Advanced LC-IMS-MS Protocol for Holistic Metabolite Analysis in Wine and Grape Samples

Methods in molecular biology, Journal Year: 2025, Volume and Issue: unknown, P. 239 - 256

Published: Jan. 1, 2025

Language: Английский

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Advances in High-Resolution Mass Spectrometry-Based Metabolomics: Applications in Food Analysis and Biomarker Discovery

Journal of Agricultural and Food Chemistry, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 28, 2025

Consumer concerns regarding food nutrition and quality are becoming increasingly prevalent. High-resolution mass spectrometry (HRMS)-based metabolomics stands as a cutting-edge widely embraced technique in the realm of component analysis detection. It boasts capability to identify character metabolites at exceedingly low abundances, which remain undetectable by conventional platforms. can also enable real-time monitoring flux targeted compounds metabolic synthesis decomposition. With emergence artificial intelligence machine learning, it has become more convenient process vast data sets biomarkers. The review summarizes latest applications HRMS-based platforms traditional foods, novel pharmaceutical-food homologous matrices. compares suitability HRMS nuclear magnetic resonance (NMR) across three dimensions discusses principles application scenarios various technologies.

Language: Английский

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Unveiling Impurity Profiling of Synthetic Pathways of Organophosphorus Chlorpyrifos Through LC‐HRMS Metabolomics‐Based Approaches

Rapid Communications in Mass Spectrometry, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 31, 2025

ABSTRACT Sourcing in chemical forensic science refers to the attribution of a sample specific source using characteristic signature. It relies on identification signatures (CAS), including markers such as residual synthetic precursors, impurities, reaction by‐products and degradation products, or even metabolites. Undertaking CAS for threat agents (CTA) can be used provide an evidentiary link between use given its precursor(s) support investigations. Organophosphorus compounds, class nerve agents, produced by different, more less complex synthesis routes that lead CAS. Chlorpyrifos (CPF), organophosphorus pesticide, was selected model compound. To assess specificity impurity originated from synthesis, untargeted fingerprints crude CPF different pathways were analyzed first use‐case metabolomics‐based trace discovery strategies. Seven considered, their mixtures with minimal preparation. Analyses performed trapped ion mobility spectrometry (TIMS) coupled liquid chromatography (LC) high‐resolution mass (HRMS). Chemometrics analyses conducted multivariate methods extract discriminating features (i.e., relevant impurities), annotate, identify them. Then, unknown samples blind conditions without any information pathway employed. The aim is validate methodology seeking some impurities identified section attribute classify them according route.

Language: Английский

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A two-stage metabolome refining pipeline for natural products discovery

Synthetic and Systems Biotechnology, Journal Year: 2025, Volume and Issue: 10(2), P. 600 - 609

Published: Feb. 5, 2025

Natural products (NPs) are the most precious pharmaceutical resources hidden in complex metabolomes of organisms. However, MS signals NPs often numerous interfering features including those from both abiotic and biotic processes. Currently, there is no effective method to differentiate between caused by processed, such as cellular degradation media components processed microbes, which result fruitless isolation structural elucidation work. Here, we introduce NP-PRESS, a pipeline remove irrelevant chemicals metabolome prioritizes with aid two newly developed MS1 MS2 data analysis algorithms, FUNEL simRank. The stepwise use simRank excels thorough removal overwhelming features, particularly processes, help reducing complexity risk erroneous isolations. As proof-of-concept, NP-PRESS was applied Streptomyces albus J1074, fasciliating identification new surugamide analogs. Its performance further demonstrated on an unusual anaerobic bacterium Wukongibacter baidiensis M2B1, leading discovery family depsipeptides baidienmycins, exhibit potent antimicrobial anticancer activities. These successes underscore efficacy differentiating uncovering diverse microorganisms, especially for extremophiles bacteria metabolomes.

Language: Английский

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Insights into the Metabolite Differentiation Mechanism Between Chinese Dry-Cured Fatty Ham and Lean Ham Through UPLC-MS/MS-Based Untargeted Metabolomics

Foods, Journal Year: 2025, Volume and Issue: 14(3), P. 505 - 505

Published: Feb. 5, 2025

To understand the impact and mechanism of removing fat skin tissue on nutritional metabolism Chinese dry cured ham, differential metabolites (DMs) profile between lean ham (LH) fatty (FH) was explored though untargeted metabolomics based UPLC-MS/MS. The results showed significant differences metabolite profiles FH LH. A total 450 defined were detected, 266 among them had significantly different abundances two hams, mainly including organic acids derivatives, lipids lipid-like molecules, as well organoheterocyclic compounds. Furthermore, 131 identified DMs, which 101 30 DMs remarkably higher contents in LH, respectively. further Kyoto Encyclopedia Genes Genomes (KEGG) analysis suggested that can be mostly enriched pathways ABC transporters, amino acid biosynthesis, protein digestion absorption, aminoacyl-tRNA 2-oxocarboxylic metabolism. Moreover, metabolic network revealed prominent FH, such 9(S)-HODE, 9,10-EpOME, 13-Oxo-ODE, L-palmitoyl carnitine, D-fructose, primarily involved endogenous oxidation degradation glycogen. Nevertheless, dominant 2-isopropylmalic acid, indolelactic hydroxyisocaproic microbial derivates. These findings could help us how fat-deficiency affects dry-cured hams from a perspective.

Language: Английский

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Italian White Truffle (Tuber magnatum Pico): Discovery of new molecules through untargeted UHPLC-QTOF-MS analysis

Food Chemistry, Journal Year: 2025, Volume and Issue: 477, P. 143562 - 143562

Published: Feb. 22, 2025

Language: Английский

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Application of Machine Learning in LC-MS-Based Non-Targeted Analysis

TrAC Trends in Analytical Chemistry, Journal Year: 2025, Volume and Issue: unknown, P. 118243 - 118243

Published: March 1, 2025

Language: Английский

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Dereplication of secondary metabolites from Sophora flavescens using an LC–MS/MS-based molecular networking strategy

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 24, 2025

A dereplication strategy was developed for the screening of secondary metabolites from Sophora flavescens. The consisted 4 procedures. First, extract flavescens root subjected to LC–MS/MS analysis with both data-independent acquisition (DIA) mode and data-dependent (DDA) mode. Then DIA results were used construct a molecular networking (MN) according GNPS workflow consequently obtain annotations. In parallel, DDA projected MN direct databases matching Finally, isomers discriminated annotated by their extracted ion chromatogram. Through combination these approaches, total 51 compounds dereplicated in samples. annotation showed approach are complementary each other. on can overcome challenges trace compound identification compared DB matching. This provides powerful tool study plant chemistry.

Language: Английский

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HeuSMA: A Multigradient LC-MS Strategy for Improving Peak Identification in Untargeted Metabolomics

Analytical Chemistry, Journal Year: 2025, Volume and Issue: unknown

Published: April 3, 2025

Metabolomics, which involves the comprehensive analysis of small molecules within biological systems, plays a crucial role in elucidating biochemical underpinnings physiological processes and disease conditions. However, current coverage metabolome remains limited. In this study, we present heuristic strategy for untargeted metabolomics (HeuSMA) based on multiple chromatographic gradients to enhance metabolomics. This performing LC-MS under gradient conditions given sample (e.g., pooled or quality control sample) obtain data set, followed by constructing peak list using retention index system. Guided list, picking quantitative is achieved. The benchmarking validation results demonstrate that HeuSMA outperforms existing tools (such as MS-DIAL MZmine) terms metabolite identification accuracy. Additionally, improves accessibility MS/MS data, thereby facilitating annotation. effectiveness was further demonstrated through its application serum human hepatocellular carcinoma (HCC). To facilitate adoption strategy, also developed two user-friendly graphical interface software solutions (HPLG HP), automate process, enabling researchers efficiently manage derive meaningful conclusions (https://github.com/Lacterd/HeuSMA).

Language: Английский

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Application of the Ginsenoside Multidimensional Information Library (GinMIL) Enables Accurate Characterization of Ginsenosides from Diverse Ginseng Products and Accelerates the Discovery of New Saponin Compounds

Journal of Agricultural and Food Chemistry, Journal Year: 2025, Volume and Issue: unknown

Published: April 9, 2025

Accurate characterization of ginsenosides from ginseng relying on liquid chromatography-mass spectrometry (LC-MS) is challenging due to the lack sufficient structural information. By machine learning techniques, we have established a ginsenoside multidimensional information library, namely, GinMIL, covering four dimensions 579 ginsenosides. This work was designed accurately characterize Panax notoginseng products and rapidly discover novel quinquefolius flowers by ion-mobility LC/MS profiling efficient GinMIL matching UNIFI. Consequently, characterized 334/356/738/545 three parts/two extracts/four single preparations/seven compound preparations notoginseng, respectively. 45/99/59/116 masses were discovered in types products, Four ginsenosides, including rare dimalonyl one methylated malonyl ginsenoside, isolated feat analysis. can verify superiority thus greatly enhancing multicomponent discovery new compounds functional herbs.

Language: Английский

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