1
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Cheng H, Miller D, Southwell N, Porcari P, Fischer JL, Taylor I, Salbaum JM, Kappen C, Hu F, Yang C, Keshari KR, Gross SS, D'Aurelio M, Chen Q. Untargeted pixel-by-pixel metabolite ratio imaging as a novel tool for biomedical discovery in mass spectrometry imaging. eLife 2025; 13:RP96892. [PMID: 40100251 PMCID: PMC11919253 DOI: 10.7554/elife.96892] [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] [Indexed: 03/20/2025] Open
Abstract
Mass spectrometry imaging (MSI) is a powerful technology used to define the spatial distribution and relative abundance of metabolites across tissue cryosections. While software packages exist for pixel-by-pixel individual metabolite and limited target pairs of ratio imaging, the research community lacks an easy computing and application tool that images any metabolite abundance ratio pairs. Importantly, recognition of correlated metabolite pairs may contribute to the discovery of unanticipated molecules in shared metabolic pathways. Here, we describe the development and implementation of an untargeted R package workflow for pixel-by-pixel ratio imaging of all metabolites detected in an MSI experiment. Considering untargeted MSI studies of murine brain and embryogenesis, we demonstrate that ratio imaging minimizes systematic data variation introduced by sample handling, markedly enhances spatial image contrast, and reveals previously unrecognized metabotype-distinct tissue regions. Furthermore, ratio imaging facilitates identification of novel regional biomarkers and provides anatomical information regarding spatial distribution of metabolite-linked biochemical pathways. The algorithm described herein is applicable to any MSI dataset containing spatial information for metabolites, peptides or proteins, offering a potent hypothesis generation tool to enhance knowledge obtained from current spatial metabolite profiling technologies.
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Affiliation(s)
- Huiyong Cheng
- Department of Pharmacology, Weill Cornell Medicine, New York, United States
| | - Dawson Miller
- Department of Pharmacology, Weill Cornell Medicine, New York, United States
| | - Nneka Southwell
- Brain and Mind Research Institute, Weill Cornell Medicine, New York City, United States
| | - Paola Porcari
- Memorial Sloan Kettering Cancer Center, New York, United States
| | | | - Isobel Taylor
- Department of Pharmacology, Weill Cornell Medicine, New York, United States
| | - J Michael Salbaum
- Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, United States
| | - Claudia Kappen
- Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, United States
| | - Fenghua Hu
- Cornell University, Department of Molecular Biology & Genetics, Ithaca, United States
| | - Cha Yang
- Cornell University, Department of Molecular Biology & Genetics, Ithaca, United States
| | | | - Steven S Gross
- Department of Pharmacology, Weill Cornell Medicine, New York, United States
| | - Marilena D'Aurelio
- Brain and Mind Research Institute, Weill Cornell Medicine, New York City, United States
| | - Qiuying Chen
- Department of Pharmacology, Weill Cornell Medicine, New York, United States
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2
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Shang W, Wei G, Li H, Zhao G, Wang D. Advances in High-Resolution Mass Spectrometry-Based Metabolomics: Applications in Food Analysis and Biomarker Discovery. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2025; 73:3305-3325. [PMID: 39874461 DOI: 10.1021/acs.jafc.4c10295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/30/2025]
Abstract
Consumer concerns regarding food nutrition and quality are becoming increasingly prevalent. High-resolution mass spectrometry (HRMS)-based metabolomics stands as a cutting-edge and widely embraced technique in the realm of food component analysis and detection. It boasts the capability to identify character metabolites at exceedingly low abundances, which remain undetectable by conventional platforms. It can also enable real-time monitoring of the flux of targeted compounds in metabolic synthesis and decomposition. With the emergence of artificial intelligence and machine learning, it has become more convenient to process the vast data sets of metabolomics and identify biomarkers. The review summarizes the latest applications of HRMS-based metabolomics platforms in traditional foods, novel foods, and pharmaceutical-food homologous matrices. It compares the suitability of HRMS to nuclear magnetic resonance (NMR) in metabolomics across three dimensions and discusses the principles and application scenarios of various mass spectrometry technologies.
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Affiliation(s)
- Wenqi Shang
- Yibin Academy of Southwest University, Yibin 644000, China
- College of Food Science, Southwest University, Chongqing 400715, China
| | - Guozheng Wei
- College of Food Science, Southwest University, Chongqing 400715, China
| | - Haibo Li
- Guizhou Fanjingshan Forest Ecosystem National Observation and Research Station,Guizhou 554400, China
| | - Guohua Zhao
- College of Food Science, Southwest University, Chongqing 400715, China
| | - Damao Wang
- Yibin Academy of Southwest University, Yibin 644000, China
- College of Food Science, Southwest University, Chongqing 400715, China
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3
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Cheng H, Miller D, Southwell N, Porcari P, Fischer JL, Taylor I, Michael Salbaum J, Kappen C, Hu F, Yang C, Keshari KR, Gross SS, D'Aurelio M, Chen Q. Untargeted Pixel-by-Pixel Imaging of Metabolite Ratio Pairs as a Novel Tool for Biomedical Discovery in Mass Spectrometry Imaging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.10.575105. [PMID: 38370710 PMCID: PMC10871215 DOI: 10.1101/2024.01.10.575105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Mass spectrometry imaging (MSI) is a powerful technology used to define the spatial distribution and relative abundance of metabolites across tissue cryosections. While software packages exist for pixel-by-pixel individual metabolite and limited target pairs of ratio imaging, the research community lacks an easy computing and application tool that images any metabolite abundance ratio pairs. Importantly, recognition of correlated metabolite pairs may contribute to the discovery of unanticipated molecules in shared metabolic pathways. Here, we describe the development and implementation of an untargeted R package workflow for pixel-by-pixel ratio imaging of all metabolites detected in an MSI experiment. Considering untargeted MSI studies of murine brain and embryogenesis, we demonstrate that ratio imaging minimizes systematic data variation introduced by sample handling, markedly enhances spatial image contrast, and reveals previously unrecognized metabotype-distinct tissue regions. Furthermore, ratio imaging facilitates identification of novel regional biomarkers and provides anatomical information regarding spatial distribution of metabolite-linked biochemical pathways. The algorithm described herein is applicable to any MSI dataset containing spatial information for metabolites, peptides or proteins, offering a potent hypothesis generation tool to enhance knowledge obtained from current spatial metabolite profiling technologies.
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4
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Lai H, Fan P, Wang H, Wang Z, Chen N. New perspective on central nervous system disorders: focus on mass spectrometry imaging. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2024; 16:8080-8102. [PMID: 39508396 DOI: 10.1039/d4ay01205d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2024]
Abstract
An abnormally organized brain spatial network is linked to the development of various central nervous system (CNS) disorders, including neurodegenerative diseases and neuropsychiatric disorders. However, the complicated molecular mechanisms of these diseases remain unresolved, making the development of treatment strategies difficult. A novel molecular imaging technique, called mass spectrometry imaging (MSI), captures molecular information on the surface of samples in situ. With MSI, multiple compounds can be simultaneously visualized in a single experiment. The high spatial resolution enables the simultaneous visualization of the spatial distribution and relative content of various compounds. The wide application of MSI in biomedicine has facilitated extensive studies on CNS disorders in recent years. This review provides a concise overview of the processes, applications, advantages, and disadvantages, as well as mechanisms of the main types of MSI. Meanwhile, this review summarizes the main applications of MSI in studying CNS diseases, including Alzheimer's disease (AD), CNS tumors, stroke, depression, Huntington's disease (HD), and Parkinson's disease (PD). Finally, this review comprehensively discusses the synergistic application of MSI with other advanced imaging modalities, its utilization in organoid models, its integration with spatial omics techniques, and provides an outlook on its future potential in single-cell analysis.
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Affiliation(s)
- Huaqing Lai
- Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou 510405, Guangdong, China
- State Key Laboratory of Bioactive Substances and Functions of Natural Medicines, Institute of Materia Medica & Neuroscience Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China.
| | - Pinglong Fan
- Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou 510405, Guangdong, China
| | - Huiqin Wang
- Hunan University of Chinese Medicine, Hunan Engineering Technology Center of Standardization and Function of Chinese Herbal Decoction Pieces, Changsha 410208, Hunan, China
| | - Zhenzhen Wang
- State Key Laboratory of Bioactive Substances and Functions of Natural Medicines, Institute of Materia Medica & Neuroscience Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China.
| | - Naihong Chen
- Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou 510405, Guangdong, China
- State Key Laboratory of Bioactive Substances and Functions of Natural Medicines, Institute of Materia Medica & Neuroscience Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China.
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5
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Zhang J, Mao Z, Zhang D, Guo L, Zhao H, Miao M. Mass spectrometry imaging as a promising analytical technique for herbal medicines: an updated review. Front Pharmacol 2024; 15:1442870. [PMID: 39148546 PMCID: PMC11324582 DOI: 10.3389/fphar.2024.1442870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Accepted: 07/18/2024] [Indexed: 08/17/2024] Open
Abstract
Herbal medicines (HMs) have long played a pivotal role in preventing and treating various human diseases and have been studied widely. However, the complexities present in HM metabolites and their unclear mechanisms of action have posed significant challenges in the modernization of traditional Chinese medicine (TCM). Over the past two decades, mass spectrometry imaging (MSI) has garnered increasing attention as a robust analytical technique that enables the simultaneous execution of qualitative, quantitative, and localization analyses without complex sample pretreatment. With advances in technical solutions, MSI has been extensively applied in the field of HMs. MSI, a label-free ion imaging technique can comprehensively map the spatial distribution of HM metabolites in plant native tissues, thereby facilitating the effective quality control of HMs. Furthermore, the spatial dimension information of small molecule endogenous metabolites within animal tissues provided by MSI can also serve as a supplement to uncover pharmacological and toxicological mechanisms of HMs. In the review, we provide an overview of the three most common MSI techniques. In addition, representative applications in HM are highlighted. Finally, we discuss the current challenges and propose several potential solutions. We hope that the summary of recent findings will contribute to the application of MSI in exploring metabolites and mechanisms of action of HMs.
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Affiliation(s)
- Jinying Zhang
- School of Pharmacy, Henan University of Chinese Medicine, Zhengzhou, China
- Henan Collaborative Innovation Center for Research and Development on the Whole Industry Chain of Yu-Yao, Zhengzhou, China
| | - Zhiguo Mao
- School of Pharmacy, Henan University of Chinese Medicine, Zhengzhou, China
- Henan Collaborative Innovation Center for Research and Development on the Whole Industry Chain of Yu-Yao, Zhengzhou, China
| | - Ding Zhang
- School of Pharmacy, Henan University of Chinese Medicine, Zhengzhou, China
- Henan Collaborative Innovation Center for Research and Development on the Whole Industry Chain of Yu-Yao, Zhengzhou, China
| | - Lin Guo
- School of Pharmacy, Henan University of Chinese Medicine, Zhengzhou, China
- Henan Collaborative Innovation Center for Research and Development on the Whole Industry Chain of Yu-Yao, Zhengzhou, China
| | - Hui Zhao
- School of Pharmacy, Henan University of Chinese Medicine, Zhengzhou, China
- Henan Collaborative Innovation Center for Research and Development on the Whole Industry Chain of Yu-Yao, Zhengzhou, China
| | - Mingsan Miao
- School of Pharmacy, Henan University of Chinese Medicine, Zhengzhou, China
- Henan Collaborative Innovation Center for Research and Development on the Whole Industry Chain of Yu-Yao, Zhengzhou, China
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6
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Zhang M, Niu H, Li Q, Jiao L, Li H, Wu W. Active Compounds of Panax ginseng in the Improvement of Alzheimer's Disease and Application of Spatial Metabolomics. Pharmaceuticals (Basel) 2023; 17:38. [PMID: 38256872 PMCID: PMC10818864 DOI: 10.3390/ph17010038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 12/14/2023] [Accepted: 12/24/2023] [Indexed: 01/24/2024] Open
Abstract
Panax ginseng C.A. Meyer (P. ginseng) is one of the more common traditional Chinese medicines (TCMs). It contains numerous chemical components and exhibits a range of pharmacological effects. An enormous burden is placed on people's health and life by Alzheimer's disease (AD), a neurodegenerative condition. Recent research has shown that P. ginseng's chemical constituents, particularly ginsenosides, have a significant beneficial impact on the prevention and management of neurological disorders. To understand the current status of research on P. ginseng to improve AD, this paper discusses the composition of P. ginseng, its mechanism of action, and its clinical application. The pathogenesis of AD includes amyloid beta protein (Aβ) generation and aggregation, tau protein hyperphosphorylation, oxidant stress, neuroinflammation, mitochondrial damage, and neurotransmitter and gut microbiota disorders. This review presents the key molecular mechanisms and signaling pathways of the active ingredients in P. ginseng involved in improving AD from the perspective of AD pathogenesis. A P. ginseng-related signaling pathway network was constructed to provide effective targets for the treatment of AD. In addition, the application of spatial metabolomics techniques in studying P. ginseng and AD is discussed. In summary, this paper discusses research perspectives for the study of P. ginseng in the treatment of AD, including a systematic and in-depth review of the mechanisms of action of the active substances in P. ginseng, and evaluates the feasibility of applying spatial metabolomics in the study of AD pathogenesis and pharmacological treatment.
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Affiliation(s)
| | | | | | | | - Hui Li
- Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun 130117, China; (M.Z.); (H.N.); (Q.L.); (L.J.)
| | - Wei Wu
- Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun 130117, China; (M.Z.); (H.N.); (Q.L.); (L.J.)
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7
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Wang XN, Song Y, Tang W, Li P, Li B. Integration of fluorescence and MALDI imaging for microfluidic chip-based screening of potential thrombin inhibitors from natural products. Biosens Bioelectron 2023; 237:115527. [PMID: 37480787 DOI: 10.1016/j.bios.2023.115527] [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: 05/03/2023] [Revised: 07/02/2023] [Accepted: 07/09/2023] [Indexed: 07/24/2023]
Abstract
The microfluidic technology provides an ideal platform for in situ screening of enzyme inhibitors and activators from natural products. This work described a surface-modified ITO glass-PDMS hybrid microfluidic chip for evaluating thrombin interaction with its potential inhibitors by fluorescence imaging and matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI). The fluorescence-labeled substrate was immobilized on a conductive ITO glass slide coated with gold nanoparticles/thiol-β-cyclodextrin modified TiO2 nanowires (Au-β-CD@TiO2 NWs) via Au-S bonds. A PDMS microchannel plate was placed on top of the modified ITO slide. The premixed solutions of thrombin and candidate thrombin inhibitors were infused into the microchannels to form a microreactor environment. The enzymatic reaction was rapidly monitored by fluorescence microscopy, and MALDI MS was used to validate and quantify the enzymatic hydrolysate of thrombin to determine the enzyme kinetic process and inhibitory activities of selected flavonoids. The fluorescence and MALDI MS results showed that luteolin, cynaroside, and baicalin have good thrombin inhibitory activity and their half-maximal inhibitory concentrations (IC50) were below 30 μM. The integration of fluorescence imaging and MALDI MSI for in situ monitoring and quantifying the enzymatic reaction in a microfluidic chip is capable of rapid and accurate screening of thrombin inhibitors from natural products.
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Affiliation(s)
- Xian-Na Wang
- State Key Laboratory of Natural Medicines and School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
| | - Yahui Song
- State Key Laboratory of Natural Medicines and School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
| | - Weiwei Tang
- State Key Laboratory of Natural Medicines and School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
| | - Ping Li
- State Key Laboratory of Natural Medicines and School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, 210009, China.
| | - Bin Li
- State Key Laboratory of Natural Medicines and School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, 210009, China.
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8
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Maciel LÍL, Bernardo RA, Martins RO, Batista Junior AC, Oliveira JVA, Chaves AR, Vaz BG. Desorption electrospray ionization and matrix-assisted laser desorption/ionization as imaging approaches for biological samples analysis. Anal Bioanal Chem 2023:10.1007/s00216-023-04783-8. [PMID: 37329466 DOI: 10.1007/s00216-023-04783-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 05/19/2023] [Accepted: 05/30/2023] [Indexed: 06/19/2023]
Abstract
The imaging of biological tissues can offer valuable information about the sample composition, which improves the understanding of analyte distribution in such complex samples. Different approaches using mass spectrometry imaging (MSI), also known as imaging mass spectrometry (IMS), enabled the visualization of the distribution of numerous metabolites, drugs, lipids, and glycans in biological samples. The high sensitivity and multiple analyte evaluation/visualization in a single sample provided by MSI methods lead to various advantages and overcome drawbacks of classical microscopy techniques. In this context, the application of MSI methods, such as desorption electrospray ionization-MSI (DESI-MSI) and matrix-assisted laser desorption/ionization-MSI (MALDI-MSI), has significantly contributed to this field. This review discusses the evaluation of exogenous and endogenous molecules in biological samples using DESI and MALDI imaging. It offers rare technical insights not commonly found in the literature (scanning speed and geometric parameters), making it a comprehensive guide for applying these techniques step-by-step. Furthermore, we provide an in-depth discussion of recent research findings on using these methods to study biological tissues.
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Affiliation(s)
| | | | | | | | | | | | - Boniek Gontijo Vaz
- Instituto de Química, Universidade Federal de Goiás, Goiânia, GO, 74690-900, Brazil.
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9
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Guo X, Wang X, Tian C, Dai J, Zhao Z, Duan Y. Development of mass spectrometry imaging techniques and its latest applications. Talanta 2023; 264:124721. [PMID: 37271004 DOI: 10.1016/j.talanta.2023.124721] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Revised: 05/03/2023] [Accepted: 05/22/2023] [Indexed: 06/06/2023]
Abstract
Mass spectrometry imaging (MSI) is a novel molecular imaging technology that collects molecular information from the surface of samples in situ. The spatial distribution and relative content of various compounds can be visualized simultaneously with high spatial resolution. The prominent advantages of MSI promote the active development of ionization technology and its broader applications in diverse fields. This article first gives a brief introduction to the vital parts of the processes during MSI. On this basis, provides a comprehensive overview of the most relevant MS-based imaging techniques from their mechanisms, pros and cons, and applications. In addition, a critical issue in MSI, matrix effects is also discussed. Then, the representative applications of MSI in biological, forensic, and environmental fields in the past 5 years have been summarized, with a focus on various types of analytes (e.g., proteins, lipids, polymers, etc.) Finally, the challenges and further perspectives of MSI are proposed and concluded.
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Affiliation(s)
- Xing Guo
- College of Chemistry and Material Science, Northwest University, Xi'an, 710069, PR China
| | - Xin Wang
- College of Chemistry and Material Science, Northwest University, Xi'an, 710069, PR China
| | - Caiyan Tian
- College of Life Science, Sichuan University, Chengdu, 610064, PR China
| | - Jianxiong Dai
- Aliben Science and Technology Company Limited, Chengdu, 610064, PR China
| | | | - Yixiang Duan
- College of Chemistry and Material Science, Northwest University, Xi'an, 710069, PR China; Research Center of Analytical Instrumentation, Sichuan University, Chengdu, 610064, PR China.
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10
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Spatial segmentation of mass spectrometry imaging data featuring selected principal components. Talanta 2023; 253:123958. [PMID: 36179560 DOI: 10.1016/j.talanta.2022.123958] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Revised: 09/16/2022] [Accepted: 09/19/2022] [Indexed: 12/13/2022]
Abstract
Spatial segmentation aims to find homogeneous/heterogeneous subgroups of spectra or ion images in mass spectrometry imaging (MSI) data. The maps it generated inform researchers of vital characteristics of the data and thus provide the basis for strategizing further biological analysis. Dimensional reduction and clustering are two basic steps of segmentation. Due to the variations in the quality, resolution, density of spectral information, and sizes, not all datasets could be segmented ideally with combinations of different dimensional reduction and clustering algorithms. Here, we proposed a segmentation pipeline that utilized pattern compression by principal component analysis (PCA) and represented by principal components. Instead of preprocessed or raw MSI data, normalized principal components were used for the segmentation process. Multiple datasets of rat brains and mouse kidneys were tested, and the proposed segmentation pipeline presented the obvious advantage of easy-to-use and can be readily intergraded with other existing innovative pipelines.
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11
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Feucherolles M, Frache G. MALDI Mass Spectrometry Imaging: A Potential Game-Changer in a Modern Microbiology. Cells 2022; 11:cells11233900. [PMID: 36497158 PMCID: PMC9738593 DOI: 10.3390/cells11233900] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 11/24/2022] [Accepted: 11/28/2022] [Indexed: 12/11/2022] Open
Abstract
Nowadays, matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) is routinely implemented as the reference method for the swift and straightforward identification of microorganisms. However, this method is not flawless and there is a need to upgrade the current methodology in order to free the routine lab from incubation time and shift from a culture-dependent to an even faster independent culture system. Over the last two decades, mass spectrometry imaging (MSI) gained tremendous popularity in life sciences, including microbiology, due to its ability to simultaneously detect biomolecules, as well as their spatial distribution, in complex samples. Through this literature review, we summarize the latest applications of MALDI-MSI in microbiology. In addition, we discuss the challenges and avenues of exploration for applying MSI to solve current MALDI-TOF MS limits in routine and research laboratories.
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12
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Li H, Li Z. The Exploration of Microbial Natural Products and Metabolic Interaction Guided by Mass Spectrometry Imaging. Bioengineering (Basel) 2022; 9:707. [PMID: 36421108 PMCID: PMC9687252 DOI: 10.3390/bioengineering9110707] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 11/02/2022] [Accepted: 11/12/2022] [Indexed: 10/17/2023] Open
Abstract
As an impressive mass spectrometry technology, mass spectrometric imaging (MSI) can provide mass spectra data and spatial distribution of analytes simultaneously. MSI has been widely used in diverse fields such as clinical diagnosis, the pharmaceutical industry and environmental study due to its accuracy, high resolution and developing reproducibility. Natural products (NPs) have been a critical source of leading drugs; almost half of marketed drugs are derived from NPs or their derivatives. The continuous search for bioactive NPs from microorganisms or microbiomes has always been attractive. MSI allows us to analyze and characterize NPs directly in monocultured microorganisms or a microbial community. In this review, we briefly introduce current mainstream ionization technologies for microbial samples and the key issue of sample preparation, and then summarize some applications of MSI in the exploration of microbial NPs and metabolic interaction, especially NPs from marine microbes. Additionally, remaining challenges and future prospects are discussed.
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Affiliation(s)
| | - Zhiyong Li
- State Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
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13
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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: 1.7] [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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14
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Sun R, Zhang Y, Tang W, Li B. Submicron 3,4-dihydroxybenzoic acid–TiO 2 composite particles for enhanced MALDI MS imaging of secondary metabolites in the root of differently aged baical skullcap. Analyst 2022; 147:3017-3024. [DOI: 10.1039/d2an00710j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
This work provides a high-efficient organic-inorganic hybrid matrix for MALDI MSI of secondary metabolites in plant tissues.
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Affiliation(s)
- Ruiyang Sun
- State Key Laboratory of Natural Medicines and School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
| | - Ying Zhang
- State Key Laboratory of Natural Medicines and School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
| | - Weiwei Tang
- State Key Laboratory of Natural Medicines and School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
| | - Bin Li
- State Key Laboratory of Natural Medicines and School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
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