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Metabolites
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New Tools for Metabolomics
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New Tools for Metabolomics

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Advances in Metabolomics".

Deadline for manuscript submissions: closed (31 July 2020) | Viewed by 8096

Special Issue Editors

Dr. Hamid Eghbalnia

E-Mail Website
Guest Editor
Director of Analytics, Technology Development, University of Wisconsin-Madison, Madison, WI 53706-1544, USA
Interests: NMR Spectroscopy
Prof. Dr. John L. Markley

E-Mail Website
Guest Editor
Biochemistry Department, University of Wisconsin-Madison, 433 Babcock Drive, Madison, WI 53706, USA
Interests: metabolomics; Structural Genomics; NMR spectroscopy and its biological applications; structure function relationships in protein

Special Issue Information

Dear Colleagues,

Metabolomics, the process of identifying and quantifying metabolites within a cell, tissue, or organism, provides functional information that represents the sum of actions by genes, RNA, proteins, and external factors. The richness of metabolic information has stimulated research for more than a century, but the technology for delivering more comprehensive data about metabolic components and the corresponding pathway dynamics has only been available for a short time. Nuclear magnetic resonance (NMR) spectroscopy, high-resolution mass spectrometry, integration of methodologies and tools, and powerful software tools have led to rapid advances and accelerated research opportunities. In this Special Edition, we have invited a selection of emerging techniques, established methodologies, and technological innovations in order to provide a timely overview of the current state-of-the-art. By inviting authors that represent a diverse cross-section of research efforts in the field, this issue aims to forecast a vision for the future of tools, methodologies, and technologies that will advance the state-of-the-art of research in the field.

Dr. Hamid Eghbalnia
Prof. Dr. John L. Markley
Guest Editors

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.

Published Papers (2 papers)

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Research

13 pages, 1905 KiB  
Article
Evaluation of Non-Uniform Sampling 2D 1H–13C HSQC Spectra for Semi-Quantitative Metabolomics
by Bo Zhang, Robert Powers and Elizabeth M. O’Day
Metabolites 2020, 10(5), 203; https://doi.org/10.3390/metabo10050203 - 16 May 2020
Cited by 15 | Viewed by 3814
Abstract
Metabolomics is the comprehensive study of metabolism, the biochemical processes that sustain life. By comparing metabolites between healthy and disease states, new insights into disease mechanisms can be uncovered. NMR is a powerful analytical method to detect and quantify metabolites. Standard one-dimensional (1D) [...] Read more.
Metabolomics is the comprehensive study of metabolism, the biochemical processes that sustain life. By comparing metabolites between healthy and disease states, new insights into disease mechanisms can be uncovered. NMR is a powerful analytical method to detect and quantify metabolites. Standard one-dimensional (1D) 1H-NMR metabolite profiling is informative but challenged by significant chemical shift overlap. Multi-dimensional NMR can increase resolution, but the required long acquisition times lead to limited throughput. Non-uniform sampling (NUS) is a well-accepted mode of acquiring multi-dimensional NMR data, enabling either reduced acquisition times or increased sensitivity in equivalent time. Despite these advantages, the technique is not widely applied to metabolomics. In this study, we evaluated the utility of NUS 1H–13C heteronuclear single quantum coherence (HSQC) for semi-quantitative metabolomics. We demonstrated that NUS improved sensitivity compared to uniform sampling (US). We verified that the NUS measurement maintains linearity, making it possible to detect metabolite changes across samples and studies. Furthermore, we calculated the lower limit of detection and quantification (LOD/LOQ) of common metabolites. Finally, we demonstrate that the measurements are repeatable on the same system and across different systems. In conclusion, our results detail the analytical capability of NUS and, in doing so, empower the future use of NUS 1H–13C HSQC in metabolomic studies. Full article
(This article belongs to the Special Issue New Tools for Metabolomics)
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13 pages, 1753 KiB  
Article
Untargeted Metabolomics and Steroid Signatures in Urine of Male Pattern Baldness Patients after Finasteride Treatment for a Year
by Yu Ra Lee, Eunju Im, Haksoon Kim, Bark Lynn Lew, Woo-Young Sim, Jeongae Lee, Han Bin Oh, Ki Jung Paeng, Jongki Hong and Bong Chul Chung
Metabolites 2020, 10(4), 131; https://doi.org/10.3390/metabo10040131 - 30 Mar 2020
Cited by 10 | Viewed by 3963
Abstract
Male pattern baldness (MPB) has been associated with dihydrotestosterone (DHT) expression. Finasteride treats MPB by inhibiting 5-alpha reductase and blocking DHT production. In this study, we aimed to identify metabolic differences in urinary metabolomics profiles between MPB patients after a one-year treatment with [...] Read more.
Male pattern baldness (MPB) has been associated with dihydrotestosterone (DHT) expression. Finasteride treats MPB by inhibiting 5-alpha reductase and blocking DHT production. In this study, we aimed to identify metabolic differences in urinary metabolomics profiles between MPB patients after a one-year treatment with finasteride and healthy controls. Untargeted and targeted metabolomics profiling was performed using liquid chromatography-mass spectrometry (LC-MS). We hypothesized that there would be changes in overall metabolite concentrations, especially steroids, in the urine of hair loss patients treated with finasteride and normal subjects. Untargeted analysis indicated differences in steroid hormone biosynthesis. Therefore, we conducted targeted profiling for steroid hormone biosynthesis to identify potential biomarkers, especially androgens and estrogens. Our study confirmed the differences in the concentration of urinary androgens and estrogens between healthy controls and MPB patients. Moreover, the effect of finasteride was confirmed by the DHT/T ratio in urine samples of MPB patients. Our metabolomics approach provided insight into the physiological alterations in MPB patients who have been treated with finasteride for a year and provided evidence for the association of finasteride and estrogen levels. Through a targeted approach, our results suggest that urinary estrogens must be studied in relation to MPB and post-finasteride syndrome. Full article
(This article belongs to the Special Issue New Tools for Metabolomics)
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