Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.7
3.4
Journals
Metabolites
Special Issues
10th Anniversary of Metabolites: The Changing Landscape of Metabolomics
share announcement

10th Anniversary of Metabolites: The Changing Landscape of Metabolomics

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

Deadline for manuscript submissions: closed (30 December 2020) | Viewed by 46878

Special Issue Editor

Prof. Dr. Peter Meikle

E-Mail Website
Guest Editor
Metabolomics Laboratory NHMRC, Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia
Interests: dyslipidemia associated with obesity, diabetes and cardiovascular disease and its relationship to the pathogenesis of these disease states; application of lipidomics to the early diagnosis, risk assessment and therapeutic monitoring of these most prevalent diseases
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is dedicated to celebration of the 10th anniversary of Metabolites (ISSN 2218-1989). To commemorate this milestone, we are requesting submission of reviews of the field and research papers that are "pushing the boundaries of metabolomics and lipidomics". The scope of these manuscripts should fall within the range of the mission of the journal, but is not limited to any particular themes: https://www.mdpi.com/journal/metabolites/about.

Metabolites (ISSN 2218-1989) is an open-access journal of metabolism and metabolomics, supported by an outstanding Editorial Board composed of high-profile researchers. It just received its First Impact Factor of 3.303, and is indexed by the Science Citation Index Expanded (Web of Science), PubMed Central, Scopus (CiteScore in 2018: 3.75), and other important databases. In addition, the Metabolomics Society (MetSoc) is now an affiliated society member of Metabolites.

We look forward to your contribution. Please feel free to contact us if you have any questions.

Prof. Dr. Peter Meikle
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.

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (7 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Review

18 pages, 3326 KiB  
Article
Stable Isotopic Tracer Phospholipidomics Reveals Contributions of Key Phospholipid Biosynthetic Pathways to Low Hepatocyte Phosphatidylcholine to Phosphatidylethanolamine Ratio Induced by Free Fatty Acids
by Kang-Yu Peng, Christopher K Barlow, Helene Kammoun, Natalie A Mellett, Jacquelyn M Weir, Andrew J Murphy, Mark A Febbraio and Peter J Meikle
Metabolites 2021, 11(3), 188; https://doi.org/10.3390/metabo11030188 - 22 Mar 2021
Cited by 6 | Viewed by 3141
Abstract
There is a strong association between hepatocyte phospholipid homeostasis and non-alcoholic fatty liver disease (NAFLD). The phosphatidylcholine to phosphatidylethanolamine ratio (PC/PE) often draws special attention as genetic and dietary disruptions to this ratio can provoke steatohepatitis and other signs of NAFLD. Here we [...] Read more.
There is a strong association between hepatocyte phospholipid homeostasis and non-alcoholic fatty liver disease (NAFLD). The phosphatidylcholine to phosphatidylethanolamine ratio (PC/PE) often draws special attention as genetic and dietary disruptions to this ratio can provoke steatohepatitis and other signs of NAFLD. Here we demonstrated that excessive free fatty acid (1:2 mixture of palmitic and oleic acid) alone was able to significantly lower the phosphatidylcholine to phosphatidylethanolamine ratio, along with substantial alterations to phospholipid composition in rat hepatocytes. This involved both a decrease in hepatocyte phosphatidylcholine (less prominent) and an increase in phosphatidylethanolamine, with the latter contributing more to the lowered ratio. Stable isotopic tracer phospholipidomic analysis revealed several previously unidentified changes that were triggered by excessive free fatty acid. Importantly, the enhanced cytidine diphosphate (CDP)-ethanolamine pathway activity appeared to be driven by the increased supply of preferred fatty acid substrates. By contrast, the phosphatidylethanolamine N-methyl transferase (PEMT) pathway was restricted by low endogenous methionine and consequently low S-adenosylmethionine, which resulted in a concomitant decrease in phosphatidylcholine and accumulation of phosphatidylethanolamine. Overall, our study identified several previously unreported links in the relationship between hepatocyte free fatty acid overload, phospholipid homeostasis, and the development of NAFLD. Full article
(This article belongs to the Special Issue 10th Anniversary of Metabolites: The Changing Landscape of Metabolomics)
►▼ Show Figures

Figure 1

40 pages, 2354 KiB  
Article
Using Out-of-Batch Reference Populations to Improve Untargeted Metabolomics for Screening Inborn Errors of Metabolism
by Michiel Bongaerts, Ramon Bonte, Serwet Demirdas, Edwin H. Jacobs, Esmee Oussoren, Ans T. van der Ploeg, Margreet A. E. M. Wagenmakers, Robert M. W. Hofstra, Henk J. Blom, Marcel J. T. Reinders and George J. G. Ruijter
Metabolites 2021, 11(1), 8; https://doi.org/10.3390/metabo11010008 - 25 Dec 2020
Cited by 10 | Viewed by 3259
Abstract
Untargeted metabolomics is an emerging technology in the laboratory diagnosis of inborn errors of metabolism (IEM). Analysis of a large number of reference samples is crucial for correcting variations in metabolite concentrations that result from factors, such as diet, age, and gender in [...] Read more.
Untargeted metabolomics is an emerging technology in the laboratory diagnosis of inborn errors of metabolism (IEM). Analysis of a large number of reference samples is crucial for correcting variations in metabolite concentrations that result from factors, such as diet, age, and gender in order to judge whether metabolite levels are abnormal. However, a large number of reference samples requires the use of out-of-batch samples, which is hampered by the semi-quantitative nature of untargeted metabolomics data, i.e., technical variations between batches. Methods to merge and accurately normalize data from multiple batches are urgently needed. Based on six metrics, we compared the existing normalization methods on their ability to reduce the batch effects from nine independently processed batches. Many of those showed marginal performances, which motivated us to develop Metchalizer, a normalization method that uses 10 stable isotope-labeled internal standards and a mixed effect model. In addition, we propose a regression model with age and sex as covariates fitted on reference samples that were obtained from all nine batches. Metchalizer applied on log-transformed data showed the most promising performance on batch effect removal, as well as in the detection of 195 known biomarkers across 49 IEM patient samples and performed at least similar to an approach utilizing 15 within-batch reference samples. Furthermore, our regression model indicates that 6.5–37% of the considered features showed significant age-dependent variations. Our comprehensive comparison of normalization methods showed that our Log-Metchalizer approach enables the use out-of-batch reference samples to establish clinically-relevant reference values for metabolite concentrations. These findings open the possibilities to use large scale out-of-batch reference samples in a clinical setting, increasing the throughput and detection accuracy. Full article
(This article belongs to the Special Issue 10th Anniversary of Metabolites: The Changing Landscape of Metabolomics)
►▼ Show Figures

Figure 1

20 pages, 4000 KiB  
Article
Absolute Quantification of the Central Carbon Metabolome in Eight Commonly Applied Prokaryotic and Eukaryotic Model Systems
by Lisa M. Røst, Lilja Brekke Thorfinnsdottir, Kanhaiya Kumar, Katsuya Fuchino, Ida Eide Langørgen, Zdenka Bartosova, Kåre Andre Kristiansen and Per Bruheim
Metabolites 2020, 10(2), 74; https://doi.org/10.3390/metabo10020074 - 19 Feb 2020
Cited by 36 | Viewed by 7471
Abstract
Absolute quantification of intracellular metabolite pools is a prerequisite for modeling and in-depth biological interpretation of metabolomics data. It is the final step of an elaborate metabolomics workflow, with challenges associated with all steps—from sampling to quantifying the physicochemically diverse metabolite pool. Chromatographic [...] Read more.
Absolute quantification of intracellular metabolite pools is a prerequisite for modeling and in-depth biological interpretation of metabolomics data. It is the final step of an elaborate metabolomics workflow, with challenges associated with all steps—from sampling to quantifying the physicochemically diverse metabolite pool. Chromatographic separation combined with mass spectrometric (MS) detection is the superior platform for high coverage, selective, and sensitive detection of metabolites. Herein, we apply our quantitative MS-metabolomics workflow to measure and present the central carbon metabolome of a panel of commonly applied biological model systems. The workflow includes three chromatographic methods combined with isotope dilution tandem mass spectrometry to allow for absolute quantification of 68 metabolites of glycolysis, the pentose phosphate pathway, the tricarboxylic acid cycle, and the amino acid and (deoxy) nucleoside pools. The biological model systems; Bacillus subtilis, Saccharomyces cerevisiae, two microalgal species, and four human cell lines were all cultured in commonly applied culture media and sampled in exponential growth phase. Both literature and databases are scarce with comprehensive metabolite datasets, and existing entries range over several orders of magnitude. The workflow and metabolite panel presented herein can be employed to expand the list of reference metabolomes, as encouraged by the metabolomics community, in a continued effort to develop and refine high-quality quantitative metabolomics workflows. Full article
(This article belongs to the Special Issue 10th Anniversary of Metabolites: The Changing Landscape of Metabolomics)
►▼ Show Figures

Figure 1

Review

Jump to: Research

41 pages, 1774 KiB  
Review
Metabolomics-Guided Elucidation of Plant Abiotic Stress Responses in the 4IR Era: An Overview
by Morena M. Tinte, Kekeletso H. Chele, Justin J. J. van der Hooft and Fidele Tugizimana
Metabolites 2021, 11(7), 445; https://doi.org/10.3390/metabo11070445 - 8 Jul 2021
Cited by 12 | Viewed by 5758
Abstract
Plants are constantly challenged by changing environmental conditions that include abiotic stresses. These are limiting their development and productivity and are subsequently threatening our food security, especially when considering the pressure of the increasing global population. Thus, there is an urgent need for [...] Read more.
Plants are constantly challenged by changing environmental conditions that include abiotic stresses. These are limiting their development and productivity and are subsequently threatening our food security, especially when considering the pressure of the increasing global population. Thus, there is an urgent need for the next generation of crops with high productivity and resilience to climate change. The dawn of a new era characterized by the emergence of fourth industrial revolution (4IR) technologies has redefined the ideological boundaries of research and applications in plant sciences. Recent technological advances and machine learning (ML)-based computational tools and omics data analysis approaches are allowing scientists to derive comprehensive metabolic descriptions and models for the target plant species under specific conditions. Such accurate metabolic descriptions are imperatively essential for devising a roadmap for the next generation of crops that are resilient to environmental deterioration. By synthesizing the recent literature and collating data on metabolomics studies on plant responses to abiotic stresses, in the context of the 4IR era, we point out the opportunities and challenges offered by omics science, analytical intelligence, computational tools and big data analytics. Specifically, we highlight technological advancements in (plant) metabolomics workflows and the use of machine learning and computational tools to decipher the dynamics in the chemical space that define plant responses to abiotic stress conditions. Full article
(This article belongs to the Special Issue 10th Anniversary of Metabolites: The Changing Landscape of Metabolomics)
►▼ Show Figures

Graphical abstract

34 pages, 2754 KiB  
Review
Metabolomics and Lipidomics: Expanding the Molecular Landscape of Exercise Biology
by Mehdi R. Belhaj, Nathan G. Lawler and Nolan J. Hoffman
Metabolites 2021, 11(3), 151; https://doi.org/10.3390/metabo11030151 - 7 Mar 2021
Cited by 55 | Viewed by 9605
Abstract
Dynamic changes in circulating and tissue metabolites and lipids occur in response to exercise-induced cellular and whole-body energy demands to maintain metabolic homeostasis. The metabolome and lipidome in a given biological system provides a molecular snapshot of these rapid and complex metabolic perturbations. [...] Read more.
Dynamic changes in circulating and tissue metabolites and lipids occur in response to exercise-induced cellular and whole-body energy demands to maintain metabolic homeostasis. The metabolome and lipidome in a given biological system provides a molecular snapshot of these rapid and complex metabolic perturbations. The application of metabolomics and lipidomics to map the metabolic responses to an acute bout of aerobic/endurance or resistance exercise has dramatically expanded over the past decade thanks to major analytical advancements, with most exercise-related studies to date focused on analyzing human biofluids and tissues. Experimental and analytical considerations, as well as complementary studies using animal model systems, are warranted to help overcome challenges associated with large human interindividual variability and decipher the breadth of molecular mechanisms underlying the metabolic health-promoting effects of exercise. In this review, we provide a guide for exercise researchers regarding analytical techniques and experimental workflows commonly used in metabolomics and lipidomics. Furthermore, we discuss advancements in human and mammalian exercise research utilizing metabolomic and lipidomic approaches in the last decade, as well as highlight key technical considerations and remaining knowledge gaps to continue expanding the molecular landscape of exercise biology. Full article
(This article belongs to the Special Issue 10th Anniversary of Metabolites: The Changing Landscape of Metabolomics)
►▼ Show Figures

Graphical abstract

31 pages, 2671 KiB  
Review
Metabolic Signatures of the Exposome—Quantifying the Impact of Exposure to Environmental Chemicals on Human Health
by Matej Orešič, Aidan McGlinchey, Craig E. Wheelock and Tuulia Hyötyläinen
Metabolites 2020, 10(11), 454; https://doi.org/10.3390/metabo10110454 - 10 Nov 2020
Cited by 24 | Viewed by 7234
Abstract
Human health and well-being are intricately linked to environmental quality. Environmental exposures can have lifelong consequences. In particular, exposures during the vulnerable fetal or early development period can affect structure, physiology and metabolism, causing potential adverse, often permanent, health effects at any point [...] Read more.
Human health and well-being are intricately linked to environmental quality. Environmental exposures can have lifelong consequences. In particular, exposures during the vulnerable fetal or early development period can affect structure, physiology and metabolism, causing potential adverse, often permanent, health effects at any point in life. External exposures, such as the “chemical exposome” (exposures to environmental chemicals), affect the host’s metabolism and immune system, which, in turn, mediate the risk of various diseases. Linking such exposures to adverse outcomes, via intermediate phenotypes such as the metabolome, is one of the central themes of exposome research. Much progress has been made in this line of research, including addressing some key challenges such as analytical coverage of the exposome and metabolome, as well as the integration of heterogeneous, multi-omics data. There is strong evidence that chemical exposures have a marked impact on the metabolome, associating with specific disease risks. Herein, we review recent progress in the field of exposome research as related to human health as well as selected metabolic and autoimmune diseases, with specific emphasis on the impacts of chemical exposures on the host metabolome. Full article
(This article belongs to the Special Issue 10th Anniversary of Metabolites: The Changing Landscape of Metabolomics)
►▼ Show Figures

Figure 1

28 pages, 1201 KiB  
Review
Toward a Standardized Strategy of Clinical Metabolomics for the Advancement of Precision Medicine
by Nguyen Phuoc Long, Tran Diem Nghi, Yun Pyo Kang, Nguyen Hoang Anh, Hyung Min Kim, Sang Ki Park and Sung Won Kwon
Metabolites 2020, 10(2), 51; https://doi.org/10.3390/metabo10020051 - 29 Jan 2020
Cited by 54 | Viewed by 9445
Abstract
Despite the tremendous success, pitfalls have been observed in every step of a clinical metabolomics workflow, which impedes the internal validity of the study. Furthermore, the demand for logistics, instrumentations, and computational resources for metabolic phenotyping studies has far exceeded our expectations. In [...] Read more.
Despite the tremendous success, pitfalls have been observed in every step of a clinical metabolomics workflow, which impedes the internal validity of the study. Furthermore, the demand for logistics, instrumentations, and computational resources for metabolic phenotyping studies has far exceeded our expectations. In this conceptual review, we will cover inclusive barriers of a metabolomics-based clinical study and suggest potential solutions in the hope of enhancing study robustness, usability, and transferability. The importance of quality assurance and quality control procedures is discussed, followed by a practical rule containing five phases, including two additional “pre-pre-” and “post-post-” analytical steps. Besides, we will elucidate the potential involvement of machine learning and demonstrate that the need for automated data mining algorithms to improve the quality of future research is undeniable. Consequently, we propose a comprehensive metabolomics framework, along with an appropriate checklist refined from current guidelines and our previously published assessment, in the attempt to accurately translate achievements in metabolomics into clinical and epidemiological research. Furthermore, the integration of multifaceted multi-omics approaches with metabolomics as the pillar member is in urgent need. When combining with other social or nutritional factors, we can gather complete omics profiles for a particular disease. Our discussion reflects the current obstacles and potential solutions toward the progressing trend of utilizing metabolomics in clinical research to create the next-generation healthcare system. Full article
(This article belongs to the Special Issue 10th Anniversary of Metabolites: The Changing Landscape of Metabolomics)
►▼ Show Figures

Graphical abstract

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-7
Back to TopTop