Metabolites

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Special Issue Editor

Special Issue Information

Dear Colleagues,

Metabolomics and lipidomics, making up the largest part of metabolomics, have become valuable tools for researchers to enhance our understanding of disease mechanisms and drug effects, as well as for improving our ability to predict individual variation in drug response phenotypes and shape more targeted responses. Metabolomics and lipidomics have the potential to make a powerful impact in pharmaceutical and clinical research, including in the identification of new targets, the elucidation of the mechanism of action of new drugs, the development of safety and efficacy profiles, and the discovery of biomarkers for early disease diagnosis and treatment. In addition, refinements in the identification and characterization of new biomarkers will allow earlier and more accurate diagnosis and prevention of many diseases, which in turn, will be valuable in the discovery of new drugs for both prevention and treatment. The most widely used analytical tools for metabolomics and lipidomics include NMR, LC–MS/MS and GC–MS/MS. Their impacts are expanding dramatically as the use of these and other technologies grows throughout the spectrum of drug discovery and development, and as their applications broaden. For example, technological advances now enable simultaneous, quantitative analysis of hundreds of lipid and metabolite species, allowing researchers to unravel the close interconnection between altered metabolism and pathogenic processes.

This Special Issue is devoted to metabolomics and lipidomics studies to aid in the research on disease mechanisms and on biomarker discovery and drug development. These technologies and their ever-expanding applications are proving to be great tools for biomarker discovery and validation, although many challenges need to be addressed. These impediments include proper selection and preparation of samples, human error, reliability and reproducibility of metabolites, biological pathway identification, and replication across populations, along with ever-more complex statistical data analysis and integration.

Dr. Ala F. Nassar
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metabolites is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

mass spectrometry
lipidomics
metabolomics
single-cell analysis
metabolism
pharmacology

Published Papers (2 papers)

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Research

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16 pages, 2107 KiB

Open AccessArticle

The Metabolic and Lipidomic Fingerprint of Torin1 Exposure in Mouse Embryonic Fibroblasts Using Untargeted Metabolomics

by Rani Robeyns, Angela Sisto, Elias Iturrospe, Katyeny Manuela da Silva, Maria van de Lavoir, Vincent Timmerman, Adrian Covaci, Sigrid Stroobants and Alexander L. N. van Nuijs

Metabolites 2024, 14(5), 248; https://doi.org/10.3390/metabo14050248 - 25 Apr 2024

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Abstract

Torin1, a selective kinase inhibitor targeting the mammalian target of rapamycin (mTOR), remains widely used in autophagy research due to its potent autophagy-inducing abilities, regardless of its unspecific properties. Recognizing the impact of mTOR inhibition on metabolism, our objective was to develop a reliable and thorough untargeted metabolomics workflow to study torin1-induced metabolic changes in mouse embryonic fibroblast (MEF) cells. Crucially, our quality assurance and quality control (QA/QC) protocols were designed to increase confidence in the reported findings by reducing the likelihood of false positives, including a validation experiment replicating all experimental steps from sample preparation to data analysis. This study investigated the metabolic fingerprint of torin1 exposure by using liquid chromatography—high resolution mass spectrometry (LC-HRMS)-based untargeted metabolomics platforms. Our workflow identified 67 altered metabolites after torin1 exposure, combining univariate and multivariate statistics and the implementation of a validation experiment. In particular, intracellular ceramides, diglycerides, phosphatidylcholines, phosphatidylethanolamines, glutathione, and 5′-methylthioadenosine were downregulated. Lyso-phosphatidylcholines, lyso-phosphatidylethanolamines, glycerophosphocholine, triglycerides, inosine, and hypoxanthine were upregulated. Further biochemical pathway analyses provided deeper insights into the reported changes. Ultimately, our study provides a valuable workflow that can be implemented for future investigations into the effects of other compounds, including more specific autophagy modulators. Full article

(This article belongs to the Special Issue Mass Spectrometry-Based Metabolomics and Lipidomics for Biomarker Discovery and Drug Development)

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Review

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16 pages, 6181 KiB

Open AccessReview

Matrix- and Surface-Assisted Laser Desorption/Ionization Mass Spectrometry Methods for Urological Cancer Biomarker Discovery—Metabolomics and Lipidomics Approaches

by Adrian Arendowski

Metabolites 2024, 14(3), 173; https://doi.org/10.3390/metabo14030173 - 20 Mar 2024

Viewed by 1044

Abstract

Urinary tract cancers, including those of the bladder, the kidneys, and the prostate, represent over 12% of all cancers, with significant global incidence and mortality rates. The continuous challenge that these cancers present necessitates the development of innovative diagnostic and prognostic methods, such as identifying specific biomarkers indicative of cancer. Biomarkers, which can be genes, proteins, metabolites, or lipids, are vital for various clinical purposes including early detection and prognosis. Mass spectrometry (MS), particularly soft ionization techniques such as electrospray ionization (ESI) and laser desorption/ionization (LDI), has emerged as a key tool in metabolic profiling for biomarker discovery, due to its high resolution, sensitivity, and ability to analyze complex biological samples. Among the LDI techniques, matrix-assisted laser desorption/ionization (MALDI) and surface-assisted laser desorption/ionization (SALDI) should be mentioned. While MALDI methodology, which uses organic compounds as matrices, is effective for larger molecules, SALDI, based on the various types of nanoparticles and nanostructures, is preferred for smaller metabolites and lipids due to its reduced spectral interference. This study highlights the application of LDI techniques, along with mass spectrometry imaging (MSI), in identifying potential metabolic and lipid biomarkers for urological cancers, focusing on the most common bladder, kidney, and prostate cancers. Full article

(This article belongs to the Special Issue Mass Spectrometry-Based Metabolomics and Lipidomics for Biomarker Discovery and Drug Development)

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