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Metabolites
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Advances in Metabolic Profiling of Biological Samples 2nd Edition
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Advances in Metabolic Profiling of Biological Samples 2nd Edition

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

Deadline for manuscript submissions: 31 May 2024 | Viewed by 4703

Special Issue Editor

Dr. Joana Pinto

E-Mail Website
Guest Editor
1. Associate Laboratory i4HB–Institute for Health and Bioeconomy, University of Porto, 4050-313 Porto, Portugal
2. UCIBIO—Applied Molecular Biosciences Unit, Laboratory of Toxicology, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
Interests: targeted and untargeted metabolomics; GC-MS; NMR; biomarker discovery; cancer
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Metabolomics has been a powerful approach for studying low-molecular-weight metabolites and their interactions within a biological system in a wide range of research fields (e.g., clinical and biomedical research, toxicology, microbiology, nutrition, environment). The biological samples analysed include blood serum/plasma, urine, tissues, cells, saliva, cerebrospinal fluid, and faeces, among others. Due to the chemical diversity and concentration range of all metabolites present in biological samples, there are still several challenges from sample collection to metabolite annotation that need to be addressed. This Special Issue of Metabolites is dedicated to reviews and original articles covering the current methodological and technological advancements on the pre-analytical handling of biological samples, sample preparation protocols, analytical approaches for untargeted and targeted metabolic profiling, data quality assessment in large-scale metabolomics studies, and data processing and metabolite annotation tools. Manuscripts dealing with current methodological and technological advancements on metabolomics branches (e.g., lipidomics, volatilomics, fluxomics) and other challenging issues are also welcomed.

Dr. Joana Pinto
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

  • metabolomics
  • lipidomics
  • volatilomics
  • fluxomics
  • biological samples
  • pre-analytical handling
  • sample preparation techniques
  • analytical approaches
  • data processing
  • metabolite annotation

Published Papers (4 papers)

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Research

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13 pages, 3523 KiB  
Article
Direct Infusion Mass Spectrometry to Rapidly Map Metabolic Flux of Substrates Labeled with Stable Isotopes
by Nils W. F. Meijer, Susan Zwakenberg, Johan Gerrits, Denise Westland, Arif I. Ardisasmita, Sabine A. Fuchs, Nanda M. Verhoeven-Duif, Judith J. M. Jans and Fried J. T. Zwartkruis
Metabolites 2024, 14(5), 246; https://doi.org/10.3390/metabo14050246 - 25 Apr 2024
Viewed by 225
Abstract
Direct infusion–high-resolution mass spectrometry (DI-HRMS) allows for rapid profiling of complex mixtures of metabolites in blood, cerebrospinal fluid, tissue samples and cultured cells. Here, we present a DI-HRMS method suitable for the rapid determination of metabolic fluxes of isotopically labeled substrates in cultured [...] Read more.
Direct infusion–high-resolution mass spectrometry (DI-HRMS) allows for rapid profiling of complex mixtures of metabolites in blood, cerebrospinal fluid, tissue samples and cultured cells. Here, we present a DI-HRMS method suitable for the rapid determination of metabolic fluxes of isotopically labeled substrates in cultured cells and organoids. We adapted an automated annotation pipeline by selecting labeled adducts that best represent the majority of 13C and/or 15N-labeled glycolytic and tricarboxylic acid cycle intermediates as well as a number of their derivatives. Furthermore, valine, leucine and several of their degradation products were included. We show that DI-HRMS can determine anticipated and unanticipated alterations in metabolic fluxes along these pathways that result from the genetic alteration of single metabolic enzymes, including pyruvate dehydrogenase (PDHA1) and glutaminase (GLS). In addition, it can precisely pinpoint metabolic adaptations to the loss of methylmalonyl-CoA mutase in patient-derived liver organoids. Our results highlight the power of DI-HRMS in combination with stable isotopically labeled compounds as an efficient screening method for fluxomics. Full article
(This article belongs to the Special Issue Advances in Metabolic Profiling of Biological Samples 2nd Edition)
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14 pages, 1963 KiB  
Article
Advancing Personalized Medicine by Analytical Means: Selection of Three Metabolites That Allows Discrimination between Glaucoma, Diabetes, and Controls
by David Bernal-Casas, Joan Serrano-Marín, Juan Sánchez-Navés, Josep M. Oller and Rafael Franco
Metabolites 2024, 14(3), 149; https://doi.org/10.3390/metabo14030149 - 29 Feb 2024
Viewed by 1128
Abstract
This paper aimed at devising an intelligence-based method to select compounds that can distinguish between open-angle glaucoma patients, type 2 diabetes patients, and healthy controls. Taking the concentration of 188 compounds measured in the aqueous humour (AH) of patients and controls, linear discriminant [...] Read more.
This paper aimed at devising an intelligence-based method to select compounds that can distinguish between open-angle glaucoma patients, type 2 diabetes patients, and healthy controls. Taking the concentration of 188 compounds measured in the aqueous humour (AH) of patients and controls, linear discriminant analysis (LDA) was used to identify the right combination of compounds that could lead to accurate diagnosis. All possibilities, using the leave-one-out approach, were considered through ad hoc programming and in silico massive data production and statistical analysis. Our proof of concept led to the selection of four molecules: acetyl-ornithine (Ac-Orn), C3 acyl-carnitine (C3), diacyl C42:6 phosphatidylcholine (PC aa C42:6), and C3-DC (C4-OH) acyl-carnitine (C3-DC (C4-OH)) that, taken in combination, would lead to a 95% discriminative success. 100% success was obtained with a non-linear combination of the concentration of three of these four compounds. By discarding younger controls to adjust by age, results were similar although one control was misclassified as a diabetes patient. Methods based on the consideration of individual clinical chemical parameters have limitations in the ability to make a reliable diagnosis, stratify patients, and assess disease progression. Leveraging human AH metabolomic data, we developed a procedure that selects a minimal number of metabolites (3–5) and designs algorithms that maximize the overall accuracy evaluating both positive predictive (PPV) and negative predictive (NPV) values. Our approach of simultaneously considering the levels of a few metabolites can be extended to any other body fluid and has potential to advance precision medicine. Artificial intelligence is expected to use algorithms that use the concentration of three to five molecules to correctly diagnose diseases, also allowing stratification of patients and evaluation of disease progression. In addition, this significant advance shifts focus from a single-molecule biomarker approach to that of an appropriate combination of metabolites. Full article
(This article belongs to the Special Issue Advances in Metabolic Profiling of Biological Samples 2nd Edition)
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Review

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22 pages, 1737 KiB  
Review
Revolutionizing Blood Collection: Innovations, Applications, and the Potential of Microsampling Technologies for Monitoring Metabolites and Lipids
by Eleonora Bossi, Elena Limo, Lisa Pagani, Nicole Monza, Simone Serrao, Vanna Denti, Giuseppe Astarita and Giuseppe Paglia
Metabolites 2024, 14(1), 46; https://doi.org/10.3390/metabo14010046 - 11 Jan 2024
Cited by 2 | Viewed by 1587
Abstract
Blood serves as the primary global biological matrix for health surveillance, disease diagnosis, and response to drug treatment, holding significant promise for personalized medicine. The diverse array of lipids and metabolites in the blood provides a snapshot of both physiological and pathological processes, [...] Read more.
Blood serves as the primary global biological matrix for health surveillance, disease diagnosis, and response to drug treatment, holding significant promise for personalized medicine. The diverse array of lipids and metabolites in the blood provides a snapshot of both physiological and pathological processes, with many routinely monitored during conventional wellness checks. The conventional method involves intravenous blood collection, extracting a few milliliters via venipuncture, a technique limited to clinical settings due to its dependence on trained personnel. Microsampling methods have evolved to be less invasive (collecting ≤150 µL of capillary blood), user-friendly (enabling self-collection), and suitable for remote collection in longitudinal studies. Dried blood spot (DBS), a pioneering microsampling technique, dominates clinical and research domains. Recent advancements in device technology address critical limitations of classical DBS, specifically variations in hematocrit and volume. This review presents a comprehensive overview of state-of-the-art microsampling devices, emphasizing their applications and potential for monitoring metabolites and lipids in blood. The scope extends to diverse areas, encompassing population studies, nutritional investigations, drug discovery, sports medicine, and multi-omics research. Full article
(This article belongs to the Special Issue Advances in Metabolic Profiling of Biological Samples 2nd Edition)
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24 pages, 866 KiB  
Review
Volumetric Absorptive Microsampling in the Analysis of Endogenous Metabolites
by Daniel Marques de Sá e Silva, Marlene Thaitumu, Georgios Theodoridis, Michael Witting and Helen Gika
Metabolites 2023, 13(10), 1038; https://doi.org/10.3390/metabo13101038 - 26 Sep 2023
Viewed by 1248
Abstract
Volumetric absorptive microsampling (VAMS) has arisen as a relevant tool in biological analysis, offering simplified sampling procedures and enhanced stability. Most of the attention VAMS has received in the past decade has been from pharmaceutical research, with most of the published work employing [...] Read more.
Volumetric absorptive microsampling (VAMS) has arisen as a relevant tool in biological analysis, offering simplified sampling procedures and enhanced stability. Most of the attention VAMS has received in the past decade has been from pharmaceutical research, with most of the published work employing VAMS targeting drugs or other exogenous compounds, such as toxins and pollutants. However, biomarker analysis by employing blood microsampling has high promise. Herein, a comprehensive review on the applicability of VAMS devices for the analysis of endogenous metabolites/biomarkers was performed. The study presents a full overview of the analysis process, incorporating all the steps in sample treatment and validation parameters. Overall, VAMS devices have proven to be reliable tools for the analysis of endogenous analytes with biological importance, often offering improved analyte stability in comparison with blood under ambient conditions as well as a convenient and straightforward sample acquisition model. Full article
(This article belongs to the Special Issue Advances in Metabolic Profiling of Biological Samples 2nd Edition)
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