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Special Issue "Application of Mass Spectrometry Analysis in Metabolomics"

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

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 3913

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Special Issue Editors

Dr. Nicole Strittmatter

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Guest Editor

Faculty of Chemistry, Technische Universität München, 85748 Garching b., München, Germany
Interests: spatial metabolomics; shotgun approaches; ambient mass spectrometry; in situ mass spectrometry

Dr. Regina Verena Taudte

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Guest Editor

Faculty of Medicine, Core Facility Medical Mass Spectrometry, Institute of Laboratory Medicine, Philipps University Marburg, 35043 Marburg, Germany
Interests: untargeted metabolomics; targeted metabolomics; flux analyses; chromatography-based approaches; immunometabolism

Special Issue Information

Dear Colleagues,

Mass spectrometry has become the leading technology deployed in ‘omics’ studies due to its high sensitivity, specificity, speed and suitability for combination with other methods. Technical advances such as high-mass-resolution analysers or the incorporation of ion mobility continue to improve mass spectrometry instrumentation and help us overcome current bottlenecks in metabolite identification and coverage of the global metabolome.

In this Special Issue on “Application of Mass Spectrometry Analysis in Metabolomics” we want to highlight the breadth of research and applications of mass spectrometry in the metabolomics field. Areas of interest include, but are not limited to: environmental and clinical research; methodological approaches from shotgun/profiling methods and spatial metabolomics; fluxomics; and more classical separation-based approaches.

We encourage submissions of both primary research papers and reviews on any aspect of mass spectrometry relating to application, method and instrumentation development as well as bioinformatics.

Dr. Nicole Strittmatter
Dr. Regina Verena Taudte
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 2200 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

lipidomics
metabolomics
bioinformatics
mass spectrometry
chromatography-based approaches
shotgun analysis
spatial metabolomics
fluxomics

Published Papers (5 papers)

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Research

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Open AccessArticle

Effects of Different Storage Conditions on Lipid Stability in Mice Tissue Homogenates

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Metabolites 2023, 13(4), 504; https://doi.org/10.3390/metabo13040504 - 31 Mar 2023

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Abstract

Lipids are biomolecules involved in numerous (patho-)physiological processes and their elucidation in tissue samples is of particular interest. However, tissue analysis goes hand in hand with many challenges and the influence of pre-analytical factors can intensively change lipid concentrations ex vivo, compromising the results of the whole research project. Here, we study the influence of pre-analytical factors on lipid profiles during the processing of homogenized tissues. Homogenates from four different mice tissues (liver, kidney, heart, spleen) were stored at room temperature as well as in ice water for up to 120 min and analyzed via ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS). Lipid class ratios were calculated since their suitability as indicators for sample stability has been previously illustrated. Only approx. 40% of lipid class ratios were unchanged after 35 min, which was further reduced to 25% after 120 min during storage at room temperature. In contrast, lipids in tissue homogenates were generally stable when samples were kept in ice water, as more than 90% of investigated lipid class ratios remained unchanged after 35 min. Ultimately, swift processing of tissue homogenates under cooled conditions represents a viable option for lipid analysis and pre-analytical factors require more attention to achieve reliable results. Full article

(This article belongs to the Special Issue Application of Mass Spectrometry Analysis in Metabolomics)

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Open AccessArticle

Metabolomic Analysis Demonstrates the Impacts of Polyketide Synthases PKS14 and PKS15 on the Production of Beauvericins, Bassianolide, Enniatin A, and Ferricrocin in Entomopathogen Beauveria bassiana

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Alongkorn Amnuaykanjanasin

Metabolites 2023, 13(3), 425; https://doi.org/10.3390/metabo13030425 - 14 Mar 2023

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Abstract

Beauveria bassiana is a globally distributed entomopathogenic fungus that produces various secondary metabolites to support its pathogenesis in insects. Two polyketide synthase genes, pks14 and pks15, are highly conserved in entomopathogenic fungi and are important for insect virulence. However, understanding of their mechanisms in insect pathogenicity is still limited. Here, we overexpressed these two genes in B. bassiana and compared the metabolite profiles of pks14 and pks15 overexpression strains to those of their respective knockout strains in culture and in vivo using tandem liquid chromatography-mass spectrometry (LC-MS/MS) with Global Natural Products Social Molecular Networking (GNPS). The pks14 and pks15 clusters exhibited crosstalk with biosynthetic clusters encoding insect-virulent metabolites, including beauvericins, bassianolide, enniatin A, and the intracellular siderophore ferricrocin under certain conditions. These secondary metabolites were upregulated in the pks14-overexpressing strain in culture and the pks15-overexpressing strain in vivo. These data suggest that pks14 and pks15, their proteins or their cluster components might be directly or indirectly associated with key pathways in insect pathogenesis of B. bassiana, particularly those related to secondary metabolism. Information about interactions between the polyketide clusters and other biosynthetic clusters improves scientific understanding about crosstalk among biosynthetic pathways and mechanisms of pathogenesis. Full article

(This article belongs to the Special Issue Application of Mass Spectrometry Analysis in Metabolomics)

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Open AccessCommunication

Surface-Coated Acupuncture Needles as Solid-Phase Microextraction Probes for In Vivo Analysis of Bioactive Molecules in Living Plants by Mass Spectrometry

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Metabolites 2023, 13(2), 220; https://doi.org/10.3390/metabo13020220 - 02 Feb 2023

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Abstract

In this work, we report the coupling of solid-phase microextraction (SPME) enabled by surface-coated acupuncture needles with nano-electrospray mass spectrometry (nanoESI-MS) for the analysis of bioactive molecules in living plants. The needle tip was oxidized by a mixture of nitric acid and hydrogen peroxide solution and then subject to surface coating via carbonization of paraffin. A combination of oxidation and surface coating resulted in a thin coating of carbon film, whereby the significantly increased surface area promoted both analyte enrichment and ionization for MS analysis. The analytical performances were evaluated through the characterization of small molecules, peptides and proteins. Compared with conventional nanoESI, our new strategy of employing surface-coated needles had a high salt tolerance. The streamlined experimental workflow could be completed within one minute. The linear dynamic ranges for L-histidine and L-lysine, as two representatives, were over two orders of magnitude with a limit of detection (LOD) of 3.0~5.0 ng/mL. A mark is made on the needle at 2 mm from the tip, the needle is then kept in the sample for 30 s. In vivo sampling and identification of α-tomatine and organic acids from the stem of a living tomato plant were demonstrated as a practical application, while the physiological activities of the plant were not disrupted due to the minimally invasive sampling. We anticipate that the developed strategy may be of potential use for real-time clinical and other on-site analyses. Full article

(This article belongs to the Special Issue Application of Mass Spectrometry Analysis in Metabolomics)

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Open AccessArticle

Rapid Profiling of Metabolites Combined with Network Pharmacology to Explore the Potential Mechanism of Sanguisorba officinalis L. against Thrombocytopenia

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Metabolites 2022, 12(11), 1074; https://doi.org/10.3390/metabo12111074 - 05 Nov 2022

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Abstract

Sanguisorba officinalis L. (SO), a well-known herbal medicine, has been proven to show effect against thrombocytopenia. However, metabolites of SO in vivo are still unclear, and the underlying mechanism of SO against thrombocytopenia from the aspect of metabolites have not been well elucidated. In this study, an improved analytical method combined with UHPLC-QTOF MS and a molecular network was developed for the rapid characterization of metabolites in vivo based on fragmentation patterns. Then, network pharmacology (NP) was used to elucidate the potential mechanism of SO against thrombocytopenia. As a result, a total of 1678 exogenous metabolites were detected in urine, feces, plasma, and bone marrow, in which 104 metabolites were tentatively characterized. These characterized metabolites that originated from plasma, urine, and feces were then imported to the NP analysis. The results showed that the metabolites from plasma, urine, and feces could be responsible for the pharmacological activity against thrombocytopenia by regulating the PI3K-Akt, MAPK, JAK-STAT, VEGF, chemokine, actin cytoskeleton, HIF-1, and pluripotency of stem cells. This study provides a rapid method for metabolite characterization and a new perspective of underlying mechanism study from the aspect of active metabolites in vivo. Full article

(This article belongs to the Special Issue Application of Mass Spectrometry Analysis in Metabolomics)

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Open AccessReview

Instrumental Drift in Untargeted Metabolomics: Optimizing Data Quality with Intrastudy QC Samples

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Metabolites 2023, 13(5), 665; https://doi.org/10.3390/metabo13050665 - 16 May 2023

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Abstract

Untargeted metabolomics is an important tool in studying health and disease and is employed in fields such as biomarker discovery and drug development, as well as precision medicine. Although significant technical advances were made in the field of mass-spectrometry driven metabolomics, instrumental drifts, such as fluctuations in retention time and signal intensity, remain a challenge, particularly in large untargeted metabolomics studies. Therefore, it is crucial to consider these variations during data processing to ensure high-quality data. Here, we will provide recommendations for an optimal data processing workflow using intrastudy quality control (QC) samples that identifies errors resulting from instrumental drifts, such as shifts in retention time and metabolite intensities. Furthermore, we provide an in-depth comparison of the performance of three popular batch-effect correction methods of different complexity. By using different evaluation metrics based on QC samples and a machine learning approach based on biological samples, the performance of the batch-effect correction methods were evaluated. Here, the method TIGER demonstrated the overall best performance by reducing the relative standard deviation of the QCs and dispersion-ratio the most, as well as demonstrating the highest area under the receiver operating characteristic with three different probabilistic classifiers (Logistic regression, Random Forest, and Support Vector Machine). In summary, our recommendations will help to generate high-quality data that are suitable for further downstream processing, leading to more accurate and meaningful insights into the underlying biological processes. Full article

(This article belongs to the Special Issue Application of Mass Spectrometry Analysis in Metabolomics)

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Special Issue "Application of Mass Spectrometry Analysis in Metabolomics"

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