MLinvitroTox reloaded for high-throughput hazard-based prioritization of high-resolution mass spectrometry data

Journal of Cheminformatics, Год журнала: 2025, Номер 17(1)

Опубликована: Янв. 31, 2025

MLinvitroTox is an automated Python pipeline developed for high-throughput hazard-driven prioritization of toxicologically relevant signals detected in complex environmental samples through high-resolution tandem mass spectrometry (HRMS/MS). a machine learning (ML) framework comprising 490 independent XGBoost classifiers trained on molecular fingerprints from chemical structures and target-specific endpoints the ToxCast/Tox21 invitroDBv4.1 database. For each analyzed HRMS feature, generates 490-bit bioactivity fingerprint used as basis prioritization, focusing time-consuming identification efforts features most likely to cause adverse effects. The practical advantages are demonstrated groundwater data. Among 874 which were derived spectra, including 630 nontargets, 185 spectral matches, 59 targets, around 4% feature/endpoint relationship pairs predicted be active. Cross-checking predictions targets matches with invitroDB data confirmed 120 active 6791 nonactive while mislabeling 88 56 non-active relationships. By filtering according probability, endpoint scores, similarity training data, number potentially toxic was reduced by at least one order magnitude. This refinement makes analytical confirmation feasible, offering significant benefits cost-efficient risk assessment.Scientific Contribution:In contrast classical ML-based approaches toxicity prediction, predicts (i.e., distinct m/z signals) based MS2 fragmentation spectra rather than identified features. While original proof concept study accompanied release v1 KNIME workflow, this study, we v2 package, which, addition automation, expands functionality include predicting structures, cleaning up generating fingerprints, customizing models, retraining custom Furthermore, result improvements processing, realized concurrently released pytcpl package processing input MLinvitroTox, current introduces enhancements model accuracy, coverage biological mechanistic overall interpretability.

Язык: Английский

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Chemical Profile and Bioactivities of Three Species of Mentha Growing in the Campania Region, Southern Italy

Plants, Год журнала: 2025, Номер 14(3), С. 360 - 360

Опубликована: Янв. 24, 2025

The genus Mentha (Lamiaceae), comprising aromatic perennial plants widely distributed in temperate regions, holds significant medicinal and commercial value. This study aimed to investigate the chemical profile bioactivities of hydroalcoholic extracts from longifolia (L.) L., pulegium spicata L. harvested Campania region, Southern Italy. Chemical analysis using LC-HRESIMS/MS identified a total 21 compounds. extracts, particularly M. pulegium, exhibited notable antioxidant activity, evaluated through DPPH FRAP assays, probably related their composition. Both demonstrated higher phenolic content, with also containing highest levels flavonoids. In addition, extract’s ability inhibit biofilm formation was against several pathogenic strains, including Gram-positive bacteria (Listeria monocytogenes Staphylococcus aureus) Gram-negative (Acinetobacter baumannii, Pseudomonas aeruginosa, Escherichia coli) crystal violet MTT assays. All effectively inhibited A. baumannii P. showing moderate activity metabolism monocytogenes. pronounced antibacterial biofilm-inhibitory properties highlight its potential for pharmaceutical applications.

Язык: Английский

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Statistical analysis of feature-based molecular networking results from non-targeted metabolomics data

Nature Protocols, Год журнала: 2024, Номер unknown

Опубликована: Сен. 20, 2024

Язык: Английский

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Signal Processing Workflow for Suspect Screening in LC × LC-HRMS: Efficient Extraction of Pure Mass Spectra for Identification of Suspects in Complex Samples Using a Mass Filtering Algorithm

Analytical Chemistry, Год журнала: 2025, Номер unknown

Опубликована: Янв. 7, 2025

The data processing workflows for comprehensive two-dimensional liquid chromatography (LC × LC) hyphenated to high-resolution mass spectrometry (HRMS) operated in data-independent acquisition (DIA) are limited compared their one-dimensional counterparts. A two-step workflow is proposed extract pure spectra from LC LC-HRMS. First, a filtering (MF) algorithm groups ions belonging the same compound based on elution profile similarity first (1D) and second dimension (2D). Second, filtered deconvoluted using multivariate curve resolution (MCR) address potential coelution. presented termed MF + MCR was tested pulsed elution-LC LC-HRMS wastewater effluent extract. benchmarked following three strategies extraction: peak apex (PAM), approach alone, or without prior MF. identified 25 suspect compounds, 23, 16, 10 by MF, MCR, PAM, respectively. nine suspects that could not be all had low total signal contributions, i.e., intensities TIC. This showed adequate preprocessing essential trace level analysis. Additionally, it shown extracted statistically significantly purer PAM (p-value: 0.003) 0.04) spiked blank sample. results highlight utilizing profiles both chromatographic dimensions, clean of analytes at levels measured DIA can extracted, allowing more reliable identification were used benchmarking.

Язык: Английский

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SAPID: a Strategy to Analyze Plant Extracts Taste In Depth. Application to the complex taste of Swertia chirayita (Roxb.) H.Karst.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2025, Номер unknown

Опубликована: Янв. 12, 2025

ABSTRACT Bitterness is challenging to analyze due the diversity of bitter compounds, variability in sensory perception, and its interplay with other tastes. To address this, we developed an untargeted approach deconvolute taste molecular composition complex plant extracts. We applied our methodology ethanolic extract Swertia chirayita (Roxb.) H.Karst., a known for unique bitterness. Chemical characterization was performed through nuclear magnetic resonance spectroscopy experiments together liquid chromatography-high resolution tandem mass spectrometry analysis coupled charged aerosol detector. After clustering fractions based on chemical similarity, free classical descriptive each cluster. Our results confirmed attribution bitterness iridoids highlighted role important compounds overall taste. This method offers systematic analyzing enhancing profiles plant-based beverages. Highlights An depth extracts’ has been developed. The H.Karst. well-known major minor using methods. Chemically informed tasting allowed highlight less pronounced tastes within extract, contributing complexity. led interesting insights into sub-threshold impact modulating properties. Graphical Abstract

Язык: Английский

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Liquid and gas-chromatography-mass spectrometry methods for exposome analysis

Journal of Chromatography A, Год журнала: 2025, Номер unknown, С. 465728 - 465728

Опубликована: Янв. 1, 2025

Язык: Английский

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A guide to reverse metabolomics—a framework for big data discovery strategy

Nature Protocols, Год журнала: 2025, Номер unknown

Опубликована: Фев. 28, 2025

Язык: Английский

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Computational metabolomics reveals overlooked chemodiversity of alkaloid scaffolds in Piper fimbriulatum

The Plant Journal, Год журнала: 2025, Номер 121(5)

Опубликована: Март 1, 2025

Plant specialized metabolites play key roles in diverse physiological processes and ecological interactions. Identifying structurally novel metabolites, as well discovering known compounds new species, is often crucial for answering broader biological questions. The Piper genus (Piperaceae family) its special phytochemistry has been extensively studied over the past decades. Here, we investigated alkaloid diversity of fimbriulatum, a myrmecophytic plant native to Central America, using metabolomics workflow that combines untargeted LC-MS/MS analysis with range recently developed computational tools. Specifically, leverage open MS/MS spectral libraries data repositories metabolite annotation, guiding isolation efforts toward (i.e., dereplication). As result, identified several alkaloids belonging five different classes isolated one seco-benzylisoquinoline featuring linear quaternary amine moiety which named fimbriulatumine. Notably, many were never reported Piperaceae plants. Our findings expand this family demonstrate value revisiting well-studied families state-of-the-art workflows uncover previously overlooked chemodiversity. To contextualize our within context, employed automated mining literature reports scaffolds mapped results onto angiosperm tree life. By doing so, highlight remarkable provide framework generating hypotheses on biosynthetic evolution these metabolites. Many tools resources used study remain underutilized science community. This manuscript demonstrates their potential through practical application aims promote accessibility approaches.

Язык: Английский

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Untargeted Characterization and Biological Activity of Amazonian Aqueous Stem Bark Extracts by Liquid and Gas Chromatography–Mass Spectrometry

Phytochemical Analysis, Год журнала: 2025, Номер unknown

Опубликована: Янв. 14, 2025

ABSTRACT Introduction Aqueous stem bark extracts of Aspidosperma rigidum Rusby, Couroupita guianensis Aubl., Monteverdia laevis (Reissek) Biral, and Protium sagotianum Marchand have been reported as traditional remedies in several countries the Amazonian region. Despite previous research, further investigation to characterize secondary metabolites biological activity is needed derive potential applications. Material Methods Metabolic profiling was carried out using liquid gas chromatography coupled with mass spectrometry (UHPLC–MS/MS GC–MS). The chemical composition studied plants compared by principal component analysis (PCA). Additionally, profiles were correlated antimicrobial toxicity activities, which suggested for future research. Results We identified 16 32 compounds UHPLC–MS/MS GC–MS analysis, respectively. Antimicrobial detected three extracts. C. showed inhibition all tested microorganisms, including antibiotic‐resistant strains. Molecular networking approaches, silico tools, Pearson's correlation that antifungal could be a terpene glycoside ( r = 0.918) and/or phenolic 0.882) metabolite class. Conclusion This study highlights use established procedure exploring metabolomes these species, novel source drug discovery. Coupling observed data has also accelerated tracing their bioactive compounds. These findings update state art regarding plant extracts, defining new applications pharmaceutical

Язык: Английский

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Workflow4Metabolomics (W4M): A User‐Friendly Metabolomics Platform for Analysis of Mass Spectrometry and Nuclear Magnetic Resonance Data

Current Protocols, Год журнала: 2025, Номер 5(2)

Опубликована: Фев. 1, 2025

Abstract Various spectrometric methods can be used to conduct metabolomics studies. Nuclear magnetic resonance (NMR) or mass spectrometry (MS) coupled with separation methods, such as liquid gas chromatography (LC and GC, respectively), are the most commonly techniques. Once raw data have been obtained, real challenge lies in bioinformatics required conduct: (i) processing (including preprocessing, normalization, quality control); (ii) statistical analysis for comparative studies (such univariate multivariate analyses, including PCA PLS‐DA/OPLS‐DA); (iii) annotation of metabolites interest; (iv) interpretation relationships between key relevant phenotypes scientific questions addressed. Here, we will introduce detail a stepwise protocol use Workflow4Metabolomics platform (W4M), which provides user‐friendly access workflows LC–MS, GC–MS, NMR data. Those modular extensible composed existing standalone components (e.g., XCMS CAMERA packages) well suite complementary W4M‐implemented modules. This tool is accessible worldwide through web interface hosted on UseGalaxy France. The Virtual Research Environment (VRE) provided offers pre‐configured communities (platforms, end users, etc.), possibilities sharing among users. By providing consistent ecosystem tools Galaxy, W4M makes it possible process MS from hundreds samples using an ordinary personal computer, after step‐by‐step workflow optimization. © 2025 Wiley Periodicals LLC. Basic Protocol 1 : account creation, working history preparation, upload Support How prepare zip file 2 convert proprietary format open 3 get help (IFB forum) how report problem GitHub repository LC–MS Alternate GC–MS Statistical 4 Annotation

Язык: Английский

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