Advances in Cellular Metabolomics

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Cell Metabolism".

Deadline for manuscript submissions: closed (15 March 2021) | Viewed by 6400

Special Issue Editors


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Guest Editor
Institute of Functional Genomics, University of Regensburg, Am BioPark 9, 93053 Regensburg, Germany
Interests: metabolomics; small molecule analysis; separation science; hyphenated mass spectrometry; sample preparation for metabolomics; cancer
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Institute of Functional Genomics, University of Regensburg, Am BioPark 9, 93053 Regensburg, Germany
Interests: metabolomics; hyphenated mass spectrometry; cancer metabolism; tracing analysis

Special Issue Information

Dear Colleagues,

Shifts in cellular function are often accompanied by alterations of cellular metabolism, and numerous links to pathology, carcinogenesis and the immune response have been identified in recent years. A prominent example is the altered metabolism in cancer cells to meet the increased energy need and the requirement for cellular building blocks. Metabolic profiling and fingerprinting using various instrumental set ups have evolved as valuable tools for studying metabolism and tremendously increased our knowledge on cellular metabolism. Both targeted and untargeted approaches, however, only reflect a cell’s metabolic state, e.g., a metabolite pool size at the time point of sample collection. To gain further insights, tracing and flux analyses using stable-isotope-labeled nutrients are used to reveal changes in pathway activities and contributions. These experiments are typically performed with cells in culture.

Over the past years, huge progress has been made in the field of cellular metabolomics, including sample preparation and technical improvements, such as ion mobility-MS, single cell analysis and imaging techniques together with new algorithms and biostatistics tools to handle the data sets. This Special Issue of Metabolites “Advances in Cellular Metabolomics” is dedicated to these developments that have resulted in new insights into the interplay of cellular function and metabolism gained from the comprehensive analysis of cellular metabolites. Reviews and research manuscripts dealing with these and related issues are highly welcomed.

Dr. Katja Dettmer-Wilde
Dr. Raffaela Berger
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.

Keywords

  • (Un-)targeted metabolomics
  • Metabolic flux and tracer analysis
  • Multivariate biostatistics analysis
  • Cell metabolism
  • Chromatography
  • Enantioselective analysis

Published Papers (2 papers)

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Research

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11 pages, 2358 KiB  
Article
Robust Metabolite Quantification from J-Compensated 2D 1H-13C-HSQC Experiments
by Alexander Weitzel, Claudia Samol, Peter J. Oefner and Wolfram Gronwald
Metabolites 2020, 10(11), 449; https://doi.org/10.3390/metabo10110449 - 7 Nov 2020
Cited by 5 | Viewed by 2134
Abstract
The spectral resolution of 2D 1H-13C heteronuclear single quantum coherence (1H-13C-HSQC) nuclear magnetic resonance (NMR) spectra facilitates both metabolite identification and quantification in nuclear magnetic resonance-based metabolomics. However, quantification is complicated by variations in magnetization transfer, [...] Read more.
The spectral resolution of 2D 1H-13C heteronuclear single quantum coherence (1H-13C-HSQC) nuclear magnetic resonance (NMR) spectra facilitates both metabolite identification and quantification in nuclear magnetic resonance-based metabolomics. However, quantification is complicated by variations in magnetization transfer, which among others originate mainly from scalar coupling differences. Methods that compensate for variation in scalar coupling include the generation of calibration factors for individual signals or the use of additional pulse sequence schemes such as quantitative HSQC (Q-HSQC) that suppress the JCH-dependence by modulating the polarization transfer delays of HSQC or, additionally, employ a pure-shift homodecoupling approach in the 1H dimension, such as Quantitative, Perfected and Pure Shifted HSQC (QUIPU-HSQC). To test the quantitative accuracy of these three methods, employing a 600 MHz NMR spectrometer equipped with a helium cooled cryoprobe, a Latin-square design that covered the physiological concentration ranges of 10 metabolites was used. The results show the suitability of all three methods for the quantification of highly abundant metabolites. However, the substantially increased residual water signal observed in QUIPU-HSQC spectra impeded the quantification of low abundant metabolites located near the residual water signal, thus limiting its utility in high-throughput metabolite fingerprinting studies. Full article
(This article belongs to the Special Issue Advances in Cellular Metabolomics)
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Review

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28 pages, 9935 KiB  
Review
Glioblastoma Metabolomics—In Vitro Studies
by Karol Jaroch, Paulina Modrakowska and Barbara Bojko
Metabolites 2021, 11(5), 315; https://doi.org/10.3390/metabo11050315 - 13 May 2021
Cited by 11 | Viewed by 3777
Abstract
In 2016, the WHO introduced new guidelines for the diagnosis of brain gliomas based on new genomic markers. The addition of these new markers to the pre-existing diagnostic methods provided a new level of precision for the diagnosis of glioma and the prediction [...] Read more.
In 2016, the WHO introduced new guidelines for the diagnosis of brain gliomas based on new genomic markers. The addition of these new markers to the pre-existing diagnostic methods provided a new level of precision for the diagnosis of glioma and the prediction of treatment effectiveness. Yet, despite this new classification tool, glioblastoma (GBM), a grade IV glioma, continues to have one of the highest mortality rates among central nervous system tumors. Metabolomics is a particularly promising tool for the analysis of GBM tumors and potential methods of treating them, as it is the only “omics” approach that is capable of providing a metabolic signature of a tumor’s phenotype. With careful experimental design, cell cultures can be a useful matrix in GBM metabolomics, as they ensure stable conditions and, under proper conditions, are capable of capturing different tumor phenotypes. This paper reviews in vitro metabolomic profiling studies of high-grade gliomas, with a particular focus on sample-preparation techniques, crucial metabolites identified, cell culture conditions, in vitro-in vivo extrapolation, and pharmacometabolomics. Ultimately, this review aims to elucidate potential future directions for in vitro GBM metabolomics. Full article
(This article belongs to the Special Issue Advances in Cellular Metabolomics)
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