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Castro DC, Chan-Andersen P, Romanova EV, Sweedler JV. Probe-based mass spectrometry approaches for single-cell and single-organelle measurements. MASS SPECTROMETRY REVIEWS 2024; 43:888-912. [PMID: 37010120 PMCID: PMC10545815 DOI: 10.1002/mas.21841] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 02/09/2023] [Accepted: 03/01/2023] [Indexed: 06/19/2023]
Abstract
Exploring the chemical content of individual cells not only reveals underlying cell-to-cell chemical heterogeneity but is also a key component in understanding how cells combine to form emergent properties of cellular networks and tissues. Recent technological advances in many analytical techniques including mass spectrometry (MS) have improved instrumental limits of detection and laser/ion probe dimensions, allowing the analysis of micron and submicron sized areas. In the case of MS, these improvements combined with MS's broad analyte detection capabilities have enabled the rise of single-cell and single-organelle chemical characterization. As the chemical coverage and throughput of single-cell measurements increase, more advanced statistical and data analysis methods have aided in data visualization and interpretation. This review focuses on secondary ion MS and matrix-assisted laser desorption/ionization MS approaches for single-cell and single-organelle characterization, which is followed by advances in mass spectral data visualization and analysis.
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Affiliation(s)
- Daniel C. Castro
- Department of Molecular and Integrative Physiology, University of Illinois at Urbana-Champaign, Urbana, IL USA
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL USA
| | - Peter Chan-Andersen
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL USA
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL USA
| | - Elena V. Romanova
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL USA
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL USA
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL USA
| | - Jonathan V. Sweedler
- Department of Molecular and Integrative Physiology, University of Illinois at Urbana-Champaign, Urbana, IL USA
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL USA
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL USA
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL USA
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL USA
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2
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Rietjens RG, Wang G, van den Berg BM, Rabelink TJ. Spatial metabolomics in tissue injury and regeneration. Curr Opin Genet Dev 2024; 87:102223. [PMID: 38901101 DOI: 10.1016/j.gde.2024.102223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Revised: 06/04/2024] [Accepted: 06/04/2024] [Indexed: 06/22/2024]
Abstract
Tissue homeostasis is intricately linked to cellular metabolism and metabolite exchange within the tissue microenvironment. The orchestration of adaptive cellular responses during injury and repair depends critically upon metabolic adaptation. This adaptation, in turn, shapes cell fate decisions required for the restoration of tissue homeostasis. Understanding the nuances of metabolic processes within the tissue context and comprehending the intricate communication between cells is therefore imperative for unraveling the complexity of tissue homeostasis and the processes of injury and repair. In this review, we focus on mass spectrometry imaging as an advanced platform with the potential to provide such comprehensive insights into the metabolic instruction governing tissue function. Recent advances in this technology allow to decipher the intricate metabolic networks that determine cellular behavior in the context of tissue resilience, injury, and repair. These insights not only advance our fundamental understanding of tissue biology but also hold implications for therapeutic interventions by targeting metabolic pathways critical for maintaining tissue homeostasis.
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Affiliation(s)
- Rosalie Gj Rietjens
- Department of Internal Medicine (Nephrology) & Einthoven Laboratory of Vascular and Regenerative Medicine & The Novo Nordisk Foundation Center for Stem Cell Medicine (reNEW), Leiden University Medical Center, Leiden, The Netherlands. https://twitter.com/@RietjensRosalie
| | - Gangqi Wang
- Department of Internal Medicine (Nephrology) & Einthoven Laboratory of Vascular and Regenerative Medicine & The Novo Nordisk Foundation Center for Stem Cell Medicine (reNEW), Leiden University Medical Center, Leiden, The Netherlands. https://twitter.com/@GangqiW
| | - Bernard M van den Berg
- Department of Internal Medicine (Nephrology) & Einthoven Laboratory of Vascular and Regenerative Medicine & The Novo Nordisk Foundation Center for Stem Cell Medicine (reNEW), Leiden University Medical Center, Leiden, The Netherlands
| | - Ton J Rabelink
- Department of Internal Medicine (Nephrology) & Einthoven Laboratory of Vascular and Regenerative Medicine & The Novo Nordisk Foundation Center for Stem Cell Medicine (reNEW), Leiden University Medical Center, Leiden, The Netherlands.
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3
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Bi S, Wang M, Pu Q, Yang J, Jiang N, Zhao X, Qiu S, Liu R, Xu R, Li X, Hu C, Yang L, Gu J, Du D. Multi-MSIProcessor: Data Visualizing and Analysis Software for Spatial Metabolomics Research. Anal Chem 2024; 96:339-346. [PMID: 38102989 DOI: 10.1021/acs.analchem.3c04192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2023]
Abstract
Mass spectrometry imaging (MSI) has emerged as a revolutionary analytical strategy in biomedical research for molecular visualization. By linking the characterization of functional metabolites with tissue architecture, it is now possible to reveal unknown biological functions of tissues. However, due to the complexity and high dimensionality of MSI data, mining bioinformatics-related peaks from batch MSI data sets and achieving complete spatially resolved metabolomics analysis remain a great challenge. Here, we propose novel MSI data processing software, Multi-MSIProcessor (MMP), which integrates the data read-in, MSI visualization, processed data preservation, and biomarker discovery functions. The MMP focuses on the AFADESI-MSI data platform but also supports mzXML and imzmL data input formats for compatibility with data generated by other MSI platforms such as MALDI/SIMS-MSI. MMP enables deep mining of batch MSI data and has flexible adaptability with the source code opened that welcomes new functions and personalized analysis strategies. Using multiple clinical biosamples with complex heterogeneity, we demonstrated that MMP can rapidly establish complete MSI analysis workflows, assess batch sample data quality, screen and annotate differential MS peaks, and obtain abnormal metabolic pathways. MMP provides a novel platform for spatial metabolomics analysis of multiple samples that could meet the diverse analysis requirements of scholars.
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Affiliation(s)
- Siwei Bi
- Department of Plastic and Burn Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Manjiangcuo Wang
- Advanced Mass Spectrometry Center, Research Core Facility, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610213, China
| | - Qianlun Pu
- Advanced Mass Spectrometry Center, Research Core Facility, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610213, China
| | - Jinxi Yang
- West China Centre of Excellence for Pancreatitis, Institute of Integrated Traditional Chinese and Western Medicine, West China Hospital/West China Medical School, Sichuan University, Chengdu 610041, China
| | - Na Jiang
- Advanced Mass Spectrometry Center, Research Core Facility, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610213, China
| | - Xueshan Zhao
- Department of Cardiovascular Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Siyuan Qiu
- Division of Gastrointestinal Surgery, Department of General Surgery, West China Hospital, Sichuan University, Chengdu,Sichuan 610041, China
| | - Ruiqi Liu
- Department of Plastic and Burn Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Renjie Xu
- Department of Respiratory Health West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Xia Li
- West China School of Nursing, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Chenggong Hu
- Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Lie Yang
- Division of Gastrointestinal Surgery, Department of General Surgery, West China Hospital, Sichuan University, Chengdu,Sichuan 610041, China
| | - Jun Gu
- Department of Cardiovascular Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Dan Du
- Advanced Mass Spectrometry Center, Research Core Facility, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610213, China
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4
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Vandenbosch M, Mutuku SM, Mantas MJQ, Patterson NH, Hallmark T, Claesen M, Heeren RMA, Hatcher NG, Verbeeck N, Ekroos K, Ellis SR. Toward Omics-Scale Quantitative Mass Spectrometry Imaging of Lipids in Brain Tissue Using a Multiclass Internal Standard Mixture. Anal Chem 2023; 95:18719-18730. [PMID: 38079536 DOI: 10.1021/acs.analchem.3c02724] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2023]
Abstract
Mass spectrometry imaging (MSI) has accelerated our understanding of lipid metabolism and spatial distribution in tissues and cells. However, few MSI studies have approached lipid imaging quantitatively and those that have focused on a single lipid class. We overcome this limitation by using a multiclass internal standard (IS) mixture sprayed homogeneously over the tissue surface with concentrations that reflect those of endogenous lipids. This enabled quantitative MSI (Q-MSI) of 13 lipid classes and subclasses representing almost 200 sum-composition lipid species using both MALDI (negative ion mode) and MALDI-2 (positive ion mode) and pixel-wise normalization of each lipid species in a manner analogous to that widely used in shotgun lipidomics. The Q-MSI approach covered 3 orders of magnitude in dynamic range (lipid concentrations reported in pmol/mm2) and revealed subtle changes in distribution compared to data without normalization. The robustness of the method was evaluated by repeating experiments in two laboratories using both timsTOF and Orbitrap mass spectrometers with an ∼4-fold difference in mass resolution power. There was a strong overall correlation in the Q-MSI results obtained by using the two approaches. Outliers were mostly rationalized by isobaric interferences or the higher sensitivity of one instrument for a particular lipid species. These data provide insight into how the mass resolving power can affect Q-MSI data. This approach opens up the possibility of performing large-scale Q-MSI studies across numerous lipid classes and subclasses and revealing how absolute lipid concentrations vary throughout and between biological tissues.
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Affiliation(s)
- Michiel Vandenbosch
- Maastricht MultiModal Molecular Imaging (M4I) Institute, Division of Imaging Mass Spectrometry, Maastricht University, Maastricht 6229ER, Netherlands
| | - Shadrack M Mutuku
- Molecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Wollongong, NSW 2522, Australia
| | | | | | | | | | - Ron M A Heeren
- Maastricht MultiModal Molecular Imaging (M4I) Institute, Division of Imaging Mass Spectrometry, Maastricht University, Maastricht 6229ER, Netherlands
| | - Nathan G Hatcher
- Merck & Co., Inc., 770 Sumneytown Pk, West Point, Pennsylvania 19486, United States
| | | | - Kim Ekroos
- Lipidomics Consulting Ltd., Esbo 02230, Finland
| | - Shane R Ellis
- Molecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Wollongong, NSW 2522, Australia
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5
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Krestensen KK, Heeren RMA, Balluff B. State-of-the-art mass spectrometry imaging applications in biomedical research. Analyst 2023; 148:6161-6187. [PMID: 37947390 DOI: 10.1039/d3an01495a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2023]
Abstract
Mass spectrometry imaging has advanced from a niche technique to a widely applied spatial biology tool operating at the forefront of numerous fields, most notably making a significant impact in biomedical pharmacological research. The growth of the field has gone hand in hand with an increase in publications and usage of the technique by new laboratories, and consequently this has led to a shift from general MSI reviews to topic-specific reviews. Given this development, we see the need to recapitulate the strengths of MSI by providing a more holistic overview of state-of-the-art MSI studies to provide the new generation of researchers with an up-to-date reference framework. Here we review scientific advances for the six largest biomedical fields of MSI application (oncology, pharmacology, neurology, cardiovascular diseases, endocrinology, and rheumatology). These publications thereby give examples for at least one of the following categories: they provide novel mechanistic insights, use an exceptionally large cohort size, establish a workflow that has the potential to become a high-impact methodology, or are highly cited in their field. We finally have a look into new emerging fields and trends in MSI (immunology, microbiology, infectious diseases, and aging), as applied MSI is continuously broadening as a result of technological breakthroughs.
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Affiliation(s)
- Kasper K Krestensen
- The Maastricht MultiModal Molecular Imaging (M4I) Institute, Maastricht University, 6229 ER Maastricht, The Netherlands.
| | - Ron M A Heeren
- The Maastricht MultiModal Molecular Imaging (M4I) Institute, Maastricht University, 6229 ER Maastricht, The Netherlands.
| | - Benjamin Balluff
- The Maastricht MultiModal Molecular Imaging (M4I) Institute, Maastricht University, 6229 ER Maastricht, The Netherlands.
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6
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Planque M, Igelmann S, Ferreira Campos AM, Fendt SM. Spatial metabolomics principles and application to cancer research. Curr Opin Chem Biol 2023; 76:102362. [PMID: 37413787 DOI: 10.1016/j.cbpa.2023.102362] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 05/07/2023] [Accepted: 06/06/2023] [Indexed: 07/08/2023]
Abstract
Mass spectrometry imaging (MSI) is an emerging technology in cancer metabolomics. Desorption electrospray ionization (DESI) and matrix-assisted laser desorption ionization (MALDI) MSI are complementary techniques to identify hundreds of metabolites in space with close to single-cell resolution. This technology leap enables research focusing on tumor heterogeneity, cancer cell plasticity, and the communication signals between cancer and stromal cells in the tumor microenvironment (TME). Currently, unprecedented knowledge is generated using spatial metabolomics in fundamental cancer research. Yet, also translational applications are emerging, including the assessment of spatial drug distribution in organs and tumors. Moreover, clinical research investigates the use of spatial metabolomics as a rapid pathology tool during cancer surgeries. Here, we summarize MSI applications, the knowledge gained by this technology in space, future directions, and developments needed.
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Affiliation(s)
- Mélanie Planque
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, VIB, Leuven, Belgium; Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium
| | - Sebastian Igelmann
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, VIB, Leuven, Belgium; Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium
| | - Ana Margarida Ferreira Campos
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, VIB, Leuven, Belgium; Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium
| | - Sarah-Maria Fendt
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, VIB, Leuven, Belgium; Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium.
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7
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Giraud EL, de Jong LAW, van den Hombergh E, Kaal SEJ, van Erp NP, Desar IME. Measuring Tumour Imatinib Concentrations in Gastrointestinal Stromal Tumours: Relevant or Redundant? Cancers (Basel) 2023; 15:cancers15112875. [PMID: 37296838 DOI: 10.3390/cancers15112875] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 05/17/2023] [Accepted: 05/20/2023] [Indexed: 06/12/2023] Open
Abstract
Imatinib plasma trough concentrations are associated with efficacy for patients treated for advanced or metastatic KIT-positive gastrointestinal stromal tumours (GISTs). This relationship has not been studied for patients treated in the neoadjuvant setting, let alone its correlation with tumour drug concentrations. In this exploratory study we aimed to determine the correlation between plasma and tumour imatinib concentrations in the neoadjuvant setting, investigate tumour imatinib distribution patterns within GISTs, and analyse its correlation with pathological response. Imatinib concentrations were measured in both plasma and in three regions of the resected primary tumour: the core, middle part, and periphery. Twenty-four tumour samples derived from the primary tumours of eight patients were included in the analyses. Imatinib tumour concentrations were higher compared to plasma concentrations. No correlation was observed between plasma and tumour concentrations. Interpatient variability in tumour concentrations was high compared to interindividual variability in plasma concentrations. Although imatinib accumulates in tumour tissue, no distribution pattern of imatinib in tumour tissue could be identified. There was no correlation between imatinib concentrations in tumour tissue and pathological treatment response.
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Affiliation(s)
- Eline L Giraud
- Radboud University Medical Centre, Department of Pharmacy, 6500 HB Nijmegen, The Netherlands
| | - Loek A W de Jong
- Radboud University Medical Centre, Department of Pharmacy, 6500 HB Nijmegen, The Netherlands
| | - Erik van den Hombergh
- Radboud University Medical Centre, Department of Pharmacy, 6500 HB Nijmegen, The Netherlands
| | - Suzanne E J Kaal
- Radboud University Medical Centre, Department of Medical Oncology, 6500 HB Nijmegen, The Netherlands
| | - Nielka P van Erp
- Radboud University Medical Centre, Department of Pharmacy, 6500 HB Nijmegen, The Netherlands
| | - Ingrid M E Desar
- Radboud University Medical Centre, Department of Medical Oncology, 6500 HB Nijmegen, The Netherlands
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8
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Rittel MF, Schmidt S, Weis CA, Birgin E, van Marwick B, Rädle M, Diehl SJ, Rahbari NN, Marx A, Hopf C. Spatial Omics Imaging of Fresh-Frozen Tissue and Routine FFPE Histopathology of a Single Cancer Needle Core Biopsy: A Freezing Device and Multimodal Workflow. Cancers (Basel) 2023; 15:2676. [PMID: 37345020 DOI: 10.3390/cancers15102676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Revised: 04/16/2023] [Accepted: 05/06/2023] [Indexed: 06/23/2023] Open
Abstract
The complex molecular alterations that underlie cancer pathophysiology are studied in depth with omics methods using bulk tissue extracts. For spatially resolved tissue diagnostics using needle biopsy cores, however, histopathological analysis using stained FFPE tissue and the immunohistochemistry (IHC) of a few marker proteins is currently the main clinical focus. Today, spatial omics imaging using MSI or IRI is an emerging diagnostic technology for the identification and classification of various cancer types. However, to conserve tissue-specific metabolomic states, fast, reliable, and precise methods for the preparation of fresh-frozen (FF) tissue sections are crucial. Such methods are often incompatible with clinical practice, since spatial metabolomics and the routine histopathology of needle biopsies currently require two biopsies for FF and FFPE sampling, respectively. Therefore, we developed a device and corresponding laboratory and computational workflows for the multimodal spatial omics analysis of fresh-frozen, longitudinally sectioned needle biopsies to accompany standard FFPE histopathology of the same biopsy core. As a proof-of-concept, we analyzed surgical human liver cancer specimens using IRI and MSI with precise co-registration and, following FFPE processing, by sequential clinical pathology analysis of the same biopsy core. This workflow allowed for a spatial comparison between different spectral profiles and alterations in tissue histology, as well as a direct comparison for histological diagnosis without the need for an extra biopsy.
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Affiliation(s)
- Miriam F Rittel
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163 Mannheim, Germany
- Institute of Medical Technology, Heidelberg University and Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163 Mannheim, Germany
- Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
| | - Stefan Schmidt
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163 Mannheim, Germany
| | - Cleo-Aron Weis
- Institute of Pathology, University Medical Centre Mannheim, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
| | - Emrullah Birgin
- Department of Surgery, University Medical Centre Mannheim, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
| | - Björn van Marwick
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163 Mannheim, Germany
| | - Matthias Rädle
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163 Mannheim, Germany
- Institute of Medical Technology, Heidelberg University and Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163 Mannheim, Germany
- Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
| | - Steffen J Diehl
- Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
- Clinic of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
| | - Nuh N Rahbari
- Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
- Department of Surgery, University Medical Centre Mannheim, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
| | - Alexander Marx
- Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
- Institute of Pathology, University Medical Centre Mannheim, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
| | - Carsten Hopf
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163 Mannheim, Germany
- Institute of Medical Technology, Heidelberg University and Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163 Mannheim, Germany
- Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
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9
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Abu Sammour D, Cairns JL, Boskamp T, Marsching C, Kessler T, Ramallo Guevara C, Panitz V, Sadik A, Cordes J, Schmidt S, Mohammed SA, Rittel MF, Friedrich M, Platten M, Wolf I, von Deimling A, Opitz CA, Wick W, Hopf C. Spatial probabilistic mapping of metabolite ensembles in mass spectrometry imaging. Nat Commun 2023; 14:1823. [PMID: 37005414 PMCID: PMC10067847 DOI: 10.1038/s41467-023-37394-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Accepted: 03/13/2023] [Indexed: 04/04/2023] Open
Abstract
Mass spectrometry imaging vows to enable simultaneous spatially resolved investigation of hundreds of metabolites in tissues, but it primarily relies on traditional ion images for non-data-driven metabolite visualization and analysis. The rendering and interpretation of ion images neither considers nonlinearities in the resolving power of mass spectrometers nor does it yet evaluate the statistical significance of differential spatial metabolite abundance. Here, we outline the computational framework moleculaR ( https://github.com/CeMOS-Mannheim/moleculaR ) that is expected to improve signal reliability by data-dependent Gaussian-weighting of ion intensities and that introduces probabilistic molecular mapping of statistically significant nonrandom patterns of relative spatial abundance of metabolites-of-interest in tissue. moleculaR also enables cross-tissue statistical comparisons and collective molecular projections of entire biomolecular ensembles followed by their spatial statistical significance evaluation on a single tissue plane. It thereby fosters the spatially resolved investigation of ion milieus, lipid remodeling pathways, or complex scores like the adenylate energy charge within the same image.
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Affiliation(s)
- Denis Abu Sammour
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Mannheim, Germany
- Mannheim Center for Translational Neuroscience (MCTN), Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - James L Cairns
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Mannheim, Germany
- Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany
| | - Tobias Boskamp
- Bruker Daltonics GmbH & Co. KG, Bremen, Germany
- Center for Industrial Mathematics, University of Bremen, Bremen, Germany
| | - Christian Marsching
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Mannheim, Germany
- Bruker Daltonics GmbH & Co. KG, Bremen, Germany
| | - Tobias Kessler
- Clinical Cooperation Unit Neurooncology, German Cancer Consortium, German Cancer Research Center, Heidelberg, Germany
- DKTK Metabolic Crosstalk in Cancer, German Consortium of Translational Cancer Research (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Carina Ramallo Guevara
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Mannheim, Germany
| | - Verena Panitz
- DKTK Metabolic Crosstalk in Cancer, German Consortium of Translational Cancer Research (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Neurology and National Center for Tumor Diseases, Heidelberg University Hospital, Heidelberg, Germany
| | - Ahmed Sadik
- DKTK Metabolic Crosstalk in Cancer, German Consortium of Translational Cancer Research (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Bioscience, Heidelberg University, Heidelberg, Germany
| | - Jonas Cordes
- Faculty of Computer Science, Mannheim University of Applied Sciences, Mannheim, Germany
| | - Stefan Schmidt
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Mannheim, Germany
| | - Shad A Mohammed
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Mannheim, Germany
- Mannheim Center for Translational Neuroscience (MCTN), Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Miriam F Rittel
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Mannheim, Germany
- Mannheim Center for Translational Neuroscience (MCTN), Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Mirco Friedrich
- Mannheim Center for Translational Neuroscience (MCTN), Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Department of Neurology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- DKTK Clinical Cooperation Unit Neuroimmunology and Brain Tumor Immunology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Michael Platten
- Mannheim Center for Translational Neuroscience (MCTN), Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Department of Neurology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- DKTK Clinical Cooperation Unit Neuroimmunology and Brain Tumor Immunology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Ivo Wolf
- Faculty of Computer Science, Mannheim University of Applied Sciences, Mannheim, Germany
| | - Andreas von Deimling
- Department of Neuropathology, University Hospital Heidelberg, Heidelberg, Germany
- DKTK Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Christiane A Opitz
- DKTK Metabolic Crosstalk in Cancer, German Consortium of Translational Cancer Research (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Neurology and National Center for Tumor Diseases, Heidelberg University Hospital, Heidelberg, Germany
| | - Wolfgang Wick
- Clinical Cooperation Unit Neurooncology, German Cancer Consortium, German Cancer Research Center, Heidelberg, Germany
- DKTK Metabolic Crosstalk in Cancer, German Consortium of Translational Cancer Research (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Carsten Hopf
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Mannheim, Germany.
- Mannheim Center for Translational Neuroscience (MCTN), Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
- Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany.
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10
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Deschamps E, Calabrese V, Schmitz I, Hubert-Roux M, Castagnos D, Afonso C. Advances in Ultra-High-Resolution Mass Spectrometry for Pharmaceutical Analysis. Molecules 2023; 28:molecules28052061. [PMID: 36903305 PMCID: PMC10003995 DOI: 10.3390/molecules28052061] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 02/16/2023] [Accepted: 02/19/2023] [Indexed: 02/25/2023] Open
Abstract
Pharmaceutical analysis refers to an area of analytical chemistry that deals with active compounds either by themselves (drug substance) or when formulated with excipients (drug product). In a less simplistic way, it can be defined as a complex science involving various disciplines, e.g., drug development, pharmacokinetics, drug metabolism, tissue distribution studies, and environmental contamination analyses. As such, the pharmaceutical analysis covers drug development to its impact on health and the environment. Moreover, due to the need for safe and effective medications, the pharmaceutical industry is one of the most heavily regulated sectors of the global economy. For this reason, powerful analytical instrumentation and efficient methods are required. In the last decades, mass spectrometry has been increasingly used in pharmaceutical analysis both for research aims and routine quality controls. Among different instrumental setups, ultra-high-resolution mass spectrometry with Fourier transform instruments, i.e., Fourier transform ion cyclotron resonance (FTICR) and Orbitrap, gives access to valuable molecular information for pharmaceutical analysis. In fact, thanks to their high resolving power, mass accuracy, and dynamic range, reliable molecular formula assignments or trace analysis in complex mixtures can be obtained. This review summarizes the principles of the two main types of Fourier transform mass spectrometers, and it highlights applications, developments, and future perspectives in pharmaceutical analysis.
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Affiliation(s)
- Estelle Deschamps
- Normandie Univ, COBRA, UMR 6014 and FR 3038, Université de Rouen, INSA de Rouen, CNRS, IRCOF, 1 rue Tesnières, CEDEX, 76821 Mont-Saint-Aignan, France
- ORIL Industrie, Servier Group, 13 r Auguste Desgenétais, 76210 Bolbec, France
| | - Valentina Calabrese
- Normandie Univ, COBRA, UMR 6014 and FR 3038, Université de Rouen, INSA de Rouen, CNRS, IRCOF, 1 rue Tesnières, CEDEX, 76821 Mont-Saint-Aignan, France
- Université de Lyon, Université Claude Bernard Lyon 1, Institut des Sciences Analytiques, CNRS UMR 5280, 5 Rue de La Doua, F-69100 Villeurbanne, France
| | - Isabelle Schmitz
- Normandie Univ, COBRA, UMR 6014 and FR 3038, Université de Rouen, INSA de Rouen, CNRS, IRCOF, 1 rue Tesnières, CEDEX, 76821 Mont-Saint-Aignan, France
| | - Marie Hubert-Roux
- Normandie Univ, COBRA, UMR 6014 and FR 3038, Université de Rouen, INSA de Rouen, CNRS, IRCOF, 1 rue Tesnières, CEDEX, 76821 Mont-Saint-Aignan, France
| | - Denis Castagnos
- ORIL Industrie, Servier Group, 13 r Auguste Desgenétais, 76210 Bolbec, France
| | - Carlos Afonso
- Normandie Univ, COBRA, UMR 6014 and FR 3038, Université de Rouen, INSA de Rouen, CNRS, IRCOF, 1 rue Tesnières, CEDEX, 76821 Mont-Saint-Aignan, France
- Correspondence:
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11
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Mass spectrometry imaging in gynecological cancers: the best is yet to come. Cancer Cell Int 2022; 22:414. [PMID: 36536419 PMCID: PMC9764543 DOI: 10.1186/s12935-022-02832-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 12/11/2022] [Indexed: 12/23/2022] Open
Abstract
Mass spectrometry imaging (MSI) enables obtaining multidimensional results simultaneously in a single run, including regiospecificity and m/z values corresponding with specific proteins, peptides, lipids, etc. The knowledge obtained in this way allows for a multifaceted analysis of the studied issue, e.g., the specificity of the neoplastic process and the search for new therapeutic targets. Despite the enormous possibilities, this relatively new technique in many aspects still requires the development or standardization of analytical protocols (from collecting biological material, through sample preparation, analysis, and data collection, to data processing). The introduction of standardized protocols for MSI studies, with its current potential to extend diagnostic and prognostic capabilities, can revolutionize clinical pathology. As far as identifying ovarian cancer subtypes can be challenging, especially in poorly differentiated tumors, developing MSI-based algorithms may enhance determining prognosis and tumor staging without the need for extensive surgery and optimize the choice of subsequent therapy. MSI might bring new solutions in predicting response to treatment in patients with endometrial cancer. Therefore, MSI may help to revolutionize the future of gynecological oncology in terms of diagnostics, treatment, and predicting the response to therapy. This review will encompass several aspects, e.g., contemporary discoveries in gynecological cancer research utilizing MSI, indicates current challenges, and future perspectives on MSI.
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12
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Nascentes Melo LM, Lesner NP, Sabatier M, Ubellacker JM, Tasdogan A. Emerging metabolomic tools to study cancer metastasis. Trends Cancer 2022; 8:988-1001. [PMID: 35909026 DOI: 10.1016/j.trecan.2022.07.003] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 06/24/2022] [Accepted: 07/06/2022] [Indexed: 12/24/2022]
Abstract
Metastasis is responsible for 90% of deaths in patients with cancer. Understanding the role of metabolism during metastasis has been limited by the development of robust and sensitive technologies that capture metabolic processes in metastasizing cancer cells. We discuss the current technologies available to study (i) metabolism in primary and metastatic cancer cells and (ii) metabolic interactions between cancer cells and the tumor microenvironment (TME) at different stages of the metastatic cascade. We identify advantages and disadvantages of each method and discuss how these tools and technologies will further improve our understanding of metastasis. Studies investigating the complex metabolic rewiring of different cells using state-of-the-art metabolomic technologies have the potential to reveal novel biological processes and therapeutic interventions for human cancers.
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Affiliation(s)
| | - Nicholas P Lesner
- Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Marie Sabatier
- Department of Molecular Metabolism, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jessalyn M Ubellacker
- Department of Molecular Metabolism, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Alpaslan Tasdogan
- Department of Dermatology, University Hospital Essen and German Cancer Consortium, Partner Site, Essen, Germany.
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13
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Wu Q. A review on quantitation-related factors and quantitation strategies in mass spectrometry imaging of small biomolecules. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2022; 14:3932-3943. [PMID: 36164961 DOI: 10.1039/d2ay01257j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Accurate quantitative information of the analytes in mass spectrometry imaging (MSI) is fundamental for determining the accurate spatial distribution, which can provide additional insight into the living processes, disease progression or the pharmacokinetic-pharmacodynamic mechanisms. However, performing a quantitative analysis in MSI is still challenging. This review focuses on the quantitation-related factors and recent advances in the strategies of quantitative MSI (q-MSI) of small molecules. The main quantitation-related factors are discussed according to the new investigations in recent years, including the regionally varied extraction efficiencies and ionization efficiencies, signal-concentration regression functions, and the repeatability of surface sampling/ionization methods. Newly developed quantitation strategies in MSI based on aforementioned factors are introduced, including new techniques in standard curve calibration with normalization to an internal standard, kinetic calibration, and chemometric methods. Different strategies for validating q-MSI methods are discussed. Finally, the future perspectives to q-MSI are proposed.
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Affiliation(s)
- Qian Wu
- College of Chemistry and Chemical Engineering, Central South University, Changsha, Hunan, 410083, P. R. China.
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14
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DeLaney K, Phetsanthad A, Li L. ADVANCES IN HIGH-RESOLUTION MALDI MASS SPECTROMETRY FOR NEUROBIOLOGY. MASS SPECTROMETRY REVIEWS 2022; 41:194-214. [PMID: 33165982 PMCID: PMC8106695 DOI: 10.1002/mas.21661] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Accepted: 09/13/2020] [Indexed: 05/08/2023]
Abstract
Research in the field of neurobiology and neurochemistry has seen a rapid expansion in the last several years due to advances in technologies and instrumentation, facilitating the detection of biomolecules critical to the complex signaling of neurons. Part of this growth has been due to the development and implementation of high-resolution Fourier transform (FT) mass spectrometry (MS), as is offered by FT ion cyclotron resonance (FTICR) and Orbitrap mass analyzers, which improves the accuracy of measurements and helps resolve the complex biological mixtures often analyzed in the nervous system. The coupling of matrix-assisted laser desorption/ionization (MALDI) with high-resolution MS has drastically expanded the information that can be obtained with these complex samples. This review discusses notable technical developments in MALDI-FTICR and MALDI-Orbitrap platforms and their applications toward molecules in the nervous system, including sequence elucidation and profiling with de novo sequencing, analysis of post-translational modifications, in situ analysis, key advances in sample preparation and handling, quantitation, and imaging. Notable novel applications are also discussed to highlight key developments critical to advancing our understanding of neurobiology and providing insight into the exciting future of this field. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.
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Affiliation(s)
- Kellen DeLaney
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, WI 53706, USA
| | - Ashley Phetsanthad
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, WI 53706, USA
| | - Lingjun Li
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, WI 53706, USA
- School of Pharmacy, University of Wisconsin-Madison, 777 Highland Avenue, Madison, WI 53705, USA
- To whom correspondence should be addressed. , Phone: (608) 265-8491, Fax: (608) 262-5345., Mailing Address: 5125 Rennebohm Hall, 777 Highland Avenue, Madison, WI 53706
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15
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Hahm TH, Matsui T, Tanaka M. Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging of Tissues via the Formation of Reproducible Matrix Crystals by the Fluorescence-Assisted Spraying Method: A Quantification Approach. Anal Chem 2022; 94:1990-1998. [PMID: 35040638 DOI: 10.1021/acs.analchem.1c03369] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
The application of matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) imaging to quantitative analyses is restricted by the variability of MS intensity of the analytes in nonreproducible matrix crystals of tissues. To overcome this challenge, a fluorescence-assisted spraying method was developed for a constant matrix amount employing an MS-detectable fluorescent reagent, rhodamine 6G (R6G), which was sprayed with the matrix. To form a homogeneous matrix crystal on the tissue section, a matrix solution, 1,5-diaminonaphthalene (10 mg/mL), containing R6G (40 μg/mL) and O-dinitrobenzene (O-DNB, 10 mg/mL) was sprayed until the desired constant fluorescence intensity was achieved. Compared with that obtained via conventional cycle-number-fixed spraying [relative standard deviation (RSD) = 31.1%], the reproducibility of the relative MS intensity of the analyte [ferulic acid (FA), RSD = 3.1%] to R6G was significantly improved by the fluorescence-assisted matrix spraying. This result indicated that R6G could be employed as an index of the matrix amount and an MS normalizing standard. The proposed matrix spraying successfully quantified nifedipine (0.5-40 pmol/mm2 in the positive mode, R2 = 0.965) and FA (0.5-75 pmol/mm2 in the negative mode, R2 = 0.9972) in the kidney section of a rat. Employing the quantitative MALDI-MS imaging assay, FA, which accumulated in the kidney of the rat after 50 mg/kg was orally administered, was visually determined to be 3.5, 3.0, and 0.2 μmol/g tissue at 15, 30, and 60 min, respectively.
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Affiliation(s)
- Tae Hun Hahm
- Faculty of Agriculture, Graduate School of Kyushu University, Fukuoka 819-0395, Japan
| | - Toshiro Matsui
- Faculty of Agriculture, Graduate School of Kyushu University, Fukuoka 819-0395, Japan.,Research and Development Center for Five-Sense Devices, Kyushu University, Fukuoka 819-0395, Japan
| | - Mitsuru Tanaka
- Faculty of Agriculture, Graduate School of Kyushu University, Fukuoka 819-0395, Japan.,Research and Development Center for Five-Sense Devices, Kyushu University, Fukuoka 819-0395, Japan
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16
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Abstract
Mass spectrometry imaging (MSI) could provide chemical spatial distribution within a diverse range of samples, but absolute quantitation with those techniques is still challenging. Recent years, ambient liquid extraction-based MSI techniques, such as liquid microjunction surface sampling (LMJSS), have been largely developed and were found to be favorable to quantitation by directly doping standards in the extraction solvent. Here, we describe the detailed experimental protocols and the data processing methods for quantitative MSI with LMJSS. The new methods could have absolute quantitative MSI of both endogenous lipids and small metabolites from tissue samples.
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Affiliation(s)
- Qian Wu
- College of Chemistry and Chemical Engineering, Central South University, Changsha, Hunan, P. R. China
| | - Hongmei Lu
- College of Chemistry and Chemical Engineering, Central South University, Changsha, Hunan, P. R. China.
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17
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Capturing the third dimension in drug discovery: Spatially-resolved tools for interrogation of complex 3D cell models. Biotechnol Adv 2021; 55:107883. [PMID: 34875362 DOI: 10.1016/j.biotechadv.2021.107883] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 11/22/2021] [Accepted: 11/30/2021] [Indexed: 02/07/2023]
Abstract
Advanced three-dimensional (3D) cell models have proven to be capable of depicting architectural and microenvironmental features of several tissues. By providing data of higher physiological and pathophysiological relevance, 3D cell models have been contributing to a better understanding of human development, pathology onset and progression mechanisms, as well as for 3D cell-based assays for drug discovery. Nonetheless, the characterization and interrogation of these tissue-like structures pose major challenges on the conventional analytical methods, pushing the development of spatially-resolved technologies. Herein, we review recent advances and pioneering technologies suitable for the interrogation of multicellular 3D models, while capable of retaining biological spatial information. We focused on imaging technologies and omics tools, namely transcriptomics, proteomics and metabolomics. The advantages and shortcomings of these novel methodologies are discussed, alongside the opportunities to intertwine data from the different tools.
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18
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Luo S, Wu Q, Li Y, Lu H. Per-pixel absolute quantitation for mass spectrometry imaging of endogenous lipidomes by model prediction of mass transfer kinetics in single-probe-based ambient liquid extraction. Talanta 2021; 234:122654. [PMID: 34364463 DOI: 10.1016/j.talanta.2021.122654] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 06/21/2021] [Accepted: 06/22/2021] [Indexed: 10/21/2022]
Abstract
With the development of mass spectrometry imaging (MSI), techniques providing quantitative information on the spatial distribution have attracted more attentions recent years. However, for MSI of endogenous compounds in bio-samples, the uncertainty of locally varied sampling efficiencies always hinders accurate absolute quantitation. Here single-probe was used for ambient liquid extraction MSI in rat cerebellum, and standards of phosphatidylcholines (PCs) and cerebrosides (CBs) were doped in extraction solvent. The extraction kinetic curves of endogenous lipids in the ambient liquid extraction during probe parking in single pixel of tissue were investigated. From the results, the extraction kinetic curves were varied between different lipid species in different brain regions, resulting in variations of extraction efficiencies between imaging pixels, and calibration with standards deposited in tissue could not compensate for the variations. In our approach, the theoretical kinetic model of ambient liquid extraction was established, and original concentrations of endogenous lipids in each pixel of tissue were predicted by fitting the experimental extraction kinetic curve in each imaging pixel to the model. The experimental data was demonstrated to be well fitted to the kinetic model with R2 > 0.86, and only with 18-s extraction in each pixel, the original lipid concentrations were predicted accurately with relative errors <23%. With the new method, totally 157 lipids and small metabolites were imaged, and per-pixel quantitation was achieved for 19 PCs and 4 CBs. Compared with conventional quantitative MSI (q-MSI) method, the new q-MSI method had better reproducibility and wider linear range, and produced better contrast in the quantitative images of lipids in brain tissue with less hot spots and noises. The absolute quantitation results by the new method were verified by quantitative LC-MS method with Pearson'r > 0.9 and the slope of the linear fitting line of the correlation plot near 1.
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Affiliation(s)
- Shifen Luo
- College of Chemistry and Chemical Engineering, Central South University, Changsha, Hunan, 410083, PR China
| | - Qian Wu
- College of Chemistry and Chemical Engineering, Central South University, Changsha, Hunan, 410083, PR China.
| | - Youmei Li
- College of Chemistry and Chemical Engineering, Central South University, Changsha, Hunan, 410083, PR China
| | - Hongmei Lu
- College of Chemistry and Chemical Engineering, Central South University, Changsha, Hunan, 410083, PR China
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19
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Castellino S, Lareau NM, Groseclose MR. The emergence of imaging mass spectrometry in drug discovery and development: Making a difference by driving decision making. JOURNAL OF MASS SPECTROMETRY : JMS 2021; 56:e4717. [PMID: 33724654 PMCID: PMC8365693 DOI: 10.1002/jms.4717] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 02/25/2021] [Accepted: 03/02/2021] [Indexed: 05/10/2023]
Abstract
The pharmaceutical industry is a dynamic, science-driven business constantly under pressure to innovate and morph into a higher performing organization. Innovations can include the implementation of new technologies, adopting new scientific methods, changing the decision-making process, compressing timelines, or making changes to the organizational structure. The drivers for the constant focus on performance improvement are the high cost of R&D as well as the lengthy timelines required to deliver new medicines for unmet needs. Successful innovations are measured against both the quality and quantity of potential new medicines in the pipeline and the delivery to patients. In this special feature article, we share our collective experience implementing matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) technology as an innovative approach to better understand the tissue biodistribution of drugs in the early phases of drug discovery to establish pharmacokinetic-pharmacodynamic (PK-PD) relationships, as well as in the development phase to understand pharmacology, toxicology, and disease pathogenesis. In our experience, successful implementation of MALDI IMS in support of therapeutic programs can be measured by the impact IMS studies have on driving decision making in pipeline progression. This provides a direct quantifiable measurement of the return to the organization for the investment in IMS. We have included discussion not only on the technical merits of IMS study conduct but also the key elements of setting study objectives, building collaborations, data integration into the medicine progression milestones, and potential pitfalls when trying to establish IMS in the pharmaceutical arena. We categorized IMS study types into five groups that parallel pipeline progression from the earliest phases of discovery to late stages of preclinical development. We conclude the article with some perspectives on how we see MALDI IMS maintaining relevance and becoming further embedded as an essential tool in the constantly changing environment of the pharmaceutical industry.
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Affiliation(s)
- Stephen Castellino
- GlaxoSmithKline BioimagingCollegevillePennsylvania19426USA
- Xenovista LLCChapel HillNorth Carolina27516USA
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20
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Davoli E, Zucchetti M, Matteo C, Ubezio P, D'Incalci M, Morosi L. THE SPACE DIMENSION AT THE MICRO LEVEL: MASS SPECTROMETRY IMAGING OF DRUGS IN TISSUES. MASS SPECTROMETRY REVIEWS 2021; 40:201-214. [PMID: 32501572 DOI: 10.1002/mas.21633] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Revised: 04/24/2020] [Accepted: 04/29/2020] [Indexed: 06/11/2023]
Abstract
Mass spectrometry imaging (MSI) has seen remarkable development in recent years. The possibility of getting quantitative or semiquantitative data, while maintaining the spatial component in the tissues has opened up unique study possibilities. Now with a spatial window of few tens of microns, we can characterize the events occurring in tissue subcompartments in physiological and pathological conditions. For example, in oncology-especially in preclinical models-we can quantitatively measure drug distribution within tumors, correlating it with pharmacological treatments intended to modify it. We can also study the local effects of the drug in the tissue, and their effects in relation to histology. This review focuses on the main results in the field of drug MSI in clinical pharmacology, looking at the literature on the distribution of drugs in human tissues, and also the first preclinical evidence of drug intratissue effects. The main instrumental techniques are discussed, looking at the different instrumentation, sample preparation protocols, and raw data management employed to obtain the sensitivity required for these studies. Finally, we review the applications that describe in situ metabolic events and pathways induced by the drug, in animal models, showing that MSI makes it possible to study effects that go beyond the simple concentration of the drug, maintaining the space dimension. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.
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Affiliation(s)
- Enrico Davoli
- Laboratory of Mass Spectrometry, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Massimo Zucchetti
- Laboratory of Antitumoral Pharmacology, Department of Oncology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Cristina Matteo
- Laboratory of Antitumoral Pharmacology, Department of Oncology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Paolo Ubezio
- Laboratory of Antitumoral Pharmacology, Department of Oncology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Maurizio D'Incalci
- Laboratory of Antitumoral Pharmacology, Department of Oncology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Lavinia Morosi
- Laboratory of Antitumoral Pharmacology, Department of Oncology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
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21
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Taylor M, Lukowski JK, Anderton CR. Spatially Resolved Mass Spectrometry at the Single Cell: Recent Innovations in Proteomics and Metabolomics. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2021; 32:872-894. [PMID: 33656885 PMCID: PMC8033567 DOI: 10.1021/jasms.0c00439] [Citation(s) in RCA: 131] [Impact Index Per Article: 43.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 01/20/2021] [Accepted: 01/25/2021] [Indexed: 05/02/2023]
Abstract
Biological systems are composed of heterogeneous populations of cells that intercommunicate to form a functional living tissue. Biological function varies greatly across populations of cells, as each single cell has a unique transcriptome, proteome, and metabolome that translates to functional differences within single species and across kingdoms. Over the past decade, substantial advancements in our ability to characterize omic profiles on a single cell level have occurred, including in multiple spectroscopic and mass spectrometry (MS)-based techniques. Of these technologies, spatially resolved mass spectrometry approaches, including mass spectrometry imaging (MSI), have shown the most progress for single cell proteomics and metabolomics. For example, reporter-based methods using heavy metal tags have allowed for targeted MS investigation of the proteome at the subcellular level, and development of technologies such as laser ablation electrospray ionization mass spectrometry (LAESI-MS) now mean that dynamic metabolomics can be performed in situ. In this Perspective, we showcase advancements in single cell spatial metabolomics and proteomics over the past decade and highlight important aspects related to high-throughput screening, data analysis, and more which are vital to the success of achieving proteomic and metabolomic profiling at the single cell scale. Finally, using this broad literature summary, we provide a perspective on how the next decade may unfold in the area of single cell MS-based proteomics and metabolomics.
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Affiliation(s)
- Michael
J. Taylor
- Environmental Molecular Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Jessica K. Lukowski
- Environmental Molecular Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Christopher R. Anderton
- Environmental Molecular Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
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22
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RamalloGuevara C, Paulssen D, Popova AA, Hopf C, Levkin PA. Fast Nanoliter-Scale Cell Assays Using Droplet Microarray-Mass Spectrometry Imaging. Adv Biol (Weinh) 2021; 5:e2000279. [PMID: 33729695 DOI: 10.1002/adbi.202000279] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 12/23/2020] [Indexed: 12/21/2022]
Abstract
In pharmaceutical research and development, cell-based assays are primarily used with readout that rely on fluorescence-based and other label-dependent techniques for analysis of different cellular processes. Superhydrophobic-hydrophilic droplet microarrays (DMA) and matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) have recently emerged as key technologies for miniaturized high-throughput cell assays and for label-free molecular high-content drug profiling, respectively. Here, nanoliter-scale cell assays are integrated on DMAs with MALDI-MS imaging (MALDI-MSI) approaches to a droplet microarray-mass spectrometry imaging (DMA-MSI) platform. Using A549 lung cancer cells, concentration-response profiling of a pharmaceutical compound, the fatty acid synthase inhibitor GSK2194069, are demonstrated. Direct cell culture on DMAs enables combination of microscopy and high speed, high molecular content analysis using MALDI-MSI. Miniaturization of array spots down to 0.5 mm confining 40 nL droplets allows for MALDI imaging analysis of as few as ten cells per spot. Partial automation ensures a fast sample preparation workflow. Taken together, the integrated DMA-MSI platform that combines MALDI-MSI, as a label-free analytical readout, with the miniaturized droplet microarray platform is a valuable complement to high throughput cell-based assays technologies.
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Affiliation(s)
- Carina RamalloGuevara
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Paul-Wittsack Str. 10, Mannheim, 68163, Germany
| | - Dorothea Paulssen
- Karlsruhe Institute of Technology (KIT), Institute of Biological and Chemical Systems - Functional Molecular Systems (IBCS-FMS), Hermann-von-Helmholtz-Platz 1, Eggenstein-Leopoldshafen, 76344, Germany
| | - Anna A Popova
- Karlsruhe Institute of Technology (KIT), Institute of Biological and Chemical Systems - Functional Molecular Systems (IBCS-FMS), Hermann-von-Helmholtz-Platz 1, Eggenstein-Leopoldshafen, 76344, Germany
| | - Carsten Hopf
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Paul-Wittsack Str. 10, Mannheim, 68163, Germany
| | - Pavel A Levkin
- Karlsruhe Institute of Technology (KIT), Institute of Biological and Chemical Systems - Functional Molecular Systems (IBCS-FMS), Hermann-von-Helmholtz-Platz 1, Eggenstein-Leopoldshafen, 76344, Germany
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23
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Fresnais M, Yildirim E, Karabulut S, Jäger D, Zörnig I, Benzel J, Pajtler KW, Pfister SM, Burhenne J, Haefeli WE, Longuespée R. Rapid MALDI-MS Assays for Drug Quantification in Biological Matrices: Lessons Learned, New Developments, and Future Perspectives. Molecules 2021; 26:molecules26051281. [PMID: 33652935 PMCID: PMC7956427 DOI: 10.3390/molecules26051281] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 02/22/2021] [Accepted: 02/23/2021] [Indexed: 12/11/2022] Open
Abstract
Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) has rarely been used in the field of therapeutic drug monitoring, partly because of the complexity of the ionization processes between the compounds to be quantified and the many MALDI matrices available. The development of a viable MALDI-MS method that meets regulatory guidelines for bioanalytical method validation requires prior knowledge of the suitability of (i) the MALDI matrix with the analyte class and properties for ionization, (ii) the crystallization properties of the MALDI matrix with automation features, and (iii) the MS instrumentation used to achieve sensitive and specific measurements in order to determine low pharmacological drug concentrations in biological matrices. In the present hybrid article/white paper, we review the developments required for the establishment of MALDI-MS assays for the quantification of drugs in tissues and plasma, illustrated with concrete results for the different steps. We summarize the necessary parameters that need to be controlled for the successful development of fully validated MALDI-MS methods according to regulatory authorities, as well as currently unsolved problems and promising ways to address them. Finally, we propose an expert opinion on future perspectives and needs in order to establish MALDI-MS as a universal method for therapeutic drug monitoring.
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Affiliation(s)
- Margaux Fresnais
- Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Im Neuenheimer Feld 410, 69120 Heidelberg, Germany; (M.F.); (E.Y.); (S.K.); (J.B.); (W.E.H.)
| | - Esra Yildirim
- Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Im Neuenheimer Feld 410, 69120 Heidelberg, Germany; (M.F.); (E.Y.); (S.K.); (J.B.); (W.E.H.)
| | - Seda Karabulut
- Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Im Neuenheimer Feld 410, 69120 Heidelberg, Germany; (M.F.); (E.Y.); (S.K.); (J.B.); (W.E.H.)
| | - Dirk Jäger
- National Center for Tumor Diseases Heidelberg, Department of Medical Oncology, Heidelberg University Hospital, Im Neuenheimer Feld 460, 69120 Heidelberg, Germany; (D.J.); (I.Z.)
| | - Inka Zörnig
- National Center for Tumor Diseases Heidelberg, Department of Medical Oncology, Heidelberg University Hospital, Im Neuenheimer Feld 460, 69120 Heidelberg, Germany; (D.J.); (I.Z.)
| | - Julia Benzel
- Hopp Children’s Cancer Center Heidelberg (KiTZ), Im Neuenheimer Feld 430, 69120 Heidelberg, Germany; (J.B.); (K.W.P.); (S.M.P.)
- German Cancer Research Center (DKFZ), Division of Pediatric Neurooncology, German Cancer Consortium (DKTK), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
| | - Kristian W. Pajtler
- Hopp Children’s Cancer Center Heidelberg (KiTZ), Im Neuenheimer Feld 430, 69120 Heidelberg, Germany; (J.B.); (K.W.P.); (S.M.P.)
- German Cancer Research Center (DKFZ), Division of Pediatric Neurooncology, German Cancer Consortium (DKTK), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
- Department of Pediatric Hematology, Oncology and Immunology, Heidelberg University Hospital, 69120 Heidelberg, Germany
| | - Stefan M. Pfister
- Hopp Children’s Cancer Center Heidelberg (KiTZ), Im Neuenheimer Feld 430, 69120 Heidelberg, Germany; (J.B.); (K.W.P.); (S.M.P.)
- German Cancer Research Center (DKFZ), Division of Pediatric Neurooncology, German Cancer Consortium (DKTK), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
- Department of Pediatric Hematology, Oncology and Immunology, Heidelberg University Hospital, 69120 Heidelberg, Germany
| | - Jürgen Burhenne
- Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Im Neuenheimer Feld 410, 69120 Heidelberg, Germany; (M.F.); (E.Y.); (S.K.); (J.B.); (W.E.H.)
| | - Walter E. Haefeli
- Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Im Neuenheimer Feld 410, 69120 Heidelberg, Germany; (M.F.); (E.Y.); (S.K.); (J.B.); (W.E.H.)
| | - Rémi Longuespée
- Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Im Neuenheimer Feld 410, 69120 Heidelberg, Germany; (M.F.); (E.Y.); (S.K.); (J.B.); (W.E.H.)
- Correspondence:
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24
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Dewez F, De Pauw E, Heeren RMA, Balluff B. Multilabel Per-Pixel Quantitation in Mass Spectrometry Imaging. Anal Chem 2021; 93:1393-1400. [PMID: 33373197 PMCID: PMC7871324 DOI: 10.1021/acs.analchem.0c03186] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Accepted: 12/16/2020] [Indexed: 01/30/2023]
Abstract
In quantitative mass spectrometry imaging (MSI), the gold standard adds a single structural homologue of the target compound at a known concentration to the sample. This internal standard enables to map the detected intensity of the target molecule against an external calibration curve. This approach, however, ignores local noise levels and disproportional ion suppression effects, which might depend on the concentration of the target compound. To overcome these issues, we propose a novel approach that applies several isotopically labeled versions, each at a different concentration, to the sample. This allows creating individual internal calibration curves for every MSI pixel. As proof of principle, we have quantified an endogenous peptide of histone H4 by matrix-assisted laser desorption/ionization-Q-MSI (MALDI-Q-MSI), using a mixture of three isotopically labeled versions. The usage of a fourth label allowed us to compare the gold standard to our multilabel approach. We observed substantial heterogeneity in ion suppression across the tissue, which disclosed itself as varying slopes in the per-pixel regression analyses. These slopes were histology-dependent and differed from each other by up to a factor of 4. The results were validated by liquid chromatography-mass spectrometry (LC-MS), exhibiting a high agreement between LC-MS and MALDI-Q-MSI (Pearson correlation r = 0.87). A comparison between the multilabel and single-label approaches revealed a higher accuracy for the multilabel method when the local target compound concentration differed too much from the concentration of the single label. In conclusion, we show that the multilabel approach provides superior quantitation compared to a single-label approach, in case the target compound is inhomogeneously distributed at a wide concentration range in the tissue.
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Affiliation(s)
- Frédéric Dewez
- Maastricht
Multimodal Molecular Imaging Institute (M4I), Maastricht University, 6200 MD Maastricht, The Netherlands
- Mass
Spectrometry Laboratory (MSLab), University
of Liège, 4000 Liège, Belgium
| | - Edwin De Pauw
- Mass
Spectrometry Laboratory (MSLab), University
of Liège, 4000 Liège, Belgium
| | - Ron M. A. Heeren
- Maastricht
Multimodal Molecular Imaging Institute (M4I), Maastricht University, 6200 MD Maastricht, The Netherlands
| | - Benjamin Balluff
- Maastricht
Multimodal Molecular Imaging Institute (M4I), Maastricht University, 6200 MD Maastricht, The Netherlands
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25
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Dannhorn A, Ling S, Powell S, McCall E, Maglennon G, Jones GN, Pierce AJ, Strittmatter N, Hamm G, Barry ST, Bunch J, Goodwin RJA, Takats Z. Evaluation of UV-C Decontamination of Clinical Tissue Sections for Spatially Resolved Analysis by Mass Spectrometry Imaging (MSI). Anal Chem 2021; 93:2767-2775. [PMID: 33474935 DOI: 10.1021/acs.analchem.0c03430] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Clinical tissue specimens are often unscreened, and preparation of tissue sections for analysis by mass spectrometry imaging (MSI) can cause aerosolization of particles potentially carrying an infectious load. We here present a decontamination approach based on ultraviolet-C (UV-C) light to inactivate clinically relevant pathogens such as herpesviridae, papovaviridae human immunodeficiency virus, or SARS-CoV-2, which may be present in human tissue samples while preserving the biodistributions of analytes within the tissue. High doses of UV-C required for high-level disinfection were found to cause oxidation and photodegradation of endogenous species. Lower UV-C doses maintaining inactivation of clinically relevant pathogens to a level of increased operator safety were found to be less destructive to the tissue metabolome and xenobiotics. These doses caused less alterations of the tissue metabolome and allowed elucidation of the biodistribution of the endogenous metabolites. Additionally, we were able to determine the spatially integrated abundances of the ATR inhibitor ceralasertib from decontaminated human biopsies using desorption electrospray ionization-MSI (DESI-MSI).
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Affiliation(s)
- Andreas Dannhorn
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, 605 SAF Building, South Kensington Campus, London CB4 0FZ, U.K.,Imaging and Data Analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge SW7 2AZ, U.K
| | - Stephanie Ling
- Imaging and Data Analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge SW7 2AZ, U.K
| | - Steven Powell
- Safety, Health and Environment (SHE), Cambridge Operations, BioPharmaceuticals R&D, AstraZeneca, Cambridge CB4 0FZ, U.K
| | - Eileen McCall
- Safety, Health and Environment (SHE), Cambridge Operations, BioPharmaceuticals R&D, AstraZeneca, Cambridge CB4 0FZ, U.K
| | - Gareth Maglennon
- Oncology Safety, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge CB22 3AT, U.K
| | - Gemma N Jones
- Translational Medicine, Oncology R&D, AstraZeneca, Cambridge SG8 6EH, U.K
| | - Andrew J Pierce
- Translational Medicine, Oncology R&D, AstraZeneca, Cambridge SG8 6EH, U.K
| | - Nicole Strittmatter
- Imaging and Data Analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge SW7 2AZ, U.K
| | - Gregory Hamm
- Imaging and Data Analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge SW7 2AZ, U.K
| | - Simon T Barry
- Bioscience, Discovery, Oncology R&D, AstraZeneca, Cambridge CB2 0RE, U.K
| | - Josephine Bunch
- National Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI), National Physical Laboratory, Teddington TW11 0LW, U.K
| | - Richard J A Goodwin
- Imaging and Data Analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge SW7 2AZ, U.K.,Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8QQ, U.K
| | - Zoltan Takats
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, 605 SAF Building, South Kensington Campus, London CB4 0FZ, U.K
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26
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Stolley DL, Crouch AC, Özkan A, Seeley EH, Whitley EM, Rylander MN, Cressman ENK. Combining Chemistry and Engineering for Hepatocellular Carcinoma: Nano-Scale and Smaller Therapies. Pharmaceutics 2020; 12:E1243. [PMID: 33419304 PMCID: PMC7766014 DOI: 10.3390/pharmaceutics12121243] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 12/14/2020] [Accepted: 12/17/2020] [Indexed: 12/24/2022] Open
Abstract
Primary liver cancer, or hepatocellular carcinoma (HCC), is a major worldwide cause of death from carcinoma. Most patients are not candidates for surgery and medical therapies, including new immunotherapies, have not shown major improvements since the modest benefit seen with the introduction of sorafenib over a decade ago. Locoregional therapies for intermediate stage disease are not curative but provide some benefit. However, upon close scrutiny, there is still residual disease in most cases. We review the current status for treatment of intermediate stage disease, summarize the literature on correlative histopathology, and discuss emerging methods at micro-, nano-, and pico-scales to improve therapy. These include transarterial hyperthermia methods and thermoembolization, along with microfluidics model systems and new applications of mass spectrometry imaging for label-free analysis of pharmacokinetics and pharmacodynamics.
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Affiliation(s)
- Danielle L. Stolley
- Department of Biomedical Engineering, The University of Texas, Austin, TX 78712, USA; (D.L.S.); (M.N.R.)
| | - Anna Colleen Crouch
- Interventional Radiology, M.D. Anderson Cancer Center, Houston, TX 77030, USA; (A.C.C.); (E.M.W.)
| | - Aliçan Özkan
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA 02115, USA;
| | - Erin H. Seeley
- Department of Chemistry, University of Texas at Austin, Austin, TX 78712, USA;
| | - Elizabeth M. Whitley
- Interventional Radiology, M.D. Anderson Cancer Center, Houston, TX 77030, USA; (A.C.C.); (E.M.W.)
| | - Marissa Nichole Rylander
- Department of Biomedical Engineering, The University of Texas, Austin, TX 78712, USA; (D.L.S.); (M.N.R.)
| | - Erik N. K. Cressman
- Interventional Radiology, M.D. Anderson Cancer Center, Houston, TX 77030, USA; (A.C.C.); (E.M.W.)
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27
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Tobias F, Hummon AB. Considerations for MALDI-Based Quantitative Mass Spectrometry Imaging Studies. J Proteome Res 2020; 19:3620-3630. [PMID: 32786684 DOI: 10.1021/acs.jproteome.0c00443] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Significant advances in mass spectrometry imaging (MSI) have pushed the boundaries in obtaining spatial information and quantification in biological samples. Quantitative MSI (qMSI) has typically been challenging to achieve because of matrix and tissue heterogeneity, inefficient analyte extraction, and ion suppression effects, but recent studies have demonstrated approaches to obtain highly robust methods and reproducible results. In this perspective, we share our insights into sample preparation, how the choice of matrix influences sensitivity, construction of calibration curves, signal normalization, and visualization of MSI data. We hope that by articulating these guidelines that qMSI can be routinely conducted while retaining the analytical merits of other mass spectrometry modalities.
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28
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Patel SK, George B, Rai V. Artificial Intelligence to Decode Cancer Mechanism: Beyond Patient Stratification for Precision Oncology. Front Pharmacol 2020; 11:1177. [PMID: 32903628 PMCID: PMC7438594 DOI: 10.3389/fphar.2020.01177] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2020] [Accepted: 07/20/2020] [Indexed: 12/13/2022] Open
Abstract
The multitude of multi-omics data generated cost-effectively using advanced high-throughput technologies has imposed challenging domain for research in Artificial Intelligence (AI). Data curation poses a significant challenge as different parameters, instruments, and sample preparations approaches are employed for generating these big data sets. AI could reduce the fuzziness and randomness in data handling and build a platform for the data ecosystem, and thus serve as the primary choice for data mining and big data analysis to make informed decisions. However, AI implication remains intricate for researchers/clinicians lacking specific training in computational tools and informatics. Cancer is a major cause of death worldwide, accounting for an estimated 9.6 million deaths in 2018. Certain cancers, such as pancreatic and gastric cancers, are detected only after they have reached their advanced stages with frequent relapses. Cancer is one of the most complex diseases affecting a range of organs with diverse disease progression mechanisms and the effectors ranging from gene-epigenetics to a wide array of metabolites. Hence a comprehensive study, including genomics, epi-genomics, transcriptomics, proteomics, and metabolomics, along with the medical/mass-spectrometry imaging, patient clinical history, treatments provided, genetics, and disease endemicity, is essential. Cancer Moonshot℠ Research Initiatives by NIH National Cancer Institute aims to collect as much information as possible from different regions of the world and make a cancer data repository. AI could play an immense role in (a) analysis of complex and heterogeneous data sets (multi-omics and/or inter-omics), (b) data integration to provide a holistic disease molecular mechanism, (c) identification of diagnostic and prognostic markers, and (d) monitor patient's response to drugs/treatments and recovery. AI enables precision disease management well beyond the prevalent disease stratification patterns, such as differential expression and supervised classification. This review highlights critical advances and challenges in omics data analysis, dealing with data variability from lab-to-lab, and data integration. We also describe methods used in data mining and AI methods to obtain robust results for precision medicine from "big" data. In the future, AI could be expanded to achieve ground-breaking progress in disease management.
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Affiliation(s)
- Sandip Kumar Patel
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
- Buck Institute for Research on Aging, Novato, CA, United States
| | - Bhawana George
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Vineeta Rai
- Department of Entomology & Plant Pathology, North Carolina State University, Raleigh, NC, United States
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29
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Nice EC. The status of proteomics as we enter the 2020s: Towards personalised/precision medicine. Anal Biochem 2020; 644:113840. [PMID: 32745541 DOI: 10.1016/j.ab.2020.113840] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Revised: 06/06/2020] [Accepted: 06/18/2020] [Indexed: 12/18/2022]
Abstract
The last decade has seen many major advances in proteomics, with over 70,000 publications in the field since 2010. A comprehensive omics toolbox has been developed facilitating rapid in depth analysis of the human proteome. Such studies are advancing our understanding of the biology of both health and disease. The combination of proteomics with other omics platforms (the omics pipeline), in particular proteogenomics, is giving important insights to the molecular changes leading to disease, covering the spectrum from genotype to phenotype and identifying potential biomarkers for disease detection, surveillance and monitoring, and revealing potential new drug targets. Discovery-based finding are now being translated to clinical application, supporting the rollout of precision/personalised medicine. This perspective has focused on twelve areas of importance that have fuelled the field. Recent exemplars are given to illustrate this and show how, together with some emerging technologies, they are anticipated to lead to further advances in the field. However, hurdles still remain to be overcome, especially in the area of Big Data analysis.
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Affiliation(s)
- Edouard C Nice
- Department of Biochemistry and Molecular Biology, Monash University, Clayton, Victoria, 3800, Australia.
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30
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Gachumi G, Purves RW, Hopf C, El-Aneed A. Fast Quantification Without Conventional Chromatography, The Growing Power of Mass Spectrometry. Anal Chem 2020; 92:8628-8637. [PMID: 32510944 DOI: 10.1021/acs.analchem.0c00877] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Mass spectrometry (MS) in hyphenated techniques is widely accepted as the gold standard quantitative tool in life sciences. However, MS possesses intrinsic analytical capabilities that allow it to be a stand-alone quantitative technique, particularly with current technological advancements. MS has a great potential for simplifying quantitative analysis without the need for tedious chromatographic separation. Its selectivity relies on multistage MS analysis (MSn), including tandem mass spectrometry (MS/MS), as well as the ever-growing advancements of high-resolution MS instruments. This perspective describes various analytical platforms that utilize MS as a stand-alone quantitative technique, namely, flow injection analysis (FIA), matrix assisted laser desorption ionization (MALDI), including MALDI-MS imaging and ion mobility, particularly high-field asymmetric waveform ion mobility spectrometry (FAIMS). When MS alone is not capable of providing reliable quantitative data, instead of conventional liquid chromatography (LC)-MS, the use of a guard column (i.e., fast chromatography) may be sufficient for quantification. Although the omission of chromatographic separation simplifies the analytical process, extra procedures may be needed during sample preparation and clean-up to address the issue of matrix effects. The discussion of this manuscript focuses on key parameters underlying the uniqueness of each technique for its application in quantitative analysis without the need for a chromatographic separation. In addition, the potential for each analytical strategy and its challenges are discussed as well as improvements needed to render them as mainstream quantitative analytical tools. Overcoming the hurdles for fully validating a quantitative method will allow MS alone to eventually become an indispensable quantitative tool for clinical and toxicological studies.
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Affiliation(s)
- George Gachumi
- College of Pharmacy and Nutrition, University of Saskatchewan, 107 Wiggins Road, Saskatoon, Saskatchewan Canada, S7N 5E5
| | - Randy W Purves
- College of Pharmacy and Nutrition, University of Saskatchewan, 107 Wiggins Road, Saskatoon, Saskatchewan Canada, S7N 5E5.,Centre for Veterinary Drug Residues, Canadian Food Inspection Agency, 116 Veterinary Rd, Saskatoon, Saskatchewan Canada, S7N 2R3
| | - Carsten Hopf
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Paul-Wittsack-Strasse 10, 68163 Mannheim, Germany
| | - Anas El-Aneed
- College of Pharmacy and Nutrition, University of Saskatchewan, 107 Wiggins Road, Saskatoon, Saskatchewan Canada, S7N 5E5
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31
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Fresnais M, Muck A, Majewsky M, Statz B, Krausert S, Benzel J, Castel D, Le Dret L, Pfister S, Haefeli WE, Burhenne J, Longuespée R. Rapid and Sensitive Drug Quantification in Tissue Sections Using Matrix Assisted Laser Desorption Ionization-Ion Mobility-Mass Spectrometry Profiling. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2020; 31:742-751. [PMID: 31971791 DOI: 10.1021/jasms.0c00005] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Ion mobility spectrometry (IMS) represents a considerable asset for analytics of complex samples as it allows for rapid mass spectrometric separation of compounds. IMS is even more useful for the separation of isobaric compounds when classical separation methods such as liquid chromatography or electrophoresis cannot be used, e.g., during matrix-assisted laser desorption/ionization (MALDI) analyses of biological surfaces. In the present study, we proved the usefulness of IMS for pharmacological applications of MALDI analyses on tissue sections. To illustrate our proof-of-concept, we used the anthelmintic drug mebendazole (MBZ) as a model. Using this exemplary drug, we demonstrated the possibility of using ion mobility to discriminate a drug in tissues from the biological background that masked its signal at low concentrations. In this proof-of-concept, the IMS mode together with the use of a profiling approach for sample preparation enabled quantification of the model drug MBZ from tissue sections in the concentration range 5 to 5,000 ng/g and with a limit of detection of 1 ng/g of tissue, within 2 h. This study highlights the importance of IMS as a separation method for on-surface quantification of drugs in tissue sections.
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Affiliation(s)
- Margaux Fresnais
- Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Im Neuenheimer Feld 410, 69120 Heidelberg, Germany
- German Cancer Consortium (DKTK)-German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
| | | | - Marius Majewsky
- Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Im Neuenheimer Feld 410, 69120 Heidelberg, Germany
| | - Britta Statz
- Hopp Children's Cancer Center, NCT Heidelberg (KiTZ), Im Neuenheimer Feld 460, 69120 Heidelberg, Germany
- Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Grabengasse 1, 69117 Heidelberg, Germany
| | - Sonja Krausert
- Hopp Children's Cancer Center, NCT Heidelberg (KiTZ), Im Neuenheimer Feld 460, 69120 Heidelberg, Germany
- Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Grabengasse 1, 69117 Heidelberg, Germany
| | - Julia Benzel
- Hopp Children's Cancer Center, NCT Heidelberg (KiTZ), Im Neuenheimer Feld 460, 69120 Heidelberg, Germany
| | - David Castel
- Biomarqueurs prédictifs et nouvelles stratégies thérapeutiques en oncologie, Inserm, Gustave Roussy, Université Paris-Saclay, 114 Rue Edouard Vaillant, 94800 Villejuif, France
| | - Ludivine Le Dret
- Biomarqueurs prédictifs et nouvelles stratégies thérapeutiques en oncologie, Inserm, Gustave Roussy, Université Paris-Saclay, 114 Rue Edouard Vaillant, 94800 Villejuif, France
| | - Stefan Pfister
- Hopp Children's Cancer Center, NCT Heidelberg (KiTZ), Im Neuenheimer Feld 460, 69120 Heidelberg, Germany
- Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
| | - Walter E Haefeli
- Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Im Neuenheimer Feld 410, 69120 Heidelberg, Germany
| | - Jürgen Burhenne
- Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Im Neuenheimer Feld 410, 69120 Heidelberg, Germany
| | - Rémi Longuespée
- Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Im Neuenheimer Feld 410, 69120 Heidelberg, Germany
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32
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Föll MC, Moritz L, Wollmann T, Stillger MN, Vockert N, Werner M, Bronsert P, Rohr K, Grüning BA, Schilling O. Accessible and reproducible mass spectrometry imaging data analysis in Galaxy. Gigascience 2019; 8:giz143. [PMID: 31816088 PMCID: PMC6901077 DOI: 10.1093/gigascience/giz143] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2019] [Revised: 09/10/2019] [Accepted: 11/10/2019] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Mass spectrometry imaging is increasingly used in biological and translational research because it has the ability to determine the spatial distribution of hundreds of analytes in a sample. Being at the interface of proteomics/metabolomics and imaging, the acquired datasets are large and complex and often analyzed with proprietary software or in-house scripts, which hinders reproducibility. Open source software solutions that enable reproducible data analysis often require programming skills and are therefore not accessible to many mass spectrometry imaging (MSI) researchers. FINDINGS We have integrated 18 dedicated mass spectrometry imaging tools into the Galaxy framework to allow accessible, reproducible, and transparent data analysis. Our tools are based on Cardinal, MALDIquant, and scikit-image and enable all major MSI analysis steps such as quality control, visualization, preprocessing, statistical analysis, and image co-registration. Furthermore, we created hands-on training material for use cases in proteomics and metabolomics. To demonstrate the utility of our tools, we re-analyzed a publicly available N-linked glycan imaging dataset. By providing the entire analysis history online, we highlight how the Galaxy framework fosters transparent and reproducible research. CONCLUSION The Galaxy framework has emerged as a powerful analysis platform for the analysis of MSI data with ease of use and access, together with high levels of reproducibility and transparency.
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Affiliation(s)
- Melanie Christine Föll
- Institute of Surgical Pathology, Medical Center – University of Freiburg, Breisacher Straße 115a, 79106 Freiburg, Germany
- Faculty of Biology, University of Freiburg, Schänzlestraße 1, 79104 Freiburg, Germany
| | - Lennart Moritz
- Institute of Surgical Pathology, Medical Center – University of Freiburg, Breisacher Straße 115a, 79106 Freiburg, Germany
| | - Thomas Wollmann
- Biomedical Computer Vision Group, BioQuant, IPMB, Heidelberg University, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany
| | - Maren Nicole Stillger
- Institute of Surgical Pathology, Medical Center – University of Freiburg, Breisacher Straße 115a, 79106 Freiburg, Germany
- Faculty of Biology, University of Freiburg, Schänzlestraße 1, 79104 Freiburg, Germany
- Institute of Molecular Medicine and Cell Research, Faculty of Medicine, University of Freiburg, Stefan-Meier-Straße 17, 79104 Freiburg, Germany
| | - Niklas Vockert
- Biomedical Computer Vision Group, BioQuant, IPMB, Heidelberg University, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany
| | - Martin Werner
- Institute of Surgical Pathology, Medical Center – University of Freiburg, Breisacher Straße 115a, 79106 Freiburg, Germany
- Faculty of Medicine - University of Freiburg, Breisacher Straße 153, 79110 Freiburg, Germany
- Tumorbank Comprehensive Cancer Center Freiburg, Medical Center – University of Freiburg, Breisacher Straße 115a, 79106 Freiburg, Germany
- German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Hugstetter Straße 55, 79106 Freiburg, Germany
| | - Peter Bronsert
- Institute of Surgical Pathology, Medical Center – University of Freiburg, Breisacher Straße 115a, 79106 Freiburg, Germany
- Faculty of Medicine - University of Freiburg, Breisacher Straße 153, 79110 Freiburg, Germany
- Tumorbank Comprehensive Cancer Center Freiburg, Medical Center – University of Freiburg, Breisacher Straße 115a, 79106 Freiburg, Germany
- German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Hugstetter Straße 55, 79106 Freiburg, Germany
| | - Karl Rohr
- Biomedical Computer Vision Group, BioQuant, IPMB, Heidelberg University, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany
| | - Björn Andreas Grüning
- Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, 79110 Freiburg, Germany
| | - Oliver Schilling
- Institute of Surgical Pathology, Medical Center – University of Freiburg, Breisacher Straße 115a, 79106 Freiburg, Germany
- Faculty of Medicine - University of Freiburg, Breisacher Straße 153, 79110 Freiburg, Germany
- German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Hugstetter Straße 55, 79106 Freiburg, Germany
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