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Metabolites
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Integration of Emerging Technologies in Metabolite Analysis
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Integration of Emerging Technologies in Metabolite Analysis

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Metabolomic Profiling Technology".

Deadline for manuscript submissions: 31 July 2025 | Viewed by 2375

Special Issue Editor

Dr. Kumari Ubhayasekera

E-Mail Website
Guest Editor
Department of Chemistry—Biomedical Center (BMC), Box 599, Uppsala University, 751 24 Uppsala, Sweden
Interests: gas chromatography; liquid chromatography; mass spectrometry; metabolomics; NMR; smaller molecules; supercritical chromatography

Special Issue Information

Dear Colleagues,

In recent years, the field of metabolomics has witnessed rapid developments powered by the integration of novel technologies. This Special Issue aims to explore the application of emerging technologies in metabolite analysis, shedding light on their potential to revolutionize our understanding of metabolic processes and their implications for human health and disease.

The contributions to this Special Issue include a diverse array of methodologies and approaches, from mass spectrometry and nuclear magnetic resonance spectroscopy with chromatographic techniques. These technologies offer unique sensitivity, resolution, and throughput, enabling comprehensive profiling of metabolites in complex biological systems.

Furthermore, this Special Issue highlights the innovative strategies developed for metabolite identification, quantification, and data analysis, including metabolic pathway modeling, and multi-omics integration. By connecting the power of these cutting-edge technologies, researchers can unravel complex metabolic networks, uncover biomarkers of disease, and accelerate the discovery of therapeutic targets.

Moreover, the articles featured in this Special Issue explore the application of metabolomics in various research domains, such as cancer biology, drug discovery, environmental science, and personalized medicine. By elucidating the dynamic interplay between metabolites and physiological processes, these studies cover the way for the development of precision diagnostics and tailored interventions for metabolic disorders.

In conclusion, this Special Issue provides a comprehensive overview of the latest advancements in metabolite analysis, highlighting the transformative impact of emerging technologies on the field of metabolomics. Through collaborative efforts and interdisciplinary approaches, researchers can attach these innovations to address fundamental questions in biology and medicine, ultimately improving human health and well-being.

Dr. Kumari Ubhayasekera
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

  • liquid chromatography
  • mass spectrometry
  • NMR
  • metabolomics
  • smaller molecules
  • supercritical chromatography
  • gas chromatography

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Published Papers (2 papers)

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19 pages, 10209 KiB  
Article
Urine Metabolomic Patterns to Discriminate the Burnout Levels and Night-Shift-Related Stress in Healthcare Professionals
by Andreea Petra Ungur, Andreea-Iulia Socaciu, Maria Barsan, Armand Gabriel Rajnoveanu, Razvan Ionut, Carmen Socaciu and Lucia Maria Procopciuc
Metabolites 2025, 15(4), 273; https://doi.org/10.3390/metabo15040273 - 14 Apr 2025
Viewed by 464
Abstract
Burnout syndrome, which significantly impacts both individual and societal quality of life, is primarily characterized by three key criteria: depersonalization, emotional exhaustion, and low personal accomplishment, all linked to work-related stress. Purpose: Comparative evaluation of urine metabolite patterns that may discriminate the [...] Read more.
Burnout syndrome, which significantly impacts both individual and societal quality of life, is primarily characterized by three key criteria: depersonalization, emotional exhaustion, and low personal accomplishment, all linked to work-related stress. Purpose: Comparative evaluation of urine metabolite patterns that may discriminate the burnout levels and the effects of night shifts on healthcare professionals. The Maslach Burnout Inventory survey was administered to 64 physicians and nurses working day and night shifts, with scores for each criterion recorded. Methods: Urine samples were collected, and metabolomic patterns were analyzed using UHPLC-QTOF-ESI+-MS technology. This analysis employed both untargeted and semi-targeted metabolomics, coupled with multivariate and ANOVA statistics, utilizing the online Metaboanalyst 6.0 platform. Partial Least Squares Discriminant Analysis (PLSDA) was performed, along with VIP values, Random Forest graphs, and heatmaps based on 79 identified metabolites. These were further complemented by biomarker analysis (AUC ranking) and pathway analysis of metabolic networks. Results: The findings highlighted the biochemical effects of night shifts and their correlation with burnout scores from each dimension. Conclusions: This study demonstrated the involvement of three major metabolic pathways in diagnosing burnout: lipid metabolism, particularly related to steroid hormones (cortisol, cortisone, and androsterone metabolites); energetic metabolism, involving long-chain acylated carnitines as transporters of free fatty acids, which play a role in burnout control; and a third pathway affecting catecholamine metabolism (neurotransmitters derived from tyrosine, such as dopamine, adrenaline, and noradrenaline), as well as tryptophan metabolism (serotonin and melatonin metabolites) and amino acid metabolism (including aspartate, arginine, and valine). Full article
(This article belongs to the Special Issue Integration of Emerging Technologies in Metabolite Analysis)
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14 pages, 1907 KiB  
Article
Online Direct Infusion Mass Spectrometry of Liquid–Liquid Extraction Phases for Metabolite and Lipid Profiling with the Direct Infusion Probe
by Cátia Marques, Lena Blaase and Ingela Lanekoff
Metabolites 2024, 14(11), 587; https://doi.org/10.3390/metabo14110587 - 30 Oct 2024
Viewed by 1345
Abstract
Background/Objectives: Profiling of metabolites and lipids in biological samples can provide invaluable insights into life-sustaining chemical processes. The ability to detect both metabolites and lipids in the same sample can enhance these understandings and connect cellular dynamics. However, simultaneous detection of metabolites and [...] Read more.
Background/Objectives: Profiling of metabolites and lipids in biological samples can provide invaluable insights into life-sustaining chemical processes. The ability to detect both metabolites and lipids in the same sample can enhance these understandings and connect cellular dynamics. However, simultaneous detection of metabolites and lipids is generally hampered by chromatographic systems tailored to one molecular type. This void can be filled by direct infusion mass spectrometry (MS), where all ionizable molecules can be detected simultaneously. However, in direct infusion MS, the high chemical complexity of biological samples can introduce limitations in detectability due to matrix effects causing ionization suppression. Methods: Decreased sample complexity and increased detectability and molecular coverage was provided by combining our direct infusion probe (DIP) with liquid–liquid extraction (LLE) and directly sampling the different phases for direct infusion. Three commonly used LLE methods for separating lipids and metabolites were evaluated. Results: The butanol–methanol (BUME) method was found to be preferred since it provides high molecular coverage and have low solvent toxicity. The established BUME DIP-MS method was used as a fast and sensitive analysis tool to study chemical changes in insulin-secreting cells upon glucose stimulation. By analyzing the metabolome at distinct time points, down to 1-min apart, we found high dynamics of the intracellular metabolome. Conclusions: The rapid workflow with LLE DIP-MS enables higher sensitivity of phase separated metabolites and lipids. The application of BUME DIP-MS provides novel information on the dynamics of the intracellular metabolome of INS-1 during the two phases of insulin release for both metabolite and lipid classes. Full article
(This article belongs to the Special Issue Integration of Emerging Technologies in Metabolite Analysis)
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