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Metabolites
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Spatial Metabolomics
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Spatial Metabolomics

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

Deadline for manuscript submissions: closed (30 June 2021) | Viewed by 24498

Special Issue Editors

Prof. Dr. Giuseppe Paglia

E-Mail Website
Guest Editor
School of Medicine and Surgery, University of Milano-Bicocca, 20126 Milano, Italy
Interests: metabolomics; lipidomics; ion mobility; mass spectrometry; spatial lipidomics
Special Issues, Collections and Topics in MDPI journals
Dr. Andrew Smith

E-Mail Website
Guest Editor
Clinical Proteomics and Metabolomics Unit, Department of Medicine and Surgery, University of Milano-Bicocca, 20854 Monza, Italy
Interests: mass spectrometry imaging; spatial omics; molecular pathology; kidney; oncology; proteomics; lipidomics; metabolomics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Metabolomics aims to characterize all the small molecules derived by cellular processes and it has the potential to improve our understanding of cell biology and medicine. In particular, studying metabolites and lipids in their native spatial context is at the forefront of metabolomics and lipidomics research. Along these lines, one of the latest challenges in spatial metabolomics is to map metabolites and lipids with cellular and subcellular spatial resolution. Recent instrumental advancements now allow commercial MSI instruments to offer near single-cell lateral resolutions while still having sufficient sensitivity to detect endogenous metabolites and lipids within the micromolar concentration range. Furthermore, the integration of MSI with new separation techniques, such as ion mobility, can further improve the mass resolution and annotation of isobaric and isomeric species.

Understanding metabolic processes in their native spatial context will enable a heightened understanding of cell metabolism and is fundamental for precision medicine. This Special Issue of Metabolites, “Spatial Metabolomics”, is dedicated to the strategies for investigating spatial metabolomics, and it is open to method development, bioinformatic solutions and concepts, as well as the application of spatial metabolomics to study cell metabolism and to answer biomedical questions. Contributions which search to detail the in situ metabolome of single cells are particularly welcomed.

Prof. Dr. Giuseppe Paglia
Dr. Andrew J. Smith
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

  • metabolomics
  • lipidomics
  • mass spectrometry imaging
  • ion mobility
  • bioinformatics
  • data mining
  • clinical metabolomics
  • single cell
  • metabolite annotation

Published Papers (7 papers)

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Research

12 pages, 2223 KiB  
Article
Mass Spectrometry Imaging Disclosed Spatial Distribution of Defense-Related Metabolites in Triticum spp.
by Laura Righetti, Sven Gottwald, Sara Tortorella, Bernhard Spengler and Dhaka Ram Bhandari
Metabolites 2022, 12(1), 48; https://doi.org/10.3390/metabo12010048 - 07 Jan 2022
Cited by 6 | Viewed by 1993
Abstract
Fusarium Head Blight is the most common fungal disease that strongly affects Triticum spp., reducing crop yield and leading to the accumulation of toxic metabolites. Several studies have investigated the plant metabolic response to counteract mycotoxins accumulation. However, information on the precise location [...] Read more.
Fusarium Head Blight is the most common fungal disease that strongly affects Triticum spp., reducing crop yield and leading to the accumulation of toxic metabolites. Several studies have investigated the plant metabolic response to counteract mycotoxins accumulation. However, information on the precise location where the defense mechanism is taking place is scarce. Therefore, this study aimed to investigate the specific tissue distribution of defense metabolites in two Triticum species and use this information to postulate on the metabolites’ functional role, unlocking the “location-to-function” paradigm. To address this challenge, transversal cross-sections were obtained from the middle of the grains. They were analyzed using an atmospheric-pressure (AP) SMALDI MSI source (AP-SMALDI5 AF, TransMIT GmbH, Giessen, Germany) coupled to a Q Exactive HF (Thermo Fisher Scientific GmbH, Bremen, Germany) orbital trapping mass spectrometer. Our result revealed the capability of (AP)-SMALDI MSI instrumentation to finely investigate the spatial distribution of wheat defense metabolites, such as hydroxycinnamic acid amides, oxylipins, linoleic and α-linoleic acids, galactolipids, and glycerolipids. Full article
(This article belongs to the Special Issue Spatial Metabolomics)
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14 pages, 6009 KiB  
Communication
Lipidomic Typing of Colorectal Cancer Tissue Containing Tumour-Infiltrating Lymphocytes by MALDI Mass Spectrometry Imaging
by Vanna Denti, Allia Mahajneh, Giulia Capitoli, Francesca Clerici, Isabella Piga, Lisa Pagani, Clizia Chinello, Maddalena Maria Bolognesi, Giuseppe Paglia, Stefania Galimberti, Fulvio Magni and Andrew Smith
Metabolites 2021, 11(9), 599; https://doi.org/10.3390/metabo11090599 - 05 Sep 2021
Cited by 12 | Viewed by 3455
Abstract
Predicting the prognosis of colorectal cancer (CRC) patients remains challenging and a characterisation of the tumour immune environment represents one of the most crucial avenues when attempting to do so. For this reason, molecular approaches which are capable of classifying the immune environments [...] Read more.
Predicting the prognosis of colorectal cancer (CRC) patients remains challenging and a characterisation of the tumour immune environment represents one of the most crucial avenues when attempting to do so. For this reason, molecular approaches which are capable of classifying the immune environments associated with tumour infiltrating lymphocytes (TILs) are being readily investigated. In this proof of concept study, we aim to explore the feasibility of using spatial lipidomics by MALDI-MSI to distinguish CRC tissue based upon their TIL content. Formalin-fixed paraffin-embedded tissue from human thymus and tonsil was first analysed by MALDI-MSI to obtain a curated mass list from a pool of single positive T lymphocytes, whose putative identities were annotated using an LC-MS-based lipidomic approach. A CRC tissue microarray (TMA, n = 30) was then investigated to determine whether these cases could be distinguished based upon their TIL content in the tumour and its microenvironment. MALDI-MSI from the pool of mature T lymphocytes resulted in the generation of a curated mass list containing 18 annotated m/z features. Initially, subsets of T lymphocytes were then distinguished based on their state of maturation and differentiation in the human thymus and tonsil tissue. Then, when applied to a CRC TMA containing differing amounts of T lymphocyte infiltration, those cases with a high TIL content were distinguishable from those with a lower TIL content, especially within the tumour microenvironment, with three lipid signals being shown to have the greatest impact on this separation (p < 0.05). On the whole, this preliminary study represents a promising starting point and suggests that a lipidomics MALDI-MSI approach could be a promising tool for subtyping the diverse immune environments in CRC. Full article
(This article belongs to the Special Issue Spatial Metabolomics)
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15 pages, 22247 KiB  
Article
Reproducible Lipid Alterations in Patient-Derived Breast Cancer Xenograft FFPE Tissue Identified with MALDI MSI for Pre-Clinical and Clinical Application
by Vanna Denti, Maria K. Andersen, Andrew Smith, Anna Mary Bofin, Anna Nordborg, Fulvio Magni, Siver Andreas Moestue and Marco Giampà
Metabolites 2021, 11(9), 577; https://doi.org/10.3390/metabo11090577 - 26 Aug 2021
Cited by 8 | Viewed by 4267
Abstract
The association between lipid metabolism and long-term outcomes is relevant for tumor diagnosis and therapy. Archival material such as formalin-fixed and paraffin embedded (FFPE) tissues is a highly valuable resource for this aim as it is linked to long-term clinical follow-up. Therefore, there [...] Read more.
The association between lipid metabolism and long-term outcomes is relevant for tumor diagnosis and therapy. Archival material such as formalin-fixed and paraffin embedded (FFPE) tissues is a highly valuable resource for this aim as it is linked to long-term clinical follow-up. Therefore, there is a need to develop robust methodologies able to detect lipids in FFPE material and correlate them with clinical outcomes. In this work, lipidic alterations were investigated in patient-derived xenograft of breast cancer by using a matrix-assisted laser desorption ionization mass spectrometry (MALDI MSI) based workflow that included antigen retrieval as a sample preparation step. We evaluated technical reproducibility, spatial metabolic differentiation within tissue compartments, and treatment response induced by a glutaminase inhibitor (CB-839). This protocol shows a good inter-day robustness (CV = 26 ± 12%). Several lipids could reliably distinguish necrotic and tumor regions across the technical replicates. Moreover, this protocol identified distinct alterations in the tissue lipidome of xenograft treated with glutaminase inhibitors. In conclusion, lipidic alterations in FFPE tissue of breast cancer xenograft observed in this study are a step-forward to a robust and reproducible MALDI-MSI based workflow for pre-clinical and clinical applications. Full article
(This article belongs to the Special Issue Spatial Metabolomics)
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9 pages, 984 KiB  
Communication
Multi-Modal Mass Spectrometric Imaging of Uveal Melanoma
by Laura M. Cole, Joshua Handley, Emmanuelle Claude, Catherine J. Duckett, Hardeep S. Mudhar, Karen Sisley and Malcolm R. Clench
Metabolites 2021, 11(8), 560; https://doi.org/10.3390/metabo11080560 - 23 Aug 2021
Cited by 2 | Viewed by 2994
Abstract
Matrix assisted laser desorption ionisation mass spectrometry imaging (MALDI-MSI), was used to obtain images of lipids and metabolite distribution in formalin fixed and embedded in paraffin (FFPE) whole eye sections containing primary uveal melanomas (UM). Using this technique, it was possible to obtain [...] Read more.
Matrix assisted laser desorption ionisation mass spectrometry imaging (MALDI-MSI), was used to obtain images of lipids and metabolite distribution in formalin fixed and embedded in paraffin (FFPE) whole eye sections containing primary uveal melanomas (UM). Using this technique, it was possible to obtain images of lysophosphatidylcholine (LPC) type lipid distribution that highlighted the tumour regions. Laser ablation inductively coupled plasma mass spectrometry images (LA-ICP-MS) performed on UM sections showed increases in copper within the tumour periphery and intratumoural zinc in tissue from patients with poor prognosis. These preliminary data indicate that multi-modal MSI has the potential to provide insights into the role of trace metals and cancer metastasis. Full article
(This article belongs to the Special Issue Spatial Metabolomics)
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21 pages, 7839 KiB  
Article
Comparison of Osteosarcoma Aggregated Tumour Models with Human Tissue by Multimodal Mass Spectrometry Imaging
by Lucy E. Flint, Gregory Hamm, Joseph D. Ready, Stephanie Ling, Catherine J. Duckett, Neil A. Cross, Laura M. Cole, David P. Smith, Richard J. A. Goodwin and Malcolm R. Clench
Metabolites 2021, 11(8), 506; https://doi.org/10.3390/metabo11080506 - 31 Jul 2021
Cited by 4 | Viewed by 4084
Abstract
Osteosarcoma (OS) is the most common primary bone malignancy and largely effects adolescents and young adults, with 60% of patients under the age of 25. There are multiple cell models of OS described in vitro that express the specific genetic alterations of the [...] Read more.
Osteosarcoma (OS) is the most common primary bone malignancy and largely effects adolescents and young adults, with 60% of patients under the age of 25. There are multiple cell models of OS described in vitro that express the specific genetic alterations of the sarcoma. In the work reported here, multiple mass spectrometry imaging (MSI) modalities were employed to characterise two aggregated cellular models of OS models formed using the MG63 and SAOS-2 cell lines. Phenotyping of the metabolite activity within the two OS aggregoid models was achieved and a comparison of the metabolite data with OS human tissue samples revealed relevant fatty acid and phospholipid markers. Although, annotations of these species require MS/MS analysis for confident identification of the metabolites. From the putative assignments however, it was suggested that the MG63 aggregoids are an aggressive tumour model that exhibited metastatic-like potential. Alternatively, the SAOS-2 aggregoids are more mature osteoblast-like phenotype that expressed characteristics of cellular differentiation and bone development. It was determined the two OS aggregoid models shared similarities of metabolic behaviour with different regions of OS human tissues, specifically of the higher metastatic grade. Full article
(This article belongs to the Special Issue Spatial Metabolomics)
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9 pages, 1000 KiB  
Communication
Facilitating Imaging Mass Spectrometry of Microbial Specialized Metabolites with METASPACE
by Don D. Nguyen, Veronika Saharuka, Vitaly Kovalev, Lachlan Stuart, Massimo Del Prete, Kinga Lubowiecka, René De Mot, Vittorio Venturi and Theodore Alexandrov
Metabolites 2021, 11(8), 477; https://doi.org/10.3390/metabo11080477 - 23 Jul 2021
Cited by 9 | Viewed by 2788
Abstract
Metabolite annotation from imaging mass spectrometry (imaging MS) data is a difficult undertaking that is extremely resource intensive. Here, we adapted METASPACE, cloud software for imaging MS metabolite annotation and data interpretation, to quickly annotate microbial specialized metabolites from high-resolution and high-mass accuracy [...] Read more.
Metabolite annotation from imaging mass spectrometry (imaging MS) data is a difficult undertaking that is extremely resource intensive. Here, we adapted METASPACE, cloud software for imaging MS metabolite annotation and data interpretation, to quickly annotate microbial specialized metabolites from high-resolution and high-mass accuracy imaging MS data. Compared with manual ion image and MS1 annotation, METASPACE is faster and, with the appropriate database, more accurate. We applied it to data from microbial colonies grown on agar containing 10 diverse bacterial species and showed that METASPACE was able to annotate 53 ions corresponding to 32 different microbial metabolites. This demonstrates METASPACE to be a useful tool to annotate the chemistry and metabolic exchange factors found in microbial interactions, thereby elucidating the functions of these molecules. Full article
(This article belongs to the Special Issue Spatial Metabolomics)
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18 pages, 7705 KiB  
Article
Mass Spectrometry Imaging as a Tool to Investigate Region Specific Lipid Alterations in Symptomatic Human Carotid Atherosclerotic Plaques
by Francesco Greco, Laura Quercioli, Angela Pucci, Silvia Rocchiccioli, Mauro Ferrari, Fabio A. Recchia and Liam A. McDonnell
Metabolites 2021, 11(4), 250; https://doi.org/10.3390/metabo11040250 - 18 Apr 2021
Cited by 16 | Viewed by 2925
Abstract
Atherosclerosis is characterized by fatty plaques in large and medium sized arteries. Their rupture can causes thrombi, occlusions of downstream vessels and adverse clinical events. The investigation of atherosclerotic plaques is made difficult by their highly heterogeneous nature. Here we propose a spatially [...] Read more.
Atherosclerosis is characterized by fatty plaques in large and medium sized arteries. Their rupture can causes thrombi, occlusions of downstream vessels and adverse clinical events. The investigation of atherosclerotic plaques is made difficult by their highly heterogeneous nature. Here we propose a spatially resolved approach based on matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging to investigate lipids in specific regions of atherosclerotic plaques. The method was applied to a small dataset including symptomatic and asymptomatic human carotid atherosclerosis plaques. Tissue sections of symptomatic and asymptomatic human carotid atherosclerotic plaques were analyzed by MALDI mass spectrometry imaging (MALDI MSI) of lipids, and adjacent sections analyzed by histology and immunofluorescence. These multimodal datasets were used to compare the lipid profiles of specific histopathological regions within the plaque. The lipid profiles of macrophage-rich regions and intimal vascular smooth muscle cells exhibited the largest changes associated with plaque outcome. Macrophage-rich regions from symptomatic lesions were found to be enriched in sphingomyelins, and intimal vascular smooth muscle cells of symptomatic plaques were enriched in cholesterol and cholesteryl esters. The proposed method enabled the MALDI MSI analysis of specific regions of the atherosclerotic lesion, confirming MALDI MSI as a promising tool for the investigation of histologically heterogeneous atherosclerotic plaques. Full article
(This article belongs to the Special Issue Spatial Metabolomics)
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