LC-MS Method Development and Metabolomics Data Analysis

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Bioinformatics and Data Analysis".

Deadline for manuscript submissions: closed (30 July 2024) | Viewed by 1435

Special Issue Editors


E-Mail Website
Guest Editor
EMSL, Pacific Northwest National Laboratory, Richland, WA 99354, USA
Interests: LC–MS; GC–MS; NMR metabolomics and structural elucidation

E-Mail Website
Guest Editor
Pacific Northwest National Laboratory, Richland, WA 99354, USA
Interests: statistical and machine learning methods for omics data; data integration; biomarker discovery

Special Issue Information

Dear Colleagues,

Liquid chromatography–mass spectrometry (LC–MS) is an important analytical platform in metabolomics and lipidomics research, providing an essential and robust toolset for elucidating the complexities of biological systems. This remains the case even as other techniques like Nuclear Magnetic Resonance (NMR) and Gas Chromatography–Mass Spectrometry (GC–MS) offer their own unique advantages and contributions to this growing field. With the advent of increasingly sophisticated LC–MS methodologies, researchers are gaining a better understanding of metabolic pathways and systematic biological changes.

This Special Issue explores the advancements in LC–MS metabolomics, the introduction of new chromatographic methods, and the innovations in spectral deconvolution. Furthermore, it is devoted to spotlighting advances in LC–MS data analytics and data visualization. Though the primary focus is LC–MS metabolomics, this Special Issue is also open to topics that include the use of important analytical platforms like NMR and GC–MS and their respective data analysis strategies. In fact, of particular interest is how these other platforms can work together with LC–MS to gain a richer, more nuanced understanding of metabolic pathways and systematic biological changes.

Dr. Chaevien S. Clendinen
Dr. Lisa Bramer
Guest Editors

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Keywords

  • LC–MS
  • data visualization
  • mass spectrometry
  • NMR
  • chromatography
  • metabolomics
  • lipidomics

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Published Papers (1 paper)

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Research

12 pages, 2303 KiB  
Article
LC-QToF-MS Analysis of Stimulant Drugs and Their Metabolites in Wastewater During Football Games
by Brandon J. Stamper, Krishna Chaturvedi, Bharathi Avula, Ji-Yeong Bae, Yan-Hong Wang, Kyle S. Bledsoe, Ikhlas A. Khan and Murrell Godfrey
Metabolites 2025, 15(2), 69; https://doi.org/10.3390/metabo15020069 - 22 Jan 2025
Viewed by 933
Abstract
Background: The use of illicit drugs and stimulants is a burgeoning socioeconomic problem, ultimately leading to an increase in street crimes and deteriorating human health. The persistent presence of CNS drugs in wastewater can also lead to downstream adverse effects on aquatic wildlife [...] Read more.
Background: The use of illicit drugs and stimulants is a burgeoning socioeconomic problem, ultimately leading to an increase in street crimes and deteriorating human health. The persistent presence of CNS drugs in wastewater can also lead to downstream adverse effects on aquatic wildlife and humans. Objectives: In the present study, a method was developed for the solid-phase extraction and quantitative liquid chromatography coupled with tandem quadrupole/time-of-flight mass spectrometry (LC-QToF-MS) analysis of CNS stimulant drugs and their metabolites in municipal wastewater. The targeted species included amphetamine, methamphetamine, methylenedioxy-methamphetamine (MDMA), methylenedioxyethylamphetamine (MDEA), cocaine, and benzoylecgonine (BE). Methods: The method was validated and applied to analyzing wastewater samples collected at the University of Mississippi and the City of Oxford wastewater treatment plants (WWTPs) during weekends when the university hosted home college football games. Results: Our results indicate that while amphetamine, methamphetamine, MDMA, cocaine, and BE were all detected at quantifiable levels, amphetamine and BE were present in significantly higher concentrations in wastewater during football games. Conclusion: The insights from this study can be utilized to monitor long-term drug use trends, providing local law enforcement agencies with relevant data on consumption patterns over time. Full article
(This article belongs to the Special Issue LC-MS Method Development and Metabolomics Data Analysis)
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