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Hernly E, Hu H, Laskin J. MSIGen: An Open-Source Python Package for Processing and Visualizing Mass Spectrometry Imaging Data. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2024. [PMID: 39221961 DOI: 10.1021/jasms.4c00178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/04/2024]
Abstract
Mass spectrometry imaging (MSI) provides information about the spatial localization of molecules in complex samples with high sensitivity and molecular selectivity. Although point-wise data acquisition, in which mass spectra are acquired at predefined points in a grid pattern, is common in MSI, several MSI techniques use line-wise data acquisition. In line-wise mode, the imaged surface is continuously sampled along consecutive parallel lines and MSI data are acquired as a collection of line scans across the sample. Furthermore, aside from the standard imaging mode in which full mass spectra are acquired, other acquisition modes have been developed to enhance molecular specificity, enable separation of isobaric and isomeric species, and improve sensitivity to facilitate the imaging of low abundance species. These methods, including MS/MS-MSI in both MS2 and MS3 modes, multiple-reaction monitoring (MRM)-MSI, and ion mobility spectrometry (IMS)-MSI have all demonstrated their capabilities, but their broader implementation is limited by the existing MSI analysis software. Here, we present MSIGen, an open-source Python package for the visualization of MSI experiments performed in line-wise acquisition mode containing MS1, MS2, MRM, and IMS data, which is available at https://github.com/LabLaskin/MSIGen. The package supports multiple vendor-specific and open-source data formats and contains tools for targeted extraction of ion images, normalization, and exportation as images, arrays, or publication-style images. MSIGen offers multiple interfaces, allowing for accessibility and easy integration with other workflows. Considering its support for a wide variety of MSI imaging modes and vendor formats, MSIGen is a valuable tool for the visualization and analysis of MSI data.
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Affiliation(s)
- Emerson Hernly
- Department of Chemistry, Purdue University, West Lafayette, Indiana 47907, United States
| | - Hang Hu
- Department of Chemistry, Purdue University, West Lafayette, Indiana 47907, United States
| | - Julia Laskin
- Department of Chemistry, Purdue University, West Lafayette, Indiana 47907, United States
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2
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Leontyev D, Olivos H, Shrestha B, Datta Roy PM, LaPlaca MC, Fernández FM. Desorption Electrospray Ionization Cyclic Ion Mobility-Mass Spectrometry Imaging for Traumatic Brain Injury Spatial Metabolomics. Anal Chem 2024; 96:13598-13606. [PMID: 39106040 PMCID: PMC11339727 DOI: 10.1021/acs.analchem.4c02394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 07/20/2024] [Accepted: 07/25/2024] [Indexed: 08/07/2024]
Abstract
Lipidomics focuses on investigating alterations in a wide variety of lipids that harness important information on metabolic processes and disease pathology. However, the vast structural diversity of lipids and the presence of isobaric and isomeric species creates serious challenges in feature identification, particularly in mass spectrometry imaging experiments that lack front-end separations. Ion mobility has emerged as a potential solution to address some of these challenges and is increasingly being utilized as part of mass spectrometry imaging platforms. Here, we present the results of a pilot mass spectrometry imaging study on rat brains subjected to traumatic brain injury (TBI) to evaluate the depth and quality of the information yielded by desorption electrospray ionization cyclic ion mobility mass spectrometry (DESI cIM MSI). Imaging data were collected with one and six passes through the cIM cell. Increasing the number of passes increased the ion mobility resolving power and the resolution of isobaric lipids, enabling the creation of more specific maps. Interestingly, drift time data enabled the recognition of multiply charged phosphoinositide species in the complex data set generated. These species have not been previously reported in TBI MSI studies and were found to decrease in the hippocampus region following injury. These changes were attributed to increased enzymatic activity after TBI, releasing arachidonic acid that is converted to eicosanoids to control inflammation. A substantial reduction in NAD and alterations in other adenine metabolites were also observed, supporting the hypothesis that energy metabolism in the brain is severely disrupted in TBI.
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Affiliation(s)
- Dmitry Leontyev
- School
of Chemistry and Biochemistry, Georgia Institute
of Technology, Atlanta, Georgia 30332, United State
| | - Hernando Olivos
- Waters
Corporation, Milford, Massachusetts 01757, United State
| | | | - Pooja M. Datta Roy
- Coulter
Department of Biomedical Engineering, Georgia
Institute of Technology/Emory University, Atlanta, Georgia 30332, United State
| | - Michelle C. LaPlaca
- Coulter
Department of Biomedical Engineering, Georgia
Institute of Technology/Emory University, Atlanta, Georgia 30332, United State
- Parker
H. Petit Institute for Bioengineering and Bioscience, Atlanta, Georgia 30332, United
States
| | - Facundo M. Fernández
- School
of Chemistry and Biochemistry, Georgia Institute
of Technology, Atlanta, Georgia 30332, United State
- Parker
H. Petit Institute for Bioengineering and Bioscience, Atlanta, Georgia 30332, United
States
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3
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Colley ME, Esselman AB, Scott CF, Spraggins JM. High-Specificity Imaging Mass Spectrometry. ANNUAL REVIEW OF ANALYTICAL CHEMISTRY (PALO ALTO, CALIF.) 2024; 17:1-24. [PMID: 38594938 DOI: 10.1146/annurev-anchem-083023-024546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/11/2024]
Abstract
Imaging mass spectrometry (IMS) enables highly multiplexed, untargeted tissue mapping for a broad range of molecular classes, facilitating in situ biological discovery. Yet, challenges persist in molecular specificity, which is the ability to discern one molecule from another, and spatial specificity, which is the ability to link untargeted imaging data to specific tissue features. Instrumental developments have dramatically improved IMS spatial resolution, allowing molecular observations to be more readily associated with distinct tissue features across spatial scales, ranging from larger anatomical regions to single cells. High-performance mass analyzers and systems integrating ion mobility technologies are also becoming more prevalent, further improving molecular coverage and the ability to discern chemical identity. This review provides an overview of recent advancements in high-specificity IMS that are providing critical biological context to untargeted molecular imaging, enabling integrated analyses, and addressing advanced biomedical research applications.
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Affiliation(s)
- Madeline E Colley
- 1Department of Biochemistry, Vanderbilt University, Nashville, Tennessee, USA;
- 2Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee, USA
| | - Allison B Esselman
- 2Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee, USA
- 3Department of Chemistry, Vanderbilt University, Nashville, Tennessee, USA
| | - Claire F Scott
- 2Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee, USA
- 4Department of Cell and Developmental Biology, Vanderbilt University, Nashville, Tennessee, USA
| | - Jeffrey M Spraggins
- 1Department of Biochemistry, Vanderbilt University, Nashville, Tennessee, USA;
- 2Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee, USA
- 3Department of Chemistry, Vanderbilt University, Nashville, Tennessee, USA
- 4Department of Cell and Developmental Biology, Vanderbilt University, Nashville, Tennessee, USA
- 5Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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4
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Ross DH, Bhotika H, Zheng X, Smith RD, Burnum-Johnson KE, Bilbao A. Computational tools and algorithms for ion mobility spectrometry-mass spectrometry. Proteomics 2024; 24:e2200436. [PMID: 38438732 DOI: 10.1002/pmic.202200436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 02/12/2024] [Accepted: 02/14/2024] [Indexed: 03/06/2024]
Abstract
Ion mobility spectrometry-mass spectrometry (IMS-MS or IM-MS) is a powerful analytical technique that combines the gas-phase separation capabilities of IM with the identification and quantification capabilities of MS. IM-MS can differentiate molecules with indistinguishable masses but different structures (e.g., isomers, isobars, molecular classes, and contaminant ions). The importance of this analytical technique is reflected by a staged increase in the number of applications for molecular characterization across a variety of fields, from different MS-based omics (proteomics, metabolomics, lipidomics, etc.) to the structural characterization of glycans, organic matter, proteins, and macromolecular complexes. With the increasing application of IM-MS there is a pressing need for effective and accessible computational tools. This article presents an overview of the most recent free and open-source software tools specifically tailored for the analysis and interpretation of data derived from IM-MS instrumentation. This review enumerates these tools and outlines their main algorithmic approaches, while highlighting representative applications across different fields. Finally, a discussion of current limitations and expectable improvements is presented.
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Affiliation(s)
- Dylan H Ross
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Harsh Bhotika
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Xueyun Zheng
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Richard D Smith
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Kristin E Burnum-Johnson
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Aivett Bilbao
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington, USA
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5
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Ma X, Fernández FM. Advances in mass spectrometry imaging for spatial cancer metabolomics. MASS SPECTROMETRY REVIEWS 2024; 43:235-268. [PMID: 36065601 PMCID: PMC9986357 DOI: 10.1002/mas.21804] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 08/02/2022] [Accepted: 08/02/2022] [Indexed: 05/09/2023]
Abstract
Mass spectrometry (MS) has become a central technique in cancer research. The ability to analyze various types of biomolecules in complex biological matrices makes it well suited for understanding biochemical alterations associated with disease progression. Different biological samples, including serum, urine, saliva, and tissues have been successfully analyzed using mass spectrometry. In particular, spatial metabolomics using MS imaging (MSI) allows the direct visualization of metabolite distributions in tissues, thus enabling in-depth understanding of cancer-associated biochemical changes within specific structures. In recent years, MSI studies have been increasingly used to uncover metabolic reprogramming associated with cancer development, enabling the discovery of key biomarkers with potential for cancer diagnostics. In this review, we aim to cover the basic principles of MSI experiments for the nonspecialists, including fundamentals, the sample preparation process, the evolution of the mass spectrometry techniques used, and data analysis strategies. We also review MSI advances associated with cancer research in the last 5 years, including spatial lipidomics and glycomics, the adoption of three-dimensional and multimodal imaging MSI approaches, and the implementation of artificial intelligence/machine learning in MSI-based cancer studies. The adoption of MSI in clinical research and for single-cell metabolomics is also discussed. Spatially resolved studies on other small molecule metabolites such as amino acids, polyamines, and nucleotides/nucleosides will not be discussed in the context.
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Affiliation(s)
- Xin Ma
- School of Chemistry and Biochemistry and Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Facundo M Fernández
- School of Chemistry and Biochemistry and Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia, USA
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6
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Abstract
Imaging mass spectrometry is a well-established technology that can easily and succinctly communicate the spatial localization of molecules within samples. This review communicates the recent advances in the field, with a specific focus on matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) applied on tissues. The general sample preparation strategies for different analyte classes are explored, including special considerations for sample types (fresh frozen or formalin-fixed,) strategies for various analytes (lipids, metabolites, proteins, peptides, and glycans) and how multimodal imaging strategies can leverage the strengths of each approach is mentioned. This work explores appropriate experimental design approaches and standardization of processes needed for successful studies, as well as the various data analysis platforms available to analyze data and their strengths. The review concludes with applications of imaging mass spectrometry in various fields, with a focus on medical research, and some examples from plant biology and microbe metabolism are mentioned, to illustrate the breadth and depth of MALDI IMS.
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Affiliation(s)
- Jessica L Moore
- Department of Proteomics, Discovery Life Sciences, Huntsville, Alabama 35806, United States
| | - Georgia Charkoftaki
- Department of Environmental Health Sciences, Yale School of Public Health, Yale University, New Haven, Connecticut 06520, United States
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7
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Yang M, Unsihuay D, Hu H, Meke FN, Qu Z, Zhang ZY, Laskin J. Nano-DESI Mass Spectrometry Imaging of Proteoforms in Biological Tissues with High Spatial Resolution. Anal Chem 2023; 95:5214-5222. [PMID: 36917636 PMCID: PMC11330692 DOI: 10.1021/acs.analchem.2c04795] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
Abstract
Mass spectrometry imaging (MSI) is a powerful tool for label-free mapping of the spatial distribution of proteins in biological tissues. We have previously demonstrated imaging of individual proteoforms in biological tissues using nanospray desorption electrospray ionization (nano-DESI), an ambient liquid extraction-based MSI technique. Nano-DESI MSI generates multiply charged protein ions, which is advantageous for their identification using top-down proteomics analysis. In this study, we demonstrate proteoform mapping in biological tissues with a spatial resolution down to 7 μm using nano-DESI MSI. A substantial decrease in protein signals observed in high-spatial-resolution MSI makes these experiments challenging. We have enhanced the sensitivity of nano-DESI MSI experiments by optimizing the design of the capillary-based probe and the thickness of the tissue section. In addition, we demonstrate that oversampling may be used to further improve spatial resolution at little or no expense to sensitivity. These developments represent a new step in MSI-based spatial proteomics, which complements targeted imaging modalities widely used for studying biological systems.
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Affiliation(s)
- Manxi Yang
- Department of Chemistry, Purdue University, West Lafayette, IN, 47907, USA
| | - Daisy Unsihuay
- Department of Chemistry, Purdue University, West Lafayette, IN, 47907, USA
| | - Hang Hu
- Department of Chemistry, Purdue University, West Lafayette, IN, 47907, USA
| | - Frederick Nguele Meke
- Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, IN, 47907, USA
| | - Zihan Qu
- Department of Chemistry, Purdue University, West Lafayette, IN, 47907, USA
- Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, IN, 47907, USA
| | - Zhong-Yin Zhang
- Department of Chemistry, Purdue University, West Lafayette, IN, 47907, USA
- Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, IN, 47907, USA
| | - Julia Laskin
- Department of Chemistry, Purdue University, West Lafayette, IN, 47907, USA
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8
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Caleb Bagley M, Garrard KP, Muddiman DC. The development and application of matrix assisted laser desorption electrospray ionization: The teenage years. MASS SPECTROMETRY REVIEWS 2023; 42:35-66. [PMID: 34028071 DOI: 10.1002/mas.21696] [Citation(s) in RCA: 31] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 04/20/2021] [Accepted: 04/21/2021] [Indexed: 05/24/2023]
Abstract
In the past 15 years, ambient ionization techniques have witnessed a significant incursion into the field of mass spectrometry imaging, demonstrating their ability to provide complementary information to matrix-assisted laser desorption ionization. Matrix-assisted laser desorption electrospray ionization is one such technique that has evolved since its first demonstrations with ultraviolet lasers coupled to Fourier transform-ion cyclotron resonance mass spectrometers to extensive use with infrared lasers coupled to orbitrap-based mass spectrometers. Concurrently, there have been transformative developments of this imaging platform due to the high level of control the principal group has retained over the laser technology, data acquisition software (RastirX), instrument communication, and image processing software (MSiReader). This review will discuss the developments of MALDESI since its first laboratory demonstration in 2005 to the most recent advances in 2021.
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Affiliation(s)
- Michael Caleb Bagley
- FTMS Laboratory for Human Health Research, Department of Chemistry, North Carolina State University, Raleigh, North Carolina, USA
| | - Kenneth P Garrard
- FTMS Laboratory for Human Health Research, Department of Chemistry, North Carolina State University, Raleigh, North Carolina, USA
- The Precision Engineering Consortium, North Carolina State University, Raleigh, North Carolina, USA
- Molecular Education, Technology, and Research Innovation Center (METRIC), North Carolina State University, Raleigh, North Carolina, USA
| | - David C Muddiman
- FTMS Laboratory for Human Health Research, Department of Chemistry, North Carolina State University, Raleigh, North Carolina, USA
- Molecular Education, Technology, and Research Innovation Center (METRIC), North Carolina State University, Raleigh, North Carolina, USA
- Department of Plant and Microbial Biology, North Carolina State University, Raleigh, North Carolina, USA
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9
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Harvey DJ. Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2019-2020. MASS SPECTROMETRY REVIEWS 2022:e21806. [PMID: 36468275 DOI: 10.1002/mas.21806] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2020. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. The review is basically divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of arrays. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other areas such as medicine, industrial processes and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. The reported work shows increasing use of incorporation of new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented nearly 40 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show little sign of diminishing.
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Affiliation(s)
- David J Harvey
- Nuffield Department of Medicine, Target Discovery Institute, University of Oxford, Oxford, UK
- Department of Chemistry, University of Oxford, Oxford, Oxfordshire, United Kingdom
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10
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High-end ion mobility mass spectrometry: A current review of analytical capacity in omics applications and structural investigations. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116761] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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11
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Hu H, Laskin J. Emerging Computational Methods in Mass Spectrometry Imaging. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2203339. [PMID: 36253139 PMCID: PMC9731724 DOI: 10.1002/advs.202203339] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 09/17/2022] [Indexed: 05/10/2023]
Abstract
Mass spectrometry imaging (MSI) is a powerful analytical technique that generates maps of hundreds of molecules in biological samples with high sensitivity and molecular specificity. Advanced MSI platforms with capability of high-spatial resolution and high-throughput acquisition generate vast amount of data, which necessitates the development of computational tools for MSI data analysis. In addition, computation-driven MSI experiments have recently emerged as enabling technologies for further improving the MSI capabilities with little or no hardware modification. This review provides a critical summary of computational methods and resources developed for MSI data analysis and interpretation along with computational approaches for improving throughput and molecular coverage in MSI experiments. This review is focused on the recently developed artificial intelligence methods and provides an outlook for a future paradigm shift in MSI with transformative computational methods.
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Affiliation(s)
- Hang Hu
- Department of ChemistryPurdue University560 Oval DriveWest LafayetteIN47907USA
| | - Julia Laskin
- Department of ChemistryPurdue University560 Oval DriveWest LafayetteIN47907USA
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12
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Ma S, Leng Y, Li X, Meng Y, Yin Z, Hang W. High spatial resolution mass spectrometry imaging for spatial metabolomics: Advances, challenges, and future perspectives. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
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13
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Mass spectrometry imaging of diclofenac and its metabolites in tissues using nanospray desorption electrospray ionization. Anal Chim Acta 2022; 1233:340490. [DOI: 10.1016/j.aca.2022.340490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 09/20/2022] [Accepted: 10/05/2022] [Indexed: 11/19/2022]
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14
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Rensner JJ, Lee YJ. Efficient Hydrogen-Deuterium Exchange in Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging for Confident Metabolite Identification. Anal Chem 2022; 94:11129-11133. [PMID: 35917496 DOI: 10.1021/acs.analchem.2c00978] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Highly efficient hydrogen-deuterium exchange (HDX) is developed for mass spectrometry imaging (MSI) with low-vacuum matrix-assisted laser desorption/ionization (MALDI). A HDX efficiency of 73-85% is achieved by introducing D2O vapor into a heated MALDI source in combination with a deuterium-labeled matrix, which allows correct determination of the number of possible H/D exchanges for up to 17 labile hydrogens. This provides valuable orthogonal information to supplement m/z, allowing for increased confidence in metabolite identification while retaining the spatial information MSI supplies. When combined with high-throughput METASPACE annotation, this approach can systematically improve untargeted metabolite annotations in MALDI-MS imaging. The developed method was applied to MALDI-MS imaging of the top surface, bottom surface, and middle section of Lemna minor fronds. Out of a total of 56 on-sample annotations made with the BraChem database using a 10% false discovery rate, 31 of these annotations (55%) matched our HDX data, providing additional confidence. For the remaining 45%, our data allowed us to narrow down structural possibilities and eliminate incorrect structures, greatly increasing confidence in metabolite identification.
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Affiliation(s)
- Josiah J Rensner
- Department of Chemistry, Iowa State University, Ames Iowa 50011, United States
| | - Young Jin Lee
- Department of Chemistry, Iowa State University, Ames Iowa 50011, United States
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15
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Baquer G, Sementé L, Mahamdi T, Correig X, Ràfols P, García-Altares M. What are we imaging? Software tools and experimental strategies for annotation and identification of small molecules in mass spectrometry imaging. MASS SPECTROMETRY REVIEWS 2022:e21794. [PMID: 35822576 DOI: 10.1002/mas.21794] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Mass spectrometry imaging (MSI) has become a widespread analytical technique to perform nonlabeled spatial molecular identification. The Achilles' heel of MSI is the annotation and identification of molecular species due to intrinsic limitations of the technique (lack of chromatographic separation and the difficulty to apply tandem MS). Successful strategies to perform annotation and identification combine extra analytical steps, like using orthogonal analytical techniques to identify compounds; with algorithms that integrate the spectral and spatial information. In this review, we discuss different experimental strategies and bioinformatics tools to annotate and identify compounds in MSI experiments. We target strategies and tools for small molecule applications, such as lipidomics and metabolomics. First, we explain how sample preparation and the acquisition process influences annotation and identification, from sample preservation to the use of orthogonal techniques. Then, we review twelve software tools for annotation and identification in MSI. Finally, we offer perspectives on two current needs of the MSI community: the adaptation of guidelines for communicating confidence levels in identifications; and the creation of a standard format to store and exchange annotations and identifications in MSI.
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Affiliation(s)
- Gerard Baquer
- Department of Electronic Engineering, University Rovira I Virgili, Tarragona, Spain
| | - Lluc Sementé
- Department of Electronic Engineering, University Rovira I Virgili, Tarragona, Spain
| | - Toufik Mahamdi
- Department of Electronic Engineering, University Rovira I Virgili, Tarragona, Spain
| | - Xavier Correig
- Department of Electronic Engineering, University Rovira I Virgili, Tarragona, Spain
- Spanish Biomedical Research Center in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid, Spain
- Institut D'Investigacio Sanitaria Pere Virgili, Tarragona, Spain
| | - Pere Ràfols
- Department of Electronic Engineering, University Rovira I Virgili, Tarragona, Spain
- Spanish Biomedical Research Center in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid, Spain
- Institut D'Investigacio Sanitaria Pere Virgili, Tarragona, Spain
| | - María García-Altares
- Department of Electronic Engineering, University Rovira I Virgili, Tarragona, Spain
- Spanish Biomedical Research Center in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid, Spain
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16
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Müller WH, Verdin A, De Pauw E, Malherbe C, Eppe G. Surface-assisted laser desorption/ionization mass spectrometry imaging: A review. MASS SPECTROMETRY REVIEWS 2022; 41:373-420. [PMID: 33174287 PMCID: PMC9292874 DOI: 10.1002/mas.21670] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 10/22/2020] [Accepted: 10/24/2020] [Indexed: 05/04/2023]
Abstract
In the last decades, surface-assisted laser desorption/ionization mass spectrometry (SALDI-MS) has attracted increasing interest due to its unique capabilities, achievable through the nanostructured substrates used to promote the analyte desorption/ionization. While the most widely recognized asset of SALDI-MS is the untargeted analysis of small molecules, this technique also offers the possibility of targeted approaches. In particular, the implementation of SALDI-MS imaging (SALDI-MSI), which is the focus of this review, opens up new opportunities. After a brief discussion of the nomenclature and the fundamental mechanisms associated with this technique, which are still highly controversial, the analytical strategies to perform SALDI-MSI are extensively discussed. Emphasis is placed on the sample preparation but also on the selection of the nanosubstrate (in terms of chemical composition and morphology) as well as its functionalization possibilities for the selective analysis of specific compounds in targeted approaches. Subsequently, some selected applications of SALDI-MSI in various fields (i.e., biomedical, biological, environmental, and forensic) are presented. The strengths and the remaining limitations of SALDI-MSI are finally summarized in the conclusion and some perspectives of this technique, which has a bright future, are proposed in this section.
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Affiliation(s)
- Wendy H. Müller
- Mass Spectrometry Laboratory, MolSys Research Unit, Chemistry DepartmentUniversity of LiègeLiègeBelgium
| | - Alexandre Verdin
- Mass Spectrometry Laboratory, MolSys Research Unit, Chemistry DepartmentUniversity of LiègeLiègeBelgium
| | - Edwin De Pauw
- Mass Spectrometry Laboratory, MolSys Research Unit, Chemistry DepartmentUniversity of LiègeLiègeBelgium
| | - Cedric Malherbe
- Mass Spectrometry Laboratory, MolSys Research Unit, Chemistry DepartmentUniversity of LiègeLiègeBelgium
| | - Gauthier Eppe
- Mass Spectrometry Laboratory, MolSys Research Unit, Chemistry DepartmentUniversity of LiègeLiègeBelgium
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17
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Hou J, Zhang Z, Zhang L, Wu W, Huang Y, Jia Z, Zhou L, Gao L, Long H, Lei M, Wu W, Guo DA. Spatial lipidomics of eight edible nuts by desorption electrospray ionization with ion mobility mass spectrometry imaging. Food Chem 2022; 371:130893. [PMID: 34808757 DOI: 10.1016/j.foodchem.2021.130893] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 07/16/2021] [Accepted: 08/16/2021] [Indexed: 12/19/2022]
Abstract
Nuts have long been known for their health benefits which are mainly contributed by their lipid components. However, the spatial distribution of lipids in nuts has not been firmly established. In this study, desorption electrospray ionization combined with ion mobility and quadrupole time-of-flight mass spectrometry in positive and negative ion modes was applied to visualize spatially the lipids in eight edible nuts, namely almonds, hazelnuts, cashews, walnuts, peanuts, peach seeds, bitter almonds, and Chinese dwarf cherry seeds. The glycerophospholipids were first imaged in nuts in the negative ion mode, while the glycerolipids and phosphatidylcholines were mainly detected in the positive ion mode. In total 87 characterized components, including 47 glycerophospholipids, 24 glycerolipids, eight alkyl phenolic acids, three fatty acid acyl metabolites, four oligosaccharides, and amygdalin, were visualized in the eight nuts, and the collision cross-sectional values of these components were obtained. The outer shell of the nut cotyledon concentrated more abundant components than the center, while for the hydrolyzed glycerophospholipids, the reverse was observed. The results provide a more comprehensive and in-depth understanding of the location of the diverse metabolite profiles in nuts and of their relationship to their respective health benefits.
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Affiliation(s)
- Jinjun Hou
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Zijia Zhang
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Linlin Zhang
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Wenyong Wu
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China; School of Chinese Materia Medica, Nanjing University of Chinese Medicine, Nanjing 210029, China
| | - Yong Huang
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Zhengwei Jia
- Waters Technologies (Shanghai) Ltd., No. 1000 Jinhai Road, Shanghai 201203, China
| | - Lihong Zhou
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Lei Gao
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Huali Long
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Min Lei
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wanying Wu
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - De-An Guo
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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18
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Unsihuay D, Yin R, Sanchez DM, Yang M, Li Y, Sun X, Dey SK, Laskin J. High-resolution imaging and identification of biomolecules using Nano-DESI coupled to ion mobility spectrometry. Anal Chim Acta 2021; 1186:339085. [PMID: 34756271 DOI: 10.1016/j.aca.2021.339085] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 09/15/2021] [Accepted: 09/19/2021] [Indexed: 10/20/2022]
Abstract
Simultaneous spatial localization and structural characterization of molecules in complex biological samples currently represents an analytical challenge for mass spectrometry imaging (MSI) techniques. In this study, we describe a novel experimental platform, which substantially expands the capabilities and enhances the depth of chemical information obtained in high spatial resolution MSI experiments performed using nanospray desorption electrospray ionization (nano-DESI). Specifically, we designed and constructed a portable nano-DESI MSI platform and coupled it with a drift tube ion mobility (IM) spectrometer-mass spectrometer. We demonstrate imaging of drift time-separated ions with a high spatial resolution of better than ∼25 μm using uterine tissues on day 4 of pregnancy in mice. Collision cross-section measurements provide unique molecular descriptors of molecules observed in nano-DESI-IM-MSI necessary for their unambiguous identification by comparison with databases. Meanwhile, isomer-specific imaging reveals variations in the isomeric composition across the tissue. Furthermore, IM separation efficiently eliminates isobaric and isomeric interferences originating from solvent peaks, overlapping isotopic peaks of endogenous molecules extracted from the tissue, and products of in-source fragmentation, which is critical to obtaining accurate concentration gradients in the sample using MSI. The structural information provided by the IM separation substantially expands the molecular specificity of high-resolution MSI necessary for unraveling the complexity of biological systems.
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Affiliation(s)
- Daisy Unsihuay
- Department of Chemistry, Purdue University, West Lafayette, IN, 47907, USA
| | - Ruichuan Yin
- Department of Chemistry, Purdue University, West Lafayette, IN, 47907, USA
| | | | - Manxi Yang
- Department of Chemistry, Purdue University, West Lafayette, IN, 47907, USA
| | - Yingju Li
- Division of Reproductive Sciences, Cincinnati Children's Hospital Medical Centre and Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45229, USA
| | - Xiaofei Sun
- Division of Reproductive Sciences, Cincinnati Children's Hospital Medical Centre and Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45229, USA
| | - Sudhansu K Dey
- Division of Reproductive Sciences, Cincinnati Children's Hospital Medical Centre and Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45229, USA
| | - Julia Laskin
- Department of Chemistry, Purdue University, West Lafayette, IN, 47907, USA.
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19
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Merdas M, Lagarrigue M, Vanbellingen Q, Umbdenstock T, Da Violante G, Pineau C. On-tissue chemical derivatization reagents for matrix-assisted laser desorption/ionization mass spectrometry imaging. JOURNAL OF MASS SPECTROMETRY : JMS 2021; 56:e4731. [PMID: 34080257 DOI: 10.1002/jms.4731] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Revised: 03/26/2021] [Accepted: 04/13/2021] [Indexed: 05/27/2023]
Abstract
Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) is a key tool for the analysis of biological tissues. It provides spatial and quantitative information about different types of analytes within tissue sections. Despite the increasing improvements of this technique, the low detection sensitivity of some compounds remains an important challenge to overcome. Poor sensitivity is related to weak ionization efficiency, low abundance of analytes and matrix ions, or endogenous interferences. On-tissue chemical derivatization (OTCD) has proven to be an important solution to these issues and is increasingly employed in MALDI MSI studies. OTCD reagents, synthesized or commercially available, have been essentially used for the detection of small exogenous or endogenous molecules within tissues. Optimally, an OTCD reaction is performed in mild conditions, in an acceptable range of time, preserves the integrity of the tissues, and prevents the delocalization. In addition to their reactivity with a targeted chemical function, some OTCD reagents can also be used as a matrix, which simplifies the sample preparation procedure. In this review, we present an exhaustive overview of OTCD reagents and methods used in MALDI MSI studies.
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Affiliation(s)
- Mira Merdas
- Univ Rennes, Inserm, EHESP, Irset (Institut de Recherche en Santé, Environnement et Travail) - UMR_S 1085, Rennes, F-35042, France
- Protim, Univ Rennes, Rennes, F-35042, France
- DMPK Department, Technologie Servier, Orléans, 45007, France
| | - Mélanie Lagarrigue
- Univ Rennes, Inserm, EHESP, Irset (Institut de Recherche en Santé, Environnement et Travail) - UMR_S 1085, Rennes, F-35042, France
- Protim, Univ Rennes, Rennes, F-35042, France
| | | | | | | | - Charles Pineau
- Univ Rennes, Inserm, EHESP, Irset (Institut de Recherche en Santé, Environnement et Travail) - UMR_S 1085, Rennes, F-35042, France
- Protim, Univ Rennes, Rennes, F-35042, France
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20
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Reveglia P, Paolillo C, Ferretti G, De Carlo A, Angiolillo A, Nasso R, Caputo M, Matrone C, Di Costanzo A, Corso G. Challenges in LC-MS-based metabolomics for Alzheimer's disease early detection: targeted approaches versus untargeted approaches. Metabolomics 2021; 17:78. [PMID: 34453619 PMCID: PMC8403122 DOI: 10.1007/s11306-021-01828-w] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 08/06/2021] [Indexed: 01/22/2023]
Abstract
BACKGROUND Alzheimer's disease (AD) is one of the most common causes of dementia in old people. Neuronal deficits such as loss of memory, language and problem-solving are severely compromised in affected patients. The molecular features of AD are Aβ deposits in plaques or in oligomeric structures and neurofibrillary tau tangles in brain. However, the challenge is that Aβ is only one piece of the puzzle, and recent findings continue to support the hypothesis that their presence is not sufficient to predict decline along the AD outcome. In this regard, metabolomic-based techniques are acquiring a growing interest for either the early diagnosis of diseases or the therapy monitoring. Mass spectrometry is one the most common analytical platforms used for detection, quantification, and characterization of metabolic biomarkers. In the past years, both targeted and untargeted strategies have been applied to identify possible interesting compounds. AIM OF REVIEW The overall goal of this review is to guide the reader through the most recent studies in which LC-MS-based metabolomics has been proposed as a powerful tool for the identification of new diagnostic biomarkers in AD. To this aim, herein studies spanning the period 2009-2020 have been reported. Advantages and disadvantages of targeted vs untargeted metabolomic approaches have been outlined and critically discussed.
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Affiliation(s)
- Pierluigi Reveglia
- Department of Clinical and Experimental Medicine, University of Foggia, 71122, Foggia, Italy
| | - Carmela Paolillo
- Department of Clinical and Experimental Medicine, University of Foggia, 71122, Foggia, Italy
| | - Gabriella Ferretti
- Department of Neuroscience, School of Medicine, University of Naples Federico II, 80131, Napoli, Italy
| | - Armando De Carlo
- Department of Clinical and Experimental Medicine, University of Foggia, 71122, Foggia, Italy
- Policlinico Riuniti University Hospital, 71122, Foggia, Italy
| | - Antonella Angiolillo
- Department of Medicine and Health Sciences, Center for Research and Training in Aging Medicine, University of Molise, 86100, Campobasso, Italy
| | - Rosarita Nasso
- Department of Neuroscience, School of Medicine, University of Naples Federico II, 80131, Napoli, Italy
| | - Mafalda Caputo
- Department of Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, 80131, Napoli, Italy
| | - Carmela Matrone
- Department of Neuroscience, School of Medicine, University of Naples Federico II, 80131, Napoli, Italy
| | - Alfonso Di Costanzo
- Department of Medicine and Health Sciences, Center for Research and Training in Aging Medicine, University of Molise, 86100, Campobasso, Italy
| | - Gaetano Corso
- Department of Clinical and Experimental Medicine, University of Foggia, 71122, Foggia, Italy.
- Policlinico Riuniti University Hospital, 71122, Foggia, Italy.
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21
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Angel PM, Rujchanarong D, Pippin S, Spruill L, Drake R. Mass Spectrometry Imaging of Fibroblasts: Promise and Challenge. Expert Rev Proteomics 2021; 18:423-436. [PMID: 34129411 PMCID: PMC8717608 DOI: 10.1080/14789450.2021.1941893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 06/09/2021] [Indexed: 10/21/2022]
Abstract
INTRODUCTION Fibroblasts maintain tissue and organ homeostasis through output of extracellular matrix that affects nearby cell signaling within the stroma. Altered fibroblast signaling contributes to many disease states and extracellular matrix secreted by fibroblasts has been used to stratify patient by outcome, recurrence, and therapeutic resistance. Recent advances in imaging mass spectrometry allow access to single cell fibroblasts and their ECM niche within clinically relevant tissue samples. AREAS COVERED We review biological and technical challenges as well as new solutions to proteomic access of fibroblast expression within the complex tissue microenvironment. Review topics cover conventional proteomic methods for single fibroblast analysis and current approaches to accessing single fibroblast proteomes by imaging mass spectrometry approaches. Strategies to target and evaluate the single cell stroma proteome on the basis of cell signaling are presented. EXPERT OPINION The promise of defining proteomic signatures from fibroblasts and their extracellular matrix niches is the discovery of new disease markers and the ability to refine therapeutic treatments. Several imaging mass spectrometry approaches exist to define the fibroblast in the setting of pathological changes from clinically acquired samples. Continued technology advances are needed to access and understand the stromal proteome and apply testing to the clinic.
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Affiliation(s)
- Peggi M. Angel
- Department of Cell and Molecular Pharmacology & Experimental Therapeutics, Bruker-MUSC Center of Excellence, Clinical Glycomics, Medical University of South Carolina, Charleston SC USA
| | - Denys Rujchanarong
- Department of Cell and Molecular Pharmacology & Experimental Therapeutics, Bruker-MUSC Center of Excellence, Clinical Glycomics, Medical University of South Carolina, Charleston SC USA
| | - Sarah Pippin
- Department of Cell and Molecular Pharmacology & Experimental Therapeutics, Bruker-MUSC Center of Excellence, Clinical Glycomics, Medical University of South Carolina, Charleston SC USA
| | - Laura Spruill
- Department of Pathology and Laboratory Medicine, Medical University of South Carolina, Charleston, SC
| | - Richard Drake
- Department of Cell and Molecular Pharmacology & Experimental Therapeutics, Bruker-MUSC Center of Excellence, Clinical Glycomics, Medical University of South Carolina, Charleston SC USA
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22
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Romsdahl TB, Kambhampati S, Koley S, Yadav UP, Alonso AP, Allen DK, Chapman KD. Analyzing Mass Spectrometry Imaging Data of 13C-Labeled Phospholipids in Camelina sativa and Thlaspi arvense (Pennycress) Embryos. Metabolites 2021; 11:metabo11030148. [PMID: 33806402 PMCID: PMC7999836 DOI: 10.3390/metabo11030148] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2021] [Revised: 02/27/2021] [Accepted: 03/02/2021] [Indexed: 12/20/2022] Open
Abstract
The combination of 13C-isotopic labeling and mass spectrometry imaging (MSI) offers an approach to analyze metabolic flux in situ. However, combining isotopic labeling and MSI presents technical challenges ranging from sample preparation, label incorporation, data collection, and analysis. Isotopic labeling and MSI individually create large, complex data sets, and this is compounded when both methods are combined. Therefore, analyzing isotopically labeled MSI data requires streamlined procedures to support biologically meaningful interpretations. Using currently available software and techniques, here we describe a workflow to analyze 13C-labeled isotopologues of the membrane lipid and storage oil lipid intermediate―phosphatidylcholine (PC). Our results with embryos of the oilseed crops, Camelina sativa and Thlaspi arvense (pennycress), demonstrated greater 13C-isotopic labeling in the cotyledons of developing embryos compared with the embryonic axis. Greater isotopic enrichment in PC molecular species with more saturated and longer chain fatty acids suggest different flux patterns related to fatty acid desaturation and elongation pathways. The ability to evaluate MSI data of isotopically labeled plant embryos will facilitate the potential to investigate spatial aspects of metabolic flux in situ.
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Affiliation(s)
- Trevor B. Romsdahl
- Department of Biological Sciences & BioDiscovery Institute, University of North Texas, Denton, TX 76203, USA; (T.B.R.); (U.P.Y.); (A.P.A.)
| | | | - Somnath Koley
- Donald Danforth Plant Science Center, St. Louis, MO 63132, USA; (S.K.); (S.K.)
| | - Umesh P. Yadav
- Department of Biological Sciences & BioDiscovery Institute, University of North Texas, Denton, TX 76203, USA; (T.B.R.); (U.P.Y.); (A.P.A.)
| | - Ana Paula Alonso
- Department of Biological Sciences & BioDiscovery Institute, University of North Texas, Denton, TX 76203, USA; (T.B.R.); (U.P.Y.); (A.P.A.)
| | - Doug K. Allen
- Donald Danforth Plant Science Center, St. Louis, MO 63132, USA; (S.K.); (S.K.)
- United States Department of Agriculture, Agriculture Research Service, St. Louis, MO 63132, USA
- Correspondence: (D.K.A.); or (K.D.C.); Tel.: +1-940-565-2969 (K.D.C.)
| | - Kent D. Chapman
- Department of Biological Sciences & BioDiscovery Institute, University of North Texas, Denton, TX 76203, USA; (T.B.R.); (U.P.Y.); (A.P.A.)
- Correspondence: (D.K.A.); or (K.D.C.); Tel.: +1-940-565-2969 (K.D.C.)
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