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Metabolites
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Mass Spectrometry-Based Metabolomics and Its Applications
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Mass Spectrometry-Based Metabolomics and Its Applications

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

Deadline for manuscript submissions: closed (31 January 2019) | Viewed by 44423

Special Issue Editor

Dr. Zhentian Lei

E-Mail Website
Guest Editor
Metabolomics Center, Department of Biochemistry, University of Missouri, Columbia, MO 65211, USA
Interests: metabolomics; biochemistry; biological mass spectrometry; food chemistry; wood chemistry
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Mass spectrometry (MS)-based metabolomics has evolved as an important and indispensable platform in biological research owing to the development of modern MS technologies and informatics. MS offers the best combination of sensitivity and selectivity and, when coupled to gas chromatography (GC) and/or liquid chromatography (LC), provides an excellent solution to complex mixture analyses. It is well suited for non-targeted large scale metabolite profiling, as well as targeted metabolomics for metabolite detection and quantification. Significantly improved informatics techniques including multivariate statistic tools and spectral libraries facilitate data processing, peak annotation, statistical analysis, and data mining and effectively extract metabolite information from the complex metabolomics datasets. MS-based metabolomics has been widely used in many different fields including medicine, biology and agriculture for metabolite biomarker discovery, drug development, biosynthetic pathway elucidation and gene discovery. It will continue to evolve and contribute to our understanding of complex biological processes.

This Special Issue “Mass Spectrometry-Based Metabolomics and Its Applications” of Metabolites will focus on cutting-edge metabolomics researches. Specific topics include, but are not limited to, metabolomics method and technology developments, informatics tools, and applications of metabolomics.

Dr. Zhentian Lei
Guest Editor

Manuscript Submission Information

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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

  • mass spectrometry
  • metabolomics
  • metabolites
  • gas chromatogram (GC)
  • liquid chromatogram (LC)
  • informatics

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Published Papers (7 papers)

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Research

21 pages, 1739 KiB  
Article
HILIC-Enabled 13C Metabolomics Strategies: Comparing Quantitative Precision and Spectral Accuracy of QTOF High- and QQQ Low-Resolution Mass Spectrometry
by André Feith, Attila Teleki, Michaela Graf, Lorenzo Favilli and Ralf Takors
Metabolites 2019, 9(4), 63; https://doi.org/10.3390/metabo9040063 - 2 Apr 2019
Cited by 31 | Viewed by 5113
Abstract
Dynamic 13C-tracer-based flux analyses of in vivo reaction networks still require a continuous development of advanced quantification methods applying state-of-the-art mass spectrometry platforms. Utilizing alkaline HILIC chromatography, we adapt strategies for a systematic quantification study in non- and 13C-labeled multicomponent endogenous [...] Read more.
Dynamic 13C-tracer-based flux analyses of in vivo reaction networks still require a continuous development of advanced quantification methods applying state-of-the-art mass spectrometry platforms. Utilizing alkaline HILIC chromatography, we adapt strategies for a systematic quantification study in non- and 13C-labeled multicomponent endogenous Corynebacterium glutamicum extracts by LC-QTOF high resolution (HRMS) and LC-QQQ tandem mass spectrometry (MS/MS). Without prior derivatization, a representative cross-section of 17 central carbon and anabolic key intermediates were analyzed with high selectivity and sensitivity under optimized ESI-MS settings. In column detection limits for the absolute quantification range were between 6.8–304.7 (QQQ) and 28.7–881.5 fmol (QTOF) with comparable linearities (3–5 orders of magnitude) and enhanced precision using QQQ-MRM detection. Tailor-made preparations of uniformly (U)13C-labeled cultivation extracts for isotope dilution mass spectrometry enabled the accurate quantification in complex sample matrices and extended linearities without effect on method parameters. Furthermore, evaluation of metabolite-specific m+1-to-m+0 ratios (ISR1:0) in non-labeled extracts exhibited sufficient methodical spectral accuracies with mean deviations of 3.89 ± 3.54% (QTOF) and 4.01 ± 3.01% (QQQ). Based on the excellent HILIC performance, conformity analysis of time-resolved isotopic enrichments in 13C-tracer experiments revealed sufficient spectral accuracy for QQQ-SIM detection. However, only QTOF-HRMS ensures determination of the full isotopologue space in complex matrices without mass interferences. Full article
(This article belongs to the Special Issue Mass Spectrometry-Based Metabolomics and Its Applications)
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14 pages, 2778 KiB  
Article
Maternal Dietary Docosahexaenoic Acid Alters Lipid Peroxidation Products and (n-3)/(n-6) Fatty Acid Balance in Offspring Mice
by Bo Yang, Runting Li, Taeseon Woo, Jimmy D. Browning, Jr., Hailong Song, Zezong Gu, Jiankun Cui, James C. Lee, Kevin L. Fritsche, David Q. Beversdorf, Grace Y. Sun and C. Michael Greenlief
Metabolites 2019, 9(3), 40; https://doi.org/10.3390/metabo9030040 - 1 Mar 2019
Cited by 14 | Viewed by 6601
Abstract
The abundance of docosahexaenoic acid (DHA) in the mammalian brain has generated substantial interest in the search for its roles in regulating brain functions. Our recent study with a gene/stress mouse model provided evidence to support the ability for the maternal supplement of [...] Read more.
The abundance of docosahexaenoic acid (DHA) in the mammalian brain has generated substantial interest in the search for its roles in regulating brain functions. Our recent study with a gene/stress mouse model provided evidence to support the ability for the maternal supplement of DHA to alleviate autism-associated behavior in the offspring. DHA and arachidonic acid (ARA) are substrates of enzymatic and non-enzymatic reactions, and lipid peroxidation results in the production of 4-hydroxyhexenal (4-HHE) and 4-hydroxynonenal (4-HNE), respectively. In this study, we examine whether a maternal DHA-supplemented diet alters fatty acids (FAs), as well as lipid peroxidation products in the pup brain, heart and plasma by a targeted metabolite approach. Pups in the maternal DHA-supplemented diet group showed an increase in DHA and a concomitant decrease in ARA in all brain regions examined. However, significant increases in 4-HHE, and not 4-HNE, were found mainly in the cerebral cortex and hippocampus. Analysis of heart and plasma showed large increases in DHA and 4-HHE, but a significant decrease in 4-HNE levels only in plasma. Taken together, the DHA-supplemented maternal diet alters the (n-3)/(n-6) FA ratio, and increases 4-HHE levels in pup brain, heart and plasma. These effects may contribute to the beneficial effects of DHA on neurodevelopment, as well as functional changes in other body organs. Full article
(This article belongs to the Special Issue Mass Spectrometry-Based Metabolomics and Its Applications)
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11 pages, 810 KiB  
Article
Metabolic Profiling of Fish Meat by GC-MS Analysis, and Correlations with Taste Attributes Obtained Using an Electronic Tongue
by Ryota Mabuchi, Ayaka Ishimaru, Mao Tanaka, Osamu Kawaguchi and Shota Tanimoto
Metabolites 2019, 9(1), 1; https://doi.org/10.3390/metabo9010001 - 21 Dec 2018
Cited by 39 | Viewed by 5577
Abstract
To evaluate the taste of ordinary muscle from white-fleshed fish, we used GC-MS metabolomic analysis to characterise the compounds therein, and correlated the obtained data with taste measurements from an electronic tongue. Prediction models using orthogonal partial least squares were produced for different [...] Read more.
To evaluate the taste of ordinary muscle from white-fleshed fish, we used GC-MS metabolomic analysis to characterise the compounds therein, and correlated the obtained data with taste measurements from an electronic tongue. Prediction models using orthogonal partial least squares were produced for different taste attributes, and the primary metabolic components correlated with the taste attributes were identified. Clear differences were observed in the component profiles for different fish species. Using an electronic tongue, differences in tastes were noted among the fish species in terms of sourness, acidic bitterness, umami and saltiness. The obtained correlations allowed the construction of good taste prediction models, especially for sourness, acidic bitterness and saltiness. Compounds such as phosphoric acid, lactic acid and creatinine were found to be highly correlated with some taste attributes. Phosphoric acid in particular showed the highest variable important for prediction (VIP) scores in many of the taste prediction models, and it is therefore a candidate marker to evaluate the tastes of white-fleshed fish. Full article
(This article belongs to the Special Issue Mass Spectrometry-Based Metabolomics and Its Applications)
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18 pages, 2356 KiB  
Article
Identifying Antibacterial Compounds in Black Walnuts (Juglans nigra) Using a Metabolomics Approach
by Khanh-Van Ho, Zhentian Lei, Lloyd W. Sumner, Mark V. Coggeshall, Hsin-Yeh Hsieh, George C. Stewart and Chung-Ho Lin
Metabolites 2018, 8(4), 58; https://doi.org/10.3390/metabo8040058 - 29 Sep 2018
Cited by 32 | Viewed by 8618
Abstract
Black walnut (Juglans nigra L.) is one of the most economically valuable hardwood species and a high value tree for edible nut production in the United States. Although consumption of black walnut has been linked to multiple health-promoting effects (e.g., antioxidant, antimicrobial, [...] Read more.
Black walnut (Juglans nigra L.) is one of the most economically valuable hardwood species and a high value tree for edible nut production in the United States. Although consumption of black walnut has been linked to multiple health-promoting effects (e.g., antioxidant, antimicrobial, anti-inflammatory), the bioactive compounds have not been systematically characterized. In addition, the associations between different black walnut cultivars and their health-promoting compounds have not been well established. In this study, the kernels of twenty-two black walnut cultivars selected for nut production by the University of Missouri Center for Agroforestry (Columbia, MO, USA) were evaluated for their antibacterial activities using agar-well diffusion assay. Among the selected cultivars, four black walnut cultivars (i.e., Mystry, Surprise, D.34, and A.36) exhibited antibacterial activity against a Gram-positive bacterium (Staphylococcus aureus), whereas other cultivars showed no effect on the inhibition of this bacterium. The antibacterial compounds showing the strongest activity were isolated with bioassay-guided purification and identified using a metabolomics approach. Six antibacterial bioactive compounds responsible for antimicrobial activity were successfully identified. Glansreginin A, azelaic acid, quercetin, and eriodictyol-7-O-glucoside are novel antibacterial compounds identified in the kernels of black walnuts. The metabolomics approach provides a simple and cost-effective tool for bioactive compound identification. Full article
(This article belongs to the Special Issue Mass Spectrometry-Based Metabolomics and Its Applications)
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10 pages, 2197 KiB  
Article
Metabolomics of Two Pecan Varieties Provides Insights into Scab Resistance
by Zhentian Lei, Clayton Kranawetter, Barbara W. Sumner, David Huhman, Daniel J. Wherritt, Andrew L. Thomas, Charles Rohla and Lloyd W. Sumner
Metabolites 2018, 8(4), 56; https://doi.org/10.3390/metabo8040056 - 23 Sep 2018
Cited by 7 | Viewed by 4464
Abstract
UHPLC-MS-based non-targeted metabolomics was used to investigate the biochemical basis of pecan scab resistance. Two contrasting pecan varieties, Kanza (scab-resistant) and Pawnee (scab-susceptible), were profiled and the metabolomics data analyzed using multivariate statistics. Significant qualitative and quantitative metabolic differences were observed between the [...] Read more.
UHPLC-MS-based non-targeted metabolomics was used to investigate the biochemical basis of pecan scab resistance. Two contrasting pecan varieties, Kanza (scab-resistant) and Pawnee (scab-susceptible), were profiled and the metabolomics data analyzed using multivariate statistics. Significant qualitative and quantitative metabolic differences were observed between the two varieties. Both varieties were found to have some unique metabolites. Metabolites that were only present or more abundant in Kanza relative to Pawnee could potentially contribute to the scab resistance in Kanza. Some of these metabolites were putatively identified as quercetin derivatives using tandem mass spectrometry. This suggests that quercetin derivatives could be important to pecan scab resistance. Full article
(This article belongs to the Special Issue Mass Spectrometry-Based Metabolomics and Its Applications)
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15 pages, 1778 KiB  
Article
Untargeted Metabolomics Analysis of Eggplant (Solanum melongena L.) Fruit and Its Correlation to Fruit Morphologies
by Abu Hanifah, Awang Maharijaya, Sastia P. Putri, Walter A. Laviña and Sobir
Metabolites 2018, 8(3), 49; https://doi.org/10.3390/metabo8030049 - 1 Sep 2018
Cited by 31 | Viewed by 7011
Abstract
Eggplant is one of the most widely cultivated vegetables in the world and has high biodiversity in terms of fruit shape, size, and color. Therefore, fruit morphology and nutrient content become important considerations for both consumers and breeders who develop new eggplant-based products. [...] Read more.
Eggplant is one of the most widely cultivated vegetables in the world and has high biodiversity in terms of fruit shape, size, and color. Therefore, fruit morphology and nutrient content become important considerations for both consumers and breeders who develop new eggplant-based products. To gain insight on the diversity of eggplant metabolites, twenty-one eggplant accessions were analyzed by untargeted metabolomics using GC-MS and LC-MS. The dataset of eggplant fruit morphologies, and metabolites specific to different eggplant fruit accessions were used for correlation analysis. Untargeted metabolomics analysis using LC-MS and GC-MS was able to detect 136 and 207 peaks, respectively. Fifty-one (51) metabolites from the LC-MS analysis and 207 metabolites from the GC-MS analysis were putatively identified, which included alkaloids, terpenes, terpenoids, fatty acids, and flavonoids. Spearman correlation analysis revealed that 14 fruit morphologies were correlated with several metabolites. This information will be very useful for the development of strategies for eggplant breeding. Full article
(This article belongs to the Special Issue Mass Spectrometry-Based Metabolomics and Its Applications)
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15 pages, 1143 KiB  
Article
GC-MS-Based Endometabolome Analysis Differentiates Prostate Cancer from Normal Prostate Cells
by Ana Rita Lima, Ana Margarida Araújo, Joana Pinto, Carmen Jerónimo, Rui Henrique, Maria De Lourdes Bastos, Márcia Carvalho and Paula Guedes de Pinho
Metabolites 2018, 8(1), 23; https://doi.org/10.3390/metabo8010023 - 19 Mar 2018
Cited by 25 | Viewed by 5761
Abstract
Prostate cancer (PCa) is an important health problem worldwide. Diagnosis and management of PCa is very complex because the detection of serum prostate specific antigen (PSA) has several drawbacks. Metabolomics brings promise for cancer biomarker discovery and for better understanding PCa biochemistry. In [...] Read more.
Prostate cancer (PCa) is an important health problem worldwide. Diagnosis and management of PCa is very complex because the detection of serum prostate specific antigen (PSA) has several drawbacks. Metabolomics brings promise for cancer biomarker discovery and for better understanding PCa biochemistry. In this study, a gas chromatography–mass spectrometry (GC-MS) based metabolomic profiling of PCa cell lines was performed. The cell lines include 22RV1 and LNCaP from PCa with androgen receptor (AR) expression, DU145 and PC3 (which lack AR expression), and one normal prostate cell line (PNT2). Regarding the metastatic potential, PC3 is from an adenocarcinoma grade IV with high metastatic potential, DU145 has a moderate metastatic potential, and LNCaP has a low metastatic potential. Using multivariate analysis, alterations in levels of several intracellular metabolites were detected, disclosing the capability of the endometabolome to discriminate all PCa cell lines from the normal prostate cell line. Discriminant metabolites included amino acids, fatty acids, steroids, and sugars. Six stood out for the separation of all the studied PCa cell lines from the normal prostate cell line: ethanolamine, lactic acid, β-Alanine, L-valine, L-leucine, and L-tyrosine. Full article
(This article belongs to the Special Issue Mass Spectrometry-Based Metabolomics and Its Applications)
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