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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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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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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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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The plant-beneficial fungus Trichoderma harzianum T22 modulates plant metabolism and negatively affects Nezara viridula

BMC Plant Biology, Год журнала: 2025, Номер 25(1)

Опубликована: Май 10, 2025

Plant-beneficial fungi play an important role in enhancing plant health and resistance against biotic abiotic stresses. Although extensive research has focused on their eliciting defences pathogens, contribution to induced herbivorous insects the underlying mechanisms remain poorly understood. In this study, we used insect bioassays untargeted metabolomics investigate impact of root inoculation sweet pepper with plant-beneficial fungus Trichoderma harzianum T22 direct defence responses herbivore Nezara viridula. We observed reduced relative growth rate N. viridula leaves fungus-inoculated plants, no change mortality. Untargeted metabolomic analyses revealed that T. did not affect leaf metabolome absence herbivory five weeks after inoculation. However, compared non-inoculated inoculated plants exhibited significant metabolic alterations herbivore-damaged following feeding, while changes profile distant were less pronounced. Notably, metabolites involved shikimate-phenylpropanoid pathway, known be responses, displayed higher accumulation damaged plants. Our results indicate affects viridula, leading performance. Metabolite-level effects primarily leaves, suggesting priming effect mainly localized metabolite at site attack. Future should focus identifying detected compounds determining impairing

Язык: Английский

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Describing the complex chemistry of benthic seawater: from exometabolite sampling strategies to MS-based metabolomics

Natural Product Reports, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

This review highlights advances in characterizing exometabolites (EMs) from benthic organisms, starting with situ sampling methods, then discussing how marine MS-based (exo)metabolomics benefits various fields while addressing ongoing challenges.

Язык: Английский

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MetMiner: A user‐friendly pipeline for large‐scale plant metabolomics data analysis

Journal of Integrative Plant Biology, Год журнала: 2024, Номер unknown

Опубликована: Сен. 10, 2024

ABSTRACT The utilization of metabolomics approaches to explore the metabolic mechanisms underlying plant fitness and adaptation dynamic environments is growing, highlighting need for an efficient user‐friendly toolkit tailored analyzing extensive datasets generated by studies. Current protocols metabolome data analysis often struggle with handling large‐scale or require programming skills. To address this, we present MetMiner ( https://github.com/ShawnWx2019/MetMiner ), a user‐friendly, full‐functionality pipeline specifically designed analysis. Built on R shiny, can be deployed servers utilize additional computational resources processing datasets. ensures transparency, traceability, reproducibility throughout analytical process. Its intuitive interface provides robust interaction graphical capabilities, enabling users without prior skills engage deeply in Additionally, constructed integrated plant‐specific mass spectrometry database into optimize metabolite annotation. We have also developed MDAtoolkits, which include complete set tools statistical analysis, classification, enrichment facilitate mining biological meaning from Moreover, propose iterative weighted gene co‐expression network strategy biomarker screening mining. In two case studies, validated MetMiner's efficiency robustness Together, represents promising solution providing valuable tool scientific community use ease.

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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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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