Special Issue "Selected Paper from the Australian and New Zealand Metabolomics Conference"

A special issue of Metabolites (ISSN 2218-1989).

Deadline for manuscript submissions: closed (31 August 2016)

Special Issue Editors

Guest Editor
Dr. Devin Benheim

La Trobe University, Melbourne, Australia
E-Mail
Interests: agriculture; bioanalytical chemistry; bioinformatics; plant science
Guest Editor
Dr. Farhana R. Pinu

The New Zealand Institute for Plant and Food Research Limited, Private Bag 92169, Auckland 1142, New Zealand
Website | E-Mail
Interests: microbial and plant metabolomics; biostatistics; volatile metabolite analysis; yeast metabolism; fermentation and food metabolomics
Guest Editor
Dr. Konstantinos A. Kouremenos

Metabolomics Australia, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, 30 Flemington Road, Parkville, VIC, 3010, Australia
Website | E-Mail
Interests: targeted/untargeted polar metabolic profiling; quantitative metabolomics; lipidomics; data processing methods; biostatistics
Guest Editor
Dr. Damien L. Callahan

Centre for Chemistry and Biotechnology, School of Life and Environmental Sciences, Deakin University, Australia
Website | E-Mail
Interests: plant metabolomics; lipidomics; microalgae lipid biochemistry; metal hyperacumulating plants; mass spectrometry; analytical chemistry
Guest Editor
Dr. David P. De Souza

Metabolomics Australia, Bio21 Molecular Science and Biotechnology Institute, 30 Flemington Road, Parkville, 3052, Australia
Website | E-Mail
Interests: biomedical metabolomics; stable isotope labelling; flux analysis; bioinformatics; GC-MS

Special Issue Information

Dear Colleagues,

This Special Issue will collect selected invited and contributed talks presented during the Australian and New Zealand Metabolomics Conference (ANZAMT 2016), which was held at Melbourne, Victoria, Australia, from 30 March to 1 April, 2016. Website: http://www.anzmet.org/.

Dr. Devin Benheim
Dr. Farhana R. Pinu
Dr. Konstantinos A. Kouremenos
Dr. Damien L. Callahan
Dr. David P. De Souza
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 papers will be 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 quarterly 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 850 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 (7 papers)

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Research

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Open AccessCommunication Fully Automated Trimethylsilyl (TMS) Derivatisation Protocol for Metabolite Profiling by GC-MS
Metabolites 2017, 7(1), 1; https://doi.org/10.3390/metabo7010001
Received: 23 September 2016 / Revised: 22 December 2016 / Accepted: 26 December 2016 / Published: 29 December 2016
Cited by 2 | PDF Full-text (14284 KB) | HTML Full-text | XML Full-text
Abstract
Gas Chromatography-Mass Spectrometry (GC-MS) has long been used for metabolite profiling of a wide range of biological samples. Many derivatisation protocols are already available and among these, trimethylsilyl (TMS) derivatisation is one of the most widely used in metabolomics. However, most TMS methods
[...] Read more.
Gas Chromatography-Mass Spectrometry (GC-MS) has long been used for metabolite profiling of a wide range of biological samples. Many derivatisation protocols are already available and among these, trimethylsilyl (TMS) derivatisation is one of the most widely used in metabolomics. However, most TMS methods rely on off-line derivatisation prior to GC-MS analysis. In the case of manual off-line TMS derivatisation, the derivative created is unstable, so reduction in recoveries occurs over time. Thus, derivatisation is carried out in small batches. Here, we present a fully automated TMS derivatisation protocol using robotic autosamplers and we also evaluate a commercial software, Maestro available from Gerstel GmbH. Because of automation, there was no waiting time of derivatised samples on the autosamplers, thus reducing degradation of unstable metabolites. Moreover, this method allowed us to overlap samples and improved throughputs. We compared data obtained from both manual and automated TMS methods performed on three different matrices, including standard mix, wine, and plasma samples. The automated TMS method showed better reproducibility and higher peak intensity for most of the identified metabolites than the manual derivatisation method. We also validated the automated method using 114 quality control plasma samples. Additionally, we showed that this online method was highly reproducible for most of the metabolites detected and identified (RSD < 20) and specifically achieved excellent results for sugars, sugar alcohols, and some organic acids. To the very best of our knowledge, this is the first time that the automated TMS method has been applied to analyse a large number of complex plasma samples. Furthermore, we found that this method was highly applicable for routine metabolite profiling (both targeted and untargeted) in any metabolomics laboratory. Full article
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Open AccessArticle A Simple Method for Measuring Carbon-13 Fatty Acid Enrichment in the Major Lipid Classes of Microalgae Using GC-MS
Metabolites 2016, 6(4), 42; https://doi.org/10.3390/metabo6040042
Received: 5 September 2016 / Revised: 29 October 2016 / Accepted: 7 November 2016 / Published: 11 November 2016
PDF Full-text (1983 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
A simple method for tracing carbon fixation and lipid synthesis in microalgae was developed using a combination of solid-phase extraction (SPE) and negative ion chemical ionisation gas chromatography mass spectrometry (NCI-GC-MS). NCI-GC-MS is an extremely sensitive technique that can produce an unfragmented molecular
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A simple method for tracing carbon fixation and lipid synthesis in microalgae was developed using a combination of solid-phase extraction (SPE) and negative ion chemical ionisation gas chromatography mass spectrometry (NCI-GC-MS). NCI-GC-MS is an extremely sensitive technique that can produce an unfragmented molecular ion making this technique particularly useful for stable isotope enrichment studies. Derivatisation of fatty acids using pentafluorobenzyl bromide (PFBBr) allows the coupling of the high separation efficiency of GC and the measurement of unfragmented molecular ions for each of the fatty acids by single quadrupole MS. The key is that isotope spectra can be measured without interference from co-eluting fatty acids or other molecules. Pre-fractionation of lipid extracts by SPE allows the measurement of 13C isotope incorporation into the three main lipid classes (phospholipids, glycolipids, neutral lipids) in microalgae thus allowing the study of complex lipid biochemistry using relatively straightforward analytical technology. The high selectivity of GC is necessary as it allows the collection of mass spectra for individual fatty acids, including cis/trans isomers, of the PFB-derivatised fatty acids. The combination of solid-phase extraction and GC-MS enables the accurate determination of 13C incorporation into each lipid pool. Three solvent extraction protocols that are commonly used in lipidomics were also evaluated and are described here with regard to extraction efficiencies for lipid analysis in microalgae. Full article
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Open AccessFeature PaperArticle Analysis of Mammalian Cell Proliferation and Macromolecule Synthesis Using Deuterated Water and Gas Chromatography-Mass Spectrometry
Metabolites 2016, 6(4), 34; https://doi.org/10.3390/metabo6040034
Received: 2 September 2016 / Revised: 10 October 2016 / Accepted: 10 October 2016 / Published: 13 October 2016
Cited by 4 | PDF Full-text (2397 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Deuterated water (2H2O), a stable isotopic tracer, provides a convenient and reliable way to label multiple cellular biomass components (macromolecules), thus permitting the calculation of their synthesis rates. Here, we have combined 2H2O labelling, GC-MS analysis
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Deuterated water (2H2O), a stable isotopic tracer, provides a convenient and reliable way to label multiple cellular biomass components (macromolecules), thus permitting the calculation of their synthesis rates. Here, we have combined 2H2O labelling, GC-MS analysis and a novel cell fractionation method to extract multiple biomass components (DNA, protein and lipids) from the one biological sample, thus permitting the simultaneous measurement of DNA (cell proliferation), protein and lipid synthesis rates. We have used this approach to characterize the turnover rates and metabolism of a panel of mammalian cells in vitro (muscle C2C12 and colon cancer cell lines). Our data show that in actively-proliferating cells, biomass synthesis rates are strongly linked to the rate of cell division. Furthermore, in both proliferating and non-proliferating cells, it is the lipid pool that undergoes the most rapid turnover when compared to DNA and protein. Finally, our data in human colon cancer cell lines reveal a marked heterogeneity in the reliance on the de novo lipogenic pathway, with the cells being dependent on both ‘self-made’ and exogenously-derived fatty acid. Full article
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Open AccessFeature PaperArticle Optimized Method for Untargeted Metabolomics Analysis of MDA-MB-231 Breast Cancer Cells
Metabolites 2016, 6(4), 30; https://doi.org/10.3390/metabo6040030
Received: 31 August 2016 / Revised: 15 September 2016 / Accepted: 19 September 2016 / Published: 22 September 2016
Cited by 3 | PDF Full-text (3028 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Cancer cells often have dysregulated metabolism, which is largely characterized by the Warburg effect—an increase in glycolytic activity at the expense of oxidative phosphorylation—and increased glutamine utilization. Modern metabolomics tools offer an efficient means to investigate metabolism in cancer cells. Currently, a number
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Cancer cells often have dysregulated metabolism, which is largely characterized by the Warburg effect—an increase in glycolytic activity at the expense of oxidative phosphorylation—and increased glutamine utilization. Modern metabolomics tools offer an efficient means to investigate metabolism in cancer cells. Currently, a number of protocols have been described for harvesting adherent cells for metabolomics analysis, but the techniques vary greatly and they lack specificity to particular cancer cell lines with diverse metabolic and structural features. Here we present an optimized method for untargeted metabolomics characterization of MDA-MB-231 triple negative breast cancer cells, which are commonly used to study metastatic breast cancer. We found that an approach that extracted all metabolites in a single step within the culture dish optimally detected both polar and non-polar metabolite classes with higher relative abundance than methods that involved removal of cells from the dish. We show that this method is highly suited to diverse applications, including the characterization of central metabolic flux by stable isotope labelling and differential analysis of cells subjected to specific pharmacological interventions. Full article
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Open AccessCommunication Vinegar Metabolomics: An Explorative Study of Commercial Balsamic Vinegars Using Gas Chromatography-Mass Spectrometry
Metabolites 2016, 6(3), 22; https://doi.org/10.3390/metabo6030022
Received: 22 June 2016 / Revised: 18 July 2016 / Accepted: 19 July 2016 / Published: 23 July 2016
Cited by 9 | PDF Full-text (5223 KB) | HTML Full-text | XML Full-text
Abstract
Balsamic vinegar is a popular food condiment produced from cooked grape must by two successive fermentation (anaerobic and aerobic) processes. Although many studies have been performed to determine the composition of major metabolites, including sugars and aroma compounds, no study has been undertaken
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Balsamic vinegar is a popular food condiment produced from cooked grape must by two successive fermentation (anaerobic and aerobic) processes. Although many studies have been performed to determine the composition of major metabolites, including sugars and aroma compounds, no study has been undertaken yet to characterize the comprehensive metabolite composition of balsamic vinegars. Here, we present the first metabolomics study of commercial balsamic vinegars by gas chromatography coupled to mass spectrometry (GC-MS). The combination of three GC-MS methods allowed us to detect >1500 features in vinegar samples, of which 123 metabolites were accurately identified, including 25 amino acids, 26 carboxylic acids, 13 sugars and sugar alcohols, four fatty acids, one vitamin, one tripeptide and over 47 aroma compounds. Moreover, we identified for the first time in vinegar five volatile metabolites: acetin, 2-methylpyrazine, 2-acetyl-1-pyroline, 4-anisidine and 1,3-diacetoxypropane. Therefore, we demonstrated the capability of metabolomics for detecting and identifying large number of metabolites and some of them could be used to distinguish vinegar samples based on their origin and potentially quality. Full article
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Review

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Open AccessReview Current and Future Perspectives on the Structural Identification of Small Molecules in Biological Systems
Metabolites 2016, 6(4), 46; https://doi.org/10.3390/metabo6040046
Received: 6 November 2016 / Revised: 4 December 2016 / Accepted: 6 December 2016 / Published: 15 December 2016
Cited by 23 | PDF Full-text (2775 KB) | HTML Full-text | XML Full-text
Abstract
Although significant advances have been made in recent years, the structural elucidation of small molecules continues to remain a challenging issue for metabolite profiling. Many metabolomic studies feature unknown compounds; sometimes even in the list of features identified as “statistically significant” in the
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Although significant advances have been made in recent years, the structural elucidation of small molecules continues to remain a challenging issue for metabolite profiling. Many metabolomic studies feature unknown compounds; sometimes even in the list of features identified as “statistically significant” in the study. Such metabolic “dark matter” means that much of the potential information collected by metabolomics studies is lost. Accurate structure elucidation allows researchers to identify these compounds. This in turn, facilitates downstream metabolite pathway analysis, and a better understanding of the underlying biology of the system under investigation. This review covers a range of methods for the structural elucidation of individual compounds, including those based on gas and liquid chromatography hyphenated to mass spectrometry, single and multi-dimensional nuclear magnetic resonance spectroscopy, and high-resolution mass spectrometry and includes discussion of data standardization. Future perspectives in structure elucidation are also discussed; with a focus on the potential development of instruments and techniques, in both nuclear magnetic resonance spectroscopy and mass spectrometry that, may help solve some of the current issues that are hampering the complete identification of metabolite structure and function. Full article
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Other

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Open AccessFeature PaperBrief Report Strategies for Extending Metabolomics Studies with Stable Isotope Labelling and Fluxomics
Metabolites 2016, 6(4), 32; https://doi.org/10.3390/metabo6040032
Received: 31 August 2016 / Revised: 21 September 2016 / Accepted: 28 September 2016 / Published: 1 October 2016
Cited by 6 | PDF Full-text (222 KB) | HTML Full-text | XML Full-text
Abstract
This is a perspective from the peer session on stable isotope labelling and fluxomics at the Australian & New Zealand Metabolomics Conference (ANZMET) held from 30 March to 1 April 2016 at La Trobe University, Melbourne, Australia. This report summarizes the key points
[...] Read more.
This is a perspective from the peer session on stable isotope labelling and fluxomics at the Australian & New Zealand Metabolomics Conference (ANZMET) held from 30 March to 1 April 2016 at La Trobe University, Melbourne, Australia. This report summarizes the key points raised in the peer session which focused on the advantages of using stable isotopes in modern metabolomics and the challenges in conducting flux analyses. The session highlighted the utility of stable isotope labelling in generating reference standards for metabolite identification, absolute quantification, and in the measurement of the dynamic activity of metabolic pathways. The advantages and disadvantages of different approaches of fluxomics analyses including flux balance analysis, metabolic flux analysis and kinetic flux profiling were also discussed along with the use of stable isotope labelling in in vivo dynamic metabolomics. A number of crucial technical considerations for designing experiments and analyzing data with stable isotope labelling were discussed which included replication, instrumentation, methods of labelling, tracer dilution and data analysis. This report reflects the current viewpoint on the use of stable isotope labelling in metabolomics experiments, identifying it as a great tool with the potential to improve biological interpretation of metabolomics data in a number of ways. Full article
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