingerprints and metagenomic modifications of sun-exposed skin to help elucidate the interactions between the skin and its microbiota. Application of SPF50+ sunscreen protected the skin ecosystem model from the deleterious effects of SSR and preserved the physiological interactions within the skin ecosystem. These innovative technologies could thus be used to evaluate the effectiveness of sunscreen.

The fate of bisphenol A, bisphenol S, and their respective glucuronide metabolites in ovarian cells.

Ovarian cells are critical for reproduction and steroidogenesis, which are functions that can be impacted by exposure to xenobiotics. As in other extra-hepatic tissues, biotransformation events may occur at the ovarian level. Such metabolic events deserve interest, notably as they may modulate the overall exposure and toxicity of xenobiotics. In this study, the comparative metabolic fate of two bisphenols was investigated in ovarian cells. Bisphenol A (BPA), a model endocrine disruptor, and its major substitute bisphenol S (BPS) were selected. Bovine granulosa cells (primary cultures) and theca explants (ex vivo tissue) were exposed for 24 hr to tritium-labeled BPA, BPS and their respective glucuronides (i.e. their major circulating forms), at concentrations consistent with low-dose exposure scenarios. Mass balance studies were performed, followed by radio-HPLC profiling. The capability of both cell compartments to biotransform BPA and BPS into their respective sulfo-conjugates was demonstrated, with sulfation being the predominant metabolic route. In theca, there was a significantly higher persistence of BPA (compared to BPS) residues over 24 hr. Moreover, only theca explants were able to deconjugate inactive BPA-glucuronide and BPS-glucuronide back into their biologically active aglycone forms. Deconjugation rates were demonstrated to be higher for BPS-G than for BPA-G. These findings raise concerns about the in situ direct release of bisphenols at the level of the ovary and demonstrate the relevance of exploring the biotransformation of bisphenols and their circulating metabolites in different ovarian cells with specific metabolic capabilities. This work also provides essential knowledge for the improved risk assessment of bisphenols.

Urinary Metabolome Analysis Reveals Potential Microbiota Alteration and Electrophilic Burden Induced by High Red Meat Diet: Results from the French NutriNet-Santé Cohort and an In Vivo Intervention Study in Rats.

SCOPE: High red and processed meat consumption is associated with several adverse outcomes such as colorectal cancer and overall global mortality. However, the underlying mechanisms remain debated and need to be elucidated. METHODS AND RESULTS: Urinary untargeted Liquid Chromatography-Mass Spectrometry (LC-MS) metabolomics data from 240 subjects from the French cohort NutriNet-Santé are analyzed. Individuals are matched and divided into three groups according to their consumption of red and processed meat: high red and processed meat consumers, non-red and processed meat consumers, and at random group. Results are supported by a preclinical experiment where rats are fed either a high red meat or a control diet. Microbiota derived metabolites, in particular indoxyl sulfate and cinnamoylglycine, are found impacted by the high red meat diet in both studies, suggesting a modification of microbiota by the high red/processed meat diet. Rat microbiota sequencing analysis strengthens this observation. Although not evidenced in the human study, rat mercapturic acid profile concomitantly reveals an increased lipid peroxidation induced by high red meat diet. CONCLUSION: Novel microbiota metabolites are identified as red meat consumption potential biomarkers, suggesting a deleterious effect, which could partly explain the adverse effects associated with high red and processed meat consumption.

Miniaturized Two-Dimensional Heart Cutting for LC-MS-Based Metabolomics.

Liquid chromatography-mass spectrometry (LC-MS)-based metabolomics usually combines hydrophilic interaction liquid chromatography (HILIC) and reversed-phase (RP) chromatography to cover a wide range of metabolomes, requiring both significant sample consumption and analysis time for separate workflows. We developed an integrated workflow enabling the coverage of both polar and nonpolar metabolites with only one injection of the sample for each ionization mode using heart-cutting trapping to combine HILIC and RP separations. This approach enables the trapping of some compounds eluted from the first chromatographic dimension for separation later in the second dimension. In our case, we applied heart-cutting to non-retained metabolites in the first dimension. For that purpose, two independent miniaturized one-dimensional HILIC and RP methods were developed by optimizing the chromatographic and ionization conditions using columns with an inner diameter of 1 mm. They were then merged into one two-dimensional micro LC-MS method by optimization of the trapping conditions. Equilibration of the HILIC column during elution on the RP column and vice versa reduced the overall analysis time, and the multidimensionality allows us to avoid signal measurements during the solvent front. To demonstrate the benefits of this approach to metabolomics, it was applied to the analysis of the human plasma standard reference material SRM 1950, enabling the detection of hundreds of metabolites without the significant loss of some of them while requiring an injection volume of only 0.5 µL.

Metabolism of versicolorin A, a genotoxic precursor of aflatoxin B1: Characterization of metabolites using in vitro production of standards.

The toxicity of mycotoxins containing bisfuranoid structures such as aflatoxin B1 (AFB1) depends largely on biotransformation processes. While the genotoxicity and mutagenicity of several bisfuranoid mycotoxins including AFB1 and sterigmatocystin have been linked to in vivo bioactivation of these molecules into reactive epoxide forms, the metabolites of genotoxic and mutagenic AFB1 precursor versicolorin A (VerA) have not yet been characterized. Because this molecule is not available commercially, our strategy was to produce a library of metabolites derived from the biotransformation of in-house purified VerA, following incubation with human liver S9 fractions, in presence of appropriate cofactors. The resulting chromatographic and mass-spectrometric data were used to identify VerA metabolites produced by intestinal cell lines as well as intestinal and liver tissues exposed ex vivo. In this way, we obtained a panel of metabolites suggesting the involvement of phase I (M + O) and phase II (glucuronide and sulfate metabolites) enzymes, the latter of which is implicated in the detoxification process. This first qualitative description of the metabolization products of VerA suggests bioactivation of the molecule into an epoxide form and provides qualitative analytic data to further conduct a precise metabolism study of VerA required for the risk assessment of this emerging mycotoxin.

PeakForest: a multi-platform digital infrastructure for interoperable metabolite spectral data and metadata management.

INTRODUCTION: Accuracy of feature annotation and metabolite identification in biological samples is a key element in metabolomics research. However, the annotation process is often hampered by the lack of spectral reference data in experimental conditions, as well as logistical difficulties in the spectral data management and exchange of annotations between laboratories. OBJECTIVES: To design an open-source infrastructure allowing hosting both nuclear magnetic resonance (NMR) and mass spectra (MS), with an ergonomic Web interface and Web services to support metabolite annotation and laboratory data management. METHODS: We developed the PeakForest infrastructure, an open-source Java tool with automatic programming interfaces that can be deployed locally to organize spectral data for metabolome annotation in laboratories. Standardized operating procedures and formats were included to ensure data quality and interoperability, in line with international recommendations and FAIR principles. RESULTS: PeakForest is able to capture and store experimental spectral MS and NMR metadata as well as collect and display signal annotations. This modular system provides a structured database with inbuilt tools to curate information, browse and reuse spectral information in data treatment. PeakForest offers data formalization and centralization at the laboratory level, facilitating shared spectral data across laboratories and integration into public databases. CONCLUSION: PeakForest is a comprehensive resource which addresses a technical bottleneck, namely large-scale spectral data annotation and metabolite identification for metabolomics laboratories with multiple instruments. PeakForest databases can be used in conjunction with bespoke data analysis pipelines in the Galaxy environment, offering the opportunity to meet the evolving needs of metabolomics research. Developed and tested by the French metabolomics community, PeakForest is freely-available at https://github.com/peakforest .