Effective data visualization strategies in untargeted metabolomics DOI Creative Commons
Kevin Mildau, Henry Ehlers, Mara Meisenburg

и другие.

Natural Product Reports, Год журнала: 2024, Номер unknown

Опубликована: Дек. 2, 2024

Covering: 2014 to 2023 for metabolomics, 2002 information visualizationLC-MS/MS-based untargeted metabolomics is a rapidly developing research field spawning increasing numbers of computational tools assisting researchers with their complex data processing, analysis, and interpretation tasks. In this article, we review the entire workflow from perspective visualization, visual analytics integration. Data visualization crucial step at every stage workflow, where it provides core components inspection, evaluation, sharing capabilities. However, due large number available analysis corresponding components, hard both users developers get an overview what already which are suitable analysis. addition, there little cross-pollination between fields leaving be designed in secondary mostly ad hoc fashion. With review, aim bridge gap visualization. First, introduce as topic worthy its own dedicated research, provide primer on cutting-edge into well active metabolomics. We extend discussion best practices they have emerged studies. Second, practical roadmap tool landscape use within field. Here, several stages commonly used strategies examples. context, will also outline promising areas further development. end set recommendations how make visualizations more effective transparent communication results.

Язык: Английский

Integrating Ultra‐High‐Performance Liquid Chromatography and Orbitrap High‐Resolution Mass Spectrometry, Feature‐Based Molecular Networking, and Network Medicine to Unlock Harvesting Strategies for Endangered Sinocalycanthus Chinensis DOI Open Access
Yingpeng Tong, Xin Li,

Jiang Wan

и другие.

Journal of Separation Science, Год журнала: 2025, Номер 48(1)

Опубликована: Янв. 1, 2025

Evaluating the practical utility of endangered plant species is crucial for their conservation. Nevertheless, numerous plants, including Sinocalycanthus chinensis, lack historical usage data, leading to a paucity guidance in traditional pharmacological research. This gap impedes development and potential utilization. Ultra-high-performance liquid chromatography Orbitrap high-resolution mass spectrometry were employed analyze S. chinensis leaves collected at different harvesting times. Then, metabolites automatically annotated by self-built R script conjunction with characteristic fragment ions, neutral loss filtering, feature-based molecular networking. By integrating metabolomics network medicine analysis, optimal harvest times unlocked. A total 305 identified, 66.8% script. progressive increase metabolite disparities was observed from May August, followed relatively minor distinction August October. Notably diverse detected harvested during periods, implying variations efficacy. Network analysis indicated possible therapeutic implications lung cancer, diabetes, bladder Alzheimer's disease. Samples September demonstrated exceptional Harvesting strategically conducted these months based on sample characteristics content, tailored intended applications dietary or medicinal purposes. study developed an efficient methodology investigating exploring food herbal medicine. Consequently, it provides technical support sustainable conservation plants limited clinical application experience.

Язык: Английский

Процитировано

1
Seasonal changes in bay water column properties and their influence on the distribution of dissolved and particulate substances along the south coast of Curaçao (Caribbean Sea) DOI Creative Commons

V Sanchez Baranco,

L. Schellenberg,

Furu Mienis

и другие.

Marine Pollution Bulletin, Год журнала: 2025, Номер 212, С. 117545 - 117545

Опубликована: Янв. 16, 2025

As endpoints of watersheds, bays concentrate erosion- and human-derived substances such as dissolved inorganic nutrients pollutants. We investigated the water movement biogeochemistry two in Curaçao: Piscadera Bay Spaanse Water, during dry (May 2022 2023) wet seasons (November 2021 2023). Bay-ocean exchange was limited season, enhancing nutrient concentrations bays. The season showed increased mixing between bay offshore water. Extreme rainfall from 2023 El Niño event led to heavy runoff wastewater influx, particularly Bay, where enriched δ15N total xenobiotic were over 1.5 times higher than season. Elevated δ13C values reflected greater terrestrial influence Bay. These findings show how extreme weather, likely under future climate scenarios, can enhance pollutant export reefs.

Язык: Английский

Процитировано

0
A guide to reverse metabolomics—a framework for big data discovery strategy DOI
Vincent Charron‐Lamoureux, Helena Mannochio-Russo, Santosh Lamichhane

и другие.

Nature Protocols, Год журнала: 2025, Номер unknown

Опубликована: Фев. 28, 2025

Язык: Английский

Процитировано

0
Analysis of plant metabolomics data using identification‐free approaches DOI Creative Commons
Xinyu Yuan, Nathaniel Smith, Gaurav D. Moghe

и другие.

Applications in Plant Sciences, Год журнала: 2025, Номер unknown

Опубликована: Март 1, 2025

Abstract Plant metabolomes are structurally diverse. One of the most popular techniques for sampling this diversity is liquid chromatography–mass spectrometry (LC‐MS), which typically detects thousands peaks from single organ extracts, many representing true metabolites. These usually annotated using in‐house retention time or spectral libraries, in silico fragmentation and increasingly through computational such as machine learning. Despite these advances, over 85% LC‐MS remain unidentified, posing a major challenge data analysis biological interpretation. This bottleneck limits our ability to fully understand diversity, functions, evolution plant In review, we first summarize current approaches metabolite identification, highlighting their challenges limitations. We further focus on alternative strategies that bypass need allowing researchers interpret global metabolic patterns pinpoint key signals. methods include molecular networking, distance‐based approaches, information theory–based metrics, discriminant analysis. Additionally, explore practical applications science highlight set useful tools support analyzing complex metabolomics data. By adopting can enhance uncover new insights into metabolism.

Язык: Английский

Процитировано

0
Dereplication of secondary metabolites from Sophora flavescens using an LC–MS/MS-based molecular networking strategy DOI Creative Commons
Hua Wang, Hui Ding

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Март 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.

Язык: Английский

Процитировано

0
Combined LC-MS/MS feature grouping, statistical prioritization, and interactive networking in msFeaST DOI Creative Commons
Kevin Mildau,

Christoph Büschl,

Jürgen Zanghellini

и другие.

Bioinformatics, Год журнала: 2024, Номер 40(10)

Опубликована: Сен. 26, 2024

Abstract Summary Computational metabolomics workflows have revolutionized the untargeted field. However, organization and prioritization of metabolite features remains a laborious process. Organizing data is often done through mass fragmentation-based spectral similarity grouping, resulting in feature sets that also represent an intuitive scientifically meaningful first stage analysis metabolomics. Exploiting such sets, feature-set testing has emerged as approach widely used genomics targeted pathway enrichment analyses. It allows for formally combining groupings with statistical into more conclusions. Here, we present msFeaST (mass Feature Set Testing), visualization workflow LC-MS/MS data. Feature-set involves statistically assessing differential abundance patterns groups across experimental conditions. We developed to make use similarity-based generated using k-medoids clustering, where clusters serve proxy grouping structurally similar potential biosynthesis relationships. Spectral clustering this way group-wise globaltest package, which provides high power detect small concordant effects via joint modeling reduced multiplicity adjustment penalties. Hence, interactive integration semi-quantitative information mass-spectral structural information, enhancing during exploratory analysis. Availability implementation The freely available https://github.com/kevinmildau/msFeaST built work on MacOS Linux systems.

Язык: Английский

Процитировано

1
Effective data visualization strategies in untargeted metabolomics DOI Creative Commons
Kevin Mildau, Henry Ehlers, Mara Meisenburg

и другие.

Natural Product Reports, Год журнала: 2024, Номер unknown

Опубликована: Дек. 2, 2024

Covering: 2014 to 2023 for metabolomics, 2002 information visualizationLC-MS/MS-based untargeted metabolomics is a rapidly developing research field spawning increasing numbers of computational tools assisting researchers with their complex data processing, analysis, and interpretation tasks. In this article, we review the entire workflow from perspective visualization, visual analytics integration. Data visualization crucial step at every stage workflow, where it provides core components inspection, evaluation, sharing capabilities. However, due large number available analysis corresponding components, hard both users developers get an overview what already which are suitable analysis. addition, there little cross-pollination between fields leaving be designed in secondary mostly ad hoc fashion. With review, aim bridge gap visualization. First, introduce as topic worthy its own dedicated research, provide primer on cutting-edge into well active metabolomics. We extend discussion best practices they have emerged studies. Second, practical roadmap tool landscape use within field. Here, several stages commonly used strategies examples. context, will also outline promising areas further development. end set recommendations how make visualizations more effective transparent communication results.

Язык: Английский

Процитировано

1