1
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Guan C, Kong L. Mass spectrometry imaging in pulmonary disorders. Clin Chim Acta 2024; 561:119835. [PMID: 38936534 DOI: 10.1016/j.cca.2024.119835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Revised: 06/24/2024] [Accepted: 06/24/2024] [Indexed: 06/29/2024]
Abstract
Mass Spectrometry Imaging (MSI) represents a novel and advancing technology that offers unparalleled in situ characterization of tissues. It provides comprehensive insights into the chemical structures, relative abundances, and spatial distributions of a vast array of both identified and unidentified endogenous and exogenous compounds, a capability not paralleled by existing analytical methodologies. Recent scholarly endeavors have increasingly explored the utility of MSI in the adjunct diagnosis and biomarker research of pulmonary disorders, including but not limited to lung cancer. Concurrently, MSI has proven instrumental in elucidating the spatiotemporal dynamics of various pharmacological agents. This review concisely delineates the fundamental principles underpinning MSI, its applications in pulmonary disease diagnosis, biomarker discovery, and drug distribution investigations. Additionally, it presents a forward-looking perspective on the prospective trajectories of MSI technological advancements.
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Affiliation(s)
- Chunliu Guan
- Key Laboratory of Environment Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, Jiangsu 210009, China
| | - Lu Kong
- Key Laboratory of Environment Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, Jiangsu 210009, China.
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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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Thorp EB, Karlstaedt A. Intersection of Immunology and Metabolism in Myocardial Disease. Circ Res 2024; 134:1824-1840. [PMID: 38843291 DOI: 10.1161/circresaha.124.323660] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 04/15/2024] [Indexed: 06/12/2024]
Abstract
Immunometabolism is an emerging field at the intersection of immunology and metabolism. Immune cell activation plays a critical role in the pathogenesis of cardiovascular diseases and is integral for regeneration during cardiac injury. We currently possess a limited understanding of the processes governing metabolic interactions between immune cells and cardiomyocytes. The impact of this intercellular crosstalk can manifest as alterations to the steady state flux of metabolites and impact cardiac contractile function. Although much of our knowledge is derived from acute inflammatory response, recent work emphasizes heterogeneity and flexibility in metabolism between cardiomyocytes and immune cells during pathological states, including ischemic, cardiometabolic, and cancer-associated disease. Metabolic adaptation is crucial because it influences immune cell activation, cytokine release, and potential therapeutic vulnerabilities. This review describes current concepts about immunometabolic regulation in the heart, focusing on intercellular crosstalk and intrinsic factors driving cellular regulation. We discuss experimental approaches to measure the cardio-immunologic crosstalk, which are necessary to uncover unknown mechanisms underlying the immune and cardiac interface. Deeper insight into these axes holds promise for therapeutic strategies that optimize cardioimmunology crosstalk for cardiac health.
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Affiliation(s)
- Edward B Thorp
- Department of Pathology, Feinberg School of Medicine, Northwestern University, Chicago, IL (E.B.T.)
| | - Anja Karlstaedt
- Department of Cardiology, Smidt Heart Institute, Cedars Sinai Medical Center, Los Angeles, CA (A.K.)
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4
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Ozdemir A, Lin JL, Gulfen M, Chen CH. Advancing mass spectrometry-based chemical imaging: A noncontact continuous flow surface probe in mass spectrometry for enhanced signal detection and spatial resolution. Talanta 2024; 273:125858. [PMID: 38442563 DOI: 10.1016/j.talanta.2024.125858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 02/26/2024] [Accepted: 02/28/2024] [Indexed: 03/07/2024]
Abstract
A new method has been developed for mass spectrometric imaging of small molecules and proteins on tissue or in thinly sliced materials. A laser desorption Venturi electrospray ionization-mass spectrometer was developed for molecular imaging. This method combines laser desorption (LD) and electrospray ionization (ESI) systems before a mass spectrometer (MS). To carry out laser desorption, samples are excited with a laser from the back side of a glass substrate. The desorbed molecules or particles are then captured by a solvent flow. In the ESI system, these desorbed particles and molecules are ionized. The spray part of the solvent system consists of two capillaries: one delivers solvent to the sample plate sides to capture desorbed molecules and particles, and the other carries the solution to the mass spectrometry side using the Venturi effect. A 2D stage facilitates sampling. The system is designed to minimize the sample size after desorption using a 355 nm diode laser, and it is optimized for molecules of various sizes, including organic molecules, amino acids, and proteins. Despite challenging atmospheric conditions for protein desorption, this specialized design enables the collection of protein spectra. The amino acids and other small molecules showed high sensitivity in the MSI measurements. This innovative MS imaging system can be directly applied to real tissue systems and other plant samples to visualize the molecular level distributions.
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Affiliation(s)
- Abdil Ozdemir
- Department of Chemistry, Faculty of Science, Sakarya University, 54187, Esentepe, Sakarya, Turkey.
| | - Jung-Lee Lin
- Genomics Research Center, Academia Sinica, Taipei, Taiwan
| | - Mustafa Gulfen
- Department of Chemistry, Faculty of Science, Sakarya University, 54187, Esentepe, Sakarya, Turkey
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5
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Santos AA, Delgado TC, Marques V, Ramirez-Moncayo C, Alonso C, Vidal-Puig A, Hall Z, Martínez-Chantar ML, Rodrigues CM. Spatial metabolomics and its application in the liver. Hepatology 2024; 79:1158-1179. [PMID: 36811413 PMCID: PMC11020039 DOI: 10.1097/hep.0000000000000341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 01/05/2023] [Indexed: 02/24/2023]
Abstract
Hepatocytes work in highly structured, repetitive hepatic lobules. Blood flow across the radial axis of the lobule generates oxygen, nutrient, and hormone gradients, which result in zoned spatial variability and functional diversity. This large heterogeneity suggests that hepatocytes in different lobule zones may have distinct gene expression profiles, metabolic features, regenerative capacity, and susceptibility to damage. Here, we describe the principles of liver zonation, introduce metabolomic approaches to study the spatial heterogeneity of the liver, and highlight the possibility of exploring the spatial metabolic profile, leading to a deeper understanding of the tissue metabolic organization. Spatial metabolomics can also reveal intercellular heterogeneity and its contribution to liver disease. These approaches facilitate the global characterization of liver metabolic function with high spatial resolution along physiological and pathological time scales. This review summarizes the state of the art for spatially resolved metabolomic analysis and the challenges that hinder the achievement of metabolome coverage at the single-cell level. We also discuss several major contributions to the understanding of liver spatial metabolism and conclude with our opinion on the future developments and applications of these exciting new technologies.
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Affiliation(s)
- André A. Santos
- Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, Universidade de Lisboa, Lisbon, Portugal
| | - Teresa C. Delgado
- Liver Disease Lab, Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance, Derio, Bizkaia, Spain
- Congenital Metabolic Disorders, Biocruces Bizkaia Health Research Institute, Barakaldo, Spain
- Ikerbasque, Basque Foundation for Science, Bilbao, Spain
| | - Vanda Marques
- Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, Universidade de Lisboa, Lisbon, Portugal
| | - Carmen Ramirez-Moncayo
- Institute of Clinical Sciences, Imperial College London, London, UK
- MRC London Institute of Medical Sciences, London, UK
| | | | - Antonio Vidal-Puig
- MRC Metabolic Diseases Unit, Wellcome Trust-Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Centro Investigation Principe Felipe, Valencia, Spain
| | - Zoe Hall
- Division of Systems Medicine, Imperial College London, London, UK
| | - María Luz Martínez-Chantar
- Liver Disease Lab, Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance, Derio, Bizkaia, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Carlos III National Health Institute, Madrid, Spain
| | - Cecilia M.P. Rodrigues
- Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, Universidade de Lisboa, Lisbon, Portugal
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6
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Ma X, Fernández FM. Advances in mass spectrometry imaging for spatial cancer metabolomics. MASS SPECTROMETRY REVIEWS 2024; 43:235-268. [PMID: 36065601 PMCID: PMC9986357 DOI: 10.1002/mas.21804] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 08/02/2022] [Accepted: 08/02/2022] [Indexed: 05/09/2023]
Abstract
Mass spectrometry (MS) has become a central technique in cancer research. The ability to analyze various types of biomolecules in complex biological matrices makes it well suited for understanding biochemical alterations associated with disease progression. Different biological samples, including serum, urine, saliva, and tissues have been successfully analyzed using mass spectrometry. In particular, spatial metabolomics using MS imaging (MSI) allows the direct visualization of metabolite distributions in tissues, thus enabling in-depth understanding of cancer-associated biochemical changes within specific structures. In recent years, MSI studies have been increasingly used to uncover metabolic reprogramming associated with cancer development, enabling the discovery of key biomarkers with potential for cancer diagnostics. In this review, we aim to cover the basic principles of MSI experiments for the nonspecialists, including fundamentals, the sample preparation process, the evolution of the mass spectrometry techniques used, and data analysis strategies. We also review MSI advances associated with cancer research in the last 5 years, including spatial lipidomics and glycomics, the adoption of three-dimensional and multimodal imaging MSI approaches, and the implementation of artificial intelligence/machine learning in MSI-based cancer studies. The adoption of MSI in clinical research and for single-cell metabolomics is also discussed. Spatially resolved studies on other small molecule metabolites such as amino acids, polyamines, and nucleotides/nucleosides will not be discussed in the context.
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Affiliation(s)
- Xin Ma
- School of Chemistry and Biochemistry and Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Facundo M Fernández
- School of Chemistry and Biochemistry and Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia, USA
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7
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Huergo-Baños C, Velasco V, Garate J, Fernández R, Martín-Allende J, Zabalza I, Artola JL, Martí RM, Asumendi A, Astigarraga E, Barreda-Gómez G, Fresnedo O, Ochoa B, Boyano MD, Fernández JA. Lipid fingerprint-based histology accurately classifies nevus, primary melanoma, and metastatic melanoma samples. Int J Cancer 2024; 154:712-722. [PMID: 37984064 DOI: 10.1002/ijc.34800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 10/24/2023] [Accepted: 11/02/2023] [Indexed: 11/22/2023]
Abstract
Probably, the most important factor for the survival of a melanoma patient is early detection and precise diagnosis. Although in most cases these tasks are readily carried out by pathologists and dermatologists, there are still difficult cases in which no consensus among experts is achieved. To deal with such cases, new methodologies are required. Following this motivation, we explore here the use of lipid imaging mass spectrometry as a complementary tool for the aid in the diagnosis. Thus, 53 samples (15 nevus, 24 primary melanomas, and 14 metastasis) were explored with the aid of a mass spectrometer, using negative polarity. The rich lipid fingerprint obtained from the samples allowed us to set up an artificial intelligence-based classification model that achieved 100% of specificity and precision both in training and validation data sets. A deeper analysis of the image data shows that the technique reports important information on the tumor microenvironment that may give invaluable insights in the prognosis of the lesion, with the correct interpretation.
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Affiliation(s)
- Cristina Huergo-Baños
- Department of Physical Chemistry, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), Leioa, Spain
| | - Verónica Velasco
- Department of Pathology, Cruces University Hospital, Barakaldo, Spain
- Biocruces-Bizkaia Health Research Institute, Cruces University Hospital, Barakaldo, Spain
| | - Jone Garate
- Department of Physical Chemistry, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), Leioa, Spain
| | - Roberto Fernández
- Department of Physical Chemistry, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), Leioa, Spain
| | - Javier Martín-Allende
- Languages and Computer Systems, School of Engineering University of the Basque Country (UPV/EHU), Bilbao, Spain
| | - Ignacio Zabalza
- Biocruces-Bizkaia Health Research Institute, Cruces University Hospital, Barakaldo, Spain
- Department of Pathology, Galdakao-Usansolo University Hospital, Galdakao, Spain
| | - Juan L Artola
- Biocruces-Bizkaia Health Research Institute, Cruces University Hospital, Barakaldo, Spain
- Department of Dermatology, Galdakao-Usansolo University Hospital, Galdakao, Spain
| | - Rosa M Martí
- Department of Dermatology, Arnau de Vilanova University Hospital, Institute of Biomedic Research (IRBLleida), University of Lleida, Lleida, Spain
- Centre of Biomedical Research on Cancer (CIBERONC), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Aintzane Asumendi
- Biocruces-Bizkaia Health Research Institute, Cruces University Hospital, Barakaldo, Spain
- Department of Cell Biology and Histology, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), Leioa, Spain
| | | | | | - Olatz Fresnedo
- Department of Physiology, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), Leioa, Spain
| | - Begoña Ochoa
- Department of Physiology, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), Leioa, Spain
| | - Maria D Boyano
- Biocruces-Bizkaia Health Research Institute, Cruces University Hospital, Barakaldo, Spain
- Department of Cell Biology and Histology, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), Leioa, Spain
| | - José A Fernández
- Department of Physical Chemistry, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), Leioa, Spain
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8
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Verheijen FWM, Tran TNM, Chang JC, Broere F, Zaal EA, Berkers CR. Deciphering metabolic crosstalk in context: lessons from inflammatory diseases. Mol Oncol 2024. [PMID: 38275212 DOI: 10.1002/1878-0261.13588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 11/02/2023] [Accepted: 01/15/2024] [Indexed: 01/27/2024] Open
Abstract
Metabolism plays a crucial role in regulating the function of immune cells in both health and disease, with altered metabolism contributing to the pathogenesis of cancer and many inflammatory diseases. The local microenvironment has a profound impact on the metabolism of immune cells. Therefore, immunological and metabolic heterogeneity as well as the spatial organization of cells in tissues should be taken into account when studying immunometabolism. Here, we highlight challenges of investigating metabolic communication. Additionally, we review the capabilities and limitations of current technologies for studying metabolism in inflamed microenvironments, including single-cell omics techniques, flow cytometry-based methods (Met-Flow, single-cell energetic metabolism by profiling translation inhibition (SCENITH)), cytometry by time of flight (CyTOF), cellular indexing of transcriptomes and epitopes by sequencing (CITE-Seq), and mass spectrometry imaging. Considering the importance of metabolism in regulating immune cells in diseased states, we also discuss the applications of metabolomics in clinical research, as well as some hurdles to overcome to implement these techniques in standard clinical practice. Finally, we provide a flowchart to assist scientists in designing effective strategies to unravel immunometabolism in disease-relevant contexts.
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Affiliation(s)
- Fenne W M Verheijen
- Division of Cell Biology, Metabolism & Cancer, Department Biomolecular Health Sciences, Faculty of Veterinary Medicine, Utrecht University, The Netherlands
- Division of Infectious Diseases and Immunology, Department Biomolecular Health Sciences, Faculty of Veterinary Medicine, Utrecht University, The Netherlands
| | - Thi N M Tran
- Division of Cell Biology, Metabolism & Cancer, Department Biomolecular Health Sciences, Faculty of Veterinary Medicine, Utrecht University, The Netherlands
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Centre for Biomolecular Research, Utrecht University, The Netherlands
| | - Jung-Chin Chang
- Division of Cell Biology, Metabolism & Cancer, Department Biomolecular Health Sciences, Faculty of Veterinary Medicine, Utrecht University, The Netherlands
| | - Femke Broere
- Division of Infectious Diseases and Immunology, Department Biomolecular Health Sciences, Faculty of Veterinary Medicine, Utrecht University, The Netherlands
| | - Esther A Zaal
- Division of Cell Biology, Metabolism & Cancer, Department Biomolecular Health Sciences, Faculty of Veterinary Medicine, Utrecht University, The Netherlands
| | - Celia R Berkers
- Division of Cell Biology, Metabolism & Cancer, Department Biomolecular Health Sciences, Faculty of Veterinary Medicine, Utrecht University, The Netherlands
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9
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Gu J, Cao H, Chen X, Zhang XD, Thorne RF, Liu X. RNA m6A modifications regulate crosstalk between tumor metabolism and immunity. WILEY INTERDISCIPLINARY REVIEWS. RNA 2024; 15:e1829. [PMID: 38114887 DOI: 10.1002/wrna.1829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 11/20/2023] [Accepted: 11/27/2023] [Indexed: 12/21/2023]
Abstract
In recent years, m6A modifications in RNA transcripts have arisen as a hot topic in cancer research. Indeed, a number of independent studies have elaborated that the m6A modification impacts the behavior of tumor cells and tumor-infiltrating immune cells, altering tumor cell metabolism along with the differentiation and functional activity of immune cells. This review elaborates on the links between RNA m6A modifications, tumor cell metabolism, and immune cell behavior, discussing this topic from the viewpoint of reciprocal regulation through "RNA m6A-tumor cell metabolism-immune cell behavior" and "RNA m6A-immune cell behavior-tumor cell metabolism" axes. In addition, we discuss the various factors affecting RNA m6A modifications in the tumor microenvironment, particularly the effects of hypoxia associated with cancer cell metabolism along with immune cell-secreted cytokines. Our analysis proposes the conclusion that RNA m6A modifications support widespread interactions between tumor metabolism and tumor immunity. With the current viewpoint that long-term cancer control must tackle cancer cell malignant behavior while strengthening anti-tumor immunity, the recognition of RNA m6A modifications as a key factor provides a new direction for the targeted therapy of tumors. This article is categorized under: RNA Processing > RNA Editing and Modification RNA in Disease and Development > RNA in Disease RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications.
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Affiliation(s)
- Jinghua Gu
- School of Life Sciences, Anhui Medical University, Hefei, China
- The First Clinical Medical College of Anhui Medical University, Hefei, China
| | - Huake Cao
- School of Life Sciences, Anhui Medical University, Hefei, China
- The First Clinical Medical College of Anhui Medical University, Hefei, China
| | - Xiaoli Chen
- Henan International Joint Laboratory of Non-coding RNA and Metabolism in Cancer, Henan Provincial Key Laboratory of Long Non-coding RNA and Cancer Metabolism, Translational Research Institute of Henan Provincial People's Hospital and People's Hospital of Zhengzhou University, Henan, China
| | - Xu Dong Zhang
- Henan International Joint Laboratory of Non-coding RNA and Metabolism in Cancer, Henan Provincial Key Laboratory of Long Non-coding RNA and Cancer Metabolism, Translational Research Institute of Henan Provincial People's Hospital and People's Hospital of Zhengzhou University, Henan, China
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Newcastle, New South Wales, Australia
| | - Rick F Thorne
- Henan International Joint Laboratory of Non-coding RNA and Metabolism in Cancer, Henan Provincial Key Laboratory of Long Non-coding RNA and Cancer Metabolism, Translational Research Institute of Henan Provincial People's Hospital and People's Hospital of Zhengzhou University, Henan, China
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Newcastle, New South Wales, Australia
| | - Xiaoying Liu
- School of Life Sciences, Anhui Medical University, Hefei, China
- Henan International Joint Laboratory of Non-coding RNA and Metabolism in Cancer, Henan Provincial Key Laboratory of Long Non-coding RNA and Cancer Metabolism, Translational Research Institute of Henan Provincial People's Hospital and People's Hospital of Zhengzhou University, Henan, China
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10
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Daphnis T, Tomasetti B, Delmez V, Vanvarenberg K, Préat V, Thieffry C, Henriet P, Dupont-Gillain C, Delcorte A. Improvement of Lipid Detection in Mouse Brain and Human Uterine Tissue Sections Using In Situ Matrix Enhanced Secondary Ion Mass Spectrometry. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:2259-2268. [PMID: 37712225 DOI: 10.1021/jasms.3c00195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/16/2023]
Abstract
The potential of mass spectrometry imaging, and especially ToF-SIMS 2D and 3D imaging, for submicrometer-scale, label-free molecular localization in biological tissues is undisputable. Nevertheless, sensitivity issues remain, especially when one wants to achieve the best lateral and vertical (nanometer-scale) resolution. In this study, the interest of in situ matrix transfer for tissue analysis with cluster ion beams (Bin+, Arn+) is explored in detail, using a series of six low molecular weight acidic (MALDI) matrices. After estimating the sensitivity enhancements for phosphatidylcholine (PC), an abundant lipid type present in almost any kind of cell membrane, the most promising matrices were softly transferred in situ on mouse brain and human uterine tissue samples using a 10 keV Ar3000+ cluster beam. Signal enhancements up to 1 order of magnitude for intact lipid signals were observed in both tissues under Bi5+ and Ar3000+ bombardment. The main findings of this study lie in the in-depth characterization of uterine tissue samples, the demonstration that the transferred matrices also improve signal efficiency in the negative ion polarity and that they perform as well when using Bin+ and Arn+ primary ions for analysis and imaging.
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Affiliation(s)
- Thomas Daphnis
- Institute of Condensed Matter and Nanoscience, Université catholique de Louvain, 1 Place Louis Pasteur, 1348 Louvain-la-Neuve, Belgium
| | - Benjamin Tomasetti
- Institute of Condensed Matter and Nanoscience, Université catholique de Louvain, 1 Place Louis Pasteur, 1348 Louvain-la-Neuve, Belgium
| | - Vincent Delmez
- Institute of Condensed Matter and Nanoscience, Université catholique de Louvain, 1 Place Louis Pasteur, 1348 Louvain-la-Neuve, Belgium
| | - Kevin Vanvarenberg
- Louvain Drug Research Institute, Université catholique de Louvain, Avenue Mounier 73, 1200 Brussels, Belgium
| | - Véronique Préat
- Louvain Drug Research Institute, Université catholique de Louvain, Avenue Mounier 73, 1200 Brussels, Belgium
| | - Charlotte Thieffry
- Institut De Duve, Université catholique de Louvain, Avenue Hippocrate 75, 1200 Brussels, Belgium
| | - Patrick Henriet
- Institut De Duve, Université catholique de Louvain, Avenue Hippocrate 75, 1200 Brussels, Belgium
| | - Christine Dupont-Gillain
- Institute of Condensed Matter and Nanoscience, Université catholique de Louvain, 1 Place Louis Pasteur, 1348 Louvain-la-Neuve, Belgium
| | - Arnaud Delcorte
- Institute of Condensed Matter and Nanoscience, Université catholique de Louvain, 1 Place Louis Pasteur, 1348 Louvain-la-Neuve, Belgium
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11
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Jia F, Zhao X, Zhao Y. Advancements in ToF-SIMS imaging for life sciences. Front Chem 2023; 11:1237408. [PMID: 37693171 PMCID: PMC10483116 DOI: 10.3389/fchem.2023.1237408] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 08/14/2023] [Indexed: 09/12/2023] Open
Abstract
In the last 2 decades, Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) has gained significant prominence as a powerful imaging technique in the field of life sciences. This comprehensive review provides an in-depth overview of recent advancements in ToF-SIMS instrument technology and its applications in metabolomics, lipidomics, and single-cell analysis. We highlight the use of ToF-SIMS imaging for studying lipid distribution, composition, and interactions in cells and tissues, and discuss its application in metabolomics, including the analysis of metabolic pathways. Furthermore, we review recent progress in single-cell analysis using ToF-SIMS, focusing on sample preparation techniques, in situ investigation for subcellular distribution of drugs, and interactions between drug molecules and biological targets. The high spatial resolution and potential for multimodal analysis of ToF-SIMS make it a promising tool for unraveling the complex molecular landscape of biological systems. We also discuss future prospects and potential advancements of ToF-SIMS in the research of life sciences, with the expectation of a significant impact in the field.
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Affiliation(s)
- Feifei Jia
- National Institutes for Food and Drug Control, Beijing, China
| | - Xia Zhao
- National Institutes for Food and Drug Control, Beijing, China
| | - Yao Zhao
- Beijing National Laboratory for Molecular Sciences, CAS Research/Education Center for Excellence in Molecular Sciences, CAS Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing, China
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12
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Chen TY, You L, Hardillo JAU, Chien MP. Spatial Transcriptomic Technologies. Cells 2023; 12:2042. [PMID: 37626852 PMCID: PMC10453065 DOI: 10.3390/cells12162042] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Revised: 08/02/2023] [Accepted: 08/08/2023] [Indexed: 08/27/2023] Open
Abstract
Spatial transcriptomic technologies enable measurement of expression levels of genes systematically throughout tissue space, deepening our understanding of cellular organizations and interactions within tissues as well as illuminating biological insights in neuroscience, developmental biology and a range of diseases, including cancer. A variety of spatial technologies have been developed and/or commercialized, differing in spatial resolution, sensitivity, multiplexing capability, throughput and coverage. In this paper, we review key enabling spatial transcriptomic technologies and their applications as well as the perspective of the techniques and new emerging technologies that are developed to address current limitations of spatial methodologies. In addition, we describe how spatial transcriptomics data can be integrated with other omics modalities, complementing other methods in deciphering cellar interactions and phenotypes within tissues as well as providing novel insight into tissue organization.
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Affiliation(s)
- Tsai-Ying Chen
- Department of Molecular Genetics, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands; (T.-Y.C.); (L.Y.)
- Erasmus MC Cancer Institute, 3015 GD Rotterdam, The Netherlands;
- Oncode Institute, 3521 AL Utrecht, The Netherlands
| | - Li You
- Department of Molecular Genetics, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands; (T.-Y.C.); (L.Y.)
- Erasmus MC Cancer Institute, 3015 GD Rotterdam, The Netherlands;
- Oncode Institute, 3521 AL Utrecht, The Netherlands
| | - Jose Angelito U. Hardillo
- Erasmus MC Cancer Institute, 3015 GD Rotterdam, The Netherlands;
- Department of Otorhinolaryngology, Head and Neck Surgery, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands
| | - Miao-Ping Chien
- Department of Molecular Genetics, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands; (T.-Y.C.); (L.Y.)
- Erasmus MC Cancer Institute, 3015 GD Rotterdam, The Netherlands;
- Oncode Institute, 3521 AL Utrecht, The Netherlands
- Department of Otorhinolaryngology, Head and Neck Surgery, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands
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13
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Parker GD, Hanley L, Yu XY. Mass Spectral Imaging to Map Plant-Microbe Interactions. Microorganisms 2023; 11:2045. [PMID: 37630605 PMCID: PMC10459445 DOI: 10.3390/microorganisms11082045] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Revised: 07/23/2023] [Accepted: 08/08/2023] [Indexed: 08/27/2023] Open
Abstract
Plant-microbe interactions are of rising interest in plant sustainability, biomass production, plant biology, and systems biology. These interactions have been a challenge to detect until recent advancements in mass spectrometry imaging. Plants and microbes interact in four main regions within the plant, the rhizosphere, endosphere, phyllosphere, and spermosphere. This mini review covers the challenges within investigations of plant and microbe interactions. We highlight the importance of sample preparation and comparisons among time-of-flight secondary ion mass spectroscopy (ToF-SIMS), matrix-assisted laser desorption/ionization (MALDI), laser desorption ionization (LDI/LDPI), and desorption electrospray ionization (DESI) techniques used for the analysis of these interactions. Using mass spectral imaging (MSI) to study plants and microbes offers advantages in understanding microbe and host interactions at the molecular level with single-cell and community communication information. More research utilizing MSI has emerged in the past several years. We first introduce the principles of major MSI techniques that have been employed in the research of microorganisms. An overview of proper sample preparation methods is offered as a prerequisite for successful MSI analysis. Traditionally, dried or cryogenically prepared, frozen samples have been used; however, they do not provide a true representation of the bacterial biofilms compared to living cell analysis and chemical imaging. New developments such as microfluidic devices that can be used under a vacuum are highly desirable for the application of MSI techniques, such as ToF-SIMS, because they have a subcellular spatial resolution to map and image plant and microbe interactions, including the potential to elucidate metabolic pathways and cell-to-cell interactions. Promising results due to recent MSI advancements in the past five years are selected and highlighted. The latest developments utilizing machine learning are captured as an important outlook for maximal output using MSI to study microorganisms.
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Affiliation(s)
- Gabriel D. Parker
- Department of Chemistry, University of Illinois Chicago, Chicago, IL 60607, USA
| | - Luke Hanley
- Department of Chemistry, University of Illinois Chicago, Chicago, IL 60607, USA
| | - Xiao-Ying Yu
- Materials Science and Technology Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
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14
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Guo L, Zhu J, Wang K, Cheng KK, Xu J, Dong L, Xu X, Chen C, Shah M, Peng Z, Wang J, Cai Z, Dong J. Multimodal Image Fusion Offers Better Spatial Resolution for Mass Spectrometry Imaging. Anal Chem 2023. [PMID: 37296503 DOI: 10.1021/acs.analchem.3c02002] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
High-resolution reconstruction has attracted increasing research interest in mass spectrometry imaging (MSI), but it remains a challenging ill-posed problem. In the present study, we proposed a deep learning model to fuse multimodal images to enhance the spatial resolution of MSI data, namely, DeepFERE. Hematoxylin and eosin (H&E) stain microscopy imaging was used to pose constraints in the process of high-resolution reconstruction to alleviate the ill-posedness. A novel model architecture was designed to achieve multi-task optimization by incorporating multi-modal image registration and fusion in a mutually reinforced framework. Experimental results demonstrated that the proposed DeepFERE model is able to produce high-resolution reconstruction images with rich chemical information and a detailed structure on both visual inspection and quantitative evaluation. In addition, our method was found to be able to improve the delimitation of the boundary between cancerous and para-cancerous regions in the MSI image. Furthermore, the reconstruction of low-resolution spatial transcriptomics data demonstrated that the developed DeepFERE model may find wider applications in biomedical fields.
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Affiliation(s)
- Lei Guo
- Department of Electronic Science, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen 361005, China
| | - Jinyu Zhu
- Department of Electronic Science, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen 361005, China
| | - Keqi Wang
- Institute of Big Data Science and Industry, Shanxi University, Taiyuan 030006, China
| | - Kian-Kai Cheng
- Faculty of Chemical and Energy Engineering, Universiti Teknologi Malaysia, Johor Bahru, Johor 81310, Malaysia
| | - Jingjing Xu
- Department of Electronic Science, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen 361005, China
| | - Liheng Dong
- School of Computing and Data Science, Xiamen University Malaysia, Sepang 43600, Malaysia
| | - Xiangnan Xu
- School of Mathematics and Statistics, The University of Sydney, Sydney, NSW 2006, Australia
| | - Can Chen
- Department of Hepatobiliary Surgery and Fujian Institute of Hepatobiliary Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, China
| | - Mudassir Shah
- Department of Electronic Science, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen 361005, China
| | - Zhangxiao Peng
- Department of Molecular Oncology, Eastern Hepatobiliary Surgery Hospital & National Centre for Liver Cancer, Navy Military Medical University, Shanghai 200438, China
| | - Jianing Wang
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR 999077, China
| | - Zongwei Cai
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR 999077, China
| | - Jiyang Dong
- Department of Electronic Science, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen 361005, China
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15
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Liu J, Hu W, Han Y, Nie H. Recent advances in mass spectrometry imaging of single cells. Anal Bioanal Chem 2023:10.1007/s00216-023-04774-9. [PMID: 37269305 DOI: 10.1007/s00216-023-04774-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 05/18/2023] [Accepted: 05/23/2023] [Indexed: 06/05/2023]
Abstract
Mass spectrometry imaging (MSI) is a sensitive, specific, label-free imaging analysis technique that can simultaneously obtain the spatial distribution, relative content, and structural information of hundreds of biomolecules in cells and tissues, such as lipids, small drug molecules, peptides, proteins, and other compounds. The study of molecular mapping of single cells can reveal major scientific issues such as the activity pattern of living organisms, disease pathogenesis, drug-targeted therapy, and cellular heterogeneity. Applying MSI technology to the molecular mapping of single cells can provide new insights and ideas for the study of single-cell metabolomics. This review aims to provide an informative resource for those in the MSI community who are interested in single-cell imaging. Particularly, we discuss advances in imaging schemes and sample preparation, instrumentation improvements, data processing and analysis, and 3D MSI over the past few years that have allowed MSI to emerge as a powerful technique in the molecular imaging of single cells. Also, we highlight some of the most cutting-edge studies in single-cell MSI, demonstrating the future potential of single-cell MSI. Visualizing molecular distribution at the single-cell or even sub-cellular level can provide us with richer cell information, which strongly contributes to advancing research fields such as biomedicine, life sciences, pharmacodynamic testing, and metabolomics. At the end of the review, we summarize the current development of single-cell MSI technology and look into the future of this technology.
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Affiliation(s)
- Jikun Liu
- State Key Laboratory of Heavy Oil Processing, China University of Petroleum, Beijing, 102249, China
- Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
- Analytical Instrumental Center, Peking University, Beijing, 100871, China
| | - Wenya Hu
- State Key Laboratory of Heavy Oil Processing, China University of Petroleum, Beijing, 102249, China
- Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
- Analytical Instrumental Center, Peking University, Beijing, 100871, China
| | - Yehua Han
- State Key Laboratory of Heavy Oil Processing, China University of Petroleum, Beijing, 102249, China.
| | - Honggang Nie
- Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China.
- Analytical Instrumental Center, Peking University, Beijing, 100871, China.
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16
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Borisjuk L, Horn P, Chapman K, Jakob PM, Gündel A, Rolletschek H. Seeing plants as never before. THE NEW PHYTOLOGIST 2023; 238:1775-1794. [PMID: 36895109 DOI: 10.1111/nph.18871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 02/06/2023] [Indexed: 05/04/2023]
Abstract
Imaging has long supported our ability to understand the inner life of plants, their development, and response to a dynamic environment. While optical microscopy remains the core tool for imaging, a suite of novel technologies is now beginning to make a significant contribution to visualize plant metabolism. The purpose of this review was to provide the scientific community with an overview of current imaging methods, which rely variously on either nuclear magnetic resonance (NMR), mass spectrometry (MS) or infrared (IR) spectroscopy, and to present some examples of their application in order to illustrate their utility. In addition to providing a description of the basic principles underlying these technologies, the review discusses their various advantages and limitations, reveals the current state of the art, and suggests their potential application to experimental practice. Finally, a view is presented as to how the technologies will likely develop, how these developments may encourage the formulation of novel experimental strategies, and how the enormous potential of these technologies can contribute to progress in plant science.
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Affiliation(s)
- Ljudmilla Borisjuk
- Leibniz-Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstrasse 3, 06466, Seeland-Gatersleben, Germany
| | - Patrick Horn
- Department of Biological Sciences, BioDiscovery Institute, University of North Texas, Denton, TX, 76203, USA
| | - Kent Chapman
- Department of Biological Sciences, BioDiscovery Institute, University of North Texas, Denton, TX, 76203, USA
| | - Peter M Jakob
- Institute of Experimental Physics 5, University of Würzburg, Am Hubland, 97074, Würzburg, Germany
| | - Andre Gündel
- Leibniz-Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstrasse 3, 06466, Seeland-Gatersleben, Germany
| | - Hardy Rolletschek
- Leibniz-Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstrasse 3, 06466, Seeland-Gatersleben, Germany
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17
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Luo L, Chua YJB, Liu T, Liang K, Chua MWJ, Ma W, Goh JW, Wang Y, Su J, Ho YS, Li CW, Liu KH, Teh BT, Yu K, Shyh-Chang N. Muscle Injuries Induce a Prostacyclin-PPARγ/PGC1a-FAO Spike That Boosts Regeneration. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023:e2301519. [PMID: 37140179 PMCID: PMC10375192 DOI: 10.1002/advs.202301519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 03/14/2023] [Indexed: 05/05/2023]
Abstract
It is well-known that muscle regeneration declines with aging, and aged muscles undergo degenerative atrophy or sarcopenia. While exercise and acute injury are both known to induce muscle regeneration, the molecular signals that help trigger muscle regeneration have remained unclear. Here, mass spectrometry imaging (MSI) is used to show that injured muscles induce a specific subset of prostanoids during regeneration, including PGG1, PGD2, and the prostacyclin PGI2. The spike in prostacyclin promotes skeletal muscle regeneration via myoblasts, and declines with aging. Mechanistically, the prostacyclin spike promotes a spike in PPARγ/PGC1a signaling, which induces a spike in fatty acid oxidation (FAO) to control myogenesis. LC-MS/MS and MSI further confirm that an early FAO spike is associated with normal regeneration, but muscle FAO became dysregulated during aging. Functional experiments demonstrate that the prostacyclin-PPARγ/PGC1a-FAO spike is necessary and sufficient to promote both young and aged muscle regeneration, and that prostacyclin can synergize with PPARγ/PGC1a-FAO signaling to restore aged muscles' regeneration and physical function. Given that the post-injury prostacyclin-PPARγ-FAO spike can be modulated pharmacologically and via post-exercise nutrition, this work has implications for how prostacyclin-PPARγ-FAO might be fine-tuned to promote regeneration and treat muscle diseases of aging.
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Affiliation(s)
- Lanfang Luo
- Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, P. R. China
- Beijing Institute for Stem Cell and Regenerative Medicine, Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, P. R. China
- University of Chinese Academy of Sciences, Beijing, 100049, P. R. China
| | - Yan-Jiang Benjamin Chua
- NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore City, 119077, Singapore
- Genome Institute of Singapore, Institute of Molecular and Cell Biology, Agency for Science Technology and Research, Singapore City, 138672, Singapore
| | - Taoyan Liu
- Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, P. R. China
- Beijing Institute for Stem Cell and Regenerative Medicine, Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, P. R. China
| | - Kun Liang
- Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, P. R. China
- Beijing Institute for Stem Cell and Regenerative Medicine, Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, P. R. China
- University of Chinese Academy of Sciences, Beijing, 100049, P. R. China
| | - Min-Wen Jason Chua
- NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore City, 119077, Singapore
- Genome Institute of Singapore, Institute of Molecular and Cell Biology, Agency for Science Technology and Research, Singapore City, 138672, Singapore
| | - Wenwu Ma
- Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, P. R. China
- Beijing Institute for Stem Cell and Regenerative Medicine, Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, P. R. China
- University of Chinese Academy of Sciences, Beijing, 100049, P. R. China
| | - Jun-Wei Goh
- Genome Institute of Singapore, Institute of Molecular and Cell Biology, Agency for Science Technology and Research, Singapore City, 138672, Singapore
| | - Yuefan Wang
- Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, P. R. China
- Beijing Institute for Stem Cell and Regenerative Medicine, Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, P. R. China
- University of Chinese Academy of Sciences, Beijing, 100049, P. R. China
| | - Jiali Su
- Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, P. R. China
- Beijing Institute for Stem Cell and Regenerative Medicine, Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, P. R. China
- University of Chinese Academy of Sciences, Beijing, 100049, P. R. China
| | - Ying Swan Ho
- Bioprocessing Technology Institute, Agency for Science Technology and Research, Singapore City, 138668, Singapore
| | - Chun-Wei Li
- Department of Clinical Nutrition, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, P. R. China
| | - Ke Hui Liu
- Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, P. R. China
- Beijing Institute for Stem Cell and Regenerative Medicine, Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, P. R. China
| | - Bin Tean Teh
- Laboratory of Cancer Therapeutics, Program in Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore City, 169857, Singapore
- Division of Medical Science, Laboratory of Cancer Epigenome, National Cancer Centre Singapore, Singapore City, 119074, Singapore
| | - Kang Yu
- Department of Clinical Nutrition, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, P. R. China
| | - Ng Shyh-Chang
- Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, P. R. China
- Beijing Institute for Stem Cell and Regenerative Medicine, Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, P. R. China
- University of Chinese Academy of Sciences, Beijing, 100049, P. R. China
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18
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Mogilenko DA, Sergushichev A, Artyomov MN. Systems Immunology Approaches to Metabolism. Annu Rev Immunol 2023; 41:317-342. [PMID: 37126419 DOI: 10.1146/annurev-immunol-101220-031513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
Over the last decade, immunometabolism has emerged as a novel interdisciplinary field of research and yielded significant fundamental insights into the regulation of immune responses. Multiple classical approaches to interrogate immunometabolism, including bulk metabolic profiling and analysis of metabolic regulator expression, paved the way to appreciating the physiological complexity of immunometabolic regulation in vivo. Studying immunometabolism at the systems level raised the need to transition towards the next-generation technology for metabolic profiling and analysis. Spatially resolved metabolic imaging and computational algorithms for multi-modal data integration are new approaches to connecting metabolism and immunity. In this review, we discuss recent studies that highlight the complex physiological interplay between immune responses and metabolism and give an overview of technological developments that bear the promise of capturing this complexity most directly and comprehensively.
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Affiliation(s)
- Denis A Mogilenko
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri, USA; ,
- Current affiliation: Department of Medicine, Department of Pathology, Microbiology, and Immunology, and Vanderbilt Center for Immunobiology, Vanderbilt University Medical Center, Nashville, Tennessee, USA;
| | - Alexey Sergushichev
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri, USA; ,
- Computer Technologies Laboratory, ITMO University, Saint Petersburg, Russia
| | - Maxim N Artyomov
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri, USA; ,
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19
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Krijnen K, Keelor JD, Böhm S, Ellis SR, Köster C, Höhndorf J, Heeren RMA, Anthony IGM. A Multimodal SIMS/MALDI Mass Spectrometry Imaging Source with Secondary Electron Imaging Capabilities for Use with timsTOF Instruments. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:720-727. [PMID: 36891615 PMCID: PMC10080675 DOI: 10.1021/jasms.2c00381] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 02/09/2023] [Accepted: 02/13/2023] [Indexed: 06/18/2023]
Abstract
Mass spectrometry imaging (MSI) is a surface analysis technique that produces chemical images and is commonly used for biological and biomedical research. Multimodal imaging combines multiple imaging modes in order to get a more comprehensive view of a sample. Multimodal MSI images are often acquired using multiple MSI instruments, which leads to issues regarding image registration and increases the chance of sample damage or degradation during sample transfer. These problems can be solved by using a single instrument that can image in multiple modes. In order to improve the efficiency of multimodal imaging and investigate complementary modes of MSI, we have modified a prototype Bruker timsTOF fleX by adding secondary ion mass spectrometry (SIMS) and secondary electron (SE) imaging capabilities while preserving the ability to perform matrix-assisted laser desorption/ionization (MALDI). We show multimodal images collected on this instrument that required only trivial registration and were acquired without sample transfer between imaging trials. Furthermore, we characterize the performance of SIMS, SE, and MALDI imaging and compare the performance of the modified instrument to a commercial timsTOF fleX.
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Affiliation(s)
- Kasper Krijnen
- Maastricht
MultiModal Molecular Imaging (M4i) Institute, Division of Imaging
Mass Spectrometry, Maastricht University, 6229 ER Maastricht, The Netherlands
| | - Joel D. Keelor
- Maastricht
MultiModal Molecular Imaging (M4i) Institute, Division of Imaging
Mass Spectrometry, Maastricht University, 6229 ER Maastricht, The Netherlands
| | - Sebastian Böhm
- Bruker
Daltonics GmbH & Co KG, Fahrenheitstraße 4, 28359 Bremen, Germany
| | - Shane R. Ellis
- Maastricht
MultiModal Molecular Imaging (M4i) Institute, Division of Imaging
Mass Spectrometry, Maastricht University, 6229 ER Maastricht, The Netherlands
- Molecular
Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Wollongong, New South Wales 2522, Australia
| | - Claus Köster
- Bruker
Daltonics GmbH & Co KG, Fahrenheitstraße 4, 28359 Bremen, Germany
| | - Jens Höhndorf
- Bruker
Daltonics GmbH & Co KG, Fahrenheitstraße 4, 28359 Bremen, Germany
| | - Ron M. A. Heeren
- Maastricht
MultiModal Molecular Imaging (M4i) Institute, Division of Imaging
Mass Spectrometry, Maastricht University, 6229 ER Maastricht, The Netherlands
| | - Ian G. M. Anthony
- Maastricht
MultiModal Molecular Imaging (M4i) Institute, Division of Imaging
Mass Spectrometry, Maastricht University, 6229 ER Maastricht, The Netherlands
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20
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Chen Q, Li H, Tian H, Lam SM, Liao Y, Zhang Z, Dong M, Chen S, Yao Y, Meng J, Zhang Y, Zheng L, Meng ZX, Han W, Shui G, Zhu D, Fu S. Global determination of reaction rates and lipid turnover kinetics in Mus musculus. Cell Metab 2023; 35:711-721.e4. [PMID: 37019081 DOI: 10.1016/j.cmet.2023.03.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 11/01/2022] [Accepted: 03/07/2023] [Indexed: 04/07/2023]
Abstract
Metabolism is fundamental to life, but measuring metabolic reaction rates remains challenging. Here, we applied C13 fluxomics to monitor the metabolism of dietary glucose carbon in 12 tissues, 9 brain compartments, and over 1,000 metabolite isotopologues over a 4-day period. The rates of 85 reactions surrounding central carbon metabolism are determined with elementary metabolite unit (EMU) modeling. Lactate oxidation, not glycolysis, occurs at a comparable pace with the tricarboxylic acid cycle (TCA), supporting lactate as the primary fuel. We expand the EMU framework to track and quantify metabolite flows across tissues. Specifically, multi-organ EMU simulation of uridine metabolism shows that tissue-blood exchange, not synthesis, controls nucleotide homeostasis. In contrast, isotopologue fingerprinting and kinetic analyses reveal the brown adipose tissue (BAT) having the highest palmitate synthesis activity but no apparent contribution to circulation, suggesting a tissue-autonomous synthesis-to-burn mechanism. Together, this study demonstrates the utility of dietary fluxomics for kinetic mapping in vivo and provides a rich resource for elucidating inter-organ metabolic cross talk.
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Affiliation(s)
- Qishan Chen
- Guangzhou Laboratory, Guangzhou, Guangdong 510005, China
| | - Hu Li
- Bioland Laboratory, Guangzhou, Guangdong 510320, China
| | - He Tian
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Sin Man Lam
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China; LipidALL Technologies Company Limited, Changzhou, Jiangsu 213022, China
| | - Yilie Liao
- Bioland Laboratory, Guangzhou, Guangdong 510320, China; Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A(∗)STAR), Singapore 138673, Singapore
| | - Ziyin Zhang
- Department of Pathology and Pathophysiology and Department of Cardiology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China
| | - Manyuan Dong
- The Institute of Cardiovascular Sciences and Institute of Systems Biomedicine, School of Basic Medical Sciences, Key Laboratory of Molecular Cardiovascular Science of Ministry of Education, NHC Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Beijing Key Laboratory of Cardiovascular Receptors Research, Health Science Center, Peking University, Beijing 100191, China
| | - Shaoru Chen
- Bioland Laboratory, Guangzhou, Guangdong 510320, China
| | - Yuxiao Yao
- Bioland Laboratory, Guangzhou, Guangdong 510320, China
| | - Jiemiao Meng
- Bioland Laboratory, Guangzhou, Guangdong 510320, China
| | - Yong Zhang
- Bioland Laboratory, Guangzhou, Guangdong 510320, China; The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing 100005, China
| | - Lemin Zheng
- The Institute of Cardiovascular Sciences and Institute of Systems Biomedicine, School of Basic Medical Sciences, Key Laboratory of Molecular Cardiovascular Science of Ministry of Education, NHC Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Beijing Key Laboratory of Cardiovascular Receptors Research, Health Science Center, Peking University, Beijing 100191, China
| | - Zhuo-Xian Meng
- Department of Pathology and Pathophysiology and Department of Cardiology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China
| | - Weiping Han
- Bioland Laboratory, Guangzhou, Guangdong 510320, China; Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A(∗)STAR), Singapore 138673, Singapore
| | - Guanghou Shui
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Dahai Zhu
- Bioland Laboratory, Guangzhou, Guangdong 510320, China; The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing 100005, China
| | - Suneng Fu
- Guangzhou Laboratory, Guangzhou, Guangdong 510005, China.
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21
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Hogan KA, Zeidler JD, Beasley HK, Alsaadi AI, Alshaheeb AA, Chang YC, Tian H, Hinton AO, McReynolds MR. Using mass spectrometry imaging to visualize age-related subcellular disruption. Front Mol Biosci 2023; 10:906606. [PMID: 36968274 PMCID: PMC10032471 DOI: 10.3389/fmolb.2023.906606] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 01/24/2023] [Indexed: 03/10/2023] Open
Abstract
Metabolic homeostasis balances the production and consumption of energetic molecules to maintain active, healthy cells. Cellular stress, which disrupts metabolism and leads to the loss of cellular homeostasis, is important in age-related diseases. We focus here on the role of organelle dysfunction in age-related diseases, including the roles of energy deficiencies, mitochondrial dysfunction, endoplasmic reticulum (ER) stress, changes in metabolic flux in aging (e.g., Ca2+ and nicotinamide adenine dinucleotide), and alterations in the endoplasmic reticulum-mitochondria contact sites that regulate the trafficking of metabolites. Tools for single-cell resolution of metabolite pools and metabolic flux in animal models of aging and age-related diseases are urgently needed. High-resolution mass spectrometry imaging (MSI) provides a revolutionary approach for capturing the metabolic states of individual cells and cellular interactions without the dissociation of tissues. mass spectrometry imaging can be a powerful tool to elucidate the role of stress-induced cellular dysfunction in aging.
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Affiliation(s)
- Kelly A. Hogan
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA, United States
- Signal Transduction and Molecular Nutrition Laboratory, Kogod Aging Center, Department of Anesthesiology and Perioperative Medicine, Mayo Clinic College of Medicine, Rochester, MN, United States
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, United States
| | - Julianna D. Zeidler
- Instituto de Bioquímica Médica Leopoldo de Meis, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Heather K. Beasley
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, United States
| | - Abrar I. Alsaadi
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA, United States
| | - Abdulkareem A. Alshaheeb
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA, United States
| | - Yi-Chin Chang
- Department of Chemistry, Pennsylvania State University, University Park, PA, United States
| | - Hua Tian
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, United States
- Department of Chemistry, Pennsylvania State University, University Park, PA, United States
- *Correspondence: Hua Tian, ; Antentor O. Hinton Jr, ; Melanie R. McReynolds,
| | - Antentor O. Hinton
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, United States
- *Correspondence: Hua Tian, ; Antentor O. Hinton Jr, ; Melanie R. McReynolds,
| | - Melanie R. McReynolds
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA, United States
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, United States
- *Correspondence: Hua Tian, ; Antentor O. Hinton Jr, ; Melanie R. McReynolds,
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22
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Chandran M, S S, Abhirami, Chandran A, Jaleel A, Plakkal Ayyappan J. Defining atherosclerotic plaque biology by mass spectrometry-based omics approaches. Mol Omics 2023; 19:6-26. [PMID: 36426765 DOI: 10.1039/d2mo00260d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Atherosclerosis is the principal cause of vascular diseases and one of the leading causes of worldwide death. Even though several insights into its natural course, risk factors and interventions have been identified, it is still an ongoing global pandemic. Since the structure and biochemical composition of the plaques show high heterogeneity, a comprehensive understanding of the intraplaque composition, its microenvironment, and the mechanisms of the progression and instability across different vascular beds at their progression stages is crucial for better risk stratification and treatment modalities. Even though several cell-based studies, animal studies, and extensive multicentric population studies have been conducted concerning cardiovascular diseases for assessing the risk factors and plaque biology, the studies on human clinical samples are very limited. New novel approaches utilize samples from percutaneous coronary interventions, which could possibly gain more access to clinical samples at different stages of the diseases without complex invasive resections. As an emerging technological platform in disease discovery research, mass spectrometry-based omics technologies offer capabilities for a comprehensive understanding of the mechanisms linked to several vascular diseases. Here, we discuss the cellular and molecular processes of atherosclerosis, different mass spectrometry-based omics approaches, and the studies mostly done on clinical samples of atheroma plaque using mass spectrometry-based proteomics, metabolomics and lipidomics approaches.
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Affiliation(s)
- Mahesh Chandran
- Translational Nanomedicine and Lifestyle Disease Research Laboratory, Department of Biochemistry, University of Kerala, Thiruvananthapuram 695034, Kerala, India. .,Department of Biotechnology, University of Kerala, Thiruvananthapuram 695034, Kerala, India.,Mass Spectrometry and Proteomics Core Facility, Rajiv Gandhi Centre for Biotechnology, Thiruvananthapuram, Kerala, 695012, India
| | - Sudhina S
- Translational Nanomedicine and Lifestyle Disease Research Laboratory, Department of Biochemistry, University of Kerala, Thiruvananthapuram 695034, Kerala, India.
| | - Abhirami
- Translational Nanomedicine and Lifestyle Disease Research Laboratory, Department of Biochemistry, University of Kerala, Thiruvananthapuram 695034, Kerala, India.
| | - Akash Chandran
- Department of Nanoscience and Nanotechnology, University of Kerala, Kariavattom, Thiruvananthapuram-695581, Kerala, India
| | - Abdul Jaleel
- Mass Spectrometry and Proteomics Core Facility, Rajiv Gandhi Centre for Biotechnology, Thiruvananthapuram, Kerala, 695012, India
| | - Janeesh Plakkal Ayyappan
- Translational Nanomedicine and Lifestyle Disease Research Laboratory, Department of Biochemistry, University of Kerala, Thiruvananthapuram 695034, Kerala, India. .,Department of Biotechnology, University of Kerala, Thiruvananthapuram 695034, Kerala, India.,Department of Nanoscience and Nanotechnology, University of Kerala, Kariavattom, Thiruvananthapuram-695581, Kerala, India.,Centre for Advanced Cancer Research, Department of Biochemistry, University of Kerala, Thiruvananthapuram 695034, Kerala, India
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23
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Martín-Saiz L, Abad-García B, Solano-Iturri JD, Mosteiro L, Martín-Allende J, Rueda Y, Pérez-Fernández A, Unda M, Coterón-Ochoa P, Goya A, Saiz A, Martínez J, Ochoa B, Fresnedo O, Larrinaga G, Fernández JA. Using the Synergy between HPLC-MS and MALDI-MS Imaging to Explore the Lipidomics of Clear Cell Renal Cell Carcinoma. Anal Chem 2023; 95:2285-2293. [PMID: 36638042 PMCID: PMC9893214 DOI: 10.1021/acs.analchem.2c03953] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Lipid imaging mass spectrometry (LIMS) has been tested in several pathological contexts, demonstrating its ability to segregate and isolate lipid signatures in complex tissues, thanks to the technique's spatial resolution. However, it cannot yet compete with the superior identification power of high-performance liquid chromatography coupled to mass spectrometry (HPLC-MS), and therefore, very often, the latter is used to refine the assignment of the species detected by LIMS. Also, it is not clear if the differences in sensitivity and spatial resolution between the two techniques lead to a similar panel of biomarkers for a given disease. Here, we explore the capabilities of LIMS and HPLC-MS to produce a panel of lipid biomarkers to screen nephrectomy samples from 40 clear cell renal cell carcinoma patients. The same set of samples was explored by both techniques, and despite the important differences between them in terms of the number of detected and identified species (148 by LIMS and 344 by HPLC-MS in negative-ion mode) and the presence/absence of image capabilities, similar conclusions were reached: using the lipid fingerprint, it is possible to set up classifiers that correctly identify the samples as either healthy or tumor samples. The spatial resolution of LIMS enables extraction of additional information, such as the existence of necrotic areas or the existence of different tumor cell populations, but such information does not seem determinant for the correct classification of the samples, or it may be somehow compensated by the higher analytical power of HPLC-MS. Similar conclusions were reached with two very different techniques, validating their use for the discovery of lipid biomarkers.
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Affiliation(s)
- Lucía Martín-Saiz
- Department
of Physical Chemistry, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), B. Sarriena, s/n, Leioa 48940, Spain
| | - Beatriz Abad-García
- Central
Analysis Service, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), Leioa 48940, Spain
| | - Jon D. Solano-Iturri
- Service
of Anatomic Pathology, Donostia University
Hospital, Donostia/San
Sebastian 20014, Spain,Biocruces
Bizkaia Health Research Institute, Barakaldo 48903, Spain
| | - Lorena Mosteiro
- Service
of Anatomic Pathology, Cruces University
Hospital, Barakaldo 48903, Spain
| | - Javier Martín-Allende
- Department
of Physical Chemistry, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), B. Sarriena, s/n, Leioa 48940, Spain
| | - Yuri Rueda
- Lipids &
Liver, Department of Physiology, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), B. Sarriena, s/n, Leioa 48940, Spain
| | | | - Miguel Unda
- Service
of Urology, Basurto University Hospital, Bilbao 48003, Spain
| | - Pedro Coterón-Ochoa
- Service
of Urology, Galdakao-Usansolo University
Hospital, Galdakao 48960, Spain
| | - Aintzane Goya
- Service
of Urology, Galdakao-Usansolo University
Hospital, Galdakao 48960, Spain
| | - Alberto Saiz
- Service
of Anatomic Pathology, Galdakao-Usansolo
University Hospital, Galdakao 48960, Spain
| | - Jennifer Martínez
- Service
of Anatomic Pathology, Galdakao-Usansolo
University Hospital, Galdakao 48960, Spain
| | - Begoña Ochoa
- Lipids &
Liver, Department of Physiology, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), B. Sarriena, s/n, Leioa 48940, Spain
| | - Olatz Fresnedo
- Lipids &
Liver, Department of Physiology, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), B. Sarriena, s/n, Leioa 48940, Spain
| | - Gorka Larrinaga
- Biocruces
Bizkaia Health Research Institute, Barakaldo 48903, Spain,Department
of Nursing and Department of Physiology, Faculty of Medicine and Nursing (UPV/EHU), Leioa 48940, Spain
| | - José A. Fernández
- Department
of Physical Chemistry, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), B. Sarriena, s/n, Leioa 48940, Spain,. Phone: +34 6015387
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24
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Zhang Z, Bao C, Jiang L, Wang S, Wang K, Lu C, Fang H. When cancer drug resistance meets metabolomics (bulk, single-cell and/or spatial): Progress, potential, and perspective. Front Oncol 2023; 12:1054233. [PMID: 36686803 PMCID: PMC9854130 DOI: 10.3389/fonc.2022.1054233] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 12/20/2022] [Indexed: 01/07/2023] Open
Abstract
Resistance to drug treatment is a critical barrier in cancer therapy. There is an unmet need to explore cancer hallmarks that can be targeted to overcome this resistance for therapeutic gain. Over time, metabolic reprogramming has been recognised as one hallmark that can be used to prevent therapeutic resistance. With the advent of metabolomics, targeting metabolic alterations in cancer cells and host patients represents an emerging therapeutic strategy for overcoming cancer drug resistance. Driven by technological and methodological advances in mass spectrometry imaging, spatial metabolomics involves the profiling of all the metabolites (metabolomics) so that the spatial information is captured bona fide within the sample. Spatial metabolomics offers an opportunity to demonstrate the drug-resistant tumor profile with metabolic heterogeneity, and also poses a data-mining challenge to reveal meaningful insights from high-dimensional spatial information. In this review, we discuss the latest progress, with the focus on currently available bulk, single-cell and spatial metabolomics technologies and their successful applications in pre-clinical and translational studies on cancer drug resistance. We provide a summary of metabolic mechanisms underlying cancer drug resistance from different aspects; these include the Warburg effect, altered amino acid/lipid/drug metabolism, generation of drug-resistant cancer stem cells, and immunosuppressive metabolism. Furthermore, we propose solutions describing how to overcome cancer drug resistance; these include early detection during cancer initiation, monitoring of clinical drug response, novel anticancer drug and target metabolism, immunotherapy, and the emergence of spatial metabolomics. We conclude by describing the perspectives on how spatial omics approaches (integrating spatial metabolomics) could be further developed to improve the management of drug resistance in cancer patients.
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Affiliation(s)
- Zhiqiang Zhang
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China,School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
| | - Chaohui Bao
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lu Jiang
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shan Wang
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Kankan Wang
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chang Lu
- MRC London Institute of Medical Sciences, Imperial College London, London, United Kingdom
| | - Hai Fang
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China,*Correspondence: Hai Fang,
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25
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Hu R, Li Y, Yang Y, Liu M. Mass spectrometry-based strategies for single-cell metabolomics. MASS SPECTROMETRY REVIEWS 2023; 42:67-94. [PMID: 34028064 DOI: 10.1002/mas.21704] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 05/05/2021] [Accepted: 05/11/2021] [Indexed: 06/12/2023]
Abstract
Single cell analysis has drawn increasing interest from the research community due to its capability to interrogate cellular heterogeneity, allowing refined tissue classification and facilitating novel biomarker discovery. With the advancement of relevant instruments and techniques, it is now possible to perform multiple omics including genomics, transcriptomics, metabolomics or even proteomics at single cell level. In comparison with other omics studies, single-cell metabolomics (SCM) represents a significant challenge since it involves many types of dynamically changing compounds with a wide range of concentrations. In addition, metabolites cannot be amplified. Although difficult, considerable progress has been made over the past decade in mass spectrometry (MS)-based SCM in terms of processing technologies and biochemical applications. In this review, we will summarize recent progress in the development of promising MS platforms, sample preparation methods and SCM analysis of various cell types (including plant cell, cancer cell, neuron, embryo cell, and yeast cell). Current limitations and future research directions in the field of SCM will also be discussed.
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Affiliation(s)
- Rui Hu
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Ying Li
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yunhuang Yang
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Maili Liu
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
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26
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Schneemann J, Schäfer KC, Spengler B, Heiles S. IR-MALDI Mass Spectrometry Imaging with Plasma Post-Ionization of Nonpolar Metabolites. Anal Chem 2022; 94:16086-16094. [DOI: 10.1021/acs.analchem.2c03247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Julian Schneemann
- Institute of Inorganic and Analytical Chemistry, Justus Liebig University Giessen, 35392 Giessen, Germany
| | | | - Bernhard Spengler
- Institute of Inorganic and Analytical Chemistry, Justus Liebig University Giessen, 35392 Giessen, Germany
| | - Sven Heiles
- Institute of Inorganic and Analytical Chemistry, Justus Liebig University Giessen, 35392 Giessen, Germany
- Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V., Otto-Hahn-Straße 6b, 44139 Dortmund, Germany
- Lipidomics, Faculty of Chemistry, University of Duisburg-Essen, Universitätsstrasse 5, 45141 Essen, Germany
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27
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Dreisbach D, Heiles S, Bhandari DR, Petschenka G, Spengler B. Molecular Networking and On-Tissue Chemical Derivatization for Enhanced Identification and Visualization of Steroid Glycosides by MALDI Mass Spectrometry Imaging. Anal Chem 2022; 94:15971-15979. [DOI: 10.1021/acs.analchem.2c02694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Domenic Dreisbach
- Institute for Inorganic and Analytical Chemistry, Justus Liebig University Giessen, Heinrich-Buff-Ring 17, 35392 Giessen, Germany
| | - Sven Heiles
- Institute for Inorganic and Analytical Chemistry, Justus Liebig University Giessen, Heinrich-Buff-Ring 17, 35392 Giessen, Germany
- Leibniz Institute for Analytical Sciences, ISAS−e.V., Otto-Hahn-Straße 6b, 44139 Dortmund, Germany
- Lipidomics, Faculty of Chemistry, University of Duisburg-Essen, Universitätsstraße 5, 45141 Essen, Germany
| | - Dhaka R. Bhandari
- Institute for Inorganic and Analytical Chemistry, Justus Liebig University Giessen, Heinrich-Buff-Ring 17, 35392 Giessen, Germany
| | - Georg Petschenka
- Institute of Phytomedicine, University of Hohenheim, Otto-Sander-Straße 5, 70599 Stuttgart, Germany
| | - Bernhard Spengler
- Institute for Inorganic and Analytical Chemistry, Justus Liebig University Giessen, Heinrich-Buff-Ring 17, 35392 Giessen, Germany
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28
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Pillai MS, Paritala ST, Shah RP, Sharma N, Sengupta P. Cutting-edge strategies and critical advancements in characterization and quantification of metabolites concerning translational metabolomics. Drug Metab Rev 2022; 54:401-426. [PMID: 36351878 DOI: 10.1080/03602532.2022.2125987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Despite remarkable progress in drug discovery strategies, significant challenges are still remaining in translating new insights into clinical applications. Scientists are devising creative approaches to bridge the gap between scientific and translational research. Metabolomics is a unique field among other omics techniques for identifying novel metabolites and biomarkers. Fortunately, characterization and quantification of metabolites are becoming faster due to the progress in the field of orthogonal analytical techniques. This review detailed the advancement in the progress of sample preparation, and data processing techniques including data mining tools, database, and their quality control (QC). Advances in data processing tools make it easier to acquire unbiased data that includes a diverse set of metabolites. In addition, novel breakthroughs including, miniaturization as well as their integration with other devices, metabolite array technology, and crystalline sponge-based method have led to faster, more efficient, cost-effective, and holistic metabolomic analysis. The use of cutting-edge techniques to identify the human metabolite, including biomarkers has proven to be advantageous in terms of early disease identification, tracking the progression of illness, and possibility of personalized treatments. This review addressed the constraints of current metabolomics research, which are impeding the facilitation of translation of research from bench to bedside. Nevertheless, the possible way out from such constraints and future direction of translational metabolomics has been conferred.
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Affiliation(s)
- Megha Sajakumar Pillai
- Department of Pharmaceutical Analysis, National Institute of Pharmaceutical Education and Research (NIPER), Ahmedabad, India
| | - Sree Teja Paritala
- Department of Pharmaceutical Analysis, National Institute of Pharmaceutical Education and Research (NIPER), Ahmedabad, India
| | - Ravi P Shah
- Department of Pharmaceutical Analysis, National Institute of Pharmaceutical Education and Research (NIPER), Ahmedabad, India
| | - Nitish Sharma
- Department of Pharmaceutical Analysis, National Institute of Pharmaceutical Education and Research (NIPER), Ahmedabad, India
| | - Pinaki Sengupta
- Department of Pharmaceutical Analysis, National Institute of Pharmaceutical Education and Research (NIPER), Ahmedabad, India
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29
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Tajik M, Baharfar M, Donald WA. Single-cell mass spectrometry. Trends Biotechnol 2022; 40:1374-1392. [PMID: 35562238 DOI: 10.1016/j.tibtech.2022.04.004] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 04/04/2022] [Accepted: 04/09/2022] [Indexed: 01/21/2023]
Abstract
Owing to recent advances in mass spectrometry (MS), tens to hundreds of proteins, lipids, and small molecules can be measured in single cells. The ability to characterize the molecular heterogeneity of individual cells is necessary to define the full assortment of cell subtypes and identify their function. We review single-cell MS including high-throughput, targeted, mass cytometry-based approaches and antibody-free methods for broad profiling of the proteome and metabolome of single cells. The advantages and disadvantages of different methods are discussed, as well as the challenges and opportunities for further improvements in single-cell MS. These methods is being used in biomedicine in several applications including revealing tumor heterogeneity and high-content drug screening.
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Affiliation(s)
- Mohammad Tajik
- School of Chemistry, University of New South Wales, Sydney, New South Wales, 2052, Australia
| | - Mahroo Baharfar
- School of Chemical Engineering, University of New South Wales, Sydney, New South Wales, 2052, Australia
| | - William A Donald
- School of Chemistry, University of New South Wales, Sydney, New South Wales, 2052, Australia.
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30
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Liu Z, Li H, Dang Q, Weng S, Duo M, Lv J, Han X. Integrative insights and clinical applications of single-cell sequencing in cancer immunotherapy. Cell Mol Life Sci 2022; 79:577. [DOI: 10.1007/s00018-022-04608-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Revised: 10/12/2022] [Accepted: 10/20/2022] [Indexed: 11/03/2022]
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31
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Körber A, Keelor JD, Claes BSR, Heeren RMA, Anthony IGM. Fast Mass Microscopy: Mass Spectrometry Imaging of a Gigapixel Image in 34 Minutes. Anal Chem 2022; 94:14652-14658. [PMID: 36223179 PMCID: PMC9607864 DOI: 10.1021/acs.analchem.2c02870] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 09/22/2022] [Indexed: 11/29/2022]
Abstract
Mass spectrometry imaging (MSI) maps the spatial distributions of chemicals on surfaces. MSI requires improvements in throughput and spatial resolution, and often one is compromised for the other. In microprobe-mode MSI, improvements in spatial resolution increase the imaging time quadratically, thus limiting the use of high spatial resolution MSI for large areas or sample cohorts and time-sensitive measurements. Here, we bypass this quadratic relationship by combining a Timepix3 detector with a continuously sampling secondary ion mass spectrometry mass microscope. By reconstructing the data into large-field mass images, this new method, fast mass microscopy, enables orders of magnitude higher throughput than conventional MSI albeit yet at lower mass resolution. We acquired submicron, gigapixel images of fingerprints and rat tissue at acquisition speeds of 600,000 and 15,500 pixels s-1, respectively. For the first image, a comparable microprobe-mode measurement would take more than 2 months, whereas our approach took 33.3 min.
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Affiliation(s)
- Aljoscha Körber
- The
Maastricht MultiModal Molecular Imaging Institute (M4i), Division
of Imaging Mass Spectrometry, Maastricht
University, Universiteitssingel 50, Maastricht 6229 ER, The Netherlands
| | - Joel D. Keelor
- Amsterdam
Scientific Instruments B.V. (ASI), Science Park 106, Amsterdam 1098 XG, The Netherlands
| | - Britt S. R. Claes
- The
Maastricht MultiModal Molecular Imaging Institute (M4i), Division
of Imaging Mass Spectrometry, Maastricht
University, Universiteitssingel 50, Maastricht 6229 ER, The Netherlands
| | - Ron M. A. Heeren
- The
Maastricht MultiModal Molecular Imaging Institute (M4i), Division
of Imaging Mass Spectrometry, Maastricht
University, Universiteitssingel 50, Maastricht 6229 ER, The Netherlands
| | - Ian G. M. Anthony
- The
Maastricht MultiModal Molecular Imaging Institute (M4i), Division
of Imaging Mass Spectrometry, Maastricht
University, Universiteitssingel 50, Maastricht 6229 ER, The Netherlands
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32
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Metabolomics and modelling approaches for systems metabolic engineering. Metab Eng Commun 2022; 15:e00209. [PMID: 36281261 PMCID: PMC9587336 DOI: 10.1016/j.mec.2022.e00209] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 10/13/2022] [Accepted: 10/14/2022] [Indexed: 11/21/2022] Open
Abstract
Metabolic engineering involves the manipulation of microbes to produce desirable compounds through genetic engineering or synthetic biology approaches. Metabolomics involves the quantitation of intracellular and extracellular metabolites, where mass spectrometry and nuclear magnetic resonance based analytical instrumentation are often used. Here, the experimental designs, sample preparations, metabolite quenching and extraction are essential to the quantitative metabolomics workflow. The resultant metabolomics data can then be used with computational modelling approaches, such as kinetic and constraint-based modelling, to better understand underlying mechanisms and bottlenecks in the synthesis of desired compounds, thereby accelerating research through systems metabolic engineering. Constraint-based models, such as genome scale models, have been used successfully to enhance the yield of desired compounds from engineered microbes, however, unlike kinetic or dynamic models, constraint-based models do not incorporate regulatory effects. Nevertheless, the lack of time-series metabolomic data generation has hindered the usefulness of dynamic models till today. In this review, we show that improvements in automation, dynamic real-time analysis and high throughput workflows can drive the generation of more quality data for dynamic models through time-series metabolomics data generation. Spatial metabolomics also has the potential to be used as a complementary approach to conventional metabolomics, as it provides information on the localization of metabolites. However, more effort must be undertaken to identify metabolites from spatial metabolomics data derived through imaging mass spectrometry, where machine learning approaches could prove useful. On the other hand, single-cell metabolomics has also seen rapid growth, where understanding cell-cell heterogeneity can provide more insights into efficient metabolic engineering of microbes. Moving forward, with potential improvements in automation, dynamic real-time analysis, high throughput workflows, and spatial metabolomics, more data can be produced and studied using machine learning algorithms, in conjunction with dynamic models, to generate qualitative and quantitative predictions to advance metabolic engineering efforts.
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33
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Bowman AP, Sawicki J, Talaty NN, Buck WR, Yang J, Wagner DS. Evaluation of Quantitative Platforms for Single Target Mass Spectrometry Imaging. Pharmaceuticals (Basel) 2022; 15:ph15101180. [PMID: 36297291 PMCID: PMC9609477 DOI: 10.3390/ph15101180] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 09/19/2022] [Accepted: 09/21/2022] [Indexed: 12/05/2022] Open
Abstract
(1) Imaging of pharmaceutical compounds in tissue is an increasingly important subsection of Mass Spectrometry Imaging (MSI). Identifying proper target engagement requires MS platforms with high sensitivity and spatial resolution. Three prominent categories of drugs are small molecule drugs, antibody-drug conjugate payloads, and protein degraders. (2) We tested six common MSI platforms for their limit of detection (LoD) on a representative compound for each category: a Matrix-Assisted Laser Desorption/Ionization (MALDI) Fourier Transform Ion Cyclotron, a MALDI-2 Time-of-Flight (ToF), a MALDI-2 Trapped Ion Mobility Spectrometry ToF, a Desorption Electrospray Ionization Orbitrap, and 2 Atmospheric Pressure-MALDI Triple Quadrupoles. Samples were homogenized tissue mimetic models of rat liver spiked with known concentrations of analytes. (3) We found that the AP-MALDI-QQQ platform outperformed all 4 competing platforms by a minimum of 2- to 52-fold increase in LoD for representative compounds from each category of pharmaceutical. (4) AP-MALDI-QQQ platforms are effective, cost-efficient mass spectrometers for the identification of targeted analytes of interest.
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34
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Chen Y, Xie Y, Li L, Wang Z, Yang L. Advances in mass spectrometry imaging for toxicological analysis and safety evaluation of pharmaceuticals. MASS SPECTROMETRY REVIEWS 2022:e21807. [PMID: 36146929 DOI: 10.1002/mas.21807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 07/27/2022] [Accepted: 08/08/2022] [Indexed: 06/16/2023]
Abstract
Safety issues caused by pharmaceuticals have frequently occurred worldwide, posing a tremendous threat to human health. As an essential part of drug development, the toxicological analysis and safety evaluation is of great significance. In addition, the risk of pharmaceuticals accumulation in the environment and the monitoring of the toxicity from natural medicines have also received ongoing concerns. Due to a lack of spatial distribution information provided by common analytical methods, analyses that provide spatial dimensions could serve as complementary safety evaluation methods for better prediction and evaluation of drug toxicity. With advances in technical solutions and software algorithms, mass spectrometry imaging (MSI) has received increasing attention as a popular analytical tool that enables the simultaneous implementation of qualitative, quantitative, and localization without complex sample pretreatment and labeling steps. In recent years, MSI has become more attractive, powerful, and sensitive and has been applied in several scientific fields that can meet the safety assessment requirements. This review aims to cover a detailed summary of the various MSI technologies utilized in the biomedical and pharmaceutical area, including technical principles, advantages, current status, and future trends. Representative applications and developments in the safety-related issues of different pharmaceuticals and natural medicines are also described to provide a reference for pharmaceutical research, improve rational clinical medicine use, and ensure public safety.
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Affiliation(s)
- Yilin Chen
- The MOE Key Laboratory of Standardization of Chinese Medicines, the SATCM Key Laboratory of New Resources and Quality Evaluation of Chinese Medicines, Shanghai Key Laboratory of Compound Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Shanghai Frontiers Science Center of TCM Chemical Biology, Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Yanqiao Xie
- The MOE Key Laboratory of Standardization of Chinese Medicines, the SATCM Key Laboratory of New Resources and Quality Evaluation of Chinese Medicines, Shanghai Key Laboratory of Compound Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Linnan Li
- The MOE Key Laboratory of Standardization of Chinese Medicines, the SATCM Key Laboratory of New Resources and Quality Evaluation of Chinese Medicines, Shanghai Key Laboratory of Compound Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Zhengtao Wang
- The MOE Key Laboratory of Standardization of Chinese Medicines, the SATCM Key Laboratory of New Resources and Quality Evaluation of Chinese Medicines, Shanghai Key Laboratory of Compound Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Li Yang
- The MOE Key Laboratory of Standardization of Chinese Medicines, the SATCM Key Laboratory of New Resources and Quality Evaluation of Chinese Medicines, Shanghai Key Laboratory of Compound Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Shanghai Frontiers Science Center of TCM Chemical Biology, Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai, China
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35
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Stopka SA, van der Reest J, Abdelmoula WM, Ruiz DF, Joshi S, Ringel AE, Haigis MC, Agar NYR. Spatially resolved characterization of tissue metabolic compartments in fasted and high-fat diet livers. PLoS One 2022; 17:e0261803. [PMID: 36067168 PMCID: PMC9447892 DOI: 10.1371/journal.pone.0261803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 08/12/2022] [Indexed: 11/18/2022] Open
Abstract
Cells adapt their metabolism to physiological stimuli, and metabolic heterogeneity exists between cell types, within tissues, and subcellular compartments. The liver plays an essential role in maintaining whole-body metabolic homeostasis and is structurally defined by metabolic zones. These zones are well-understood on the transcriptomic level, but have not been comprehensively characterized on the metabolomic level. Mass spectrometry imaging (MSI) can be used to map hundreds of metabolites directly from a tissue section, offering an important advance to investigate metabolic heterogeneity in tissues compared to extraction-based metabolomics methods that analyze tissue metabolite profiles in bulk. We established a workflow for the preparation of tissue specimens for matrix-assisted laser desorption/ionization (MALDI) MSI that can be implemented to achieve broad coverage of central carbon, nucleotide, and lipid metabolism pathways. Herein, we used this approach to visualize the effect of nutrient stress and excess on liver metabolism. Our data revealed a highly organized metabolic tissue compartmentalization in livers, which becomes disrupted under high fat diet. Fasting caused changes in the abundance of several metabolites, including increased levels of fatty acids and TCA intermediates while fatty livers had higher levels of purine and pentose phosphate-related metabolites, which generate reducing equivalents to counteract oxidative stress. This spatially conserved approach allowed the visualization of liver metabolic compartmentalization at 30 μm pixel resolution and can be applied more broadly to yield new insights into metabolic heterogeneity in vivo.
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Affiliation(s)
- Sylwia A. Stopka
- Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United Statees of America
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United Statees of America
| | - Jiska van der Reest
- Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United Statees of America
- Department of Cell Biology, Blavatnik Institute, Ludwig Center, Harvard Medical School, Boston, MA, United Statees of America
| | - Walid M. Abdelmoula
- Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United Statees of America
| | - Daniela F. Ruiz
- Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United Statees of America
- Bouvé College of Health Sciences, Northeastern University, Boston, MA, United Statees of America
| | - Shakchhi Joshi
- Department of Cell Biology, Blavatnik Institute, Ludwig Center, Harvard Medical School, Boston, MA, United Statees of America
| | - Alison E. Ringel
- Department of Cell Biology, Blavatnik Institute, Ludwig Center, Harvard Medical School, Boston, MA, United Statees of America
| | - Marcia C. Haigis
- Department of Cell Biology, Blavatnik Institute, Ludwig Center, Harvard Medical School, Boston, MA, United Statees of America
- * E-mail: (MCH); (NYRA)
| | - Nathalie Y. R. Agar
- Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United Statees of America
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United Statees of America
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, United Statees of America
- * E-mail: (MCH); (NYRA)
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36
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Nilsson R. Zooming in on kidney metabolism. Nat Metab 2022; 4:1089-1090. [PMID: 36008551 DOI: 10.1038/s42255-022-00621-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Roland Nilsson
- Cardiovascular Medicine Unit, Department of Medicine, Karolinska Institutet, Stockholm, Sweden.
- Division of Cardiovascular Medicine, Karolinska University Hospital, Stockholm, Sweden.
- Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.
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37
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Nwabufo CK, Aigbogun OP. The Role of Mass Spectrometry Imaging in Pharmacokinetic Studies. Xenobiotica 2022; 52:811-827. [PMID: 36048000 DOI: 10.1080/00498254.2022.2119900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
Abstract
Although liquid chromatography-tandem mass spectrometry is the gold standard analytical platform for the quantification of drugs, metabolites, and biomarkers in biological samples, it cannot localize them in target tissues.The localization and quantification of drugs and/or their associated metabolites in target tissues is a more direct measure of bioavailability, biodistribution, efficacy, and regional toxicity compared to the traditional substitute studies using plasma.Therefore, combining high spatial resolution imaging functionality with the superior selectivity and sensitivity of mass spectrometry into one analytical technique will be a valuable tool for targeted localization and quantification of drugs, metabolites, and biomarkers.Mass spectrometry imaging (MSI) is a tagless analytical technique that allows for the direct localization and quantification of drugs, metabolites, and biomarkers in biological tissues, and has been used extensively in pharmaceutical research.The overall goal of this current review is to provide a detailed description of the working principle of MSI and its application in pharmacokinetic studies encompassing absorption, distribution, metabolism, excretion, and toxicity processes, followed by a discussion of the strategies for addressing the challenges associated with the functional utility of MSI in pharmacokinetic studies that support drug development.
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Affiliation(s)
- Chukwunonso K Nwabufo
- Department of Pharmaceutical Sciences, Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada
| | - Omozojie P Aigbogun
- Drug Discovery and Development Research Group, College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, Canada.,Department of Chemistry, University of Saskatchewan, Saskatoon, Canada
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38
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Advances in measuring cancer cell metabolism with subcellular resolution. Nat Methods 2022; 19:1048-1063. [PMID: 36008629 DOI: 10.1038/s41592-022-01572-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Accepted: 07/05/2022] [Indexed: 11/08/2022]
Abstract
Characterizing metabolism in cancer is crucial for understanding tumor biology and for developing potential therapies. Although most metabolic investigations analyze averaged metabolite levels from all cell compartments, subcellular metabolomics can provide more detailed insight into the biochemical processes associated with the disease. Methodological limitations have historically prevented the wider application of subcellular metabolomics in cancer research. Recently, however, ways to distinguish and identify metabolic pathways within organelles have been developed, including state-of-the-art methods to monitor metabolism in situ (such as mass spectrometry-based imaging, Raman spectroscopy and fluorescence microscopy), to isolate key organelles via new approaches and to use tailored isotope-tracing strategies. Herein, we examine the advantages and limitations of these developments and look to the future of this field of research.
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Lewis HM, Costa C, Dartois V, Kaya F, Chambers M, de Jesus J, Palitsin V, Webb R, Bailey MJ. Colocation of Lipids, Drugs, and Metal Biomarkers Using Spatially Resolved Lipidomics with Elemental Mapping. Anal Chem 2022; 94:11798-11806. [PMID: 35981335 PMCID: PMC9434551 DOI: 10.1021/acs.analchem.2c01940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
![]()
Elemental imaging is widely used for imaging cells and
tissues
but rarely in combination with organic mass spectrometry, which can
be used to profile lipids and measure drug concentrations. Here, we
demonstrate how elemental imaging and a new method for spatially resolved
lipidomics (DAPNe-LC-MS, based on capillary microsampling and liquid
chromatography mass spectrometry) can be used in combination to probe
the relationship between metals, drugs, and lipids in discrete areas
of tissues. This new method for spatial lipidomics, reported here
for the first time, has been applied to rabbit lung tissues containing
a lesion (caseous granuloma) caused by tuberculosis infection. We
demonstrate how elemental imaging with spatially resolved lipidomics
can be used to probe the association between ion accumulation and
lipid profiles and verify local drug distribution.
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Affiliation(s)
- Holly-May Lewis
- Department of Chemistry, University of Surrey, Guildford, Surrey GU2 7XH, U.K
| | - Catia Costa
- University of Surrey Ion Beam Centre, Guildford, Surrey GU2 7XH, U.K
| | - Véronique Dartois
- Center for Discovery and Innovation, Hackensack Meridian School of Medicine, 123 Metro Boulevard, Nutley, New Jersey 07110, United States
| | - Firat Kaya
- Center for Discovery and Innovation, Hackensack Meridian School of Medicine, 123 Metro Boulevard, Nutley, New Jersey 07110, United States
| | - Mark Chambers
- Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey GU2 7XH, U.K
| | - Janella de Jesus
- Department of Chemistry, University of Surrey, Guildford, Surrey GU2 7XH, U.K
| | - Vladimir Palitsin
- University of Surrey Ion Beam Centre, Guildford, Surrey GU2 7XH, U.K
| | - Roger Webb
- University of Surrey Ion Beam Centre, Guildford, Surrey GU2 7XH, U.K
| | - Melanie J Bailey
- Department of Chemistry, University of Surrey, Guildford, Surrey GU2 7XH, U.K
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40
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Nezhad ZS, Salazar JP, Pryce RS, Munter LM, Chaurand P. Absolute quantification of cholesterol from thin tissue sections by silver-assisted laser desorption ionization mass spectrometry imaging. Anal Bioanal Chem 2022; 414:6947-6954. [PMID: 35953724 DOI: 10.1007/s00216-022-04262-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 07/29/2022] [Accepted: 08/02/2022] [Indexed: 11/25/2022]
Abstract
Cholesterol is essential to all animal life, and its dysregulation is observed in many diseases. For some of these, the precise determination of cholesterol's histological location and absolute abundance at cellular length scales within tissue samples would open the door to a more fundamental understanding of the role of cholesterol in disease onset and progression. We have developed a fast and simple method for absolute quantification of cholesterol within brain samples based on the sensitive detection and mapping of cholesterol by silver-assisted laser desorption ionization mass spectrometry imaging (AgLDI MSI) from thin tissue sections. Reproducible calibration curves were generated by depositing a range of cholesterol-D7 concentrations on brain homogenate tissue sections combined with the homogeneous spray deposition of a non-animal steroid reference standard detectable by AgLDI MSI to minimize experimental variability. Results obtained from serial brain sections gave consistent cholesterol quantitative values in very good agreement with those obtained with other mass spectrometry-based methods.
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Affiliation(s)
- Zari Saadati Nezhad
- Department of Chemistry, Université de Montréal, C.P. 6128, succursale Centre-ville, Montréal, Québec, H3C 3J7, Canada
| | - Juan Pablo Salazar
- Department of Chemistry, Université de Montréal, C.P. 6128, succursale Centre-ville, Montréal, Québec, H3C 3J7, Canada
| | - Rachel S Pryce
- Department of Chemistry, Université de Montréal, C.P. 6128, succursale Centre-ville, Montréal, Québec, H3C 3J7, Canada
| | - Lisa M Munter
- Dept of Pharmacology & Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Pierre Chaurand
- Department of Chemistry, Université de Montréal, C.P. 6128, succursale Centre-ville, Montréal, Québec, H3C 3J7, Canada.
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41
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Mass Spectrometry Imaging Spatial Tissue Analysis toward Personalized Medicine. LIFE (BASEL, SWITZERLAND) 2022; 12:life12071037. [PMID: 35888125 PMCID: PMC9318569 DOI: 10.3390/life12071037] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 07/04/2022] [Accepted: 07/10/2022] [Indexed: 12/19/2022]
Abstract
Novel profiling methodologies are redefining the diagnostic capabilities and therapeutic approaches towards more precise and personalized healthcare. Complementary information can be obtained from different omic approaches in combination with the traditional macro- and microscopic analysis of the tissue, providing a more complete assessment of the disease. Mass spectrometry imaging, as a tissue typing approach, provides information on the molecular level directly measured from the tissue. Lipids, metabolites, glycans, and proteins can be used for better understanding imbalances in the DNA to RNA to protein translation, which leads to aberrant cellular behavior. Several studies have explored the capabilities of this technology to be applied to tumor subtyping, patient prognosis, and tissue profiling for intraoperative tissue evaluation. In the future, intercenter studies may provide the needed confirmation on the reproducibility, robustness, and applicability of the developed classification models for tissue characterization to assist in disease management.
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42
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Mass spectral imaging showing the plant growth-promoting rhizobacteria's effect on the Brachypodium awn. Biointerphases 2022; 17:031006. [PMID: 35738921 DOI: 10.1116/6.0001949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
The plant growth-promoting rhizobacteria (PGPR) on the host plant surface play a key role in biological control and pathogenic response in plant functions and growth. However, it is difficult to elucidate the PGPR effect on plants. Such information is important in biomass production and conversion. Brachypodium distachyon (Brachypodium), a genomics model for bioenergy and native grasses, was selected as a C3 plant model; and the Gram-negative Pseudomonas fluorescens SBW25 (P.) and Gram-positive Arthrobacter chlorophenolicus A6 (A.) were chosen as representative PGPR strains. The PGPRs were introduced to the Brachypodium seed's awn prior to germination, and their possible effects on the seeding and growth were studied using different modes of time-of-flight secondary ion mass spectrometry (ToF-SIMS) measurements, including a high mass-resolution spectral collection and delayed image extraction. We observed key plant metabolic products and biomarkers, such as flavonoids, phenolic compounds, fatty acids, and auxin indole-3-acetic acid in the Brachypodium awns. Furthermore, principal component analysis and two-dimensional imaging analysis reveal that the Brachypodium awns are sensitive to the PGPR, leading to chemical composition and morphology changes on the awn surface. Our results show that ToF-SIMS can be an effective tool to probe cell-to-cell interactions at the biointerface. This work provides a new approach to studying the PGPR effects on awn and shows its potential for the research of plant growth in the future.
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43
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Suvannapruk W, Edney MK, Kim DH, Scurr DJ, Ghaemmaghami AM, Alexander MR. Single-Cell Metabolic Profiling of Macrophages Using 3D OrbiSIMS: Correlations with Phenotype. Anal Chem 2022; 94:9389-9398. [PMID: 35713879 PMCID: PMC9260720 DOI: 10.1021/acs.analchem.2c01375] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
![]()
Macrophages are important
immune cells that respond to environmental
cues acquiring a range of activation statuses represented by pro-inflammatory
(M1) and anti-inflammatory (M2) phenotypes at each end of their spectrum.
Characterizing the metabolic signature (metabolic profiling) of different
macrophage subsets is a powerful tool to understand the response of
the human immune system to different stimuli. Here, the recently developed
3D OrbiSIMS instrument is applied to yield useful insight into the
metabolome from individual cells after in vitro differentiation of
macrophages into naïve, M1, and M2 phenotypes using different
cytokines. This analysis strategy not only requires more than 6 orders
of magnitude less sample than traditional mass spectrometry approaches
but also allows the study of cell-to-cell variance. Characteristic
metabolites in macrophage subsets are identified using a targeted
lipid and data-driven multivariate approach highlighting amino acids
and other small molecules. The diamino acids alanylasparagine and
lipid sphingomyelin SM(d18/16:0) are uniquely found in M1 macrophages,
while pyridine and pyrimidine are observed at increased intensity
in M2 macrophages, findings which link to known biological pathways.
The first demonstration of this capability illustrates the great potential
of direct cell analysis for in situ metabolite profiling with the
3D OrbiSIMS to probe functional phenotype at the single-cell level
using molecular signatures and to understand the response of the human
body to implanted devices and immune diseases.
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Affiliation(s)
- Waraporn Suvannapruk
- Advanced Materials and Healthcare Technologies Division, School of Pharmacy, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom
| | - Max K Edney
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom
| | - Dong-Hyun Kim
- Advanced Materials and Healthcare Technologies Division, School of Pharmacy, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom
| | - David J Scurr
- Advanced Materials and Healthcare Technologies Division, School of Pharmacy, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom
| | - Amir M Ghaemmaghami
- Immunology & Immuno-bioengineering Group, School of Life Sciences, Faculty of Medicine and Health Sciences, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom
| | - Morgan R Alexander
- Advanced Materials and Healthcare Technologies Division, School of Pharmacy, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom
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44
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Bailey MJ, de Puit M, Romolo FS. Surface Analysis Techniques in Forensic Science: Successes, Challenges, and Opportunities for Operational Deployment. ANNUAL REVIEW OF ANALYTICAL CHEMISTRY (PALO ALTO, CALIF.) 2022; 15:173-196. [PMID: 35167323 DOI: 10.1146/annurev-anchem-061020-124221] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Surface analysis techniques have rapidly evolved in the last decade. Some of these are already routinely used in forensics, such as for the detection of gunshot residue or for glass analysis. Some surface analysis approaches are attractive for their portability to the crime scene. Others can be very helpful in forensic laboratories owing to their high spatial resolution, analyte coverage, speed, and specificity. Despite this, many proposed applications of the techniques have not yet led to operational deployment. Here, we explore the application of these techniques to the most important traces commonly found in forensic casework. We highlight where there is potential to add value and outline the progress that is needed to achieve operational deployment. We consider within the scope of this review surface mass spectrometry, surface spectroscopy, and surface X-ray spectrometry. We show how these tools show great promise for the analysis of fingerprints, hair, drugs, explosives, and microtraces.
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Affiliation(s)
- Melanie J Bailey
- Department of Chemistry, Stag Hill Campus, University of Surrey, Guildford, United Kingdom;
| | - Marcel de Puit
- Netherlands Forensic Institute, The Hague, The Netherlands
- Delft University of Technology, Delft, The Netherlands
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45
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Morgan EW, Perdew GH, Patterson AD. Multi-Omics Strategies for Investigating the Microbiome in Toxicology Research. Toxicol Sci 2022; 187:189-213. [PMID: 35285497 PMCID: PMC9154275 DOI: 10.1093/toxsci/kfac029] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Microbial communities on and within the host contact environmental pollutants, toxic compounds, and other xenobiotic compounds. These communities of bacteria, fungi, viruses, and archaea possess diverse metabolic potential to catabolize compounds and produce new metabolites. Microbes alter chemical disposition thus making the microbiome a natural subject of interest for toxicology. Sequencing and metabolomics technologies permit the study of microbiomes altered by acute or long-term exposure to xenobiotics. These investigations have already contributed to and are helping to re-interpret traditional understandings of toxicology. The purpose of this review is to provide a survey of the current methods used to characterize microbes within the context of toxicology. This will include discussion of commonly used techniques for conducting omic-based experiments, their respective strengths and deficiencies, and how forward-looking techniques may address present shortcomings. Finally, a perspective will be provided regarding common assumptions that currently impede microbiome studies from producing causal explanations of toxicologic mechanisms.
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Affiliation(s)
- Ethan W Morgan
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Gary H Perdew
- Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Andrew D Patterson
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania 16802, USA.,Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
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46
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A Reliable Approach for Revealing Molecular Targets in Secondary Ion Mass Spectrometry. Int J Mol Sci 2022; 23:ijms23094615. [PMID: 35563005 PMCID: PMC9103194 DOI: 10.3390/ijms23094615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 04/07/2022] [Accepted: 04/11/2022] [Indexed: 12/10/2022] Open
Abstract
Nano secondary ion mass spectrometry (nanoSIMS) imaging is a rapidly growing field in biological sciences, which enables investigators to describe the chemical composition of cells and tissues with high resolution. One of the major challenges of nanoSIMS is to identify specific molecules or organelles, as these are not immediately recognizable in nanoSIMS and need to be revealed by SIMS-compatible probes. Few laboratories have generated such probes, and none are commercially available. To address this, we performed a systematic study of probes initially developed for electron microscopy. Relying on nanoscale SIMS, we found that antibodies coupled to 6 nm gold particles are surprisingly efficient in terms of labeling specificity while offering a reliable detection threshold. These tools enabled accurate visualization and sample analysis and were easily employed in correlating SIMS with other imaging approaches, such as fluorescence microscopy. We conclude that antibodies conjugated to moderately sized gold particles are promising tools for SIMS imaging.
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47
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Islimye E, Girard V, Gould AP. Functions of Stress-Induced Lipid Droplets in the Nervous System. Front Cell Dev Biol 2022; 10:863907. [PMID: 35493070 PMCID: PMC9047859 DOI: 10.3389/fcell.2022.863907] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 03/22/2022] [Indexed: 12/12/2022] Open
Abstract
Lipid droplets are highly dynamic intracellular organelles that store neutral lipids such as cholesteryl esters and triacylglycerols. They have recently emerged as key stress response components in many different cell types. Lipid droplets in the nervous system are mostly observed in vivo in glia, ependymal cells and microglia. They tend to become more numerous in these cell types and can also form in neurons as a consequence of ageing or stresses involving redox imbalance and lipotoxicity. Abundant lipid droplets are also a characteristic feature of several neurodegenerative diseases. In this minireview, we take a cell-type perspective on recent advances in our understanding of lipid droplet metabolism in glia, neurons and neural stem cells during health and disease. We highlight that a given lipid droplet subfunction, such as triacylglycerol lipolysis, can be physiologically beneficial or harmful to the functions of the nervous system depending upon cellular context. The mechanistic understanding of context-dependent lipid droplet functions in the nervous system is progressing apace, aided by new technologies for probing the lipid droplet proteome and lipidome with single-cell type precision.
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48
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Zhong AB, Muti IH, Eyles SJ, Vachet RW, Sikora KN, Bobst CE, Calligaris D, Stopka SA, Agar JN, Wu CL, Mino-Kenudson MA, Agar NYR, Christiani DC, Kaltashov IA, Cheng LL. Multiplatform Metabolomics Studies of Human Cancers With NMR and Mass Spectrometry Imaging. Front Mol Biosci 2022; 9:785232. [PMID: 35463966 PMCID: PMC9024335 DOI: 10.3389/fmolb.2022.785232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 03/02/2022] [Indexed: 11/22/2022] Open
Abstract
The status of metabolomics as a scientific branch has evolved from proof-of-concept to applications in science, particularly in medical research. To comprehensively evaluate disease metabolomics, multiplatform approaches of NMR combining with mass spectrometry (MS) have been investigated and reported. This mixed-methods approach allows for the exploitation of each individual technique's unique advantages to maximize results. In this article, we present our findings from combined NMR and MS imaging (MSI) analysis of human lung and prostate cancers. We further provide critical discussions of the current status of NMR and MS combined human prostate and lung cancer metabolomics studies to emphasize the enhanced metabolomics ability of the multiplatform approach.
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Affiliation(s)
- Anya B. Zhong
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Isabella H. Muti
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Stephen J. Eyles
- Department of Biochemistry and Molecular Biology, University of Massachusetts-Amherst, Amherst, MA, United States
| | - Richard W. Vachet
- Department of Biochemistry and Molecular Biology, University of Massachusetts-Amherst, Amherst, MA, United States
| | - Kristen N. Sikora
- Department of Biochemistry and Molecular Biology, University of Massachusetts-Amherst, Amherst, MA, United States
| | - Cedric E. Bobst
- Department of Biochemistry and Molecular Biology, University of Massachusetts-Amherst, Amherst, MA, United States
| | - David Calligaris
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Sylwia A. Stopka
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Jeffery N. Agar
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA, United States
| | - Chin-Lee Wu
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | | | - Nathalie Y. R. Agar
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- Dana-Farber Cancer Institute, Boston, MA, United States
| | - David C. Christiani
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
- Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Igor A. Kaltashov
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Leo L. Cheng
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
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Metabolism in atherosclerotic plaques: immunoregulatory mechanisms in the arterial wall. Clin Sci (Lond) 2022; 136:435-454. [PMID: 35348183 PMCID: PMC8965849 DOI: 10.1042/cs20201293] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 03/02/2022] [Accepted: 03/16/2022] [Indexed: 02/05/2023]
Abstract
Over the last decade, there has been a growing interest to understand the link between metabolism and the immune response in the context of metabolic diseases but also beyond, giving then birth to a new field of research. Termed 'immunometabolism', this interdisciplinary field explores paradigms of both immunology and metabolism to provided unique insights into different disease pathogenic processes, and the identification of new potential therapeutic targets. Similar to other inflammatory conditions, the atherosclerotic inflammatory process in the artery has been associated with a local dysregulated metabolic response. Thus, recent studies show that metabolites are more than just fuels in their metabolic pathways, and they can act as modulators of vascular inflammation and atherosclerosis. In this review article, we describe the most common immunometabolic pathways characterised in innate and adaptive immune cells, and discuss how macrophages' and T cells' metabolism may influence phenotypic changes in the plaque. Moreover, we discuss the potential of targeting immunometabolism to prevent and treat cardiovascular diseases (CVDs).
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50
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Chen W, Liu S, Yang Y, Zhang Z, Zhao Y. Spatiotemporal Monitoring of NAD+ Metabolism with Fluorescent Biosensors. Mech Ageing Dev 2022; 204:111657. [DOI: 10.1016/j.mad.2022.111657] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 03/09/2022] [Accepted: 03/09/2022] [Indexed: 01/07/2023]
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